Improved sample size determination for attributes and variables sampling
International Nuclear Information System (INIS)
Stirpe, D.; Picard, R.R.
1985-01-01
Earlier INMM papers have addressed the attributes/variables problem and, under conservative/limiting approximations, have reported analytical solutions for the attributes and variables sample sizes. Through computer simulation of this problem, we have calculated attributes and variables sample sizes as a function of falsification, measurement uncertainties, and required detection probability without using approximations. Using realistic assumptions for uncertainty parameters of measurement, the simulation results support the conclusions: (1) previously used conservative approximations can be expensive because they lead to larger sample sizes than needed; and (2) the optimal verification strategy, as well as the falsification strategy, are highly dependent on the underlying uncertainty parameters of the measurement instruments. 1 ref., 3 figs
Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.
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
Directory of Open Access Journals (Sweden)
Stefanović Milena
2013-01-01
Full Text Available In studies of population variability, particular attention has to be paid to the selection of a representative sample. The aim of this study was to assess the size of the new representative sample on the basis of the variability of chemical content of the initial sample on the example of a whitebark pine population. Statistical analysis included the content of 19 characteristics (terpene hydrocarbons and their derivates of the initial sample of 10 elements (trees. It was determined that the new sample should contain 20 trees so that the mean value calculated from it represents a basic set with a probability higher than 95 %. Determination of the lower limit of the representative sample size that guarantees a satisfactory reliability of generalization proved to be very important in order to achieve cost efficiency of the research. [Projekat Ministarstva nauke Republike Srbije, br. OI-173011, br. TR-37002 i br. III-43007
Optimum strata boundaries and sample sizes in health surveys using auxiliary variables.
Reddy, Karuna Garan; Khan, Mohammad G M; Khan, Sabiha
2018-01-01
Using convenient stratification criteria such as geographical regions or other natural conditions like age, gender, etc., is not beneficial in order to maximize the precision of the estimates of variables of interest. Thus, one has to look for an efficient stratification design to divide the whole population into homogeneous strata that achieves higher precision in the estimation. In this paper, a procedure for determining Optimum Stratum Boundaries (OSB) and Optimum Sample Sizes (OSS) for each stratum of a variable of interest in health surveys is developed. The determination of OSB and OSS based on the study variable is not feasible in practice since the study variable is not available prior to the survey. Since many variables in health surveys are generally skewed, the proposed technique considers the readily-available auxiliary variables to determine the OSB and OSS. This stratification problem is formulated into a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. It is then solved for the OSB by using a dynamic programming (DP) technique. A numerical example with a real data set of a population, aiming to estimate the Haemoglobin content in women in a national Iron Deficiency Anaemia survey, is presented to illustrate the procedure developed in this paper. Upon comparisons with other methods available in literature, results reveal that the proposed approach yields a substantial gain in efficiency over the other methods. A simulation study also reveals similar results.
Desu, M M
2012-01-01
One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropria
Syed, Mushabbar A; Oshinski, John N; Kitchen, Charles; Ali, Arshad; Charnigo, Richard J; Quyyumi, Arshed A
2009-08-01
Carotid MRI measurements are increasingly being employed in research studies for atherosclerosis imaging. The majority of carotid imaging studies use 1.5 T MRI. Our objective was to investigate intra-observer and inter-observer variability in carotid measurements using high resolution 3 T MRI. We performed 3 T carotid MRI on 10 patients (age 56 +/- 8 years, 7 male) with atherosclerosis risk factors and ultrasound intima-media thickness > or =0.6 mm. A total of 20 transverse images of both right and left carotid arteries were acquired using T2 weighted black-blood sequence. The lumen and outer wall of the common carotid and internal carotid arteries were manually traced; vessel wall area, vessel wall volume, and average wall thickness measurements were then assessed for intra-observer and inter-observer variability. Pearson and intraclass correlations were used in these assessments, along with Bland-Altman plots. For inter-observer variability, Pearson correlations ranged from 0.936 to 0.996 and intraclass correlations from 0.927 to 0.991. For intra-observer variability, Pearson correlations ranged from 0.934 to 0.954 and intraclass correlations from 0.831 to 0.948. Calculations showed that inter-observer variability and other sources of error would inflate sample size requirements for a clinical trial by no more than 7.9%, indicating that 3 T MRI is nearly optimal in this respect. In patients with subclinical atherosclerosis, 3 T carotid MRI measurements are highly reproducible and have important implications for clinical trial design.
Directory of Open Access Journals (Sweden)
Levendowski Daniel
2009-01-01
treatment outcomes. The sample size of this study was small given the night-to-night variability in OSA and limited understanding of polysomnography reliability. We found that in-home studies provided a repeated measure of sleep disordered breathing less variable then polysomnography. Investigators using polysomnography to assess treatment outcomes should factor in the increased variability and bias toward increased AHI values upon retest to ensure the study is adequately powered.
Ramírez, Cristian; Young, Ashley; James, Bryony; Aguilera, José M
2010-10-01
Quantitative analysis of food structure is commonly obtained by image analysis of a small portion of the material that may not be the representative of the whole sample. In order to quantify structural parameters (air cells) of 2 types of bread (bread and bagel) the concept of representative volume element (RVE) was employed. The RVE for bread, bagel, and gelatin-gel (used as control) was obtained from the relationship between sample size and the coefficient of variation, calculated from the apparent Young's modulus measured on 25 replicates. The RVE was obtained when the coefficient of variation for different sample sizes converged to a constant value. In the 2 types of bread tested, the tendency of the coefficient of variation was to decrease as the sample size increased, while in the homogeneous gelatin-gel, it remained always constant around 2.3% to 2.4%. The RVE resulted to be cubes with sides of 45 mm for bread, 20 mm for bagels, and 10 mm for gelatin-gel (smallest sample tested). The quantitative image analysis as well as visual observation demonstrated that bread presented the largest dispersion of air-cell sizes. Moreover, both the ratio of maximum air-cell area/image area and maximum air-cell height/image height were greater for bread (values of 0.05 and 0.30, respectively) than for bagels (0.03 and 0.20, respectively). Therefore, the size and the size variation of air cells present in the structure determined the size of the RVE. It was concluded that RVE is highly dependent on the heterogeneity of the structure of the types of baked products.
Uijlenhoet, R.; Porrà, J.M.; Sempere Torres, D.; Creutin, J.D.
2006-01-01
A stochastic model of the microstructure of rainfall is used to derive explicit expressions for the magnitude of the sampling fluctuations in rainfall properties estimated from raindrop size measurements in stationary rainfall. The model is a marked point process, in which the points represent the
Biological Sampling Variability Study
Energy Technology Data Exchange (ETDEWEB)
Amidan, Brett G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hutchison, Janine R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2016-11-08
There are many sources of variability that exist in the sample collection and analysis process. This paper addresses many, but not all, sources of variability. The main focus of this paper was to better understand and estimate variability due to differences between samplers. Variability between days was also studied, as well as random variability within each sampler. Experiments were performed using multiple surface materials (ceramic and stainless steel), multiple contaminant concentrations (10 spores and 100 spores), and with and without the presence of interfering material. All testing was done with sponge sticks using 10-inch by 10-inch coupons. Bacillus atrophaeus was used as the BA surrogate. Spores were deposited using wet deposition. Grime was coated on the coupons which were planned to include the interfering material (Section 3.3). Samples were prepared and analyzed at PNNL using CDC protocol (Section 3.4) and then cultured and counted. Five samplers were trained so that samples were taken using the same protocol. Each sampler randomly sampled eight coupons each day, four coupons with 10 spores deposited and four coupons with 100 spores deposited. Each day consisted of one material being tested. The clean samples (no interfering materials) were run first, followed by the dirty samples (coated with interfering material). There was a significant difference in recovery efficiency between the coupons with 10 spores deposited (mean of 48.9%) and those with 100 spores deposited (mean of 59.8%). There was no general significant difference between the clean and dirty (containing interfering material) coupons or between the two surface materials; however, there was a significant interaction between concentration amount and presence of interfering material. The recovery efficiency was close to the same for coupons with 10 spores deposited, but for the coupons with 100 spores deposited, the recovery efficiency for the dirty samples was significantly larger (65
Variability in human body size
Annis, J. F.
1978-01-01
The range of variability found among homogeneous groups is described and illustrated. Those trends that show significantly marked differences between sexes and among a number of racial/ethnic groups are also presented. Causes of human-body size variability discussed include genetic endowment, aging, nutrition, protective garments, and occupation. The information is presented to aid design engineers of space flight hardware and equipment.
Choosing a suitable sample size in descriptive sampling
International Nuclear Information System (INIS)
Lee, Yong Kyun; Choi, Dong Hoon; Cha, Kyung Joon
2010-01-01
Descriptive sampling (DS) is an alternative to crude Monte Carlo sampling (CMCS) in finding solutions to structural reliability problems. It is known to be an effective sampling method in approximating the distribution of a random variable because it uses the deterministic selection of sample values and their random permutation,. However, because this method is difficult to apply to complex simulations, the sample size is occasionally determined without thorough consideration. Input sample variability may cause the sample size to change between runs, leading to poor simulation results. This paper proposes a numerical method for choosing a suitable sample size for use in DS. Using this method, one can estimate a more accurate probability of failure in a reliability problem while running a minimal number of simulations. The method is then applied to several examples and compared with CMCS and conventional DS to validate its usefulness and efficiency
Sample size determination and power
Ryan, Thomas P, Jr
2013-01-01
THOMAS P. RYAN, PhD, teaches online advanced statistics courses for Northwestern University and The Institute for Statistics Education in sample size determination, design of experiments, engineering statistics, and regression analysis.
The large sample size fallacy.
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.
Concepts in sample size determination
Directory of Open Access Journals (Sweden)
Umadevi K Rao
2012-01-01
Full Text Available Investigators involved in clinical, epidemiological or translational research, have the drive to publish their results so that they can extrapolate their findings to the population. This begins with the preliminary step of deciding the topic to be studied, the subjects and the type of study design. In this context, the researcher must determine how many subjects would be required for the proposed study. Thus, the number of individuals to be included in the study, i.e., the sample size is an important consideration in the design of many clinical studies. The sample size determination should be based on the difference in the outcome between the two groups studied as in an analytical study, as well as on the accepted p value for statistical significance and the required statistical power to test a hypothesis. The accepted risk of type I error or alpha value, which by convention is set at the 0.05 level in biomedical research defines the cutoff point at which the p value obtained in the study is judged as significant or not. The power in clinical research is the likelihood of finding a statistically significant result when it exists and is typically set to >80%. This is necessary since the most rigorously executed studies may fail to answer the research question if the sample size is too small. Alternatively, a study with too large a sample size will be difficult and will result in waste of time and resources. Thus, the goal of sample size planning is to estimate an appropriate number of subjects for a given study design. This article describes the concepts in estimating the sample size.
Sample size estimation and sampling techniques for selecting a representative sample
Directory of Open Access Journals (Sweden)
Aamir Omair
2014-01-01
Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.
Sample size calculation in metabolic phenotyping studies.
Billoir, Elise; Navratil, Vincent; Blaise, Benjamin J
2015-09-01
The number of samples needed to identify significant effects is a key question in biomedical studies, with consequences on experimental designs, costs and potential discoveries. In metabolic phenotyping studies, sample size determination remains a complex step. This is due particularly to the multiple hypothesis-testing framework and the top-down hypothesis-free approach, with no a priori known metabolic target. Until now, there was no standard procedure available to address this purpose. In this review, we discuss sample size estimation procedures for metabolic phenotyping studies. We release an automated implementation of the Data-driven Sample size Determination (DSD) algorithm for MATLAB and GNU Octave. Original research concerning DSD was published elsewhere. DSD allows the determination of an optimized sample size in metabolic phenotyping studies. The procedure uses analytical data only from a small pilot cohort to generate an expanded data set. The statistical recoupling of variables procedure is used to identify metabolic variables, and their intensity distributions are estimated by Kernel smoothing or log-normal density fitting. Statistically significant metabolic variations are evaluated using the Benjamini-Yekutieli correction and processed for data sets of various sizes. Optimal sample size determination is achieved in a context of biomarker discovery (at least one statistically significant variation) or metabolic exploration (a maximum of statistically significant variations). DSD toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) for Kernel and log-normal estimates, and in GNU Octave for log-normal estimates (Kernel density estimates are not robust enough in GNU octave). It is available at http://www.prabi.fr/redmine/projects/dsd/repository, with a tutorial at http://www.prabi.fr/redmine/projects/dsd/wiki. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Sample size for morphological traits of pigeonpea
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Giovani Facco
2015-12-01
Full Text Available The objectives of this study were to determine the sample size (i.e., number of plants required to accurately estimate the average of morphological traits of pigeonpea (Cajanus cajan L. and to check for variability in sample size between evaluation periods and seasons. Two uniformity trials (i.e., experiments without treatment were conducted for two growing seasons. In the first season (2011/2012, the seeds were sown by broadcast seeding, and in the second season (2012/2013, the seeds were sown in rows spaced 0.50 m apart. The ground area in each experiment was 1,848 m2, and 360 plants were marked in the central area, in a 2 m × 2 m grid. Three morphological traits (e.g., number of nodes, plant height and stem diameter were evaluated 13 times during the first season and 22 times in the second season. Measurements for all three morphological traits were normally distributed and confirmed through the Kolmogorov-Smirnov test. Randomness was confirmed using the Run Test, and the descriptive statistics were calculated. For each trait, the sample size (n was calculated for the semiamplitudes of the confidence interval (i.e., estimation error equal to 2, 4, 6, ..., 20% of the estimated mean with a confidence coefficient (1-? of 95%. Subsequently, n was fixed at 360 plants, and the estimation error of the estimated percentage of the average for each trait was calculated. Variability of the sample size for the pigeonpea culture was observed between the morphological traits evaluated, among the evaluation periods and between seasons. Therefore, to assess with an accuracy of 6% of the estimated average, at least 136 plants must be evaluated throughout the pigeonpea crop cycle to determine the sample size for the traits (e.g., number of nodes, plant height and stem diameter in the different evaluation periods and between seasons.
How Sample Size Affects a Sampling Distribution
Mulekar, Madhuri S.; Siegel, Murray H.
2009-01-01
If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…
Preeminence and prerequisites of sample size calculations in clinical trials
Directory of Open Access Journals (Sweden)
Richa Singhal
2015-01-01
Full Text Available The key components while planning a clinical study are the study design, study duration, and sample size. These features are an integral part of planning a clinical trial efficiently, ethically, and cost-effectively. This article describes some of the prerequisites for sample size calculation. It also explains that sample size calculation is different for different study designs. The article in detail describes the sample size calculation for a randomized controlled trial when the primary outcome is a continuous variable and when it is a proportion or a qualitative variable.
Sample size calculations for case-control studies
This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.
Sample size in qualitative interview studies
DEFF Research Database (Denmark)
Malterud, Kirsti; Siersma, Volkert Dirk; Guassora, Ann Dorrit Kristiane
2016-01-01
Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is “saturation.” Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose...... the concept “information power” to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power...... and during data collection of a qualitative study is discussed....
Sample size optimization in nuclear material control. 1
International Nuclear Information System (INIS)
Gladitz, J.
1982-01-01
Equations have been derived and exemplified which allow the determination of the minimum variables sample size for given false alarm and detection probabilities of nuclear material losses and diversions, respectively. (author)
Wynants, L.; Bouwmeester, W.; Moons, K. G. M.; Moerbeek, M.; Timmerman, D.; Van Huffel, S.; Van Calster, B.; Vergouwe, Y.
2015-01-01
Objectives: This study aims to investigate the influence of the amount of clustering [intraclass correlation (ICC) = 0%, 5%, or 20%], the number of events per variable (EPV) or candidate predictor (EPV = 5, 10, 20, or 50), and backward variable selection on the performance of prediction models.
RNA-seq: technical variability and sampling
2011-01-01
Background RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. PMID:21645359
Dynamically variable spot size laser system
Gradl, Paul R. (Inventor); Hurst, John F. (Inventor); Middleton, James R. (Inventor)
2012-01-01
A Dynamically Variable Spot Size (DVSS) laser system for bonding metal components includes an elongated housing containing a light entry aperture coupled to a laser beam transmission cable and a light exit aperture. A plurality of lenses contained within the housing focus a laser beam from the light entry aperture through the light exit aperture. The lenses may be dynamically adjusted to vary the spot size of the laser. A plurality of interoperable safety devices, including a manually depressible interlock switch, an internal proximity sensor, a remotely operated potentiometer, a remotely activated toggle and a power supply interlock, prevent activation of the laser and DVSS laser system if each safety device does not provide a closed circuit. The remotely operated potentiometer also provides continuous variability in laser energy output.
Decision Support on Small size Passive Samples
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Vladimir Popukaylo
2018-05-01
Full Text Available A construction technique of adequate mathematical models for small size passive samples, in conditions when classical probabilistic-statis\\-tical methods do not allow obtaining valid conclusions was developed.
Experimental determination of size distributions: analyzing proper sample sizes
International Nuclear Information System (INIS)
Buffo, A; Alopaeus, V
2016-01-01
The measurement of various particle size distributions is a crucial aspect for many applications in the process industry. Size distribution is often related to the final product quality, as in crystallization or polymerization. In other cases it is related to the correct evaluation of heat and mass transfer, as well as reaction rates, depending on the interfacial area between the different phases or to the assessment of yield stresses of polycrystalline metals/alloys samples. The experimental determination of such distributions often involves laborious sampling procedures and the statistical significance of the outcome is rarely investigated. In this work, we propose a novel rigorous tool, based on inferential statistics, to determine the number of samples needed to obtain reliable measurements of size distribution, according to specific requirements defined a priori. Such methodology can be adopted regardless of the measurement technique used. (paper)
Estimating Sample Size for Usability Testing
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Alex Cazañas
2017-02-01
Full Text Available One strategy used to assure that an interface meets user requirements is to conduct usability testing. When conducting such testing one of the unknowns is sample size. Since extensive testing is costly, minimizing the number of participants can contribute greatly to successful resource management of a project. Even though a significant number of models have been proposed to estimate sample size in usability testing, there is still not consensus on the optimal size. Several studies claim that 3 to 5 users suffice to uncover 80% of problems in a software interface. However, many other studies challenge this assertion. This study analyzed data collected from the user testing of a web application to verify the rule of thumb, commonly known as the “magic number 5”. The outcomes of the analysis showed that the 5-user rule significantly underestimates the required sample size to achieve reasonable levels of problem detection.
Predicting sample size required for classification performance
Directory of Open Access Journals (Sweden)
Figueroa Rosa L
2012-02-01
Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.
Sample size allocation in multiregional equivalence studies.
Liao, Jason J Z; Yu, Ziji; Li, Yulan
2018-06-17
With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches. Copyright © 2018 John Wiley & Sons, Ltd.
Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.
Algina, James; Olejnik, Stephen
2000-01-01
Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)
Variability of the raindrop size distribution at small spatial scales
Berne, A.; Jaffrain, J.
2010-12-01
Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.
Estimating Search Engine Index Size Variability
DEFF Research Database (Denmark)
Van den Bosch, Antal; Bogers, Toine; De Kunder, Maurice
2016-01-01
One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel...... method of estimating the size of a Web search engine’s index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing’s indices over a nine-year period, from March 2006...... until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find...
Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.
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.
Estimation of sample size and testing power (part 6).
Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo
2012-03-01
The design of one factor with k levels (k ≥ 3) refers to the research that only involves one experimental factor with k levels (k ≥ 3), and there is no arrangement for other important non-experimental factors. This paper introduces the estimation of sample size and testing power for quantitative data and qualitative data having a binary response variable with the design of one factor with k levels (k ≥ 3).
Mobile Variable Depth Sampling System Design Study
International Nuclear Information System (INIS)
BOGER, R.M.
2000-01-01
A design study is presented for a mobile, variable depth sampling system (MVDSS) that will support the treatment and immobilization of Hanford LAW and HLW. The sampler can be deployed in a 4-inch tank riser and has a design that is based on requirements identified in the Level 2 Specification (latest revision). The waste feed sequence for the MVDSS is based on Phase 1, Case 3S6 waste feed sequence. Technical information is also presented that supports the design study
Mobile Variable Depth Sampling System Design Study
Energy Technology Data Exchange (ETDEWEB)
BOGER, R.M.
2000-08-25
A design study is presented for a mobile, variable depth sampling system (MVDSS) that will support the treatment and immobilization of Hanford LAW and HLW. The sampler can be deployed in a 4-inch tank riser and has a design that is based on requirements identified in the Level 2 Specification (latest revision). The waste feed sequence for the MVDSS is based on Phase 1, Case 3S6 waste feed sequence. Technical information is also presented that supports the design study.
Extension of Latin hypercube samples with correlated variables
Energy Technology Data Exchange (ETDEWEB)
Sallaberry, C.J. [Sandia National Laboratories, Department 6784, MS 0776, Albuquerque, NM 87185-0776 (United States); Helton, J.C. [Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804 (United States)], E-mail: jchelto@sandia.gov; Hora, S.C. [University of Hawaii at Hilo, Hilo, HI 96720-4091 (United States)
2008-07-15
A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.
Extension of Latin hypercube samples with correlated variables
International Nuclear Information System (INIS)
Sallaberry, C.J.; Helton, J.C.; Hora, S.C.
2008-01-01
A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations
Extension of latin hypercube samples with correlated variables.
Energy Technology Data Exchange (ETDEWEB)
Hora, Stephen Curtis (University of Hawaii at Hilo, HI); Helton, Jon Craig (Arizona State University, Tempe, AZ); Sallaberry, Cedric J. PhD. (.; .)
2006-11-01
A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.
Vanishing auxiliary variables in PPS sampling - with applications in microscopy
DEFF Research Database (Denmark)
Andersen, Ina Trolle; Hahn, Ute; Jensen, Eva B. Vedel
Recently, non-uniform sampling has been suggested in microscopy to increase eﬃciency. More precisely, sampling proportional to size (PPS) has been introduced where the probability of sampling a unit in the population is proportional to the value of an auxiliary variable. Unfortunately, vanishing...... auxiliary variables are a common phenomenon in microscopy and, accordingly, part of the population is not accessible, using PPS sampling. We propose a modiﬁcation of the design, for which an optimal solution can be found, using a model assisted approach. The optimal design has independent interest...... in sampling theory. We verify robustness of the new approach by numerical results, and we use real data to illustrate the applicability....
Spatial Variability of CCN Sized Aerosol Particles
Asmi, A.; Väänänen, R.
2014-12-01
The computational limitations restrict the grid size used in GCM models, and for many cloud types they are too large when compared to the scale of the cloud formation processes. Several parameterizations for e.g. convective cloud formation exist, but information on spatial subgrid variation of the cloud condensation nuclei (CCNs) sized aerosol concentration is not known. We quantify this variation as a function of the spatial scale by using datasets from airborne aerosol measurement campaigns around the world including EUCAARI LONGREX, ATAR, INCA, INDOEX, CLAIRE, PEGASOS and several regional airborne campaigns in Finland. The typical shapes of the distributions are analyzed. When possible, we use information obtained by CCN counters. In some other cases, we use particle size distribution measured by for example SMPS to get approximated CCN concentration. Other instruments used include optical particle counters or condensational particle counters. When using the GCM models, the CCN concentration used for each the grid-box is often considered to be either flat, or as an arithmetic mean of the concentration inside the grid-box. However, the aircraft data shows that the concentration values are often lognormal distributed. This, combined with the subgrid variations in the land use and atmospheric properties, might cause that the aerosol-cloud interactions calculated by using mean values to vary significantly from the true effects both temporary and spatially. This, in turn, can cause non-linear bias into the GCMs. We calculate the CCN aerosol concentration distribution as a function of different spatial scales. The measurements allow us to study the variation of these distributions within from hundreds of meters up to hundreds of kilometers. This is used to quantify the potential error when mean values are used in GCMs.
Estimation of sample size and testing power (Part 3).
Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo
2011-12-01
This article introduces the definition and sample size estimation of three special tests (namely, non-inferiority test, equivalence test and superiority test) for qualitative data with the design of one factor with two levels having a binary response variable. Non-inferiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is not clinically inferior to that of the positive control drug. Equivalence test refers to the research design of which the objective is to verify that the experimental drug and the control drug have clinically equivalent efficacy. Superiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is clinically superior to that of the control drug. By specific examples, this article introduces formulas of sample size estimation for the three special tests, and their SAS realization in detail.
Preeminence and prerequisites of sample size calculations in clinical trials
Richa Singhal; Rakesh Rana
2015-01-01
The key components while planning a clinical study are the study design, study duration, and sample size. These features are an integral part of planning a clinical trial efficiently, ethically, and cost-effectively. This article describes some of the prerequisites for sample size calculation. It also explains that sample size calculation is different for different study designs. The article in detail describes the sample size calculation for a randomized controlled trial when the primary out...
Simple and multiple linear regression: sample size considerations.
Hanley, James A
2016-11-01
The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Research on test of product based on spatial sampling criteria and variable step sampling mechanism
Li, Ruihong; Han, Yueping
2014-09-01
This paper presents an effective approach for online testing the assembly structures inside products using multiple views technique and X-ray digital radiography system based on spatial sampling criteria and variable step sampling mechanism. Although there are some objects inside one product to be tested, there must be a maximal rotary step for an object within which the least structural size to be tested is predictable. In offline learning process, Rotating the object by the step and imaging it and so on until a complete cycle is completed, an image sequence is obtained that includes the full structural information for recognition. The maximal rotary step is restricted by the least structural size and the inherent resolution of the imaging system. During online inspection process, the program firstly finds the optimum solutions to all different target parts in the standard sequence, i.e., finds their exact angles in one cycle. Aiming at the issue of most sizes of other targets in product are larger than that of the least structure, the paper adopts variable step-size sampling mechanism to rotate the product specific angles with different steps according to different objects inside the product and match. Experimental results show that the variable step-size method can greatly save time compared with the traditional fixed-step inspection method while the recognition accuracy is guaranteed.
Decision-making and sampling size effect
Ismariah Ahmad; Rohana Abd Rahman; Roda Jean-Marc; Lim Hin Fui; Mohd Parid Mamat
2010-01-01
Sound decision-making requires quality information. Poor information does not help in decision making. Among the sources of low quality information, an important cause is inadequate and inappropriate sampling. In this paper we illustrate the case of information collected on timber prices.
Thermal barriers constrain microbial elevational range size via climate variability.
Wang, Jianjun; Soininen, Janne
2017-08-01
Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.
Effects of sample size on the second magnetization peak in ...
Indian Academy of Sciences (India)
the sample size decreases – a result that could be interpreted as a size effect in the order– disorder vortex matter phase transition. However, local magnetic measurements trace this effect to metastable disordered vortex states, revealing the same order–disorder transition induction in samples of different size. Keywords.
Computing Confidence Bounds for Power and Sample Size of the General Linear Univariate Model
Taylor, Douglas J.; Muller, Keith E.
1995-01-01
The power of a test, the probability of rejecting the null hypothesis in favor of an alternative, may be computed using estimates of one or more distributional parameters. Statisticians frequently fix mean values and calculate power or sample size using a variance estimate from an existing study. Hence computed power becomes a random variable for a fixed sample size. Likewise, the sample size necessary to achieve a fixed power varies randomly. Standard statistical practice requires reporting ...
Sample sizes to control error estimates in determining soil bulk density in California forest soils
Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber
2016-01-01
Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...
Sample size determination in clinical trials with multiple endpoints
Sozu, Takashi; Hamasaki, Toshimitsu; Evans, Scott R
2015-01-01
This book integrates recent methodological developments for calculating the sample size and power in trials with more than one endpoint considered as multiple primary or co-primary, offering an important reference work for statisticians working in this area. The determination of sample size and the evaluation of power are fundamental and critical elements in the design of clinical trials. If the sample size is too small, important effects may go unnoticed; if the sample size is too large, it represents a waste of resources and unethically puts more participants at risk than necessary. Recently many clinical trials have been designed with more than one endpoint considered as multiple primary or co-primary, creating a need for new approaches to the design and analysis of these clinical trials. The book focuses on the evaluation of power and sample size determination when comparing the effects of two interventions in superiority clinical trials with multiple endpoints. Methods for sample size calculation in clin...
CT dose survey in adults: what sample size for what precision?
International Nuclear Information System (INIS)
Taylor, Stephen; Muylem, Alain van; Howarth, Nigel; Gevenois, Pierre Alain; Tack, Denis
2017-01-01
To determine variability of volume computed tomographic dose index (CTDIvol) and dose-length product (DLP) data, and propose a minimum sample size to achieve an expected precision. CTDIvol and DLP values of 19,875 consecutive CT acquisitions of abdomen (7268), thorax (3805), lumbar spine (3161), cervical spine (1515) and head (4106) were collected in two centers. Their variabilities were investigated according to sample size (10 to 1000 acquisitions) and patient body weight categories (no weight selection, 67-73 kg and 60-80 kg). The 95 % confidence interval in percentage of their median (CI95/med) value was calculated for increasing sample sizes. We deduced the sample size that set a 95 % CI lower than 10 % of the median (CI95/med ≤ 10 %). Sample size ensuring CI95/med ≤ 10 %, ranged from 15 to 900 depending on the body region and the dose descriptor considered. In sample sizes recommended by regulatory authorities (i.e., from 10-20 patients), mean CTDIvol and DLP of one sample ranged from 0.50 to 2.00 times its actual value extracted from 2000 samples. The sampling error in CTDIvol and DLP means is high in dose surveys based on small samples of patients. Sample size should be increased at least tenfold to decrease this variability. (orig.)
CT dose survey in adults: what sample size for what precision?
Energy Technology Data Exchange (ETDEWEB)
Taylor, Stephen [Hopital Ambroise Pare, Department of Radiology, Mons (Belgium); Muylem, Alain van [Hopital Erasme, Department of Pneumology, Brussels (Belgium); Howarth, Nigel [Clinique des Grangettes, Department of Radiology, Chene-Bougeries (Switzerland); Gevenois, Pierre Alain [Hopital Erasme, Department of Radiology, Brussels (Belgium); Tack, Denis [EpiCURA, Clinique Louis Caty, Department of Radiology, Baudour (Belgium)
2017-01-15
To determine variability of volume computed tomographic dose index (CTDIvol) and dose-length product (DLP) data, and propose a minimum sample size to achieve an expected precision. CTDIvol and DLP values of 19,875 consecutive CT acquisitions of abdomen (7268), thorax (3805), lumbar spine (3161), cervical spine (1515) and head (4106) were collected in two centers. Their variabilities were investigated according to sample size (10 to 1000 acquisitions) and patient body weight categories (no weight selection, 67-73 kg and 60-80 kg). The 95 % confidence interval in percentage of their median (CI95/med) value was calculated for increasing sample sizes. We deduced the sample size that set a 95 % CI lower than 10 % of the median (CI95/med ≤ 10 %). Sample size ensuring CI95/med ≤ 10 %, ranged from 15 to 900 depending on the body region and the dose descriptor considered. In sample sizes recommended by regulatory authorities (i.e., from 10-20 patients), mean CTDIvol and DLP of one sample ranged from 0.50 to 2.00 times its actual value extracted from 2000 samples. The sampling error in CTDIvol and DLP means is high in dose surveys based on small samples of patients. Sample size should be increased at least tenfold to decrease this variability. (orig.)
Estimation of sample size and testing power (Part 4).
Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo
2012-01-01
Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.
Sample size determination for mediation analysis of longitudinal data.
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.
Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
Directory of Open Access Journals (Sweden)
Bruno Giacomini Sari
2017-09-01
Full Text Available ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.
Directory of Open Access Journals (Sweden)
Marcos Rafael Nanni
2011-06-01
Full Text Available The importance of understanding spatial variability of soils is connected to crop management planning. This understanding makes it possible to treat soil not as a uniform, but a variable entity, and it enables site-specific management to increase production efficiency, which is the target of precision agriculture. Questions remain as the optimum soil sampling interval needed to make site-specific fertilizer recommendations in Brazil. The objectives of this study were: i to evaluate the spatial variability of the main attributes that influence fertilization recommendations, using georeferenced soil samples arranged in grid patterns of different resolutions; ii to compare the spatial maps generated with those obtained with the standard sampling of 1 sample ha-1, in order to verify the appropriateness of the spatial resolution. The attributes evaluated were phosphorus (P, potassium (K, organic matter (OM, base saturation (V% and clay. Soil samples were collected in a 100 × 100 m georeferenced grid. Thinning was performed in order to create a grid with one sample every 2.07, 2.88, 3.75 and 7.20 ha. Geostatistical techniques, such as semivariogram and interpolation using kriging, were used to analyze the attributes at the different grid resolutions. This analysis was performed with the Vesper software package. The maps created by this method were compared using the kappa statistics. Additionally, correlation graphs were drawn by plotting the observed values against the estimated values using cross-validation. P, K and V%, a finer sampling resolution than the one using 1 sample ha-1 is required, while for OM and clay coarser resolutions of one sample every two and three hectares, respectively, may be acceptable.A importância de compreender a variabilidade espacial do solo está conectada ao planejamento do manejo das culturas. Este entendimento faz com que seja possível tratar o solo não como uma entidade uniforme, mas variável, e permite o
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
Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm
Directory of Open Access Journals (Sweden)
S. Radhika
2016-04-01
Full Text Available Maximum correntropy criterion (MCC based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.
Sample size reassessment for a two-stage design controlling the false discovery rate.
Zehetmayer, Sonja; Graf, Alexandra C; Posch, Martin
2015-11-01
Sample size calculations for gene expression microarray and NGS-RNA-Seq experiments are challenging because the overall power depends on unknown quantities as the proportion of true null hypotheses and the distribution of the effect sizes under the alternative. We propose a two-stage design with an adaptive interim analysis where these quantities are estimated from the interim data. The second stage sample size is chosen based on these estimates to achieve a specific overall power. The proposed procedure controls the power in all considered scenarios except for very low first stage sample sizes. The false discovery rate (FDR) is controlled despite of the data dependent choice of sample size. The two-stage design can be a useful tool to determine the sample size of high-dimensional studies if in the planning phase there is high uncertainty regarding the expected effect sizes and variability.
Impact analysis of flow variability in sizing kanbans
Directory of Open Access Journals (Sweden)
Isaac Pergher
2014-02-01
Full Text Available The aim of this paper is to analyze the effects of variability flow, advocated by Factory Physics, in sizing Kanban production systems. The variability of flow presupposes that the variability of activities performed by a process is dissipated throughout the productive flow system, causing variations in the lead time, the work-in-process levels and the equipment availability, among others. To conduct the research, we created a didactic model of discrete event computer simulation. The proposed model aims to present the possible impacts caused by the variability flow in a production system regarding the sizing of the number of Kanbans cards, by using the results supplied by two different investigated scenarios. The main results of the research allow concluding that, by comparing the two scenarios developed in the model, the presence of variability in the production system caused an average increase of 32% in the number of Kanban cards (p=0,000. This implies that, in real productive systems, the study of Kanban sizing should consider the variability of individual operations, a fact often relegated as an assumption in the formulation from classical literature on the definition of the number of Kanbans, thus providing opportunities for the development of future research.
40 CFR 80.127 - Sample size guidelines.
2010-07-01
... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Sample size guidelines. 80.127 Section 80.127 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Attest Engagements § 80.127 Sample size guidelines. In performing the...
Selection for altruism through random drift in variable size populations
Directory of Open Access Journals (Sweden)
Houchmandzadeh Bahram
2012-05-01
Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.
Sample Size in Qualitative Interview Studies: Guided by Information Power.
Malterud, Kirsti; Siersma, Volkert Dirk; Guassora, Ann Dorrit
2015-11-27
Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is "saturation." Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose the concept "information power" to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning and during data collection of a qualitative study is discussed. © The Author(s) 2015.
[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].
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.
Effect of sample size on bias correction performance
Reiter, Philipp; Gutjahr, Oliver; Schefczyk, Lukas; Heinemann, Günther; Casper, Markus C.
2014-05-01
extended by varying the splitting of the 40 years into calibration and validation period. The results indicate, that in comparison to the "best fit" a significant decrease in the median performance is on average observed when reducing the length of the calibration period to about half of the "best fit" of 30 years, but the spread between RCMs is quite large. More important than the median performances are however the performances of the repetitions with the largest mean absolute error for each sample size. For these, a significant decrease in performance can already be observed when reducing the length of the calibration period by only a few years. This is caused by the fact that the larger number of repetitions for reduced sample sizes goes along with an increase in the variability of the bias correction performance.
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.
Sampling strategies for estimating brook trout effective population size
Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher
2012-01-01
The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...
Sample sizes and model comparison metrics for species distribution models
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....
Estimation of sample size and testing power (part 5).
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.
Variable screening and ranking using sampling-based sensitivity measures
International Nuclear Information System (INIS)
Wu, Y-T.; Mohanty, Sitakanta
2006-01-01
This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables
Determination of the optimal sample size for a clinical trial accounting for the population size.
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.
Neuromuscular dose-response studies: determining sample size.
Kopman, A F; Lien, C A; Naguib, M
2011-02-01
Investigators planning dose-response studies of neuromuscular blockers have rarely used a priori power analysis to determine the minimal sample size their protocols require. Institutional Review Boards and peer-reviewed journals now generally ask for this information. This study outlines a proposed method for meeting these requirements. The slopes of the dose-response relationships of eight neuromuscular blocking agents were determined using regression analysis. These values were substituted for γ in the Hill equation. When this is done, the coefficient of variation (COV) around the mean value of the ED₅₀ for each drug is easily calculated. Using these values, we performed an a priori one-sample two-tailed t-test of the means to determine the required sample size when the allowable error in the ED₅₀ was varied from ±10-20%. The COV averaged 22% (range 15-27%). We used a COV value of 25% in determining the sample size. If the allowable error in finding the mean ED₅₀ is ±15%, a sample size of 24 is needed to achieve a power of 80%. Increasing 'accuracy' beyond this point requires increasing greater sample sizes (e.g. an 'n' of 37 for a ±12% error). On the basis of the results of this retrospective analysis, a total sample size of not less than 24 subjects should be adequate for determining a neuromuscular blocking drug's clinical potency with a reasonable degree of assurance.
On sample size and different interpretations of snow stability datasets
Schirmer, M.; Mitterer, C.; Schweizer, J.
2009-04-01
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
Sample size calculation for comparing two negative binomial rates.
Zhu, Haiyuan; Lakkis, Hassan
2014-02-10
Negative binomial model has been increasingly used to model the count data in recent clinical trials. It is frequently chosen over Poisson model in cases of overdispersed count data that are commonly seen in clinical trials. One of the challenges of applying negative binomial model in clinical trial design is the sample size estimation. In practice, simulation methods have been frequently used for sample size estimation. In this paper, an explicit formula is developed to calculate sample size based on the negative binomial model. Depending on different approaches to estimate the variance under null hypothesis, three variations of the sample size formula are proposed and discussed. Important characteristics of the formula include its accuracy and its ability to explicitly incorporate dispersion parameter and exposure time. The performance of the formula with each variation is assessed using simulations. Copyright © 2013 John Wiley & Sons, Ltd.
[Practical aspects regarding sample size in clinical research].
Vega Ramos, B; Peraza Yanes, O; Herrera Correa, G; Saldívar Toraya, S
1996-01-01
The knowledge of the right sample size let us to be sure if the published results in medical papers had a suitable design and a proper conclusion according to the statistics analysis. To estimate the sample size we must consider the type I error, type II error, variance, the size of the effect, significance and power of the test. To decide what kind of mathematics formula will be used, we must define what kind of study we have, it means if its a prevalence study, a means values one or a comparative one. In this paper we explain some basic topics of statistics and we describe four simple samples of estimation of sample size.
Effects of sample size on the second magnetization peak in ...
Indian Academy of Sciences (India)
8+ crystals are observed at low temperatures, above the temperature where the SMP totally disappears. In particular, the onset of the SMP shifts to lower fields as the sample size decreases - a result that could be interpreted as a size effect in ...
Sample size computation for association studies using case–parents ...
Indian Academy of Sciences (India)
ple size needed to reach a given power (Knapp 1999; Schaid. 1999; Chen and Deng 2001; Brown 2004). In their seminal paper, Risch and Merikangas (1996) showed that for a mul- tiplicative mode of inheritance (MOI) for the susceptibility gene, sample size depends on two parameters: the frequency of the risk allele at the ...
The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.
Shen, Dan; Shen, Haipeng; Zhu, Hongtu; Marron, J S
2016-10-01
The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirections under the spike models with distinguishable (or indistinguishable) eigenvalues, when the sample size and/or the number of variables (or dimension) tend to infinity. The consistency of the sample eigenvectors relative to their population counterparts is determined by the ratio between the dimension and the product of the sample size with the spike size. When this ratio converges to a nonzero constant, the sample eigenvector converges to a cone, with a certain angle to its corresponding population eigenvector. In the High Dimension, Low Sample Size case, the angle between the sample eigenvector and its population counterpart converges to a limiting distribution. Several generalizations of the multi-spike covariance models are also explored, and additional theoretical results are presented.
Size variability of handwriting in healthy Korean older adults.
Yoon, Ji Hye; Kim, Hyanghee; Kim, Jungwan; Park, Eunjeong; Kim, Soo Ryon
2014-04-01
The aim of the present study was to delineate how age-related deterioration affects the handwriting of healthy elderly (HE) subjects. A total of 235 HE (54 males, 181 females) aged 57-91 years participated as subjects in the study. In order to compare the area of handwriting, we divided the participants into two groups: (i) aged 57-74 years; and (ii) aged 75-91 years. The writing stimulus was a four-syllabic word with one-to-one grapheme-to-phoneme correspondence. The size of each syllable in the target word was measured using a software program. Alignment of the word to baseline was assessed using a multiple-choice checklist. As compared with handwriting by the younger group, the older group showed greater variability in the size of the written syllables within the word (P = 0.023). The handwriting was characterized by unequal size among syllables and non-perpendicular alignment, which could be explained by several factors. First, the variability might have resulted from irregular fine movement motor control in older adults. Second, the deterioration of visual feedback and visuomotor integration in normal aging might have affected handwriting performance. In conclusion, variability of handwriting can be sensitive in predicting the aging process. © 2013 Japan Geriatrics Society.
Sample size determination for equivalence assessment with multiple endpoints.
Sun, Anna; Dong, Xiaoyu; Tsong, Yi
2014-01-01
Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.
A flexible method for multi-level sample size determination
International Nuclear Information System (INIS)
Lu, Ming-Shih; Sanborn, J.B.; Teichmann, T.
1997-01-01
This paper gives a flexible method to determine sample sizes for both systematic and random error models (this pertains to sampling problems in nuclear safeguard questions). In addition, the method allows different attribute rejection limits. The new method could assist achieving a higher detection probability and enhance inspection effectiveness
Chen, Henian; Zhang, Nanhua; Lu, Xiaosun; Chen, Sophie
2013-08-01
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.
Directory of Open Access Journals (Sweden)
Lee Tae-Hoon
2016-12-01
Full Text Available In many cases, a X¯$\\overline X $ control chart based on a performance variable is used in industrial fields. Typically, the control chart monitors the measurements of a performance variable itself. However, if the performance variable is too costly or impossible to measure, and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we present a model for the economic statistical design of a VSI (Variable Sampling Interval X¯$\\overline X $ control chart using a surrogate variable that is linearly correlated with the performance variable. We derive the total average profit model from an economic viewpoint and apply the model to a Very High Temperature Reactor (VHTR nuclear fuel measurement system and derive the optimal result using genetic algorithms. Compared with the control chart based on a performance variable, the proposed model gives a larger expected net income per unit of time in the long-run if the correlation between the performance variable and the surrogate variable is relatively high. The proposed model was confined to the sample mean control chart under the assumption that a single assignable cause occurs according to the Poisson process. However, the model may also be extended to other types of control charts using a single or multiple assignable cause assumptions such as VSS (Variable Sample Size X¯$\\overline X $ control chart, EWMA, CUSUM charts and so on.
Student throughput variables and properties: Varying cohort sizes
Directory of Open Access Journals (Sweden)
Lucas C.A. Stoop
2017-11-01
Full Text Available A recent research paper described how student throughput variables and properties combine to explain the behaviour of stationary or simplified throughput systems. Such behaviour can be understood in terms of the locus of a point in the triangular admissible region of the H-S plane, where H represents headcounts and S successful credits, each depending on the system properties at that point. The efficiency of the student throughput process is given by the ratio S/H. Simplified throughput systems are characterised by stationary graduation and dropout patterns of students as well as by annual intakes of student cohorts of equal size. The effect of varying the size of the annual intakes of student cohorts is reported on here. The observations made lead to the establishment of a more generalised student throughput theory which includes the simplified theory as a special case. The generalised theory still retains the notion of a triangular admissible region in the H-S plane but with the size and shape of the triangle depending on the size of the student cohorts. The ratio S/H again emerges as the process efficiency measure for throughput systems in general with unchanged roles assigned to important system properties. This theory provides for a more fundamental understanding of student throughput systems encountered in real life. Significance: A generalised stationary student throughput theory through varying cohort sizes allows for a far better understanding of real student throughput systems.
Directory of Open Access Journals (Sweden)
R. Eric Heidel
2016-01-01
Full Text Available Statistical power is the ability to detect a significant effect, given that the effect actually exists in a population. Like most statistical concepts, statistical power tends to induce cognitive dissonance in hepatology researchers. However, planning for statistical power by an a priori sample size calculation is of paramount importance when designing a research study. There are five specific empirical components that make up an a priori sample size calculation: the scale of measurement of the outcome, the research design, the magnitude of the effect size, the variance of the effect size, and the sample size. A framework grounded in the phenomenon of isomorphism, or interdependencies amongst different constructs with similar forms, will be presented to understand the isomorphic effects of decisions made on each of the five aforementioned components of statistical power.
Sample Size Determination for One- and Two-Sample Trimmed Mean Tests
Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng
2008-01-01
Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…
Revisiting sample size: are big trials the answer?
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.
Sample size in psychological research over the past 30 years.
Marszalek, Jacob M; Barber, Carolyn; Kohlhart, Julie; Holmes, Cooper B
2011-04-01
The American Psychological Association (APA) Task Force on Statistical Inference was formed in 1996 in response to a growing body of research demonstrating methodological issues that threatened the credibility of psychological research, and made recommendations to address them. One issue was the small, even dramatically inadequate, size of samples used in studies published by leading journals. The present study assessed the progress made since the Task Force's final report in 1999. Sample sizes reported in four leading APA journals in 1955, 1977, 1995, and 2006 were compared using nonparametric statistics, while data from the last two waves were fit to a hierarchical generalized linear growth model for more in-depth analysis. Overall, results indicate that the recommendations for increasing sample sizes have not been integrated in core psychological research, although results slightly vary by field. This and other implications are discussed in the context of current methodological critique and practice.
Impact of shoe size in a sample of elderly individuals
Directory of Open Access Journals (Sweden)
Daniel López-López
Full Text Available Summary Introduction: The use of an improper shoe size is common in older people and is believed to have a detrimental effect on the quality of life related to foot health. The objective is to describe and compare, in a sample of participants, the impact of shoes that fit properly or improperly, as well as analyze the scores related to foot health and health overall. Method: A sample of 64 participants, with a mean age of 75.3±7.9 years, attended an outpatient center where self-report data was recorded, the measurements of the size of the feet and footwear were determined and the scores compared between the group that wears the correct size of shoes and another group of individuals who do not wear the correct size of shoes, using the Spanish version of the Foot Health Status Questionnaire. Results: The group wearing an improper shoe size showed poorer quality of life regarding overall health and specifically foot health. Differences between groups were evaluated using a t-test for independent samples resulting statistically significant (p<0.05 for the dimension of pain, function, footwear, overall foot health, and social function. Conclusion: Inadequate shoe size has a significant negative impact on quality of life related to foot health. The degree of negative impact seems to be associated with age, sex, and body mass index (BMI.
Optimal sample size for probability of detection curves
International Nuclear Information System (INIS)
Annis, Charles; Gandossi, Luca; Martin, Oliver
2013-01-01
Highlights: • We investigate sample size requirement to develop probability of detection curves. • We develop simulations to determine effective inspection target sizes, number and distribution. • We summarize these findings and provide guidelines for the NDE practitioner. -- Abstract: The use of probability of detection curves to quantify the reliability of non-destructive examination (NDE) systems is common in the aeronautical industry, but relatively less so in the nuclear industry, at least in European countries. Due to the nature of the components being inspected, sample sizes tend to be much lower. This makes the manufacturing of test pieces with representative flaws, in sufficient numbers, so to draw statistical conclusions on the reliability of the NDT system under investigation, quite costly. The European Network for Inspection and Qualification (ENIQ) has developed an inspection qualification methodology, referred to as the ENIQ Methodology. It has become widely used in many European countries and provides assurance on the reliability of NDE systems, but only qualitatively. The need to quantify the output of inspection qualification has become more important as structural reliability modelling and quantitative risk-informed in-service inspection methodologies become more widely used. A measure of the NDE reliability is necessary to quantify risk reduction after inspection and probability of detection (POD) curves provide such a metric. The Joint Research Centre, Petten, The Netherlands supported ENIQ by investigating the question of the sample size required to determine a reliable POD curve. As mentioned earlier manufacturing of test pieces with defects that are typically found in nuclear power plants (NPPs) is usually quite expensive. Thus there is a tendency to reduce sample sizes, which in turn increases the uncertainty associated with the resulting POD curve. The main question in conjunction with POS curves is the appropriate sample size. Not
Determining sample size for assessing species composition in ...
African Journals Online (AJOL)
Species composition is measured in grasslands for a variety of reasons. Commonly, observations are made using the wheel-point apparatus, but the problem of determining optimum sample size has not yet been satisfactorily resolved. In this study the wheel-point apparatus was used to record 2 000 observations in each of ...
Research Note Pilot survey to assess sample size for herbaceous ...
African Journals Online (AJOL)
A pilot survey to determine sub-sample size (number of point observations per plot) for herbaceous species composition assessments, using a wheel-point apparatus applying the nearest-plant method, was conducted. Three plots differing in species composition on the Zululand coastal plain were selected, and on each plot ...
Test of a sample container for shipment of small size plutonium samples with PAT-2
International Nuclear Information System (INIS)
Kuhn, E.; Aigner, H.; Deron, S.
1981-11-01
A light-weight container for the air transport of plutonium, to be designated PAT-2, has been developed in the USA and is presently undergoing licensing. The very limited effective space for bearing plutonium required the design of small size sample canisters to meet the needs of international safeguards for the shipment of plutonium samples. The applicability of a small canister for the sampling of small size powder and solution samples has been tested in an intralaboratory experiment. The results of the experiment, based on the concept of pre-weighed samples, show that the tested canister can successfully be used for the sampling of small size PuO 2 -powder samples of homogeneous source material, as well as for dried aliquands of plutonium nitrate solutions. (author)
Sample size determination for logistic regression on a logit-normal distribution.
Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance
2017-06-01
Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.
The PowerAtlas: a power and sample size atlas for microarray experimental design and research
Directory of Open Access Journals (Sweden)
Wang Jelai
2006-02-01
Full Text Available Abstract Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas 1. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO. The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC. Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.
Pengaruh Current Ratio, Asset Size, dan Earnings Variability terhadap Beta Pasar
Directory of Open Access Journals (Sweden)
Ahim Abdurahim
2016-02-01
Full Text Available The research objective was to determine the effect of variable accounting ie :, current ratio, asset size and earnings variability of the market beta. This study used 72 samples. Analyzer used to test the hypothesis that regression. Previous methods of Fowler and Rorke (1983 to adjust the market beta, and BLUE test is used to test classic assumptions of the independent variables are multikolinearitas, heteroskedasitas with Breushch-Pagan-Godfrey test, and autocorrelation with BG (The Breussh-Godfrey. The results found that the hypothesis H1a, H1b, H1c, and H2a powered means no influence current ratio, asset size and earnings variability of the market beta, both individually and simultaneously.
Optical variability of the medium-bright quasar sample
International Nuclear Information System (INIS)
Huang, K.; Mitchell, K.J.; Usher, P.D.
1990-01-01
A variability study of the 32-member Medium-Bright Quasar Sample is reported. It is found that the star US 1953 has undergone a noticeable variation in the course of 26 hr. Apparent variations in the extragalactic object US 3498 may be illusory, owing to its partially resolved appearance. No other evidence for variability was detected. 34 refs
Petruzzellis, Francesco; Palandrani, Chiara; Savi, Tadeja; Alberti, Roberto; Nardini, Andrea; Bacaro, Giovanni
2017-12-01
The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV BI ) and among populations (ITV POP ), relatively few studies have analyzed intraspecific variability within individuals (ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.
Effects of sample size on estimates of population growth rates calculated with matrix models.
Directory of Open Access Journals (Sweden)
Ian J Fiske
Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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
Effects of sample size on estimates of population growth rates calculated with matrix models.
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.
Rock sampling. [method for controlling particle size distribution
Blum, P. (Inventor)
1971-01-01
A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.
Development of sample size allocation program using hypergeometric distribution
International Nuclear Information System (INIS)
Kim, Hyun Tae; Kwack, Eun Ho; Park, Wan Soo; Min, Kyung Soo; Park, Chan Sik
1996-01-01
The objective of this research is the development of sample allocation program using hypergeometric distribution with objected-oriented method. When IAEA(International Atomic Energy Agency) performs inspection, it simply applies a standard binomial distribution which describes sampling with replacement instead of a hypergeometric distribution which describes sampling without replacement in sample allocation to up to three verification methods. The objective of the IAEA inspection is the timely detection of diversion of significant quantities of nuclear material, therefore game theory is applied to its sampling plan. It is necessary to use hypergeometric distribution directly or approximate distribution to secure statistical accuracy. Improved binomial approximation developed by Mr. J. L. Jaech and correctly applied binomial approximation are more closer to hypergeometric distribution in sample size calculation than the simply applied binomial approximation of the IAEA. Object-oriented programs of 1. sample approximate-allocation with correctly applied standard binomial approximation, 2. sample approximate-allocation with improved binomial approximation, and 3. sample approximate-allocation with hypergeometric distribution were developed with Visual C ++ and corresponding programs were developed with EXCEL(using Visual Basic for Application). 8 tabs., 15 refs. (Author)
Comparing Server Energy Use and Efficiency Using Small Sample Sizes
Energy Technology Data Exchange (ETDEWEB)
Coles, Henry C.; Qin, Yong; Price, Phillip N.
2014-11-01
This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency. The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro. Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured. At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a
Estimation of individual reference intervals in small sample sizes
DEFF Research Database (Denmark)
Hansen, Ase Marie; Garde, Anne Helene; Eller, Nanna Hurwitz
2007-01-01
In occupational health studies, the study groups most often comprise healthy subjects performing their work. Sampling is often planned in the most practical way, e.g., sampling of blood in the morning at the work site just after the work starts. Optimal use of reference intervals requires...... from various variables such as gender, age, BMI, alcohol, smoking, and menopause. The reference intervals were compared to reference intervals calculated using IFCC recommendations. Where comparable, the IFCC calculated reference intervals had a wider range compared to the variance component models...
Rational Variability in Children's Causal Inferences: The Sampling Hypothesis
Denison, Stephanie; Bonawitz, Elizabeth; Gopnik, Alison; Griffiths, Thomas L.
2013-01-01
We present a proposal--"The Sampling Hypothesis"--suggesting that the variability in young children's responses may be part of a rational strategy for inductive inference. In particular, we argue that young learners may be randomly sampling from the set of possible hypotheses that explain the observed data, producing different hypotheses with…
Sample Size Calculation for Controlling False Discovery Proportion
Directory of Open Access Journals (Sweden)
Shulian Shang
2012-01-01
Full Text Available The false discovery proportion (FDP, the proportion of incorrect rejections among all rejections, is a direct measure of abundance of false positive findings in multiple testing. Many methods have been proposed to control FDP, but they are too conservative to be useful for power analysis. Study designs for controlling the mean of FDP, which is false discovery rate, have been commonly used. However, there has been little attempt to design study with direct FDP control to achieve certain level of efficiency. We provide a sample size calculation method using the variance formula of the FDP under weak-dependence assumptions to achieve the desired overall power. The relationship between design parameters and sample size is explored. The adequacy of the procedure is assessed by simulation. We illustrate the method using estimated correlations from a prostate cancer dataset.
An integrated approach for multi-level sample size determination
International Nuclear Information System (INIS)
Lu, M.S.; Teichmann, T.; Sanborn, J.B.
1997-01-01
Inspection procedures involving the sampling of items in a population often require steps of increasingly sensitive measurements, with correspondingly smaller sample sizes; these are referred to as multilevel sampling schemes. In the case of nuclear safeguards inspections verifying that there has been no diversion of Special Nuclear Material (SNM), these procedures have been examined often and increasingly complex algorithms have been developed to implement them. The aim in this paper is to provide an integrated approach, and, in so doing, to describe a systematic, consistent method that proceeds logically from level to level with increasing accuracy. The authors emphasize that the methods discussed are generally consistent with those presented in the references mentioned, and yield comparable results when the error models are the same. However, because of its systematic, integrated approach the proposed method elucidates the conceptual understanding of what goes on, and, in many cases, simplifies the calculations. In nuclear safeguards inspections, an important aspect of verifying nuclear items to detect any possible diversion of nuclear fissile materials is the sampling of such items at various levels of sensitivity. The first step usually is sampling by ''attributes'' involving measurements of relatively low accuracy, followed by further levels of sampling involving greater accuracy. This process is discussed in some detail in the references given; also, the nomenclature is described. Here, the authors outline a coordinated step-by-step procedure for achieving such multilevel sampling, and they develop the relationships between the accuracy of measurement and the sample size required at each stage, i.e., at the various levels. The logic of the underlying procedures is carefully elucidated; the calculations involved and their implications, are clearly described, and the process is put in a form that allows systematic generalization
Effects of sample size and sampling frequency on studies of brown bear home ranges and habitat use
Arthur, Steve M.; Schwartz, Charles C.
1999-01-01
We equipped 9 brown bears (Ursus arctos) on the Kenai Peninsula, Alaska, with collars containing both conventional very-high-frequency (VHF) transmitters and global positioning system (GPS) receivers programmed to determine an animal's position at 5.75-hr intervals. We calculated minimum convex polygon (MCP) and fixed and adaptive kernel home ranges for randomly-selected subsets of the GPS data to examine the effects of sample size on accuracy and precision of home range estimates. We also compared results obtained by weekly aerial radiotracking versus more frequent GPS locations to test for biases in conventional radiotracking data. Home ranges based on the MCP were 20-606 km2 (x = 201) for aerial radiotracking data (n = 12-16 locations/bear) and 116-1,505 km2 (x = 522) for the complete GPS data sets (n = 245-466 locations/bear). Fixed kernel home ranges were 34-955 km2 (x = 224) for radiotracking data and 16-130 km2 (x = 60) for the GPS data. Differences between means for radiotracking and GPS data were due primarily to the larger samples provided by the GPS data. Means did not differ between radiotracking data and equivalent-sized subsets of GPS data (P > 0.10). For the MCP, home range area increased and variability decreased asymptotically with number of locations. For the kernel models, both area and variability decreased with increasing sample size. Simulations suggested that the MCP and kernel models required >60 and >80 locations, respectively, for estimates to be both accurate (change in area bears. Our results suggest that the usefulness of conventional radiotracking data may be limited by potential biases and variability due to small samples. Investigators that use home range estimates in statistical tests should consider the effects of variability of those estimates. Use of GPS-equipped collars can facilitate obtaining larger samples of unbiased data and improve accuracy and precision of home range estimates.
Sample size of the reference sample in a case-augmented study.
Ghosh, Palash; Dewanji, Anup
2017-05-01
The case-augmented study, in which a case sample is augmented with a reference (random) sample from the source population with only covariates information known, is becoming popular in different areas of applied science such as pharmacovigilance, ecology, and econometrics. In general, the case sample is available from some source (for example, hospital database, case registry, etc.); however, the reference sample is required to be drawn from the corresponding source population. The required minimum size of the reference sample is an important issue in this regard. In this work, we address the minimum sample size calculation and discuss related issues. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Sample size for monitoring sirex populations and their natural enemies
Directory of Open Access Journals (Sweden)
Susete do Rocio Chiarello Penteado
2016-09-01
Full Text Available The woodwasp Sirex noctilio Fabricius (Hymenoptera: Siricidae was introduced in Brazil in 1988 and became the main pest in pine plantations. It has spread to about 1.000.000 ha, at different population levels, in the states of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo and Minas Gerais. Control is done mainly by using a nematode, Deladenus siricidicola Bedding (Nematoda: Neothylenchidae. The evaluation of the efficiency of natural enemies has been difficult because there are no appropriate sampling systems. This study tested a hierarchical sampling system to define the sample size to monitor the S. noctilio population and the efficiency of their natural enemies, which was found to be perfectly adequate.
Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization
Trevelin, Leonardo Carreira; Novaes, Roberto Leonan Morim; Colas-Rosas, Paul François; Benathar, Thayse Cristhina Melo; Peres, Carlos A.
2017-01-01
The advantages of mist-netting, the main technique used in Neotropical bat community studies to date, include logistical implementation, standardization and sampling representativeness. Nonetheless, study designs still have to deal with issues of detectability related to how different species behave and use the environment. Yet there is considerable sampling heterogeneity across available studies in the literature. Here, we approach the problem of sample size optimization. We evaluated the co...
Forecasting transient sleep episodes by pupil size variability
Directory of Open Access Journals (Sweden)
Schumann Andy
2017-09-01
Full Text Available The ability to predict when a person is about to fall asleep is an important challenge in recent biomedical research and has various possible applications. Sleepiness and fatigue are known to increase pupillary fluctuations and the occurrence of eye blinks. In this study, we evaluated the use of the pupil diameter to forecast sleep episodes of short duration (>1s. We conducted multi-channel physiological and pupillometric recordings (diameter, gaze position in 91 healthy volunteers at rest in supine position. Although they were instructed to keep their eyes open, short sleep episodes were detected in 20 participants (16 males, age: 26.2±5.6 years, 53 events in total. Before each sleep event, pupil size was extracted in a window of 30s (without additional sleep event. Mean pupil diameter and its standard deviation, Shannon entropy and wavelet entropy in the first half (15s were compared to the second half of the window (15s. Linear and nonlinear measures demonstrated an elevation of pupil size variability before sleep onset. Most obviously, WE and SD increased significantly from 0.054±0.056 and 0.38±0.16 mm to 0.113±0.103 (T(102=2.44, p<0.001 and 0.46±0.18 mm (T(104=3.67, p<0.05 in the second half of each analysis window. We were able to identify 83% of the pre-sleep segments by linear discriminant analysis. Although our data was acquired in an experimental condition, it suggests that pupillary unrest might be a suitable predictor of events related to transient sleep or inattentiveness. In the future, we are going to involve the other recorded physiological signals into the analysis.
Directory of Open Access Journals (Sweden)
Simon Dellicour
Full Text Available Morphological traits can be highly variable over time in a particular geographical area. Different selective pressures shape those traits, which is crucial in evolutionary biology. Among these traits, insect wing morphometry has already been widely used to describe phenotypic variability at the inter-specific level. On the contrary, fewer studies have focused on intra-specific wing morphometric variability. Yet, such investigations are relevant to study potential convergences of variation that could highlight micro-evolutionary processes. The recent sampling and sequencing of three solitary bees of the genus Melitta across their entire species range provides an excellent opportunity to jointly analyse genetic and morphometric variability. In the present study, we first aim to analyse the spatial distribution of the wing shape and centroid size (used as a proxy for body size variability. Secondly, we aim to test different potential predictors of this variability at both the intra- and inter-population levels, which includes genetic variability, but also geographic locations and distances, elevation, annual mean temperature and precipitation. The comparison of spatial distribution of intra-population morphometric diversity does not reveal any convergent pattern between species, thus undermining the assumption of a potential local and selective adaptation at the population level. Regarding intra-specific wing shape differentiation, our results reveal that some tested predictors, such as geographic and genetic distances, are associated with a significant correlation for some species. However, none of these predictors are systematically identified for the three species as an important factor that could explain the intra-specific morphometric variability. As a conclusion, for the three solitary bee species and at the scale of this study, our results clearly tend to discard the assumption of the existence of a common pattern of intra-specific signal
Dellicour, Simon; Gerard, Maxence; Prunier, Jérôme G; Dewulf, Alexandre; Kuhlmann, Michael; Michez, Denis
2017-01-01
Morphological traits can be highly variable over time in a particular geographical area. Different selective pressures shape those traits, which is crucial in evolutionary biology. Among these traits, insect wing morphometry has already been widely used to describe phenotypic variability at the inter-specific level. On the contrary, fewer studies have focused on intra-specific wing morphometric variability. Yet, such investigations are relevant to study potential convergences of variation that could highlight micro-evolutionary processes. The recent sampling and sequencing of three solitary bees of the genus Melitta across their entire species range provides an excellent opportunity to jointly analyse genetic and morphometric variability. In the present study, we first aim to analyse the spatial distribution of the wing shape and centroid size (used as a proxy for body size) variability. Secondly, we aim to test different potential predictors of this variability at both the intra- and inter-population levels, which includes genetic variability, but also geographic locations and distances, elevation, annual mean temperature and precipitation. The comparison of spatial distribution of intra-population morphometric diversity does not reveal any convergent pattern between species, thus undermining the assumption of a potential local and selective adaptation at the population level. Regarding intra-specific wing shape differentiation, our results reveal that some tested predictors, such as geographic and genetic distances, are associated with a significant correlation for some species. However, none of these predictors are systematically identified for the three species as an important factor that could explain the intra-specific morphometric variability. As a conclusion, for the three solitary bee species and at the scale of this study, our results clearly tend to discard the assumption of the existence of a common pattern of intra-specific signal/structure within the
Predictors of Citation Rate in Psychology: Inconclusive Influence of Effect and Sample Size.
Hanel, Paul H P; Haase, Jennifer
2017-01-01
In the present article, we investigate predictors of how often a scientific article is cited. Specifically, we focus on the influence of two often neglected predictors of citation rate: effect size and sample size, using samples from two psychological topical areas. Both can be considered as indicators of the importance of an article and post hoc (or observed) statistical power, and should, especially in applied fields, predict citation rates. In Study 1, effect size did not have an influence on citation rates across a topical area, both with and without controlling for numerous variables that have been previously linked to citation rates. In contrast, sample size predicted citation rates, but only while controlling for other variables. In Study 2, sample and partly effect sizes predicted citation rates, indicating that the relations vary even between scientific topical areas. Statistically significant results had more citations in Study 2 but not in Study 1. The results indicate that the importance (or power) of scientific findings may not be as strongly related to citation rate as is generally assumed.
Optimal Sample Size for Probability of Detection Curves
International Nuclear Information System (INIS)
Annis, Charles; Gandossi, Luca; Martin, Oliver
2012-01-01
The use of Probability of Detection (POD) curves to quantify NDT reliability is common in the aeronautical industry, but relatively less so in the nuclear industry. The European Network for Inspection Qualification's (ENIQ) Inspection Qualification Methodology is based on the concept of Technical Justification, a document assembling all the evidence to assure that the NDT system in focus is indeed capable of finding the flaws for which it was designed. This methodology has become widely used in many countries, but the assurance it provides is usually of qualitative nature. The need to quantify the output of inspection qualification has become more important, especially as structural reliability modelling and quantitative risk-informed in-service inspection methodologies become more widely used. To credit the inspections in structural reliability evaluations, a measure of the NDT reliability is necessary. A POD curve provides such metric. In 2010 ENIQ developed a technical report on POD curves, reviewing the statistical models used to quantify inspection reliability. Further work was subsequently carried out to investigate the issue of optimal sample size for deriving a POD curve, so that adequate guidance could be given to the practitioners of inspection reliability. Manufacturing of test pieces with cracks that are representative of real defects found in nuclear power plants (NPP) can be very expensive. Thus there is a tendency to reduce sample sizes and in turn reduce the conservatism associated with the POD curve derived. Not much guidance on the correct sample size can be found in the published literature, where often qualitative statements are given with no further justification. The aim of this paper is to summarise the findings of such work. (author)
The Impact of Soil Sampling Errors on Variable Rate Fertilization
Energy Technology Data Exchange (ETDEWEB)
R. L. Hoskinson; R C. Rope; L G. Blackwood; R D. Lee; R K. Fink
2004-07-01
Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and a predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash differences
Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao
2014-10-07
In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.
Two-Stage Variable Sample-Rate Conversion System
Tkacenko, Andre
2009-01-01
A two-stage variable sample-rate conversion (SRC) system has been pro posed as part of a digital signal-processing system in a digital com munication radio receiver that utilizes a variety of data rates. The proposed system would be used as an interface between (1) an analog- todigital converter used in the front end of the receiver to sample an intermediatefrequency signal at a fixed input rate and (2) digita lly implemented tracking loops in subsequent stages that operate at v arious sample rates that are generally lower than the input sample r ate. This Two-Stage System would be capable of converting from an input sample rate to a desired lower output sample rate that could be var iable and not necessarily a rational fraction of the input rate.
Influence of Sample Size on Automatic Positional Accuracy Assessment Methods for Urban Areas
Directory of Open Access Journals (Sweden)
Francisco J. Ariza-López
2018-05-01
Full Text Available In recent years, new approaches aimed to increase the automation level of positional accuracy assessment processes for spatial data have been developed. However, in such cases, an aspect as significant as sample size has not yet been addressed. In this paper, we study the influence of sample size when estimating the planimetric positional accuracy of urban databases by means of an automatic assessment using polygon-based methodology. Our study is based on a simulation process, which extracts pairs of homologous polygons from the assessed and reference data sources and applies two buffer-based methods. The parameter used for determining the different sizes (which range from 5 km up to 100 km has been the length of the polygons’ perimeter, and for each sample size 1000 simulations were run. After completing the simulation process, the comparisons between the estimated distribution functions for each sample and population distribution function were carried out by means of the Kolmogorov–Smirnov test. Results show a significant reduction in the variability of estimations when sample size increased from 5 km to 100 km.
Analysis of time series and size of equivalent sample
International Nuclear Information System (INIS)
Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge
2004-01-01
In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions
Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size
Buscombe, Daniel; Rubin, David M.; Lacy, Jessica R.; Storlazzi, Curt D.; Hatcher, Gerald; Chezar, Henry; Wyland, Robert; Sherwood, Christopher R.
2014-01-01
We describe a remotely operated video microscope system, designed to provide high-resolution images of seabed sediments. Two versions were developed, which differ in how they raise the camera from the seabed. The first used hydraulics and the second used the energy associated with wave orbital motion. Images were analyzed using automated frequency-domain methods, which following a rigorous partially supervised quality control procedure, yielded estimates to within 20% of the true size as determined by on-screen manual measurements of grains. Long-term grain-size variability at a sandy inner shelf site offshore of Santa Cruz, California, USA, was investigated using the hydraulic system. Eighteen months of high frequency (min to h), high-resolution (μm) images were collected, and grain size distributions compiled. The data constitutes the longest known high-frequency record of seabed-grain size at this sample frequency, at any location. Short-term grain-size variability of sand in an energetic surf zone at Praa Sands, Cornwall, UK was investigated using the ‘wave-powered’ system. The data are the first high-frequency record of grain size at a single location of a highly mobile and evolving bed in a natural surf zone. Using this technology, it is now possible to measure bed-sediment-grain size at a time-scale comparable with flow conditions. Results suggest models of sediment transport at sandy, wave-dominated, nearshore locations should allow for substantial changes in grain-size distribution over time-scales as short as a few hours.
Development of a multi-lane X-ray mirror providing variable beam sizes
Energy Technology Data Exchange (ETDEWEB)
Laundy, D., E-mail: david.laundy@diamond.ac.uk; Sawhney, K.; Nistea, I.; Alcock, S. G.; Pape, I.; Sutter, J.; Alianelli, L.; Evans, G. [Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE (United Kingdom)
2016-05-15
Grazing incidence mirrors are used on most X-ray synchrotron beamlines to focus, collimate or suppress harmonics. Increasingly beamline users are demanding variable beam shapes and sizes at the sample position. We have now developed a new concept to rapidly vary the beam size and shape of a focused X-ray beam. The surface of an elliptically figured mirror is divided into a number of laterally separated lanes, each of which is given an additional longitudinal height profile calculated to shape the X-ray beam to a top-hat profile in the focal plane. We have now fabricated two prototype mirrors and present the results of metrology tests and measurements made with one of the mirrors focusing the X-rays on a synchrotron beamline. We envisage that such mirrors could be widely applied to rapid beam-size switching on many synchrotron beamlines.
Krishnamoorthi, R; Anna Poorani, G
2016-01-01
Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.
Continuous-Variable Instantaneous Quantum Computing is Hard to Sample.
Douce, T; Markham, D; Kashefi, E; Diamanti, E; Coudreau, T; Milman, P; van Loock, P; Ferrini, G
2017-02-17
Instantaneous quantum computing is a subuniversal quantum complexity class, whose circuits have proven to be hard to simulate classically in the discrete-variable realm. We extend this proof to the continuous-variable (CV) domain by using squeezed states and homodyne detection, and by exploring the properties of postselected circuits. In order to treat postselection in CVs, we consider finitely resolved homodyne detectors, corresponding to a realistic scheme based on discrete probability distributions of the measurement outcomes. The unavoidable errors stemming from the use of finitely squeezed states are suppressed through a qubit-into-oscillator Gottesman-Kitaev-Preskill encoding of quantum information, which was previously shown to enable fault-tolerant CV quantum computation. Finally, we show that, in order to render postselected computational classes in CVs meaningful, a logarithmic scaling of the squeezing parameter with the circuit size is necessary, translating into a polynomial scaling of the input energy.
Statistical conditional sampling for variable-resolution video compression.
Directory of Open Access Journals (Sweden)
Alexander Wong
Full Text Available In this study, we investigate a variable-resolution approach to video compression based on Conditional Random Field and statistical conditional sampling in order to further improve compression rate while maintaining high-quality video. In the proposed approach, representative key-frames within a video shot are identified and stored at full resolution. The remaining frames within the video shot are stored and compressed at a reduced resolution. At the decompression stage, a region-based dictionary is constructed from the key-frames and used to restore the reduced resolution frames to the original resolution via statistical conditional sampling. The sampling approach is based on the conditional probability of the CRF modeling by use of the constructed dictionary. Experimental results show that the proposed variable-resolution approach via statistical conditional sampling has potential for improving compression rates when compared to compressing the video at full resolution, while achieving higher video quality when compared to compressing the video at reduced resolution.
Sources of variability in collection and preparation of paint and lead-coating samples.
Harper, S L; Gutknecht, W F
2001-06-01
Chronic exposure of children to lead (Pb) can result in permanent physiological impairment. Since surfaces coated with lead-containing paints and varnishes are potential sources of exposure, it is extremely important that reliable methods for sampling and analysis be available. The sources of variability in the collection and preparation of samples were investigated to improve the performance and comparability of methods and to ensure that data generated will be adequate for its intended use. Paint samples of varying sizes (areas and masses) were collected at different locations across a variety of surfaces including metal, plaster, concrete, and wood. A variety of grinding techniques were compared. Manual mortar and pestle grinding for at least 1.5 min and mechanized grinding techniques were found to generate similar homogenous particle size distributions required for aliquots as small as 0.10 g. When 342 samples were evaluated for sample weight loss during mortar and pestle grinding, 4% had 20% or greater loss with a high of 41%. Homogenization and sub-sampling steps were found to be the principal sources of variability related to the size of the sample collected. Analysis of samples from different locations on apparently identical surfaces were found to vary by more than a factor of two both in Pb concentration (mg cm-2 or %) and areal coating density (g cm-2). Analyses of substrates were performed to determine the Pb remaining after coating removal. Levels as high as 1% Pb were found in some substrate samples, corresponding to more than 35 mg cm-2 Pb. In conclusion, these sources of variability must be considered in development and/or application of any sampling and analysis methodologies.
Sample Size of One: Operational Qualitative Analysis in the Classroom
Directory of Open Access Journals (Sweden)
John Hoven
2015-10-01
Full Text Available Qualitative analysis has two extraordinary capabilities: first, finding answers to questions we are too clueless to ask; and second, causal inference – hypothesis testing and assessment – within a single unique context (sample size of one. These capabilities are broadly useful, and they are critically important in village-level civil-military operations. Company commanders need to learn quickly, "What are the problems and possibilities here and now, in this specific village? What happens if we do A, B, and C?" – and that is an ill-defined, one-of-a-kind problem. The U.S. Army's Eighty-Third Civil Affairs Battalion is our "first user" innovation partner in a new project to adapt qualitative research methods to an operational tempo and purpose. Our aim is to develop a simple, low-cost methodology and training program for local civil-military operations conducted by non-specialist conventional forces. Complementary to that, this paper focuses on some essential basics that can be implemented by college professors without significant cost, effort, or disruption.
Genetic variability of sexual size dimorphism in a natural population ...
Indian Academy of Sciences (India)
Unknown
Most animal species exhibit sexual size dimorphism (SSD). SSD is a trait difficult to ...... 26, 15–28. Charnov E. L. 1982 The theory of sex allocation. Princeton .... success in Drosophila melanogaster: the roles of male and female behavior. Anim ...
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.
Hermetic Seal Leak Detection Apparatus with Variable Size Test Chamber
Kelley, Anthony R. (Inventor)
2015-01-01
The present invention is a versatile hermetic seal leak detection apparatus for testing hermetically sealed containers and devices for leaks without the need to create a custom or specially manufactured testing chamber conforming to the dimensions of the specific object under test. The size of the testing chamber may be mechanically adjusted by the novel use of bellows to reduce and optimize the amount of gas space in a test chamber which surrounds the hermetically sealed object under test. The present invention allows the size of the test chamber to be selectively adjusted during testing to provide an optimum test chamber gas space. The present invention may be further adapted to isolate and test specific portions of the hermetically sealed object under test for leaks.
Non-radioactive detection of trinucleotide repeat size variability.
Tomé, Stéphanie; Nicole, Annie; Gomes-Pereira, Mario; Gourdon, Genevieve
2014-03-06
Many human diseases are associated with the abnormal expansion of unstable trinucleotide repeat sequences. The mechanisms of trinucleotide repeat size mutation have not been fully dissected, and their understanding must be grounded on the detailed analysis of repeat size distributions in human tissues and animal models. Small-pool PCR (SP-PCR) is a robust, highly sensitive and efficient PCR-based approach to assess the levels of repeat size variation, providing both quantitative and qualitative data. The method relies on the amplification of a very low number of DNA molecules, through sucessive dilution of a stock genomic DNA solution. Radioactive Southern blot hybridization is sensitive enough to detect SP-PCR products derived from single template molecules, separated by agarose gel electrophoresis and transferred onto DNA membranes. We describe a variation of the detection method that uses digoxigenin-labelled locked nucleic acid probes. This protocol keeps the sensitivity of the original method, while eliminating the health risks associated with the manipulation of radiolabelled probes, and the burden associated with their regulation, manipulation and waste disposal.
Lee, Eun Gyung; Lee, Taekhee; Kim, Seung Won; Lee, Larry; Flemmer, Michael M; Harper, Martin
2014-01-01
This second, and concluding, part of this study evaluated changes in sampling efficiency of respirable size-selective samplers due to air pulsations generated by the selected personal sampling pumps characterized in Part I (Lee E, Lee L, Möhlmann C et al. Evaluation of pump pulsation in respirable size-selective sampling: Part I. Pulsation measurements. Ann Occup Hyg 2013). Nine particle sizes of monodisperse ammonium fluorescein (from 1 to 9 μm mass median aerodynamic diameter) were generated individually by a vibrating orifice aerosol generator from dilute solutions of fluorescein in aqueous ammonia and then injected into an environmental chamber. To collect these particles, 10-mm nylon cyclones, also known as Dorr-Oliver (DO) cyclones, were used with five medium volumetric flow rate pumps. Those were the Apex IS, HFS513, GilAir5, Elite5, and Basic5 pumps, which were found in Part I to generate pulsations of 5% (the lowest), 25%, 30%, 56%, and 70% (the highest), respectively. GK2.69 cyclones were used with the Legacy [pump pulsation (PP) = 15%] and Elite12 (PP = 41%) pumps for collection at high flows. The DO cyclone was also used to evaluate changes in sampling efficiency due to pulse shape. The HFS513 pump, which generates a more complex pulse shape, was compared to a single sine wave fluctuation generated by a piston. The luminescent intensity of the fluorescein extracted from each sample was measured with a luminescence spectrometer. Sampling efficiencies were obtained by dividing the intensity of the fluorescein extracted from the filter placed in a cyclone with the intensity obtained from the filter used with a sharp-edged reference sampler. Then, sampling efficiency curves were generated using a sigmoid function with three parameters and each sampling efficiency curve was compared to that of the reference cyclone by constructing bias maps. In general, no change in sampling efficiency (bias under ±10%) was observed until pulsations exceeded 25% for the
DEFF Research Database (Denmark)
Martínez Vega, Mabel V.; Wulfsohn, Dvoralai; Clemmensen, Line Katrine Harder
2013-01-01
sample of ‘Granny Smith’ (Malus x domestica cv. ‘Granny Smith’) apples obtained from a 17 ha orchard based on a final sample of 74 fruit. Estimates of fruit marketable yield and fruit size distribution agreed well with packing house records. The estimated marketable yield was 356.6 ± 89.2 t compared...... recommended sample sizes to accurately describe the distribution of various quality variables of apples at the orchard scale....
14CO2 analysis of soil gas: Evaluation of sample size limits and sampling devices
Wotte, Anja; Wischhöfer, Philipp; Wacker, Lukas; Rethemeyer, Janet
2017-12-01
Radiocarbon (14C) analysis of CO2 respired from soils or sediments is a valuable tool to identify different carbon sources. The collection and processing of the CO2, however, is challenging and prone to contamination. We thus continuously improve our handling procedures and present a refined method for the collection of even small amounts of CO2 in molecular sieve cartridges (MSCs) for accelerator mass spectrometry 14C analysis. Using a modified vacuum rig and an improved desorption procedure, we were able to increase the CO2 recovery from the MSC (95%) as well as the sample throughput compared to our previous study. By processing series of different sample size, we show that our MSCs can be used for CO2 samples of as small as 50 μg C. The contamination by exogenous carbon determined in these laboratory tests, was less than 2.0 μg C from fossil and less than 3.0 μg C from modern sources. Additionally, we tested two sampling devices for the collection of CO2 samples released from soils or sediments, including a respiration chamber and a depth sampler, which are connected to the MSC. We obtained a very promising, low process blank for the entire CO2 sampling and purification procedure of ∼0.004 F14C (equal to 44,000 yrs BP) and ∼0.003 F14C (equal to 47,000 yrs BP). In contrast to previous studies, we observed no isotopic fractionation towards lighter δ13C values during the passive sampling with the depth samplers.
Genetic variability of sexual size dimorphism in a natural population ...
Indian Academy of Sciences (India)
In a homogeneous sample of 30 lines of Drosophila melanogaster, both indices provided similar intraclass correlations, on average 0.21, significantly greater than zero but lower than those for the traits themselves: 0.50 and 0.36 for wing and thorax length respectively. Wing and thorax length were strongly positively ...
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.
Directory of Open Access Journals (Sweden)
Shaukat S. Shahid
2016-06-01
Full Text Available In this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50 on the eigenvalues and eigenvectors resulting from principal component analysis (PCA. For each sample size, 100 bootstrap samples were drawn from environmental data matrix pertaining to water quality variables (p = 22 of a small data set comprising of 55 samples (stations from where water samples were collected. Because in ecology and environmental sciences the data sets are invariably small owing to high cost of collection and analysis of samples, we restricted our study to relatively small sample sizes. We focused attention on comparison of first 6 eigenvectors and first 10 eigenvalues. Data sets were compared using agglomerative cluster analysis using Ward’s method that does not require any stringent distributional assumptions.
Shieh, Gwowen
2013-01-01
The a priori determination of a proper sample size necessary to achieve some specified power is an important problem encountered frequently in practical studies. To establish the needed sample size for a two-sample "t" test, researchers may conduct the power analysis by specifying scientifically important values as the underlying population means…
Real-time laser cladding control with variable spot size
Arias, J. L.; Montealegre, M. A.; Vidal, F.; Rodríguez, J.; Mann, S.; Abels, P.; Motmans, F.
2014-03-01
Laser cladding processing has been used in different industries to improve the surface properties or to reconstruct damaged pieces. In order to cover areas considerably larger than the diameter of the laser beam, successive partially overlapping tracks are deposited. With no control over the process variables this conduces to an increase of the temperature, which could decrease mechanical properties of the laser cladded material. Commonly, the process is monitored and controlled by a PC using cameras, but this control suffers from a lack of speed caused by the image processing step. The aim of this work is to design and develop a FPGA-based laser cladding control system. This system is intended to modify the laser beam power according to the melt pool width, which is measured using a CMOS camera. All the control and monitoring tasks are carried out by a FPGA, taking advantage of its abundance of resources and speed of operation. The robustness of the image processing algorithm is assessed, as well as the control system performance. Laser power is decreased as substrate temperature increases, thus maintaining a constant clad width. This FPGA-based control system is integrated in an adaptive laser cladding system, which also includes an adaptive optical system that will control the laser focus distance on the fly. The whole system will constitute an efficient instrument for part repair with complex geometries and coating selective surfaces. This will be a significant step forward into the total industrial implementation of an automated industrial laser cladding process.
Variability of mass-size relationships in tropical Mesoscale Convective Systems
Fontaine, Emmanuel; Leroy, Delphine; Delanoë, Julien; Dupuy, Régis; Lilie, Lyle; Strapp, Walter; Protat, Alain; Schwarzenböeck, Alfons
2015-04-01
The mass of individual ice hydrometeors in Mesoscale Convective Systems (MCS) has been investigated in the past using different methods in order to retrieve power law type mass-size relationships m(D) with m = α D^β. This study focuses on the variability of mass-size relationships in different types of MCS. Three types of tropical MCS were sampled during different airborne campaigns: (i) continental MCS during the West African monsoon (Megha-Tropique 2010), (ii) oceanic MCS over the Indian Ocean (Megha-Tropique 2011), and (iii) coastal MCS during the North-Australian monsoon (HAIC-HIWC). Mass-size relationships of ice hydrometeors are derived from a combined analysis of particle images from 2D-array probes and associated reflectivity factors measured with a Doppler cloud radar (94GHz) on the same research aircraft. A theoretical study of numerous hydrometeor shapes simulated in 3D and arbitrarily projected on a 2D plan allowed to constrain the exponent β of the m(D) relationship as a function of the derived surface-diameter relationship S(D), which is likewise written as a power law. Since S(D) always can be determined for real data from 2D optical array probes or other particle imagers, the evolution of the m(D) exponent β can be calculated along the flight trajectory. Then the pre-factor α of m(D) is constrained from theoretical simulations of the radar reflectivity factor matching the measured reflectivity factor along the aircraft trajectory. Finally, the Condensed Water Content (CWC) is deduced from measured particle size distributions (PSD) and retrieved m(D) relationships along the flight trajectory. Solely for the HAIC-HIWC campaign (North Australian Monsoon) a bulk reference measurement (IKP instrument) of high CWC could be performed in order to compare with the above described CWC deduced from ice hydrometeor images and reflectivity factors. Both CWC are coherent. Mean profiles of m(D) coefficients, PSD, and CWC are calculated as a function of the
A contemporary decennial global sample of changing agricultural field sizes
White, E.; Roy, D. P.
2011-12-01
In the last several hundred years agriculture has caused significant human induced Land Cover Land Use Change (LCLUC) with dramatic cropland expansion and a marked increase in agricultural productivity. The size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLUC. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, diffusion of disease pathogens and pests, and loss or degradation in buffers to nutrient, herbicide and pesticide flows. In this study, globally distributed locations with significant contemporary field size change were selected guided by a global map of agricultural yield and literature review and were selected to be representative of different driving forces of field size change (associated with technological innovation, socio-economic conditions, government policy, historic patterns of land cover land use, and environmental setting). Seasonal Landsat data acquired on a decadal basis (for 1980, 1990, 2000 and 2010) were used to extract field boundaries and the temporal changes in field size quantified and their causes discussed.
Zhong, Wei; Koopmeiners, Joseph S; Carlin, Bradley P
2013-11-01
Frequentist sample size determination for binary outcome data in a two-arm clinical trial requires initial guesses of the event probabilities for the two treatments. Misspecification of these event rates may lead to a poor estimate of the necessary sample size. In contrast, the Bayesian approach that considers the treatment effect to be random variable having some distribution may offer a better, more flexible approach. The Bayesian sample size proposed by (Whitehead et al., 2008) for exploratory studies on efficacy justifies the acceptable minimum sample size by a "conclusiveness" condition. In this work, we introduce a new two-stage Bayesian design with sample size reestimation at the interim stage. Our design inherits the properties of good interpretation and easy implementation from Whitehead et al. (2008), generalizes their method to a two-sample setting, and uses a fully Bayesian predictive approach to reduce an overly large initial sample size when necessary. Moreover, our design can be extended to allow patient level covariates via logistic regression, now adjusting sample size within each subgroup based on interim analyses. We illustrate the benefits of our approach with a design in non-Hodgkin lymphoma with a simple binary covariate (patient gender), offering an initial step toward within-trial personalized medicine. Copyright © 2013 Elsevier Inc. All rights reserved.
Variability in permanent tooth size of three ancient populations in Xi'an, northern China.
Huang, Shi-You; Kang, Ting; Liu, Dai-Yun; Duan, Yin-Zhong; Shao, Jin-Ling
2012-11-01
This paper compares permanent dental dimensions between three ancient populations that belonged to the same biological population throughout a temporal range of 2000 years to detect temporal trends and metric variation in dentition. The samples analysed were dental remains of 4502 permanent teeth from 321 individuals, which were excavated from three archaeological sites: Chang'an (1000-1300 years BP), Shanren (2200 years BP) and Shaolingyuan (3000 years BP) in the Xi'an region (northern China). For each tooth three standard measurements were taken: Mesiodistal (MD) diameter of crown, labiolingual or buccolingual (BL) diameter of crown and length of root (LR). Three ancient population samples generally displayed the same dental dimensions (p>0.05), whereas some tooth types varied. The Shaolingyuan had larger canine and the smallest maxillary second molars and the Chang'an had the largest mandibular first molars in the MD dimension. The Shanren had the smallest maxillary third molars and mandibular central incisors, and the Chang'an had the smallest maxillary lateral incisors in the BL dimension. In the LR measures, statistically significant differences of five tooth types showed that the Chang'an were smaller than the Shaolingyuan and the Shanren. Comparisons of coefficients of variation for teeth showed that the length of root and third molar usually displayed greater variation. Decreasing or increasing trend for crown size does not occur between the ancient populations, while changes in crown size of a few tooth types fluctuate. The root size is more variable than the crown size and is likely to reflect a degenerated trend in a few tooth types. Copyright © 2012 Elsevier Ltd. All rights reserved.
7 CFR 52.775 - Sample unit size.
2010-01-01
... Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946... extraneous material—The total contents of each container in the sample. Factors of Quality ...
7 CFR 201.43 - Size of sample.
2010-01-01
... units. Coated seed for germination test only shall consist of at least 1,000 seed units. [10 FR 9950... of samples of agricultural seed, vegetable seed and screenings to be submitted for analysis, test, or..., Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT...
Sample size reduction in groundwater surveys via sparse data assimilation
Hussain, Z.
2013-04-01
In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.
Sample size reduction in groundwater surveys via sparse data assimilation
Hussain, Z.; Muhammad, A.
2013-01-01
In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.
Energy Technology Data Exchange (ETDEWEB)
Aksnes, D.W.; Rørstad, K.; Piro, F.N.
2016-07-01
In this study, we investigate whether university department size is important in determining publication productivity and citation impact. Drawing on a unique dataset containing a variety of different variables at department levels, we are able to provide a richer picture of the research performance than what typically has been the case in many previous studies. In addition to analyzing the basic question of how size relates to scientific performance, we address whether the funding profile of the departments plays a role, whether the scientific performance is influenced by the composition of the academic personnel (in terms of gender, academic positions, recruiting personnel and the share of doctoral degree holders). The study shows that virtually no size effect can be identified and highly productive and highly cited units are found among both small, medium and large departments. For none of the organizational variables we are able to identify statistically significant relationships in respect to research performance at an overall level. We conclude that the productivity and citation differences at the level of departments cannot generally be explained by the selected variables for department size, funding structure and the composition of scientific personnel. (Author)
Observations of the Variability of Floc Sizes on the Louisiana Shelf
Sahin, Cihan; Sheremet, Alexandru
2014-05-01
The general principles of floc formation under variable turbulent stresses and sediment availability are well known, but the details of the dynamics are still unclear. Flocculation of primary particles occurs when these particles get close enough to collide, and a significant number of these collisions result in adhesion. Particle concentration, the intensity and number of collisions (turbulent shear) control the size of the flocs. However, aggregation transitions into fragmentation if the intensity of collisions or turbulent shear exceeds a certain threshold. In this case, a limiting maximum size might exist (Berhane et al., 1997; Dyer and Manning, 1999; Uncles et al., 2010). This study investigates the relation between SSC (suspended sediment concentration), turbulent stresses, and floc size using the high-resolution observations of suspended sediment concentration, flow and acoustic backscatter made for 2 weeks in Spring 2008 on the muddy Atchafalaya Shelf. During the experiment, pressure, near-bed current velocities, and acoustic backscatter profiles were sampled using a downward-pointing 1500-kHz PC-ADP (Pulse-Coherent Acoustic Doppler Profiler, Sontek/YSI). In addition, a downward-pointing single frequency ABS (Acoustic Backscatter Sensor, 700-kHz, Marine Electronics, Isle of Guernsey) measured the intensity of acoustic return in the first meter above bed. Thus, acoustic backscatter profiles were observed by two different frequencies (700 kHz for the ABS and 1500 kHz for the PC-ADP). Direct SSC observations were provided by two OBS-3s at 15 and 40-cm above the bed, which sampled synchronously with the PC-ADP. Simultaneous profiles of SSC and the mean floc size at cm-scale vertical resolution were obtained using acoustic backscatter intensity at the different acoustic frequencies. For the calibration of the instruments, which involves estimation of the instruments system constants, the algorithm described in Sahin et al. (2013) was followed. The mean floc size
Tang, Yongqiang
2015-01-01
A sample size formula is derived for negative binomial regression for the analysis of recurrent events, in which subjects can have unequal follow-up time. We obtain sharp lower and upper bounds on the required size, which is easy to compute. The upper bound is generally only slightly larger than the required size, and hence can be used to approximate the sample size. The lower and upper size bounds can be decomposed into two terms. The first term relies on the mean number of events in each group, and the second term depends on two factors that measure, respectively, the extent of between-subject variability in event rates, and follow-up time. Simulation studies are conducted to assess the performance of the proposed method. An application of our formulae to a multiple sclerosis trial is provided.
The attention-weighted sample-size model of visual short-term memory
DEFF Research Database (Denmark)
Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.
2016-01-01
exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items...
Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A
2017-06-30
Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
A. de Verneil
2018-04-01
Full Text Available Research cruises to quantify biogeochemical fluxes in the ocean require taking measurements at stations lasting at least several days. A popular experimental design is the quasi-Lagrangian drifter, often mounted with in situ incubations or sediment traps that follow the flow of water over time. After initial drifter deployment, the ship tracks the drifter for continuing measurements that are supposed to represent the same water environment. An outstanding question is how to best determine whether this is true. During the Oligotrophy to UlTra-oligotrophy PACific Experiment (OUTPACE cruise, from 18 February to 3 April 2015 in the western tropical South Pacific, three separate stations of long duration (five days over the upper 500 m were conducted in this quasi-Lagrangian sampling scheme. Here we present physical data to provide context for these three stations and to assess whether the sampling strategy worked, i.e., that a single body of water was sampled. After analyzing tracer variability and local water circulation at each station, we identify water layers and times where the drifter risks encountering another body of water. While almost no realization of this sampling scheme will be truly Lagrangian, due to the presence of vertical shear, the depth-resolved observations during the three stations show most layers sampled sufficiently homogeneous physical environments during OUTPACE. By directly addressing the concerns raised by these quasi-Lagrangian sampling platforms, a protocol of best practices can begin to be formulated so that future research campaigns include the complementary datasets and analyses presented here to verify the appropriate use of the drifter platform.
International Nuclear Information System (INIS)
Garcia, D.; Gonzalez, L.M.; Gumberra, R.
1993-01-01
Induced variability in the size of rice plantules was determined using the heritability calculation in a narrow sense, by means of the progenitor-descendant regression. Progenitor stands for the original variety, whereas descendant stands for plant population from CO6 0 gamma-rays irradiated seeds (at 100-600 Gy doses), treated at different temperatures. Results obtained: show the possibility to increase efficiency in variability induction by a combined course of action of both factors. In this experience, the best combination turned out to be 300 Gy-0 celsius grated, which of all the changes that it caused, some 75 percent was of a genetic nature
Soetaert, K.; Heip, C.H.R.
1990-01-01
Diversity indices, although designed for comparative purposes, often cannot be used as such, due to their sample-size dependence. It is argued here that this dependence is more pronounced in high diversity than in low diversity assemblages and that indices more sensitive to rarer species require larger sample sizes to estimate diversity with reasonable precision than indices which put more weight on commoner species. This was tested for Hill's diversity number N sub(0) to N sub( proportional ...
Evaluation of design flood estimates with respect to sample size
Kobierska, Florian; Engeland, Kolbjorn
2016-04-01
Estimation of design floods forms the basis for hazard management related to flood risk and is a legal obligation when building infrastructure such as dams, bridges and roads close to water bodies. Flood inundation maps used for land use planning are also produced based on design flood estimates. In Norway, the current guidelines for design flood estimates give recommendations on which data, probability distribution, and method to use dependent on length of the local record. If less than 30 years of local data is available, an index flood approach is recommended where the local observations are used for estimating the index flood and regional data are used for estimating the growth curve. For 30-50 years of data, a 2 parameter distribution is recommended, and for more than 50 years of data, a 3 parameter distribution should be used. Many countries have national guidelines for flood frequency estimation, and recommended distributions include the log Pearson II, generalized logistic and generalized extreme value distributions. For estimating distribution parameters, ordinary and linear moments, maximum likelihood and Bayesian methods are used. The aim of this study is to r-evaluate the guidelines for local flood frequency estimation. In particular, we wanted to answer the following questions: (i) Which distribution gives the best fit to the data? (ii) Which estimation method provides the best fit to the data? (iii) Does the answer to (i) and (ii) depend on local data availability? To answer these questions we set up a test bench for local flood frequency analysis using data based cross-validation methods. The criteria were based on indices describing stability and reliability of design flood estimates. Stability is used as a criterion since design flood estimates should not excessively depend on the data sample. The reliability indices describe to which degree design flood predictions can be trusted.
Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A
2013-01-01
Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall pdecrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.
Sample Size Induced Brittle-to-Ductile Transition of Single-Crystal Aluminum Nitride
2015-08-01
ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal Aluminum...originator. ARL-RP-0528 ● AUG 2015 US Army Research Laboratory Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal...Sample Size Induced Brittle-to- Ductile Transition of Single-Crystal Aluminum Nitride 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT
Multiple sensitive estimation and optimal sample size allocation in the item sum technique.
Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz
2018-01-01
For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Breaking Free of Sample Size Dogma to Perform Innovative Translational Research
Bacchetti, Peter; Deeks, Steven G.; McCune, Joseph M.
2011-01-01
Innovative clinical and translational research is often delayed or prevented by reviewers’ expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an N of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation. PMID:21677197
Mayer, B; Muche, R
2013-01-01
Animal studies are highly relevant for basic medical research, although their usage is discussed controversially in public. Thus, an optimal sample size for these projects should be aimed at from a biometrical point of view. Statistical sample size calculation is usually the appropriate methodology in planning medical research projects. However, required information is often not valid or only available during the course of an animal experiment. This article critically discusses the validity of formal sample size calculation for animal studies. Within the discussion, some requirements are formulated to fundamentally regulate the process of sample size determination for animal experiments.
Sample size clay kaolin of primary in pegmatites regions Junco Serido - PB and Equador - RN
International Nuclear Information System (INIS)
Meyer, M.F.; Sousa, J.B.M.; Sales, L.R.; Silva, P.A.S.; Lima, A.D.D.
2016-01-01
Kaolin is a clay formed mainly of kaolinite resulting from feldspar weathering or hydrothermal. This study aims to investigate the way of occurrence, kaolin particle size of the pegmatites of the Borborema Province Pegmatitic in the regions of Junco do Serido-PB and Ecuador-RN. These variables were analyzed considering granulometric intervals obtained from wet sieving of samples of pegmatite mines in the region. Kaolin was received using sieves of 200, 325, 400 and 500 mesh and the sieve fractions retained by generating statistical parameters histograms. kaolin particles are extremely fine and pass in its entirety through 500 mesh sieve. The characterization of minerals in fine fractions by diffraction of X-rays showed that the relative amount of sericite in fractions retained in sieves 400 and 500 mesh impairing the whiteness and mineralogical texture kaolin production. (author)
Sampling bee communities using pan traps: alternative methods increase sample size
Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...
Eisenberg, Sarita L.; Guo, Ling-Yu
2015-01-01
Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…
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Kagainis Uìis
2015-12-01
Full Text Available The morphology of Oribatida and similar little-known groups of organisms varies considerably, which complicates morphological analysis (e.g. species descriptions. Qualitative analyses have been carried out mostly on a small number of individuals (n < 25. There is lack of studies dealing with mechanisms of how that variation can change in relation to sample size and insufficient discussion on whether qualitative or quantitative analysis is more appropriate for description of morphological variability. A total of 500 adult Carabodes subarcticus Trägårdh, 1902 Oribatida were collected from a local population. Six qualitative and six quantitative traits were characterised using light microscopy and scanning electron microscopy. The relationships between the sample size of different subsamples (n < 500 and morphological variation were examined using randomised selection (10 000 replicates and calculation of the percentage of cases in which the sizevalues were within a certain distance (less than 10%, 25%, or 50% from the range of the reference population (n = 500. Qualitative traits were significantly less variable than quantitative due to binomial distribution of the obtained data; thus they were less comparable and interpretive to describe morphological variability. When sample size was small (n < 25, in less than 2 to 15% of cases the observed variability was within 10% distance of the range of the reference population. Larger sample sizes resulted in size-ranges that approached those of the reference population. It is possible that execution of quantitative characterisation and use of relatively larger sample sizes could improve species descriptions by characterising the morphological variability more precisely and objectively.
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis
2016-09-08
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order two and three) with variable step size, and prove their optimality, stability, and convergence. The choice of step size for multistep SSP methods is an interesting problem because the allowable step size depends on the SSP coefficient, which in turn depends on the chosen step sizes. The description of the methods includes an optimal step-size strategy. We prove sharp upper bounds on the allowable step size for explicit SSP linear multistep methods and show the existence of methods with arbitrarily high order of accuracy. The effectiveness of the methods is demonstrated through numerical examples.
Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia
2017-04-01
Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental
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Yue Wu
2017-01-01
Full Text Available Firefly Algorithm (FA, for short is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.
The quasar luminosity function from a variability-selected sample
Hawkins, M. R. S.; Veron, P.
1993-01-01
A sample of quasars is selected from a 10-yr sequence of 30 UK Schmidt plates. Luminosity functions are derived in several redshift intervals, which in each case show a featureless power-law rise towards low luminosities. There is no sign of the 'break' found in the recent UVX sample of Boyle et al. It is suggested that reasons for the disagreement are connected with biases in the selection of the UVX sample. The question of the nature of quasar evolution appears to be still unresolved.
Effects of undernutrition and litter size on material variables and pup development.
Jen, K C; Wehmer, F; Morofski, J
1978-05-01
Differential effects of maternal nutrition and litter size variation were examined in a 2 x 2 factorial design in which undernourished or lib fed mothers nursed litters of 4 or 12. Litter size accounted for a greater proportion of pup body weight a weaning than did maternal nutrition. When the mother was fed ad lib, birth weight of individual pups and later body weight were correlated regardless of litter size. When the mother was undernourished, these correlations were not found. Enlargement of littersize increased the pup weight coefficient of variability only when the mother was fed ad lib. Size of the litter did not influence the maternal variables under study: open field behavior, adrenal weight, and body weight.
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.
Lusiana, Evellin Dewi
2017-12-01
The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.
Awunyo-Vitor, Dadson; Al-Hassan, Ramatu M.; Sarpong, Daniel B.
2014-01-01
The study examined maize farmers’ participation in the formal financial market and its impact on farm size and expenditure on variable farm inputs. A multistage sampling method was used in selecting 595 maize farmers from the seven districts in Ashanti and Brong Ahafo Regions of Ghana. A structured questionnaire and interview schedule were used to elicit information from the respondents. The impact of formal financial market participation on farm size and expenditure on variable inputs was es...
Using Environmental Variables for Studying of the Quality of Sampling in Soil Mapping
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A. Jafari
2016-02-01
profiles, which were then described, sampled, analyzed and classified according to the USDA soil classification system (16. The basic rationale is to set up a hypercube, the axes of which are the quantiles of rasters of environmental covariates, e.g., digital elevation model. Sampling evaluation was made using the HELS algorithm. This algorithm was written based on the study of Carre et al., 2007 (3 and run in R. Results and Discussion: The covariate dataset is represented by elevation, slope and wetness index (Table 2. All data layers were interpolated to a common grid of 30 m resolution. The size of the raster layer is 421 by 711 grid cells. Each of the three covariates is divided into four quantiles (Table 2. The hypercube character space has 43, i.e. 64 strata (Figure 5. The average number of grid cells within each stratum is therefore 4677 grid cells. The map of the covariate index (Figure 6 shows some patterns representative of the covariate variability. The values of the covariate index range between 0.0045 and 5.95. This means that some strata are very dense compared to others. This index allows us to explain if high or low relative weight of the sampling units (see below is due to soil sampling or covariate density. The strata with the highest density are in the areas with high geomorphology diversity. It means that geomorphology processes can cause the diversity and variability and it is in line with the geomorphology map (Figure 2. Of the 64 strata, 30.4% represent under-sampling, 60.2% represent adequate sampling and 9.4% represent over-sampling. Regarding the covariate index, most of the under-sampling appears in the high covariate index, where soil covariates are then highly variable. Actually, it is difficult to collect field samples in these highly variable areas (Figure 7. Also, most of the over-sampling was observed in areas with alow covariate index (Figure 7. We calculated the weights of all the sampling units and showed the results in Figure 8. One 64
Moustakas, Aristides; Evans, Matthew R
2015-02-28
Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose. We investigate the survival rates of ten tree species in a dataset designed to monitor growth rates. As some individuals were not included in the census at some time points we use capture-mark-recapture methods both to allow us to account for missing individuals, and to estimate relocation probabilities. Growth rates, size, and light availability were included as covariates in the model predicting survival rates. The study demonstrates that tree mortality is best described as constant between years and size-dependent at early life stages and size independent at later life stages for most species of UK hardwood. We have demonstrated that even with a twenty-year dataset it is possible to discern variability both between individuals and between species. Our work illustrates the potential utility of the method applied here for calculating plant population dynamics parameters in time replicated datasets with small sample sizes and missing individuals without any loss of sample size, and including explanatory covariates.
Brus, D.J.; Gruijter, de J.J.
2003-01-01
In estimating spatial means of environmental variables of a region from data collected by convenience or purposive sampling, validity of the results can be ensured by collecting additional data through probability sampling. The precision of the pi estimator that uses the probability sample can be
Distinct features of intraspecific and intrapopulation variability of the skull size in the red fox.
Gos'kov, A M; Bol'shakov, V N; Korytin, N S
2017-05-01
The range of chronographic variability of the average size of the skull in the red fox (data collected by the authors) from a compact area in the Middle Urals has been assessed for a 30-year period, and the results obtained have been compared with the published data on the geographical variability within the vast species range. The range of changes of the average dimensions of the skull over time spanned almost the entire range of geographical variability. Therefore, the problem of search for factors that determine the morphological diversity arises.
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
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Elias Chaibub Neto
Full Text Available 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.
Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello
2013-10-26
Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.
Eye-size variability in deep-sea lanternfishes (Myctophidae): an ecological and phylogenetic study.
de Busserolles, Fanny; Fitzpatrick, John L; Paxton, John R; Marshall, N Justin; Collin, Shaun P
2013-01-01
One of the most common visual adaptations seen in the mesopelagic zone (200-1000 m), where the amount of light diminishes exponentially with depth and where bioluminescent organisms predominate, is the enlargement of the eye and pupil area. However, it remains unclear how eye size is influenced by depth, other environmental conditions and phylogeny. In this study, we determine the factors influencing variability in eye size and assess whether this variability is explained by ecological differences in habitat and lifestyle within a family of mesopelagic fishes characterized by broad intra- and interspecific variance in depth range and luminous patterns. We focus our study on the lanternfish family (Myctophidae) and hypothesise that lanternfishes with a deeper distribution and/or a reduction of bioluminescent emissions have smaller eyes and that ecological factors rather than phylogenetic relationships will drive the evolution of the visual system. Eye diameter and standard length were measured in 237 individuals from 61 species of lanternfishes representing all the recognised tribes within the family in addition to compiling an ecological dataset including depth distribution during night and day and the location and sexual dimorphism of luminous organs. Hypotheses were tested by investigating the relationship between the relative size of the eye (corrected for body size) and variations in depth and/or patterns of luminous-organs using phylogenetic comparative analyses. Results show a great variability in relative eye size within the Myctophidae at all taxonomic levels (from subfamily to genus), suggesting that this character may have evolved several times. However, variability in eye size within the family could not be explained by any of our ecological variables (bioluminescence and depth patterns), and appears to be driven solely by phylogenetic relationships.
Novikov, I; Fund, N; Freedman, L S
2010-01-15
Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.
Finite-size analysis of continuous-variable measurement-device-independent quantum key distribution
Zhang, Xueying; Zhang, Yichen; Zhao, Yijia; Wang, Xiangyu; Yu, Song; Guo, Hong
2017-10-01
We study the impact of the finite-size effect on the continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) protocol, mainly considering the finite-size effect on the parameter estimation procedure. The central-limit theorem and maximum likelihood estimation theorem are used to estimate the parameters. We also analyze the relationship between the number of exchanged signals and the optimal modulation variance in the protocol. It is proved that when Charlie's position is close to Bob, the CV-MDI QKD protocol has the farthest transmission distance in the finite-size scenario. Finally, we discuss the impact of finite-size effects related to the practical detection in the CV-MDI QKD protocol. The overall results indicate that the finite-size effect has a great influence on the secret-key rate of the CV-MDI QKD protocol and should not be ignored.
International Nuclear Information System (INIS)
Schaaf, Arjen van der; Xu Chengjian; Luijk, Peter van; Veld, Aart A. van’t; Langendijk, Johannes A.; Schilstra, Cornelis
2012-01-01
Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small
Arnup, Sarah J; McKenzie, Joanne E; Pilcher, David; Bellomo, Rinaldo; Forbes, Andrew B
2018-06-01
The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. We show sample size calculations for a two-intervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design). The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design. The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.
Nomogram for sample size calculation on a straightforward basis for the kappa statistic.
Hong, Hyunsook; Choi, Yunhee; Hahn, Seokyung; Park, Sue Kyung; Park, Byung-Joo
2014-09-01
Kappa is a widely used measure of agreement. However, it may not be straightforward in some situation such as sample size calculation due to the kappa paradox: high agreement but low kappa. Hence, it seems reasonable in sample size calculation that the level of agreement under a certain marginal prevalence is considered in terms of a simple proportion of agreement rather than a kappa value. Therefore, sample size formulae and nomograms using a simple proportion of agreement rather than a kappa under certain marginal prevalences are proposed. A sample size formula was derived using the kappa statistic under the common correlation model and goodness-of-fit statistic. The nomogram for the sample size formula was developed using SAS 9.3. The sample size formulae using a simple proportion of agreement instead of a kappa statistic and nomograms to eliminate the inconvenience of using a mathematical formula were produced. A nomogram for sample size calculation with a simple proportion of agreement should be useful in the planning stages when the focus of interest is on testing the hypothesis of interobserver agreement involving two raters and nominal outcome measures. Copyright © 2014 Elsevier Inc. All rights reserved.
Modi ed strip packing heuristics for the rectangular variable-sized ...
African Journals Online (AJOL)
Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP) and the variable-sized bin packing problem (VSBPP). A total of 252 strip packing heuristics (and variations thereof) from the literature, as well as novel heuristics proposed by the authors, are compared statistically by ...
Wu, Yue; Li, Q.; Hu, Qingjie; Borgart, A.
2017-01-01
Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly,
DEFF Research Database (Denmark)
Hamamoto, Shoichiro; Møldrup, Per; Kawamoto, Ken
2009-01-01
The soil gas diffusion coefficient (Dp) and air permeability (ka) and their dependency on soil air content ( ) control gas diffusion and advection in soils. This study investigated the effects of average particle size (D50) and dry bulk density ( b) on Dp and ka for six sandy soils under variably...
The Sample Size Influence in the Accuracy of the Image Classification of the Remote Sensing
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Thomaz C. e C. da Costa
2004-12-01
Full Text Available Landuse/landcover maps produced by classification of remote sensing images incorporate uncertainty. This uncertainty is measured by accuracy indices using reference samples. The size of the reference sample is defined by approximation by a binomial function without the use of a pilot sample. This way the accuracy are not estimated, but fixed a priori. In case of divergency between the estimated and a priori accuracy the error of the sampling will deviate from the expected error. The size using pilot sample (theorically correct procedure justify when haven´t estimate of accuracy for work area, referent the product remote sensing utility.
Variability, plot size and border effect in lettuce trials in protected environment
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Daniel Santos
2018-03-01
Full Text Available ABSTRACT The variability within rows of cultivation may reduce the accuracy of experiments conducted in a complete randomized block design if the rows are considered as blocks, however, little is known about this variability in protected environments. Thus, our aim was to study the variability of the fresh mass in lettuce shoot, growing in protected environment, and to verify the border effect and size of the experimental unit in minimizing the productive variability. Data from two uniformity trials carried out in a greenhouse in autumn and spring growing seasons were used. In the statistical analyses, it was considered the existence of parallel cultivation rows the lateral openings of the greenhouse and of columns perpendicular to these openings. Different scenarios were simulated by excluding rows and columns to generate several borders arrangements and also to use different sizes of the experimental unit. For each scenario, homogeneity test of variances between remaining rows and columns was performed, and it was calculated the variance and coefficient of variation. There is variability among rows in trials with lettuce in plastic greenhouses and the border use does not bring benefits in terms of reduction of the coefficient of variation or minimizing the cases of heterogeneous variances among rows. In experiments with lettuce in a plastic greenhouse, the use of an experimental unit size greater than or equal to two plants provides homogeneity of variances among rows and columns and, therefore, allows the use of a completely randomized design.
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.
Approaches for developing a sizing method for stand-alone PV systems with variable demand
Energy Technology Data Exchange (ETDEWEB)
Posadillo, R. [Grupo de Investigacion en Energias y Recursos Renovables, Dpto. de Fisica Aplicada, E.P.S., Universidad de Cordoba, Avda. Menendez Pidal s/n, 14004 Cordoba (Spain); Lopez Luque, R. [Grupo de Investigacion de Fisica para las Energias y Recursos Renovables, Dpto. de Fisica Aplicada. Edificio C2 Campus de Rabanales, 14071 Cordoba (Spain)
2008-05-15
Accurate sizing is one of the most important aspects to take into consideration when designing a stand-alone photovoltaic system (SAPV). Various methods, which differ in terms of their simplicity or reliability, have been developed for this purpose. Analytical methods, which seek functional relationships between variables of interest to the sizing problem, are one of these approaches. A series of rational considerations are presented in this paper with the aim of shedding light upon the basic principles and results of various sizing methods proposed by different authors. These considerations set the basis for a new analytical method that has been designed for systems with variable monthly energy demands. Following previous approaches, the method proposed is based on the concept of loss of load probability (LLP) - a parameter that is used to characterize system design. The method includes information on the standard deviation of loss of load probability ({sigma}{sub LLP}) and on two new parameters: annual number of system failures (f) and standard deviation of annual number of failures ({sigma}{sub f}). The method proves useful for sizing a PV system in a reliable manner and serves to explain the discrepancies found in the research on systems with LLP<10{sup -2}. We demonstrate that reliability depends not only on the sizing variables and on the distribution function of solar radiation, but on the minimum value as well, which in a given location and with a monthly average clearness index, achieves total solar radiation on the receiver surface. (author)
What is the optimum sample size for the study of peatland testate amoeba assemblages?
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.
Sample Size and Saturation in PhD Studies Using Qualitative Interviews
Directory of Open Access Journals (Sweden)
Mark Mason
2010-08-01
Full Text Available A number of issues can affect sample size in qualitative research; however, the guiding principle should be the concept of saturation. This has been explored in detail by a number of authors but is still hotly debated, and some say little understood. A sample of PhD studies using qualitative approaches, and qualitative interviews as the method of data collection was taken from theses.com and contents analysed for their sample sizes. Five hundred and sixty studies were identified that fitted the inclusion criteria. Results showed that the mean sample size was 31; however, the distribution was non-random, with a statistically significant proportion of studies, presenting sample sizes that were multiples of ten. These results are discussed in relation to saturation. They suggest a pre-meditated approach that is not wholly congruent with the principles of qualitative research. URN: urn:nbn:de:0114-fqs100387
Directory of Open Access Journals (Sweden)
Pitchaiah Mandava
Full Text Available OBJECTIVE: Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS, a range of scores ("Shift" is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. METHODS: We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. RESULTS: Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD. Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001. Taking errors into account, SAINT I would have required 24% more subjects than were randomized. CONCLUSION: We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We
Lawson, Chris A
2014-07-01
Three experiments with 81 3-year-olds (M=3.62years) examined the conditions that enable young children to use the sample size principle (SSP) of induction-the inductive rule that facilitates generalizations from large rather than small samples of evidence. In Experiment 1, children exhibited the SSP when exemplars were presented sequentially but not when exemplars were presented simultaneously. Results from Experiment 3 suggest that the advantage of sequential presentation is not due to the additional time to process the available input from the two samples but instead may be linked to better memory for specific individuals in the large sample. In addition, findings from Experiments 1 and 2 suggest that adherence to the SSP is mediated by the disparity between presented samples. Overall, these results reveal that the SSP appears early in development and is guided by basic cognitive processes triggered during the acquisition of input. Copyright © 2013 Elsevier Inc. All rights reserved.
Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.
Youssef, Noha H; Elshahed, Mostafa S
2008-09-01
Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.
Test of methods for retrospective activity size distribution determination from filter samples
International Nuclear Information System (INIS)
Meisenberg, Oliver; Tschiersch, Jochen
2015-01-01
Determining the activity size distribution of radioactive aerosol particles requires sophisticated and heavy equipment, which makes measurements at large number of sites difficult and expensive. Therefore three methods for a retrospective determination of size distributions from aerosol filter samples in the laboratory were tested for their applicability. Extraction into a carrier liquid with subsequent nebulisation showed size distributions with a slight but correctable bias towards larger diameters compared with the original size distribution. Yields in the order of magnitude of 1% could be achieved. Sonication-assisted extraction into a carrier liquid caused a coagulation mode to appear in the size distribution. Sonication-assisted extraction into the air did not show acceptable results due to small yields. The method of extraction into a carrier liquid without sonication was applied to aerosol samples from Chernobyl in order to calculate inhalation dose coefficients for 137 Cs based on the individual size distribution. The effective dose coefficient is about half of that calculated with a default reference size distribution. - Highlights: • Activity size distributions can be recovered after aerosol sampling on filters. • Extraction into a carrier liquid and subsequent nebulisation is appropriate. • This facilitates the determination of activity size distributions for individuals. • Size distributions from this method can be used for individual dose coefficients. • Dose coefficients were calculated for the workers at the new Chernobyl shelter
Frictional behaviour of sandstone: A sample-size dependent triaxial investigation
Roshan, Hamid; Masoumi, Hossein; Regenauer-Lieb, Klaus
2017-01-01
Frictional behaviour of rocks from the initial stage of loading to final shear displacement along the formed shear plane has been widely investigated in the past. However the effect of sample size on such frictional behaviour has not attracted much attention. This is mainly related to the limitations in rock testing facilities as well as the complex mechanisms involved in sample-size dependent frictional behaviour of rocks. In this study, a suite of advanced triaxial experiments was performed on Gosford sandstone samples at different sizes and confining pressures. The post-peak response of the rock along the formed shear plane has been captured for the analysis with particular interest in sample-size dependency. Several important phenomena have been observed from the results of this study: a) the rate of transition from brittleness to ductility in rock is sample-size dependent where the relatively smaller samples showed faster transition toward ductility at any confining pressure; b) the sample size influences the angle of formed shear band and c) the friction coefficient of the formed shear plane is sample-size dependent where the relatively smaller sample exhibits lower friction coefficient compared to larger samples. We interpret our results in terms of a thermodynamics approach in which the frictional properties for finite deformation are viewed as encompassing a multitude of ephemeral slipping surfaces prior to the formation of the through going fracture. The final fracture itself is seen as a result of the self-organisation of a sufficiently large ensemble of micro-slip surfaces and therefore consistent in terms of the theory of thermodynamics. This assumption vindicates the use of classical rock mechanics experiments to constrain failure of pressure sensitive rocks and the future imaging of these micro-slips opens an exciting path for research in rock failure mechanisms.
Productive variability, border use and plot size in trials with cherry tomato
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Daniel Santos
2018-02-01
Full Text Available ABSTRACT: Knowing the productive variability within protected environments is crucial for choosing the experimental design to be used in that conditions. Thus, the aim of the present study was to assess the variability of fruit production in protected environment cultivated with cherry tomatoes and to verify the border effect and plot size in reducing this variability. To this, data from an uniformity test carried out in a greenhouse with cherry tomato cv. ‘Lili’ were used. Total fresh mass of fruits per plant was considered being these plants arranged in cropping rows parallel to the lateral openings of the greenhouse and also the same plants arranged in columns perpendicular to these openings. To generate the borders, different scenarios were designed by excluding rows and columns and using different plot sizes. In each scenario, homogeneity of variances among the remaining rows and columns was tested. There is no variability of fruit production among rows or columns in trials with cherry tomatoes carried out in greenhouses and the use of border does not bring benefits in terms of reduction of coefficient of variation or reduction of cases of variance heterogeneity among rows or columns. Plots with a size equal to or greater than two plants make possible to use the completely randomized design in the cherry tomato trials in greenhouses.
A sizing method for stand-alone PV installations with variable demand
Energy Technology Data Exchange (ETDEWEB)
Posadillo, R. [Grupo de Investigacion en Energias y Recursos Renovables, Dpto. de Fisica Aplicada, E.P.S., Universidad de Cordoba, Avda. Menendez Pidal s/n, 14004 Cordoba (Spain); Lopez Luque, R. [Grupo de Investigacion de Fisica Para las Energias y Recursos Renovables, Dpto. de Fisica Aplicada, Edificio C2 Campus de Rabanales, 14071 Cordoba (Spain)
2008-05-15
The practical applicability of the considerations made in a previous paper to characterize energy balances in stand-alone photovoltaic systems (SAPV) is presented. Given that energy balances were characterized based on monthly estimations, the method is appropriate for sizing installations with variable monthly demands and variable monthly panel tilt (for seasonal estimations). The method presented is original in that it is the only method proposed for this type of demand. The method is based on the rational utilization of daily solar radiation distribution functions. When exact mathematical expressions are not available, approximate empirical expressions can be used. The more precise the statistical characterization of the solar radiation on the receiver module, the more precise the sizing method given that the characterization will solely depend on the distribution function of the daily global irradiation on the tilted surface H{sub g{beta}}{sub i}. This method, like previous ones, uses the concept of loss of load probability (LLP) as a parameter to characterize system design and includes information on the standard deviation of this parameter ({sigma}{sub LLP}) as well as two new parameters: annual number of system failures (f) and the standard deviation of annual number of system failures ({sigma}{sub f}). This paper therefore provides an analytical method for evaluating and sizing stand-alone PV systems with variable monthly demand and panel inclination. The sizing method has also been applied in a practical manner. (author)
Sensitivity of Mantel Haenszel Model and Rasch Model as Viewed From Sample Size
ALWI, IDRUS
2011-01-01
The aims of this research is to study the sensitivity comparison of Mantel Haenszel and Rasch Model for detection differential item functioning, observed from the sample size. These two differential item functioning (DIF) methods were compared using simulate binary item respon data sets of varying sample size, 200 and 400 examinees were used in the analyses, a detection method of differential item functioning (DIF) based on gender difference. These test conditions were replication 4 tim...
Bergtold, Jason S.; Yeager, Elizabeth A.; Featherstone, Allen M.
2011-01-01
The logistic regression models has been widely used in the social and natural sciences and results from studies using this model can have significant impact. Thus, confidence in the reliability of inferences drawn from these models is essential. The robustness of such inferences is dependent on sample size. The purpose of this study is to examine the impact of sample size on the mean estimated bias and efficiency of parameter estimation and inference for the logistic regression model. A numbe...
Grulke, Eric A.; Wu, Xiaochun; Ji, Yinglu; Buhr, Egbert; Yamamoto, Kazuhiro; Song, Nam Woong; Stefaniak, Aleksandr B.; Schwegler-Berry, Diane; Burchett, Woodrow W.; Lambert, Joshua; Stromberg, Arnold J.
2018-04-01
Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.
Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani
2015-01-01
This paper describes the importance of developing students' reasoning about samples and sampling variability as a foundation for statistical thinking. Research on expert-novice thinking as well as statistical thinking is reviewed and compared. A case is made that statistical thinking is a type of expert thinking, and as such, research…
Broberg, Per
2013-07-19
One major concern with adaptive designs, such as the sample size adjustable designs, has been the fear of inflating the type I error rate. In (Stat Med 23:1023-1038, 2004) it is however proven that when observations follow a normal distribution and the interim result show promise, meaning that the conditional power exceeds 50%, type I error rate is protected. This bound and the distributional assumptions may seem to impose undesirable restrictions on the use of these designs. In (Stat Med 30:3267-3284, 2011) the possibility of going below 50% is explored and a region that permits an increased sample size without inflation is defined in terms of the conditional power at the interim. A criterion which is implicit in (Stat Med 30:3267-3284, 2011) is derived by elementary methods and expressed in terms of the test statistic at the interim to simplify practical use. Mathematical and computational details concerning this criterion are exhibited. Under very general conditions the type I error rate is preserved under sample size adjustable schemes that permit a raise. The main result states that for normally distributed observations raising the sample size when the result looks promising, where the definition of promising depends on the amount of knowledge gathered so far, guarantees the protection of the type I error rate. Also, in the many situations where the test statistic approximately follows a normal law, the deviation from the main result remains negligible. This article provides details regarding the Weibull and binomial distributions and indicates how one may approach these distributions within the current setting. There is thus reason to consider such designs more often, since they offer a means of adjusting an important design feature at little or no cost in terms of error rate.
Sample size choices for XRCT scanning of highly unsaturated soil mixtures
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Smith Jonathan C.
2016-01-01
Full Text Available Highly unsaturated soil mixtures (clay, sand and gravel are used as building materials in many parts of the world, and there is increasing interest in understanding their mechanical and hydraulic behaviour. In the laboratory, x-ray computed tomography (XRCT is becoming more widely used to investigate the microstructures of soils, however a crucial issue for such investigations is the choice of sample size, especially concerning the scanning of soil mixtures where there will be a range of particle and void sizes. In this paper we present a discussion (centred around a new set of XRCT scans on sample sizing for scanning of samples comprising soil mixtures, where a balance has to be made between realistic representation of the soil components and the desire for high resolution scanning, We also comment on the appropriateness of differing sample sizes in comparison to sample sizes used for other geotechnical testing. Void size distributions for the samples are presented and from these some hypotheses are made as to the roles of inter- and intra-aggregate voids in the mechanical behaviour of highly unsaturated soils.
Rodríguez-Barranco, Miguel; Tobías, Aurelio; Redondo, Daniel; Molina-Portillo, Elena; Sánchez, María José
2017-03-17
Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables.
Impedance modulation and feedback corrections in tracking targets of variable size and frequency.
Selen, Luc P J; van Dieën, Jaap H; Beek, Peter J
2006-11-01
Humans are able to adjust the accuracy of their movements to the demands posed by the task at hand. The variability in task execution caused by the inherent noisiness of the neuromuscular system can be tuned to task demands by both feedforward (e.g., impedance modulation) and feedback mechanisms. In this experiment, we studied both mechanisms, using mechanical perturbations to estimate stiffness and damping as indices of impedance modulation and submovement scaling as an index of feedback driven corrections. Eight subjects tracked three differently sized targets (0.0135, 0.0270, and 0.0405 rad) moving at three different frequencies (0.20, 0.25, and 0.33 Hz). Movement variability decreased with both decreasing target size and movement frequency, whereas stiffness and damping increased with decreasing target size, independent of movement frequency. These results are consistent with the theory that mechanical impedance acts as a filter of noisy neuromuscular signals but challenge stochastic theories of motor control that do not account for impedance modulation and only partially for feedback control. Submovements during unperturbed cycles were quantified in terms of their gain, i.e., the slope between their duration and amplitude in the speed profile. Submovement gain decreased with decreasing movement frequency and increasing target size. The results were interpreted to imply that submovement gain is related to observed tracking errors and that those tracking errors are expressed in units of target size. We conclude that impedance and submovement gain modulation contribute additively to tracking accuracy.
Rao, M R P; Bajaj, A
2014-12-01
Telmisartan, an orally active nonpeptide angiotensin II receptor antagonist is a BCS Class II drug having aqueous solubility of 9.9 µg/ml and hence oral bioavailability of 40%. The present study involved preparation of nanosuspensions by evaporative antisolvent precipitation technique to improve the saturation solubility and dissolution rate of telmisartan. Various stabilizers such as TPGS, PVPK 30, PEG 6000 were investigated of which TPGS was found to provide maximum decrease in particle size and accord greater stability to the nanosuspensions. Box-Behnken design was used to investigate the effect of independent variables like stabilizer concentration, time and speed of stirring on particle size of nanosuspensions. Pharmacodynamic studies using Goldblatt technique were undertaken to evaluate the effect of nano-sizing on the hypotensive effect of the drug. Concentration of TPGS and speed of rotation were found to play an important role in particle size of the nanosuspensions whereas time of stirring displayed an exponential relationship with particle size. Freeze dried nanocrystals obtained from nanosuspension of least particle size were found to have increased saturation solubility of telmisartan in different dissolution media. The reconstituted nanosuspension was found to reduce both systolic and diastolic blood pressure without affecting pulse pressure and heart rate. Statistical tools can be used to identify key process and formulation parameters which play a significant role in controlling the particle size in nanosuspensions. © Georg Thieme Verlag KG Stuttgart · New York.
The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings.
Lorca-Puls, Diego L; Gajardo-Vidal, Andrea; White, Jitrachote; Seghier, Mohamed L; Leff, Alexander P; Green, David W; Crinion, Jenny T; Ludersdorfer, Philipp; Hope, Thomas M H; Bowman, Howard; Price, Cathy J
2018-07-01
This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.
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.
Sample Size for Tablet Compression and Capsule Filling Events During Process Validation.
Charoo, Naseem Ahmad; Durivage, Mark; Rahman, Ziyaur; Ayad, Mohamad Haitham
2017-12-01
During solid dosage form manufacturing, the uniformity of dosage units (UDU) is ensured by testing samples at 2 stages, that is, blend stage and tablet compression or capsule/powder filling stage. The aim of this work is to propose a sample size selection approach based on quality risk management principles for process performance qualification (PPQ) and continued process verification (CPV) stages by linking UDU to potential formulation and process risk factors. Bayes success run theorem appeared to be the most appropriate approach among various methods considered in this work for computing sample size for PPQ. The sample sizes for high-risk (reliability level of 99%), medium-risk (reliability level of 95%), and low-risk factors (reliability level of 90%) were estimated to be 299, 59, and 29, respectively. Risk-based assignment of reliability levels was supported by the fact that at low defect rate, the confidence to detect out-of-specification units would decrease which must be supplemented with an increase in sample size to enhance the confidence in estimation. Based on level of knowledge acquired during PPQ and the level of knowledge further required to comprehend process, sample size for CPV was calculated using Bayesian statistics to accomplish reduced sampling design for CPV. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
A normative inference approach for optimal sample sizes in decisions from experience
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
Rambo, Robert P
2017-01-01
The success of a SAXS experiment for structural investigations depends on two precise measurements, the sample and the buffer background. Buffer matching between the sample and background can be achieved using dialysis methods but in biological SAXS of monodisperse systems, sample preparation is routinely being performed with size exclusion chromatography (SEC). SEC is the most reliable method for SAXS sample preparation as the method not only purifies the sample for SAXS but also almost guarantees ideal buffer matching. Here, I will highlight the use of SEC for SAXS sample preparation and demonstrate using example proteins that SEC purification does not always provide for ideal samples. Scrutiny of the SEC elution peak using quasi-elastic and multi-angle light scattering techniques can reveal hidden features (heterogeneity) of the sample that should be considered during SAXS data analysis. In some cases, sample heterogeneity can be controlled using a small molecule additive and I outline a simple additive screening method for sample preparation.
Optimum sample size to estimate mean parasite abundance in fish parasite surveys
Directory of Open Access Journals (Sweden)
Shvydka S.
2018-03-01
Full Text Available To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI was based on the Bag of Little Bootstraps (BLB. The abundance of two species of monogenean parasites Ligophorus cephali and L. mediterraneus from Mugil cephalus across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i based on CIs width a reasonable precision level for the mean abundance in parasitological surveys of Ligophorus spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the CIs width, and ii the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.
Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz
2014-07-01
Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Method of MPPT Control Based on Power Variable Step-size in Photovoltaic Converter System
Directory of Open Access Journals (Sweden)
Xu Hui-xiang
2016-01-01
Full Text Available Since the disadvantage of traditional MPPT algorithms of variable step-size, proposed power tracking based on variable step-size with the advantage method of the constant-voltage and the perturb-observe (P&O[1-3]. The control strategy modify the problem of voltage fluctuation caused by perturb-observe method, at the same time, introducing the advantage of constant-voltage method and simplify the circuit topology. With the theoretical derivation, control the output power of photovoltaic modules to change the duty cycle of main switch. Achieve the maximum power stabilization output, reduce the volatility of energy loss effectively, and improve the inversion efficiency[3,4]. Given the result of experimental test based theoretical derivation and the curve of MPPT when the prototype work.
Fuel temperature prediction using a variable bypass gap size in the prismatic VHTR
International Nuclear Information System (INIS)
Lee, Sung Nam; Tak, Nam-il; Kim, Min Hwan
2016-01-01
Highlights: • The bypass flow of the prismatic very high temperature reactor is analyzed. • The bypass gap sizes are calculated considering the effect of the neutron fluences and thermal expansion. • The fuel hot spot temperature and temperature profiles are calculated using the variable gap size. • The BOC, MOC and EOC condition at the cycle 07 and 14 are applied. - Abstract: The temperature gradient and hot spot temperatures were calculated in the prismatic very high temperature reactor as a function of the variable bypass gap size. Many previous studies have predicted the temperature of the reactor core based on a fixed bypass gap size. The graphite matrix of the assemblies in the reactor core undergoes a dimensional change during the operation due to thermal expansion and neutron fluence. The expansion and shrinkage of the bypass gaps change the coolant flow fractions into the coolant channels, the control rod holes, and the bypass gaps. Therefore, the temperature of the assemblies may differ compared to those for the fixed bypass gap case. The temperature gradient and the hot spot temperatures are important for the design of reactor structures to ensure their safety and efficiency. In the present study, the temperature variation of the PMR200 is studied at the beginning (BOC), middle (MOC), and end (EOC) of cycles 07 and 14. CORONA code which has been developed in KAERI is applied to solve the thermal-hydraulics of the reactor core of the PMR200. CORONA solves a fluid region using a one-dimensional formulation and a solid region using a three-dimensional formulation to enhance the computational speed and still obtain a reasonable accuracy. The maximum temperatures in the fuel assemblies using the variable bypass gaps did not differ much from the corresponding temperatures using the fixed bypass gaps. However, the maximum temperatures in the reflector assemblies using the variable bypass gaps differ significantly from the corresponding temperatures
Generating Random Samples of a Given Size Using Social Security Numbers.
Erickson, Richard C.; Brauchle, Paul E.
1984-01-01
The purposes of this article are (1) to present a method by which social security numbers may be used to draw cluster samples of a predetermined size and (2) to describe procedures used to validate this method of drawing random samples. (JOW)
Page sample size in web accessibility testing: how many pages is enough?
Velleman, Eric Martin; van der Geest, Thea
2013-01-01
Various countries and organizations use a different sampling approach and sample size of web pages in accessibility conformance tests. We are conducting a systematic analysis to determine how many pages is enough for testing whether a website is compliant with standard accessibility guidelines. This
Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests
Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.
2015-01-01
The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…
Particle Sampling and Real Time Size Distribution Measurement in H2/O2/TEOS Diffusion Flame
International Nuclear Information System (INIS)
Ahn, K.H.; Jung, C.H.; Choi, M.; Lee, J.S.
2001-01-01
Growth characteristics of silica particles have been studied experimentally using in situ particle sampling technique from H 2 /O 2 /Tetraethylorthosilicate (TEOS) diffusion flame with carefully devised sampling probe. The particle morphology and the size comparisons are made between the particles sampled by the local thermophoretic method from the inside of the flame and by the electrostatic collector sampling method after the dilution sampling probe. The Transmission Electron Microscope (TEM) image processed data of these two sampling techniques are compared with Scanning Mobility Particle Sizer (SMPS) measurement. TEM image analysis of two sampling methods showed a good agreement with SMPS measurement. The effects of flame conditions and TEOS flow rates on silica particle size distributions are also investigated using the new particle dilution sampling probe. It is found that the particle size distribution characteristics and morphology are mostly governed by the coagulation process and sintering process in the flame. As the flame temperature increases, the effect of coalescence or sintering becomes an important particle growth mechanism which reduces the coagulation process. However, if the flame temperature is not high enough to sinter the aggregated particles then the coagulation process is a dominant particle growth mechanism. In a certain flame condition a secondary particle formation is observed which results in a bimodal particle size distribution
Directory of Open Access Journals (Sweden)
Michael Cusack
2013-02-01
Full Text Available This study focuses on the daily and seasonal variability of particle number size distributions and concentrations, performed at the Montseny (MSY regional background station in the western Mediterranean from October 2010 to June 2011. Particle number concentrations at MSY were shown to be within range of various other sites across Europe reported in literature, but the seasonality of the particle number size distributions revealed significant differences. The Aitken mode is the dominant particle mode at MSY, with arithmetic mean concentrations of 1698 cm3, followed by the accumulation mode (877 cm−3 and the nucleation mode (246 cm−3. Concentrations showed a strong seasonal variability with large increases in particle number concentrations observed from the colder to warmer months. The modality of median size distributions was typically bimodal, except under polluted conditions when the size distribution was unimodal. During the colder months, the daily variation of particle number size distributions are strongly influenced by a diurnal breeze system, whereby the Aitken and accumulation modes vary similarly to PM1 and BC mass concentrations, with nocturnal minima and sharp day-time increases owing to the development of a diurnal mountain breeze. Under clean air conditions, high levels of nucleation and lower Aitken mode concentrations were measured, highlighting the importance of new particle formation as a source of particles in the absence of a significant condensation sink. During the warmer months, nucleation mode concentrations were observed to be relatively elevated both under polluted and clean conditions due to increased photochemical reactions, with enhanced subsequent growth owing to elevated concentrations of condensable organic vapours produced from biogenic volatile organic compounds, indicating that nucleation at MSY does not exclusively occur under clean air conditions. Finally, mixing of air masses between polluted and non
Sample size calculation to externally validate scoring systems based on logistic regression models.
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Antonio Palazón-Bru
Full Text Available A sample size containing at least 100 events and 100 non-events has been suggested to validate a predictive model, regardless of the model being validated and that certain factors can influence calibration of the predictive model (discrimination, parameterization and incidence. Scoring systems based on binary logistic regression models are a specific type of predictive model.The aim of this study was to develop an algorithm to determine the sample size for validating a scoring system based on a binary logistic regression model and to apply it to a case study.The algorithm was based on bootstrap samples in which the area under the ROC curve, the observed event probabilities through smooth curves, and a measure to determine the lack of calibration (estimated calibration index were calculated. To illustrate its use for interested researchers, the algorithm was applied to a scoring system, based on a binary logistic regression model, to determine mortality in intensive care units.In the case study provided, the algorithm obtained a sample size with 69 events, which is lower than the value suggested in the literature.An algorithm is provided for finding the appropriate sample size to validate scoring systems based on binary logistic regression models. This could be applied to determine the sample size in other similar cases.
Precision of quantization of the hall conductivity in a finite-size sample: Power law
International Nuclear Information System (INIS)
Greshnov, A. A.; Kolesnikova, E. N.; Zegrya, G. G.
2006-01-01
A microscopic calculation of the conductivity in the integer quantum Hall effect (IQHE) mode is carried out. The precision of quantization is analyzed for finite-size samples. The precision of quantization shows a power-law dependence on the sample size. A new scaling parameter describing this dependence is introduced. It is also demonstrated that the precision of quantization linearly depends on the ratio between the amplitude of the disorder potential and the cyclotron energy. The data obtained are compared with the results of magnetotransport measurements in mesoscopic samples
Estimating search engine index size variability: a 9-year longitudinal study.
van den Bosch, Antal; Bogers, Toine; de Kunder, Maurice
One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel method of estimating the size of a Web search engine's index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing's indices over a nine-year period, from March 2006 until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find that much, if not all of this variability can be explained by changes in the indexing and ranking infrastructure of Google and Bing. This casts further doubt on whether Web search engines can be used reliably for cross-sectional webometric studies.
Constrained statistical inference: sample-size tables for ANOVA and regression
Directory of Open Access Journals (Sweden)
Leonard eVanbrabant
2015-01-01
Full Text Available Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient beta1 is larger than beta2 and beta3. The corresponding hypothesis is H: beta1 > {beta2, beta3} and this is known as an (order constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a smaller sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a prespecified power (say, 0.80 for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30% to 50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., beta1 > beta2 results in a higher power than assigning a positive or a negative sign to the parameters (e.g., beta1 > 0.
Johnson, Kenneth L.; White, K. Preston, Jr.
2012-01-01
The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.
A simple nomogram for sample size for estimating sensitivity and specificity of medical tests
Directory of Open Access Journals (Sweden)
Malhotra Rajeev
2010-01-01
Full Text Available Sensitivity and specificity measure inherent validity of a diagnostic test against a gold standard. Researchers develop new diagnostic methods to reduce the cost, risk, invasiveness, and time. Adequate sample size is a must to precisely estimate the validity of a diagnostic test. In practice, researchers generally decide about the sample size arbitrarily either at their convenience, or from the previous literature. We have devised a simple nomogram that yields statistically valid sample size for anticipated sensitivity or anticipated specificity. MS Excel version 2007 was used to derive the values required to plot the nomogram using varying absolute precision, known prevalence of disease, and 95% confidence level using the formula already available in the literature. The nomogram plot was obtained by suitably arranging the lines and distances to conform to this formula. This nomogram could be easily used to determine the sample size for estimating the sensitivity or specificity of a diagnostic test with required precision and 95% confidence level. Sample size at 90% and 99% confidence level, respectively, can also be obtained by just multiplying 0.70 and 1.75 with the number obtained for the 95% confidence level. A nomogram instantly provides the required number of subjects by just moving the ruler and can be repeatedly used without redoing the calculations. This can also be applied for reverse calculations. This nomogram is not applicable for testing of the hypothesis set-up and is applicable only when both diagnostic test and gold standard results have a dichotomous category.
Effects of sample size on robustness and prediction accuracy of a prognostic gene signature
Directory of Open Access Journals (Sweden)
Kim Seon-Young
2009-05-01
Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.
Gridsampler – A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies
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Mark Heckmann
2017-01-01
Full Text Available The repertory grid is a psychological data collection technique that is used to elicit qualitative data in the form of attributes as well as quantitative ratings. A common approach for evaluating multiple repertory grid data is sorting the elicited bipolar attributes (so called constructs into mutually exclusive categories by means of content analysis. An important question when planning this type of study is determining the sample size needed to a discover all attribute categories relevant to the field and b yield a predefined minimal number of attributes per category. For most applied researchers who collect multiple repertory grid data, programming a numeric simulation to answer these questions is not feasible. The gridsampler software facilitates determining the required sample size by providing a GUI for conducting the necessary numerical simulations. Researchers can supply a set of parameters suitable for the specific research situation, determine the required sample size, and easily explore the effects of changes in the parameter set.
Mulder, V.L.; Bruin, de S.; Schaepman, M.E.
2013-01-01
This paper presents a sparse, remote sensing-based sampling approach making use of conditioned Latin Hypercube Sampling (cLHS) to assess variability in soil properties at regional scale. The method optimizes the sampling scheme for a defined spatial population based on selected covariates, which are
Threshold-dependent sample sizes for selenium assessment with stream fish tissue
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
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
Overestimation of test performance by ROC analysis: Effect of small sample size
International Nuclear Information System (INIS)
Seeley, G.W.; Borgstrom, M.C.; Patton, D.D.; Myers, K.J.; Barrett, H.H.
1984-01-01
New imaging systems are often observer-rated by ROC techniques. For practical reasons the number of different images, or sample size (SS), is kept small. Any systematic bias due to small SS would bias system evaluation. The authors set about to determine whether the area under the ROC curve (AUC) would be systematically biased by small SS. Monte Carlo techniques were used to simulate observer performance in distinguishing signal (SN) from noise (N) on a 6-point scale; P(SN) = P(N) = .5. Four sample sizes (15, 25, 50 and 100 each of SN and N), three ROC slopes (0.8, 1.0 and 1.25), and three intercepts (0.8, 1.0 and 1.25) were considered. In each of the 36 combinations of SS, slope and intercept, 2000 runs were simulated. Results showed a systematic bias: the observed AUC exceeded the expected AUC in every one of the 36 combinations for all sample sizes, with the smallest sample sizes having the largest bias. This suggests that evaluations of imaging systems using ROC curves based on small sample size systematically overestimate system performance. The effect is consistent but subtle (maximum 10% of AUC standard deviation), and is probably masked by the s.d. in most practical settings. Although there is a statistically significant effect (F = 33.34, P<0.0001) due to sample size, none was found for either the ROC curve slope or intercept. Overestimation of test performance by small SS seems to be an inherent characteristic of the ROC technique that has not previously been described
Automated size-specific CT dose monitoring program: Assessing variability in CT dose
International Nuclear Information System (INIS)
Christianson, Olav; Li Xiang; Frush, Donald; Samei, Ehsan
2012-01-01
Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED adj ). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED adj between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED adj that differed by up to 44% from effective dose estimates that were not
Automated size-specific CT dose monitoring program: Assessing variability in CT dose
Energy Technology Data Exchange (ETDEWEB)
Christianson, Olav; Li Xiang; Frush, Donald; Samei, Ehsan [Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States) and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Department of Physics, Duke University, Durham, North Carolina 27710 (United States); and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708 (United States)
2012-11-15
Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED{sub adj}). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED{sub adj} between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED{sub adj} that differed by up to 44% from effective dose
Bayesian sample size determination for cost-effectiveness studies with censored data.
Directory of Open Access Journals (Sweden)
Daniel P Beavers
Full Text Available Cost-effectiveness models are commonly utilized to determine the combined clinical and economic impact of one treatment compared to another. However, most methods for sample size determination of cost-effectiveness studies assume fully observed costs and effectiveness outcomes, which presents challenges for survival-based studies in which censoring exists. We propose a Bayesian method for the design and analysis of cost-effectiveness data in which costs and effectiveness may be censored, and the sample size is approximated for both power and assurance. We explore two parametric models and demonstrate the flexibility of the approach to accommodate a variety of modifications to study assumptions.
International Nuclear Information System (INIS)
Jaech, J.L.; Lemaire, R.J.
1986-11-01
Generalized procedures have been developed to determine sample sizes in connection with the planning of inspection activities. These procedures are based on different measurement methods. They are applied mainly to Bulk Handling Facilities and Physical Inventory Verifications. The present report attempts (i) to assign to appropriate statistical testers (viz. testers for gross, partial and small defects) the measurement methods to be used, and (ii) to associate the measurement uncertainties with the sample sizes required for verification. Working papers are also provided to assist in the application of the procedures. This volume contains the detailed explanations concerning the above mentioned procedures
Sample size for post-marketing safety studies based on historical controls.
Wu, Yu-te; Makuch, Robert W
2010-08-01
As part of a drug's entire life cycle, post-marketing studies are an important part in the identification of rare, serious adverse events. Recently, the US Food and Drug Administration (FDA) has begun to implement new post-marketing safety mandates as a consequence of increased emphasis on safety. The purpose of this research is to provide exact sample size formula for the proposed hybrid design, based on a two-group cohort study with incorporation of historical external data. Exact sample size formula based on the Poisson distribution is developed, because the detection of rare events is our outcome of interest. Performance of exact method is compared to its approximate large-sample theory counterpart. The proposed hybrid design requires a smaller sample size compared to the standard, two-group prospective study design. In addition, the exact method reduces the number of subjects required in the treatment group by up to 30% compared to the approximate method for the study scenarios examined. The proposed hybrid design satisfies the advantages and rationale of the two-group design with smaller sample sizes generally required. 2010 John Wiley & Sons, Ltd.
Effect on spot welding variables on nugget size and bond strength of 304 austenitic stainless steel
International Nuclear Information System (INIS)
Charde, Nachimani
2012-01-01
Resistance spot welding (RSW) has revolutionized mechanical assembly in the automotive industry since its introduction in the early 1970s. Currently, one mechanical assembly in five is welded using spot welding technology, with welding of stainless steel sheet becoming increasingly common. Consequently, this research paper examines the spot welding of 2 mm thick 304 austenitic stainless steel sheet. The size of a spot weld nugget is primarily determined by the welding parameters: welding current, welding time, electrode force and electrode tip diameter However, other factors such as electrode deformation, corrosion, dissimilar materials and material properties also affect the nugget size and shape. This paper analyzes only the effects of current, weld time and force variations with unchanged electrode tip diameter. A pneumatically driven 75kVA spot welder was used to accomplish the welding process and the welded samples were subjected to tensile, hardness and metallurgical testing to characterize the size and shape of the weld nugget and the bond strength.
Directory of Open Access Journals (Sweden)
Sara M. Rodríguez
2017-08-01
Full Text Available Background Parasites are essential components of natural communities, but the factors that generate skewed distributions of parasite occurrences and abundances across host populations are not well understood. Methods Here, we analyse at a seascape scale the spatiotemporal relationships of parasite exposure and host body-size with the proportion of infected hosts (i.e., prevalence and aggregation of parasite burden across ca. 150 km of the coast and over 22 months. We predicted that the effects of parasite exposure on prevalence and aggregation are dependent on host body-sizes. We used an indirect host-parasite interaction in which migratory seagulls, sandy-shore molecrabs, and an acanthocephalan worm constitute the definitive hosts, intermediate hosts, and endoparasite, respectively. In such complex systems, increments in the abundance of definitive hosts imply increments in intermediate hosts’ exposure to the parasite’s dispersive stages. Results Linear mixed-effects models showed a significant, albeit highly variable, positive relationship between seagull density and prevalence. This relationship was stronger for small (cephalothorax length >15 mm than large molecrabs (<15 mm. Independently of seagull density, large molecrabs carried significantly more parasites than small molecrabs. The analysis of the variance-to-mean ratio of per capita parasite burden showed no relationship between seagull density and mean parasite aggregation across host populations. However, the amount of unexplained variability in aggregation was strikingly higher in larger than smaller intermediate hosts. This unexplained variability was driven by a decrease in the mean-variance scaling in heavily infected large molecrabs. Conclusions These results show complex interdependencies between extrinsic and intrinsic population attributes on the structure of host-parasite interactions. We suggest that parasite accumulation—a characteristic of indirect host
Rodríguez, Sara M; Valdivia, Nelson
2017-01-01
Parasites are essential components of natural communities, but the factors that generate skewed distributions of parasite occurrences and abundances across host populations are not well understood. Here, we analyse at a seascape scale the spatiotemporal relationships of parasite exposure and host body-size with the proportion of infected hosts (i.e., prevalence) and aggregation of parasite burden across ca. 150 km of the coast and over 22 months. We predicted that the effects of parasite exposure on prevalence and aggregation are dependent on host body-sizes. We used an indirect host-parasite interaction in which migratory seagulls, sandy-shore molecrabs, and an acanthocephalan worm constitute the definitive hosts, intermediate hosts, and endoparasite, respectively. In such complex systems, increments in the abundance of definitive hosts imply increments in intermediate hosts' exposure to the parasite's dispersive stages. Linear mixed-effects models showed a significant, albeit highly variable, positive relationship between seagull density and prevalence. This relationship was stronger for small (cephalothorax length >15 mm) than large molecrabs (analysis of the variance-to-mean ratio of per capita parasite burden showed no relationship between seagull density and mean parasite aggregation across host populations. However, the amount of unexplained variability in aggregation was strikingly higher in larger than smaller intermediate hosts. This unexplained variability was driven by a decrease in the mean-variance scaling in heavily infected large molecrabs. These results show complex interdependencies between extrinsic and intrinsic population attributes on the structure of host-parasite interactions. We suggest that parasite accumulation-a characteristic of indirect host-parasite interactions-and subsequent increasing mortality rates over ontogeny underpin size-dependent host-parasite dynamics.
International Nuclear Information System (INIS)
Bode, P.; Koster-Ammerlaan, M.J.J.
2018-01-01
Pragmatic rather than physical correction factors for neutron and gamma-ray shielding were studied for samples of intermediate size, i.e. up to the 10-100 gram range. It was found that for most biological and geological materials, the neutron self-shielding is less than 5 % and the gamma-ray self-attenuation can easily be estimated. A trueness control material of 1 kg size was made based on use of left-overs of materials, used in laboratory intercomparisons. A design study for a large sample pool-side facility, handling plate-type volumes, had to be stopped because of a reduction in human resources, available for this CRP. The large sample NAA facilities were made available to guest scientists from Greece and Brazil. The laboratory for neutron activation analysis participated in the world’s first laboratory intercomparison utilizing large samples. (author)
Performance Analysis of an Optical CDMA MAC Protocol With Variable-Size Sliding Window
Mohamed, Mohamed Aly A.; Shalaby, Hossam M. H.; Abdel-Moety El-Badawy, El-Sayed
2006-10-01
A media access control protocol for optical code-division multiple-access packet networks with variable length data traffic is proposed. This protocol exhibits a sliding window with variable size. A model for interference-level fluctuation and an accurate analysis for channel usage are presented. Both multiple-access interference (MAI) and photodetector's shot noise are considered. Both chip-level and correlation receivers are adopted. The system performance is evaluated using a traditional average system throughput and average delay. Finally, in order to enhance the overall performance, error control codes (ECCs) are applied. The results indicate that the performance can be enhanced to reach its peak using the ECC with an optimum number of correctable errors. Furthermore, chip-level receivers are shown to give much higher performance than that of correlation receivers. Also, it has been shown that MAI is the main source of signal degradation.
Chung, Kyong-Sook; Weber, Jaime A; Hipp, Andrew L
2011-01-01
High intraspecific cytogenetic variation in the sedge genus Carex (Cyperaceae) is hypothesized to be due to the "diffuse" or non-localized centromeres, which facilitate chromosome fission and fusion. If chromosome number changes are dominated by fission and fusion, then chromosome evolution will result primarily in changes in the potential for recombination among populations. Chromosome duplications, on the other hand, entail consequent opportunities for divergent evolution of paralogs. In this study, we evaluate whether genome size and chromosome number covary within species. We used flow cytometry to estimate genome sizes in Carex scoparia var. scoparia, sampling 99 plants (23 populations) in the Chicago region, and we used meiotic chromosome observations to document chromosome numbers and chromosome pairing relations. Chromosome numbers range from 2n = 62 to 2n = 68, and nuclear DNA 1C content from 0.342 to 0.361 pg DNA. Regressions of DNA content on chromosome number are nonsignificant for data analyzed by individual or population, and a regression model that excludes slope is favored over a model in which chromosome number predicts genome size. Chromosome rearrangements within cytogenetically variable Carex species are more likely a consequence of fission and fusion than of duplication and deletion. Moreover, neither genome size nor chromosome number is spatially autocorrelated, which suggests the potential for rapid chromosome evolution by fission and fusion at a relatively fine geographic scale (<350 km). These findings have important implications for ecological restoration and speciation within the largest angiosperm genus of the temperate zone.
Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun
2014-12-19
In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different
Uncertainty budget in internal monostandard NAA for small and large size samples analysis
International Nuclear Information System (INIS)
Dasari, K.B.; Acharya, R.
2014-01-01
Total uncertainty budget evaluation on determined concentration value is important under quality assurance programme. Concentration calculation in NAA or carried out by relative NAA and k0 based internal monostandard NAA (IM-NAA) method. IM-NAA method has been used for small and large sample analysis of clay potteries. An attempt was made to identify the uncertainty components in IM-NAA and uncertainty budget for La in both small and large size samples has been evaluated and compared. (author)
Directory of Open Access Journals (Sweden)
Esther Wong
Full Text Available We have developed a modified FlowCAM procedure for efficiently quantifying the size distribution of zooplankton. The modified method offers the following new features: 1 prevents animals from settling and clogging with constant bubbling in the sample container; 2 prevents damage to sample animals and facilitates recycling by replacing the built-in peristaltic pump with an external syringe pump, in order to generate negative pressure, creates a steady flow by drawing air from the receiving conical flask (i.e. vacuum pump, and transfers plankton from the sample container toward the main flowcell of the imaging system and finally into the receiving flask; 3 aligns samples in advance of imaging and prevents clogging with an additional flowcell placed ahead of the main flowcell. These modifications were designed to overcome the difficulties applying the standard FlowCAM procedure to studies where the number of individuals per sample is small, and since the FlowCAM can only image a subset of a sample. Our effective recycling procedure allows users to pass the same sample through the FlowCAM many times (i.e. bootstrapping the sample in order to generate a good size distribution. Although more advanced FlowCAM models are equipped with syringe pump and Field of View (FOV flowcells which can image all particles passing through the flow field; we note that these advanced setups are very expensive, offer limited syringe and flowcell sizes, and do not guarantee recycling. In contrast, our modifications are inexpensive and flexible. Finally, we compared the biovolumes estimated by automated FlowCAM image analysis versus conventional manual measurements, and found that the size of an individual zooplankter can be estimated by the FlowCAM image system after ground truthing.
Sample Size Bounding and Context Ranking as Approaches to the Human Error Quantification Problem
Energy Technology Data Exchange (ETDEWEB)
Reer, B
2004-03-01
The paper describes a technique denoted as Sub-Sample-Size Bounding (SSSB), which is useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications to human reliability analysis (HRA) are emphasised in the presentation of this technique. Exemplified by a sample of 180 abnormal event sequences, the manner in which SSSB can provide viable input for the quantification of errors of commission (EOCs) are outlined. (author)
Sample Size Bounding and Context Ranking as Approaches to the Human Error Quantification Problem
International Nuclear Information System (INIS)
Reer, B.
2004-01-01
The paper describes a technique denoted as Sub-Sample-Size Bounding (SSSB), which is useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications to human reliability analysis (HRA) are emphasised in the presentation of this technique. Exemplified by a sample of 180 abnormal event sequences, the manner in which SSSB can provide viable input for the quantification of errors of commission (EOCs) are outlined. (author)
The effect of short-range spatial variability on soil sampling uncertainty
Energy Technology Data Exchange (ETDEWEB)
Perk, Marcel van der [Department of Physical Geography, Utrecht University, P.O. Box 80115, 3508 TC Utrecht (Netherlands)], E-mail: m.vanderperk@geo.uu.nl; De Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria [Agenzia per la Protezione dell' Ambiente e per i Servizi Tecnici (APAT), Servizio Laboratori, Misure ed Attivita di Campo, Via di Castel Romano, 100-00128 Roma (Italy); Fajgelj, Ales; Sansone, Umberto [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-1400 Vienna (Austria); Jeran, Zvonka; Jacimovic, Radojko [Jozef Stefan Institute, Jamova 39, 1000 Ljubljana (Slovenia)
2008-11-15
This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.
The effect of short-range spatial variability on soil sampling uncertainty.
Van der Perk, Marcel; de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Sansone, Umberto; Jeran, Zvonka; Jaćimović, Radojko
2008-11-01
This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.
In vitro neutral detergent fiber (NDF) digestibility (NDFD) is an empirical measurement used to describe fermentability of NDF by rumen microbes. Variability is inherent in assays and affects the precision that can be expected for replicated samples. The study objective was to evaluate variability w...
Re-estimating sample size in cluster randomized trials with active recruitment within clusters
van Schie, Sander; Moerbeek, Mirjam
2014-01-01
Often only a limited number of clusters can be obtained in cluster randomised trials, although many potential participants can be recruited within each cluster. Thus, active recruitment is feasible within the clusters. To obtain an efficient sample size in a cluster randomised trial, the cluster
Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen
2017-01-01
Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.
Size Distributions and Characterization of Native and Ground Samples for Toxicology Studies
McKay, David S.; Cooper, Bonnie L.; Taylor, Larry A.
2010-01-01
This slide presentation shows charts and graphs that review the particle size distribution and characterization of natural and ground samples for toxicology studies. There are graphs which show the volume distribution versus the number distribution for natural occurring dust, jet mill ground dust, and ball mill ground dust.
Size-Resolved Penetration Through High-Efficiency Filter Media Typically Used for Aerosol Sampling
Czech Academy of Sciences Publication Activity Database
Zíková, Naděžda; Ondráček, Jakub; Ždímal, Vladimír
2015-01-01
Roč. 49, č. 4 (2015), s. 239-249 ISSN 0278-6826 R&D Projects: GA ČR(CZ) GBP503/12/G147 Institutional support: RVO:67985858 Keywords : filters * size-resolved penetration * atmospheric aerosol sampling Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.953, year: 2015
Sample Size Requirements for Assessing Statistical Moments of Simulated Crop Yield Distributions
Lehmann, N.; Finger, R.; Klein, T.; Calanca, P.
2013-01-01
Mechanistic crop growth models are becoming increasingly important in agricultural research and are extensively used in climate change impact assessments. In such studies, statistics of crop yields are usually evaluated without the explicit consideration of sample size requirements. The purpose of
The Effects of Test Length and Sample Size on Item Parameters in Item Response Theory
Sahin, Alper; Anil, Duygu
2017-01-01
This study investigates the effects of sample size and test length on item-parameter estimation in test development utilizing three unidimensional dichotomous models of item response theory (IRT). For this purpose, a real language test comprised of 50 items was administered to 6,288 students. Data from this test was used to obtain data sets of…
Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning
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.…
Umesh P. Agarwal; Sally A. Ralph; Carlos Baez; Richard S. Reiner; Steve P. Verrill
2017-01-01
Although X-ray diffraction (XRD) has been the most widely used technique to investigate crystallinity index (CrI) and crystallite size (L200) of cellulose materials, there are not many studies that have taken into account the role of sample moisture on these measurements. The present investigation focuses on a variety of celluloses and cellulose...
Sample size determination for disease prevalence studies with partially validated data.
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.
B-graph sampling to estimate the size of a hidden population
Spreen, M.; Bogaerts, S.
2015-01-01
Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is
Required sample size for monitoring stand dynamics in strict forest reserves: a case study
Diego Van Den Meersschaut; Bart De Cuyper; Kris Vandekerkhove; Noel Lust
2000-01-01
Stand dynamics in European strict forest reserves are commonly monitored using inventory densities of 5 to 15 percent of the total surface. The assumption that these densities guarantee a representative image of certain parameters is critically analyzed in a case study for the parameters basal area and stem number. The required sample sizes for different accuracy and...
A simple sample size formula for analysis of covariance in cluster randomized trials.
Teerenstra, S.; Eldridge, S.; Graff, M.J.; Hoop, E. de; Borm, G.F.
2012-01-01
For cluster randomized trials with a continuous outcome, the sample size is often calculated as if an analysis of the outcomes at the end of the treatment period (follow-up scores) would be performed. However, often a baseline measurement of the outcome is available or feasible to obtain. An
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
Krishnamoorthy, K.; Xia, Yanping
2008-01-01
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Estimating sample size for a small-quadrat method of botanical ...
African Journals Online (AJOL)
Reports the results of a study conducted to determine an appropriate sample size for a small-quadrat method of botanical survey for application in the Mixed Bushveld of South Africa. Species density and grass density were measured using a small-quadrat method in eight plant communities in the Nylsvley Nature Reserve.
[Sample size calculation in clinical post-marketing evaluation of traditional Chinese medicine].
Fu, Yingkun; Xie, Yanming
2011-10-01
In recent years, as the Chinese government and people pay more attention on the post-marketing research of Chinese Medicine, part of traditional Chinese medicine breed has or is about to begin after the listing of post-marketing evaluation study. In the post-marketing evaluation design, sample size calculation plays a decisive role. It not only ensures the accuracy and reliability of post-marketing evaluation. but also assures that the intended trials will have a desired power for correctly detecting a clinically meaningful difference of different medicine under study if such a difference truly exists. Up to now, there is no systemic method of sample size calculation in view of the traditional Chinese medicine. In this paper, according to the basic method of sample size calculation and the characteristic of the traditional Chinese medicine clinical evaluation, the sample size calculation methods of the Chinese medicine efficacy and safety are discussed respectively. We hope the paper would be beneficial to medical researchers, and pharmaceutical scientists who are engaged in the areas of Chinese medicine research.
International Nuclear Information System (INIS)
Sampson, T.E.
1991-01-01
Recent advances in segmented gamma scanning have emphasized software corrections for gamma-ray self-adsorption in particulates or lumps of special nuclear material in the sample. another feature of this software is an attenuation correction factor formalism that explicitly accounts for differences in sample container size and composition between the calibration standards and the individual items being measured. Software without this container-size correction produces biases when the unknowns are not packaged in the same containers as the calibration standards. This new software allows the use of different size and composition containers for standards and unknowns, as enormous savings considering the expense of multiple calibration standard sets otherwise needed. This paper presents calculations of the bias resulting from not using this new formalism. These calculations may be used to estimate bias corrections for segmented gamma scanners that do not incorporate these advanced concepts
Collection of size fractionated particulate matter sample for neutron activation analysis in Japan
International Nuclear Information System (INIS)
Otoshi, Tsunehiko; Nakamatsu, Hiroaki; Oura, Yasuji; Ebihara, Mitsuru
2004-01-01
According to the decision of the 2001 Workshop on Utilization of Research Reactor (Neutron Activation Analysis (NAA) Section), size fractionated particulate matter collection for NAA was started from 2002 at two sites in Japan. The two monitoring sites, ''Tokyo'' and ''Sakata'', were classified into ''urban'' and ''rural''. In each site, two size fractions, namely PM 2-10 '' and PM 2 '' particles (aerodynamic particle size between 2 to 10 micrometer and less than 2 micrometer, respectively) were collected every month on polycarbonate membrane filters. Average concentrations of PM 10 (sum of PM 2-10 and PM 2 samples) during the common sampling period of August to November 2002 in each site were 0.031mg/m 3 in Tokyo, and 0.022mg/m 3 in Sakata. (author)
Jonell, T. N.; Li, Y.; Blusztajn, J.; Giosan, L.; Clift, P. D.
2017-12-01
Rare earth element (REE) radioisotope systems, such as neodymium (Nd), have been traditionally used as powerful tracers of source provenance, chemical weathering intensity, and sedimentary processes over geologic timescales. More recently, the effects of physical fractionation (hydraulic sorting) of sediments during transport have called into question the utility of Nd isotopes as a provenance tool. Is source terrane Nd provenance resolvable if sediment transport strongly induces noise? Can grain-size sorting effects be quantified? This study works to address such questions by utilizing grain size analysis, trace element geochemistry, and Nd isotope geochemistry of bulk and grain-size fractions (Pakistan. Here we evaluate how grain size effects drive Nd isotope variability and further resolve the total uncertainties associated with Nd isotope compositions of bulk sediments. Results from the Indus delta indicate bulk sediment ɛNd compositions are most similar to the <63 µm fraction as a result of strong mineralogical control on bulk compositions by silt- to clay-sized monazite and/or allanite. Replicate analyses determine that the best reproducibility (± 0.15 ɛNd points) is observed in the 125-250 µm fraction. The bulk and finest fractions display the worst reproducibility (±0.3 ɛNd points). Standard deviations (2σ) indicate that bulk sediment uncertainties are no more than ±1.0 ɛNd points. This argues that excursions of ≥1.0 ɛNd points in any bulk Indus delta sediments must in part reflect an external shift in provenance irrespective of sample composition, grain size, and grain size distribution. Sample standard deviations (2s) estimate that any terrigenous bulk sediment composition should vary no greater than ±1.1 ɛNd points if provenance remains constant. Findings from this study indicate that although there are grain-size dependent Nd isotope effects, they are minimal in the Indus delta such that resolvable provenance-driven trends can be
Support vector regression to predict porosity and permeability: Effect of sample size
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
Sample-size effects in fast-neutron gamma-ray production measurements: solid-cylinder samples
International Nuclear Information System (INIS)
Smith, D.L.
1975-09-01
The effects of geometry, absorption and multiple scattering in (n,Xγ) reaction measurements with solid-cylinder samples are investigated. Both analytical and Monte-Carlo methods are employed in the analysis. Geometric effects are shown to be relatively insignificant except in definition of the scattering angles. However, absorption and multiple-scattering effects are quite important; accurate microscopic differential cross sections can be extracted from experimental data only after a careful determination of corrections for these processes. The results of measurements performed using several natural iron samples (covering a wide range of sizes) confirm validity of the correction procedures described herein. It is concluded that these procedures are reliable whenever sufficiently accurate neutron and photon cross section and angular distribution information is available for the analysis. (13 figures, 5 tables) (auth)
In Situ Sampling of Relative Dust Devil Particle Loads and Their Vertical Grain Size Distributions.
Raack, Jan; Reiss, Dennis; Balme, Matthew R; Taj-Eddine, Kamal; Ori, Gian Gabriele
2017-04-19
During a field campaign in the Sahara Desert in southern Morocco, spring 2012, we sampled the vertical grain size distribution of two active dust devils that exhibited different dimensions and intensities. With these in situ samples of grains in the vortices, it was possible to derive detailed vertical grain size distributions and measurements of the lifted relative particle load. Measurements of the two dust devils show that the majority of all lifted particles were only lifted within the first meter (∼46.5% and ∼61% of all particles; ∼76.5 wt % and ∼89 wt % of the relative particle load). Furthermore, ∼69% and ∼82% of all lifted sand grains occurred in the first meter of the dust devils, indicating the occurrence of "sand skirts." Both sampled dust devils were relatively small (∼15 m and ∼4-5 m in diameter) compared to dust devils in surrounding regions; nevertheless, measurements show that ∼58.5% to 73.5% of all lifted particles were small enough to go into suspension (grain size classification). This relatively high amount represents only ∼0.05 to 0.15 wt % of the lifted particle load. Larger dust devils probably entrain larger amounts of fine-grained material into the atmosphere, which can have an influence on the climate. Furthermore, our results indicate that the composition of the surface, on which the dust devils evolved, also had an influence on the particle load composition of the dust devil vortices. The internal particle load structure of both sampled dust devils was comparable related to their vertical grain size distribution and relative particle load, although both dust devils differed in their dimensions and intensities. A general trend of decreasing grain sizes with height was also detected. Key Words: Mars-Dust devils-Planetary science-Desert soils-Atmosphere-Grain sizes. Astrobiology 17, xxx-xxx.
A chaos wolf optimization algorithm with self-adaptive variable step-size
Directory of Open Access Journals (Sweden)
Yong Zhu
2017-10-01
Full Text Available To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as “winner-take-all” and the update mechanism as “survival of the fittest” were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.
A chaos wolf optimization algorithm with self-adaptive variable step-size
Zhu, Yong; Jiang, Wanlu; Kong, Xiangdong; Quan, Lingxiao; Zhang, Yongshun
2017-10-01
To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA) with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as "winner-take-all" and the update mechanism as "survival of the fittest" were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.
Retention and variability of hydrogen (H2) samples stored in plastic syringes
DEFF Research Database (Denmark)
Rumessen, J J; Gudmand-Høyer, E
1987-01-01
The utility of two brands of 20 ml plastic syringes for storage of hydrogen (H2) samples as obtained in H2 breath tests were studied. Plastipak syringes were found to be significantly better with regard to the stability of the H2 concentration and the variability between the H2 samples. Storage...... of the H2 samples in Plastipak syringes at 5 degrees C significantly improved the H2 retention, whereas refrigeration of H2 samples stored in Once syringes did not reduce H2 loss. Storage of H2 samples in refrigerated plastic syringes is efficient and reliable for several days if syringes with minimal...... sample variation are used....
The impact of sample size and marker selection on the study of haplotype structures
Directory of Open Access Journals (Sweden)
Sun Xiao
2004-03-01
Full Text Available Abstract Several studies of haplotype structures in the human genome in various populations have found that the human chromosomes are structured such that each chromosome can be divided into many blocks, within which there is limited haplotype diversity. In addition, only a few genetic markers in a putative block are needed to capture most of the diversity within a block. There has been no systematic empirical study of the effects of sample size and marker set on the identified block structures and representative marker sets, however. The purpose of this study was to conduct a detailed empirical study to examine such impacts. Towards this goal, we have analysed three representative autosomal regions from a large genome-wide study of haplotypes with samples consisting of African-Americans and samples consisting of Japanese and Chinese individuals. For both populations, we have found that the sample size and marker set have significant impact on the number of blocks and the total number of representative markers identified. The marker set in particular has very strong impacts, and our results indicate that the marker density in the original datasets may not be adequate to allow a meaningful characterisation of haplotype structures. In general, we conclude that we need a relatively large sample size and a very dense marker panel in the study of haplotype structures in human populations.
Size selective isocyanate aerosols personal air sampling using porous plastic foams
International Nuclear Information System (INIS)
Cong Khanh Huynh; Trinh Vu Duc
2009-01-01
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.
Directory of Open Access Journals (Sweden)
Daniel Vasiliu
Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.
Maruyama, Takeo; Kimura, Motoo
1980-01-01
If a population (species) consists of n haploid lines (subpopulations) which reproduce asexually and each of which is subject to random extinction and subsequent replacement, it is shown that, at equilibrium in which mutational production of new alleles and their random extinction balance each other, the genetic diversity (1 minus the sum of squares of allelic frequencies) is given by 2Nev/(1 + 2Nev), where [Formula: see text] in which Ñ is the harmonic mean of the population size per line, n is the number of lines (assumed to be large), λ is the rate of line extinction, and v is the mutation rate (assuming the infinite neutral allele model). In a diploid population (species) consisting of n colonies, if migration takes place between colonies at the rate m (the island model) in addition to extinction and recolonization of colonies, it is shown that effective population size is [Formula: see text] If the rate of colony extinction (λ) is much larger than the migration rate of individuals, the effective population size is greatly reduced compared with the case in which no colony extinctions occur (in which case Ne = nÑ). The stepping-stone type of recolonization scheme is also considered. Bearing of these results on the interpretation of the level of genetic variability at the enzyme level observed in natural populations is discussed from the standpoint of the neutral mutation-random drift hypothesis. PMID:16592920
PIXE–PIGE analysis of size-segregated aerosol samples from remote areas
Energy Technology Data Exchange (ETDEWEB)
Calzolai, G., E-mail: calzolai@fi.infn.it [Department of Physics and Astronomy, University of Florence and National Institute of Nuclear Physics (INFN), Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Chiari, M.; Lucarelli, F.; Nava, S.; Taccetti, F. [Department of Physics and Astronomy, University of Florence and National Institute of Nuclear Physics (INFN), Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Becagli, S.; Frosini, D.; Traversi, R.; Udisti, R. [Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino (Italy)
2014-01-01
The chemical characterization of size-segregated samples is helpful to study the aerosol effects on both human health and environment. The sampling with multi-stage cascade impactors (e.g., Small Deposit area Impactor, SDI) produces inhomogeneous samples, with a multi-spot geometry and a non-negligible particle stratification. At LABEC (Laboratory of nuclear techniques for the Environment and the Cultural Heritage), an external beam line is fully dedicated to PIXE–PIGE analysis of aerosol samples. PIGE is routinely used as a sidekick of PIXE to correct the underestimation of PIXE in quantifying the concentration of the lightest detectable elements, like Na or Al, due to X-ray absorption inside the individual aerosol particles. In this work PIGE has been used to study proper attenuation correction factors for SDI samples: relevant attenuation effects have been observed also for stages collecting smaller particles, and consequent implications on the retrieved aerosol modal structure have been evidenced.
Li, Huili; Ostermann, Anne; Karunarathna, Samantha C; Xu, Jianchu; Hyde, Kevin D; Mortimer, Peter E
2018-07-01
The species-area relationship is an important factor in the study of species diversity, conservation biology, and landscape ecology. A deeper understanding of this relationship is necessary, in order to provide recommendations on how to improve the quality of data collection on macrofungal diversity in different land use systems in future studies, a systematic assessment of methodological parameters, in particular optimal plot sizes. The species-area relationship of macrofungi in tropical and temperate climatic zones and four different land use systems were investigated by determining the macrofungal species richness in plot sizes ranging from 100 m 2 to 10 000 m 2 over two sampling seasons. We found that the effect of plot size on recorded species richness significantly differed between land use systems with the exception of monoculture systems. For both climate zones, land use system needs to be considered when determining optimal plot size. Using an optimal plot size was more important than temporal replication (over two sampling seasons) in accurately recording species richness. Copyright © 2018 British Mycological Society. Published by Elsevier Ltd. All rights reserved.
GY SAMPLING THEORY AND GEOSTATISTICS: ALTERNATE MODELS OF VARIABILITY IN CONTINUOUS MEDIA
In the sampling theory developed by Pierre Gy, sample variability is modeled as the sum of a set of seven discrete error components. The variogram used in geostatisties provides an alternate model in which several of Gy's error components are combined in a continuous mode...
Sources of variability among replicate samples separated by two-dimensional gel electrophoresis.
Bland, Alison M; Janech, Michael G; Almeida, Jonas S; Arthur, John M
2010-04-01
Two-dimensional gel electrophoresis (2DE) offers high-resolution separation for intact proteins. However, variability in the appearance of spots can limit the ability to identify true differences between conditions. Variability can occur at a number of levels. Individual samples can differ because of biological variability. Technical variability can occur during protein extraction, processing, or storage. Another potential source of variability occurs during analysis of the gels and is not a result of any of the causes of variability named above. We performed a study designed to focus only on the variability caused by analysis. We separated three aliquots of rat left ventricle and analyzed differences in protein abundance on the replicate 2D gels. As the samples loaded on each gel were identical, differences in protein abundance are caused by variability in separation or interpretation of the gels. Protein spots were compared across gels by quantile values to determine differences. Fourteen percent of spots had a maximum difference in intensity of 0.4 quantile values or more between replicates. We then looked individually at the spots to determine the cause of differences between the measured intensities. Reasons for differences were: failure to identify a spot (59%), differences in spot boundaries (13%), difference in the peak height (6%), and a combination of these factors (21). This study demonstrates that spot identification and characterization make major contributions to variability seen with 2DE. Methods to highlight why measured protein spot abundance is different could reduce these errors.
Passive samplers deployed at 25 sites for three week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles deter...
Galbraith, Niall D; Manktelow, Ken I; Morris, Neil G
2010-11-01
Previous studies demonstrate that people high in delusional ideation exhibit a data-gathering bias on inductive reasoning tasks. The current study set out to investigate the factors that may underpin such a bias by examining healthy individuals, classified as either high or low scorers on the Peters et al. Delusions Inventory (PDI). More specifically, whether high PDI scorers have a relatively poor appreciation of sample size and heterogeneity when making statistical judgments. In Expt 1, high PDI scorers made higher probability estimates when generalizing from a sample of 1 with regard to the heterogeneous human property of obesity. In Expt 2, this effect was replicated and was also observed in relation to the heterogeneous property of aggression. The findings suggest that delusion-prone individuals are less appreciative of the importance of sample size when making statistical judgments about heterogeneous properties; this may underpin the data gathering bias observed in previous studies. There was some support for the hypothesis that threatening material would exacerbate high PDI scorers' indifference to sample size.
Evaluation of Approaches to Analyzing Continuous Correlated Eye Data When Sample Size Is Small.
Huang, Jing; Huang, Jiayan; Chen, Yong; Ying, Gui-Shuang
2018-02-01
To evaluate the performance of commonly used statistical methods for analyzing continuous correlated eye data when sample size is small. We simulated correlated continuous data from two designs: (1) two eyes of a subject in two comparison groups; (2) two eyes of a subject in the same comparison group, under various sample size (5-50), inter-eye correlation (0-0.75) and effect size (0-0.8). Simulated data were analyzed using paired t-test, two sample t-test, Wald test and score test using the generalized estimating equations (GEE) and F-test using linear mixed effects model (LMM). We compared type I error rates and statistical powers, and demonstrated analysis approaches through analyzing two real datasets. In design 1, paired t-test and LMM perform better than GEE, with nominal type 1 error rate and higher statistical power. In design 2, no test performs uniformly well: two sample t-test (average of two eyes or a random eye) achieves better control of type I error but yields lower statistical power. In both designs, the GEE Wald test inflates type I error rate and GEE score test has lower power. When sample size is small, some commonly used statistical methods do not perform well. Paired t-test and LMM perform best when two eyes of a subject are in two different comparison groups, and t-test using the average of two eyes performs best when the two eyes are in the same comparison group. When selecting the appropriate analysis approach the study design should be considered.
Variable-temperature sample system for ion implantation at -192 to +5000C
International Nuclear Information System (INIS)
Fuller, C.T.
1978-04-01
A variable-temperature sample system based on exchange-gas coupling was developed for ion-implantation use. The sample temperature can be controlled from -192 0 C to +500 0 C with rapid cooling. The system also has provisions for focusing and alignment of the ion beam, electron suppression, temperature monitoring, sample current measuring, and cryo-shielding. Design considerations and operating characteristics are discussed. 5 figures
Di Franco, Antonio; Bulleri, Fabio; Pennetta, Antonio; De Benedetto, Giuseppe; Clarke, K Robert; Guidetti, Paolo
2014-01-01
Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the
Modified strip packing heuristics for the rectangular variable-sized bin packing problem
Directory of Open Access Journals (Sweden)
FG Ortmann
2010-06-01
Full Text Available Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP and the variable-sized bin packing problem (VSBPP. A total of 252 strip packing heuristics (and variations thereof from the literature, as well as novel heuristics proposed by the authors, are compared statistically by means of 1170 SPP benchmark instances in order to identify the best heuristics in various classes. A combination of new heuristics with a new sorting method yields the best results. These heuristics are combined with a previous heuristic for the VSBPP by the authors to find good feasible solutions to 1357 VSBPP benchmark instances. This is the largest statistical comparison of algorithms for the SPP and the VSBPP to the best knowledge of the authors.
Crystallite size variation of TiO_2 samples depending time heat treatment
International Nuclear Information System (INIS)
Galante, A.G.M.; Paula, F.R. de; Montanhera, M.A.; Pereira, E.A.; Spada, E.R.
2016-01-01
Titanium dioxide (TiO_2) is an oxide semiconductor that may be found in mixed phase or in distinct phases: brookite, anatase and rutile. In this work was carried out the study of the residence time influence at a given temperature in the TiO_2 powder physical properties. After the powder synthesis, the samples were divided and heat treated at 650 °C with a ramp up to 3 °C/min and a residence time ranging from 0 to 20 hours and subsequently characterized by x-ray diffraction. Analyzing the obtained diffraction patterns, it was observed that, from 5-hour residence time, began the two-distinct phase coexistence: anatase and rutile. It also calculated the average crystallite size of each sample. The results showed an increase in average crystallite size with increasing residence time of the heat treatment. (author)
The study of the sample size on the transverse magnetoresistance of bismuth nanowires
International Nuclear Information System (INIS)
Zare, M.; Layeghnejad, R.; Sadeghi, E.
2012-01-01
The effects of sample size on the galvanomagnetice properties of semimetal nanowires are theoretically investigated. Transverse magnetoresistance (TMR) ratios have been calculated within a Boltzmann Transport Equation (BTE) approach by specular reflection approximation. Temperature and radius dependence of the transverse magnetoresistance of cylindrical Bismuth nanowires are given. The obtained values are in good agreement with the experimental results, reported by Heremans et al. - Highlights: ► In this study effects of sample size on the galvanomagnetic properties of Bi. ► Nanowires were explained by Parrott theorem by solving the Boltzmann Transport Equation. ► Transverse magnetoresistance (TMR) ratios have been measured by specular reflection approximation. ► Temperature and radius dependence of the transverse magnetoresistance of cylindrical Bismuth nanowires are given. ► The obtained values are in good agreement with the experimental results, reported by Heremans et al.
Evaluating the performance of species richness estimators: sensitivity to sample grain size
DEFF Research Database (Denmark)
Hortal, Joaquín; Borges, Paulo A. V.; Gaspar, Clara
2006-01-01
and several recent estimators [proposed by Rosenzweig et al. (Conservation Biology, 2003, 17, 864-874), and Ugland et al. (Journal of Animal Ecology, 2003, 72, 888-897)] performed poorly. 3. Estimations developed using the smaller grain sizes (pair of traps, traps, records and individuals) presented similar....... Data obtained with standardized sampling of 78 transects in natural forest remnants of five islands were aggregated in seven different grains (i.e. ways of defining a single sample): islands, natural areas, transects, pairs of traps, traps, database records and individuals to assess the effect of using...
A contemporary decennial global Landsat sample of changing agricultural field sizes
White, Emma; Roy, David
2014-05-01
Agriculture has caused significant human induced Land Cover Land Use (LCLU) change, with dramatic cropland expansion in the last century and significant increases in productivity over the past few decades. Satellite data have been used for agricultural applications including cropland distribution mapping, crop condition monitoring, crop production assessment and yield prediction. Satellite based agricultural applications are less reliable when the sensor spatial resolution is small relative to the field size. However, to date, studies of agricultural field size distributions and their change have been limited, even though this information is needed to inform the design of agricultural satellite monitoring systems. Moreover, the size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLU change. In many parts of the world field sizes may have increased. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, and impacts on the diffusion of herbicides, pesticides, disease pathogens, and pests. The Landsat series of satellites provide the longest record of global land observations, with 30m observations available since 1982. Landsat data are used to examine contemporary field size changes in a period (1980 to 2010) when significant global agricultural changes have occurred. A multi-scale sampling approach is used to locate global hotspots of field size change by examination of a recent global agricultural yield map and literature review. Nine hotspots are selected where significant field size change is apparent and where change has been driven by technological advancements (Argentina and U.S.), abrupt societal changes (Albania and Zimbabwe), government land use and agricultural policy changes (China, Malaysia, Brazil), and/or constrained by
Sample sizing of biological materials analyzed by energy dispersion X-ray fluorescence
International Nuclear Information System (INIS)
Paiva, Jose D.S.; Franca, Elvis J.; Magalhaes, Marcelo R.L.; Almeida, Marcio E.S.; Hazin, Clovis A.
2013-01-01
Analytical portions used in chemical analyses are usually less than 1g. Errors resulting from the sampling are barely evaluated, since this type of study is a time-consuming procedure, with high costs for the chemical analysis of large number of samples. The energy dispersion X-ray fluorescence - EDXRF is a non-destructive and fast analytical technique with the possibility of determining several chemical elements. Therefore, the aim of this study was to provide information on the minimum analytical portion for quantification of chemical elements in biological matrices using EDXRF. Three species were sampled in mangroves from the Pernambuco, Brazil. Tree leaves were washed with distilled water, oven-dried at 60 deg C and milled until 0.5 mm particle size. Ten test-portions of approximately 500 mg for each species were transferred to vials sealed with polypropylene film. The quality of the analytical procedure was evaluated from the reference materials IAEA V10 Hay Powder, SRM 2976 Apple Leaves. After energy calibration, all samples were analyzed under vacuum for 100 seconds for each group of chemical elements. The voltage used was 15 kV and 50 kV for chemical elements of atomic number lower than 22 and the others, respectively. For the best analytical conditions, EDXRF was capable of estimating the sample size uncertainty for further determination of chemical elements in leaves. (author)
Sample sizing of biological materials analyzed by energy dispersion X-ray fluorescence
Energy Technology Data Exchange (ETDEWEB)
Paiva, Jose D.S.; Franca, Elvis J.; Magalhaes, Marcelo R.L.; Almeida, Marcio E.S.; Hazin, Clovis A., E-mail: dan-paiva@hotmail.com, E-mail: ejfranca@cnen.gov.br, E-mail: marcelo_rlm@hotmail.com, E-mail: maensoal@yahoo.com.br, E-mail: chazin@cnen.gov.b [Centro Regional de Ciencias Nucleares do Nordeste (CRCN-NE/CNEN-PE), Recife, PE (Brazil)
2013-07-01
Analytical portions used in chemical analyses are usually less than 1g. Errors resulting from the sampling are barely evaluated, since this type of study is a time-consuming procedure, with high costs for the chemical analysis of large number of samples. The energy dispersion X-ray fluorescence - EDXRF is a non-destructive and fast analytical technique with the possibility of determining several chemical elements. Therefore, the aim of this study was to provide information on the minimum analytical portion for quantification of chemical elements in biological matrices using EDXRF. Three species were sampled in mangroves from the Pernambuco, Brazil. Tree leaves were washed with distilled water, oven-dried at 60 deg C and milled until 0.5 mm particle size. Ten test-portions of approximately 500 mg for each species were transferred to vials sealed with polypropylene film. The quality of the analytical procedure was evaluated from the reference materials IAEA V10 Hay Powder, SRM 2976 Apple Leaves. After energy calibration, all samples were analyzed under vacuum for 100 seconds for each group of chemical elements. The voltage used was 15 kV and 50 kV for chemical elements of atomic number lower than 22 and the others, respectively. For the best analytical conditions, EDXRF was capable of estimating the sample size uncertainty for further determination of chemical elements in leaves. (author)
International Nuclear Information System (INIS)
Haugboel, Steven; Pinborg, Lars H.; Arfan, Haroon M.; Froekjaer, Vibe M.; Svarer, Claus; Knudsen, Gitte M.; Madsen, Jacob; Dyrby, Tim B.
2007-01-01
To determine the reproducibility of measurements of brain 5-HT 2A receptors with an [ 18 F]altanserin PET bolus/infusion approach. Further, to estimate the sample size needed to detect regional differences between two groups and, finally, to evaluate how partial volume correction affects reproducibility and the required sample size. For assessment of the variability, six subjects were investigated with [ 18 F]altanserin PET twice, at an interval of less than 2 weeks. The sample size required to detect a 20% difference was estimated from [ 18 F]altanserin PET studies in 84 healthy subjects. Regions of interest were automatically delineated on co-registered MR and PET images. In cortical brain regions with a high density of 5-HT 2A receptors, the outcome parameter (binding potential, BP 1 ) showed high reproducibility, with a median difference between the two group measurements of 6% (range 5-12%), whereas in regions with a low receptor density, BP 1 reproducibility was lower, with a median difference of 17% (range 11-39%). Partial volume correction reduced the variability in the sample considerably. The sample size required to detect a 20% difference in brain regions with high receptor density is approximately 27, whereas for low receptor binding regions the required sample size is substantially higher. This study demonstrates that [ 18 F]altanserin PET with a bolus/infusion design has very low variability, particularly in larger brain regions with high 5-HT 2A receptor density. Moreover, partial volume correction considerably reduces the sample size required to detect regional changes between groups. (orig.)
Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.
2011-12-01
The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.
BROAD ABSORPTION LINE VARIABILITY ON MULTI-YEAR TIMESCALES IN A LARGE QUASAR SAMPLE
Energy Technology Data Exchange (ETDEWEB)
Filiz Ak, N.; Brandt, W. N.; Schneider, D. P. [Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States); Hall, P. B. [Department of Physics and Astronomy, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3 (Canada); Anderson, S. F. [Astronomy Department, University of Washington, Seattle, WA 98195 (United States); Hamann, F. [Department of Astronomy, University of Florida, Gainesville, FL 32611-2055 (United States); Lundgren, B. F. [Department of Astronomy, University of Wisconsin, Madison, WI 53706 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Pâris, I. [Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago (Chile); Petitjean, P. [Universite Paris 6, Institut d' Astrophysique de Paris, 75014, Paris (France); Ross, Nicholas P. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 92420 (United States); Shen, Yue [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., MS-51, Cambridge, MA 02138 (United States); York, Don, E-mail: nfilizak@astro.psu.edu [The University of Chicago, Department of Astronomy and Astrophysics, Chicago, IL 60637 (United States)
2013-11-10
We present a detailed investigation of the variability of 428 C IV and 235 Si IV broad absorption line (BAL) troughs identified in multi-epoch observations of 291 quasars by the Sloan Digital Sky Survey-I/II/III. These observations primarily sample rest-frame timescales of 1-3.7 yr over which significant rearrangement of the BAL wind is expected. We derive a number of observational results on, e.g., the frequency of BAL variability, the velocity range over which BAL variability occurs, the primary observed form of BAL-trough variability, the dependence of BAL variability upon timescale, the frequency of BAL strengthening versus weakening, correlations between BAL variability and BAL-trough profiles, relations between C IV and Si IV BAL variability, coordinated multi-trough variability, and BAL variations as a function of quasar properties. We assess implications of these observational results for quasar winds. Our results support models where most BAL absorption is formed within an order-of-magnitude of the wind-launching radius, although a significant minority of BAL troughs may arise on larger scales. We estimate an average lifetime for a BAL trough along our line-of-sight of a few thousand years. BAL disappearance and emergence events appear to be extremes of general BAL variability, rather than being qualitatively distinct phenomena. We derive the parameters of a random-walk model for BAL EW variability, finding that this model can acceptably describe some key aspects of EW variability. The coordinated trough variability of BAL quasars with multiple troughs suggests that changes in 'shielding gas' may play a significant role in driving general BAL variability.
Gridsampler – A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies
Heckmann, Mark; Burk, Lukas
2017-01-01
The repertory grid is a psychological data collection technique that is used to elicit qualitative data in the form of attributes as well as quantitative ratings. A common approach for evaluating multiple repertory grid data is sorting the elicited bipolar attributes (so called constructs) into mutually exclusive categories by means of content analysis. An important question when planning this type of study is determining the sample size needed to a) discover all attribute categories relevant...
Short time-scale optical variability properties of the largest AGN sample observed with Kepler/K2
Aranzana, E.; Körding, E.; Uttley, P.; Scaringi, S.; Bloemen, S.
2018-05-01
We present the first short time-scale (˜hours to days) optical variability study of a large sample of active galactic nuclei (AGNs) observed with the Kepler/K2 mission. The sample contains 252 AGN observed over four campaigns with ˜30 min cadence selected from the Million Quasar Catalogue with R magnitude <19. We performed time series analysis to determine their variability properties by means of the power spectral densities (PSDs) and applied Monte Carlo techniques to find the best model parameters that fit the observed power spectra. A power-law model is sufficient to describe all the PSDs of our sample. A variety of power-law slopes were found indicating that there is not a universal slope for all AGNs. We find that the rest-frame amplitude variability in the frequency range of 6 × 10-6-10-4 Hz varies from 1to10 per cent with an average of 1.7 per cent. We explore correlations between the variability amplitude and key parameters of the AGN, finding a significant correlation of rest-frame short-term variability amplitude with redshift. We attribute this effect to the known `bluer when brighter' variability of quasars combined with the fixed bandpass of Kepler data. This study also enables us to distinguish between Seyferts and blazars and confirm AGN candidates. For our study, we have compared results obtained from light curves extracted using different aperture sizes and with and without detrending. We find that limited detrending of the optimal photometric precision light curve is the best approach, although some systematic effects still remain present.
A Web-based Simulator for Sample Size and Power Estimation in Animal Carcinogenicity Studies
Directory of Open Access Journals (Sweden)
Hojin Moon
2002-12-01
Full Text Available A Web-based statistical tool for sample size and power estimation in animal carcinogenicity studies is presented in this paper. It can be used to provide a design with sufficient power for detecting a dose-related trend in the occurrence of a tumor of interest when competing risks are present. The tumors of interest typically are occult tumors for which the time to tumor onset is not directly observable. It is applicable to rodent tumorigenicity assays that have either a single terminal sacrifice or multiple (interval sacrifices. The design is achieved by varying sample size per group, number of sacrifices, number of sacrificed animals at each interval, if any, and scheduled time points for sacrifice. Monte Carlo simulation is carried out in this tool to simulate experiments of rodent bioassays because no closed-form solution is available. It takes design parameters for sample size and power estimation as inputs through the World Wide Web. The core program is written in C and executed in the background. It communicates with the Web front end via a Component Object Model interface passing an Extensible Markup Language string. The proposed statistical tool is illustrated with an animal study in lung cancer prevention research.
Type-II generalized family-wise error rate formulas with application to sample size determination.
Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie
2016-07-20
Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Sample size methods for estimating HIV incidence from cross-sectional surveys.
Konikoff, Jacob; Brookmeyer, Ron
2015-12-01
Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this article, we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this article at the Biometrics website on Wiley Online Library. © 2015, The International Biometric Society.
Medical image compression based on vector quantization with variable block sizes in wavelet domain.
Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo
2012-01-01
An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.
Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain
Directory of Open Access Journals (Sweden)
Huiyan Jiang
2012-01-01
Full Text Available An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.
Synthesis of variable size molecules using poly-homologation of boron compounds
International Nuclear Information System (INIS)
Goddard, J.P.
2002-01-01
During this work, we developed a method of original synthesis allowing to lead mixtures of molecules of variable size with an aim of discovering new chelating molecules of cesium. This method utilizes a reaction of poly-homologation of borated compounds with the nucleophilic ones comprising a grouping leaving in alpha of the negative charge. We tested various families from nucleophilic like anions of sulfones, sulfonium ylides, anions of hydrazones, tri-methylsilyldiazomethane and arsonium ylides. The first three families did not allow us to carry out reactions of poly-homologation. The tri-methylsilyldiazomethane possesses not either the capacity to carry out reactions successive insertions but this property was exploited to propose a chemical conversion of olefinic hydrocarbon into alkyl-methanol corresponding. The arsonium ylides made it possible to carry out reactions of poly-homologation with boronates and boranes. The alkyl-arsonium ylides were used to form polymers of controlled size having a ramification on each carbon atom of the principal chain. This type of polymer is not accessible by the current methods of polymerization. The allyl-arsonium ylides have a particular reactivity since the allyl boranes formed during the insertion reactions undergo a sigma-tropic [1,3] rearrangement before reacting again with a ylide. It is thus possible to lead with polymers of big size to which the structure is close to that of the natural rubber. By this method it is possible to lead with linear or cyclic polymers. This method is currently under development at the laboratory to form chelating structures of cesium. (author) [fr
Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses
Lanfear, Robert; Hua, Xia; Warren, Dan L.
2016-01-01
Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794
Zhang, Kai; Zhang, Bao-Zhong; Li, Shao-Meng; Zhang, Lei-Ming; Staebler, Ralf; Zeng, Eddy Y.
2012-09-01
Atmospheric gaseous and size-segregated particle samples were collected from urban Guangzhou at the heights of 100 and 150 m above the ground in daytime and at night in August and December 2010, and were analyzed for polycyclic aromatic hydrocarbons (PAHs). Particulate PAHs were more abundant at night than in daytime, and significantly higher in winter than in summer. The observed vertical, diurnal, and seasonal variability in the occurrences of PAH were attributed to varying meteorological conditions and atmospheric boundary layers. More than 60% of the particulate PAHs were contained in particles in the accumulation mode with an aerodynamic diameter (Dp) in the range of 0.1-1.8 μm. Different mass transfer velocities by volatilization and condensation are considered the main causes for the different particle size distributions among individual PAHs, while combustion at different temperatures and atmospheric transport were probable causes of the observed seasonal variation in the size distribution of PAHs. Based on the modeled size-dependent dry deposition velocities, daily mean dry deposition fluxes of particulate PAHs ranged from 604 to 1190 ng m-2 d-1, with PAHs in coarse particles (Dp > 1.8 μm) accounting for 55-95% of the total fluxes. In addition, gaseous PAHs were estimated to contribute 0.6-3.1% to the total dry deposition fluxes if a conservative dry deposition velocity for gaseous species (2 × 10-4 m s-1) were used. Finally, disequilibrium phase partitioning, meteorological conditions and atmospheric transport were regarded as the main reasons for the variances in dry deposition velocities of individual PAHs.
Directory of Open Access Journals (Sweden)
Smedslund Geir
2013-02-01
Full Text Available Abstract Background Patient reported outcomes are accepted as important outcome measures in rheumatology. The fluctuating symptoms in patients with rheumatic diseases have serious implications for sample size in clinical trials. We estimated the effects of measuring the outcome 1-5 times on the sample size required in a two-armed trial. Findings In a randomized controlled trial that evaluated the effects of a mindfulness-based group intervention for patients with inflammatory arthritis (n=71, the outcome variables Numerical Rating Scales (NRS (pain, fatigue, disease activity, self-care ability, and emotional wellbeing and General Health Questionnaire (GHQ-20 were measured five times before and after the intervention. For each variable we calculated the necessary sample sizes for obtaining 80% power (α=.05 for one up to five measurements. Two, three, and four measures reduced the required sample sizes by 15%, 21%, and 24%, respectively. With three (and five measures, the required sample size per group was reduced from 56 to 39 (32 for the GHQ-20, from 71 to 60 (55 for pain, 96 to 71 (73 for fatigue, 57 to 51 (48 for disease activity, 59 to 44 (45 for self-care, and 47 to 37 (33 for emotional wellbeing. Conclusions Measuring the outcomes five times rather than once reduced the necessary sample size by an average of 27%. When planning a study, researchers should carefully compare the advantages and disadvantages of increasing sample size versus employing three to five repeated measurements in order to obtain the required statistical power.
Moyé, Lemuel A; Lai, Dejian; Jing, Kaiyan; Baraniuk, Mary Sarah; Kwak, Minjung; Penn, Marc S; Wu, Colon O
2011-01-01
The assumptions that anchor large clinical trials are rooted in smaller, Phase II studies. In addition to specifying the target population, intervention delivery, and patient follow-up duration, physician-scientists who design these Phase II studies must select the appropriate response variables (endpoints). However, endpoint measures can be problematic. If the endpoint assesses the change in a continuous measure over time, then the occurrence of an intervening significant clinical event (SCE), such as death, can preclude the follow-up measurement. Finally, the ideal continuous endpoint measurement may be contraindicated in a fraction of the study patients, a change that requires a less precise substitution in this subset of participants.A score function that is based on the U-statistic can address these issues of 1) intercurrent SCE's and 2) response variable ascertainments that use different measurements of different precision. The scoring statistic is easy to apply, clinically relevant, and provides flexibility for the investigators' prospective design decisions. Sample size and power formulations for this statistic are provided as functions of clinical event rates and effect size estimates that are easy for investigators to identify and discuss. Examples are provided from current cardiovascular cell therapy research.
A novel approach for small sample size family-based association studies: sequential tests.
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.
Methodology for sample preparation and size measurement of commercial ZnO nanoparticles
Directory of Open Access Journals (Sweden)
Pei-Jia Lu
2018-04-01
Full Text Available This study discusses the strategies on sample preparation to acquire images with sufficient quality for size characterization by scanning electron microscope (SEM using two commercial ZnO nanoparticles of different surface properties as a demonstration. The central idea is that micrometer sized aggregates of ZnO in powdered forms need to firstly be broken down to nanosized particles through an appropriate process to generate nanoparticle dispersion before being deposited on a flat surface for SEM observation. Analytical tools such as contact angle, dynamic light scattering and zeta potential have been utilized to optimize the procedure for sample preparation and to check the quality of the results. Meanwhile, measurements of zeta potential values on flat surfaces also provide critical information and save lots of time and efforts in selection of suitable substrate for particles of different properties to be attracted and kept on the surface without further aggregation. This simple, low-cost methodology can be generally applied on size characterization of commercial ZnO nanoparticles with limited information from vendors. Keywords: Zinc oxide, Nanoparticles, Methodology
The Effect of Sterilization on Size and Shape of Fat Globules in Model Processed Cheese Samples
Directory of Open Access Journals (Sweden)
B. Tremlová
2006-01-01
Full Text Available Model cheese samples from 4 independent productions were heat sterilized (117 °C, 20 minutes after the melting process and packing with an aim to prolong their durability. The objective of the study was to assess changes in the size and shape of fat globules due to heat sterilization by using image analysis methods. The study included a selection of suitable methods of preparation mounts, taking microphotographs and making overlays for automatic processing of photographs by image analyser, ascertaining parameters to determine the size and shape of fat globules and statistical analysis of results obtained. The results of the experiment suggest that changes in shape of fat globules due to heat sterilization are not unequivocal. We found that the size of fat globules was significantly increased (p < 0.01 due to heat sterilization (117 °C, 20 min, and the shares of small fat globules (up to 500 μm2, or 100 μm2 in the samples of heat sterilized processed cheese were decreased. The results imply that the image analysis method is very useful when assessing the effect of technological process on the quality of processed cheese quality.
Statistical characterization of a large geochemical database and effect of sample size
Zhang, C.; Manheim, F.T.; Hinde, J.; Grossman, J.N.
2005-01-01
smaller numbers of data points showed that few elements passed standard statistical tests for normality or log-normality until sample size decreased to a few hundred data points. Large sample size enhances the power of statistical tests, and leads to rejection of most statistical hypotheses for real data sets. For large sample sizes (e.g., n > 1000), graphical methods such as histogram, stem-and-leaf, and probability plots are recommended for rough judgement of probability distribution if needed. ?? 2005 Elsevier Ltd. All rights reserved.
On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes.
Vegué, Marina; Perin, Rodrigo; Roxin, Alex
2017-08-30
The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering several distinct classes of network topology, including clustered networks, networks with distance-dependent connectivity, and those with broad degree distributions. To our surprise, we found that all of these qualitatively distinct topologies could account equally well for all reported nonrandom features despite being easily distinguishable from one another at the network level. This apparent paradox was a consequence of estimating network properties given only small sample sizes. In other words, networks that differ markedly in their global structure can look quite similar locally. This makes inferring network structure from small sample sizes, a necessity given the technical difficulty inherent in simultaneous intracellular recordings, problematic. We found that a network statistic called the sample degree correlation (SDC) overcomes this difficulty. The SDC depends only on parameters that can be estimated reliably given small sample sizes and is an accurate fingerprint of every topological family. We applied the SDC criterion to data from rat visual and somatosensory cortex and discovered that the connectivity was not consistent with any of these main topological classes. However, we were able to fit the experimental data with a more general network class, of which all previous topologies were special cases. The resulting network topology could be interpreted as a combination of physical spatial dependence and nonspatial, hierarchical clustering. SIGNIFICANCE STATEMENT The connectivity of cortical microcircuits exhibits features that are inconsistent with a simple random network. Here, we show that several classes of network models can account for this nonrandom structure despite qualitative differences in
Heuristics for the Variable Sized Bin Packing Problem Using a Hybrid P-System and CUDA Architecture
AlEnezi, Qadha'a; AboElFotoh, Hosam; AlBdaiwi, Bader; AlMulla, Mohammad Ali
2016-01-01
The Variable Sized Bin Packing Problem has a wide range of application areas including packing, scheduling, and manufacturing. Given a list of items and variable sized bin types, the objective is to minimize the total size of the used bins. This problem is known to be NP-hard. In this article, we present two new heuristics for solving the problem using a new variation of P systems with active membranes, which we call a hybrid P system, implemented in CUDA. Our hybrid P-system model allows usi...
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 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.
Inoue, Akiomi; Kawakami, Norito; Tsuchiya, Masao; Sakurai, Keiko; Hashimoto, Hideki
2010-01-01
The purpose of this study was to investigate the cross-sectional association of employment contract, company size, and occupation with psychological distress using a nationally representative sample of the Japanese population. From June through July 2007, a total of 9,461 male and 7,717 female employees living in the community were randomly selected and surveyed using a self-administered questionnaire and interview including questions about occupational class variables, psychological distress (K6 scale), treatment for mental disorders, and other covariates. Among males, part-time workers had a significantly higher prevalence of psychological distress than permanent workers. Among females, temporary/contract workers had a significantly higher prevalence of psychological distress than permanent workers. Among males, those who worked at companies with 300-999 employees had a significantly higher prevalence of psychological distress than those who worked at the smallest companies (with 1-29 employees). Company size was not significantly associated with psychological distress among females. Additionally, occupation was not significantly associated with psychological distress among males or females. Similar patterns were observed when the analyses were conducted for those who had psychological distress and/or received treatment for mental disorders. Working as part-time workers, for males, and as temporary/contract workers, for females, may be associated with poor mental health in Japan. No clear gradient in mental health along company size or occupation was observed in Japan.
Sampling and chemical analysis by TXRF of size-fractionated ambient aerosols and emissions
International Nuclear Information System (INIS)
John, A.C.; Kuhlbusch, T.A.J.; Fissan, H.; Schmidt, K.-G-; Schmidt, F.; Pfeffer, H.-U.; Gladtke, D.
2000-01-01
Results of recent epidemiological studies led to new European air quality standards which require the monitoring of particles with aerodynamic diameters ≤ 10 μm (PM 10) and ≤ 2.5 μm (PM 2.5) instead of TSP (total suspended particulate matter). As these ambient air limit values will be exceeded most likely at several locations in Europe, so-called 'action plans' have to be set up to reduce particle concentrations, which requires information about sources and processes of PMx aerosols. For chemical characterization of the aerosols, different samplers were used and total reflection x-ray fluorescence analysis (TXRF) was applied beside other methods (elemental and organic carbon analysis, ion chromatography, atomic absorption spectrometry). For TXRF analysis, a specially designed sampling unit was built where the particle size classes 10-2.5 μm and 2.5-1.0 μm were directly impacted on TXRF sample carriers. An electrostatic precipitator (ESP) was used as a back-up filter to collect particles <1 μm directly on a TXRF sample carrier. The sampling unit was calibrated in the laboratory and then used for field measurements to determine the elemental composition of the mentioned particle size fractions. One of the field campaigns was carried out at a measurement site in Duesseldorf, Germany, in November 1999. As the composition of the ambient aerosols may have been influenced by a large construction site directly in the vicinity of the station during the field campaign, not only the aerosol particles, but also construction material was sampled and analyzed by TXRF. As air quality is affected by natural and anthropogenic sources, the emissions of particles ≤ 10 μm and ≤ 2.5 μm, respectively, have to be determined to estimate their contributions to the so called coarse and fine particle modes of ambient air. Therefore, an in-stack particle sampling system was developed according to the new ambient air quality standards. This PM 10/PM 2.5 cascade impactor was
Sample size effect on the determination of the irreversibility line of high-Tc superconductors
International Nuclear Information System (INIS)
Li, Q.; Suenaga, M.; Li, Q.; Freltoft, T.
1994-01-01
The irreversibility lines of a high-J c superconducting Bi 2 Sr 2 Ca 2 Cu 3 O x /Ag tape were systematically measured upon a sequence of subdivisions of the sample. The irreversibility field H r (T) (parallel to the c axis) was found to change approximately as L 0.13 , where L is the effective dimension of the superconducting tape. Furthermore, it was found that the irreversibility line for a grain-aligned Bi 2 Sr 2 Ca 2 Cu 3 O x specimen can be approximately reproduced by the extrapolation of this relation down to a grain size of a few tens of micrometers. The observed size effect could significantly obscure the real physical meaning of the irreversibility lines. In addition, this finding surprisingly indicated that the Bi 2 Sr 2 Ca 2 Cu 2 O x /Ag tape and grain-aligned specimen may have similar flux line pinning strength
Autoregressive Prediction with Rolling Mechanism for Time Series Forecasting with Small Sample Size
Directory of Open Access Journals (Sweden)
Zhihua Wang
2014-01-01
Full Text Available Reasonable prediction makes significant practical sense to stochastic and unstable time series analysis with small or limited sample size. Motivated by the rolling idea in grey theory and the practical relevance of very short-term forecasting or 1-step-ahead prediction, a novel autoregressive (AR prediction approach with rolling mechanism is proposed. In the modeling procedure, a new developed AR equation, which can be used to model nonstationary time series, is constructed in each prediction step. Meanwhile, the data window, for the next step ahead forecasting, rolls on by adding the most recent derived prediction result while deleting the first value of the former used sample data set. This rolling mechanism is an efficient technique for its advantages of improved forecasting accuracy, applicability in the case of limited and unstable data situations, and requirement of little computational effort. The general performance, influence of sample size, nonlinearity dynamic mechanism, and significance of the observed trends, as well as innovation variance, are illustrated and verified with Monte Carlo simulations. The proposed methodology is then applied to several practical data sets, including multiple building settlement sequences and two economic series.
Influence of secular trends and sample size on reference equations for lung function tests.
Quanjer, P H; Stocks, J; Cole, T J; Hall, G L; Stanojevic, S
2011-03-01
The aim of our study was to determine the contribution of secular trends and sample size to lung function reference equations, and establish the number of local subjects required to validate published reference values. 30 spirometry datasets collected between 1978 and 2009 provided data on healthy, white subjects: 19,291 males and 23,741 females aged 2.5-95 yrs. The best fit for forced expiratory volume in 1 s (FEV(1)), forced vital capacity (FVC) and FEV(1)/FVC as functions of age, height and sex were derived from the entire dataset using GAMLSS. Mean z-scores were calculated for individual datasets to determine inter-centre differences. This was repeated by subdividing one large dataset (3,683 males and 4,759 females) into 36 smaller subsets (comprising 18-227 individuals) to preclude differences due to population/technique. No secular trends were observed and differences between datasets comprising >1,000 subjects were small (maximum difference in FEV(1) and FVC from overall mean: 0.30- -0.22 z-scores). Subdividing one large dataset into smaller subsets reproduced the above sample size-related differences and revealed that at least 150 males and 150 females would be necessary to validate reference values to avoid spurious differences due to sampling error. Use of local controls to validate reference equations will rarely be practical due to the numbers required. Reference equations derived from large or collated datasets are recommended.
Effect size measures in a two-independent-samples case with nonnormal and nonhomogeneous data.
Li, Johnson Ching-Hong
2016-12-01
In psychological science, the "new statistics" refer to the new statistical practices that focus on effect size (ES) evaluation instead of conventional null-hypothesis significance testing (Cumming, Psychological Science, 25, 7-29, 2014). In a two-independent-samples scenario, Cohen's (1988) standardized mean difference (d) is the most popular ES, but its accuracy relies on two assumptions: normality and homogeneity of variances. Five other ESs-the unscaled robust d (d r * ; Hogarty & Kromrey, 2001), scaled robust d (d r ; Algina, Keselman, & Penfield, Psychological Methods, 10, 317-328, 2005), point-biserial correlation (r pb ; McGrath & Meyer, Psychological Methods, 11, 386-401, 2006), common-language ES (CL; Cliff, Psychological Bulletin, 114, 494-509, 1993), and nonparametric estimator for CL (A w ; Ruscio, Psychological Methods, 13, 19-30, 2008)-may be robust to violations of these assumptions, but no study has systematically evaluated their performance. Thus, in this simulation study the performance of these six ESs was examined across five factors: data distribution, sample, base rate, variance ratio, and sample size. The results showed that A w and d r were generally robust to these violations, and A w slightly outperformed d r . Implications for the use of A w and d r in real-world research are discussed.
Practical continuous-variable quantum key distribution without finite sampling bandwidth effects.
Li, Huasheng; Wang, Chao; Huang, Peng; Huang, Duan; Wang, Tao; Zeng, Guihua
2016-09-05
In a practical continuous-variable quantum key distribution system, finite sampling bandwidth of the employed analog-to-digital converter at the receiver's side may lead to inaccurate results of pulse peak sampling. Then, errors in the parameters estimation resulted. Subsequently, the system performance decreases and security loopholes are exposed to eavesdroppers. In this paper, we propose a novel data acquisition scheme which consists of two parts, i.e., a dynamic delay adjusting module and a statistical power feedback-control algorithm. The proposed scheme may improve dramatically the data acquisition precision of pulse peak sampling and remove the finite sampling bandwidth effects. Moreover, the optimal peak sampling position of a pulse signal can be dynamically calibrated through monitoring the change of the statistical power of the sampled data in the proposed scheme. This helps to resist against some practical attacks, such as the well-known local oscillator calibration attack.
Line Shape Variability in a Sample of AGN with Broad Lines
Indian Academy of Sciences (India)
2016-01-27
Jan 27, 2016 ... We give here a comparative review of the line shape variability in a sample of five type 1 AGNs, those with broad emission lines in their spectra, of the data obtained from the international long-term optical monitoring campaign coordinated by the Special Astrophysical Observatory of the Russian Academy ...
Pet, J.S.; Densen, van W.L.T.; Machiels, M.A.M.; Sukkel, M.; Setyohady, D.; Tumuljadi, A.
1997-01-01
Temporal and spatial patterns in the fishery for Sardinella spp. around East Java, Indonesia, were studied in an attempt to develop an efficient catch and effort sampling strategy for this highly variable fishery. The inter-annual and monthly variation in catch, effort and catch per unit of effort
Finite-sample instrumental variables inference using an asymptotically pivotal statistic
Bekker, P; Kleibergen, F
2003-01-01
We consider the K-statistic, Kleibergen's (2002, Econometrica 70, 1781-1803) adaptation of the Anderson-Rubin (AR) statistic in instrumental variables regression. Whereas Kleibergen (2002) especially analyzes the asymptotic behavior of the statistic, we focus on finite-sample properties in, a
Cugerone, Katia; De Michele, Carlo; Ghezzi, Antonio; Gianelle, Vorne; Gilardoni, Stefania
2018-04-01
Particle number size distributions (PNSDs) have been collected periodically in the urban area of Milan, Italy, during 2011 and 2012 in winter and summer months. Moreover, comparable PNSD measurements were carried out in the rural mountain site of Oga-San Colombano (2250 m a.s.l.), Italy, during February 2005 and August 2011. The aerosol data have been measured through the use of optical particle counters in the size range 0.3-25 µm, with a time resolution of 1 min. The comparison of the PNSDs collected in the two sites has been done in terms of total number concentration, showing higher numbers in Milan (often exceeding 103 cm-3 in winter season) compared to Oga-San Colombano (not greater than 2×102 cm-3), as expected. The skewness-kurtosis plane has been used in order to provide a synoptic view, and select the best distribution family describing the empirical PNSD pattern. The four-parameter Johnson system-bounded distribution (called Johnson SB or JSB) has been tested for this aim, due to its great flexibility and ability to assume different shapes. The PNSD pattern has been found to be generally invariant under site and season changes. Nevertheless, several PNSDs belonging to the Milan winter season (generally more than 30 %) clearly deviate from the standard empirical pattern. The seasonal increase in the concentration of primary aerosols due to combustion processes in winter and the influence of weather variables throughout the year, such as precipitation and wind speed, could be considered plausible explanations of PNSD dynamics.
Dybwad, Marius; Skogan, Gunnar; Blatny, Janet Martha
2014-01-01
Naturally occurring bioaerosol environments may present a challenge to biological detection-identification-monitoring (BIODIM) systems aiming at rapid and reliable warning of bioterrorism incidents. One way to improve the operational performance of BIODIM systems is to increase our understanding of relevant bioaerosol backgrounds. Subway stations are enclosed public environments which may be regarded as potential bioterrorism targets. This study provides novel information concerning the temporal variability of the concentration level, size distribution, and diversity of airborne bacteria in a Norwegian subway station. Three different air samplers were used during a 72-h sampling campaign in February 2011. The results suggested that the airborne bacterial environment was stable between days and seasons, while the intraday variability was found to be substantial, although often following a consistent diurnal pattern. The bacterial levels ranged from not detected to 10(3) CFU m(-3) and generally showed increased levels during the daytime compared to the nighttime levels, as well as during rush hours compared to non-rush hours. The airborne bacterial levels showed rapid temporal variation (up to 270-fold) on some occasions, both consistent and inconsistent with the diurnal profile. Airborne bacterium-containing particles were distributed between different sizes for particles of >1.1 μm, although ∼50% were between 1.1 and 3.3 μm. Anthropogenic activities (mainly passengers) were demonstrated as major sources of airborne bacteria and predominantly contributed 1.1- to 3.3-μm bacterium-containing particles. Our findings contribute to the development of realistic testing and evaluation schemes for BIODIM equipment by providing information that may be used to simulate operational bioaerosol backgrounds during controlled aerosol chamber-based challenge tests with biological threat agents.
Dybwad, Marius; Skogan, Gunnar
2014-01-01
Naturally occurring bioaerosol environments may present a challenge to biological detection-identification-monitoring (BIODIM) systems aiming at rapid and reliable warning of bioterrorism incidents. One way to improve the operational performance of BIODIM systems is to increase our understanding of relevant bioaerosol backgrounds. Subway stations are enclosed public environments which may be regarded as potential bioterrorism targets. This study provides novel information concerning the temporal variability of the concentration level, size distribution, and diversity of airborne bacteria in a Norwegian subway station. Three different air samplers were used during a 72-h sampling campaign in February 2011. The results suggested that the airborne bacterial environment was stable between days and seasons, while the intraday variability was found to be substantial, although often following a consistent diurnal pattern. The bacterial levels ranged from not detected to 103 CFU m−3 and generally showed increased levels during the daytime compared to the nighttime levels, as well as during rush hours compared to non-rush hours. The airborne bacterial levels showed rapid temporal variation (up to 270-fold) on some occasions, both consistent and inconsistent with the diurnal profile. Airborne bacterium-containing particles were distributed between different sizes for particles of >1.1 μm, although ∼50% were between 1.1 and 3.3 μm. Anthropogenic activities (mainly passengers) were demonstrated as major sources of airborne bacteria and predominantly contributed 1.1- to 3.3-μm bacterium-containing particles. Our findings contribute to the development of realistic testing and evaluation schemes for BIODIM equipment by providing information that may be used to simulate operational bioaerosol backgrounds during controlled aerosol chamber-based challenge tests with biological threat agents. PMID:24162566
Kakimoto, Risa; Ichiba, Masayoshi; Matsumoto, Akiko; Nakai, Kunihiko; Tatsuta, Nozomi; Iwai-Shimada, Miyuki; Ishiyama, Momoko; Ryuda, Noriko; Someya, Takashi; Tokumoto, Ieyasu; Ueno, Daisuke
2018-01-13
Risk assessment of infant using a realistic persistent organic pollutant (POP) exposure through breast milk is essential to devise future regulation of POPs. However, recent investigations have demonstrated that POP levels in breast milk collected from the same mother showed a wide range of variation daily and monthly. To estimate the appropriate sample size of breast milk from the same mother to obtain reliable POP concentrations, breast milk samples were collected from five mothers living in Japan from 2006 to 2012. Milk samples from each mother were collected 3 to 6 times a day through 3 to 7 days consecutively. Food samples as the duplicated method were collected from two mothers during the period of breast milk sample collection. Those were employed for POP (PCBs, DDTs, chlordanes, and HCB) analysis. PCB concentrations detected in breast milk samples showed a wide range of variation which was maximum 63 and 60% of relative standard deviation (RSD) in lipid and wet weight basis, respectively. The time course trend of those variations among the mothers did not show any typical pattern. A larger amount of PCB intake through food seemed to affect 10 h after those concentrations in breast milk in lipid weight basis. Intraclass correlation coefficient (ICC) analyses indicated that the appropriate sample size for good reproducibility of POP concentrations in breast milk required at least two samples for lipid and wet weight basis.
318-MHz variability of complete samples of extragalactic radio sources. II
International Nuclear Information System (INIS)
Dennison, B.; Broderick, J.J.; Ledden, J.E.; O'Dell, S.L.; Condon, J.J.
1981-01-01
We report the remainder of two- and three-epoch 318-MHz observations of extragalactic sources in samples complete to 3 Jy at 1400 MHz and 1 Jy at 5000 MHz. From analysis of this low-frequency variability survey, we find that steep-spectrum (α> or =0.5) sources do not appear to vary, but about 40% of all flat-spectrum (α<0.5) sources exhibit low-frequency variability exceeding 8% over approx.5 yr. Among the flat-spectrum sources, those with inverted spectra show the largest fractional variations. We also find that the incidence of low-frequency variability is strongly correlated with the determination that a source is an optically violent variable. These statistical properties are consistent with models invoking relativistic beaming of radio and optical emission
Analysis of femtogram-sized plutonium samples by thermal ionization mass spectrometry
International Nuclear Information System (INIS)
Smith, D.H.; Duckworth, D.C.; Bostick, D.T.; Coleman, R.M.; McPherson, R.L.; McKown, H.S.
1994-01-01
The goal of this investigation was to extend the ability to perform isotopic analysis of plutonium to samples as small as possible. Plutonium ionizes thermally with quite good efficiency (first ionization potential 5.7 eV). Sub-nanogram sized samples can be analyzed on a near-routine basis given the necessary instrumentation. Efforts in this laboratory have been directed at rhenium-carbon systems; solutions of carbon in rhenium provide surfaces with work functions higher than pure rhenium (5.8 vs. ∼ 5.4 eV). Using a single resin bead as a sample loading medium both concentrates the sample nearly to a point and, due to its interaction with rhenium, produces the desired composite surface. Earlier work in this area showed that a layer of rhenium powder slurried in solution containing carbon substantially enhanced precision of isotopic measurements for uranium. Isotopic fractionation was virtually eliminated, and ionization efficiencies 2-5 times better than previously measured were attained for both Pu and U (1.7 and 0.5%, respectively). The other side of this coin should be the ability to analyze smaller samples, which is the subject of this report
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.
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.
Terry, Leann; Kelley, Ken
2012-11-01
Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.
Spearing, Debra; Woehlke, Paula
To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…
Self-navigation of a scanning tunneling microscope tip toward a micron-sized graphene sample.
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.
Magnetic response and critical current properties of mesoscopic-size YBCO superconducting samples
International Nuclear Information System (INIS)
Lisboa-Filho, P N; Deimling, C V; Ortiz, W A
2010-01-01
In this contribution superconducting specimens of YBa 2 Cu 3 O 7-δ were synthesized by a modified polymeric precursor method, yielding a ceramic powder with particles of mesoscopic-size. Samples of this powder were then pressed into pellets and sintered under different conditions. The critical current density was analyzed by isothermal AC-susceptibility measurements as a function of the excitation field, as well as with isothermal DC-magnetization runs at different values of the applied field. Relevant features of the magnetic response could be associated to the microstructure of the specimens and, in particular, to the superconducting intra- and intergranular critical current properties.
Clustering for high-dimension, low-sample size data using distance vectors
Terada, Yoshikazu
2013-01-01
In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that contain information of the cluster structure in high-dimensional space. Based on this fact, we propose an efficient and simple clustering approach, called distance vector clustering, for HDLSS data. Under the assumptions given in the work of Hall et al. (2005), w...
Magnetic response and critical current properties of mesoscopic-size YBCO superconducting samples
Energy Technology Data Exchange (ETDEWEB)
Lisboa-Filho, P N [UNESP - Universidade Estadual Paulista, Grupo de Materiais Avancados, Departamento de Fisica, Bauru (Brazil); Deimling, C V; Ortiz, W A, E-mail: plisboa@fc.unesp.b [Grupo de Supercondutividade e Magnetismo, Departamento de Fisica, Universidade Federal de Sao Carlos, Sao Carlos (Brazil)
2010-01-15
In this contribution superconducting specimens of YBa{sub 2}Cu{sub 3}O{sub 7-{delta}} were synthesized by a modified polymeric precursor method, yielding a ceramic powder with particles of mesoscopic-size. Samples of this powder were then pressed into pellets and sintered under different conditions. The critical current density was analyzed by isothermal AC-susceptibility measurements as a function of the excitation field, as well as with isothermal DC-magnetization runs at different values of the applied field. Relevant features of the magnetic response could be associated to the microstructure of the specimens and, in particular, to the superconducting intra- and intergranular critical current properties.
Directory of Open Access Journals (Sweden)
Antonio Di Franco
Full Text Available Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS. LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1 whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2 the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast. We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within
Pattanaik, Sidhartha; Huggins, Frank E; Huffman, Gerald P
2016-08-15
Ambient particulate matter (PM) containing iron can catalyze Fenton reaction leading to the production of reactive oxygen species in cells. It can also catalyze atmospheric redox reaction. These reactions are governed by the physicochemical characteristics of iron in ambient PM. As a surrogate for ambient PM, we prepared residual oil fly ash PM (ROFA PM) in a practical fire tube boiler firing residual oils with varying sulfur and ash contents. The ROFA particles were resolved into fine PM or PM2.5 (aerodynamic diameter (AD)iron speciation in PM2.5+ was ascertained using X-ray absorption spectroscopy and leaching method while that in PM2.5 was reported earlier. The results of both studies are compared to get an insight into the variability in the iron speciation in different size fractions. The results show the predominance of ferric sulfate, with a minor spinal ferrite in both PM (i.e. ZnxNi1-xFe2O4 in PM2.5, ZnFe2O4 in PM2.5+). The iron solubility in ROFA PM depends on its speciation, mode of incorporation of iron into particle's carbonaceous matrix, the grade and composition of oils, and pH of the medium. The soluble fraction of iron in PM is critical in assessing its interaction with the biological systems and its toxic potential. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Jovković Biljana
2012-12-01
Full Text Available The aim of this paper is to present the procedure of audit sampling using the variable sampling methods for conducting the tests of income from insurance premiums in insurance company 'Takovo'. Since the incomes from the insurance premiums from vehicle insurance and third-party vehicle insurance have the dominant share of the insurance company's income, the application of this method will be shown in the audit examination of these incomes - incomes from VI and TPVI premiums. For investigating the applicability of these methods in testing the income of other insurance companies, we shall implement the method of variable sampling in the audit testing of the premium income from the three leading insurance companies in Serbia, 'Dunav', 'DDOR' and 'Delta Generali' Insurance.
Directory of Open Access Journals (Sweden)
John P. SMOL
2008-02-01
Full Text Available Daphnia and Bosmina fragments were identified and measured in the surface sediments of 42 lakes in the Muskoka-Haliburton region of Ontario, Canada, in an attempt to identify environmental factors that may influence cladoceran body size. Specifically, pecten length on Daphnia post-abdominal claws, antennule length on Bosmina headshields, and carapace and mucro lengths of Bosmina carapaces were measured. These measurements were then compared to limnological variables previously identified as possibly influencing cladoceran size, including dissolved organic carbon (DOC, total phosphorus (TP, pH, calcium (Ca, Chaoborus density, and fish presence/absence. Cladoceran size displayed a linear relationship to TP, with larger Bosmina and Daphnia present in lakes with lower nutrient levels. We suspect that, as larger individuals are more efficient grazers, they may competitively exclude smaller individuals when nutrients are limiting in these lakes. Bosmina mucro length and cladoceran community size structure displayed a step response to DOC, with mean size significantly smaller when DOC concentrations were higher than 5.89 mg L-1. Daphnia pecten length displayed a negative linear relationship to DOC above a concentration of 4.90 mg l-1. Reduced predation pressure from gape-limited macroinvertebrate predators, such as Chaoborus, may have influenced these relationships. DOC was also highly correlated to TP in these lakes, and size trends might be responding to the TP gradient rather than the DOC gradient. Mean cladoceran body size in acidic lakes (pH 6.0. There was no relationship between size structure and Ca concentrations, attributed to a narrow Ca gradient in these lakes. Predation effects were examined using limited Chaoborus density and fish presence/absence data. Although there were no significant relationships between cladoceran size and Chaoborus density, some significant relationships between size variables and fish predation were identified. The
Modelling the joint variability of grain size and chemical composition in sediments
Bloemsma, M.R.; Zabel, M.; Stuut, J.B.W.; Tjallingii, R.; Collins, J.A.; Weltje, G.J.
2012-01-01
The geochemical composition of siliciclastic sediments correlates strongly with grain size. Hence, geochemical composition may serve as a grain-size proxy. In the absence of grain-size variations, geochemical data of siliciclastic sediments may be used to characterise size-independent processes,
DEFF Research Database (Denmark)
Haugbøl, Steven; Pinborg, Lars H; Arfan, Haroon M
2006-01-01
PURPOSE: To determine the reproducibility of measurements of brain 5-HT2A receptors with an [18F]altanserin PET bolus/infusion approach. Further, to estimate the sample size needed to detect regional differences between two groups and, finally, to evaluate how partial volume correction affects...... reproducibility and the required sample size. METHODS: For assessment of the variability, six subjects were investigated with [18F]altanserin PET twice, at an interval of less than 2 weeks. The sample size required to detect a 20% difference was estimated from [18F]altanserin PET studies in 84 healthy subjects....... Regions of interest were automatically delineated on co-registered MR and PET images. RESULTS: In cortical brain regions with a high density of 5-HT2A receptors, the outcome parameter (binding potential, BP1) showed high reproducibility, with a median difference between the two group measurements of 6...
Energy Technology Data Exchange (ETDEWEB)
Backlund, Peter B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shahan, David W. [HRL Labs., LLC, Malibu, CA (United States); Seepersad, Carolyn Conner [Univ. of Texas, Austin, TX (United States)
2014-04-22
A classifier-guided sampling (CGS) method is introduced for solving engineering design optimization problems with discrete and/or continuous variables and continuous and/or discontinuous responses. The method merges concepts from metamodel-guided sampling and population-based optimization algorithms. The CGS method uses a Bayesian network classifier for predicting the performance of new designs based on a set of known observations or training points. Unlike most metamodeling techniques, however, the classifier assigns a categorical class label to a new design, rather than predicting the resulting response in continuous space, and thereby accommodates nondifferentiable and discontinuous functions of discrete or categorical variables. The CGS method uses these classifiers to guide a population-based sampling process towards combinations of discrete and/or continuous variable values with a high probability of yielding preferred performance. Accordingly, the CGS method is appropriate for discrete/discontinuous design problems that are ill-suited for conventional metamodeling techniques and too computationally expensive to be solved by population-based algorithms alone. In addition, the rates of convergence and computational properties of the CGS method are investigated when applied to a set of discrete variable optimization problems. Results show that the CGS method significantly improves the rate of convergence towards known global optima, on average, when compared to genetic algorithms.
Estimated ventricle size using Evans index: reference values from a population-based sample.
Jaraj, D; Rabiei, K; Marlow, T; Jensen, C; Skoog, I; Wikkelsø, C
2017-03-01
Evans index is an estimate of ventricular size used in the diagnosis of idiopathic normal-pressure hydrocephalus (iNPH). Values >0.3 are considered pathological and are required by guidelines for the diagnosis of iNPH. However, there are no previous epidemiological studies on Evans index, and normal values in adults are thus not precisely known. We examined a representative sample to obtain reference values and descriptive data on Evans index. A population-based sample (n = 1235) of men and women aged ≥70 years was examined. The sample comprised people living in private households and residential care, systematically selected from the Swedish population register. Neuropsychiatric examinations, including head computed tomography, were performed between 1986 and 2000. Evans index ranged from 0.11 to 0.46. The mean value in the total sample was 0.28 (SD, 0.04) and 20.6% (n = 255) had values >0.3. Among men aged ≥80 years, the mean value of Evans index was 0.3 (SD, 0.03). Individuals with dementia had a mean value of Evans index of 0.31 (SD, 0.05) and those with radiological signs of iNPH had a mean value of 0.36 (SD, 0.04). A substantial number of subjects had ventricular enlargement according to current criteria. Clinicians and researchers need to be aware of the range of values among older individuals. © 2017 EAN.
Elemental analysis of size-fractionated particulate matter sampled in Goeteborg, Sweden
Energy Technology Data Exchange (ETDEWEB)
Wagner, Annemarie [Department of Chemistry, Atmospheric Science, Goeteborg University, SE-412 96 Goeteborg (Sweden)], E-mail: wagnera@chalmers.se; Boman, Johan [Department of Chemistry, Atmospheric Science, Goeteborg University, SE-412 96 Goeteborg (Sweden); Gatari, Michael J. [Institute of Nuclear Science and Technology, University of Nairobi, P.O. Box 30197-00100, Nairobi (Kenya)
2008-12-15
The aim of the study was to investigate the mass distribution of trace elements in aerosol samples collected in the urban area of Goeteborg, Sweden, with special focus on the impact of different air masses and anthropogenic activities. Three measurement campaigns were conducted during December 2006 and January 2007. A PIXE cascade impactor was used to collect particulate matter in 9 size fractions ranging from 16 to 0.06 {mu}m aerodynamic diameter. Polished quartz carriers were chosen as collection substrates for the subsequent direct analysis by TXRF. To investigate the sources of the analyzed air masses, backward trajectories were calculated. Our results showed that diurnal sampling was sufficient to investigate the mass distribution for Br, Ca, Cl, Cu, Fe, K, Sr and Zn, whereas a 5-day sampling period resulted in additional information on mass distribution for Cr and S. Unimodal mass distributions were found in the study area for the elements Ca, Cl, Fe and Zn, whereas the distributions for Br, Cu, Cr, K, Ni and S were bimodal, indicating high temperature processes as source of the submicron particle components. The measurement period including the New Year firework activities showed both an extensive increase in concentrations as well as a shift to the submicron range for K and Sr, elements that are typically found in fireworks. Further research is required to validate the quantification of trace elements directly collected on sample carriers.
Elemental analysis of size-fractionated particulate matter sampled in Goeteborg, Sweden
International Nuclear Information System (INIS)
Wagner, Annemarie; Boman, Johan; Gatari, Michael J.
2008-01-01
The aim of the study was to investigate the mass distribution of trace elements in aerosol samples collected in the urban area of Goeteborg, Sweden, with special focus on the impact of different air masses and anthropogenic activities. Three measurement campaigns were conducted during December 2006 and January 2007. A PIXE cascade impactor was used to collect particulate matter in 9 size fractions ranging from 16 to 0.06 μm aerodynamic diameter. Polished quartz carriers were chosen as collection substrates for the subsequent direct analysis by TXRF. To investigate the sources of the analyzed air masses, backward trajectories were calculated. Our results showed that diurnal sampling was sufficient to investigate the mass distribution for Br, Ca, Cl, Cu, Fe, K, Sr and Zn, whereas a 5-day sampling period resulted in additional information on mass distribution for Cr and S. Unimodal mass distributions were found in the study area for the elements Ca, Cl, Fe and Zn, whereas the distributions for Br, Cu, Cr, K, Ni and S were bimodal, indicating high temperature processes as source of the submicron particle components. The measurement period including the New Year firework activities showed both an extensive increase in concentrations as well as a shift to the submicron range for K and Sr, elements that are typically found in fireworks. Further research is required to validate the quantification of trace elements directly collected on sample carriers
Dependence of fracture mechanical and fluid flow properties on fracture roughness and sample size
International Nuclear Information System (INIS)
Tsang, Y.W.; Witherspoon, P.A.
1983-01-01
A parameter study has been carried out to investigate the interdependence of mechanical and fluid flow properties of fractures with fracture roughness and sample size. A rough fracture can be defined mathematically in terms of its aperture density distribution. Correlations were found between the shapes of the aperture density distribution function and the specific fractures of the stress-strain behavior and fluid flow characteristics. Well-matched fractures had peaked aperture distributions that resulted in very nonlinear stress-strain behavior. With an increasing degree of mismatching between the top and bottom of a fracture, the aperture density distribution broadened and the nonlinearity of the stress-strain behavior became less accentuated. The different aperture density distributions also gave rise to qualitatively different fluid flow behavior. Findings from this investigation make it possible to estimate the stress-strain and fluid flow behavior when the roughness characteristics of the fracture are known and, conversely, to estimate the fracture roughness from an examination of the hydraulic and mechanical data. Results from this study showed that both the mechanical and hydraulic properties of the fracture are controlled by the large-scale roughness of the joint surface. This suggests that when the stress-flow behavior of a fracture is being investigated, the size of the rock sample should be larger than the typical wave length of the roughness undulations
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.
Shieh, Gwowen; Jan, Show-Li
2013-01-01
The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the…
The Dependence of Cloud Particle Size on Non-Aerosol-Loading Related Variables
Energy Technology Data Exchange (ETDEWEB)
Shao, H.; Liu, G.
2005-03-18
An enhanced concentration of aerosol may increase the number of cloud drops by providing more cloud condensation nuclei (CCN), which in turn results in a higher cloud albedo at a constant cloud liquid water path. This process is often referred to as the aerosol indirect effect (AIE). Many in situ and remote sensing observations support this hypothesis (Ramanathan et al. 2001). However, satellite observed relations between aerosol concentration and cloud drop size are not always in agreement with the AIE. Based on global analysis of cloud effective radius (r{sub e}) and aerosol number concentration (N{sub a}) derived from satellite data, Sekiguchi et al. (2003) found that the correlations between the two variables can be either negative, or positive, or none, depending on the location of the clouds. They discovered that significantly negative r{sub e} - N{sub a} correlation can only be identified along coastal regions of the continents where abundant continental aerosols inflow from land, whereas Feingold et al. (2001) found that the response of r{sub e} to aerosol loading is the greatest in the region where aerosol optical depth ({tau}{sub a}) is the smallest. The reason for the discrepancy is likely due to the variations in cloud macroscopic properties such as geometrical thickness (Brenguier et al. 2003). Since r{sub e} is modified not only by aerosol but also by cloud geometrical thickness (H), the correlation between re and {tau}{sub a} actually reflects both the aerosol indirect effect and dependence of H. Therefore, discussing AIE based on the r{sub e}-{tau}{sub a} correlation without taking into account variations in cloud geometrical thickness may be misleading. This paper is motivated to extract aerosols' effect from overall effects using the independent measurements of cloud geometrical thickness, {tau}{sub a} and r{sub e}.
Color variability and body size of larvae of two Epomis species (Coleoptera: Carabidae in Israel
Directory of Open Access Journals (Sweden)
Gil Wizen
2011-07-01
Full Text Available Species identification using the characteristics of developmental stages is challenging. However, for insect taxonomy the coloration of larval stages can be an informative feature. The use of live specimens is recommended for this because the color fades in preserved specimens. In this study we examine the possibility of using variation in coloration and color pattern of larvae in order to distinguish between two ground beetles species Epomis dejeani Dejean, 1831 and E. circumscriptus Duftschmid, 1812. We present an atlas and describe the coloration and body size of the three larval stages of the above species based on live specimens. The first instar larvae of the two Epomis species can be easily distinguished based on their color. From the second instar on, the variability in coloration and color patterns increases, creating an overlap in these attributes between larvae of the two species. Except for minor differences in color of the antennae and the base of the mandibles, larvae of the two species are indistinguishable at the second and third larval stages. To the best of our knowledge this is the first attempt to use variation in coloration and color pattern in live larvae in order to identify coleopterans. The color atlas of the larvae enables simple separation of the two Epomis species without requiring sophisticated magnifying devices, although it is less straightforward at the second and third larval stages. We found similar body lengths between the two species for all developmental stages, except for third instar larvae prior to pupation. In the two species the difference in larval body length before pupation positively correlated with that of the adult beetles. More than 70% of the adults' length can be explained by the length of the late third-instar larva; i.e. the large larvae develop into large adults. The larger specimens are the females.
Home ranges of lions in the Kalahari, Botswana exhibit vast sizes and high temporal variability.
Zehnder, André; Henley, Stephen; Weibel, Robert
2018-06-01
The central Kalahari region in Botswana is one of the few remaining ecosystems with a stable lion population. Yet, relatively little is known about the ecology of the lions there. As an entry point, home range estimations provide information about the space utilization of the studied animals. The home ranges of eight lions in this region were determined to investigate their spatial overlaps and spatiotemporal variations. We found that, except for MCP, all home range estimators yielded comparable results regarding size and shape. The home ranges of all individuals were located predominantly inside the protected reserves. Their areas were among the largest known for lions with 1131 - 4314km 2 (95%), with no significant differences between males and females. Numerous overlaps between lions of different sexes were detected, although these originate from different groups. A distance chart confirmed that most of these lions directly encountered each other once or several times. Strong temporal variations of the home ranges were observed that did not match a seasonal pattern. The exceptionally large home ranges are likely to be caused by the sparse and dynamic prey populations. Since the ungulates in the study area move in an opportunistic way, too, strong spatiotemporal home range variations emerge. This can lead to misleading home ranges. We therefore recommend clarifying the stability of the home ranges by applying several levels of temporal aggregation. The lack of strict territoriality is likely an adaptation to the variable prey base and the high energetic costs associated with defending a large area. Copyright © 2018 Elsevier GmbH. All rights reserved.
Assessment of bone biopsy needles for sample size, specimen quality and ease of use
International Nuclear Information System (INIS)
Roberts, C.C.; Liu, P.T.; Morrison, W.B.; Leslie, K.O.; Carrino, J.A.; Lozevski, J.L.
2005-01-01
To assess whether there are significant differences in ease of use and quality of samples among several bone biopsy needles currently available. Eight commonly used, commercially available bone biopsy needles of different gauges were evaluated. Each needle was used to obtain five consecutive samples from a lamb lumbar pedicle. Subjective assessment of ease of needle use, ease of sample removal from the needle and sample quality, before and after fixation, was graded on a 5-point scale. The number of attempts necessary to reach a 1 cm depth was recorded. Each biopsy specimen was measured in the gross state and after fixation. The RADI Bonopty 15 g and Kendall Monoject J-type 11 g needles were rated the easiest to use, while the Parallax Core-Assure 11 g and the Bard Ostycut 16 g were rated the most difficult. Parallax Core-Assure and Kendall Monoject needles had the highest quality specimen in the gross state; Cook Elson/Ackerman 14 g and Bard Ostycut 16 g needles yielded the lowest. The MD Tech without Trap-Lok 11 g needle had the highest quality core after fixation, while the Bard Ostycut 16 g had the lowest. There was a significant difference in pre-fixation sample length between needles (P<0.0001), despite acquiring all cores to a standard 1 cm depth. Core length and width decrease in size by an average of 28% and 42% after fixation. Bone biopsy needles vary significantly in performance. Detailed knowledge of the strengths and weaknesses of different needles is important to make an appropriate selection for each individual's practice. (orig.)
The predicted CLARREO sampling error of the inter-annual SW variability
Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.
2009-12-01
The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as
The MEXSAS2 Sample and the Ensemble X-ray Variability of Quasars
Energy Technology Data Exchange (ETDEWEB)
Serafinelli, Roberto [Dipartimento di Fisica, Università di Roma Tor Vergata, Rome (Italy); Dipartimento di Fisica, Università di Roma Sapienza, Rome (Italy); Vagnetti, Fausto; Chiaraluce, Elia [Dipartimento di Fisica, Università di Roma Tor Vergata, Rome (Italy); Middei, Riccardo, E-mail: roberto.serafinelli@roma2.infn.it [Dipartimento di Matematica e Fisica, Università Roma Tre, Rome (Italy)
2017-10-11
We present the second Multi-Epoch X-ray Serendipitous AGN Sample (MEXSAS2), extracted from the 6th release of the XMM Serendipitous Source Catalog (XMMSSC-DR6), cross-matched with Sloan Digital Sky Survey quasar Catalogs DR7Q and DR12Q. Our sample also includes the available measurements for masses, bolometric luminosities, and Eddington ratios. Analyses of the ensemble structure function and spectral variability are presented, together with their dependences on such parameters. We confirm a decrease of the structure function with the X-ray luminosity, and find a weak dependence on the black hole mass. We introduce a new spectral variability estimator, taking errors on both fluxes and spectral indices into account. We confirm an ensemble softer when brighter trend, with no dependence of such estimator on black hole mass, Eddington ratio, redshift, X-ray and bolometric luminosity.
The MEXSAS2 Sample and the Ensemble X-ray Variability of Quasars
Directory of Open Access Journals (Sweden)
Roberto Serafinelli
2017-10-01
Full Text Available We present the second Multi-Epoch X-ray Serendipitous AGN Sample (MEXSAS2, extracted from the 6th release of the XMM Serendipitous Source Catalog (XMMSSC-DR6, cross-matched with Sloan Digital Sky Survey quasar Catalogs DR7Q and DR12Q. Our sample also includes the available measurements for masses, bolometric luminosities, and Eddington ratios. Analyses of the ensemble structure function and spectral variability are presented, together with their dependences on such parameters. We confirm a decrease of the structure function with the X-ray luminosity, and find a weak dependence on the black hole mass. We introduce a new spectral variability estimator, taking errors on both fluxes and spectral indices into account. We confirm an ensemble softer when brighter trend, with no dependence of such estimator on black hole mass, Eddington ratio, redshift, X-ray and bolometric luminosity.
Effects of sample size on estimation of rainfall extremes at high temperatures
Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik
2017-09-01
High precipitation quantiles tend to rise with temperature, following the so-called Clausius-Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.
Effects of sample size on estimation of rainfall extremes at high temperatures
Directory of Open Access Journals (Sweden)
B. Boessenkool
2017-09-01
Full Text Available High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.
Olson, S A; Bay, B K; Pollak, A N; Sharkey, N A; Lee, T
1996-01-01
The indications for open reduction and internal fixation of posterior wall acetabular fractures associated with a clinically stable hip joint are unclear. In previous work a large posterior wall defect (27% articular surface area) resulted in significant alteration of load transmission across the hip; specifically, there was a transition from evenly distributed loading along the acetabular articular surface to loading concentrated mainly in the superior portion of the articular surface during simulated single leg stance. However, the majority of posterior wall fractures involve a smaller amount of the articular surface. Posterior wall acetabular fractures not associated with instability of the hip are commonly treated nonoperatively. This practice does not account for the size of the posterior wall fracture. To study the biomechanical consequences of variably sized articular defects, a laboratory experiment was conducted evaluating three progressively larger posterior wall defects of the acetabulum during simulated single leg stance using superlow Fuji prescale film (Itochu International, New York): (a) 1/3 articular surface width through a 50 degrees arc along the posterior wall of the acetabulum, (b) 2/3, and (c) 3/3 articular width defects through the same 50 degrees arc along the posterior wall of the acetabulum. In the intact acetabulum, 48% of the total articular contact was located in the superior acetabulum. Twenty-eight percent of articular contact was in the anterior wall region of the acetabulum and 24% in the posterior wall region. After the 1/3 width posterior wall defect, 64% of the articular contact was located in the superior acetabulum (p = 0.0011). The 2/3 width posterior wall defect resulted in 71% of articular contact area being located in the superior acetabulum (p = 0.0006). After the 3/3 width posterior wall defect, 77% of articular contact was located in the superior acetabulum, significantly greater than the intact condition (p < 0
Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.
Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E
2015-09-03
Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
What about N? A methodological study of sample-size reporting in focus group studies.
Carlsen, Benedicte; Glenton, Claire
2011-03-11
Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96). Thirty seven (17%) studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Based on these findings we suggest that journals adopt more stringent requirements for focus group method reporting. The often poor and inconsistent reporting seen in these
What about N? A methodological study of sample-size reporting in focus group studies
Directory of Open Access Journals (Sweden)
Glenton Claire
2011-03-01
Full Text Available Abstract Background Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. Results We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96. Thirty seven (17% studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Conclusions Based on these findings we suggest that journals adopt more stringent requirements for focus group method
Bender, Christopher M; Ballard, Megan S; Wilson, Preston S
2014-06-01
The overall goal of this work is to quantify the effects of environmental variability and spatial sampling on the accuracy and uncertainty of estimates of the three-dimensional ocean sound-speed field. In this work, ocean sound speed estimates are obtained with acoustic data measured by a sparse autonomous observing system using a perturbative inversion scheme [Rajan, Lynch, and Frisk, J. Acoust. Soc. Am. 82, 998-1017 (1987)]. The vertical and horizontal resolution of the solution depends on the bandwidth of acoustic data and on the quantity of sources and receivers, respectively. Thus, for a simple, range-independent ocean sound speed profile, a single source-receiver pair is sufficient to estimate the water-column sound-speed field. On the other hand, an environment with significant variability may not be fully characterized by a large number of sources and receivers, resulting in uncertainty in the solution. This work explores the interrelated effects of environmental variability and spatial sampling on the accuracy and uncertainty of the inversion solution though a set of case studies. Synthetic data representative of the ocean variability on the New Jersey shelf are used.
Lee, Paul H; Tse, Andy C Y
2017-05-01
There are limited data on the quality of reporting of information essential for replication of the calculation as well as the accuracy of the sample size calculation. We examine the current quality of reporting of the sample size calculation in randomized controlled trials (RCTs) published in PubMed and to examine the variation in reporting across study design, study characteristics, and journal impact factor. We also reviewed the targeted sample size reported in trial registries. We reviewed and analyzed all RCTs published in December 2014 with journals indexed in PubMed. The 2014 Impact Factors for the journals were used as proxies for their quality. Of the 451 analyzed papers, 58.1% reported an a priori sample size calculation. Nearly all papers provided the level of significance (97.7%) and desired power (96.6%), and most of the papers reported the minimum clinically important effect size (73.3%). The median (inter-quartile range) of the percentage difference of the reported and calculated sample size calculation was 0.0% (IQR -4.6%;3.0%). The accuracy of the reported sample size was better for studies published in journals that endorsed the CONSORT statement and journals with an impact factor. A total of 98 papers had provided targeted sample size on trial registries and about two-third of these papers (n=62) reported sample size calculation, but only 25 (40.3%) had no discrepancy with the reported number in the trial registries. The reporting of the sample size calculation in RCTs published in PubMed-indexed journals and trial registries were poor. The CONSORT statement should be more widely endorsed. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
A Model Based Approach to Sample Size Estimation in Recent Onset Type 1 Diabetes
Bundy, Brian; Krischer, Jeffrey P.
2016-01-01
The area under the curve C-peptide following a 2-hour mixed meal tolerance test from 481 individuals enrolled on 5 prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrollment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in Observed vs. Expected calculations to estimate the presumption of benefit in ongoing trials. PMID:26991448
A model-based approach to sample size estimation in recent onset type 1 diabetes.
Bundy, Brian N; Krischer, Jeffrey P
2016-11-01
The area under the curve C-peptide following a 2-h mixed meal tolerance test from 498 individuals enrolled on five prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrolment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors, and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in observed versus expected calculations to estimate the presumption of benefit in ongoing trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
The Macdonald and Savage titrimetric procedure scaled down to 4 mg sized plutonium samples. P. 1
International Nuclear Information System (INIS)
Kuvik, V.; Lecouteux, C.; Doubek, N.; Ronesch, K.; Jammet, G.; Bagliano, G.; Deron, S.
1992-01-01
The original Macdonald and Savage amperometric method scaled down to milligram-sized plutonium samples was further modified. The electro-chemical process of each redox step and the end-point of the final titration were monitored potentiometrically. The method is designed to determine 4 mg of plutonium dissolved in nitric acid solution. It is suitable for the direct determination of plutonium in non-irradiated fuel with a uranium-to-plutonium ratio of up to 30. The precision and accuracy are ca. 0.05-0.1% (relative standard deviation). Although the procedure is very selective, the following species interfere: vanadyl(IV) and vanadate (almost quantitatively), neptunium (one electron exchange per mole), nitrites, fluorosilicates (milligram amounts yield a slight bias) and iodates. (author). 15 refs.; 8 figs.; 7 tabs
Dental arch dimensions, form and tooth size ratio among a Saudi sample
Directory of Open Access Journals (Sweden)
Haidi Omar
2018-01-01
Full Text Available Objectives: To determine the dental arch dimensions and arch forms in a sample of Saudi orthodontic patients, to investigate the prevalence of Bolton anterior and overall tooth size discrepancies, and to compare the effect of gender on the measured parameters. Methods: This study is a biometric analysis of dental casts of 149 young adults recruited from different orthodontic centers in Jeddah, Saudi Arabia. The dental arch dimensions were measured. The measured parameters were arch length, arch width, Bolton’s ratio, and arch form. The data were analyzed using IBM SPSS software version 22.0 (IBM Corporation, New York, USA; this cross-sectional study was conducted between April 2015 and May 2016. Results: Dental arch measurements, including inter-canine and inter-molar distance, were found to be significantly greater in males than females (p less than 0.05. The most prevalent dental arch forms were narrow tapered (50.3% and narrow ovoid (34.2%, respectively. The prevalence of tooth size discrepancy in all cases was 43.6% for anterior ratio and 24.8% for overall ratio. The mean Bolton’s anterior ratio in all malocclusion classes was 79.81%, whereas the mean Bolton’s overall ratio was 92.21%. There was no significant difference between males and females regarding Bolton’s ratio. Conclusion: The most prevalent arch form was narrow tapered, followed by narrow ovoid. Males generally had larger dental arch measurements than females, and the prevalence of tooth size discrepancy was more in Bolton’s anterior teeth ratio than in overall ratio.
Mori, T.; Moteki, N.; Ohata, S.; Koike, M.; Azuma, K. G.; Miyazaki, Y.; Kondo, Y.
2015-12-01
Black carbon (BC) is the strongest contributor to sunlight absorption among atmospheric aerosols. Quantitative understanding of wet deposition of BC, which strongly affects the spatial distribution of BC, is important to improve our understandings on climate change. We have devised a technique for measuring the masses of individual BC particles in rainwater and snow samples, as a combination of a nebulizer and a single-particle soot photometer (SP2) (Ohata et al. 2011, 2013; Schwarz et al. 2012; Mori et al. 2014). We show two important improvements in this technique: 1)We have extended the upper limit of detectable BC particle diameter from 0.9 μm to about 4.0 μm by modifying the photodetector for measuring the laser-induced incandescence signal. 2)We introduced a pneumatic nebulizer Marin-5 (Cetac Technologies Inc., Omaha, NE, USA) and experimentally confirmed its high extraction efficiency (~50%) independent of particle diameter up to 2.0 μm. Using our improved system, we simultaneously measured the size distribution of BC particles in air and rainwater in Tokyo. We observed that the size distribution of BC in rainwater was larger than that in air, indicating that large BC particles were effectively removed by precipitation. We also observed BC particles with diameters larger than 1.0 μm, indicating that further studies of wet deposition of BC will require the use of the modified SP2.
Hua, Xue; Hibar, Derrek P; Ching, Christopher R K; Boyle, Christina P; Rajagopalan, Priya; Gutman, Boris A; Leow, Alex D; Toga, Arthur W; Jack, Clifford R; Harvey, Danielle; Weiner, Michael W; Thompson, Paul M
2013-02-01
Various neuroimaging measures are being evaluated for tracking Alzheimer's disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI. Copyright © 2012 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Darcel, C. (Itasca Consultants SAS (France)); Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O. (Geosciences Rennes, UMR 6118 CNRS, Univ. def Rennes, Rennes (France))
2009-11-15
Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k{sub t} close to 1.2 with a density term (alpha{sub 2d}) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k{sub t} close to 3 and a density term (alpha{sub 2d}) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k{sub t} equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k{sub t} = 1.2) on one side, to
International Nuclear Information System (INIS)
Darcel, C.; Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O.
2009-11-01
Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k t close to 1.2 with a density term (α 2d ) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k t close to 3 and a density term (α 2d ) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k t equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k t = 1.2) on one side, to the lineament scale (k t = 2) on
Brooks, Mollie E; Mugabo, Marianne; Rodgers, Gwendolen M; Benton, Timothy G; Ozgul, Arpat
2016-03-01
Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.
Weighted piecewise LDA for solving the small sample size problem in face verification.
Kyperountas, Marios; Tefas, Anastasios; Pitas, Ioannis
2007-03-01
A novel algorithm that can be used to boost the performance of face-verification methods that utilize Fisher's criterion is presented and evaluated. The algorithm is applied to similarity, or matching error, data and provides a general solution for overcoming the "small sample size" (SSS) problem, where the lack of sufficient training samples causes improper estimation of a linear separation hyperplane between the classes. Two independent phases constitute the proposed method. Initially, a set of weighted piecewise discriminant hyperplanes are used in order to provide a more accurate discriminant decision than the one produced by the traditional linear discriminant analysis (LDA) methodology. The expected classification ability of this method is investigated throughout a series of simulations. The second phase defines proper combinations for person-specific similarity scores and describes an outlier removal process that further enhances the classification ability. The proposed technique has been tested on the M2VTS and XM2VTS frontal face databases. Experimental results indicate that the proposed framework greatly improves the face-verification performance.
Taisova, A S; Yakovlev, A G; Fetisova, Z G
2014-03-01
This work continuous a series of studies devoted to discovering principles of organization of natural antennas in photosynthetic microorganisms that generate in vivo large and highly effective light-harvesting structures. The largest antenna is observed in green photosynthesizing bacteria, which are able to grow over a wide range of light intensities and adapt to low intensities by increasing of size of peripheral BChl c/d/e antenna. However, increasing antenna size must inevitably cause structural changes needed to maintain high efficiency of its functioning. Our model calculations have demonstrated that aggregation of the light-harvesting antenna pigments represents one of the universal structural factors that optimize functioning of any antenna and manage antenna efficiency. If the degree of aggregation of antenna pigments is a variable parameter, then efficiency of the antenna increases with increasing size of a single aggregate of the antenna. This means that change in degree of pigment aggregation controlled by light-harvesting antenna size is biologically expedient. We showed in our previous work on the oligomeric chlorosomal BChl c superantenna of green bacteria of the Chloroflexaceae family that this principle of optimization of variable antenna structure, whose size is controlled by light intensity during growth of bacteria, is actually realized in vivo. Studies of this phenomenon are continued in the present work, expanding the number of studied biological materials and investigating optical linear and nonlinear spectra of chlorosomes having different structures. We show for oligomeric chlorosomal superantennas of green bacteria (from two different families, Chloroflexaceae and Oscillochloridaceae) that a single BChl c aggregate is of small size, and the degree of BChl c aggregation is a variable parameter, which is controlled by the size of the entire BChl c superantenna, and the latter, in turn, is controlled by light intensity in the course of cell
MEASURING X-RAY VARIABILITY IN FAINT/SPARSELY SAMPLED ACTIVE GALACTIC NUCLEI
Energy Technology Data Exchange (ETDEWEB)
Allevato, V. [Department of Physics, University of Helsinki, Gustaf Haellstroemin katu 2a, FI-00014 Helsinki (Finland); Paolillo, M. [Department of Physical Sciences, University Federico II, via Cinthia 6, I-80126 Naples (Italy); Papadakis, I. [Department of Physics and Institute of Theoretical and Computational Physics, University of Crete, 71003 Heraklion (Greece); Pinto, C. [SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584-CA Utrecht (Netherlands)
2013-07-01
We study the statistical properties of the normalized excess variance of variability process characterized by a ''red-noise'' power spectral density (PSD), as in the case of active galactic nuclei (AGNs). We perform Monte Carlo simulations of light curves, assuming both a continuous and a sparse sampling pattern and various signal-to-noise ratios (S/Ns). We show that the normalized excess variance is a biased estimate of the variance even in the case of continuously sampled light curves. The bias depends on the PSD slope and on the sampling pattern, but not on the S/N. We provide a simple formula to account for the bias, which yields unbiased estimates with an accuracy better than 15%. We show that the normalized excess variance estimates based on single light curves (especially for sparse sampling and S/N < 3) are highly uncertain (even if corrected for bias) and we propose instead the use of an ''ensemble estimate'', based on multiple light curves of the same object, or on the use of light curves of many objects. These estimates have symmetric distributions, known errors, and can also be corrected for biases. We use our results to estimate the ability to measure the intrinsic source variability in current data, and show that they could also be useful in the planning of the observing strategy of future surveys such as those provided by X-ray missions studying distant and/or faint AGN populations and, more in general, in the estimation of the variability amplitude of sources that will result from future surveys such as Pan-STARRS and LSST.
Simultaneous multicopter-based air sampling and sensing of meteorological variables
Brosy, Caroline; Krampf, Karina; Zeeman, Matthias; Wolf, Benjamin; Junkermann, Wolfgang; Schäfer, Klaus; Emeis, Stefan; Kunstmann, Harald
2017-08-01
The state and composition of the lowest part of the planetary boundary layer (PBL), i.e., the atmospheric surface layer (SL), reflects the interactions of external forcing, land surface, vegetation, human influence and the atmosphere. Vertical profiles of atmospheric variables in the SL at high spatial (meters) and temporal (1 Hz and better) resolution increase our understanding of these interactions but are still challenging to measure appropriately. Traditional ground-based observations include towers that often cover only a few measurement heights at a fixed location. At the same time, most remote sensing techniques and aircraft measurements have limitations to achieve sufficient detail close to the ground (up to 50 m). Vertical and horizontal transects of the PBL can be complemented by unmanned aerial vehicles (UAV). Our aim in this case study is to assess the use of a multicopter-type UAV for the spatial sampling of air and simultaneously the sensing of meteorological variables for the study of the surface exchange processes. To this end, a UAV was equipped with onboard air temperature and humidity sensors, while wind conditions were determined from the UAV's flight control sensors. Further, the UAV was used to systematically change the location of a sample inlet connected to a sample tube, allowing the observation of methane abundance using a ground-based analyzer. Vertical methane gradients of about 0.3 ppm were found during stable atmospheric conditions. Our results showed that both methane and meteorological conditions were in agreement with other observations at the site during the ScaleX-2015 campaign. The multicopter-type UAV was capable of simultaneous in situ sensing of meteorological state variables and sampling of air up to 50 m above the surface, which extended the vertical profile height of existing tower-based infrastructure by a factor of 5.
Fan, Chunpeng; Zhang, Donghui
2012-01-01
Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.
Size-exclusion chromatography-based enrichment of extracellular vesicles from urine samples
Directory of Open Access Journals (Sweden)
Inés Lozano-Ramos
2015-05-01
Full Text Available Renal biopsy is the gold-standard procedure to diagnose most of renal pathologies. However, this invasive method is of limited repeatability and often describes an irreversible renal damage. Urine is an easily accessible fluid and urinary extracellular vesicles (EVs may be ideal to describe new biomarkers associated with renal pathologies. Several methods to enrich EVs have been described. Most of them contain a mixture of proteins, lipoproteins and cell debris that may be masking relevant biomarkers. Here, we evaluated size-exclusion chromatography (SEC as a suitable method to isolate urinary EVs. Following a conventional centrifugation to eliminate cell debris and apoptotic bodies, urine samples were concentrated using ultrafiltration and loaded on a SEC column. Collected fractions were analysed by protein content and flow cytometry to determine the presence of tetraspanin markers (CD63 and CD9. The highest tetraspanin content was routinely detected in fractions well before the bulk of proteins eluted. These tetraspanin-peak fractions were analysed by cryo-electron microscopy (cryo-EM and nanoparticle tracking analysis revealing the presence of EVs.When analysed by sodium dodecyl sulphate–polyacrylamide gel electrophoresis, tetraspanin-peak fractions from urine concentrated samples contained multiple bands but the main urine proteins (such as Tamm–Horsfall protein were absent. Furthermore, a preliminary proteomic study of these fractions revealed the presence of EV-related proteins, suggesting their enrichment in concentrated samples. In addition, RNA profiling also showed the presence of vesicular small RNA species.To summarize, our results demonstrated that concentrated urine followed by SEC is a suitable option to isolate EVs with low presence of soluble contaminants. This methodology could permit more accurate analyses of EV-related biomarkers when further characterized by -omics technologies compared with other approaches.
Computation of Effect Size for Moderating Effects of Categorical Variables in Multiple Regression
Aguinis, Herman; Pierce, Charles A.
2006-01-01
The computation and reporting of effect size estimates is becoming the norm in many journals in psychology and related disciplines. Despite the increased importance of effect sizes, researchers may not report them or may report inaccurate values because of a lack of appropriate computational tools. For instance, Pierce, Block, and Aguinis (2004)…
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....
Energy Technology Data Exchange (ETDEWEB)
Baeza, A.; Corbacho, J.A. [LARUEX, Caceres (Spain). Environmental Radioactivity Lab.
2013-07-01
Determining the gross alpha activity concentration of water samples is one way to screen for waters whose radionuclide content is so high that its consumption could imply surpassing the Total Indicative Dose as defined in European Directive 98/83/EC. One of the most commonly used methods to prepare the sources to measure gross alpha activity in water samples is desiccation. Its main advantages are the simplicity of the procedure, the low cost of source preparation, and the possibility of simultaneously determining the gross beta activity. The preparation of the source, the construction of the calibration curves, and the measurement procedure itself involve, however, various factors that may introduce sufficient variability into the results to significantly affect the screening process. We here identify the main sources of this variability, and propose specific procedures to follow in the desiccation process that will reduce the uncertainties, and ensure that the result is indeed representative of the sum of the activities of the alpha emitters present in the sample. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)
2012-01-10
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
International Nuclear Information System (INIS)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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/
HLA-E regulatory and coding region variability and haplotypes in a Brazilian population sample.
Ramalho, Jaqueline; Veiga-Castelli, Luciana C; Donadi, Eduardo A; Mendes-Junior, Celso T; Castelli, Erick C
2017-11-01
The HLA-E gene is characterized by low but wide expression on different tissues. HLA-E is considered a conserved gene, being one of the least polymorphic class I HLA genes. The HLA-E molecule interacts with Natural Killer cell receptors and T lymphocytes receptors, and might activate or inhibit immune responses depending on the peptide associated with HLA-E and with which receptors HLA-E interacts to. Variable sites within the HLA-E regulatory and coding segments may influence the gene function by modifying its expression pattern or encoded molecule, thus, influencing its interaction with receptors and the peptide. Here we propose an approach to evaluate the gene structure, haplotype pattern and the complete HLA-E variability, including regulatory (promoter and 3'UTR) and coding segments (with introns), by using massively parallel sequencing. We investigated the variability of 420 samples from a very admixed population such as Brazilians by using this approach. Considering a segment of about 7kb, 63 variable sites were detected, arranged into 75 extended haplotypes. We detected 37 different promoter sequences (but few frequent ones), 27 different coding sequences (15 representing new HLA-E alleles) and 12 haplotypes at the 3'UTR segment, two of them presenting a summed frequency of 90%. Despite the number of coding alleles, they encode mainly two different full-length molecules, known as E*01:01 and E*01:03, which corresponds to about 90% of all. In addition, differently from what has been previously observed for other non classical HLA genes, the relationship among the HLA-E promoter, coding and 3'UTR haplotypes is not straightforward because the same promoter and 3'UTR haplotypes were many times associated with different HLA-E coding haplotypes. This data reinforces the presence of only two main full-length HLA-E molecules encoded by the many HLA-E alleles detected in our population sample. In addition, this data does indicate that the distal HLA-E promoter is by
Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli
2018-01-01
Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis; Ketcheson, David I.; Loczi, Lajos; Né meth, Adriá n
2016-01-01
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order
Directory of Open Access Journals (Sweden)
James C Wallace
Full Text Available Whole-metagenome sequencing (WMS has emerged as a powerful tool to assess potential public health risks in marine environments by measuring changes in microbial community structure and function in uncultured bacteria. In addition to monitoring public health risks such as antibiotic resistance determinants, it is essential to measure predictors of microbial variation in order to identify natural versus anthropogenic factors as well as to evaluate reproducibility of metagenomic measurements.This study expands our previous metagenomic characterization of Puget Sound by sampling new nearshore environments including the Duwamish River, an EPA superfund site, and the Hood Canal, an area characterized by highly variable oxygen levels. We also resampled a wastewater treatment plant, nearshore and open ocean sites introducing a longitudinal component measuring seasonal and locational variations and establishing metagenomics sampling reproducibility. Microbial composition from samples collected in the open sound were highly similar within the same season and location across different years, while nearshore samples revealed multi-fold seasonal variation in microbial composition and diversity. Comparisons with recently sequenced predominant marine bacterial genomes helped provide much greater species level taxonomic detail compared to our previous study. Antibiotic resistance determinants and pollution and detoxification indicators largely grouped by location showing minor seasonal differences. Metal resistance, oxidative stress and detoxification systems showed no increase in samples proximal to an EPA superfund site indicating a lack of ecosystem adaptation to anthropogenic impacts. Taxonomic analysis of common sewage influent families showed a surprising similarity between wastewater treatment plant and open sound samples suggesting a low-level but pervasive sewage influent signature in Puget Sound surface waters. Our study shows reproducibility of
Olneck, Michael R.; Bills, David B.
1979-01-01
Birth order effects in brothers were found to derive from difference in family size. Effects for family size were found even with socioeconomic background controlled. Nor were family size effects explained by parental ability. The importance of unmeasured preferences or economic resources that vary across families was suggested. (Author/RD)
Neggers, R.
2017-12-01
Recent advances in supercomputing have introduced a "grey zone" in the representation of cumulus convection in general circulation models, in which this process is partially resolved. Cumulus parameterizations need to be made scale-aware and scale-adaptive to be able to conceptually and practically deal with this situation. A potential way forward are schemes formulated in terms of discretized Cloud Size Densities, or CSDs. Advantages include i) the introduction of scale-awareness at the foundation of the scheme, and ii) the possibility to apply size-filtering of parameterized convective transport and clouds. The CSD is a new variable that requires closure; this concerns its shape, its range, but also variability in cloud number that can appear due to i) subsampling effects and ii) organization in a cloud field. The goal of this study is to gain insight by means of sub-domain analyses of various large-domain LES realizations of cumulus cloud populations. For a series of three-dimensional snapshots, each with a different degree of organization, the cloud size distribution is calculated in all subdomains, for a range of subdomain sizes. The standard deviation of the number of clouds of a certain size is found to decrease with the subdomain size, following a powerlaw scaling corresponding to an inverse-linear dependence. Cloud number variability also increases with cloud size; this reflects that subsampling affects the largest clouds first, due to their typically larger neighbor spacing. Rewriting this dependence in terms of two dimensionless groups, by dividing by cloud number and cloud size respectively, yields a data collapse. Organization in the cloud field is found to act on top of this primary dependence, by enhancing the cloud number variability at the smaller sizes. This behavior reflects that small clouds start to "live" on top of larger structures such as cold pools, favoring or inhibiting their formation (as illustrated by the attached figure of cloud mask
Directory of Open Access Journals (Sweden)
Elsa Tavernier
Full Text Available We aimed to examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial (RCT. In a simulation study, we separately considered an RCT with continuous, dichotomous or time-to-event outcomes, with associated nuisance parameters of standard deviation, success rate in the control group and survival rate in the control group at some time point, respectively. For each type of outcome, we calculated a required sample size N for a hypothesized treatment effect, an assumed nuisance parameter and a nominal power of 80%. We then assumed a nuisance parameter associated with a relative error at the design stage. For each type of outcome, we randomly drew 10,000 relative errors of the associated nuisance parameter (from empirical distributions derived from a previously published review. Then, retro-fitting the sample size formula, we derived, for the pre-calculated sample size N, the real power of the RCT, taking into account the relative error for the nuisance parameter. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was 90%. Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. Such findings raise questions about how sample size for RCTs should be determined.
Shi, Guo-Liang; Tian, Ying-Ze; Ma, Tong; Song, Dan-Lin; Zhou, Lai-Dong; Han, Bo; Feng, Yin-Chang; Russell, Armistead G
2017-06-01
Long-term and synchronous monitoring of PM 10 and PM 2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM 10 , and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM 2.5 . Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM 10 , and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM 2.5 . The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM 10 (12.7%) and PM 2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM 10 (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM 2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies. Copyright © 2016. Published by Elsevier B.V.
Tree-ring C-H-O isotope variability and sampling
International Nuclear Information System (INIS)
Leavitt, Steven W.
2010-01-01
In light of the proliferation of tree-ring isotope studies, the magnitude and cause of variability of tree-ring δ 13 C, δ 18 O and δ 2 H within individual trees (circumferential) and among trees at a site is examined in reference to field and laboratory sampling requirements and strategies. Within this framework, this paper provides a state-of-knowledge summary of the influence of 'juvenile' isotope effects, ageing effects, and genetic effects, as well as the interchangeability of species, choice of ring segment to analyze (whole ring, earlywood or latewood), and the option of sample pooling. The range of isotopic composition of the same ring among trees at a site is ca. 1-3 per mille for δ 13 C, 1-4 per mille δ 18 O, and 5-30 per mille for δ 2 H, whereas the circumferential variability within a tree is lower. A standard prescription for sampling and analysis does not exist because of differences in field environmental circumstances and mixed findings represented in relevant published literature. Decisions in this regard will usually be tightly constrained by goals of the study and project resources. Sampling 4-6 trees at a site while avoiding juvenile effects in rings near the pith seems to be the most commonly used methodology, and although there are some reasoned arguments for analyzing only latewood and developing separate isotope records from each tree, the existence of some contradictory findings together with efforts to reduce cost and effort have prompted alternate strategies (e.g., most years pooled with occasional analysis of rings in the sequence separately for each tree) that have produced useful results in many studies.
Molecular dynamics based enhanced sampling of collective variables with very large time steps
Chen, Pei-Yang; Tuckerman, Mark E.
2018-01-01
Enhanced sampling techniques that target a set of collective variables and that use molecular dynamics as the driving engine have seen widespread application in the computational molecular sciences as a means to explore the free-energy landscapes of complex systems. The use of molecular dynamics as the fundamental driver of the sampling requires the introduction of a time step whose magnitude is limited by the fastest motions in a system. While standard multiple time-stepping methods allow larger time steps to be employed for the slower and computationally more expensive forces, the maximum achievable increase in time step is limited by resonance phenomena, which inextricably couple fast and slow motions. Recently, we introduced deterministic and stochastic resonance-free multiple time step algorithms for molecular dynamics that solve this resonance problem and allow ten- to twenty-fold gains in the large time step compared to standard multiple time step algorithms [P. Minary et al., Phys. Rev. Lett. 93, 150201 (2004); B. Leimkuhler et al., Mol. Phys. 111, 3579-3594 (2013)]. These methods are based on the imposition of isokinetic constraints that couple the physical system to Nosé-Hoover chains or Nosé-Hoover Langevin schemes. In this paper, we show how to adapt these methods for collective variable-based enhanced sampling techniques, specifically adiabatic free-energy dynamics/temperature-accelerated molecular dynamics, unified free-energy dynamics, and by extension, metadynamics, thus allowing simulations employing these methods to employ similarly very large time steps. The combination of resonance-free multiple time step integrators with free-energy-based enhanced sampling significantly improves the efficiency of conformational exploration.
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.
Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun
2014-01-01
Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in ...
Peter, Emanuel K.
2017-12-01
In this article, we present a novel adaptive enhanced sampling molecular dynamics (MD) method for the accelerated simulation of protein folding and aggregation. We introduce a path-variable L based on the un-biased momenta p and displacements dq for the definition of the bias s applied to the system and derive 3 algorithms: general adaptive bias MD, adaptive path-sampling, and a hybrid method which combines the first 2 methodologies. Through the analysis of the correlations between the bias and the un-biased gradient in the system, we find that the hybrid methodology leads to an improved force correlation and acceleration in the sampling of the phase space. We apply our method on SPC/E water, where we find a conservation of the average water structure. We then use our method to sample dialanine and the folding of TrpCage, where we find a good agreement with simulation data reported in the literature. Finally, we apply our methodologies on the initial stages of aggregation of a hexamer of Alzheimer's amyloid β fragment 25-35 (Aβ 25-35) and find that transitions within the hexameric aggregate are dominated by entropic barriers, while we speculate that especially the conformation entropy plays a major role in the formation of the fibril as a rate limiting factor.
A recurrent neural network for classification of unevenly sampled variable stars
Naul, Brett; Bloom, Joshua S.; Pérez, Fernando; van der Walt, Stéfan
2018-02-01
Astronomical surveys of celestial sources produce streams of noisy time series measuring flux versus time (`light curves'). Unlike in many other physical domains, however, large (and source-specific) temporal gaps in data arise naturally due to intranight cadence choices as well as diurnal and seasonal constraints1-5. With nightly observations of millions of variable stars and transients from upcoming surveys4,6, efficient and accurate discovery and classification techniques on noisy, irregularly sampled data must be employed with minimal human-in-the-loop involvement. Machine learning for inference tasks on such data traditionally requires the laborious hand-coding of domain-specific numerical summaries of raw data (`features')7. Here, we present a novel unsupervised autoencoding recurrent neural network8 that makes explicit use of sampling times and known heteroskedastic noise properties. When trained on optical variable star catalogues, this network produces supervised classification models that rival other best-in-class approaches. We find that autoencoded features learned in one time-domain survey perform nearly as well when applied to another survey. These networks can continue to learn from new unlabelled observations and may be used in other unsupervised tasks, such as forecasting and anomaly detection.
DEFF Research Database (Denmark)
Wünsch, Urban; Murphy, Kathleen R.; Stedmon, Colin
2017-01-01
Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM...... but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical...... opportunities for elucidating the origins and biogeochemical properties of FDOM...
Kondapalli, S. P.
2017-12-01
In the present work, pulsed current microplasma arc welding is carried out on AISI 321 austenitic stainless steel of 0.3 mm thickness. Peak current, Base current, Pulse rate and Pulse width are chosen as the input variables, whereas grain size and hardness are considered as output responses. Response surface method is adopted by using Box-Behnken Design, and in total 27 experiments are performed. Empirical relation between input and output response is developed using statistical software and analysis of variance (ANOVA) at 95% confidence level to check the adequacy. The main effect and interaction effect of input variables on output response are also studied.
Directory of Open Access Journals (Sweden)
Ming-Yen Tsai
Full Text Available OBJECTIVES: The Meridian Energy Analysis Device is currently a popular tool in the scientific research of meridian electrophysiology. In this field, it is generally believed that measuring the electrical conductivity of meridians provides information about the balance of bioenergy or Qi-blood in the body. METHODS AND RESULTS: PubMed database based on some original articles from 1956 to 2014 and the authoŕs clinical experience. In this short communication, we provide clinical examples of Meridian Energy Analysis Device application, especially in the field of traditional Chinese medicine, discuss the reliability of the measurements, and put the values obtained into context by considering items of considerable variability and by estimating sample size. CONCLUSION: The Meridian Energy Analysis Device is making a valuable contribution to the diagnosis of Qi-blood dysfunction. It can be assessed from short-term and long-term meridian bioenergy recordings. It is one of the few methods that allow outpatient traditional Chinese medicine diagnosis, monitoring the progress, therapeutic effect and evaluation of patient prognosis. The holistic approaches underlying the practice of traditional Chinese medicine and new trends in modern medicine toward the use of objective instruments require in-depth knowledge of the mechanisms of meridian energy, and the Meridian Energy Analysis Device can feasibly be used for understanding and interpreting traditional Chinese medicine theory, especially in view of its expansion in Western countries.
International Nuclear Information System (INIS)
Avni, Y.; Bahcall, J.N.
1979-01-01
Methods for applying the V/Vsub(max) variable when several complete samples are analyzed simultaneously are derived. A new, related, variable Vsub(e)/Vsub(a), which is superior to V/Vsub(max) when sufficient observational data are available, is introduced. It is shown that statistically independent complete samples can be generated from partially overlapping samples such that each observed object appears only once in the analysis. These methods make it possible to combine the information from different complete samples, and to make an efficient use of all available data. Illustrative examples for quasars are given. It is shown how the generalized V/Vsub(max) and Vsub(e)/Vsub(a) can be used to find the amount of cosmological evolution of quasars and its associated range of uncertainty. This range of uncertainty is of fundamental importance for theories of quasars and for their cosmological implications. It is also given, for the first time, the formal justification of the V/Vsub(max) (and Vsub(e)/Vsub(a)) test, using a variable-sample-size formalism that allows for the total number of objects in the sample to be a random variable. (author)
Directory of Open Access Journals (Sweden)
Christopher Ryan Penton
2016-06-01
Full Text Available We examined the effect of different soil sample sizes obtained from an agricultural field, under a single cropping system uniform in soil properties and aboveground crop responses, on bacterial and fungal community structure and microbial diversity indices. DNA extracted from soil sample sizes of 0.25, 1, 5 and 10 g using MoBIO kits and from 10 and 100 g sizes using a bead-beating method (SARDI were used as templates for high-throughput sequencing of 16S and 28S rRNA gene amplicons for bacteria and fungi, respectively, on the Illumina MiSeq and Roche 454 platforms. Sample size significantly affected overall bacterial and fungal community structure, replicate dispersion and the number of operational taxonomic units (OTUs retrieved. Richness, evenness and diversity were also significantly affected. The largest diversity estimates were always associated with the 10 g MoBIO extractions with a corresponding reduction in replicate dispersion. For the fungal data, smaller MoBIO extractions identified more unclassified Eukaryota incertae sedis and unclassified glomeromycota while the SARDI method retrieved more abundant OTUs containing unclassified Pleosporales and the fungal genera Alternaria and Cercophora. Overall, these findings indicate that a 10 g soil DNA extraction is most suitable for both soil bacterial and fungal communities for retrieving optimal diversity while still capturing rarer taxa in concert with decreasing replicate variation.
Suarez Diez, M.; Saccenti, E.
2015-01-01
We investigated the effect of sample size and dimensionality on the performance of four algorithms (ARACNE, CLR, CORR, and PCLRC) when they are used for the inference of metabolite association networks. We report that as many as 100-400 samples may be necessary to obtain stable network estimations,
Impedance modulation and feedback corrections in tracking targets of variable size and frequency
Selen, L.P.J.; van Dieen, J.H.; Beek, P.J.
2006-01-01
Humans are able to adjust the accuracy of their movements to the demands posed by the task at hand. The variability in task execution caused by the inherent noisiness of the neuromuscular system can be tuned to task demands by both feedforward (e.g., impedance modulation) and feedback mechanisms. In
Nasta, P.; Romano, N.; Assouline, S; Vrugt, J.A.; Hopmans, J.W.
2013-01-01
Simultaneous scaling of soil water retention and hydraulic conductivity functions provides an effective means to characterize the heterogeneity and spatial variability of soil hydraulic properties in a given study area. The statistical significance of this approach largely depends on the number of
DEFF Research Database (Denmark)
Hanhijärvi, A.; Galimard, P.; Hoffmeyer, Preben
1998-01-01
The paper is the second in a series which sums up the results of an extensive project to quantify the duration-of-load (DOL) effect on different sized timber beams in different climates. The paper deals with straight (unnotched) beams. The results of various DOL-tests of stepwise and constant...
Swallowing thresholds of mandibular implant-retained overdentures with variable portion sizes
Fontijn-Tekamp, F.A.; Slagter, A.P.; Van der Bilt, A.; Van't Hof, M.A.; Kalk, W.; Jansen, J.A.
2004-01-01
We analysed the effect of three portion sizes Optocal Plus (small, medium and large) on swallowing thresholds in subjects with either conventional complete dentures or mandibular implant-retained overdentures (transmandibular and permucosal cylindric implants). Tests were carried out in 52 women and
Size and shape characteristics of drumlins, derived from a large sample, and associated scaling laws
Clark, Chris D.; Hughes, Anna L. C.; Greenwood, Sarah L.; Spagnolo, Matteo; Ng, Felix S. L.
2009-04-01
Ice sheets flowing across a sedimentary bed usually produce a landscape of blister-like landforms streamlined in the direction of the ice flow and with each bump of the order of 10 2 to 10 3 m in length and 10 1 m in relief. Such landforms, known as drumlins, have mystified investigators for over a hundred years. A satisfactory explanation for their formation, and thus an appreciation of their glaciological significance, has remained elusive. A recent advance has been in numerical modelling of the land-forming process. In anticipation of future modelling endeavours, this paper is motivated by the requirement for robust data on drumlin size and shape for model testing. From a systematic programme of drumlin mapping from digital elevation models and satellite images of Britain and Ireland, we used a geographic information system to compile a range of statistics on length L, width W, and elongation ratio E (where E = L/ W) for a large sample. Mean L, is found to be 629 m ( n = 58,983), mean W is 209 m and mean E is 2.9 ( n = 37,043). Most drumlins are between 250 and 1000 metres in length; between 120 and 300 metres in width; and between 1.7 and 4.1 times as long as they are wide. Analysis of such data and plots of drumlin width against length reveals some new insights. All frequency distributions are unimodal from which we infer that the geomorphological label of 'drumlin' is fair in that this is a true single population of landforms, rather than an amalgam of different landform types. Drumlin size shows a clear minimum bound of around 100 m (horizontal). Maybe drumlins are generated at many scales and this is the minimum, or this value may be an indication of the fundamental scale of bump generation ('proto-drumlins') prior to them growing and elongating. A relationship between drumlin width and length is found (with r2 = 0.48) and that is approximately W = 7 L 1/2 when measured in metres. A surprising and sharply-defined line bounds the data cloud plotted in E- W
Critical analysis of consecutive unilateral cleft lip repairs: determining ideal sample size.
Power, Stephanie M; Matic, Damir B
2013-03-01
Objective : Cleft surgeons often show 10 consecutive lip repairs to reduce presentation bias, however the validity remains unknown. The purpose of this study is to determine the number of consecutive cases that represent average outcomes. Secondary objectives are to determine if outcomes correlate with cleft severity and to calculate interrater reliability. Design : Consecutive preoperative and 2-year postoperative photographs of the unilateral cleft lip-nose complex were randomized and evaluated by cleft surgeons. Parametric analysis was performed according to chronologic, consecutive order. The mean standard deviation over all raters enabled calculation of expected 95% confidence intervals around a mean tested for various sample sizes. Setting : Meeting of the American Cleft Palate-Craniofacial Association in 2009. Patients, Participants : Ten senior cleft surgeons evaluated 39 consecutive lip repairs. Main Outcome Measures : Preoperative severity and postoperative outcomes were evaluated using descriptive and quantitative scales. Results : Intraclass correlation coefficients for cleft severity and postoperative evaluations were 0.65 and 0.21, respectively. Outcomes did not correlate with cleft severity (P = .28). Calculations for 10 consecutive cases demonstrated wide 95% confidence intervals, spanning two points on both postoperative grading scales. Ninety-five percent confidence intervals narrowed within one qualitative grade (±0.30) and one point (±0.50) on the 10-point scale for 27 consecutive cases. Conclusions : Larger numbers of consecutive cases (n > 27) are increasingly representative of average results, but less practical in presentation format. Ten consecutive cases lack statistical support. Cleft surgeons showed low interrater reliability for postoperative assessments, which may reflect personal bias when evaluating another surgeon's results.
Reliable calculation in probabilistic logic: Accounting for small sample size and model uncertainty
Energy Technology Data Exchange (ETDEWEB)
Ferson, S. [Applied Biomathematics, Setauket, NY (United States)
1996-12-31
A variety of practical computational problems arise in risk and safety assessments, forensic statistics and decision analyses in which the probability of some event or proposition E is to be estimated from the probabilities of a finite list of related subevents or propositions F,G,H,.... In practice, the analyst`s knowledge may be incomplete in two ways. First, the probabilities of the subevents may be imprecisely known from statistical estimations, perhaps based on very small sample sizes. Second, relationships among the subevents may be known imprecisely. For instance, there may be only limited information about their stochastic dependencies. Representing probability estimates as interval ranges on has been suggested as a way to address the first source of imprecision. A suite of AND, OR and NOT operators defined with reference to the classical Frochet inequalities permit these probability intervals to be used in calculations that address the second source of imprecision, in many cases, in a best possible way. Using statistical confidence intervals as inputs unravels the closure properties of this approach however, requiring that probability estimates be characterized by a nested stack of intervals for all possible levels of statistical confidence, from a point estimate (0% confidence) to the entire unit interval (100% confidence). The corresponding logical operations implied by convolutive application of the logical operators for every possible pair of confidence intervals reduces by symmetry to a manageably simple level-wise iteration. The resulting calculus can be implemented in software that allows users to compute comprehensive and often level-wise best possible bounds on probabilities for logical functions of events.
Measuring lip force by oral screens. Part 1: Importance of screen size and individual variability.
Wertsén, Madeleine; Stenberg, Manne
2017-06-01
To reduce drooling and facilitate food transport in rehabilitation of patients with oral motor dysfunction, lip force can be trained using an oral screen. Longitudinal studies evaluating the effect of training require objective methods. The aim of this study was to evaluate a method for measuring lip strength, to investigate normal values and fluctuation of lip force in healthy adults on 1 occasion and over time, to study how the size of the screen affects the force, to evaluate the most appropriate measure of reliability, and to identify force performed in relation to gender. Three different sizes of oral screens were used to measure the lip force for 24 healthy adults on 3 different occasions, during a period of 6 months, using an apparatus based on strain gauge. The maximum lip force as evaluated with this method depends on the area of the screen size. By calculating the projected area of the screen, the lip force could be normalized to an oral screen pressure quantity expressed in kPa, which can be used for comparing measurements from screens with different sizes. Both the mean value and standard deviation were shown to vary between individuals. The study showed no differences regarding gender and only small variation with age. Normal variation over time (months) may be up to 3 times greater than the standard error of measurement at a certain occasion. The lip force increases in relation to the projected area of the screen. No general standard deviation can be assigned to the method and all measurements should be analyzed individually based on oral screen pressure to compensate for different screen sizes.
Energy Technology Data Exchange (ETDEWEB)
Kim, Hye Jeong [Hallym University College of Medicine, Department of Radiology, Kangnam Sacred Heart Hospital, Seoul (Korea, Republic of); Yoon, Dae Young; Lee, Hyung Jin [Hallym University College of Medicine, Department of Radiology, Kangdong Seong-Sim Hospital, Seoul (Korea, Republic of); Kim, Eun Soo [Hallym University College of Medicine, Department of Radiology, Hallym University Sacred Heart Hospital, Anyang, Gyeonggi-do (Korea, Republic of); Jeon, Hong Jun; Lee, Jong Young; Cho, Byung-Moon [Hallym University College of Medicine, Department of Neurosurgery, Kangdong Seong-Sim Hospital, Seoul (Korea, Republic of)
2017-05-15
Accurate and reliable measurement of aneurysm size is important for treatment planning. The purpose of this study was to determine intraobserver and interobserver variability of CTA and MRA for measurement of the size of cerebral aneurysms. Thirty patients with 33 unruptured cerebral aneurysms (saccular, >3 mm in their maximal dimension, with no daughter sacs or lobulations) who underwent 256-row multislice CTA, 3-D TOF MRA at 3.0T, and 3D rotational angiography (3DRA) were retrospectively analyzed. Three independent observers measured the neck, height, and width of the aneurysms using the CTA and MRA images. Intraobserver and interobserver variability of CTA and MRA measurements was evaluated using the standardized difference and intraclass correlation coefficient, with 3DRA measurements as the reference standard. In addition, the mean values of the measurements using CTA and MRA were compared with those using 3DRA. The overall intraobserver and interobserver standardized differences in CTA/MRA were 12.83-15.92%/13.48-17.45% and 14.08-17.00%/12.08-17.67%, respectively. The overall intraobserver and interobserver intraclass correlation coefficients of CTA/MRA were 0.88-0.98/0.84-0.96 and 0.86-0.98/0.85-0.95, respectively. Compared to the height and width measurements, measurements of the neck dimensions showed higher intraobserver and interobserver variability. The sizes of the cerebral aneurysms measured by CTA and MRA were 1.13-9.26 and 5.20-9.67% larger than those measured by 3DRA, respectively; however, these differences were not statistically significant. There were no noticeable differences between intraobserver and interobserver variability for both CTA- and MRA-based measurements of the size of cerebral aneurysms. (orig.)
On sample size of the kruskal-wallis test with application to a mouse peritoneal cavity study.
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.
Farnell, C.; Rigo, T.; Pineda, N.
2018-04-01
Severe weather regularly hits the Lleida Plain (western part of Catalonia, NE of Iberian Peninsula), causing important damage to the local agriculture. In order to help severe weather surveillance tasks, the Meteorological Service of Catalonia (SMC) implemented in 2016 the Lightning Jump (LJ) algorithm as operative warning tool after an exhaustive validation phase of several months. The present study delves into the analysis of the relationship between Lightning Jump alerts and hail occurrence, through the analysis of lightning and radar variables in the moment when the warning is issued. Overall, the study has consisted of the analysis of 149 cases, grouping them into two categories according to hail size: small and large hail, with a threshold of 2 cm of diameter. The thunderstorms related to big sized hail presented remarkable differences in some of the variables analysed that could help forecast the size of hail when the LJ alert is triggered. Moreover, other variables have been allowed to observe and to corroborate how the LJ algorithm works during the 13 min before the warning is triggered.
Clustering of samples and elements based on multi-variable chemical data
International Nuclear Information System (INIS)
Op de Beeck, J.
1984-01-01
Clustering and classification are defined in the context of multivariable chemical analysis data. Classical multi-variate techniques, commonly used to interpret such data, are shown to be based on probabilistic and geometrical principles which are not justified for analytical data, since in that case one assumes or expects a system of more or less systematically related objects (samples) as defined by measurements on more or less systematically interdependent variables (elements). For the specific analytical problem of data set concerning a large number of trace elements determined in a large number of samples, a deterministic cluster analysis can be used to develop the underlying classification structure. Three main steps can be distinguished: diagnostic evaluation and preprocessing of the raw input data; computation of a symmetric matrix with pairwise standardized dissimilarity values between all possible pairs of samples and/or elements; and ultrametric clustering strategy to produce the final classification as a dendrogram. The software packages designed to perform these tasks are discussed and final results are given. Conclusions are formulated concerning the dangers of using multivariate, clustering and classification software packages as a black-box
Holland, Alexander; Aboy, Mateo
2009-07-01
We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability. We compare RFT based spectrum estimation with Lomb-Scargle Transform (LST) based estimation. PSD estimation based on the LST also does not require uniform time samples, but the LST has a computational order greater than Nlog(N). We conducted an assessment study involving the analysis of quasi-stationary signals with various levels of randomly missing heart beats. Our results indicate that the RFT leads to comparable estimation performance to the LST with significantly less computational overhead and complexity for applications requiring iterative spectrum estimations.
Directory of Open Access Journals (Sweden)
ARUN, K.
2016-05-01
Full Text Available A modified digital signal processing procedure is described for the on-line estimation of DC, fundamental and harmonics of periodic signal. A frequency locked loop (FLL incorporated within the parallel structure of observers is proposed to accommodate a wide range of frequency drift. The error in frequency generated under drifting frequencies has been used for changing the sampling frequency of the composite observer, so that the number of samples per cycle of the periodic waveform remains constant. A standard coupled oscillator with automatic gain control is used as numerically controlled oscillator (NCO to generate the enabling pulses for the digital observer. The NCO gives an integer multiple of the fundamental frequency making it suitable for power quality applications. Another observer with DC and second harmonic blocks in the feedback path act as filter and reduces the double frequency content. A systematic study of the FLL is done and a method has been proposed to design the controller. The performance of FLL is validated through simulation and experimental studies. To illustrate applications of the new FLL, estimation of individual harmonics from nonlinear load and the design of a variable sampling resonant controller, for a single phase grid-connected inverter have been presented.
Slurry feed variability in West Valley's melter feed tank and sampling system
International Nuclear Information System (INIS)
Fow, C.L.; Kurath, D.E.; Pulsipher, B.A.; Bauer, B.P.
1989-04-01
The present plan for disposal of high-level wastes at West Valley is to vitrify the wastes for disposal in deep geologic repository. The vitrification process involves mixing the high-level wastes with glass-forming chemicals and feeding the resulting slurry to a liquid-fed ceramic melter. Maintaining the quality of the glass product and proficient melter operation depends on the ability of the melter feed system to produce and maintain a homogeneous mixture of waste and glass-former materials. To investigate the mixing properties of the melter feed preparation system at West Valley, a statistically designed experiment was conducted using synthetic melter feed slurry over a range of concentrations. On the basis of the statistical data analysis, it was found that (1) a homogeneous slurry is produced in the melter feed tank, (2) the liquid-sampling system provides slurry samples that are statistically different from the slurry in the tank, and (3) analytical measurements are the major source of variability. A statistical quality control program for the analytical laboratory and a characterization test of the actual sampling system is recommended. 1 ref., 5 figs., 1 tab
Spatial Variability of Indicators of Jiaokou Reservoir Under Different Sampling Scales
Directory of Open Access Journals (Sweden)
WEI Wen-juan
2016-12-01
Full Text Available This research determined total nitrogen, total phosphorus, ammonia nitrogen and potassium permanganate contents in different scales of Jiaokou reservoir with the purpose of exploring the applicability of spatial variability and its characteristic in different sampling scales. The results showed that, compared the sampling scales of 100 m with 200 m, there were some differences among four indicators in the spatial variation, interpolation simulation and spatial distribution. About the testing model fit, the fitting model for the total nitrogen, permanganate index was Gaussian model, the fitting model for total phosphorus, ammonia nitrogen was the spherical model; Combining evaluation of parameters of models and comprehensive evaluation of spatial interpolation, total nitrogen, total phosphorus showed stronger spatial correlation and better interpolation simulation quality on the sampling scales of 200 m, while total phosphorus and permanganate index showed certain advantages on the 100 m scale; On the aspect of spatial distributions, the contents of ammonia nitrogen and potassium permanganate were mainly affected by human factors, the total phosphorus was affected by internal factors of the reservoir, while total nitrogen was closely related to farming activities around reservoir. The above results showed that total nitrogen, ammonia nitrogen were more available for the 200 m scales and total phosphorus, potassium permanganate were more available for the 100 m scales.
Hall, M B; Mertens, D R
2012-04-01
In vitro neutral detergent fiber (NDF) digestibility (NDFD) is an empirical measurement of fiber fermentability by rumen microbes. Variation is inherent in all assays and may be increased as multiple steps or differing procedures are used to assess an empirical measure. The main objective of this study was to evaluate variability within and among laboratories of 30-h NDFD values analyzed in repeated runs. Subsamples of alfalfa (n=4), corn forage (n=5), and grass (n=5) ground to pass a 6-mm screen passed a test for homogeneity. The 14 samples were sent to 10 laboratories on 3 occasions over 12 mo. Laboratories ground the samples and ran 1 to 3 replicates of each sample within fermentation run and analyzed 2 or 3 sets of samples. Laboratories used 1 of 2 NDFD procedures: 8 labs used procedures related to the 1970 Goering and Van Soest (GVS) procedure using fermentation vessels or filter bags, and 2 used a procedure with preincubated inoculum (PInc). Means and standard deviations (SD) of sample replicates within run within laboratory (lab) were evaluated with a statistical model that included lab, run within lab, sample, and lab × sample interaction as factors. All factors affected mean values for 30-h NDFD. The lab × sample effect suggests against a simple lab bias in mean values. The SD ranged from 0.49 to 3.37% NDFD and were influenced by lab and run within lab. The GVS procedure gave greater NDFD values than PInc, with an average difference across all samples of 17% NDFD. Because of the differences between GVS and PInc, we recommend using results in contexts appropriate to each procedure. The 95% probability limits for within-lab repeatability and among-lab reproducibility for GVS mean values were 10.2 and 13.4%, respectively. These percentages describe the span of the range around the mean into which 95% of analytical results for a sample fall for values generated within a lab and among labs. This degree of precision was supported in that the average maximum
Evaluation of 1H NMR relaxometry for the assessment of pore size distribution in soil samples
Jaeger, F.; Bowe, S.; As, van H.; Schaumann, G.E.
2009-01-01
1H NMR relaxometry is used in earth science as a non-destructive and time-saving method to determine pore size distributions (PSD) in porous media with pore sizes ranging from nm to mm. This is a broader range than generally reported for results from X-ray computed tomography (X-ray CT) scanning,
Biswas, Sanjib; Drzal, Lawrence T
2010-08-01
The diverse physical and chemical aspects of graphene nanosheets such as particle size surface area and edge chemistry were combined to fabricate a new supercapacitor electrode architecture consisting of a highly aligned network of large-sized nanosheets as a series of current collectors within a multilayer configuration of bulk electrode. Capillary driven self-assembly of monolayers of graphene nanosheets was employed to create a flexible, multilayer, free-standing film of highly hydrophobic nanosheets over large macroscopic areas. This nanoarchitecture exhibits a high-frequency capacitative response and a nearly rectangular cyclic voltammogram at 1000 mV/s scanning rate and possesses a rapid current response, small equivalent series resistance (ESR), and fast ionic diffusion for high-power electrical double-layer capacitor (EDLC) application.
Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos
Directory of Open Access Journals (Sweden)
Samabia Tehsin
2014-01-01
Full Text Available Textual information embedded in multimedia can provide a vital tool for indexing and retrieval. A lot of work is done in the field of text localization and detection because of its very fundamental importance. One of the biggest challenges of text detection is to deal with variation in font sizes and image resolution. This problem gets elevated due to the undersegmentation or oversegmentation of the regions in an image. The paper addresses this problem by proposing a solution using novel fuzzy-based method. This paper advocates postprocessing segmentation method that can solve the problem of variation in text sizes and image resolution. The methodology is tested on ICDAR 2011 Robust Reading Challenge dataset which amply proves the strength of the recommended method.
Effects of Variable Spot Size on Human Exposure to 95 GHz Millimeter Wave Energy
2017-05-11
Laboratory. Ross, J. A., Allen, S. J., Beason, C. W., & Johnson, L. R. (2008). Power density measurement of 94-GHz radiofrequency radiation using carbon...effectiveness) at the smallest spot size. 15. SUBJECT TERMS Avoidance, behavior, millimeter waves, nonlethal weapons, radiofrequency 16...System power density measurements (mean ± standard deviation) for the three different power density settings (low, middle, high) used in Experiment 1B
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.
Directory of Open Access Journals (Sweden)
Manan Gupta
Full Text Available Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates
DEFF Research Database (Denmark)
Larsen, Esben Kjær Unmack; Nielsen, Thomas; Wittenborn, Thomas
2012-01-01
Iron oxide nanoparticles have found widespread applications in different areas including cell separation, drug delivery and as contrast agents. Due to water insolubility and stability issues, nanoparticles utilized for biological applications require coatings such as the commonly employed...... polyethylene glycol (PEG). Despite its frequent use, the influence of PEG coatings on the physicochemical and biological properties of iron nanoparticles has hitherto not been studied in detail. To address this, we studied the effect of 333–20 000 Da PEG coatings that resulted in larger hydrodynamic size...
45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations
2010-10-01
..., YOUTH AND FAMILIES, FOSTER CARE MAINTENANCE PAYMENTS, ADOPTION ASSISTANCE, AND CHILD AND FAMILY SERVICES... dichotomous variable, is (.50)(.50) for the most conservative estimate. ER26FE08.001 • Acceptable level of...
International Nuclear Information System (INIS)
Hoo, Christopher M.; Doan, Trang; Starostin, Natasha; West, Paul E.; Mecartney, Martha L.
2010-01-01
Optimal deposition procedures are determined for nanoparticle size characterization by atomic force microscopy (AFM). Accurate nanoparticle size distribution analysis with AFM requires non-agglomerated nanoparticles on a flat substrate. The deposition of polystyrene (100 nm), silica (300 and 100 nm), gold (100 nm), and CdSe quantum dot (2-5 nm) nanoparticles by spin coating was optimized for size distribution measurements by AFM. Factors influencing deposition include spin speed, concentration, solvent, and pH. A comparison using spin coating, static evaporation, and a new fluid cell deposition method for depositing nanoparticles is also made. The fluid cell allows for a more uniform and higher density deposition of nanoparticles on a substrate at laminar flow rates, making nanoparticle size analysis via AFM more efficient and also offers the potential for nanoparticle analysis in liquid environments.
Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S
2013-04-15
Adaptive clinical trial design has been proposed as a promising new approach that may improve the drug discovery process. Proponents of adaptive sample size re-estimation promote its ability to avoid 'up-front' commitment of resources, better address the complicated decisions faced by data monitoring committees, and minimize accrual to studies having delayed ascertainment of outcomes. We investigate aspects of adaptation rules, such as timing of the adaptation analysis and magnitude of sample size adjustment, that lead to greater or lesser statistical efficiency. Owing in part to the recent Food and Drug Administration guidance that promotes the use of pre-specified sampling plans, we evaluate alternative approaches in the context of well-defined, pre-specified adaptation. We quantify the relative costs and benefits of fixed sample, group sequential, and pre-specified adaptive designs with respect to standard operating characteristics such as type I error, maximal sample size, power, and expected sample size under a range of alternatives. Our results build on others' prior research by demonstrating in realistic settings that simple and easily implemented pre-specified adaptive designs provide only very small efficiency gains over group sequential designs with the same number of analyses. In addition, we describe optimal rules for modifying the sample size, providing efficient adaptation boundaries on a variety of scales for the interim test statistic for adaptation analyses occurring at several different stages of the trial. We thus provide insight into what are good and bad choices of adaptive sampling plans when the added flexibility of adaptive designs is desired. Copyright © 2012 John Wiley & Sons, Ltd.
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
A Conceptual Model for Spatial Grain Size Variability on the Surface of and within Beaches
Directory of Open Access Journals (Sweden)
Edith Gallagher
2016-05-01
Full Text Available Grain size on the surface of natural beaches has been observed to vary spatially and temporally with morphology and wave energy. The stratigraphy of the beach at Duck, North Carolina, USA was examined using 36 vibracores (~1–1.5 m long collected along a cross-shore beach profile. Cores show that beach sediments are finer (~0.3 mm and more uniform high up on the beach. Lower on the beach, with more swash and wave action, the sand is reworked, segregated by size, and deposited in layers and patches. At the deepest measurement sites in the swash (~−1.4 to −1.6 m NAVD88, which are constantly being reworked by the energetic shore break, there is a thick layer (60–80 cm of very coarse sediment (~2 mm. Examination of two large trenches showed that continuous layers of coarse and fine sands comprise beach stratigraphy. Thicker coarse layers in the trenches (above mean sea level are likely owing to storm erosion and storm surge elevating the shore break and swash, which act to sort the sediment. Those layers are buried as water level retreats, accretion occurs and the beach recovers from the storm. Thinner coarse layers likely represent similar processes acting on smaller temporal scales.
DEFF Research Database (Denmark)
Gerke, Oke; Poulsen, Mads Hvid; Bouchelouche, Kirsten
2009-01-01
PURPOSE: For certain cancer indications, the current patient evaluation strategy is a perfect but locally restricted gold standard procedure. If positron emission tomography/computed tomography (PET/CT) can be shown to be reliable within the gold standard region and if it can be argued that PET...... of metastasized prostate cancer. RESULTS: An added value in accuracy of PET/CT in adjacent areas can outweigh a downsized target level of accuracy in the gold standard region, justifying smaller sample sizes. CONCLUSIONS: If PET/CT provides an accuracy benefit in adjacent regions, then sample sizes can be reduced....../CT also performs well in adjacent areas, then sample sizes in accuracy studies can be reduced. PROCEDURES: Traditional standard power calculations for demonstrating sensitivities of both 80% and 90% are shown. The argument is then described in general terms and demonstrated by an ongoing study...
Marvanová, Soňa; Kulich, Pavel; Skoupý, Radim; Hubatka, František; Ciganek, Miroslav; Bendl, Jan; Hovorka, Jan; Machala, Miroslav
2018-04-01
Size-segregated particulate matter (PM) is frequently used in chemical and toxicological studies. Nevertheless, toxicological in vitro studies working with the whole particles often lack a proper evaluation of PM real size distribution and characterization of agglomeration under the experimental conditions. In this study, changes in particle size distributions during the PM sample manipulation and also semiquantitative elemental composition of single particles were evaluated. Coarse (1-10 μm), upper accumulation (0.5-1 μm), lower accumulation (0.17-0.5 μm), and ultrafine (culture media. PM suspension of lower accumulation fraction in water agglomerated after freezing/thawing the sample, and the agglomerates were disrupted by subsequent sonication. Ultrafine fraction did not agglomerate after freezing/thawing the sample. Both lower accumulation and ultrafine fractions were stable in cell culture media with fetal bovine serum, while high agglomeration occurred in media without fetal bovine serum as measured during 24 h.
DEFF Research Database (Denmark)
Chan, A.W.; Hrobjartsson, A.; Jorgensen, K.J.
2008-01-01
OBJECTIVE: To evaluate how often sample size calculations and methods of statistical analysis are pre-specified or changed in randomised trials. DESIGN: Retrospective cohort study. Data source Protocols and journal publications of published randomised parallel group trials initially approved...... in 1994-5 by the scientific-ethics committees for Copenhagen and Frederiksberg, Denmark (n=70). MAIN OUTCOME MEASURE: Proportion of protocols and publications that did not provide key information about sample size calculations and statistical methods; proportion of trials with discrepancies between...... of handling missing data was described in 16 protocols and 49 publications. 39/49 protocols and 42/43 publications reported the statistical test used to analyse primary outcome measures. Unacknowledged discrepancies between protocols and publications were found for sample size calculations (18/34 trials...
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
Directory of Open Access Journals (Sweden)
Peng-Cheng Yao
Full Text Available Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P < 0.01. These results suggest that increasing the sample size in specialist habitats can improve measurements of intraspecific genetic diversity, and will have a positive effect on the application of the DNA barcodes in widely distributed species. The results of random sampling showed that when sample size reached 11 for Chloris virgata, Chenopodium glaucum, and Dysphania ambrosioides, 13 for Setaria viridis, and 15 for Eleusine indica, Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11-15.
Page, G P; Amos, C I; Boerwinkle, E
1998-04-01
We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.
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.
Bi, Ran; Liu, Peng
2016-03-31
RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments. In this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method. Our proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network ( http://cran.r-project.org ).
Volatile and non-volatile elements in grain-size separated samples of Apollo 17 lunar soils
International Nuclear Information System (INIS)
Giovanoli, R.; Gunten, H.R. von; Kraehenbuehl, U.; Meyer, G.; Wegmueller, F.; Gruetter, A.; Wyttenbach, A.
1977-01-01
Three samples of Apollo 17 lunar soils (75081, 72501 and 72461) were separated into 9 grain-size fractions between 540 and 1 μm mean diameter. In order to detect mineral fractionations caused during the separation procedures major elements were determined by instrumental neutron activation analyses performed on small aliquots of the separated samples. Twenty elements were measured in each size fraction using instrumental and radiochemical neutron activation techniques. The concentration of the main elements in sample 75081 does not change with the grain-size. Exceptions are Fe and Ti which decrease slightly and Al which increases slightly with the decrease in the grain-size. These changes in the composition in main elements suggest a decrease in Ilmenite and an increase in Anorthite with decreasing grain-size. However, it can be concluded that the mineral composition of the fractions changes less than a factor of 2. Samples 72501 and 72461 are not yet analyzed for the main elements. (Auth.)
Optical dating of single sand-sized grains of quartz: Sources of variability
DEFF Research Database (Denmark)
Duller, G.A.T.; Bøtter-Jensen, L.; Murray, A.S.
2000-01-01
of measuring single grains it is feasible to routinely measure the equivalent dose from many hundreds of grains from each sample. Analysis of such datasets requires assessment of the uncertainties on each equivalent dose since these may vary significantly. This paper assesses the significance of signal...... intensity, dose saturation characteristics and instrument uncertainty in equivalent dose calculation. (C) 2000 Elsevier Science Ltd. All rights reserved....
DEFF Research Database (Denmark)
Kostoulas, P.; Nielsen, Søren Saxmose; Browne, W. J.
2013-01-01
and power when applied to these groups. We propose the use of the variance partition coefficient (VPC), which measures the clustering of infection/disease for individuals with a common risk profile. Sample size estimates are obtained separately for those groups that exhibit markedly different heterogeneity......, thus, optimizing resource allocation. A VPC-based predictive simulation method for sample size estimation to substantiate freedom from disease is presented. To illustrate the benefits of the proposed approach we give two examples with the analysis of data from a risk factor study on Mycobacterium avium...
Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy
2016-01-01
Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.
Energy Technology Data Exchange (ETDEWEB)
Relova, I.; Leon, M.A. [Universidad de Pinar del Rio, Marti 270 esq, a 27 de Noviembre, Pinar del Rio (Cuba); Vignote, S.; Ambrosio, Y. [Departamento de Economia y Gestion Forestal, Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain)
2009-10-15
Different variables affect the processes of compacting biomass, and these variables depend on the raw material, such as the type of wood or type of biomass being compacted, its moisture, size, as well as on other aspects relating to the manufacturing process, such as the pressure applied and the temperature reached during compaction. This work analyses the influence of the size of the sawdust particles from the bark of the species Pinus caribaea var. Morelet, which ranges from 0.63 to 2 mm; it had a moisture content in dry basis of 6; 9.5; 13 and 20%; and the force applied in the laboratory was 8000, 12,000, 16,000 and 20,000 N. These values are relatively high given that they do not take into account the heat caused by the matrixes chafing with the material to be compacted, as occurs in industrial processes. The different experimental treatments were processed and statistically analysed using SSPS version 12.0, and Statgraphics version 5.0. Once the data had been tested in the ANOVA and in various comparison tests, it was observed that the results did not show any significant differences between the pellets obtained with forces of 16,000 and 20,000 N, or between pellets obtained with 9.5 and 13% moisture, and that the pellets with higher qualities were obtained from particle sizes of between 1 and 2 mm. (author)
Björklund, Jesper; Seftigen, Kristina; Schweingruber, Fritz; Fonti, Patrick; von Arx, Georg; Bryukhanova, Marina V; Cuny, Henri E; Carrer, Marco; Castagneri, Daniele; Frank, David C
2017-11-01
Interannual variability of wood density - an important plant functional trait and environmental proxy - in conifers is poorly understood. We therefore explored the anatomical basis of density. We hypothesized that earlywood density is determined by tracheid size and latewood density by wall dimensions, reflecting their different functional tasks. To determine general patterns of variability, density parameters from 27 species and 349 sites across the Northern Hemisphere were correlated to tree-ring width parameters and local climate. We performed the same analyses with density and width derived from anatomical data comprising two species and eight sites. The contributions of tracheid size and wall dimensions to density were disentangled with sensitivity analyses. Notably, correlations between density and width shifted from negative to positive moving from earlywood to latewood. Temperature responses of density varied intraseasonally in strength and sign. The sensitivity analyses revealed tracheid size as the main determinant of earlywood density, while wall dimensions become more influential for latewood density. Our novel approach of integrating detailed anatomical data with large-scale tree-ring data allowed us to contribute to an improved understanding of interannual variations of conifer growth and to illustrate how conifers balance investments in the competing xylem functions of hydraulics and mechanical support. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Directory of Open Access Journals (Sweden)
Simon Boitard
2016-03-01
Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Variability of grain sizes in a beach nourishment programme for the Danish West Caost
DEFF Research Database (Denmark)
Frigaard, Peter; Wahl, Niels Arne
2007-01-01
of naturally shaped beaches while at the same time the risk for erosion is reduced. For this reason beach nourishment is used widely along the Danish North Sea coast (called West Coast) and this method is preferred in preference to put up solid constructions. Beach nourishment is the primary method used...... is shaped. The aim of the present investigation was to examine how to extract sand samples of an actual beach nourishment to obtain a satisfactory description of the sedimentary composition. In specific the goal was a description of the variation of the sand characteristics in space. The reason...... for this is that the compositions of sand affect the erosion and the shaping of the beach. The results show that by collecting 13-15 sand samples it is possible to obtain a description of d50 with a precision of 0.1 mm within a confidence interval of 95-99 %. If a precision of 0.05 mm is wanted, it is necessary to collect 67...
GeneratorSE: A Sizing Tool for Variable-Speed Wind Turbine Generators
Energy Technology Data Exchange (ETDEWEB)
Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-09-22
This report documents a set of analytical models employed by the optimization algorithms within the GeneratorSE framework. The initial values and boundary conditions employed for the generation of the various designs and initial estimates for basic design dimensions, masses, and efficiency for the four different models of generators are presented and compared with empirical data collected from previous studies and some existing commercial turbines. These models include designs applicable for variable-speed, high-torque application featuring direct-drive synchronous generators and low-torque application featuring induction generators. In all of the four models presented, the main focus of optimization is electromagnetic design with the exception of permanent-magnet and wire-wound synchronous generators, wherein the structural design is also optimized. Thermal design is accommodated in GeneratorSE as a secondary attribute by limiting the winding current densities to acceptable limits. A preliminary validation of electromagnetic design was carried out by comparing the optimized magnetic loading against those predicted by numerical simulation in FEMM4.2, a finite-element software for analyzing electromagnetic and thermal physics problems for electrical machines. For direct-drive synchronous generators, the analytical models for the structural design are validated by static structural analysis in ANSYS.
Regression dilution bias: tools for correction methods and sample size calculation.
Berglund, Lars
2012-08-01
Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.
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.
Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory
Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo
2013-01-01
Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.
Miyatani, Makoto; Sakata, Sumiko
1999-01-01
This study investigated the effects of display set size and its variability on the event-related potentials (ERPs) during a visual search task. In Experiment 1, subjects were required to respond if a visual display, which consisted of two, four, or six alphabets, contained one of two members of memory set. In Experiment 2, subjects detected the change of the shape of a fixation stimulus, which was surrounded by the same alphabets as in Experiment 1. In the search task (Experiment 1), the incr...
Directory of Open Access Journals (Sweden)
Michael F. McNitt-Gray
2015-02-01
Full Text Available PURPOSE: To determine the variability of lesion size measurements in computed tomography data sets of patients imaged under a “no change” (“coffee break” condition and to determine the impact of two reading paradigms on measurement variability. METHOD AND MATERIALS: Using data sets from 32 non-small cell lung cancer patients scanned twice within 15 minutes (“no change”, measurements were performed by five radiologists in two phases: (1 independent reading of each computed tomography dataset (timepoint: (2 a locked, sequential reading of datasets. Readers performed measurements using several sizing methods, including one-dimensional (1D longest in-slice dimension and 3D semi-automated segmented volume. Change in size was estimated by comparing measurements performed on both timepoints for the same lesion, for each reader and each measurement method. For each reading paradigm, results were pooled across lesions, across readers, and across both readers and lesions, for each measurement method. RESULTS: The mean percent difference (±SD when pooled across both readers and lesions for 1D and 3D measurements extracted from contours was 2.8 ± 22.2% and 23.4 ± 105.0%, respectively, for the independent reads. For the locked, sequential reads, the mean percent differences (±SD reduced to 2.52 ± 14.2% and 7.4 ± 44.2% for the 1D and 3D measurements, respectively. CONCLUSION: Even under a “no change” condition between scans, there is variation in lesion size measurements due to repeat scans and variations in reader, lesion, and measurement method. This variation is reduced when using a locked, sequential reading paradigm compared to an independent reading paradigm.
Directory of Open Access Journals (Sweden)
H Mohamadi Monavar
2017-10-01
Full Text Available Introduction Precision agriculture (PA is a technology that measures and manages within-field variability, such as physical and chemical properties of soil. The nondestructive and rapid VIS-NIR technology detected a significant correlation between reflectance spectra and the physical and chemical properties of soil. On the other hand, quantitatively predict of soil factors such as nitrogen, carbon, cation exchange capacity and the amount of clay in precision farming is very important. The emphasis of this paper is comparing different techniques of choosing calibration samples such as randomly selected method, chemical data and also based on PCA. Since increasing the number of samples is usually time-consuming and costly, then in this study, the best sampling way -in available methods- was predicted for calibration models. In addition, the effect of sample size on the accuracy of the calibration and validation models was analyzed. Materials and Methods Two hundred and ten soil samples were collected from cultivated farm located in Avarzaman in Hamedan province, Iran. The crop rotation was mostly potato and wheat. Samples were collected from a depth of 20 cm above ground and passed through a 2 mm sieve and air dried at room temperature. Chemical analysis was performed in the soil science laboratory, faculty of agriculture engineering, Bu-ali Sina University, Hamadan, Iran. Two Spectrometer (AvaSpec-ULS 2048- UV-VIS and (FT-NIR100N were used to measure the spectral bands which cover the UV-Vis and NIR region (220-2200 nm. Each soil sample was uniformly tiled in a petri dish and was scanned 20 times. Then the pre-processing methods of multivariate scatter correction (MSC and base line correction (BC were applied on the raw signals using Unscrambler software. The samples were divided into two groups: one group for calibration 105 and the second group was used for validation. Each time, 15 samples were selected randomly and tested the accuracy of
(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research
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
(I Can't Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research.
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.
van Rijnsoever, F.J.
2015-01-01
This paper explores 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
(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research
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
Heymann, D.; Lakatos, S.; Walton, J. R.
1973-01-01
Review of the results of inert gas measurements performed on six grain-size fractions and two single particles from four samples of Luna 20 material. Presented and discussed data include the inert gas contents, element and isotope systematics, radiation ages, and Ar-36/Ar-40 systematics.
Tang, Yongqiang
2017-05-25
We derive the sample size formulae for comparing two negative binomial rates based on both the relative and absolute rate difference metrics in noninferiority and equivalence trials with unequal follow-up times, and establish an approximate relationship between the sample sizes required for the treatment comparison based on the two treatment effect metrics. The proposed method allows the dispersion parameter to vary by treatment groups. The accuracy of these methods is assessed by simulations. It is demonstrated that ignoring the between-subject variation in the follow-up time by setting the follow-up time for all individuals to be the mean follow-up time may greatly underestimate the required size, resulting in underpowered studies. Methods are provided for back-calculating the dispersion parameter based on the published summary results.
Analysis of reactor capital costs and correlated sampling of economic input variables - 15342
International Nuclear Information System (INIS)
Ganda, F.; Kim, T.K.; Taiwo, T.A.; Wigeland, R.
2015-01-01
In this paper we present work aimed at enhancing the capability to perform nuclear fuel cycle cost estimates and evaluation of financial risk. Reactor capital costs are of particular relevance, since they typically comprise about 60% to 70% of the calculated Levelized Cost of Electricity at Equilibrium (LCAE). The work starts with the collection of historical construction cost and construction duration of nuclear plants in the U.S. and France, as well as forecasted costs of nuclear plants currently under construction in the U.S. This data has the primary goal of supporting the introduction of an appropriate framework, supported in this paper by two case studies with historical data, which allows the development of solid and defensible assumptions on nuclear reactor capital costs. Work is also presented on the enhancement of the capability to model interdependence of cost estimates between facilities and uncertainties. The correlated sampling capabilities in the nuclear economic code NECOST have been expanded to include partial correlations between input variables, according to a given correlation matrix. Accounting for partial correlations correctly allows a narrowing, where appropriate, of the probability density function of the difference in the LCAE between alternative, but correlated, fuel cycles. It also allows the correct calculation of the standard deviation of the LCAE of multistage systems, which appears smaller than the correct value if correlated input costs are treated as uncorrelated. (authors)
Biological variability of the minutiae in the fingerprints of a sample of the Spanish population.
Gutiérrez, Esperanza; Galera, Virginia; Martínez, Jose Manuel; Alonso, Concepción
2007-10-25
The minutiae, a term coined by Galton to refer to the small peculiarities present along the length of every isolated ridge, or characteristic points, a term used primarily by the Spanish Police Scientists, have an inter- and intrapopulation variability which has not been extensively studied. However, these peculiarities constitute the bases for the fingerprint identification of individuals in the field of criminology. Using the adhesive paper and graphite method, the fingerprints of 200 students, 100 males and 100 females, with ages ranging between 20 and 35, have been taken at the University of Alcala (Madrid). From this sample, the distal phalanx of the index finger of the right hand has been studied. The total count of the minutiae, as well as that of each different type, was made of the entire print area, and inside and outside of a circle with a radius of 18 ridges. The highest frequencies were of ridge endings, followed by bifurcations and convergences, all others appearing with frequencies of lower than 5%. The distribution of the minutiae was not homogeneous for the area of the fingerprint (inside and outside the circle). In the study of minutiae statistically significant differences were found between the sexes, and between the different types of general pattern (arches, loops, and whorls).
Application of quantitative variables in the sampling method to evaluate the sugarcane rust brown
Directory of Open Access Journals (Sweden)
Joaquín Montalván Delgado
2017-01-01
Full Text Available To develop a system that increase the precision in the resistance evaluations to sugarcane brown rust disease through the use of the quantitative sampling, six cultivars of differential behavior versus the disease (PR980, My5514, Ja60-5, C334-64, C323-68 and B4362 were studied. A random block experimental design with three replications was used in a heavy infections conditions obtained from the cultivar highly susceptible B4362. The evaluations were done at three and five months of age, in the three-thirds: bottom, half and top of the +1, +3 and +5 sugarcane plant leaves of 10 plants for replica. The variable total leaf area affected of the leaf and in each third was analyzed. In 2 cm2 were observed the long and wide of the biggest and more frequent pustule, the total of pustule and the area of the biggest and more frequent pustule, and the area percentage occupied by the most frequent pustule by each cm2 were determined. Variance analysis and Tukey tests as well as confidence intervals analysis to determine the coefficient to use as constant of the pustule width, due to the little variation of this parameter were realized. The +3 leaf represented the half infection of the incidence of the brown rust, constituting for it the most appropriate to carry out the observations and the half third. An equation was also obtained to calculate the area occupied by pustules with a high level of confidence.
Basic distribution free identification tests for small size samples of environmental data
International Nuclear Information System (INIS)
Federico, A.G.; Musmeci, F.
1998-01-01
Testing two or more data sets for the hypothesis that they are sampled form the same population is often required in environmental data analysis. Typically the available samples have a small number of data and often then assumption of normal distributions is not realistic. On the other hand the diffusion of the days powerful Personal Computers opens new possible opportunities based on a massive use of the CPU resources. The paper reviews the problem introducing the feasibility of two non parametric approaches based on intrinsic equi probability properties of the data samples. The first one is based on a full re sampling while the second is based on a bootstrap approach. A easy to use program is presented. A case study is given based on the Chernobyl children contamination data [it
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA
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-...
Li, Tiandong
2012-01-01
In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…
Flaw-size measurement in a weld samples by ultrasonic frequency analysis
International Nuclear Information System (INIS)
Adler, L.; Cook, K.V.; Whaley, H.L. Jr.; McClung, R.W.
1975-01-01
An ultrasonic frequency-analysis technique was developed and applies to characterize flaws in an 8-in. (203-mm) thick heavy-section steel weld specimen. The technique applies a multitransducer system. The spectrum of the received broad-band signal is frequency analyzed at two different receivers for each of the flaws. From the two spectra, the size and orientation of the flaw are determined by the use of an analytic model proposed earlier. (auth)
Chen, Xiao; Lu, Bin; Yan, Chao-Gan
2018-01-01
Concerns regarding reproducibility of resting-state functional magnetic resonance imaging (R-fMRI) findings have been raised. Little is known about how to operationally define R-fMRI reproducibility and to what extent it is affected by multiple comparison correction strategies and sample size. We comprehensively assessed two aspects of reproducibility, test-retest reliability and replicability, on widely used R-fMRI metrics in both between-subject contrasts of sex differences and within-subject comparisons of eyes-open and eyes-closed (EOEC) conditions. We noted permutation test with Threshold-Free Cluster Enhancement (TFCE), a strict multiple comparison correction strategy, reached the best balance between family-wise error rate (under 5%) and test-retest reliability/replicability (e.g., 0.68 for test-retest reliability and 0.25 for replicability of amplitude of low-frequency fluctuations (ALFF) for between-subject sex differences, 0.49 for replicability of ALFF for within-subject EOEC differences). Although R-fMRI indices attained moderate reliabilities, they replicated poorly in distinct datasets (replicability < 0.3 for between-subject sex differences, < 0.5 for within-subject EOEC differences). By randomly drawing different sample sizes from a single site, we found reliability, sensitivity and positive predictive value (PPV) rose as sample size increased. Small sample sizes (e.g., < 80 [40 per group]) not only minimized power (sensitivity < 2%), but also decreased the likelihood that significant results reflect "true" effects (PPV < 0.26) in sex differences. Our findings have implications for how to select multiple comparison correction strategies and highlight the importance of sufficiently large sample sizes in R-fMRI studies to enhance reproducibility. Hum Brain Mapp 39:300-318, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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.
Influence sample sizing of citrus hystrix essential oil from hydrodistillation extraction
Yahya, A.; Amadi, I.; Hashib, S. A.; Mustapha, F. A.
2018-03-01
Essential oil extracted from kaffir lime leaves through hydrodistillation. The objective of this study is to quantify the oil production rate by identify the significant influence of particle size on kaffir lime leaves. Kaffir lime leaves were ground and separated by using siever into 90, 150, 300 μm and other kaffir lime leaves. The mean essential oil yield of 0.87, 0.52, 0.41 and 0.3% was obtained. 90 μm of ground gives the highest yield compared to other sizes. Thus, it can be concluded that in quantifying oil production rate, the relevance of different size of particle is clearly affects the amount of oil yield. In analysing the composition of kaffir lime essential oil using GC-MS, there were 38 compounds found in the essential oil. Some of the major compounds of the kaffir lime leave oils were detected while some are not, may due to oil experience thermal degradation which consequently losing some significant compounds in controlled temperature.
Bhaskar, Anand; Wang, Y X Rachel; Song, Yun S
2015-02-01
With the recent increase in study