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

PubMed

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

2009-04-01

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

Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.

PubMed

Diaz, Francisco J; Berg, Michel J; Krebill, Ron; Welty, Timothy; Gidal, Barry E; Alloway, Rita; Privitera, Michael

2013-12-01

Due to concern and debate in the epilepsy medical community and to the current interest of the US Food and Drug Administration (FDA) in revising approaches to the approval of generic drugs, the FDA is currently supporting ongoing bioequivalence studies of antiepileptic drugs, the EQUIGEN studies. During the design of these crossover studies, the researchers could not find commercial or non-commercial statistical software that quickly allowed computation of sample sizes for their designs, particularly software implementing the FDA requirement of using random-effects linear models for the analyses of bioequivalence studies. This article presents tables for sample-size evaluations of average bioequivalence studies based on the two crossover designs used in the EQUIGEN studies: the four-period, two-sequence, two-formulation design, and the six-period, three-sequence, three-formulation design. Sample-size computations assume that random-effects linear models are used in bioequivalence analyses with crossover designs. Random-effects linear models have been traditionally viewed by many pharmacologists and clinical researchers as just mathematical devices to analyze repeated-measures data. In contrast, a modern view of these models attributes an important mathematical role in theoretical formulations in personalized medicine to them, because these models not only have parameters that represent average patients, but also have parameters that represent individual patients. Moreover, the notation and language of random-effects linear models have evolved over the years. Thus, another goal of this article is to provide a presentation of the statistical modeling of data from bioequivalence studies that highlights the modern view of these models, with special emphasis on power analyses and sample-size computations.

How Big Is Big Enough? Sample Size Requirements for CAST Item Parameter Estimation

ERIC Educational Resources Information Center

Chuah, Siang Chee; Drasgow, Fritz; Luecht, Richard

2006-01-01

Adaptive tests offer the advantages of reduced test length and increased accuracy in ability estimation. However, adaptive tests require large pools of precalibrated items. This study looks at the development of an item pool for 1 type of adaptive administration: the computer-adaptive sequential test. An important issue is the sample size required…

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

PubMed Central

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

2014-01-01

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

Ensemble representations: effects of set size and item heterogeneity on average size perception.

PubMed

Marchant, Alexander P; Simons, Daniel J; de Fockert, Jan W

2013-02-01

Observers can accurately perceive and evaluate the statistical properties of a set of objects, forming what is now known as an ensemble representation. The accuracy and speed with which people can judge the mean size of a set of objects have led to the proposal that ensemble representations of average size can be computed in parallel when attention is distributed across the display. Consistent with this idea, judgments of mean size show little or no decrement in accuracy when the number of objects in the set increases. However, the lack of a set size effect might result from the regularity of the item sizes used in previous studies. Here, we replicate these previous findings, but show that judgments of mean set size become less accurate when set size increases and the heterogeneity of the item sizes increases. This pattern can be explained by assuming that average size judgments are computed using a limited capacity sampling strategy, and it does not necessitate an ensemble representation computed in parallel across all items in a display. Copyright © 2012 Elsevier B.V. All rights reserved.

Children's accuracy of portion size estimation using digital food images: effects of interface design and size of image on computer screen.

PubMed

Baranowski, Tom; Baranowski, Janice C; Watson, Kathleen B; Martin, Shelby; Beltran, Alicia; Islam, Noemi; Dadabhoy, Hafza; Adame, Su-heyla; Cullen, Karen; Thompson, Debbe; Buday, Richard; Subar, Amy

2011-03-01

To test the effect of image size and presence of size cues on the accuracy of portion size estimation by children. Children were randomly assigned to seeing images with or without food size cues (utensils and checked tablecloth) and were presented with sixteen food models (foods commonly eaten by children) in varying portion sizes, one at a time. They estimated each food model's portion size by selecting a digital food image. The same food images were presented in two ways: (i) as small, graduated portion size images all on one screen or (ii) by scrolling across large, graduated portion size images, one per sequential screen. Laboratory-based with computer and food models. Volunteer multi-ethnic sample of 120 children, equally distributed by gender and ages (8 to 13 years) in 2008-2009. Average percentage of correctly classified foods was 60·3 %. There were no differences in accuracy by any design factor or demographic characteristic. Multiple small pictures on the screen at once took half the time to estimate portion size compared with scrolling through large pictures. Larger pictures had more overestimation of size. Multiple images of successively larger portion sizes of a food on one computer screen facilitated quicker portion size responses with no decrease in accuracy. This is the method of choice for portion size estimation on a computer.

A Monte Carlo Program for Simulating Selection Decisions from Personnel Tests

ERIC Educational Resources Information Center

Petersen, Calvin R.; Thain, John W.

1976-01-01

Relative to test and criterion parameters and cutting scores, the correlation coefficient, sample size, and number of samples to be drawn (all inputs), this program calculates decision classification rates across samples and for combined samples. Several other related indices are also computed. (Author)

Type-II generalized family-wise error rate formulas with application to sample size determination.

PubMed

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.

Blanks: a computer program for analyzing furniture rough-part needs in standard-size blanks

Treesearch

Philip A. Araman

1983-01-01

A computer program is described that allows a company to determine the number of edge-glued, standard-size blanks required to satisfy its rough-part needs for a given production period. Yield and cost information also is determined by the program. A list of the program inputs, outputs, and uses of outputs is described, and an example analysis with sample output is...

Phase-contrast x-ray computed tomography for biological imaging

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1997-10-01

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

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

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

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

2014-04-15

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

R2 effect-size measures for mediation analysis

PubMed Central

Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.

2010-01-01

R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189

R2 effect-size measures for mediation analysis.

PubMed

Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B

2009-05-01

R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.

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

PubMed

Shieh, Gwowen

2014-09-01

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

Sample size determination for mediation analysis of longitudinal data.

PubMed

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

2018-03-27

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

Laboratory and exterior decay of wood plastic composite boards: voids analysis and computed tomography

Treesearch

Grace Sun; Rebecca E. Ibach; Meghan Faillace; Marek Gnatowski; Jessie A. Glaeser; John Haight

2016-01-01

After exposure in the field and laboratory soil block culture testing, the void content of wood–plastic composite (WPC) decking boards was compared to unexposed samples. A void volume analysis was conducted based on calculations of sample density and from micro-computed tomography (microCT) data. It was found that reference WPC contains voids of different sizes from...

A risk assessment method for multi-site damage

NASA Astrophysics Data System (ADS)

Millwater, Harry Russell, Jr.

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

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

PubMed

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

Computed Tomography to Estimate the Representative Elementary Area for Soil Porosity Measurements

PubMed Central

Borges, Jaqueline Aparecida Ribaski; Pires, Luiz Fernando; Belmont Pereira, André

2012-01-01

Computed tomography (CT) is a technique that provides images of different solid and porous materials. CT could be an ideal tool to study representative sizes of soil samples because of the noninvasive characteristic of this technique. The scrutiny of such representative elementary sizes (RESs) has been the target of attention of many researchers related to soil physics field owing to the strong relationship between physical properties and size of the soil sample. In the current work, data from gamma-ray CT were used to assess RES in measurements of soil porosity (ϕ). For statistical analysis, a study on the full width at a half maximum (FWHM) of the adjustment of distribution of ϕ at different areas (1.2 to 1162.8 mm2) selected inside of tomographic images was proposed herein. The results obtained point out that samples with a section area corresponding to at least 882.1 mm2 were the ones that provided representative values of ϕ for the studied Brazilian tropical soil. PMID:22666133

EVALUATION OF COMPUTER-CONTROLLED SCANNING ELECTRON MICROSCOPY APPLIED TO AN AMBIENT URBAN AEROSOL SAMPLE

EPA Science Inventory

Concerns about the environmental and public health effects of particulate matter (PM) have stimulated interest in analytical techniques capable of measuring the size and chemical composition of individual aerosol particles. Computer-controlled scanning electron microscopy (CCSE...

Knowledge and use of information and communication technology by health sciences students of the University of Ghana.

PubMed

Dery, Samuel; Vroom, Frances da-Costa; Godi, Anthony; Afagbedzi, Seth; Dwomoh, Duah

2016-09-01

Studies have shown that ICT adoption contributes to productivity and economic growth. It is therefore important that health workers have knowledge in ICT to ensure adoption and uptake of ICT tools to enable efficient health delivery. To determine the knowledge and use of ICT among students of the College of Health Sciences at the University of Ghana. This was a cross-sectional study conducted among students in all the five Schools of the College of Health Sciences at the University of Ghana. A total of 773 students were sampled from the Schools. Sampling proportionate to size was then used to determine the sample sizes required for each school, academic programme and level of programme. Simple random sampling was subsequently used to select students from each stratum. Computer knowledge was high among students at almost 99%. About 83% owned computers (p < 0.001) and self-rated computer knowledge was also 87 % (p <0.001). Usage was mostly for studying at 93% (p< 0.001). This study shows students have adequate knowledge and use of computers. It brings about an opportunity to introduce ICT in healthcare delivery to them. This will ensure their adequate preparedness to embrace new ways of delivering care to improve service delivery. Africa Build Project, Grant Number: FP7-266474.

Statistical computation of tolerance limits

NASA Technical Reports Server (NTRS)

Wheeler, J. T.

1993-01-01

Based on a new theory, two computer codes were developed specifically to calculate the exact statistical tolerance limits for normal distributions within unknown means and variances for the one-sided and two-sided cases for the tolerance factor, k. The quantity k is defined equivalently in terms of the noncentral t-distribution by the probability equation. Two of the four mathematical methods employ the theory developed for the numerical simulation. Several algorithms for numerically integrating and iteratively root-solving the working equations are written to augment the program simulation. The program codes generate some tables of k's associated with the varying values of the proportion and sample size for each given probability to show accuracy obtained for small sample sizes.

A new tool called DISSECT for analysing large genomic data sets using a Big Data approach

PubMed Central

Canela-Xandri, Oriol; Law, Andy; Gray, Alan; Woolliams, John A.; Tenesa, Albert

2015-01-01

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes. PMID:26657010

RAINDROP DISTRIBUTIONS AT MAJURO ATOLL, MARSHALL ISLANDS.

DTIC Science & Technology

RAINDROPS, MARSHALL ISLANDS), (*ATMOSPHERIC PRECIPITATION, TROPICAL REGIONS), PARTICLE SIZE, SAMPLING, TABLES(DATA), WATER , ATTENUATION, DISTRIBUTION, VOLUME, RADAR REFLECTIONS, RAINFALL, PHOTOGRAPHIC ANALYSIS, COMPUTERS

Terahertz Computed Tomography of NASA Thermal Protection System Materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Reyes-Rodriguez, S.; Zimdars, D. A.; Rauser, R. W.; Ussery, W. W.

2011-01-01

A terahertz axial computed tomography system has been developed that uses time domain measurements in order to form cross-sectional image slices and three-dimensional volume renderings of terahertz-transparent materials. The system can inspect samples as large as 0.0283 cubic meters (1 cubic foot) with no safety concerns as for x-ray computed tomography. In this study, the system is evaluated for its ability to detect and characterize flat bottom holes, drilled holes, and embedded voids in foam materials utilized as thermal protection on the external fuel tanks for the Space Shuttle. X-ray micro-computed tomography was also performed on the samples to compare against the terahertz computed tomography results and better define embedded voids. Limits of detectability based on depth and size for the samples used in this study are loosely defined. Image sharpness and morphology characterization ability for terahertz computed tomography are qualitatively described.

Sample Size for Measuring Grammaticality in Preschool Children from Picture-Elicited Language Samples

ERIC Educational Resources Information Center

Eisenberg, Sarita L.; Guo, Ling-Yu

2015-01-01

Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…

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

PubMed

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

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

PubMed

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

2017-12-01

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

A Bayesian Perspective on the Reproducibility Project: Psychology

PubMed Central

Etz, Alexander; Vandekerckhove, Joachim

2016-01-01

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors—a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis—for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable. PMID:26919473

A Bayesian Perspective on the Reproducibility Project: Psychology.

PubMed

Etz, Alexander; Vandekerckhove, Joachim

2016-01-01

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors-a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis-for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable.

TableSim--A program for analysis of small-sample categorical data.

Treesearch

David J. Rugg

2003-01-01

Documents a computer program for calculating correct P-values of 1-way and 2-way tables when sample sizes are small. The program is written in Fortran 90; the executable code runs in 32-bit Microsoft-- command line environments.

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

PubMed

Shieh, Gwowen

2014-09-01

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

A comparative analysis of support vector machines and extreme learning machines.

PubMed

Liu, Xueyi; Gao, Chuanhou; Li, Ping

2012-09-01

The theory of extreme learning machines (ELMs) has recently become increasingly popular. As a new learning algorithm for single-hidden-layer feed-forward neural networks, an ELM offers the advantages of low computational cost, good generalization ability, and ease of implementation. Hence the comparison and model selection between ELMs and other kinds of state-of-the-art machine learning approaches has become significant and has attracted many research efforts. This paper performs a comparative analysis of the basic ELMs and support vector machines (SVMs) from two viewpoints that are different from previous works: one is the Vapnik-Chervonenkis (VC) dimension, and the other is their performance under different training sample sizes. It is shown that the VC dimension of an ELM is equal to the number of hidden nodes of the ELM with probability one. Additionally, their generalization ability and computational complexity are exhibited with changing training sample size. ELMs have weaker generalization ability than SVMs for small sample but can generalize as well as SVMs for large sample. Remarkably, great superiority in computational speed especially for large-scale sample problems is found in ELMs. The results obtained can provide insight into the essential relationship between them, and can also serve as complementary knowledge for their past experimental and theoretical comparisons. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimation of the vortex length scale and intensity from two-dimensional samples

NASA Technical Reports Server (NTRS)

Reuss, D. L.; Cheng, W. P.

1992-01-01

A method is proposed for estimating flow features that influence flame wrinkling in reciprocating internal combustion engines, where traditional statistical measures of turbulence are suspect. Candidate methods were tested in a computed channel flow where traditional turbulence measures are valid and performance can be rationally evaluated. Two concepts are tested. First, spatial filtering is applied to the two-dimensional velocity distribution and found to reveal structures corresponding to the vorticity field. Decreasing the spatial-frequency cutoff of the filter locally changes the character and size of the flow structures that are revealed by the filter. Second, vortex length scale and intensity is estimated by computing the ensemble-average velocity distribution conditionally sampled on the vorticity peaks. The resulting conditionally sampled 'average vortex' has a peak velocity less than half the rms velocity and a size approximately equal to the two-point-correlation integral-length scale.

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

PubMed Central

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

2014-01-01

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

Computations of total sediment discharge, Niobrara River near Cody, Nebraska

USGS Publications Warehouse

Colby, Bruce R.; Hembree, C.H.

1955-01-01

A natural chute in the Niobrara River near Cody, Nebr., constricts the flow of the river except at high stages to a narrow channel in which the turbulence is sufficient to suspend nearly the total sediment discharge. Because much of the flow originates in the sandhills area of Nebraska, the water discharge and sediment discharge are relatively uniform. Sediment discharges based on depth-integrated samples at a contracted section in the chute and on streamflow records at a recording gage about 1,900 feet upstream are available for the period from April 1948 to September 1953 but are not given directly as continuous records in this report. Sediment measurements have been made periodically near the gage and at other nearby relatively unconfined sections of the stream for comparison with measurements at the contracted section. Sediment discharge at these relatively unconfined sections was computed from formulas for comparison with measured sediment discharges at the contracted section. A form of the Du Boys formula gave computed tonnages of sediment that were unsatisfactory. Sediment discharges as computed from the Schoklitsch formula agreed well with measured sediment discharges that were low, but they were much too low at measured sediment discharges that were higher. The Straub formula gave computed discharges, presumably of bed material, that were several times larger than measured discharges of sediment coarser than 0.125 millimeter. All three of these formulas gave computed sediment discharges that increased with water discharges much less rapidly than the measured discharges of sediment coarser than 0.125 millimeter. The Einstein procedure when applied to a reach that included 10 defined cross sections gave much better agreement between computed sediment discharge and measured sediment discharge than did anyone of the three other formulas that were used. This procedure does not compute the discharge of sediment that is too small to be found in the stream bed in appreciable quantities. Hence, total sediment discharges were obtained by adding computed discharges of sediment larger than 0.125 millimeter to measured discharges of sediment smaller than 0.125 millimeter. The size distributions of the computed sediment discharge compared poorly with the size distributions of sediment discharge at the contracted section. Ten sediment discharges computed from the Einstein procedure as applied to a single section averaged several times the measured sediment discharge for the contracted section and gave size distributions that were unsatisfactory. The Einstein procedure was modified to compute total sediment discharge at an alluvial section from readily measurable field data. The modified procedure uses measurements of bed-material particle sizes, suspended-sediment concentrations and particle sizes from depth-integrated samples, streamflow, and water temperatures. Computations of total sediment discharge were made by using this modified procedure, some for the section at the gaging station and some for each of two other relatively unconfined sections. The size distributions of the computed and the measured sediment discharges agreed reasonably well. Major advantages of this modified procedure include applicability to a single section rather than to a reach of channel, use of measured velocity instead of water-surface slope, use of depth-integrated samples, and apparently fair accuracy for computing both total sediment discharge and approximate size distribution of the sediment. Because of these advantages this modified procedure is being further studied to increase its accuracy, to simplify the required computations, and to define its limitations. In the development of the modified procedure, some relationships concerning theories of sediment transport were reviewed and checked against field data. Vertical distributions of suspended sediment at relatively unconfined sections did not agree well with theoretical dist

Estimating Standardized Linear Contrasts of Means with Desired Precision

ERIC Educational Resources Information Center

Bonett, Douglas G.

2009-01-01

L. Wilkinson and the Task Force on Statistical Inference (1999) recommended reporting confidence intervals for measures of effect sizes. If the sample size is too small, the confidence interval may be too wide to provide meaningful information. Recently, K. Kelley and J. R. Rausch (2006) used an iterative approach to computer-generate tables of…

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

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

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested withmore » real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.« less

DOSESCREEN: a computer program to aid dose placement

Treesearch

Kimberly C. Smith; Jacqueline L. Robertson

1984-01-01

Careful selection of an experimental design for a bioassay substantially improves the precision of effective dose (ED) estimates. Design considerations typically include determination of sample size, dose selection, and allocation of subjects to doses. DOSESCREEN is a computer program written to help investigators select an efficient design for the estimation of an...

Young Children's Computer Skills Development from Kindergarten to Third Grade

ERIC Educational Resources Information Center

Sackes, Mesut; Trundle, Kathy Cabe; Bell, Randy L.

2011-01-01

This investigation explores young children's computer skills development from kindergarten to third grade using the Early Childhood Longitudinal Study-Kindergarten (ECLS-K) dataset. The sample size of the study was 8642 children. Latent growth curve modeling analysis was used as an analytical tool to examine the development of children's computer…

Computing physical properties with quantum Monte Carlo methods with statistical fluctuations independent of system size.

PubMed

Assaraf, Roland

2014-12-01

We show that the recently proposed correlated sampling without reweighting procedure extends the locality (asymptotic independence of the system size) of a physical property to the statistical fluctuations of its estimator. This makes the approach potentially vastly more efficient for computing space-localized properties in large systems compared with standard correlated methods. A proof is given for a large collection of noninteracting fragments. Calculations on hydrogen chains suggest that this behavior holds not only for systems displaying short-range correlations, but also for systems with long-range correlations.

Modulated error diffusion CGHs for neural nets

NASA Astrophysics Data System (ADS)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

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

NASA Technical Reports Server (NTRS)

De, Salvo L. J.

1994-01-01

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

Sensitivity and specificity of normality tests and consequences on reference interval accuracy at small sample size: a computer-simulation study.

PubMed

Le Boedec, Kevin

2016-12-01

According to international guidelines, parametric methods must be chosen for RI construction when the sample size is small and the distribution is Gaussian. However, normality tests may not be accurate at small sample size. The purpose of the study was to evaluate normality test performance to properly identify samples extracted from a Gaussian population at small sample sizes, and assess the consequences on RI accuracy of applying parametric methods to samples that falsely identified the parent population as Gaussian. Samples of n = 60 and n = 30 values were randomly selected 100 times from simulated Gaussian, lognormal, and asymmetric populations of 10,000 values. The sensitivity and specificity of 4 normality tests were compared. Reference intervals were calculated using 6 different statistical methods from samples that falsely identified the parent population as Gaussian, and their accuracy was compared. Shapiro-Wilk and D'Agostino-Pearson tests were the best performing normality tests. However, their specificity was poor at sample size n = 30 (specificity for P < .05: .51 and .50, respectively). The best significance levels identified when n = 30 were 0.19 for Shapiro-Wilk test and 0.18 for D'Agostino-Pearson test. Using parametric methods on samples extracted from a lognormal population but falsely identified as Gaussian led to clinically relevant inaccuracies. At small sample size, normality tests may lead to erroneous use of parametric methods to build RI. Using nonparametric methods (or alternatively Box-Cox transformation) on all samples regardless of their distribution or adjusting, the significance level of normality tests depending on sample size would limit the risk of constructing inaccurate RI. © 2016 American Society for Veterinary Clinical Pathology.

Extension of latin hypercube samples with correlated variables.

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

Hora, Stephen Curtis; Helton, Jon Craig; 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 ofmore » model evaluations.« less

EX VIVO MODEL FOR THE CHARACTERIZATION AND IDENTIFICATION OF DRYWALL INTRAOCULAR FOREIGN BODIES ON COMPUTED TOMOGRAPHY.

PubMed

Syed, Reema; Kim, Sung-Hye; Palacio, Agustina; Nunery, William R; Schaal, Shlomit

2017-06-06

The study was inspired after the authors encountered a patient with a penetrating globe injury due to drywall, who had retained intraocular drywall foreign body. Computed tomography (CT) was read as normal in this patient. Open globe injury with drywall has never been reported previously in the literature and there are no previous studies describing its radiographic features. The case report is described in detail elsewhere. This was an experimental study. An ex vivo model of 15 porcine eyes with 1 mm to 5 mm fragments of implanted drywall, 2 vitreous only samples with drywall and 3 control eyes were used. Eyes and vitreous samples were CT scanned on Days 0, 1, and 3 postimplantation. Computed ocular images were analyzed by masked observers. Size and radiodensity of intraocular drywall were measured using Hounsfield units (HUs) over time. Intraocular drywall was hyperdense on CT. All sizes studied were detectable on Day 0 of scanning. Mean intraocular drywall foreign body density was 171 ± 52 Hounsfield units (70-237) depending on fragment size. Intraocular drywall foreign body decreased in size whereas Hounsfield unit intensity increased over time. Drywall dissolves in the eye and becomes denser over time as air in the drywall is replaced by fluid. This study identified Hounsfield Units specific to intraocular drywall foreign body over time.

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

USGS Publications Warehouse

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

1992-01-01

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

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

NASA Astrophysics Data System (ADS)

Luo, L.; Cheng, Z.

2016-12-01

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

Computer program documentation for the patch subsampling processor

NASA Technical Reports Server (NTRS)

Nieves, M. J.; Obrien, S. O.; Oney, J. K. (Principal Investigator)

1981-01-01

The programs presented are intended to provide a way to extract a sample from a full-frame scene and summarize it in a useful way. The sample in each case was chosen to fill a 512-by-512 pixel (sample-by-line) image since this is the largest image that can be displayed on the Integrated Multivariant Data Analysis and Classification System. This sample size provides one megabyte of data for manipulation and storage and contains about 3% of the full-frame data. A patch image processor computes means for 256 32-by-32 pixel squares which constitute the 512-by-512 pixel image. Thus, 256 measurements are available for 8 vegetation indexes over a 100-mile square.

Particle systems for adaptive, isotropic meshing of CAD models

PubMed Central

Levine, Joshua A.; Whitaker, Ross T.

2012-01-01

We present a particle-based approach for generating adaptive triangular surface and tetrahedral volume meshes from computer-aided design models. Input shapes are treated as a collection of smooth, parametric surface patches that can meet non-smoothly on boundaries. Our approach uses a hierarchical sampling scheme that places particles on features in order of increasing dimensionality. These particles reach a good distribution by minimizing an energy computed in 3D world space, with movements occurring in the parametric space of each surface patch. Rather than using a pre-computed measure of feature size, our system automatically adapts to both curvature as well as a notion of topological separation. It also enforces a measure of smoothness on these constraints to construct a sizing field that acts as a proxy to piecewise-smooth feature size. We evaluate our technique with comparisons against other popular triangular meshing techniques for this domain. PMID:23162181

Structure and properties of clinical coralline implants measured via 3D imaging and analysis.

PubMed

Knackstedt, Mark Alexander; Arns, Christoph H; Senden, Tim J; Gross, Karlis

2006-05-01

The development and design of advanced porous materials for biomedical applications requires a thorough understanding of how material structure impacts on mechanical and transport properties. This paper illustrates a 3D imaging and analysis study of two clinically proven coral bone graft samples (Porites and Goniopora). Images are obtained from X-ray micro-computed tomography (micro-CT) at a resolution of 16.8 microm. A visual comparison of the two images shows very different structure; Porites has a homogeneous structure and consistent pore size while Goniopora has a bimodal pore size and a strongly disordered structure. A number of 3D structural characteristics are measured directly on the images including pore volume-to-surface-area, pore and solid size distributions, chord length measurements and tortuosity. Computational results made directly on the digitized tomographic images are presented for the permeability, diffusivity and elastic modulus of the coral samples. The results allow one to quantify differences between the two samples. 3D digital analysis can provide a more thorough assessment of biomaterial structure including the pore wall thickness, local flow, mechanical properties and diffusion pathways. We discuss the implications of these results to the development of optimal scaffold design for tissue ingrowth.

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

USGS Publications Warehouse

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

2009-01-01

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

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

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

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

Internet design preferences of patients with cancer.

PubMed

Chernecky, Cynthia; Macklin, Denise; Walter, Jennifer

2006-07-01

To describe computer experience and preferences for multimedia design. Prospective, descriptive. Physician office and outpatient cancer centers in an urban area in the southeastern United States. Convenience sample of 22 volunteer patients with cancer from four racial groups. A questionnaire on computer experiences was followed by a hands-on computer session with questions regarding preferences for seven interface items. Data termination occurred when sample size was obtained. Design of Internet education site for patients. Variables include preferences, computer, cancer, multimedia, and education. Eighty-two percent had personal computers, 41% used a computer daily, and 95% believed that computers would be a good avenue for learning about cancer care. Preferences included display colors in blue and green hues; colored buttons; easy-to-read text; graphics with a simple design and large, clear pictures; serif font in dark type; light-colored background; and larger photo size in a rectangle shape. Most popular graphic icons as metaphors were 911 for emergency, picture of skull and crossbones for danger, and a picture of a string on an index finger representing reminder. The simple layout most preferred for appearances was one that included text and pictures, read from left to right, and was symmetrical in its placement of pictures and text on the page. Preferences are necessary to maintain interest and support navigation through computer designs to enhance the translation of knowledge to patients. Development of multimedia based on patient preferences will enhance education, learning, and, ultimately, quality patient care.

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

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

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

1982-05-01

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

A Fourier transform with speed improvements for microprocessor applications

NASA Technical Reports Server (NTRS)

Lokerson, D. C.; Rochelle, R.

1980-01-01

A fast Fourier transform algorithm for the RCA 1802microprocessor was developed for spacecraft instrument applications. The computations were tailored for the restrictions an eight bit machine imposes. The algorithm incorporates some aspects of Walsh function sequency to improve operational speed. This method uses a register to add a value proportional to the period of the band being processed before each computation is to be considered. If the result overflows into the DF register, the data sample is used in computation; otherwise computation is skipped. This operation is repeated for each of the 64 data samples. This technique is used for both sine and cosine portions of the computation. The processing uses eight bit data, but because of the many computations that can increase the size of the coefficient, floating point form is used. A method to reduce the alias problem in the lower bands is also described.

3D data processing with advanced computer graphics tools

NASA Astrophysics Data System (ADS)

Zhang, Song; Ekstrand, Laura; Grieve, Taylor; Eisenmann, David J.; Chumbley, L. Scott

2012-09-01

Often, the 3-D raw data coming from an optical profilometer contains spiky noises and irregular grid, which make it difficult to analyze and difficult to store because of the enormously large size. This paper is to address these two issues for an optical profilometer by substantially reducing the spiky noise of the 3-D raw data from an optical profilometer, and by rapidly re-sampling the raw data into regular grids at any pixel size and any orientation with advanced computer graphics tools. Experimental results will be presented to demonstrate the effectiveness of the proposed approach.

Influence of pore size distributions on decomposition of maize leaf residue: evidence from X-ray computed micro-tomography

NASA Astrophysics Data System (ADS)

Negassa, Wakene; Guber, Andrey; Kravchenko, Alexandra; Rivers, Mark

2014-05-01

Soil's potential to sequester carbon (C) depends not only on quality and quantity of organic inputs to soil but also on the residence time of the applied organic inputs within the soil. Soil pore structure is one of the main factors that influence residence time of soil organic matter by controlling gas exchange, soil moisture and microbial activities, thereby soil C sequestration capacity. Previous attempts to investigate the fate of organic inputs added to soil did not allow examining their decomposition in situ; the drawback that can now be remediated by application of X-ray computed micro-tomography (µ-CT). The non-destructive and non-invasive nature of µ-CT gives an opportunity to investigate the effect of soil pore size distributions on decomposition of plant residues at a new quantitative level. The objective of this study is to examine the influence of pore size distributions on the decomposition of plant residue added to soil. Samples with contrasting pore size distributions were created using aggregate fractions of five different sizes (<0.05, 0.05-0.1, 0.10-05, 0.5-1.0 and 1.0-2.0 mm). Weighted average pore diameters ranged from 10 µm (<0.05 mm fraction) to 104 µm (1-2 mm fraction), while maximum pore diameter were in a range from 29 µm (<0.05 mm fraction) to 568 µm (1-2 mm fraction) in the created soil samples. Dried pieces of maize leaves 2.5 mg in size (equivalent to 1.71 mg C g-1 soil) were added to half of the studied samples. Samples with and without maize leaves were incubated for 120 days. CO2 emission from the samples was measured at regular time intervals. In order to ensure that the observed differences are due to differences in pore structure and not due to differences in inherent properties of the studied aggregate fractions, we repeated the whole experiment using soil from the same aggregate size fractions but ground to <0.05 mm size. Five to six replicated samples were used for intact and ground samples of all sizes with and without leaves. Two replications of the intact aggregate fractions of all sizes with leaves were subjected to µ-CT scanning before and after incubation, whereas all the remaining replications of both intact and ground aggregate fractions of <0.05, 0.05-0.1, and 1.0-2.0 mm sizes with leaves were scanned with µ-CT after the incubation. The µ-CT image showed that approximately 80% of the leaves in the intact samples of large aggregate fractions (0.5-1.0 and 1.0-2.0 mm) was decomposed during the incubation, while only 50-60% of the leaves were decomposed in the intact samples of smaller sized fractions. Even lower percent of leaves (40-50%) was decomposed in the ground samples, with very similar leaf decomposition observed in all ground samples regardless of the aggregate fraction size. Consistent with µ-CT results, the proportion of decomposed leaf estimated with the conventional mass loss method was 48% and 60% for the <0.05 mm and 1.0-2.0 mm soil size fractions of intact aggregates, and 40-50% in ground samples, respectively. The results of the incubation experiment demonstrated that, while greater C mineralization was observed in samples of all size fractions amended with leaf, the effect of leaf presence was most pronounced in the smaller aggregate fractions (0.05-0.1 mm and 0.05 mm) of intact aggregates. The results of the present study unequivocally demonstrate that differences in pore size distributions have a major effect on the decomposition of plant residues added to soil. Moreover, in presence of plant residues, differences in pore size distributions appear to also influence the rates of decomposition of the intrinsic soil organic material.

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

NASA Technical Reports Server (NTRS)

Bosson, Christabelle; Xue, Min; Zelinski, Shannon

2014-01-01

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

Number of pins in two-stage stratified sampling for estimating herbage yield

Treesearch

William G. O' Regan; C. Eugene Conrad

1975-01-01

In a two-stage stratified procedure for sampling herbage yield, plots are stratified by a pin frame in stage one, and clipped. In stage two, clippings from selected plots are sorted, dried, and weighed. Sample size and distribution of plots between the two stages are determined by equations. A way to compute the effect of number of pins on the variance of estimated...

Determination of the influence of dispersion pattern of pesticide-resistant individuals on the reliability of resistance estimates using different sampling plans.

PubMed

Shah, R; Worner, S P; Chapman, R B

2012-10-01

Pesticide resistance monitoring includes resistance detection and subsequent documentation/ measurement. Resistance detection would require at least one (≥1) resistant individual(s) to be present in a sample to initiate management strategies. Resistance documentation, on the other hand, would attempt to get an estimate of the entire population (≥90%) of the resistant individuals. A computer simulation model was used to compare the efficiency of simple random and systematic sampling plans to detect resistant individuals and to document their frequencies when the resistant individuals were randomly or patchily distributed. A patchy dispersion pattern of resistant individuals influenced the sampling efficiency of systematic sampling plans while the efficiency of random sampling was independent of such patchiness. When resistant individuals were randomly distributed, sample sizes required to detect at least one resistant individual (resistance detection) with a probability of 0.95 were 300 (1%) and 50 (10% and 20%); whereas, when resistant individuals were patchily distributed, using systematic sampling, sample sizes required for such detection were 6000 (1%), 600 (10%) and 300 (20%). Sample sizes of 900 and 400 would be required to detect ≥90% of resistant individuals (resistance documentation) with a probability of 0.95 when resistant individuals were randomly dispersed and present at a frequency of 10% and 20%, respectively; whereas, when resistant individuals were patchily distributed, using systematic sampling, a sample size of 3000 and 1500, respectively, was necessary. Small sample sizes either underestimated or overestimated the resistance frequency. A simple random sampling plan is, therefore, recommended for insecticide resistance detection and subsequent documentation.

Confidence intervals and sample size calculations for the standardized mean difference effect size between two normal populations under heteroscedasticity.

PubMed

Shieh, G

2013-12-01

The use of effect sizes and associated confidence intervals in all empirical research has been strongly emphasized by journal publication guidelines. To help advance theory and practice in the social sciences, this article describes an improved procedure for constructing confidence intervals of the standardized mean difference effect size between two independent normal populations with unknown and possibly unequal variances. The presented approach has advantages over the existing formula in both theoretical justification and computational simplicity. In addition, simulation results show that the suggested one- and two-sided confidence intervals are more accurate in achieving the nominal coverage probability. The proposed estimation method provides a feasible alternative to the most commonly used measure of Cohen's d and the corresponding interval procedure when the assumption of homogeneous variances is not tenable. To further improve the potential applicability of the suggested methodology, the sample size procedures for precise interval estimation of the standardized mean difference are also delineated. The desired precision of a confidence interval is assessed with respect to the control of expected width and to the assurance probability of interval width within a designated value. Supplementary computer programs are developed to aid in the usefulness and implementation of the introduced techniques.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

Compiling and editing agricultural strata boundaries with remotely sensed imagery and map attribute data using graphics workstations

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1991-01-01

The USDA presently uses labor-intensive photographic interpretation procedures to delineate large geographical areas into manageable size sampling units for the estimation of domestic crop and livestock production. Computer software to automate the boundary delineation procedure, called the computer-assisted stratification and sampling (CASS) system, was developed using a Hewlett Packard color-graphics workstation. The CASS procedures display Thematic Mapper (TM) satellite digital imagery on a graphics display workstation as the backdrop for the onscreen delineation of sampling units. USGS Digital Line Graph (DLG) data for roads and waterways are displayed over the TM imagery to aid in identifying potential sample unit boundaries. Initial analysis conducted with three Missouri counties indicated that CASS was six times faster than the manual techniques in delineating sampling units.

An ergonomic evaluation comparing desktop, notebook, and subnotebook computers.

PubMed

Szeto, Grace P; Lee, Raymond

2002-04-01

To evaluate and compare the postures and movements of the cervical and upper thoracic spine, the typing performance, and workstation ergonomic factors when using a desktop, notebook, and subnotebook computers. Repeated-measures design. A motion analysis laboratory with an electromagnetic tracking device. A convenience sample of 21 university students between ages 20 and 24 years with no history of neck or shoulder discomfort. Each subject performed a standardized typing task by using each of the 3 computers. Measurements during the typing task were taken at set intervals. Cervical and thoracic spines adopted a more flexed posture in using the smaller-sized computers. There were significantly greater neck movements in using desktop computers when compared with the notebook and subnotebook computers. The viewing distances adopted by the subjects decreased as the computer size decreased. Typing performance and subjective rating of difficulty in using the keyboards were also significantly different among the 3 types of computers. Computer users need to consider the posture of the spine and potential risk of developing musculoskeletal discomfort in choosing computers. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Multiscaling properties of coastal waters particle size distribution from LISST in situ measurements

NASA Astrophysics Data System (ADS)

Pannimpullath Remanan, R.; Schmitt, F. G.; Loisel, H.; Mériaux, X.

2013-12-01

An eulerian high frequency sampling of particle size distribution (PSD) is performed during 5 tidal cycles (65 hours) in a coastal environment of the eastern English Channel at 1 Hz. The particle data are recorded using a LISST-100x type C (Laser In Situ Scattering and Transmissometry, Sequoia Scientific), recording volume concentrations of particles having diameters ranging from 2.5 to 500 mu in 32 size classes in logarithmic scale. This enables the estimation at each time step (every second) of the probability density function of particle sizes. At every time step, the pdf of PSD is hyperbolic. We can thus estimate PSD slope time series. Power spectral analysis shows that the mean diameter of the suspended particles is scaling at high frequencies (from 1s to 1000s). The scaling properties of particle sizes is studied by computing the moment function, from the pdf of the size distribution. Moment functions at many different time scales (from 1s to 1000 s) are computed and their scaling properties considered. The Shannon entropy at each time scale is also estimated and is related to other parameters. The multiscaling properties of the turbidity (coefficient cp computed from the LISST) are also consider on the same time scales, using Empirical Mode Decomposition.

Simplified methods for computing total sediment discharge with the modified Einstein procedure

USGS Publications Warehouse

Colby, Bruce R.; Hubbell, David Wellington

1961-01-01

A procedure was presented in 1950 by H. A. Einstein for computing the total discharge of sediment particles of sizes that are in appreciable quantities in the stream bed. This procedure was modified by the U.S. Geological Survey and adapted to computing the total sediment discharge of a stream on the basis of samples of bed sediment, depth-integrated samples of suspended sediment, streamflow measurements, and water temperature. This paper gives simplified methods for computing total sediment discharge by the modified Einstein procedure. Each of four homographs appreciably simplifies a major step in the computations. Within the stated limitations, use of the homographs introduces much less error than is present in either the basic data or the theories on which the computations of total sediment discharge are based. The results are nearly as accurate mathematically as those that could be obtained from the longer and more complex arithmetic and algebraic computations of the Einstein procedure.

Evaluation of 3D airway imaging of obstructive sleep apnea with cone-beam computed tomography.

PubMed

Ogawa, Takumi; Enciso, Reyes; Memon, Ahmed; Mah, James K; Clark, Glenn T

2005-01-01

This study evaluates the use of cone-beam Computer Tomography (CT) for imaging the upper airway structure of Obstructive Sleep Apnea (OSA) patients. The total airway volume and the anteroposterior dimension of oropharyngeal airway showed significant group differences between OSA and gender-matched controls, so if we increase sample size these measurements may distinguish the two groups. We demonstrate the utility of diagnosis of anatomy with the 3D airway imaging with cone-beam Computed Tomography.

Designing group sequential randomized clinical trials with time to event end points using a R function.

PubMed

Filleron, Thomas; Gal, Jocelyn; Kramar, Andrew

2012-10-01

A major and difficult task is the design of clinical trials with a time to event endpoint. In fact, it is necessary to compute the number of events and in a second step the required number of patients. Several commercial software packages are available for computing sample size in clinical trials with sequential designs and time to event endpoints, but there are a few R functions implemented. The purpose of this paper is to describe features and use of the R function. plansurvct.func, which is an add-on function to the package gsDesign which permits in one run of the program to calculate the number of events, and required sample size but also boundaries and corresponding p-values for a group sequential design. The use of the function plansurvct.func is illustrated by several examples and validated using East software. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Search for Minimal and Semi-Minimal Rule Sets in Incremental Learning of Context-Free and Definite Clause Grammars

NASA Astrophysics Data System (ADS)

Imada, Keita; Nakamura, Katsuhiko

This paper describes recent improvements to Synapse system for incremental learning of general context-free grammars (CFGs) and definite clause grammars (DCGs) from positive and negative sample strings. An important feature of our approach is incremental learning, which is realized by a rule generation mechanism called “bridging” based on bottom-up parsing for positive samples and the search for rule sets. The sizes of rule sets and the computation time depend on the search strategies. In addition to the global search for synthesizing minimal rule sets and serial search, another method for synthesizing semi-optimum rule sets, we incorporate beam search to the system for synthesizing semi-minimal rule sets. The paper shows several experimental results on learning CFGs and DCGs, and we analyze the sizes of rule sets and the computation time.

Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials.

PubMed

Wu, Zhichao; Medeiros, Felipe A

2018-03-20

Visual field testing is an important endpoint in glaucoma clinical trials, and the testing paradigm used can have a significant impact on the sample size requirements. To investigate this, this study included 353 eyes of 247 glaucoma patients seen over a 3-year period to extract real-world visual field rates of change and variability estimates to provide sample size estimates from computer simulations. The clinical trial scenario assumed that a new treatment was added to one of two groups that were both under routine clinical care, with various treatment effects examined. Three different visual field testing paradigms were evaluated: a) evenly spaced testing, b) United Kingdom Glaucoma Treatment Study (UKGTS) follow-up scheme, which adds clustered tests at the beginning and end of follow-up in addition to evenly spaced testing, and c) clustered testing paradigm, with clusters of tests at the beginning and end of the trial period and two intermediary visits. The sample size requirements were reduced by 17-19% and 39-40% using the UKGTS and clustered testing paradigms, respectively, when compared to the evenly spaced approach. These findings highlight how the clustered testing paradigm can substantially reduce sample size requirements and improve the feasibility of future glaucoma clinical trials.

The Effectiveness of Self-Regulated Learning Scaffolds on Academic Performance in Computer-Based Learning Environments: A Meta-Analysis

ERIC Educational Resources Information Center

Zheng, Lanqin

2016-01-01

This meta-analysis examined research on the effects of self-regulated learning scaffolds on academic performance in computer-based learning environments from 2004 to 2015. A total of 29 articles met inclusion criteria and were included in the final analysis with a total sample size of 2,648 students. Moderator analyses were performed using a…

Computed Tomography Status

DOE R&D Accomplishments Database

Hansche, B. D.

1983-01-01

Computed tomography (CT) is a relatively new radiographic technique which has become widely used in the medical field, where it is better known as computerized axial tomographic (CAT) scanning. This technique is also being adopted by the industrial radiographic community, although the greater range of densities, variation in samples sizes, plus possible requirement for finer resolution make it difficult to duplicate the excellent results that the medical scanners have achieved.

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

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

2007-07-01

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

Eye-gaze determination of user intent at the computer interface

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

Goldberg, J.H.; Schryver, J.C.

1993-12-31

Determination of user intent at the computer interface through eye-gaze monitoring can significantly aid applications for the disabled, as well as telerobotics and process control interfaces. Whereas current eye-gaze control applications are limited to object selection and x/y gazepoint tracking, a methodology was developed here to discriminate a more abstract interface operation: zooming-in or out. This methodology first collects samples of eve-gaze location looking at controlled stimuli, at 30 Hz, just prior to a user`s decision to zoom. The sample is broken into data frames, or temporal snapshots. Within a data frame, all spatial samples are connected into a minimummore » spanning tree, then clustered, according to user defined parameters. Each cluster is mapped to one in the prior data frame, and statistics are computed from each cluster. These characteristics include cluster size, position, and pupil size. A multiple discriminant analysis uses these statistics both within and between data frames to formulate optimal rules for assigning the observations into zooming, zoom-out, or no zoom conditions. The statistical procedure effectively generates heuristics for future assignments, based upon these variables. Future work will enhance the accuracy and precision of the modeling technique, and will empirically test users in controlled experiments.« less

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Parameterization of Shortwave Cloud Optical Properties for a Mixture of Ice Particle Habits for use in Atmospheric Models

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lee, Kyu-Tae; Yang, Ping; Lau, William K. M. (Technical Monitor)

2002-01-01

Based on the single-scattering optical properties pre-computed with an improved geometric optics method, the bulk absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the effective particle size of a mixture of ice habits, the ice water amount, and spectral band. The parameterization has been applied to computing fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. It is found that flux calculations are not overly sensitive to the assumed particle habits if the definition of the effective particle size is consistent with the particle habits that the parameterization is based. Otherwise, the error in the flux calculations could reach a magnitude unacceptable for climate studies. Different from many previous studies, the parameterization requires only an effective particle size representing all ice habits in a cloud layer, but not the effective size of individual ice habits.

Computer program for the calculation of grain size statistics by the method of moments

USGS Publications Warehouse

Sawyer, Michael B.

1977-01-01

A computer program is presented for a Hewlett-Packard Model 9830A desk-top calculator (1) which calculates statistics using weight or point count data from a grain-size analysis. The program uses the method of moments in contrast to the more commonly used but less inclusive graphic method of Folk and Ward (1957). The merits of the program are: (1) it is rapid; (2) it can accept data in either grouped or ungrouped format; (3) it allows direct comparison with grain-size data in the literature that have been calculated by the method of moments; (4) it utilizes all of the original data rather than percentiles from the cumulative curve as in the approximation technique used by the graphic method; (5) it is written in the computer language BASIC, which is easily modified and adapted to a wide variety of computers; and (6) when used in the HP-9830A, it does not require punching of data cards. The method of moments should be used only if the entire sample has been measured and the worker defines the measured grain-size range. (1) Use of brand names in this paper does not imply endorsement of these products by the U.S. Geological Survey.

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

PubMed

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

2009-08-01

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

Overcoming time scale and finite size limitations to compute nucleation rates from small scale well tempered metadynamics simulations.

PubMed

Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele

2016-12-07

Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.

Overcoming time scale and finite size limitations to compute nucleation rates from small scale well tempered metadynamics simulations

NASA Astrophysics Data System (ADS)

Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele

2016-12-01

Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.

Sampling design for the 1980 commercial and multifamily residential building survey

NASA Astrophysics Data System (ADS)

Bowen, W. M.; Olsen, A. R.; Nieves, A. L.

1981-06-01

The extent to which new building design practices comply with the proposed 1980 energy budget levels for commercial and multifamily residential building designs (DEB-80) can be assessed by: (1) identifying small number of building types which account for the majority of commercial buildings constructed in the U.S.A.; (2) conducting a separate survey for each building type; and (3) including only buildings designed during 1980. For each building, the design energy consumption (DEC-80) will be determined by the DOE2.1 computer program. The quantity X = (DEC-80 - DEB-80). These X quantities can then be used to compute sample statistics. Inferences about nationwide compliance with DEB-80 may then be made for each building type. Details of the population, sampling frame, stratification, sample size, and implementation of the sampling plan are provided.

Improved Optics For Quasi-Elastic Light Scattering

NASA Technical Reports Server (NTRS)

Cheung, Harry Michael

1995-01-01

Improved optical train devised for use in light-scattering measurements of quasi-elastic light scattering (QELS) and laser spectroscopy. Measurements performed on solutions, microemulsions, micellular solutions, and colloidal dispersions. Simultaneous measurements of total intensity and fluctuations in total intensity of light scattered from sample at various angles provides data used, in conjunction with diffusion coefficients, to compute sizes of particles in sample.

Influence of Sample Size of Polymer Materials on Aging Characteristics in the Salt Fog Test

NASA Astrophysics Data System (ADS)

Otsubo, Masahisa; Anami, Naoya; Yamashita, Seiji; Honda, Chikahisa; Takenouchi, Osamu; Hashimoto, Yousuke

Polymer insulators have been used in worldwide because of some superior properties; light weight, high mechanical strength, good hydrophobicity etc., as compared with porcelain insulators. In this paper, effect of sample size on the aging characteristics in the salt fog test is examined. Leakage current was measured by using 100 MHz AD board or 100 MHz digital oscilloscope and separated three components as conductive current, corona discharge current and dry band arc discharge current by using FFT and the current differential method newly proposed. Each component cumulative charge was estimated automatically by a personal computer. As the results, when the sample size increased under the same average applied electric field, the peak values of leakage current and each component current increased. Especially, the cumulative charges and the arc discharge length of dry band arc discharge increased remarkably with the increase of gap length.

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

PubMed

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

2015-02-01

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

Determining Plane-Sweep Sampling Points in Image Space Using the Cross-Ratio for Image-Based Depth Estimation

NASA Astrophysics Data System (ADS)

Ruf, B.; Erdnuess, B.; Weinmann, M.

2017-08-01

With the emergence of small consumer Unmanned Aerial Vehicles (UAVs), the importance and interest of image-based depth estimation and model generation from aerial images has greatly increased in the photogrammetric society. In our work, we focus on algorithms that allow an online image-based dense depth estimation from video sequences, which enables the direct and live structural analysis of the depicted scene. Therefore, we use a multi-view plane-sweep algorithm with a semi-global matching (SGM) optimization which is parallelized for general purpose computation on a GPU (GPGPU), reaching sufficient performance to keep up with the key-frames of input sequences. One important aspect to reach good performance is the way to sample the scene space, creating plane hypotheses. A small step size between consecutive planes, which is needed to reconstruct details in the near vicinity of the camera may lead to ambiguities in distant regions, due to the perspective projection of the camera. Furthermore, an equidistant sampling with a small step size produces a large number of plane hypotheses, leading to high computational effort. To overcome these problems, we present a novel methodology to directly determine the sampling points of plane-sweep algorithms in image space. The use of the perspective invariant cross-ratio allows us to derive the location of the sampling planes directly from the image data. With this, we efficiently sample the scene space, achieving higher sampling density in areas which are close to the camera and a lower density in distant regions. We evaluate our approach on a synthetic benchmark dataset for quantitative evaluation and on a real-image dataset consisting of aerial imagery. The experiments reveal that an inverse sampling achieves equal and better results than a linear sampling, with less sampling points and thus less runtime. Our algorithm allows an online computation of depth maps for subsequences of five frames, provided that the relative poses between all frames are given.

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

Modeling Endovascular Coils as Heterogeneous Porous Media

NASA Astrophysics Data System (ADS)

Yadollahi Farsani, H.; Herrmann, M.; Chong, B.; Frakes, D.

2016-12-01

Minimally invasive surgeries are the stat-of-the-art treatments for many pathologies. Treating brain aneurysms is no exception; invasive neurovascular clipping is no longer the only option and endovascular coiling has introduced itself as the most common treatment. Coiling isolates the aneurysm from blood circulation by promoting thrombosis within the aneurysm. One approach to studying intra-aneurysmal hemodynamics consists of virtually deploying finite element coil models and then performing computational fluid dynamics. However, this approach is often computationally expensive and requires extensive resources to perform. The porous medium approach has been considered as an alternative to the conventional coil modeling approach because it lessens the complexities of computational fluid dynamics simulations by reducing the number of mesh elements needed to discretize the domain. There have been a limited number of attempts at treating the endovascular coils as homogeneous porous media. However, the heterogeneity associated with coil configurations requires a more accurately defined porous medium in which the porosity and permeability change throughout the domain. We implemented this approach by introducing a lattice of sample volumes and utilizing techniques available in the field of interactive computer graphics. We observed that the introduction of the heterogeneity assumption was associated with significant changes in simulated aneurysmal flow velocities as compared to the homogeneous assumption case. Moreover, as the sample volume size was decreased, the flow velocities approached an asymptotical value, showing the importance of the sample volume size selection. These results demonstrate that the homogeneous assumption for porous media that are inherently heterogeneous can lead to considerable errors. Additionally, this modeling approach allowed us to simulate post-treatment flows without considering the explicit geometry of a deployed endovascular coil mass, greatly simplifying computation.

Constraining particle size-dependent plume sedimentation from the 17 June 1996 eruption of Ruapehu Volcano, New Zealand, using geophysical inversions

NASA Astrophysics Data System (ADS)

Klawonn, M.; Frazer, L. N.; Wolfe, C. J.; Houghton, B. F.; Rosenberg, M. D.

2014-03-01

Weak subplinian-plinian plumes pose frequent hazards to populations and aviation, yet many key parameters of these particle-laden plumes are, to date, poorly constrained. This study recovers the particle size-dependent mass distribution along the trajectory of a well-constrained weak plume by inverting the dispersion process of tephra fallout. We use the example of the 17 June 1996 Ruapehu eruption in New Zealand and base our computations on mass per unit area tephra measurements and grain size distributions at 118 sample locations. Comparisons of particle fall times and time of sampling collection, as well as observations during the eruption, reveal that particles smaller than 250 μm likely settled as aggregates. For simplicity we assume that all of these fine particles fell as aggregates of constant size and density, whereas we assume that large particles fell as individual particles at their terminal velocity. Mass fallout along the plume trajectory follows distinct trends between larger particles (d≥250 μm) and the fine population (d<250 μm) that are likely due to the two different settling behaviors (aggregate settling versus single-particle settling). In addition, we computed the resulting particle size distribution within the weak plume along its axis and find that the particle mode shifts from an initial 1φ mode to a 2.5φ mode 10 km from the vent and is dominated by a 2.5 to 3φ mode 10-180 km from vent, where the plume reaches the coastline and we do not have further field constraints. The computed particle distributions inside the plume provide new constraints on the mass transport processes within weak plumes and improve previous models. The distinct decay trends between single-particle settling and aggregate settling may serve as a new tool to identify particle sizes that fell as aggregates for other eruptions.

Estimating the Size of a Large Network and its Communities from a Random Sample

PubMed Central

Chen, Lin; Karbasi, Amin; Crawford, Forrest W.

2017-01-01

Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = (V, E) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G(W) be the induced subgraph in G of the vertices in W. In addition to G(W), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K, and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios. PMID:28867924

Estimating the Size of a Large Network and its Communities from a Random Sample.

PubMed

Chen, Lin; Karbasi, Amin; Crawford, Forrest W

2016-01-01

Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of the most important global properties is the number of vertices/nodes in the network. Estimating the number of vertices in a large network is a major challenge in computer science, epidemiology, demography, and intelligence analysis. In this paper we consider a population random graph G = ( V, E ) from the stochastic block model (SBM) with K communities/blocks. A sample is obtained by randomly choosing a subset W ⊆ V and letting G ( W ) be the induced subgraph in G of the vertices in W . In addition to G ( W ), we observe the total degree of each sampled vertex and its block membership. Given this partial information, we propose an efficient PopULation Size Estimation algorithm, called PULSE, that accurately estimates the size of the whole population as well as the size of each community. To support our theoretical analysis, we perform an exhaustive set of experiments to study the effects of sample size, K , and SBM model parameters on the accuracy of the estimates. The experimental results also demonstrate that PULSE significantly outperforms a widely-used method called the network scale-up estimator in a wide variety of scenarios.

Does exposure to computers affect the routine parameters of semen quality?

PubMed

Sun, Yue-Lian; Zhou, Wei-Jin; Wu, Jun-Qing; Gao, Er-Sheng

2005-09-01

To assess whether exposure to computers harms the semen quality of healthy young men. A total of 178 subjects were recruited from two maternity and children healthcare centers in Shanghai, 91 with a history of exposure to computers (i.e., exposure for 20 h or more per week in the last 2 years) and 87 persons to act as control (no or little exposure to computers). Data on the history of exposure to computers and other characteristics were obtained by means of a structured questionnaire interview. Semen samples were collected by masturbation in the place where the semen samples were analyzed. No differences in the distribution of the semen parameters (semen volume, sperm density, percentage of progressive sperm, sperm viability and percentage of normal form sperm) were found between the exposed group and the control group. Exposure to computers was not found to be a risk factor for inferior semen quality after adjusting for potential confounders, including abstinence days, testicle size, occupation, history of exposure to toxic substances. The present study did not find that healthy men exposed to computers had inferior semen quality.

Comparing the social skills of students addicted to computer games with normal students.

PubMed

Zamani, Eshrat; Kheradmand, Ali; Cheshmi, Maliheh; Abedi, Ahmad; Hedayati, Nasim

2010-01-01

This study aimed to investigate and compare the social skills of studentsaddicted to computer games with normal students. The dependentvariable in the present study is the social skills. The study population included all the students in the second grade ofpublic secondary school in the city of Isfahan at the educational year of2009-2010. The sample size included 564 students selected using thecluster random sampling method. Data collection was conducted usingQuestionnaire of Addiction to Computer Games and Social SkillsQuestionnaire (The Teenage Inventory of Social Skill or TISS). The results of the study showed that generally, there was a significantdifference between the social skills of students addicted to computer gamesand normal students. In addition, the results indicated that normal studentshad a higher level of social skills in comparison with students addicted tocomputer games. As the study results showed, addiction to computer games may affectthe quality and quantity of social skills. In other words, the higher theaddiction to computer games, the less the social skills. The individualsaddicted to computer games have less social skills.).

Comparing the Social Skills of Students Addicted to Computer Games with Normal Students

PubMed Central

Zamani, Eshrat; Kheradmand, Ali; Cheshmi, Maliheh; Abedi, Ahmad; Hedayati, Nasim

2010-01-01

Background This study aimed to investigate and compare the social skills of studentsaddicted to computer games with normal students. The dependentvariable in the present study is the social skills. Methods The study population included all the students in the second grade ofpublic secondary school in the city of Isfahan at the educational year of2009-2010. The sample size included 564 students selected using thecluster random sampling method. Data collection was conducted usingQuestionnaire of Addiction to Computer Games and Social SkillsQuestionnaire (The Teenage Inventory of Social Skill or TISS). Findings The results of the study showed that generally, there was a significantdifference between the social skills of students addicted to computer gamesand normal students. In addition, the results indicated that normal studentshad a higher level of social skills in comparison with students addicted tocomputer games. Conclusion As the study results showed, addiction to computer games may affectthe quality and quantity of social skills. In other words, the higher theaddiction to computer games, the less the social skills. The individualsaddicted to computer games have less social skills.). PMID:24494102

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

NASA Astrophysics Data System (ADS)

Gnanasaravanan, S.; Rajkumar, P.

2013-05-01

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

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

PubMed Central

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

2015-01-01

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

Recognition Using Hybrid Classifiers.

PubMed

Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

2016-04-01

A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply.

Dimensions of design space: a decision-theoretic approach to optimal research design.

PubMed

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Spatial sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

NASA Astrophysics Data System (ADS)

Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

2014-10-01

The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

2017-12-01

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

Problems with sampling desert tortoises: A simulation analysis based on field data

USGS Publications Warehouse

Freilich, J.E.; Camp, R.J.; Duda, J.J.; Karl, A.E.

2005-01-01

The desert tortoise (Gopherus agassizii) was listed as a U.S. threatened species in 1990 based largely on population declines inferred from mark-recapture surveys of 2.59-km2 (1-mi2) plots. Since then, several census methods have been proposed and tested, but all methods still pose logistical or statistical difficulties. We conducted computer simulations using actual tortoise location data from 2 1-mi2 plot surveys in southern California, USA, to identify strengths and weaknesses of current sampling strategies. We considered tortoise population estimates based on these plots as "truth" and then tested various sampling methods based on sampling smaller plots or transect lines passing through the mile squares. Data were analyzed using Schnabel's mark-recapture estimate and program CAPTURE. Experimental subsampling with replacement of the 1-mi2 data using 1-km2 and 0.25-km2 plot boundaries produced data sets of smaller plot sizes, which we compared to estimates from the 1-mi 2 plots. We also tested distance sampling by saturating a 1-mi 2 site with computer simulated transect lines, once again evaluating bias in density estimates. Subsampling estimates from 1-km2 plots did not differ significantly from the estimates derived at 1-mi2. The 0.25-km2 subsamples significantly overestimated population sizes, chiefly because too few recaptures were made. Distance sampling simulations were biased 80% of the time and had high coefficient of variation to density ratios. Furthermore, a prospective power analysis suggested limited ability to detect population declines as high as 50%. We concluded that poor performance and bias of both sampling procedures was driven by insufficient sample size, suggesting that all efforts must be directed to increasing numbers found in order to produce reliable results. Our results suggest that present methods may not be capable of accurately estimating desert tortoise populations.

An unbiased adaptive sampling algorithm for the exploration of RNA mutational landscapes under evolutionary pressure.

PubMed

Waldispühl, Jérôme; Ponty, Yann

2011-11-01

The analysis of the relationship between sequences and structures (i.e., how mutations affect structures and reciprocally how structures influence mutations) is essential to decipher the principles driving molecular evolution, to infer the origins of genetic diseases, and to develop bioengineering applications such as the design of artificial molecules. Because their structures can be predicted from the sequence data only, RNA molecules provide a good framework to study this sequence-structure relationship. We recently introduced a suite of algorithms called RNAmutants which allows a complete exploration of RNA sequence-structure maps in polynomial time and space. Formally, RNAmutants takes an input sequence (or seed) to compute the Boltzmann-weighted ensembles of mutants with exactly k mutations, and sample mutations from these ensembles. However, this approach suffers from major limitations. Indeed, since the Boltzmann probabilities of the mutations depend of the free energy of the structures, RNAmutants has difficulties to sample mutant sequences with low G+C-contents. In this article, we introduce an unbiased adaptive sampling algorithm that enables RNAmutants to sample regions of the mutational landscape poorly covered by classical algorithms. We applied these methods to sample mutations with low G+C-contents. These adaptive sampling techniques can be easily adapted to explore other regions of the sequence and structural landscapes which are difficult to sample. Importantly, these algorithms come at a minimal computational cost. We demonstrate the insights offered by these techniques on studies of complete RNA sequence structures maps of sizes up to 40 nucleotides. Our results indicate that the G+C-content has a strong influence on the size and shape of the evolutionary accessible sequence and structural spaces. In particular, we show that low G+C-contents favor the apparition of internal loops and thus possibly the synthesis of tertiary structure motifs. On the other hand, high G+C-contents significantly reduce the size of the evolutionary accessible mutational landscapes.

Snow particles extracted from X-ray computed microtomography imagery and their single-scattering properties

NASA Astrophysics Data System (ADS)

Ishimoto, Hiroshi; Adachi, Satoru; Yamaguchi, Satoru; Tanikawa, Tomonori; Aoki, Teruo; Masuda, Kazuhiko

2018-04-01

Sizes and shapes of snow particles were determined from X-ray computed microtomography (micro-CT) images, and their single-scattering properties were calculated at visible and near-infrared wavelengths using a Geometrical Optics Method (GOM). We analyzed seven snow samples including fresh and aged artificial snow and natural snow obtained from field samples. Individual snow particles were numerically extracted, and the shape of each snow particle was defined by applying a rendering method. The size distribution and specific surface area distribution were estimated from the geometrical properties of the snow particles, and an effective particle radius was derived for each snow sample. The GOM calculations at wavelengths of 0.532 and 1.242 μm revealed that the realistic snow particles had similar scattering phase functions as those of previously modeled irregular shaped particles. Furthermore, distinct dendritic particles had a characteristic scattering phase function and asymmetry factor. The single-scattering properties of particles of effective radius reff were compared with the size-averaged single-scattering properties. We found that the particles of reff could be used as representative particles for calculating the average single-scattering properties of the snow. Furthermore, the single-scattering properties of the micro-CT particles were compared to those of particle shape models using our current snow retrieval algorithm. For the single-scattering phase function, the results of the micro-CT particles were consistent with those of a conceptual two-shape model. However, the particle size dependence differed for the single-scattering albedo and asymmetry factor.

Uncertainty in sample estimates and the implicit loss function for soil information.

NASA Astrophysics Data System (ADS)

Lark, Murray

2015-04-01

One significant challenge in the communication of uncertain information is how to enable the sponsors of sampling exercises to make a rational choice of sample size. One way to do this is to compute the value of additional information given the loss function for errors. The loss function expresses the costs that result from decisions made using erroneous information. In certain circumstances, such as remediation of contaminated land prior to development, loss functions can be computed and used to guide rational decision making on the amount of resource to spend on sampling to collect soil information. In many circumstances the loss function cannot be obtained prior to decision making. This may be the case when multiple decisions may be based on the soil information and the costs of errors are hard to predict. The implicit loss function is proposed as a tool to aid decision making in these circumstances. Conditional on a logistical model which expresses costs of soil sampling as a function of effort, and statistical information from which the error of estimates can be modelled as a function of effort, the implicit loss function is the loss function which makes a particular decision on effort rational. In this presentation the loss function is defined and computed for a number of arbitrary decisions on sampling effort for a hypothetical soil monitoring problem. This is based on a logistical model of sampling cost parameterized from a recent geochemical survey of soil in Donegal, Ireland and on statistical parameters estimated with the aid of a process model for change in soil organic carbon. It is shown how the implicit loss function might provide a basis for reflection on a particular choice of sample size by comparing it with the values attributed to soil properties and functions. Scope for further research to develop and apply the implicit loss function to help decision making by policy makers and regulators is then discussed.

User's manual for semi-circular compact range reflector code

NASA Technical Reports Server (NTRS)

Gupta, Inder J.; Burnside, Walter D.

1986-01-01

A computer code was developed to analyze a semi-circular paraboloidal reflector antenna with a rolled edge at the top and a skirt at the bottom. The code can be used to compute the total near field of the antenna or its individual components at a given distance from the center of the paraboloid. Thus, it is very effective in computing the size of the sweet spot for RCS or antenna measurement. The operation of the code is described. Various input and output statements are explained. Some results obtained using the computer code are presented to illustrate the code's capability as well as being samples of input/output sets.

Laboratory theory and methods for sediment analysis

USGS Publications Warehouse

Guy, Harold P.

1969-01-01

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

Quantal Response: Estimation and Inference

DTIC Science & Technology

2014-09-01

considered. The CI-based test is just another way of looking at the Wald test. A small-sample simulation illustrates aberrant behavior of the Wald/CI...asymptotic power computation (Eq. 36) exhibits this behavior but not to such an extent as the simulated small-sample power. Sample size is n = 11 and...as |m1−m0| increases, but the power of the Wald test actually decreases for large |m1−m0| and eventually π → α . This type of behavior was reported as

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.

PubMed

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A; Robert, Christian P; Marin, Jean-Michel; Balding, David J; Guillemaud, Thomas; Estoup, Arnaud

2008-12-01

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.

Micro-computed tomography characterization of tissue engineering scaffolds: effects of pixel size and rotation step.

PubMed

Cengiz, Ibrahim Fatih; Oliveira, Joaquim Miguel; Reis, Rui L

2017-08-01

Quantitative assessment of micro-structure of materials is of key importance in many fields including tissue engineering, biology, and dentistry. Micro-computed tomography (µ-CT) is an intensively used non-destructive technique. However, the acquisition parameters such as pixel size and rotation step may have significant effects on the obtained results. In this study, a set of tissue engineering scaffolds including examples of natural and synthetic polymers, and ceramics were analyzed. We comprehensively compared the quantitative results of µ-CT characterization using 15 acquisition scenarios that differ in the combination of the pixel size and rotation step. The results showed that the acquisition parameters could statistically significantly affect the quantified mean porosity, mean pore size, and mean wall thickness of the scaffolds. The effects are also practically important since the differences can be as high as 24% regarding the mean porosity in average, and 19.5 h and 166 GB regarding the characterization time and data storage per sample with a relatively small volume. This study showed in a quantitative manner the effects of such a wide range of acquisition scenarios on the final data, as well as the characterization time and data storage per sample. Herein, a clear picture of the effects of the pixel size and rotation step on the results is provided which can notably be useful to refine the practice of µ-CT characterization of scaffolds and economize the related resources.

Resource Efficient Hardware Architecture for Fast Computation of Running Max/Min Filters

PubMed Central

Torres-Huitzil, Cesar

2013-01-01

Running max/min filters on rectangular kernels are widely used in many digital signal and image processing applications. Filtering with a k × k kernel requires of k 2 − 1 comparisons per sample for a direct implementation; thus, performance scales expensively with the kernel size k. Faster computations can be achieved by kernel decomposition and using constant time one-dimensional algorithms on custom hardware. This paper presents a hardware architecture for real-time computation of running max/min filters based on the van Herk/Gil-Werman (HGW) algorithm. The proposed architecture design uses less computation and memory resources than previously reported architectures when targeted to Field Programmable Gate Array (FPGA) devices. Implementation results show that the architecture is able to compute max/min filters, on 1024 × 1024 images with up to 255 × 255 kernels, in around 8.4 milliseconds, 120 frames per second, at a clock frequency of 250 MHz. The implementation is highly scalable for the kernel size with good performance/area tradeoff suitable for embedded applications. The applicability of the architecture is shown for local adaptive image thresholding. PMID:24288456

Evaluation of a Fluorochlorozirconate Glass-Ceramic Storage Phosphor Plate for Gamma-Ray Computed Radiography

DOE PAGES

Leonard, Russell L.; Gray, Sharon K.; Alvarez, Carlos J.; ...

2015-05-21

In this paper, a fluorochlorozirconate (FCZ) glass-ceramic containing orthorhombic barium chloride crystals doped with divalent europium was evaluated for use as a storage phosphor in gamma-ray imaging. X-ray diffraction and phosphorimetry of the glass-ceramic sample showed the presence of a significant amount of orthorhombic barium chloride crystals in the glass matrix. Transmission electron microscopy and scanning electron microscopy were used to identify crystal size, structure, and morphology. The size of the orthorhombic barium chloride crystals in the FCZ glass matrix was very large, ~0.5–0.7 μm, which can limit image resolution. The FCZ glass-ceramic sample was exposed to 1 MeV gammamore » rays to determine its photostimulated emission characteristics at high energies, which were found to be suitable for imaging applications. Test images were made at 2 MeV energies using gap and step wedge phantoms. Gaps as small as 101.6 μm in a 440 stainless steel phantom were imaged using the sample imaging plate. Analysis of an image created using a depleted uranium step wedge phantom showed that emission is proportional to incident energy at the sample and the estimated absorbed dose. Finally, the results showed that the sample imaging plate has potential for gamma-ray-computed radiography and dosimetry applications.« less

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

PubMed

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

2005-04-15

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

Studying the Binomial Distribution Using LabVIEW

ERIC Educational Resources Information Center

George, Danielle J.; Hammer, Nathan I.

2015-01-01

This undergraduate physical chemistry laboratory exercise introduces students to the study of probability distributions both experimentally and using computer simulations. Students perform the classic coin toss experiment individually and then pool all of their data together to study the effect of experimental sample size on the binomial…

EVALUATION OF COMPUTER-CONTROLLED SCANNING ELECTRON MICROSCOPY APPLIED TO AN AMBIENT URBAN AEROSOL SAMPLE

EPA Science Inventory

Recent interest in monitoring and speciation of particulate matter has led to increased application of scanning electron microscopy (SEM) coupled with energy-dispersive x-ray analysis (EDX) to individual particle analysis. SEM/EDX provides information on the size, shape, co...

Sample entropy applied to the analysis of synthetic time series and tachograms

NASA Astrophysics Data System (ADS)

Muñoz-Diosdado, A.; Gálvez-Coyt, G. G.; Solís-Montufar, E.

2017-01-01

Entropy is a method of non-linear analysis that allows an estimate of the irregularity of a system, however, there are different types of computational entropy that were considered and tested in order to obtain one that would give an index of signals complexity taking into account the data number of the analysed time series, the computational resources demanded by the method, and the accuracy of the calculation. An algorithm for the generation of fractal time-series with a certain value of β was used for the characterization of the different entropy algorithms. We obtained a significant variation for most of the algorithms in terms of the series size, which could result counterproductive for the study of real signals of different lengths. The chosen method was sample entropy, which shows great independence of the series size. With this method, time series of heart interbeat intervals or tachograms of healthy subjects and patients with congestive heart failure were analysed. The calculation of sample entropy was carried out for 24-hour tachograms and time subseries of 6-hours for sleepiness and wakefulness. The comparison between the two populations shows a significant difference that is accentuated when the patient is sleeping.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed Central

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

2017-01-01

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

Lot quality assurance sampling (LQAS) for monitoring a leprosy elimination program.

PubMed

Gupte, M D; Narasimhamurthy, B

1999-06-01

In a statistical sense, prevalences of leprosy in different geographical areas can be called very low or rare. Conventional survey methods to monitor leprosy control programs, therefore, need large sample sizes, are expensive, and are time-consuming. Further, with the lowering of prevalence to the near-desired target level, 1 case per 10,000 population at national or subnational levels, the program administrator's concern will be shifted to smaller areas, e.g., districts, for assessment and, if needed, for necessary interventions. In this paper, Lot Quality Assurance Sampling (LQAS), a quality control tool in industry, is proposed to identify districts/regions having a prevalence of leprosy at or above a certain target level, e.g., 1 in 10,000. This technique can also be considered for identifying districts/regions at or below the target level of 1 per 10,000, i.e., areas where the elimination level is attained. For simulating various situations and strategies, a hypothetical computerized population of 10 million persons was created. This population mimics the actual population in terms of the empirical information on rural/urban distributions and the distribution of households by size for the state of Tamil Nadu, India. Various levels with respect to leprosy prevalence are created using this population. The distribution of the number of cases in the population was expected to follow the Poisson process, and this was also confirmed by examination. Sample sizes and corresponding critical values were computed using Poisson approximation. Initially, villages/towns are selected from the population and from each selected village/town households are selected using systematic sampling. Households instead of individuals are used as sampling units. This sampling procedure was simulated 1000 times in the computer from the base population. The results in four different prevalence situations meet the required limits of Type I error of 5% and 90% Power. It is concluded that after validation under field conditions, this method can be considered for a rapid assessment of the leprosy situation.

Experimental design, power and sample size for animal reproduction experiments.

PubMed

Chapman, Phillip L; Seidel, George E

2008-01-01

The present paper concerns statistical issues in the design of animal reproduction experiments, with emphasis on the problems of sample size determination and power calculations. We include examples and non-technical discussions aimed at helping researchers avoid serious errors that may invalidate or seriously impair the validity of conclusions from experiments. Screen shots from interactive power calculation programs and basic SAS power calculation programs are presented to aid in understanding statistical power and computing power in some common experimental situations. Practical issues that are common to most statistical design problems are briefly discussed. These include one-sided hypothesis tests, power level criteria, equality of within-group variances, transformations of response variables to achieve variance equality, optimal specification of treatment group sizes, 'post hoc' power analysis and arguments for the increased use of confidence intervals in place of hypothesis tests.

An image-based skeletal model for the ICRP reference adult male—specific absorbed fractions for neutron-generated recoil protons

NASA Astrophysics Data System (ADS)

Jokisch, D. W.; Rajon, D. A.; Bahadori, A. A.; Bolch, W. E.

2011-11-01

Recoiling hydrogen nuclei are a principle mechanism for energy deposition from incident neutrons. For neutrons incident on the human skeleton, the small sizes of two contrasting media (trabecular bone and marrow) present unique problems due to a lack of charged-particle (protons) equilibrium. Specific absorbed fractions have been computed for protons originating in the human skeletal tissues for use in computing neutron dose response functions. The proton specific absorbed fractions were computed using a pathlength-based range-energy calculation in trabecular skeletal samples of a 40 year old male cadaver.

Computer-aided boundary delineation of agricultural lands

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1989-01-01

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures.

PubMed

Neylon, J; Sheng, K; Yu, V; Chen, Q; Low, D A; Kupelian, P; Santhanam, A

2014-10-01

Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy into a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures

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

Neylon, J., E-mail: jneylon@mednet.ucla.edu; Sheng, K.; Yu, V.

Purpose: Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. Methods: The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy intomore » a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. Results: The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. Conclusions: The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.« less

A post hoc evaluation of a sample size re-estimation in the Secondary Prevention of Small Subcortical Strokes study.

PubMed

McClure, Leslie A; Szychowski, Jeff M; Benavente, Oscar; Hart, Robert G; Coffey, Christopher S

2016-10-01

The use of adaptive designs has been increasing in randomized clinical trials. Sample size re-estimation is a type of adaptation in which nuisance parameters are estimated at an interim point in the trial and the sample size re-computed based on these estimates. The Secondary Prevention of Small Subcortical Strokes study was a randomized clinical trial assessing the impact of single- versus dual-antiplatelet therapy and control of systolic blood pressure to a higher (130-149 mmHg) versus lower (<130 mmHg) target on recurrent stroke risk in a two-by-two factorial design. A sample size re-estimation was performed during the Secondary Prevention of Small Subcortical Strokes study resulting in an increase from the planned sample size of 2500-3020, and we sought to determine the impact of the sample size re-estimation on the study results. We assessed the results of the primary efficacy and safety analyses with the full 3020 patients and compared them to the results that would have been observed had randomization ended with 2500 patients. The primary efficacy outcome considered was recurrent stroke, and the primary safety outcomes were major bleeds and death. We computed incidence rates for the efficacy and safety outcomes and used Cox proportional hazards models to examine the hazard ratios for each of the two treatment interventions (i.e. the antiplatelet and blood pressure interventions). In the antiplatelet intervention, the hazard ratio was not materially modified by increasing the sample size, nor did the conclusions regarding the efficacy of mono versus dual-therapy change: there was no difference in the effect of dual- versus monotherapy on the risk of recurrent stroke hazard ratios (n = 3020 HR (95% confidence interval): 0.92 (0.72, 1.2), p = 0.48; n = 2500 HR (95% confidence interval): 1.0 (0.78, 1.3), p = 0.85). With respect to the blood pressure intervention, increasing the sample size resulted in less certainty in the results, as the hazard ratio for higher versus lower systolic blood pressure target approached, but did not achieve, statistical significance with the larger sample (n = 3020 HR (95% confidence interval): 0.81 (0.63, 1.0), p = 0.089; n = 2500 HR (95% confidence interval): 0.89 (0.68, 1.17), p = 0.40). The results from the safety analyses were similar to 3020 and 2500 patients for both study interventions. Other trial-related factors, such as contracts, finances, and study management, were impacted as well. Adaptive designs can have benefits in randomized clinical trials, but do not always result in significant findings. The impact of adaptive designs should be measured in terms of both trial results, as well as practical issues related to trial management. More post hoc analyses of study adaptations will lead to better understanding of the balance between the benefits and the costs. © The Author(s) 2016.

A planar near-field scanning technique for bistatic radar cross section measurements

NASA Technical Reports Server (NTRS)

Tuhela-Reuning, S.; Walton, E. K.

1990-01-01

A progress report on the development of a bistatic radar cross section (RCS) measurement range is presented. A technique using one parabolic reflector and a planar scanning probe antenna is analyzed. The field pattern in the test zone is computed using a spatial array of signal sources. It achieved an illumination pattern with 1 dB amplitude and 15 degree phase ripple over the target zone. The required scan plane size is found to be proportional to the size of the desired test target. Scan plane probe sample spacing can be increased beyond the Nyquist lambda/2 limit permitting constant probe sample spacing over a range of frequencies.

Impact of geometrical properties on permeability and fluid phase distribution in porous media

NASA Astrophysics Data System (ADS)

Lehmann, P.; Berchtold, M.; Ahrenholz, B.; Tölke, J.; Kaestner, A.; Krafczyk, M.; Flühler, H.; Künsch, H. R.

2008-09-01

To predict fluid phase distribution in porous media, the effect of geometric properties on flow processes must be understood. In this study, we analyze the effect of volume, surface, curvature and connectivity (the four Minkowski functionals) on the hydraulic conductivity and the water retention curve. For that purpose, we generated 12 artificial structures with 800 3 voxels (the units of a 3D image) and compared them with a scanned sand sample of the same size. The structures were generated with a Boolean model based on a random distribution of overlapping ellipsoids whose size and shape were chosen to fulfill the criteria of the measured functionals. The pore structure of sand material was mapped with X-rays from synchrotrons. To analyze the effect of geometry on water flow and fluid distribution we carried out three types of analysis: Firstly, we computed geometrical properties like chord length, distance from the solids, pore size distribution and the Minkowski functionals as a function of pore size. Secondly, the fluid phase distribution as a function of the applied pressure was calculated with a morphological pore network model. Thirdly, the permeability was determined using a state-of-the-art lattice-Boltzmann method. For the simulated structure with the true Minkowski functionals the pores were larger and the computed air-entry value of the artificial medium was reduced to 85% of the value obtained from the scanned sample. The computed permeability for the geometry with the four fitted Minkowski functionals was equal to the permeability of the scanned image. The permeability was much more sensitive to the volume and surface than to curvature and connectivity of the medium. We conclude that the Minkowski functionals are not sufficient to characterize the geometrical properties of a porous structure that are relevant for the distribution of two fluid phases. Depending on the procedure to generate artificial structures with predefined Minkowski functionals, structures differing in pore size distribution can be obtained.

Development and analysis of a finite element model to simulate pulmonary emphysema in CT imaging.

PubMed

Diciotti, Stefano; Nobis, Alessandro; Ciulli, Stefano; Landini, Nicholas; Mascalchi, Mario; Sverzellati, Nicola; Innocenti, Bernardo

2015-01-01

In CT imaging, pulmonary emphysema appears as lung regions with Low-Attenuation Areas (LAA). In this study we propose a finite element (FE) model of lung parenchyma, based on a 2-D grid of beam elements, which simulates pulmonary emphysema related to smoking in CT imaging. Simulated LAA images were generated through space sampling of the model output. We employed two measurements of emphysema extent: Relative Area (RA) and the exponent D of the cumulative distribution function of LAA clusters size. The model has been used to compare RA and D computed on the simulated LAA images with those computed on the models output. Different mesh element sizes and various model parameters, simulating different physiological/pathological conditions, have been considered and analyzed. A proper mesh element size has been determined as the best trade-off between reliable results and reasonable computational cost. Both RA and D computed on simulated LAA images were underestimated with respect to those calculated on the models output. Such underestimations were larger for RA (≈ -44 ÷ -26%) as compared to those for D (≈ -16 ÷ -2%). Our FE model could be useful to generate standard test images and to design realistic physical phantoms of LAA images for the assessment of the accuracy of descriptors for quantifying emphysema in CT imaging.

A comparison of fitness-case sampling methods for genetic programming

NASA Astrophysics Data System (ADS)

Martínez, Yuliana; Naredo, Enrique; Trujillo, Leonardo; Legrand, Pierrick; López, Uriel

2017-11-01

Genetic programming (GP) is an evolutionary computation paradigm for automatic program induction. GP has produced impressive results but it still needs to overcome some practical limitations, particularly its high computational cost, overfitting and excessive code growth. Recently, many researchers have proposed fitness-case sampling methods to overcome some of these problems, with mixed results in several limited tests. This paper presents an extensive comparative study of four fitness-case sampling methods, namely: Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and Keep-Worst Interleaved Sampling. The algorithms are compared on 11 symbolic regression problems and 11 supervised classification problems, using 10 synthetic benchmarks and 12 real-world data-sets. They are evaluated based on test performance, overfitting and average program size, comparing them with a standard GP search. Comparisons are carried out using non-parametric multigroup tests and post hoc pairwise statistical tests. The experimental results suggest that fitness-case sampling methods are particularly useful for difficult real-world symbolic regression problems, improving performance, reducing overfitting and limiting code growth. On the other hand, it seems that fitness-case sampling cannot improve upon GP performance when considering supervised binary classification.

Evidence for a Global Sampling Process in Extraction of Summary Statistics of Item Sizes in a Set.

PubMed

Tokita, Midori; Ueda, Sachiyo; Ishiguchi, Akira

2016-01-01

Several studies have shown that our visual system may construct a "summary statistical representation" over groups of visual objects. Although there is a general understanding that human observers can accurately represent sets of a variety of features, many questions on how summary statistics, such as an average, are computed remain unanswered. This study investigated sampling properties of visual information used by human observers to extract two types of summary statistics of item sets, average and variance. We presented three models of ideal observers to extract the summary statistics: a global sampling model without sampling noise, global sampling model with sampling noise, and limited sampling model. We compared the performance of an ideal observer of each model with that of human observers using statistical efficiency analysis. Results suggest that summary statistics of items in a set may be computed without representing individual items, which makes it possible to discard the limited sampling account. Moreover, the extraction of summary statistics may not necessarily require the representation of individual objects with focused attention when the sets of items are larger than 4.

Laval University and Lakehead University Experiments at TREC 2015 Contextual Suggestion Track

DTIC Science & Technology

2015-11-20

Department of Computer Science and Software Engineering, Laval University 2 Department of Software Engineering, Lakehead University Abstract—In this...Linear Regression and Lambda Mart perform poorly in this case, be- cause the size of the training data per user is small (less than 50 samples). On the

Intraclass Correlation Values for Planning Group-Randomized Trials in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.

2007-01-01

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate…

INVESTIGATION OF PRIMARY FINE PARTICULATE MATTER FROM COAL COMBUSTION BY COMPUTER-CONTROLLED SCANNING ELECTRON MICROSCOPY

EPA Science Inventory

The particle size distributions, morphologies, and chemical composition distributions of 14 coal fly ash (CFA) samples produced by the combustion of four western U.S. coals (two subbituminous, one lignite, and one bituminous) and three eastern U.S. coals (all bituminous) have bee...

Computer modelling of grain microstructure in three dimensions

NASA Astrophysics Data System (ADS)

Narayan, K. Lakshmi

We present a program that generates the two-dimensional micrographs of a three dimensional grain microstructure. The code utilizes a novel scanning, pixel mapping technique to secure statistical distributions of surface areas, grain sizes, aspect ratios, perimeters, number of nearest neighbors and volumes of the randomly nucleated particles. The program can be used for comparing the existing theories of grain growth, and interpretation of two-dimensional microstructure of three-dimensional samples. Special features have been included to minimize the computation time and resource requirements.

A dataset describing brooding in three species of South African brittle stars, comprising seven high-resolution, micro X-ray computed tomography scans.

PubMed

Landschoff, Jannes; Du Plessis, Anton; Griffiths, Charles L

2015-01-01

Brooding brittle stars have a special mode of reproduction whereby they retain their eggs and juveniles inside respiratory body sacs called bursae. In the past, studying this phenomenon required disturbance of the sample by dissecting the adult. This caused irreversible damage and made the sample unsuitable for future studies. Micro X-ray computed tomography (μCT) is a promising technique, not only to visualise juveniles inside the bursae, but also to keep the sample intact and make the dataset of the scan available for future reference. Seven μCT scans of five freshly fixed (70 % ethanol) individuals, representing three differently sized brittle star species, provided adequate image quality to determine the numbers, sizes and postures of internally brooded young, as well as anatomy and morphology of adults. No staining agents were necessary to achieve high-resolution, high-contrast images, which permitted visualisations of both calcified and soft tissue. The raw data (projection and reconstruction images) are publicly available for download from GigaDB. Brittle stars of all sizes are suitable candidates for μCT imaging. This explicitly adds a new technique to the suite of tools available for studying the development of internally brooded young. The purpose of applying the technique was to visualise juveniles inside the adult, but because of the universally good quality of the dataset, the images can also be used for anatomical or comparative morphology-related studies of adult structures.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE PAGES

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; ...

2017-12-27

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

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

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection.

PubMed

Cruz-Roa, Angel; Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie; Tomaszewski, John; Madabhushi, Anant; González, Fabio

2018-01-01

Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500 × 500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (∼6 million of samples in 24 hours) with far fewer samples (∼2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%.

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection

PubMed Central

Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie; Tomaszewski, John; Madabhushi, Anant; González, Fabio

2018-01-01

Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500 × 500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (∼6 million of samples in 24 hours) with far fewer samples (∼2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%. PMID:29795581

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

PubMed

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

2017-10-01

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

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

PubMed

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

Light scattering by planetary-regolith analog samples: computational results

NASA Astrophysics Data System (ADS)

Väisänen, Timo; Markkanen, Johannes; Hadamcik, Edith; Levasseur-Regourd, Anny-Chantal; Lasue, Jeremie; Blum, Jürgen; Penttilä, Antti; Muinonen, Karri

2017-04-01

We compute light scattering by a planetary-regolith analog surface. The corresponding experimental work is from Hadamcik et al. [1] with the PROGRA2-surf [2] device measuring the polarization of dust particles. The analog samples are low density (volume fraction 0.15 ± 0.03) agglomerates produced by random ballistic deposition of almost equisized silica spheres (refractive index n=1.5 and diameter 1.45 ± 0.06 µm). Computations are carried out with the recently developed codes entitled Radiative Transfer with Reciprocal Transactions (R2T2) and Radiative Transfer Coherent Backscattering with incoherent interactions (RT-CB-ic). Both codes incorporate the so-called incoherent treatment which enhances the applicability of the radiative transfer as shown by Muinonen et al. [3]. As a preliminary result, we have computed scattering from a large spherical medium with the RT-CB-ic using equal-sized particles with diameters of 1.45 microns. The preliminary results have shown that the qualitative characteristics are similar for the computed and measured intensity and polarization curves but that there are still deviations between the characteristics. We plan to remove the deviations by incorporating a size distribution of particles (1.45 ± 0.02 microns) and detailed information about the volume density profile within the analog surface. Acknowledgments: We acknowledge the ERC Advanced Grant no. 320773 entitled Scattering and Absorption of Electromagnetic Waves in Particulate Media (SAEMPL). Computational resources were provided by CSC - IT Centre for Science Ltd, Finland. References: [1] Hadamcik E. et al. (2007), JQSRT, 106, 74-89 [2] Levasseur-Regourd A.C. et al. (2015), Polarimetry of stars and planetary systems, CUP, 61-80 [3] Muinonen K. et al. (2016), extended abstract for EMTS.

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

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

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

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

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

PubMed

Hedges, Larry V; Olkin, Ingram

2016-03-01

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

Six dimensional X-ray Tensor Tomography with a compact laboratory setup

NASA Astrophysics Data System (ADS)

Sharma, Y.; Wieczorek, M.; Schaff, F.; Seyyedi, S.; Prade, F.; Pfeiffer, F.; Lasser, T.

2016-09-01

Attenuation based X-ray micro computed tomography (XCT) provides three-dimensional images with micrometer resolution. However, there is a trade-off between the smallest size of the structures that can be resolved and the measurable sample size. In this letter, we present an imaging method using a compact laboratory setup that reveals information about micrometer-sized structures within samples that are several orders of magnitudes larger. We combine the anisotropic dark-field signal obtained in a grating interferometer and advanced tomographic reconstruction methods to reconstruct a six dimensional scattering tensor at every spatial location in three dimensions. The scattering tensor, thus obtained, encodes information about the orientation of micron-sized structures such as fibres in composite materials or dentinal tubules in human teeth. The sparse acquisition schemes presented in this letter enable the measurement of the full scattering tensor at every spatial location and can be easily incorporated in a practical, commercially feasible laboratory setup using conventional X-ray tubes, thus allowing for widespread industrial applications.

Body image and body type preferences in St. Kitts, Caribbean: a cross- cultural comparison with U.S. samples regarding attitudes towards muscularity, body fat, and breast size.

PubMed

Gray, Peter B; Frederick, David A

2012-09-06

We investigated body image in St. Kitts, a Caribbean island where tourism, international media, and relatively high levels of body fat are common. Participants were men and women recruited from St. Kitts (n = 39) and, for comparison, U.S. samples from universities (n = 618) and the Internet (n = 438). Participants were shown computer generated images varying in apparent body fat level and muscularity or breast size and they indicated their body type preferences and attitudes. Overall, there were only modest differences in body type preferences between St. Kitts and the Internet sample, with the St. Kitts participants being somewhat more likely to value heavier women. Notably, however, men and women from St. Kitts were more likely to idealize smaller breasts than participants in the U.S. samples. Attitudes regarding muscularity were generally similar across samples. This study provides one of the few investigations of body preferences in the Caribbean.

Computational tools for exact conditional logistic regression.

PubMed

Corcoran, C; Mehta, C; Patel, N; Senchaudhuri, P

Logistic regression analyses are often challenged by the inability of unconditional likelihood-based approximations to yield consistent, valid estimates and p-values for model parameters. This can be due to sparseness or separability in the data. Conditional logistic regression, though useful in such situations, can also be computationally unfeasible when the sample size or number of explanatory covariates is large. We review recent developments that allow efficient approximate conditional inference, including Monte Carlo sampling and saddlepoint approximations. We demonstrate through real examples that these methods enable the analysis of significantly larger and more complex data sets. We find in this investigation that for these moderately large data sets Monte Carlo seems a better alternative, as it provides unbiased estimates of the exact results and can be executed in less CPU time than can the single saddlepoint approximation. Moreover, the double saddlepoint approximation, while computationally the easiest to obtain, offers little practical advantage. It produces unreliable results and cannot be computed when a maximum likelihood solution does not exist. Copyright 2001 John Wiley & Sons, Ltd.

The electrodynamic and hydrodynamic phenomena in magnetically-levitated molten droplets. I - Steady state behavior

NASA Technical Reports Server (NTRS)

Zong, Jin-Ho; Li, Benqiang; Szekely, Julian

1992-01-01

A mathematical formulation is given and computed results are presented describing the behavior of electromagnetically-levitated metal droplets under the conditions of microgravity. In the formulation the electromagnetic force field is calculated using a modification of the volume integral method and these results are then combined with the FIDAP code to calculate the steady state melt velocities. The specific computational results are presented for the conditions corresponding to the planned IML-2 Space Shuttle experiment, using the TEMPUS device, which has separate 'heating' and 'positioning' coils. While the computed results are necessarily specific to the input conditions, some general conclusions may be drawn from this work. These include the fact that for the planned TEMPUS experiments to positioning coils will produce only a weak melt circulation, while the heating coils are like to produce a mildly turbulent recirculating flow pattern within the samples. The computed results also allow us to assess the effect of sample size, material properties and the applied current on these phenomena.

Computer re-sampling for demographically representative user populations in anthropometry: a case of doorway and clear floor space widths.

PubMed

Paquet, Victor; Joseph, Caroline; D'Souza, Clive

2012-01-01

Anthropometric studies typically require a large number of individuals that are selected in a manner so that demographic characteristics that impact body size and function are proportionally representative of a user population. This sampling approach does not allow for an efficient characterization of the distribution of body sizes and functions of sub-groups within a population and the demographic characteristics of user populations can often change with time, limiting the application of the anthropometric data in design. The objective of this study is to demonstrate how demographically representative user populations can be developed from samples that are not proportionally representative in order to improve the application of anthropometric data in design. An engineering anthropometry problem of door width and clear floor space width is used to illustrate the value of the approach.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

PubMed Central

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A.; Robert, Christian P.; Marin, Jean-Michel; Balding, David J.; Guillemaud, Thomas; Estoup, Arnaud

2008-01-01

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc PMID:18842597

Online submicron particle sizing by dynamic light scattering using autodilution

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Accuracy evaluation of an X-ray microtomography system.

PubMed

Fernandes, Jaquiel S; Appoloni, Carlos R; Fernandes, Celso P

2016-06-01

Microstructural parameter evaluation of reservoir rocks is of great importance to petroleum production companies. In this connection, X-ray computed microtomography (μ-CT) has proven to be a quite useful method for the assessment of rocks, as it provides important microstructural parameters, such as porosity, permeability, pore size distribution and porous phase of the sample. X-ray computed microtomography is a non-destructive technique that enables the reuse of samples already measured and also yields 2-D cross-sectional images of the sample as well as volume rendering. This technique offers an additional advantage, as it does not require sample preparation, of reducing the measurement time, which is approximately one to three hours, depending on the spatial resolution used. Although this technique is extensively used, accuracy verification of measurements is hard to obtain because the existing calibrated samples (phantoms) have large volumes and are assessed in medical CT scanners with millimeter spatial resolution. Accordingly, this study aims to determine the accuracy of an X-ray computed microtomography system using a Skyscan 1172 X-ray microtomograph. To accomplish this investigation, it was used a nylon thread set with known appropriate diameter inserted into a glass tube. The results for porosity size and phase distribution by X-ray microtomography were very close to the geometrically calculated values. The geometrically calculated porosity and the porosity determined by the methodology using the μ-CT was 33.4±3.4% and 31.0±0.3%, respectively. The outcome of this investigation was excellent. It was also observed a small variability in the results along all 401 sections of the analyzed image. Minimum and maximum porosity values between the cross sections were 30.9% and 31.1%, respectively. A 3-D image representing the actual structure of the sample was also rendered from the 2-D images. Copyright © 2016 Elsevier Ltd. All rights reserved.

An estimate of field size distributions for selected sites in the major grain producing countries

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1977-01-01

The field size distributions for the major grain producing countries of the World were estimated. LANDSAT-1 and 2 images were evaluated for two areas each in the United States, People's Republic of China, and the USSR. One scene each was evaluated for France, Canada, and India. Grid sampling was done for representative sub-samples of each image, measuring the long and short axes of each field; area was then calculated. Each of the resulting data sets was computer analyzed for their frequency distributions. Nearly all frequency distributions were highly peaked and skewed (shifted) towards small values, approaching that of either a Poisson or log-normal distribution. The data were normalized by a log transformation, creating a Gaussian distribution which has moments readily interpretable and useful for estimating the total population of fields. Resultant predictors of the field size estimates are discussed.

Getting more from accuracy and response time data: methods for fitting the linear ballistic accumulator.

PubMed

Donkin, Chris; Averell, Lee; Brown, Scott; Heathcote, Andrew

2009-11-01

Cognitive models of the decision process provide greater insight into response time and accuracy than do standard ANOVA techniques. However, such models can be mathematically and computationally difficult to apply. We provide instructions and computer code for three methods for estimating the parameters of the linear ballistic accumulator (LBA), a new and computationally tractable model of decisions between two or more choices. These methods-a Microsoft Excel worksheet, scripts for the statistical program R, and code for implementation of the LBA into the Bayesian sampling software WinBUGS-vary in their flexibility and user accessibility. We also provide scripts in R that produce a graphical summary of the data and model predictions. In a simulation study, we explored the effect of sample size on parameter recovery for each method. The materials discussed in this article may be downloaded as a supplement from http://brm.psychonomic-journals.org/content/supplemental.

A Review of Enhanced Sampling Approaches for Accelerated Molecular Dynamics

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; van de Walle, Axel

Molecular dynamics (MD) simulations have become a tool of immense use and popularity for simulating a variety of systems. With the advent of massively parallel computer resources, one now routinely sees applications of MD to systems as large as hundreds of thousands to even several million atoms, which is almost the size of most nanomaterials. However, it is not yet possible to reach laboratory timescales of milliseconds and beyond with MD simulations. Due to the essentially sequential nature of time, parallel computers have been of limited use in solving this so-called timescale problem. Instead, over the years a large range of statistical mechanics based enhanced sampling approaches have been proposed for accelerating molecular dynamics, and accessing timescales that are well beyond the reach of the fastest computers. In this review we provide an overview of these approaches, including the underlying theory, typical applications, and publicly available software resources to implement them.

Computational fluid dynamics (CFD) studies of a miniaturized dissolution system.

PubMed

Frenning, G; Ahnfelt, E; Sjögren, E; Lennernäs, H

2017-04-15

Dissolution testing is an important tool that has applications ranging from fundamental studies of drug-release mechanisms to quality control of the final product. The rate of release of the drug from the delivery system is known to be affected by hydrodynamics. In this study we used computational fluid dynamics to simulate and investigate the hydrodynamics in a novel miniaturized dissolution method for parenteral formulations. The dissolution method is based on a rotating disc system and uses a rotating sample reservoir which is separated from the remaining dissolution medium by a nylon screen. Sample reservoirs of two sizes were investigated (SR6 and SR8) and the hydrodynamic studies were performed at rotation rates of 100, 200 and 400rpm. The overall fluid flow was similar for all investigated cases, with a lateral upward spiraling motion and central downward motion in the form of a vortex to and through the screen. The simulations indicated that the exchange of dissolution medium between the sample reservoir and the remaining release medium was rapid for typical screens, for which almost complete mixing would be expected to occur within less than one minute at 400rpm. The local hydrodynamic conditions in the sample reservoirs depended on their size; SR8 appeared to be relatively more affected than SR6 by the resistance to liquid flow resulting from the screen. Copyright © 2017 Elsevier B.V. All rights reserved.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

PubMed

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

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

PubMed

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

2017-09-01

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

Evaluation of a High-Resolution Benchtop Micro-CT Scanner for Application in Porous Media Research

NASA Astrophysics Data System (ADS)

Tuller, M.; Vaz, C. M.; Lasso, P. O.; Kulkarni, R.; Ferre, T. A.

2010-12-01

Recent advances in Micro Computed Tomography (MCT) provided the motivation to thoroughly evaluate and optimize scanning, image reconstruction/segmentation and pore-space analysis capabilities of a new generation benchtop MCT scanner and associated software package. To demonstrate applicability to soil research the project was focused on determination of porosities and pore size distributions of two Brazilian Oxisols from segmented MCT-data. Effects of metal filters and various acquisition parameters (e.g. total rotation, rotation step, and radiograph frame averaging) on image quality and acquisition time are evaluated. Impacts of sample size and scanning resolution on CT-derived porosities and pore-size distributions are illustrated.

On the validity of the Poisson assumption in sampling nanometer-sized aerosols

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

Damit, Brian E; Wu, Dr. Chang-Yu; Cheng, Mengdawn

2014-01-01

A Poisson process is traditionally believed to apply to the sampling of aerosols. For a constant aerosol concentration, it is assumed that a Poisson process describes the fluctuation in the measured concentration because aerosols are stochastically distributed in space. Recent studies, however, have shown that sampling of micrometer-sized aerosols has non-Poissonian behavior with positive correlations. The validity of the Poisson assumption for nanometer-sized aerosols has not been examined and thus was tested in this study. Its validity was tested for four particle sizes - 10 nm, 25 nm, 50 nm and 100 nm - by sampling from indoor air withmore » a DMA- CPC setup to obtain a time series of particle counts. Five metrics were calculated from the data: pair-correlation function (PCF), time-averaged PCF, coefficient of variation, probability of measuring a concentration at least 25% greater than average, and posterior distributions from Bayesian inference. To identify departures from Poissonian behavior, these metrics were also calculated for 1,000 computer-generated Poisson time series with the same mean as the experimental data. For nearly all comparisons, the experimental data fell within the range of 80% of the Poisson-simulation values. Essentially, the metrics for the experimental data were indistinguishable from a simulated Poisson process. The greater influence of Brownian motion for nanometer-sized aerosols may explain the Poissonian behavior observed for smaller aerosols. Although the Poisson assumption was found to be valid in this study, it must be carefully applied as the results here do not definitively prove applicability in all sampling situations.« less

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

NASA Astrophysics Data System (ADS)

Ozen, Murat; Guler, Murat

2014-02-01

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

Confidence bounds for normal and lognormal distribution coefficients of variation

Treesearch

Steve Verrill

2003-01-01

This paper compares the so-called exact approach for obtaining confidence intervals on normal distribution coefficients of variation to approximate methods. Approximate approaches were found to perform less well than the exact approach for large coefficients of variation and small sample sizes. Web-based computer programs are described for calculating confidence...

Some Exact Conditional Tests of Independence for R X C Cross-Classification Tables

ERIC Educational Resources Information Center

Agresti, Alan; Wackerly, Dennis

1977-01-01

Exact conditional tests of independence in cross-classification tables are formulated based on chi square and other statistics with stronger operational interpretations, such as some nominal and ordinal measures of association. Guidelines for table dimensions and sample sizes for which the tests are economically implemented on a computer are…

State of Washington Computer Use Survey.

ERIC Educational Resources Information Center

Beal, Jack L.; And Others

This report presents the results of a spring 1982 survey of a random sample of Washington public schools which separated findings according to school level (elementary, middle, junior high, or high school) and district size (either less than or greater than 2,000 enrollment). A brief review of previous studies and a description of the survey…

The Power of the Test for Treatment Effects in Three-Level Block Randomized Designs

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2008-01-01

Experiments that involve nested structures may assign treatment conditions either to subgroups (such as classrooms) or individuals within subgroups (such as students). The design of such experiments requires knowledge of the intraclass correlation structure to compute the sample sizes necessary to achieve adequate power to detect the treatment…

Using UAS optical imagery and SfM photogrammetry to characterize the surface grain size of gravel bars in a braided river (Vénéon River, French Alps)

NASA Astrophysics Data System (ADS)

Vázquez-Tarrío, Daniel; Borgniet, Laurent; Liébault, Frédéric; Recking, Alain

2017-05-01

This paper explores the potential of unmanned aerial system (UAS) optical aerial imagery to characterize grain roughness and size distribution in a braided, gravel-bed river (Vénéon River, French Alps). With this aim in view, a Wolman field campaign (19 samples) and five UAS surveys were conducted over the Vénéon braided channel during summer 2015. The UAS consisted of a small quadcopter carrying a GoPro camera. Structure-from-Motion (SfM) photogrammetry was used to extract dense and accurate three-dimensional point clouds. Roughness descriptors (roughness heights, standard deviation of elevation) were computed from the SfM point clouds and were correlated with the median grain size of the Wolman samples. A strong relationship was found between UAS-SfM-derived grain roughness and Wolman grain size. The procedure employed has potential for the rapid and continuous characterization of grain size distribution in exposed bars of gravel-bed rivers. The workflow described in this paper has been successfully used to produce spatially continuous grain size information on exposed gravel bars and to explore textural changes following flow events.

Computer-Delivered Interventions for Health Promotion and Behavioral Risk Reduction: A Meta-Analysis of 75 Randomized Controlled Trials, 1988 – 2007

PubMed Central

Portnoy, David B.; Scott-Sheldon, Lori A. J.; Johnson, Blair T.; Carey, Michael P.

2008-01-01

Objective Use of computers to promote healthy behavior is increasing. To evaluate the efficacy of these computer-delivered interventions, we conducted a meta-analysis of the published literature. Method Studies examining health domains related to the leading health indicators outlined in Healthy People 2010 were selected. Data from 75 randomized controlled trials, published between 1988 and 2007, with 35,685 participants and 82 separate interventions were included. All studies were coded independently by two raters for study and participant characteristics, design and methodology, and intervention content. We calculated weighted mean effect sizes for theoretically-meaningful psychosocial and behavioral outcomes; moderator analyses determined the relation between study characteristics and the magnitude of effect sizes for heterogeneous outcomes. Results Compared with controls, participants who received a computer-delivered intervention improved several hypothesized antecedents of health behavior (knowledge, attitudes, intentions); intervention recipients also improved health behaviors (nutrition, tobacco use, substance use, safer sexual behavior, binge/purge behaviors) and general health maintenance. Several sample, study and intervention characteristics moderated the psychosocial and behavioral outcomes. Conclusion Computer-delivered interventions can lead to improved behavioral health outcomes at first post-intervention assessment. Interventions evaluating outcomes at extended assessment periods are needed to evaluate the longer-term efficacy of computer-delivered interventions. PMID:18403003

Finite mixture models for the computation of isotope ratios in mixed isotopic samples

NASA Astrophysics Data System (ADS)

Koffler, Daniel; Laaha, Gregor; Leisch, Friedrich; Kappel, Stefanie; Prohaska, Thomas

2013-04-01

Finite mixture models have been used for more than 100 years, but have seen a real boost in popularity over the last two decades due to the tremendous increase in available computing power. The areas of application of mixture models range from biology and medicine to physics, economics and marketing. These models can be applied to data where observations originate from various groups and where group affiliations are not known, as is the case for multiple isotope ratios present in mixed isotopic samples. Recently, the potential of finite mixture models for the computation of 235U/238U isotope ratios from transient signals measured in individual (sub-)µm-sized particles by laser ablation - multi-collector - inductively coupled plasma mass spectrometry (LA-MC-ICPMS) was demonstrated by Kappel et al. [1]. The particles, which were deposited on the same substrate, were certified with respect to their isotopic compositions. Here, we focus on the statistical model and its application to isotope data in ecogeochemistry. Commonly applied evaluation approaches for mixed isotopic samples are time-consuming and are dependent on the judgement of the analyst. Thus, isotopic compositions may be overlooked due to the presence of more dominant constituents. Evaluation using finite mixture models can be accomplished unsupervised and automatically. The models try to fit several linear models (regression lines) to subgroups of data taking the respective slope as estimation for the isotope ratio. The finite mixture models are parameterised by: • The number of different ratios. • Number of points belonging to each ratio-group. • The ratios (i.e. slopes) of each group. Fitting of the parameters is done by maximising the log-likelihood function using an iterative expectation-maximisation (EM) algorithm. In each iteration step, groups of size smaller than a control parameter are dropped; thereby the number of different ratios is determined. The analyst only influences some control parameters of the algorithm, i.e. the maximum count of ratios, the minimum relative group-size of data points belonging to each ratio has to be defined. Computation of the models can be done with statistical software. In this study Leisch and Grün's flexmix package [2] for the statistical open-source software R was applied. A code example is available in the electronic supplementary material of Kappel et al. [1]. In order to demonstrate the usefulness of finite mixture models in fields dealing with the computation of multiple isotope ratios in mixed samples, a transparent example based on simulated data is presented and problems regarding small group-sizes are illustrated. In addition, the application of finite mixture models to isotope ratio data measured in uranium oxide particles is shown. The results indicate that finite mixture models perform well in computing isotope ratios relative to traditional estimation procedures and can be recommended for more objective and straightforward calculation of isotope ratios in geochemistry than it is current practice. [1] S. Kappel, S. Boulyga, L. Dorta, D. Günther, B. Hattendorf, D. Koffler, G. Laaha, F. Leisch and T. Prohaska: Evaluation Strategies for Isotope Ratio Measurements of Single Particles by LA-MC-ICPMS, Analytical and Bioanalytical Chemistry, 2013, accepted for publication on 2012-12-18 (doi: 10.1007/s00216-012-6674-3) [2] B. Grün and F. Leisch: Fitting finite mixtures of generalized linear regressions in R. Computational Statistics & Data Analysis, 51(11), 5247-5252, 2007. (doi:10.1016/j.csda.2006.08.014)

Effect of addiction to computer games on physical and mental health of female and male students of guidance school in city of isfahan.

PubMed

Zamani, Eshrat; Chashmi, Maliheh; Hedayati, Nasim

2009-01-01

This study aimed to investigate the effects of addiction to computer games on physical and mental health of students. The study population includes all students in the second year of public guidance schools in the city of Isfahan in the educational year of 2009-2010. The sample size includes 564 students selected by multiple steps stratified sampling. Dependent variables include general health in dimensions of physical health, anxiety and sleeplessness and impaired social functioning. Data were collected using General Health Questionnaire (GHQ-28) scale and a questionnaire on addiction to computer games. Pearson's correlation coefficient and structural model were used for data analysis. There was a significant positive correlation between students' computer games addiction and their physical and mental health in dimensions of physical health, anxiety and sleeplessness There was a significant negative relationship between addictions to computer games and impaired social functioning. The results of this study are in agreement with the findings of other studies around the world. As the results show, addiction to computer games affects various dimensions of health and increases physical problems, anxiety and depression, while decreases social functioning disorder.

Effect of Addiction to Computer Games on Physical and Mental Health of Female and Male Students of Guidance School in City of Isfahan

PubMed Central

Zamani, Eshrat; Chashmi, Maliheh; Hedayati, Nasim

2009-01-01

Background: This study aimed to investigate the effects of addiction to computer games on physical and mental health of students. Methods: The study population includes all students in the second year of public guidance schools in the city of Isfahan in the educational year of 2009-2010. The sample size includes 564 students selected by multiple steps stratified sampling. Dependent variables include general health in dimensions of physical health, anxiety and sleeplessness and impaired social functioning. Data were collected using General Health Questionnaire (GHQ-28) scale and a questionnaire on addiction to computer games. Pearson's correlation coefficient and structural model were used for data analysis. Findings: There was a significant positive correlation between students' computer games addiction and their physical and mental health in dimensions of physical health, anxiety and sleeplessness There was a significant negative relationship between addictions to computer games and impaired social functioning. Conclusion: The results of this study are in agreement with the findings of other studies around the world. As the results show, addiction to computer games affects various dimensions of health and increases physical problems, anxiety and depression, while decreases social functioning disorder. PMID:24494091

Public computing options for individuals with cognitive impairments: survey outcomes.

PubMed

Fox, Lynn Elizabeth; Sohlberg, McKay Moore; Fickas, Stephen; Lemoncello, Rik; Prideaux, Jason

2009-09-01

To examine availability and accessibility of public computing for individuals with cognitive impairment (CI) who reside in the USA. A telephone survey was administered as a semi-structured interview to 145 informants representing seven types of public facilities across three geographically distinct regions using a snowball sampling technique. An Internet search of wireless (Wi-Fi) hotspots supplemented the survey. Survey results showed the availability of public computer terminals and Internet hotspots was greatest in the urban sample, followed by the mid-sized and rural cities. Across seven facility types surveyed, libraries had the highest percentage of access barriers, including complex queue procedures, login and password requirements, and limited technical support. University assistive technology centres and facilities with a restricted user policy, such as brain injury centres, had the lowest incidence of access barriers. Findings suggest optimal outcomes for people with CI will result from a careful match of technology and the user that takes into account potential barriers and opportunities to computing in an individual's preferred public environments. Trends in public computing, including the emergence of widespread Wi-Fi and limited access to terminals that permit auto-launch applications, should guide development of technology designed for use in public computing environments.

ELIPGRID-PC: A PC program for calculating hot spot probabilities

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

Davidson, J.R.

1994-10-01

ELIPGRID-PC, a new personal computer program has been developed to provide easy access to Singer`s 1972 ELIPGRID algorithm for hot-spot detection probabilities. Three features of the program are the ability to determine: (1) the grid size required for specified conditions, (2) the smallest hot spot that can be sampled with a given probability, and (3) the approximate grid size resulting from specified conditions and sampling cost. ELIPGRID-PC also provides probability of hit versus cost data for graphing with spread-sheets or graphics software. The program has been successfully tested using Singer`s published ELIPGRID results. An apparent error in the original ELIPGRIDmore » code has been uncovered and an appropriate modification incorporated into the new program.« less

SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations.

PubMed

Shannon, Casey P; Chen, Virginia; Takhar, Mandeep; Hollander, Zsuzsanna; Balshaw, Robert; McManus, Bruce M; Tebbutt, Scott J; Sin, Don D; Ng, Raymond T

2016-11-14

Gene network inference (GNI) algorithms can be used to identify sets of coordinately expressed genes, termed network modules from whole transcriptome gene expression data. The identification of such modules has become a popular approach to systems biology, with important applications in translational research. Although diverse computational and statistical approaches have been devised to identify such modules, their performance behavior is still not fully understood, particularly in complex human tissues. Given human heterogeneity, one important question is how the outputs of these computational methods are sensitive to the input sample set, or stability. A related question is how this sensitivity depends on the size of the sample set. We describe here the SABRE (Similarity Across Bootstrap RE-sampling) procedure for assessing the stability of gene network modules using a re-sampling strategy, introduce a novel criterion for identifying stable modules, and demonstrate the utility of this approach in a clinically-relevant cohort, using two different gene network module discovery algorithms. The stability of modules increased as sample size increased and stable modules were more likely to be replicated in larger sets of samples. Random modules derived from permutated gene expression data were consistently unstable, as assessed by SABRE, and provide a useful baseline value for our proposed stability criterion. Gene module sets identified by different algorithms varied with respect to their stability, as assessed by SABRE. Finally, stable modules were more readily annotated in various curated gene set databases. The SABRE procedure and proposed stability criterion may provide guidance when designing systems biology studies in complex human disease and tissues.

Effects of sample size on KERNEL home range estimates

USGS Publications Warehouse

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

1999-01-01

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

Modeling TiO2's refractive index function from bulk to nanoparticles

NASA Astrophysics Data System (ADS)

Jalava, Juho-Pertti; Taavitsainen, Veli-Matti; Lamminmäki, Ralf-Johan; Lindholm, Minna; Auvinen, Sami; Alatalo, Matti; Vartiainen, Erik; Haario, Heikki

2015-12-01

In recent decades, the use of nanomaterials has become very common. Different nanomaterials are being used in over 1600 consumer products. Nanomaterials have been defined as having at least one dimension in the range of 1-100 nm. Such materials often have unique properties. Despite some warnings of applying bulk optical constants for nano size materials, stated already in 1980s, bulk constants are still commonly used in the light scattering measurements of nano size particles. Titanium dioxide is one of the materials that is manufactured and used as an engineered nanomaterial in increasing quantities. Due to the aforementioned facts, it is quite crucial for successful research and production of nanoparticles to find out the dependence of the refractive index function (RIF) of the material on its crystal size. We have earlier performed several ab initio computations for obtaining the dependence of the RIF of TiO2 on the crystal or on the cluster size, for particles of size up to ca. 2 nm. Extending the calculations to greater sizes has turned out to be infeasible due to the unbearable increase in computational time. However, in this study we show how the crystal-size-dependent-RIF (CS-RIF), for both rutile and anatase can be modeled from measured extinction or turbidity spectra of samples with varying crystal and particle sizes. For computing the turbidity spectrum, we constructed a model including primary crystals whose distributions were parameterized by mean and standard deviation, and also including aggregates consisting of mean sized primary particles, parameterized just by mean aggregate size. Mainly because of the long computing times Mie calculation was used in the computation of extinction spectra. However, in practical process applications, the obtained RIF will be used together with the T-matrix method. We constructed the RIFs used in the model using generalized oscillator model (GOM) as expanded to crystal size dependence. The unknown parameters of the model were solved using nonlinear least squares estimation. When the crystal size becomes smaller than the bulk size the shape of the estimated CS-RIFs reveal two distinct regions for both rutile and anatase. In the first region, starting apparently already from ca. 200 nm, the height of both the real part and the imaginary part of CS-RIF decreases on crystal diameter. However, the band gap remains constant. In the second region, starting when the crystal diameter is decreased to ca. 3 nm, a blue shift starts to increase the band gap. The band gap dependence on crystal size is quite consistent with the existing experimental values. Consequently, it is of great importance to use CS-RIF in light scattering measurements for nanoparticle size determination. Neglecting this, the smaller particles in the size distribution will have too small values, already for sub-micrometer particles, naturally distorting also the mean value. To our knowledge, this is the first time ever that a CS-RIF from bulk to 1 nm size is determined for any material.

Fitting models of continuous trait evolution to incompletely sampled comparative data using approximate Bayesian computation.

PubMed

Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

2012-03-01

In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Progressive Sampling Technique for Efficient and Robust Uncertainty and Sensitivity Analysis of Environmental Systems Models: Stability and Convergence

NASA Astrophysics Data System (ADS)

Sheikholeslami, R.; Hosseini, N.; Razavi, S.

2016-12-01

Modern earth and environmental models are usually characterized by a large parameter space and high computational cost. These two features prevent effective implementation of sampling-based analysis such as sensitivity and uncertainty analysis, which require running these computationally expensive models several times to adequately explore the parameter/problem space. Therefore, developing efficient sampling techniques that scale with the size of the problem, computational budget, and users' needs is essential. In this presentation, we propose an efficient sequential sampling strategy, called Progressive Latin Hypercube Sampling (PLHS), which provides an increasingly improved coverage of the parameter space, while satisfying pre-defined requirements. The original Latin hypercube sampling (LHS) approach generates the entire sample set in one stage; on the contrary, PLHS generates a series of smaller sub-sets (also called `slices') while: (1) each sub-set is Latin hypercube and achieves maximum stratification in any one dimensional projection; (2) the progressive addition of sub-sets remains Latin hypercube; and thus (3) the entire sample set is Latin hypercube. Therefore, it has the capability to preserve the intended sampling properties throughout the sampling procedure. PLHS is deemed advantageous over the existing methods, particularly because it nearly avoids over- or under-sampling. Through different case studies, we show that PHLS has multiple advantages over the one-stage sampling approaches, including improved convergence and stability of the analysis results with fewer model runs. In addition, PLHS can help to minimize the total simulation time by only running the simulations necessary to achieve the desired level of quality (e.g., accuracy, and convergence rate).

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Quantum supremacy in constant-time measurement-based computation: A unified architecture for sampling and verification

NASA Astrophysics Data System (ADS)

Miller, Jacob; Sanders, Stephen; Miyake, Akimasa

2017-12-01

While quantum speed-up in solving certain decision problems by a fault-tolerant universal quantum computer has been promised, a timely research interest includes how far one can reduce the resource requirement to demonstrate a provable advantage in quantum devices without demanding quantum error correction, which is crucial for prolonging the coherence time of qubits. We propose a model device made of locally interacting multiple qubits, designed such that simultaneous single-qubit measurements on it can output probability distributions whose average-case sampling is classically intractable, under similar assumptions as the sampling of noninteracting bosons and instantaneous quantum circuits. Notably, in contrast to these previous unitary-based realizations, our measurement-based implementation has two distinctive features. (i) Our implementation involves no adaptation of measurement bases, leading output probability distributions to be generated in constant time, independent of the system size. Thus, it could be implemented in principle without quantum error correction. (ii) Verifying the classical intractability of our sampling is done by changing the Pauli measurement bases only at certain output qubits. Our usage of random commuting quantum circuits in place of computationally universal circuits allows a unique unification of sampling and verification, so they require the same physical resource requirements in contrast to the more demanding verification protocols seen elsewhere in the literature.

Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach

NASA Technical Reports Server (NTRS)

Warner, James E.; Hochhalter, Jacob D.

2016-01-01

This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.

Factors Associated with the Performance and Cost-Effectiveness of Using Lymphatic Filariasis Transmission Assessment Surveys for Monitoring Soil-Transmitted Helminths: A Case Study in Kenya

PubMed Central

Smith, Jennifer L.; Sturrock, Hugh J. W.; Assefa, Liya; Nikolay, Birgit; Njenga, Sammy M.; Kihara, Jimmy; Mwandawiro, Charles S.; Brooker, Simon J.

2015-01-01

Transmission assessment surveys (TAS) for lymphatic filariasis have been proposed as a platform to assess the impact of mass drug administration (MDA) on soil-transmitted helminths (STHs). This study used computer simulation and field data from pre- and post-MDA settings across Kenya to evaluate the performance and cost-effectiveness of the TAS design for STH assessment compared with alternative survey designs. Variations in the TAS design and different sample sizes and diagnostic methods were also evaluated. The district-level TAS design correctly classified more districts compared with standard STH designs in pre-MDA settings. Aggregating districts into larger evaluation units in a TAS design decreased performance, whereas age group sampled and sample size had minimal impact. The low diagnostic sensitivity of Kato-Katz and mini-FLOTAC methods was found to increase misclassification. We recommend using a district-level TAS among children 8–10 years of age to assess STH but suggest that key consideration is given to evaluation unit size. PMID:25487730

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

NASA Astrophysics Data System (ADS)

Fajriyah, Rohmatul; Rosadi, Dedi

2017-12-01

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

A computer system for analysis and transmission of spirometry waveforms using volume sampling.

PubMed

Ostler, D V; Gardner, R M; Crapo, R O

1984-06-01

A microprocessor-controlled data gathering system for telemetry and analysis of spirometry waveforms was implemented using a completely digital design. Spirometry waveforms were obtained from an optical shaft encoder attached to a rolling seal spirometer. Time intervals between 10-ml volume changes (volume sampling) were stored. The digital design eliminated problems of analog signal sampling. The system measured flows up to 12 liters/sec with 5% accuracy and volumes up to 10 liters with 1% accuracy. Transmission of 10 waveforms took about 3 min. Error detection assured that no data were lost or distorted during transmission. A pulmonary physician at the central hospital reviewed the volume-time and flow-volume waveforms and interpretations generated by the central computer before forwarding the results and consulting with the rural physician. This system is suitable for use in a major hospital, rural hospital, or small clinic because of the system's simplicity and small size.

Technologies for imaging neural activity in large volumes

PubMed Central

Ji, Na; Freeman, Jeremy; Smith, Spencer L.

2017-01-01

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Collecting data from individual planes, conventional microscopy cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here, we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for the processing and analysis of volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics, and help elucidate how brain regions work in concert to support behavior. PMID:27571194

Laser Velocimeter Measurements and Analysis in Turbulent Flows with Combustion. Part 2.

DTIC Science & Technology

1983-07-01

sampling error for 63 this sample size. Mean velocities and turbulence intensi- ties were found to be statistically accurate to ± 1 % and 13%, respectively...Although the statist - ical error was found to be rather small (± 1 % for mean velo- cities and 13% for turbulence intensities), there can be additional...34Computational and Experimental Study of a Captive Annular Eddy," Journal of Fluid Mechanics, Vol. 28, pt. 1 , pp. 43-63, 12 April, 1967. 152 REFERENCES (con’d

Three Dimensional Imaging of Paraffin Embedded Human Lung Tissue Samples by Micro-Computed Tomography

PubMed Central

Scott, Anna E.; Vasilescu, Dragos M.; Seal, Katherine A. D.; Keyes, Samuel D.; Mavrogordato, Mark N.; Hogg, James C.; Sinclair, Ian; Warner, Jane A.; Hackett, Tillie-Louise; Lackie, Peter M.

2015-01-01

Background Understanding the three-dimensional (3-D) micro-architecture of lung tissue can provide insights into the pathology of lung disease. Micro computed tomography (µCT) has previously been used to elucidate lung 3D histology and morphometry in fixed samples that have been stained with contrast agents or air inflated and dried. However, non-destructive microstructural 3D imaging of formalin-fixed paraffin embedded (FFPE) tissues would facilitate retrospective analysis of extensive tissue archives of lung FFPE lung samples with linked clinical data. Methods FFPE human lung tissue samples (n = 4) were scanned using a Nikon metrology µCT scanner. Semi-automatic techniques were used to segment the 3D structure of airways and blood vessels. Airspace size (mean linear intercept, Lm) was measured on µCT images and on matched histological sections from the same FFPE samples imaged by light microscopy to validate µCT imaging. Results The µCT imaging protocol provided contrast between tissue and paraffin in FFPE samples (15mm x 7mm). Resolution (voxel size 6.7 µm) in the reconstructed images was sufficient for semi-automatic image segmentation of airways and blood vessels as well as quantitative airspace analysis. The scans were also used to scout for regions of interest, enabling time-efficient preparation of conventional histological sections. The Lm measurements from µCT images were not significantly different to those from matched histological sections. Conclusion We demonstrated how non-destructive imaging of routinely prepared FFPE samples by laboratory µCT can be used to visualize and assess the 3D morphology of the lung including by morphometric analysis. PMID:26030902

Insomnia symptoms among Greek adolescent students with excessive computer use

PubMed Central

Siomos, K E; Braimiotis, D; Floros, G D; Dafoulis, V; Angelopoulos, N V

2010-01-01

Background: The aim of the present study is to assess the intensity of computer use and insomnia epidemiology among Greek adolescents, to examine any possible age and gender differences and to investigate whether excessive computer use is a risk factor for developing insomnia symptoms. Patients and Methods: Cross-sectional study of a stratified sample of 2195 high school students. Demographic data were recorded and two specific questionnaires were used, the Adolescent Computer Addiction Test (ACAT) and the Athens Insomnia Scale (AIS). Results: Females scored higher than males on insomnia complaints but lower on computer use and addiction. A dosemediated effect of computer use on insomnia complaints was recorded. Computer use had a larger effect size than sex on insomnia complaints. Duration of computer use was longer for those adolescents classified as suffering from insomnia compared to those who were not. Conclusions: Computer use can be a significant cause of insomnia complaints in an adolescent population regardless of whether the individual is classified as addicted or not. PMID:20981171

Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions.

PubMed

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.

From the field: Efficacy of detecting Chronic Wasting Disease via sampling hunter-killed white-tailed deer

USGS Publications Warehouse

Diefenbach, D.R.; Rosenberry, C.S.; Boyd, Robert C.

2004-01-01

Surveillance programs for Chronic Wasting Disease (CWD) in free-ranging cervids often use a standard of being able to detect 1% prevalence when determining minimum sample sizes. However, 1% prevalence may represent >10,000 infected animals in a population of 1 million, and most wildlife managers would prefer to detect the presence of CWD when far fewer infected animals exist. We wanted to detect the presence of CWD in white-tailed deer (Odocoileus virginianus) in Pennsylvania when the disease was present in only 1 of 21 wildlife management units (WMUs) statewide. We used computer simulation to estimate the probability of detecting CWD based on a sampling design to detect the presence of CWD at 0.1% and 1.0% prevalence (23-76 and 225-762 infected deer, respectively) using tissue samples collected from hunter-killed deer. The probability of detection at 0.1% prevalence was <30% with sample sizes of ???6,000 deer, and the probability of detection at 1.0% prevalence was 46-72% with statewide sample sizes of 2,000-6,000 deer. We believe that testing of hunter-killed deer is an essential part of any surveillance program for CWD, but our results demonstrated the importance of a multifaceted surveillance approach for CWD detection rather than sole reliance on testing hunter-killed deer.

Accuracy of remotely sensed data: Sampling and analysis procedures

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Oderwald, R. G.; Mead, R. A.

1982-01-01

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.

Adaptively resizing populations: Algorithm, analysis, and first results

NASA Technical Reports Server (NTRS)

Smith, Robert E.; Smuda, Ellen

1993-01-01

Deciding on an appropriate population size for a given Genetic Algorithm (GA) application can often be critical to the algorithm's success. Too small, and the GA can fall victim to sampling error, affecting the efficacy of its search. Too large, and the GA wastes computational resources. Although advice exists for sizing GA populations, much of this advice involves theoretical aspects that are not accessible to the novice user. An algorithm for adaptively resizing GA populations is suggested. This algorithm is based on recent theoretical developments that relate population size to schema fitness variance. The suggested algorithm is developed theoretically, and simulated with expected value equations. The algorithm is then tested on a problem where population sizing can mislead the GA. The work presented suggests that the population sizing algorithm may be a viable way to eliminate the population sizing decision from the application of GA's.

An Educational Software for Simulating the Sample Size of Molecular Marker Experiments

ERIC Educational Resources Information Center

Helms, T. C.; Doetkott, C.

2007-01-01

We developed educational software to show graduate students how to plan molecular marker experiments. These computer simulations give the students feedback on the precision of their experiments. The objective of the software was to show students using a hands-on approach how: (1) environmental variation influences the range of the estimates of the…

Computer programs for computing particle-size statistics of fluvial sediments

USGS Publications Warehouse

Stevens, H.H.; Hubbell, D.W.

1986-01-01

Two versions of computer programs for inputing data and computing particle-size statistics of fluvial sediments are presented. The FORTRAN 77 language versions are for use on the Prime computer, and the BASIC language versions are for use on microcomputers. The size-statistics program compute Inman, Trask , and Folk statistical parameters from phi values and sizes determined for 10 specified percent-finer values from inputed size and percent-finer data. The program also determines the percentage gravel, sand, silt, and clay, and the Meyer-Peter effective diameter. Documentation and listings for both versions of the programs are included. (Author 's abstract)

User manual for semi-circular compact range reflector code: Version 2

NASA Technical Reports Server (NTRS)

Gupta, Inder J.; Burnside, Walter D.

1987-01-01

A computer code has been developed at the Ohio State University ElectroScience Laboratory to analyze a semi-circular paraboloidal reflector with or without a rolled edge at the top and a skirt at the bottom. The code can be used to compute the total near field of the reflector or its individual components at a given distance from the center of the paraboloid. The code computes the fields along a radial, horizontal, vertical or axial cut at that distance. Thus, it is very effective in computing the size of the sweet spot for a semi-circular compact range reflector. This report describes the operation of the code. Various input and output statements are explained. Some results obtained using the computer code are presented to illustrate the code's capability as well as being samples of input/output sets.

Using computer assisted learning for clinical skills education in nursing: integrative review.

PubMed

Bloomfield, Jacqueline G; While, Alison E; Roberts, Julia D

2008-08-01

This paper is a report of an integrative review of research investigating computer assisted learning for clinical skills education in nursing, the ways in which it has been studied and the general findings. Clinical skills are an essential aspect of nursing practice and there is international debate about the most effective ways in which these can be taught. Computer assisted learning has been used as an alternative to conventional teaching methods, and robust research to evaluate its effectiveness is essential. The CINAHL, Medline, BNI, PsycInfo and ERIC electronic databases were searched for the period 1997-2006 for research-based papers published in English. Electronic citation tracking and hand searching of reference lists and relevant journals was also undertaken. Twelve studies met the inclusion criteria. An integrative review was conducted and each paper was explored in relation to: design, aims, sample, outcome measures and findings. Many of the study samples were small and there were weaknesses in designs. There is limited empirical evidence addressing the use of computer assisted learning for clinical skills education in nursing. Computer assisted learning has been used to teach a limited range of clinical skills in a variety of settings. The paucity of evaluative studies indicates the need for more rigorous research to investigate the effect of computer assisted learning for this purpose. Areas that need to be addressed in future studies include: sample size, range of skills, longitudinal follow-up and control of confounding variables.

Convex hull approach for determining rock representative elementary volume for multiple petrophysical parameters using pore-scale imaging and Lattice-Boltzmann modelling

NASA Astrophysics Data System (ADS)

Shah, S. M.; Crawshaw, J. P.; Gray, F.; Yang, J.; Boek, E. S.

2017-06-01

In the last decade, the study of fluid flow in porous media has developed considerably due to the combination of X-ray Micro Computed Tomography (micro-CT) and advances in computational methods for solving complex fluid flow equations directly or indirectly on reconstructed three-dimensional pore space images. In this study, we calculate porosity and single phase permeability using micro-CT imaging and Lattice Boltzmann (LB) simulations for 8 different porous media: beadpacks (with bead sizes 50 μm and 350 μm), sandpacks (LV60 and HST95), sandstones (Berea, Clashach and Doddington) and a carbonate (Ketton). Combining the observed porosity and calculated single phase permeability, we shed new light on the existence and size of the Representative Element of Volume (REV) capturing the different scales of heterogeneity from the pore-scale imaging. Our study applies the concept of the 'Convex Hull' to calculate the REV by considering the two main macroscopic petrophysical parameters, porosity and single phase permeability, simultaneously. The shape of the hull can be used to identify strong correlation between the parameters or greatly differing convergence rates. To further enhance computational efficiency we note that the area of the convex hull (for well-chosen parameters such as the log of the permeability and the porosity) decays exponentially with sub-sample size so that only a few small simulations are needed to determine the system size needed to calculate the parameters to high accuracy (small convex hull area). Finally we propose using a characteristic length such as the pore size to choose an efficient absolute voxel size for the numerical rock.

Tackling the conformational sampling of larger flexible compounds and macrocycles in pharmacology and drug discovery.

PubMed

Chen, I-Jen; Foloppe, Nicolas

2013-12-15

Computational conformational sampling underpins much of molecular modeling and design in pharmaceutical work. The sampling of smaller drug-like compounds has been an active area of research. However, few studies have tested in details the sampling of larger more flexible compounds, which are also relevant to drug discovery, including therapeutic peptides, macrocycles, and inhibitors of protein-protein interactions. Here, we investigate extensively mainstream conformational sampling methods on three carefully curated compound sets, namely the 'Drug-like', larger 'Flexible', and 'Macrocycle' compounds. These test molecules are chemically diverse with reliable X-ray protein-bound bioactive structures. The compared sampling methods include Stochastic Search and the recent LowModeMD from MOE, all the low-mode based approaches from MacroModel, and MD/LLMOD recently developed for macrocycles. In addition to default settings, key parameters of the sampling protocols were explored. The performance of the computational protocols was assessed via (i) the reproduction of the X-ray bioactive structures, (ii) the size, coverage and diversity of the output conformational ensembles, (iii) the compactness/extendedness of the conformers, and (iv) the ability to locate the global energy minimum. The influence of the stochastic nature of the searches on the results was also examined. Much better results were obtained by adopting search parameters enhanced over the default settings, while maintaining computational tractability. In MOE, the recent LowModeMD emerged as the method of choice. Mixed torsional/low-mode from MacroModel performed as well as LowModeMD, and MD/LLMOD performed well for macrocycles. The low-mode based approaches yielded very encouraging results with the flexible and macrocycle sets. Thus, one can productively tackle the computational conformational search of larger flexible compounds for drug discovery, including macrocycles. Copyright © 2013 Elsevier Ltd. All rights reserved.

Streamflow and suspended-sediment transport in Garvin Brook, Winona County, southeastern Minnesota: Hydrologic data for 1982

USGS Publications Warehouse

Payne, G.A.

1983-01-01

Streamflow and suspended-sediment-transport data were collected in Garvin Brook watershed in Winona County, southeastern Minnesota, during 1982. The data collection was part of a study to determine the effectiveness of agricultural best-management practices designed to improve rural water quality. The study is part of a Rural Clean Water Program demonstration project undertaken by the U.S. Department of Agriculture. Continuous streamflow data were collected at three gaging stations during March through September 1982. Suspended-sediment samples were collected at two of the gaging stations. Samples were collected manually at weekly intervals. During periods of rapidly changing stage, samples were collected at 30-minute to 12-hour intervals by stage-activated automatic samplers. The samples were analyzed for suspendedsediment concentration and particle-size distribution. Particlesize distributions were also determined for one set of bedmaterial samples collected at each sediment-sampling site. The streamflow and suspended-sediment-concentration data were used to compute records of mean-daily flow, mean-daily suspended-sediment concentration, and daily suspended-sediment discharge. The daily records are documented and results of analyses for particle-size distribution and of vertical sampling in the stream cross sections are given.

Modified Toxicity Probability Interval Design: A Safer and More Reliable Method Than the 3 + 3 Design for Practical Phase I Trials

PubMed Central

Ji, Yuan; Wang, Sue-Jane

2013-01-01

The 3 + 3 design is the most common choice among clinicians for phase I dose-escalation oncology trials. In recent reviews, more than 95% of phase I trials have been based on the 3 + 3 design. Given that it is intuitive and its implementation does not require a computer program, clinicians can conduct 3 + 3 dose escalations in practice with virtually no logistic cost, and trial protocols based on the 3 + 3 design pass institutional review board and biostatistics reviews quickly. However, the performance of the 3 + 3 design has rarely been compared with model-based designs in simulation studies with matched sample sizes. In the vast majority of statistical literature, the 3 + 3 design has been shown to be inferior in identifying true maximum-tolerated doses (MTDs), although the sample size required by the 3 + 3 design is often orders-of-magnitude smaller than model-based designs. In this article, through comparative simulation studies with matched sample sizes, we demonstrate that the 3 + 3 design has higher risks of exposing patients to toxic doses above the MTD than the modified toxicity probability interval (mTPI) design, a newly developed adaptive method. In addition, compared with the mTPI design, the 3 + 3 design does not yield higher probabilities in identifying the correct MTD, even when the sample size is matched. Given that the mTPI design is equally transparent, costless to implement with free software, and more flexible in practical situations, we highly encourage its adoption in early dose-escalation studies whenever the 3 + 3 design is also considered. We provide free software to allow direct comparisons of the 3 + 3 design with other model-based designs in simulation studies with matched sample sizes. PMID:23569307

Driven Boson Sampling.

PubMed

Barkhofen, Sonja; Bartley, Tim J; Sansoni, Linda; Kruse, Regina; Hamilton, Craig S; Jex, Igor; Silberhorn, Christine

2017-01-13

Sampling the distribution of bosons that have undergone a random unitary evolution is strongly believed to be a computationally hard problem. Key to outperforming classical simulations of this task is to increase both the number of input photons and the size of the network. We propose driven boson sampling, in which photons are input within the network itself, as a means to approach this goal. We show that the mean number of photons entering a boson sampling experiment can exceed one photon per input mode, while maintaining the required complexity, potentially leading to less stringent requirements on the input states for such experiments. When using heralded single-photon sources based on parametric down-conversion, this approach offers an ∼e-fold enhancement in the input state generation rate over scattershot boson sampling, reaching the scaling limit for such sources. This approach also offers a dramatic increase in the signal-to-noise ratio with respect to higher-order photon generation from such probabilistic sources, which removes the need for photon number resolution during the heralding process as the size of the system increases.

Supportive communication with parents moderates the negative effects of electronic media use on life satisfaction during adolescence.

PubMed

Boniel-Nissim, Meyran; Tabak, Izabela; Mazur, Joanna; Borraccino, Alberto; Brooks, Fiona; Gommans, Rob; van der Sluijs, Winfried; Zsiros, Emese; Craig, Wendy; Harel-Fisch, Yossi; Finne, Emily

2015-02-01

To examine the impact of electronic media (EM) use on teenagers' life satisfaction (LS) and to assess the potential moderating effect of supportive communication with parents (SCP). Data were drawn from the cross-national Health Behaviour in School-aged Children (HBSC) study (2009/2010) in Canada, England, Germany, Hungary, Italy, Israel, The Netherlands, Poland and Scotland. Sample size: 53,973 students aged 11-15 years. More hours per day spent on the computer were associated with lower LS; more EM communication with friends with higher LS. This relationship became negative if EM use reached and exceeded a certain threshold. SCP moderated the effect of EM communication with friends, but not computer use for the total sample. SCP seems to be more important than computer use or EM communication with friends for LS and it seems to buffer negative effects of EM use. Communication with parents seems to buffer the negative effects of EM use on LS during adolescence. Higher computer use was related to lower LS, but "optimal" frequency of EM communication with friends was country specific.

Detection of seizures from small samples using nonlinear dynamic system theory.

PubMed

Yaylali, I; Koçak, H; Jayakar, P

1996-07-01

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.

Computational Methodology for Absolute Calibration Curves for Microfluidic Optical Analyses

PubMed Central

Chang, Chia-Pin; Nagel, David J.; Zaghloul, Mona E.

2010-01-01

Optical fluorescence and absorption are two of the primary techniques used for analytical microfluidics. We provide a thorough yet tractable method for computing the performance of diverse optical micro-analytical systems. Sample sizes range from nano- to many micro-liters and concentrations from nano- to milli-molar. Equations are provided to trace quantitatively the flow of the fundamental entities, namely photons and electrons, and the conversion of energy from the source, through optical components, samples and spectral-selective components, to the detectors and beyond. The equations permit facile computations of calibration curves that relate the concentrations or numbers of molecules measured to the absolute signals from the system. This methodology provides the basis for both detailed understanding and improved design of microfluidic optical analytical systems. It saves prototype turn-around time, and is much simpler and faster to use than ray tracing programs. Over two thousand spreadsheet computations were performed during this study. We found that some design variations produce higher signal levels and, for constant noise levels, lower minimum detection limits. Improvements of more than a factor of 1,000 were realized. PMID:22163573

The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina

NASA Technical Reports Server (NTRS)

Shain, W.; Nix, L.

1982-01-01

Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.

Pore-scale simulations of drainage in granular materials: Finite size effects and the representative elementary volume

NASA Astrophysics Data System (ADS)

Yuan, Chao; Chareyre, Bruno; Darve, Félix

2016-09-01

A pore-scale model is introduced for two-phase flow in dense packings of polydisperse spheres. The model is developed as a component of a more general hydromechanical coupling framework based on the discrete element method, which will be elaborated in future papers and will apply to various processes of interest in soil science, in geomechanics and in oil and gas production. Here the emphasis is on the generation of a network of pores mapping the void space between spherical grains, and the definition of local criteria governing the primary drainage process. The pore space is decomposed by Regular Triangulation, from which a set of pores connected by throats are identified. A local entry capillary pressure is evaluated for each throat, based on the balance of capillary pressure and surface tension at equilibrium. The model reflects the possible entrapment of disconnected patches of the receding wetting phase. It is validated by a comparison with drainage experiments. In the last part of the paper, a series of simulations are reported to illustrate size and boundary effects, key questions when studying small samples made of spherical particles be it in simulations or experiments. Repeated tests on samples of different sizes give evolution of water content which are not only scattered but also strongly biased for small sample sizes. More than 20,000 spheres are needed to reduce the bias on saturation below 0.02. Additional statistics are generated by subsampling a large sample of 64,000 spheres. They suggest that the minimal sampling volume for evaluating saturation is one hundred times greater that the sampling volume needed for measuring porosity with the same accuracy. This requirement in terms of sample size induces a need for efficient computer codes. The method described herein has a low algorithmic complexity in order to satisfy this requirement. It will be well suited to further developments toward coupled flow-deformation problems in which evolution of the microstructure require frequent updates of the pore network.

The multiple imputation method: a case study involving secondary data analysis.

PubMed

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems

PubMed Central

Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.

2016-01-01

Abstract. The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment. PMID:27493982

Theory and applications of a deterministic approximation to the coalescent model

PubMed Central

Jewett, Ethan M.; Rosenberg, Noah A.

2014-01-01

Under the coalescent model, the random number nt of lineages ancestral to a sample is nearly deterministic as a function of time when nt is moderate to large in value, and it is well approximated by its expectation E[nt]. In turn, this expectation is well approximated by simple deterministic functions that are easy to compute. Such deterministic functions have been applied to estimate allele age, effective population size, and genetic diversity, and they have been used to study properties of models of infectious disease dynamics. Although a number of simple approximations of E[nt] have been derived and applied to problems of population-genetic inference, the theoretical accuracy of the formulas and the inferences obtained using these approximations is not known, and the range of problems to which they can be applied is not well understood. Here, we demonstrate general procedures by which the approximation nt ≈ E[nt] can be used to reduce the computational complexity of coalescent formulas, and we show that the resulting approximations converge to their true values under simple assumptions. Such approximations provide alternatives to exact formulas that are computationally intractable or numerically unstable when the number of sampled lineages is moderate or large. We also extend an existing class of approximations of E[nt] to the case of multiple populations of time-varying size with migration among them. Our results facilitate the use of the deterministic approximation nt ≈ E[nt] for deriving functionally simple, computationally efficient, and numerically stable approximations of coalescent formulas under complicated demographic scenarios. PMID:24412419

CAVE: A computer code for two-dimensional transient heating analysis of conceptual thermal protection systems for hypersonic vehicles

NASA Technical Reports Server (NTRS)

Rathjen, K. A.

1977-01-01

A digital computer code CAVE (Conduction Analysis Via Eigenvalues), which finds application in the analysis of two dimensional transient heating of hypersonic vehicles is described. The CAVE is written in FORTRAN 4 and is operational on both IBM 360-67 and CDC 6600 computers. The method of solution is a hybrid analytical numerical technique that is inherently stable permitting large time steps even with the best of conductors having the finest of mesh size. The aerodynamic heating boundary conditions are calculated by the code based on the input flight trajectory or can optionally be calculated external to the code and then entered as input data. The code computes the network conduction and convection links, as well as capacitance values, given basic geometrical and mesh sizes, for four generations (leading edges, cooled panels, X-24C structure and slabs). Input and output formats are presented and explained. Sample problems are included. A brief summary of the hybrid analytical-numerical technique, which utilizes eigenvalues (thermal frequencies) and eigenvectors (thermal mode vectors) is given along with aerodynamic heating equations that have been incorporated in the code and flow charts.

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

PubMed

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

2012-12-01

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

Transport and collision dynamics in periodic asymmetric obstacle arrays: Rational design of microfluidic rare-cell immunocapture devices

NASA Astrophysics Data System (ADS)

Gleghorn, Jason P.; Smith, James P.; Kirby, Brian J.

2013-09-01

Microfluidic obstacle arrays have been used in numerous applications, and their ability to sort particles or capture rare cells from complex samples has broad and impactful applications in biology and medicine. We have investigated the transport and collision dynamics of particles in periodic obstacle arrays to guide the design of convective, rather than diffusive, transport-based immunocapture microdevices. Ballistic and full computational fluid dynamics simulations are used to understand the collision modes that evolve in cylindrical obstacle arrays with various geometries. We identify previously unrecognized collision mode structures and differential size-based collision frequencies that emerge from these arrays. Previous descriptions of transverse displacements that assume unidirectional flow in these obstacle arrays cannot capture mode transitions properly as these descriptions fail to capture the dependence of the mode transitions on column spacing and the attendant change in the flow field. Using these analytical and computational simulations, we elucidate design parameters that induce high collision rates for all particles larger than a threshold size or selectively increase collision frequencies for a narrow range of particle sizes within a polydisperse population. Furthermore, we investigate how the particle Péclet number affects collision dynamics and mode transitions and demonstrate that experimental observations from various obstacle array geometries are well described by our computational model.

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

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

Hero, Alfred O.; Rajaratnam, Bala

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

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

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

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

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

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

Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM).

PubMed

Haverkamp, Nicolas; Beauducel, André

2017-01-01

We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach. In contrast to previous simulation studies on this topic, up to nine measurement occasions were considered. Effects of the level of inter-correlations between measurement occasions on Type I error rates were considered for the first time. Two populations with non-violation of the sphericity assumption, one with uncorrelated measurement occasions and one with moderately correlated measurement occasions, were generated. One population with violation of the sphericity assumption combines uncorrelated with highly correlated measurement occasions. A second population with violation of the sphericity assumption combines moderately correlated and highly correlated measurement occasions. From these four populations without any between-group effect or within-subject effect 5,000 random samples were drawn. Finally, the mean Type I error rates for Multilevel linear models (MLM) with an unstructured covariance matrix (MLM-UN), MLM with compound-symmetry (MLM-CS) and for repeated measures analysis of variance (rANOVA) models (without correction, with Greenhouse-Geisser-correction, and Huynh-Feldt-correction) were computed. To examine the effect of both the sample size and the number of measurement occasions, sample sizes of n = 20, 40, 60, 80, and 100 were considered as well as measurement occasions of m = 3, 6, and 9. With respect to rANOVA, the results plead for a use of rANOVA with Huynh-Feldt-correction, especially when the sphericity assumption is violated, the sample size is rather small and the number of measurement occasions is large. For MLM-UN, the results illustrate a massive progressive bias for small sample sizes ( n = 20) and m = 6 or more measurement occasions. This effect could not be found in previous simulation studies with a smaller number of measurement occasions. The proportionality of bias and number of measurement occasions should be considered when MLM-UN is used. The good news is that this proportionality can be compensated by means of large sample sizes. Accordingly, MLM-UN can be recommended even for small sample sizes for about three measurement occasions and for large sample sizes for about nine measurement occasions.

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

Application of a Probalistic Sizing Methodology for Ceramic Structures

NASA Astrophysics Data System (ADS)

Rancurel, Michael; Behar-Lafenetre, Stephanie; Cornillon, Laurence; Leroy, Francois-Henri; Coe, Graham; Laine, Benoit

2012-07-01

Ceramics are increasingly used in the space industry to take advantage of their stability and high specific stiffness properties. Their brittle behaviour often leads to size them by increasing the safety factors that are applied on the maximum stresses. It induces to oversize the structures. This is inconsistent with the major driver in space architecture, the mass criteria. This paper presents a methodology to size ceramic structures based on their failure probability. Thanks to failure tests on samples, the Weibull law which characterizes the strength distribution of the material is obtained. A-value (Q0.0195%) and B-value (Q0.195%) are then assessed to take into account the limited number of samples. A knocked-down Weibull law that interpolates the A- & B- values is also obtained. Thanks to these two laws, a most-likely and a knocked- down prediction of failure probability are computed for complex ceramic structures. The application of this methodology and its validation by test is reported in the paper.

Increasing the sampling efficiency of protein conformational transition using velocity-scaling optimized hybrid explicit/implicit solvent REMD simulation

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

Yu, Yuqi; Wang, Jinan; Shao, Qiang, E-mail: qshao@mail.shcnc.ac.cn, E-mail: Jiye.Shi@ucb.com, E-mail: wlzhu@mail.shcnc.ac.cn

2015-03-28

The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much lessmore » computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.« less

Galactic evolution of copper in the light of NLTE computations

NASA Astrophysics Data System (ADS)

Andrievsky, S.; Bonifacio, P.; Caffau, E.; Korotin, S.; Spite, M.; Spite, F.; Sbordone, L.; Zhukova, A. V.

2018-01-01

We have developed a model atom for Cu with which we perform statistical equilibrium computations that allow us to compute the line formation of Cu I lines in stellar atmospheres without assuming local thermodynamic equilibrium (LTE). We validate this model atom by reproducing the observed line profiles of the Sun, Procyon and 11 metal-poor stars. Our sample of stars includes both dwarfs and giants. Over a wide range of stellar parameters, we obtain excellent agreement among different Cu I lines. The 11 metal-poor stars have iron abundances in the range - 4.2 ≤ [Fe/H] ≤ -1.4, the weighted mean of the [Cu/Fe] ratios is -0.22 dex, with a scatter of -0.15 dex. This is very different from the results from LTE analysis (the difference between NLTE and LTE abundances reaches 1 dex) and in spite of the small size of our sample, it prompts for a revision of the Galactic evolution of Cu.

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

PubMed

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

2010-03-01

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

Reliable and More Powerful Methods for Power Analysis in Structural Equation Modeling

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun

2017-01-01

The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…

Phase-contrast X-ray computed tomography of non-formalin fixed biological objects

NASA Astrophysics Data System (ADS)

Takeda, Tohoru; Momose, Atsushi; Wu, Jin; Zeniya, Tsutomu; Yu, Quanwen; Thet-Thet-Lwin; Itai, Yuji

2001-07-01

Using a monolithic X-ray interferometer having the view size of 25 mm×25 mm, phase-contrast X-ray CT (PCCT) was performed for non-formalin fixed livers of two normal rats and a rabbit transplanted with VX-2 cancer. PCCT images of liver and cancer lesions resembled well those obtained by formalin fixed samples.

A simple encoding method for Sigma-Delta ADC based biopotential acquisition systems.

PubMed

Guerrero, Federico N; Spinelli, Enrique M

2017-10-01

Sigma Delta analogue-to-digital converters allow acquiring the full dynamic range of biomedical signals at the electrodes, resulting in less complex hardware and increased measurement robustness. However, the increased data size per sample (typically 24 bits) demands the transmission of extremely large volumes of data across the isolation barrier, thus increasing power consumption on the patient side. This problem is accentuated when a large number of channels is used as in current 128-256 electrodes biopotential acquisition systems, that usually opt for an optic fibre link to the computer. An analogous problem occurs for simpler low-power acquisition platforms that transmit data through a wireless link to a computing platform. In this paper, a low-complexity encoding method is presented to decrease sample data size without losses, while preserving the full DC-coupled signal. The method achieved a 2.3 average compression ratio evaluated over an ECG and EMG signal bank acquired with equipment based on Sigma-Delta converters. It demands a very low processing load: a C language implementation is presented that resulted in an 110 clock cycles average execution on an 8-bit microcontroller.

A simulation study on Bayesian Ridge regression models for several collinearity levels

NASA Astrophysics Data System (ADS)

Efendi, Achmad; Effrihan

2017-12-01

When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.

Micro-CT images reconstruction and 3D visualization for small animal studying

NASA Astrophysics Data System (ADS)

Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng

2005-01-01

A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

PubMed Central

Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

Geostatistics and the representative elementary volume of gamma ray tomography attenuation in rocks cores

USGS Publications Warehouse

Vogel, J.R.; Brown, G.O.

2003-01-01

Semivariograms of samples of Culebra Dolomite have been determined at two different resolutions for gamma ray computed tomography images. By fitting models to semivariograms, small-scale and large-scale correlation lengths are determined for four samples. Different semivariogram parameters were found for adjacent cores at both resolutions. Relative elementary volume (REV) concepts are related to the stationarity of the sample. A scale disparity factor is defined and is used to determine sample size required for ergodic stationarity with a specified correlation length. This allows for comparison of geostatistical measures and representative elementary volumes. The modifiable areal unit problem is also addressed and used to determine resolution effects on correlation lengths. By changing resolution, a range of correlation lengths can be determined for the same sample. Comparison of voxel volume to the best-fit model correlation length of a single sample at different resolutions reveals a linear scaling effect. Using this relationship, the range of the point value semivariogram is determined. This is the range approached as the voxel size goes to zero. Finally, these results are compared to the regularization theory of point variables for borehole cores and are found to be a better fit for predicting the volume-averaged range.

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

PubMed Central

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

PubMed

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Ascent velocity and dynamics of the Fiumicino mud eruption, Rome, Italy

NASA Astrophysics Data System (ADS)

Vona, A.; Giordano, G.; De Benedetti, A. A.; D'Ambrosio, R.; Romano, C.; Manga, M.

2015-08-01

In August 2013 drilling triggered the eruption of mud near the international airport of Fiumicino (Rome, Italy). We monitored the evolution of the eruption and collected samples for laboratory characterization of physicochemical and rheological properties. Over time, muds show a progressive dilution with water; the rheology is typical of pseudoplastic fluids, with a small yield stress that decreases as mud density decreases. The eruption, while not naturally triggered, shares several similarities with natural mud volcanoes, including mud componentry, grain-size distribution, gas discharge, and mud rheology. We use the size of large ballistic fragments ejected from the vent along with mud rheology to compute a minimum ascent velocity of the mud. Computed values are consistent with in situ measurements of gas phase velocities, confirming that the stratigraphic record of mud eruptions can be quantitatively used to infer eruption history and ascent rates and hence to assess (or reassess) mud eruption hazards.

Removing systematic errors in interionic potentials of mean force computed in molecular simulations using reaction-field-based electrostatics

PubMed Central

Baumketner, Andrij

2009-01-01

The performance of reaction-field methods to treat electrostatic interactions is tested in simulations of ions solvated in water. The potential of mean force between sodium chloride pair of ions and between side chains of lysine and aspartate are computed using umbrella sampling and molecular dynamics simulations. It is found that in comparison with lattice sum calculations, the charge-group-based approaches to reaction-field treatments produce a large error in the association energy of the ions that exhibits strong systematic dependence on the size of the simulation box. The atom-based implementation of the reaction field is seen to (i) improve the overall quality of the potential of mean force and (ii) remove the dependence on the size of the simulation box. It is suggested that the atom-based truncation be used in reaction-field simulations of mixed media. PMID:19292522

Computational Process Modeling for Additive Manufacturing

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2014-01-01

Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

Statistical Methods in Ai: Rare Event Learning Using Associative Rules and Higher-Order Statistics

NASA Astrophysics Data System (ADS)

Iyer, V.; Shetty, S.; Iyengar, S. S.

2015-07-01

Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (t) in our proposed ensemble always yields minimum number (m) of leafs keeping pre-processing computation to n × t log m compared to N2 for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix.

Nature's crucible: Manufacturing optical nonlinearities for high resolution, high sensitivity encoding in the compound eye of the fly, Musca domestica

NASA Technical Reports Server (NTRS)

Wilcox, Mike

1993-01-01

The number of pixels per unit area sampling an image determines Nyquist resolution. Therefore, the highest pixel density is the goal. Unfortunately, as reduction in pixel size approaches the wavelength of light, sensitivity is lost and noise increases. Animals face the same problems and have achieved novel solutions. Emulating these solutions offers potentially unlimited sensitivity with detector size approaching the diffraction limit. Once an image is 'captured', cellular preprocessing of information allows extraction of high resolution information from the scene. Computer simulation of this system promises hyperacuity for machine vision.

Variable size computer-aided detection prompts and mammography film reader decisions

PubMed Central

Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline RM; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen GC; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta

2008-01-01

Introduction The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Methods Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. Results There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). Conclusions For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision. PMID:18724867

Variable size computer-aided detection prompts and mammography film reader decisions.

PubMed

Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline Rm; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen Gc; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta

2008-01-01

The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision.

Simulation Studies as Designed Experiments: The Comparison of Penalized Regression Models in the “Large p, Small n” Setting

PubMed Central

Chaibub Neto, Elias; Bare, J. Christopher; Margolin, Adam A.

2014-01-01

New algorithms are continuously proposed in computational biology. Performance evaluation of novel methods is important in practice. Nonetheless, the field experiences a lack of rigorous methodology aimed to systematically and objectively evaluate competing approaches. Simulation studies are frequently used to show that a particular method outperforms another. Often times, however, simulation studies are not well designed, and it is hard to characterize the particular conditions under which different methods perform better. In this paper we propose the adoption of well established techniques in the design of computer and physical experiments for developing effective simulation studies. By following best practices in planning of experiments we are better able to understand the strengths and weaknesses of competing algorithms leading to more informed decisions about which method to use for a particular task. We illustrate the application of our proposed simulation framework with a detailed comparison of the ridge-regression, lasso and elastic-net algorithms in a large scale study investigating the effects on predictive performance of sample size, number of features, true model sparsity, signal-to-noise ratio, and feature correlation, in situations where the number of covariates is usually much larger than sample size. Analysis of data sets containing tens of thousands of features but only a few hundred samples is nowadays routine in computational biology, where “omics” features such as gene expression, copy number variation and sequence data are frequently used in the predictive modeling of complex phenotypes such as anticancer drug response. The penalized regression approaches investigated in this study are popular choices in this setting and our simulations corroborate well established results concerning the conditions under which each one of these methods is expected to perform best while providing several novel insights. PMID:25289666

Computation of Propagation Speed and Reflection of Axially Symmetric Waves in Composite Cylinders, with Application to Impedance Tube and Calibrator.

DTIC Science & Technology

1982-08-25

where w is the angular frequency and k the wave number; the phase speed c is related by W - kc. Because of the geometry, it is assumed that the field...PSA Phase of sample PST Phase of standard STEP Step size TEMP Temperature (C) THICK Length of sample (cm) VSA Voltage of sample VST Voltage of standard...VSA/ VST 0)027 W=4001.*RS69+.8*(TEMP-24 .0)- .037*( TEMFP-24 .0) **2.*0 00o29 E=(PSA-PST)/57.2958 0030 G=E-O 0031 IF (ABS(G)-2*3.14159 *LE. 0) GO TO 50

Online clustering algorithms for radar emitter classification.

PubMed

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

2005-08-01

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

A fixed-memory moving, expanding window for obtaining scatter corrections in X-ray CT and other stochastic averages

NASA Astrophysics Data System (ADS)

Levine, Zachary H.; Pintar, Adam L.

2015-11-01

A simple algorithm for averaging a stochastic sequence of 1D arrays in a moving, expanding window is provided. The samples are grouped in bins which increase exponentially in size so that a constant fraction of the samples is retained at any point in the sequence. The algorithm is shown to have particular relevance for a class of Monte Carlo sampling problems which includes one characteristic of iterative reconstruction in computed tomography. The code is available in the CPC program library in both Fortran 95 and C and is also available in R through CRAN.

Error in the Sampling Area of an Optical Disdrometer: Consequences in Computing Rain Variables

PubMed Central

Fraile, R.; Castro, A.; Fernández-Raga, M.; Palencia, C.; Calvo, A. I.

2013-01-01

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. The Z-R relationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006. PMID:23844393

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

PubMed

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

2010-02-01

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

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

PubMed Central

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

2014-01-01

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

A comparative appraisal of two equivalence tests for multiple standardized effects.

PubMed

Shieh, Gwowen

2016-04-01

Equivalence testing is recommended as a better alternative to the traditional difference-based methods for demonstrating the comparability of two or more treatment effects. Although equivalent tests of two groups are widely discussed, the natural extensions for assessing equivalence between several groups have not been well examined. This article provides a detailed and schematic comparison of the ANOVA F and the studentized range tests for evaluating the comparability of several standardized effects. Power and sample size appraisals of the two grossly distinct approaches are conducted in terms of a constraint on the range of the standardized means when the standard deviation of the standardized means is fixed. Although neither method is uniformly more powerful, the studentized range test has a clear advantage in sample size requirements necessary to achieve a given power when the underlying effect configurations are close to the priori minimum difference for determining equivalence. For actual application of equivalence tests and advance planning of equivalence studies, both SAS and R computer codes are available as supplementary files to implement the calculations of critical values, p-values, power levels, and sample sizes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Sampling and Visualizing Creases with Scale-Space Particles

PubMed Central

Kindlmann, Gordon L.; Estépar, Raúl San José; Smith, Stephen M.; Westin, Carl-Fredrik

2010-01-01

Particle systems have gained importance as a methodology for sampling implicit surfaces and segmented objects to improve mesh generation and shape analysis. We propose that particle systems have a significantly more general role in sampling structure from unsegmented data. We describe a particle system that computes samplings of crease features (i.e. ridges and valleys, as lines or surfaces) that effectively represent many anatomical structures in scanned medical data. Because structure naturally exists at a range of sizes relative to the image resolution, computer vision has developed the theory of scale-space, which considers an n-D image as an (n + 1)-D stack of images at different blurring levels. Our scale-space particles move through continuous four-dimensional scale-space according to spatial constraints imposed by the crease features, a particle-image energy that draws particles towards scales of maximal feature strength, and an inter-particle energy that controls sampling density in space and scale. To make scale-space practical for large three-dimensional data, we present a spline-based interpolation across scale from a small number of pre-computed blurrings at optimally selected scales. The configuration of the particle system is visualized with tensor glyphs that display information about the local Hessian of the image, and the scale of the particle. We use scale-space particles to sample the complex three-dimensional branching structure of airways in lung CT, and the major white matter structures in brain DTI. PMID:19834216

Exactly solvable random graph ensemble with extensively many short cycles

NASA Astrophysics Data System (ADS)

Aguirre López, Fabián; Barucca, Paolo; Fekom, Mathilde; Coolen, Anthony C. C.

2018-02-01

We introduce and analyse ensembles of 2-regular random graphs with a tuneable distribution of short cycles. The phenomenology of these graphs depends critically on the scaling of the ensembles’ control parameters relative to the number of nodes. A phase diagram is presented, showing a second order phase transition from a connected to a disconnected phase. We study both the canonical formulation, where the size is large but fixed, and the grand canonical formulation, where the size is sampled from a discrete distribution, and show their equivalence in the thermodynamical limit. We also compute analytically the spectral density, which consists of a discrete set of isolated eigenvalues, representing short cycles, and a continuous part, representing cycles of diverging size.

Suspended sediments from upstream tributaries as the source of downstream river sites

NASA Astrophysics Data System (ADS)

Haddadchi, Arman; Olley, Jon

2014-05-01

Understanding the efficiency with which sediment eroded from different sources is transported to the catchment outlet is a key knowledge gap that is critical to our ability to accurately target and prioritise management actions to reduce sediment delivery. Sediment fingerprinting has proven to be an efficient approach to determine the sources of sediment. This study examines the suspended sediment sources from Emu Creek catchment, south eastern Queensland, Australia. In addition to collect suspended sediments from different sites of the streams after the confluence of tributaries and outlet of the catchment, time integrated suspended samples from upper tributaries were used as the source of sediment, instead of using hillslope and channel bank samples. Totally, 35 time-integrated samplers were used to compute the contribution of suspended sediments from different upstream waterways to the downstream sediment sites. Three size fractions of materials including fine sand (63-210 μm), silt (10-63 μm) and fine silt and clay (<10 μm) were used to find the effect of particle size on the contribution of upper sediments as the sources of sediment after river confluences. And then samples were analysed by ICP-MS and -OES to find 41 sediment fingerprints. According to the results of Student's T-distribution mixing model, small creeks in the middle and lower part of the catchment were major source in different size fractions, especially in silt (10-63 μm) samples. Gowrie Creek as covers southern-upstream part of the catchment was a major contributor at the outlet of the catchment in finest size fraction (<10 μm) Large differences between the contributions of suspended sediments from upper tributaries in different size fractions necessitate the selection of appropriate size fraction on sediment tracing in the catchment and also major effect of particle size on the movement and deposition of sediments.

Computer-Aided Diagnosis Of Leukemic Blood Cells

NASA Astrophysics Data System (ADS)

Gunter, U.; Harms, H.; Haucke, M.; Aus, H. M.; ter Meulen, V.

1982-11-01

In a first clinical test, computer programs are being used to diagnose leukemias. The data collected include blood samples from patients suffering from acute myelomonocytic-, acute monocytic- and acute promyelocytic, myeloblastic, prolymphocytic, chronic lymphocytic leukemias and leukemic transformed immunocytoma. The proper differentiation of the leukemic cells is essential because the therapy depends on the type of leukemia. The algorithms analyse the fine chromatin texture and distribution in the nuclei as well as size and shape parameters from the cells and nuclei. Cells with similar nuclei from different leukemias can be distinguished from each other by analyzing the cell cytoplasm images. Recognition of these subtle differences in the cells require an image sampling rate of 15-30 pixel/micron. The results for the entire data set correlate directly to established hematological parameters and support the previously published initial training set .

Computationally efficient algorithm for Gaussian Process regression in case of structured samples

NASA Astrophysics Data System (ADS)

Belyaev, M.; Burnaev, E.; Kapushev, Y.

2016-04-01

Surrogate modeling is widely used in many engineering problems. Data sets often have Cartesian product structure (for instance factorial design of experiments with missing points). In such case the size of the data set can be very large. Therefore, one of the most popular algorithms for approximation-Gaussian Process regression-can be hardly applied due to its computational complexity. In this paper a computationally efficient approach for constructing Gaussian Process regression in case of data sets with Cartesian product structure is presented. Efficiency is achieved by using a special structure of the data set and operations with tensors. Proposed algorithm has low computational as well as memory complexity compared to existing algorithms. In this work we also introduce a regularization procedure allowing to take into account anisotropy of the data set and avoid degeneracy of regression model.

Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

PubMed

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2014-07-01

Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of Microphysical Models in the National Combustion Code (NCC) for Aircraft Particulate Emissions: Particle Loss in Sampling Lines

NASA Technical Reports Server (NTRS)

Wey, Thomas; Liu, Nan-Suey

2008-01-01

This paper at first describes the fluid network approach recently implemented into the National Combustion Code (NCC) for the simulation of transport of aerosols (volatile particles and soot) in the particulate sampling systems. This network-based approach complements the other two approaches already in the NCC, namely, the lower-order temporal approach and the CFD-based approach. The accuracy and the computational costs of these three approaches are then investigated in terms of their application to the prediction of particle losses through sample transmission and distribution lines. Their predictive capabilities are assessed by comparing the computed results with the experimental data. The present work will help establish standard methodologies for measuring the size and concentration of particles in high-temperature, high-velocity jet engine exhaust. Furthermore, the present work also represents the first step of a long term effort of validating physics-based tools for the prediction of aircraft particulate emissions.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

PubMed

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

The Use of a Binary Composite Endpoint and Sample Size Requirement: Influence of Endpoints Overlap.

PubMed

Marsal, Josep-Ramon; Ferreira-González, Ignacio; Bertran, Sandra; Ribera, Aida; Permanyer-Miralda, Gaietà; García-Dorado, David; Gómez, Guadalupe

2017-05-01

Although composite endpoints (CE) are common in clinical trials, the impact of the relationship between the components of a binary CE on the sample size requirement (SSR) has not been addressed. We performed a computational study considering 2 treatments and a CE with 2 components: the relevant endpoint (RE) and the additional endpoint (AE). We assessed the strength of the components' interrelation by the degree of relative overlap between them, which was stratified into 5 groups. Within each stratum, SSR was computed for multiple scenarios by varying the events proportion and the effect of the therapy. A lower SSR using CE was defined as the best scenario for using the CE. In 25 of 66 scenarios the degree of relative overlap determined the benefit of using CE instead of the RE. Adding an AE with greater effect than the RE leads to lower SSR using the CE regardless of the AE proportion and the relative overlap. The influence of overlapping decreases when the effect on RE increases. Adding an AE with lower effect than the RE constitutes the most uncertain situation. In summary, the interrelationship between CE components, assessed by the relative overlap, can help to define the SSR in specific situations and it should be considered for SSR computation. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Elderly Americans and the Internet: E-Mail, TV News, Information and Entertainment Websites

ERIC Educational Resources Information Center

Hilt, Michael L.; Lipschultz, Jeremy H.

2004-01-01

Older Americans, like other groups, vary in their use of the Internet. The participants for this study-elderly computer users from a Midwestern mid-size sample-used e-mail and considered it the most important Internet function. It was common for them to use e-mail with family and friends on a regular, if not daily, basis. When this group of older…

Elderly Americans and the Internet: E-Mail, TV News, Information and Entertainment Websites

ERIC Educational Resources Information Center

Hilt, Michael L.; Lipschultz, Jeremy H.

2004-01-01

Older Americans, like other groups, vary in their use of the Internet. The participants for this study--elderly computer users from a Midwestern mid-size sample--used e-mail and considered it the most important Internet function. It was common for them to use e-mail with family and friends on a regular, if not daily, basis. When this group of…

EXACT DISTRIBUTIONS OF INTRACLASS CORRELATION AND CRONBACH'S ALPHA WITH GAUSSIAN DATA AND GENERAL COVARIANCE.

PubMed

Kistner, Emily O; Muller, Keith E

2004-09-01

Intraclass correlation and Cronbach's alpha are widely used to describe reliability of tests and measurements. Even with Gaussian data, exact distributions are known only for compound symmetric covariance (equal variances and equal correlations). Recently, large sample Gaussian approximations were derived for the distribution functions. New exact results allow calculating the exact distribution function and other properties of intraclass correlation and Cronbach's alpha, for Gaussian data with any covariance pattern, not just compound symmetry. Probabilities are computed in terms of the distribution function of a weighted sum of independent chi-square random variables. New F approximations for the distribution functions of intraclass correlation and Cronbach's alpha are much simpler and faster to compute than the exact forms. Assuming the covariance matrix is known, the approximations typically provide sufficient accuracy, even with as few as ten observations. Either the exact or approximate distributions may be used to create confidence intervals around an estimate of reliability. Monte Carlo simulations led to a number of conclusions. Correctly assuming that the covariance matrix is compound symmetric leads to accurate confidence intervals, as was expected from previously known results. However, assuming and estimating a general covariance matrix produces somewhat optimistically narrow confidence intervals with 10 observations. Increasing sample size to 100 gives essentially unbiased coverage. Incorrectly assuming compound symmetry leads to pessimistically large confidence intervals, with pessimism increasing with sample size. In contrast, incorrectly assuming general covariance introduces only a modest optimistic bias in small samples. Hence the new methods seem preferable for creating confidence intervals, except when compound symmetry definitely holds.

Distance geometry protocol to generate conformations of natural products to structurally interpret ion mobility-mass spectrometry collision cross sections.

PubMed

Stow, Sarah M; Goodwin, Cody R; Kliman, Michal; Bachmann, Brian O; McLean, John A; Lybrand, Terry P

2014-12-04

Ion mobility-mass spectrometry (IM-MS) allows the separation of ionized molecules based on their charge-to-surface area (IM) and mass-to-charge ratio (MS), respectively. The IM drift time data that is obtained is used to calculate the ion-neutral collision cross section (CCS) of the ionized molecule with the neutral drift gas, which is directly related to the ion conformation and hence molecular size and shape. Studying the conformational landscape of these ionized molecules computationally provides interpretation to delineate the potential structures that these CCS values could represent, or conversely, structural motifs not consistent with the IM data. A challenge in the IM-MS community is the ability to rapidly compute conformations to interpret natural product data, a class of molecules exhibiting a broad range of biological activity. The diversity of biological activity is, in part, related to the unique structural characteristics often observed for natural products. Contemporary approaches to structurally interpret IM-MS data for peptides and proteins typically utilize molecular dynamics (MD) simulations to sample conformational space. However, MD calculations are computationally expensive, they require a force field that accurately describes the molecule of interest, and there is no simple metric that indicates when sufficient conformational sampling has been achieved. Distance geometry is a computationally inexpensive approach that creates conformations based on sampling different pairwise distances between the atoms within the molecule and therefore does not require a force field. Progressively larger distance bounds can be used in distance geometry calculations, providing in principle a strategy to assess when all plausible conformations have been sampled. Our results suggest that distance geometry is a computationally efficient and potentially superior strategy for conformational analysis of natural products to interpret gas-phase CCS data.

Distance Geometry Protocol to Generate Conformations of Natural Products to Structurally Interpret Ion Mobility-Mass Spectrometry Collision Cross Sections

PubMed Central

2015-01-01

Ion mobility-mass spectrometry (IM-MS) allows the separation of ionized molecules based on their charge-to-surface area (IM) and mass-to-charge ratio (MS), respectively. The IM drift time data that is obtained is used to calculate the ion-neutral collision cross section (CCS) of the ionized molecule with the neutral drift gas, which is directly related to the ion conformation and hence molecular size and shape. Studying the conformational landscape of these ionized molecules computationally provides interpretation to delineate the potential structures that these CCS values could represent, or conversely, structural motifs not consistent with the IM data. A challenge in the IM-MS community is the ability to rapidly compute conformations to interpret natural product data, a class of molecules exhibiting a broad range of biological activity. The diversity of biological activity is, in part, related to the unique structural characteristics often observed for natural products. Contemporary approaches to structurally interpret IM-MS data for peptides and proteins typically utilize molecular dynamics (MD) simulations to sample conformational space. However, MD calculations are computationally expensive, they require a force field that accurately describes the molecule of interest, and there is no simple metric that indicates when sufficient conformational sampling has been achieved. Distance geometry is a computationally inexpensive approach that creates conformations based on sampling different pairwise distances between the atoms within the molecule and therefore does not require a force field. Progressively larger distance bounds can be used in distance geometry calculations, providing in principle a strategy to assess when all plausible conformations have been sampled. Our results suggest that distance geometry is a computationally efficient and potentially superior strategy for conformational analysis of natural products to interpret gas-phase CCS data. PMID:25360896

Sample size for positive and negative predictive value in diagnostic research using case–control designs

PubMed Central

Steinberg, David M.; Fine, Jason; Chappell, Rick

2009-01-01

Important properties of diagnostic methods are their sensitivity, specificity, and positive and negative predictive values (PPV and NPV). These methods are typically assessed via case–control samples, which include one cohort of cases known to have the disease and a second control cohort of disease-free subjects. Such studies give direct estimates of sensitivity and specificity but only indirect estimates of PPV and NPV, which also depend on the disease prevalence in the tested population. The motivating example arises in assay testing, where usage is contemplated in populations with known prevalences. Further instances include biomarker development, where subjects are selected from a population with known prevalence and assessment of PPV and NPV is crucial, and the assessment of diagnostic imaging procedures for rare diseases, where case–control studies may be the only feasible designs. We develop formulas for optimal allocation of the sample between the case and control cohorts and for computing sample size when the goal of the study is to prove that the test procedure exceeds pre-stated bounds for PPV and/or NPV. Surprisingly, the optimal sampling schemes for many purposes are highly unbalanced, even when information is desired on both PPV and NPV. PMID:18556677

Testing of typical spacecraft materials in a simulated substorm environment

NASA Technical Reports Server (NTRS)

Stevens, N. J.; Berkopec, F. D.; Staskus, J. V.; Blech, R. A.; Narciso, S. J.

1977-01-01

The test specimens were spacecraft paints, silvered Teflon, thermal blankets, and solar array segments. The samples, ranging in size from 300 to 1000 sq cm were exposed to monoenergetic electron energies from 2 to 20 keV at a current density of 1 NA/sq cm. The samples generally behaved as capacitors with strong voltage gradient at their edges. The charging characteristics of the silvered Teflon, Kapton, and solar cell covers were controlled by the secondary emission characteristics. Insulators that did not discharge were the spacecraft paints and the quartz fiber cloth thermal blanket sample. All other samples did experience discharges when the surface voltage reached -8 to -16kV. The discharges were photographed. The breakdown voltage for each sample was determined and the average energy lost in the discharge was computed.

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Numerical sedimentation particle-size analysis using the Discrete Element Method

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

Suspended sediment transport under estuarine tidal channel conditions

USGS Publications Warehouse

Sternberg, R.W.; Kranck, K.; Cacchione, D.A.; Drake, D.E.

1988-01-01

A modified version of the GEOPROBE tripod has been used to monitor flow conditions and suspended sediment distribution in the bottom boundary layer of a tidal channel within San Francisco Bay, California. Measurements were made every 15 minutes over three successive tidal cycles. They included mean velocity profiles from four electromagnetic current meters within 1 m of the seabed; mean suspended sediment concentration profiles from seven miniature nephelometers operated within 1 m of the seabed; near-bottom pressure fluctuations; vertical temperature gradient; and bottom photographs. Additionally, suspended sediment was sampled from four levels within 1 m of the seabed three times during each successive flood and ebb cycle. While the instrument was deployed, STD-nephelometer measurements were made throughout the water column, water samples were collected each 1-2 hours, and bottom sediment was sampled at the deployment site. From these measurements, estimates were made of particle settling velocity (ws) from size distributions of the suspended sediment, friction velocity (U*) from the velocity profiles, and reference concentration (Ca) was measured at z = 20 cm. These parameters were used in the suspended sediment distribution equations to evaluate their ability to predict the observed suspended sediment profiles. Three suspended sediment particle conditions were evaluated: (1) individual particle size in the 4-11 ?? (62.5-0.5 ??m) range with the reference concentration Ca at z = 20 cm (C??), (2) individual particle size in the 4-6 ?? size range, flocs representing the 7-11 ?? size range with the reference concentration Ca at z = 20 cm (Cf), and (3) individual particle size in the 4-6 ?? size range, flocs representing the 7-11 ?? size range with the reference concentration predicted as a function of the bed sediment size distribution and the square of the excess shear stress. In addition, computations of particle flux were made in order to show vertical variations in horizontal mass flux for varying flow conditions. ?? 1988.

An empirical determination of the minimum number of measurements needed to estimate the mean random vitrinite reflectance of disseminated organic matter

USGS Publications Warehouse

Barker, C.E.; Pawlewicz, M.J.

1993-01-01

In coal samples, published recommendations based on statistical methods suggest 100 measurements are needed to estimate the mean random vitrinite reflectance (Rv-r) to within ??2%. Our survey of published thermal maturation studies indicates that those using dispersed organic matter (DOM) mostly have an objective of acquiring 50 reflectance measurements. This smaller objective size in DOM versus that for coal samples poses a statistical contradiction because the standard deviations of DOM reflectance distributions are typically larger indicating a greater sample size is needed to accurately estimate Rv-r in DOM. However, in studies of thermal maturation using DOM, even 50 measurements can be an unrealistic requirement given the small amount of vitrinite often found in such samples. Furthermore, there is generally a reduced need for assuring precision like that needed for coal applications. Therefore, a key question in thermal maturation studies using DOM is how many measurements of Rv-r are needed to adequately estimate the mean. Our empirical approach to this problem is to compute the reflectance distribution statistics: mean, standard deviation, skewness, and kurtosis in increments of 10 measurements. This study compares these intermediate computations of Rv-r statistics with a final one computed using all measurements for that sample. Vitrinite reflectance was measured on mudstone and sandstone samples taken from borehole M-25 in the Cerro Prieto, Mexico geothermal system which was selected because the rocks have a wide range of thermal maturation and a comparable humic DOM with depth. The results of this study suggest that after only 20-30 measurements the mean Rv-r is generally known to within 5% and always to within 12% of the mean Rv-r calculated using all of the measured particles. Thus, even in the worst case, the precision after measuring only 20-30 particles is in good agreement with the general precision of one decimal place recommended for mean Rv-r measurements on DOM. The coefficient of variation (V = standard deviation/mean) is proposed as a statistic to indicate the reliability of the mean Rv-r estimates made at n ??? 20. This preliminary study suggests a V 0.2 suggests an unreliable mean in such small samples. ?? 1993.

Bone Histology and Primary Growth Rates in Hatchling Titanosaurs from Madagascar: New Insights from Micro-Computed Tomography

NASA Astrophysics Data System (ADS)

Bagley, B. C.; Whitney, M.; Rogers, K. C.

2012-12-01

Sauropods are the largest known terrestrial vertebrates and exhibit a greater ontogenetic variation in body size than any other taxon. More than 120 species of sauropods are known from the Jurassic and Cretaceous, and a wealth of specimens documents their enormous adult body sizes. Juvenile sauropods, in contrast, are rare. Though titanosaur eggs containing embryos have been recovered, to date the smallest known post-hatching juveniles are only a little less than half of known adult size, and details of the earliest stages of sauropod ontogeny remain particularly poorly understood. Here we report on two partial skeletons of hatchling Rapetosaurus krausei, a titanosaur from the Upper Cretaceous Maevarano Formation of Madagascar, and provide important new data on primary early stage growth rates in sauropods. The two partial skeletons come from different localities in the Anembalemba Member of the Maevarano Formation. There is no duplication of elements for either specimen. Comparison of greatest length ratios for appendicular elements to those of a complete sub-adult Rapetosaurus confirms that there are only two individuals present, that there is no significant allometry in Rapetosaurus postcranial ontogeny, and that each individual is less than 15% adult size. The smaller specimen includes a sacral neural arch, three caudal centra, three caudal neural arches, left pubis, right femur (maximum length [ml] = 19.3 cm), tibia (ml = 12.7 cm), and metacarpal III, left and right fibulae, humeri, and metatarsal I, and a phalanx. The larger specimen includes a caudal centrum and neural arch, right metacarpal I, right tibia (ml = 17.9 cm), and left metacarpal IV. In order to non-destructively sample these exceptional Rapetosaurus juvenile elements, we employed micro-computed tomography to garner bone histology data. The micro-computed tomography was carried out using an X5000 high-resolution microfocus X-ray CT system located in the Department of Earth Sciences, University of Minnesota. The microfocus head has a minimum focal spot size of < 6 microns and the detector has a pixel pitch of 74.8 μm. Machine parameters (e.g. voltage, current, tube to detector distance) vary based on sample size and desired magnification. For this study 70-100 kV (260-370 μA) was sufficient to penetrate the samples and obtain good contrast. We were able to achieve an effective pixel pitch of 36-48 μm for the larger samples and 14-28 μm for sub-volumes. 2-D radiographs were collected and these data were reconstructed to produce a 3-D volume for visual analysis, and slices of the 3-D volume for quantitative analysis. Our results indicate that primary bone growth in Rapetosaurus is highly vascularized woven and fibrolamellar bone. However, even in these very small juvenile individuals, endosteal remodeling is common at the mid-diaphysis and extends in some areas into the mid-cortex. The presence of a single line of arrested growth is recorded in each individual. These results are surprising given the small size of the elements, and support the hypothesis that intensive remodeling observed in the bones of older juvenile Rapetosaurus may be dictated, at least in part, by resource limitations during periods of drought/ecological stress recorded in the Maevarano Formation of Madagascar.

Suspended sediment transport in an estuarine tidal channel within San Francisco Bay, California

USGS Publications Warehouse

Sternberg, R.W.; Cacchione, D.A.; Drake, D.E.; Kranck, K.

1986-01-01

Size distributions of the suspended sediment samples, estimates of particle settling velocity (??s), friction velocity (U*), and reference concentration (Ca) at z = 20 cm were used in the suspended sediment distribution equations to evaluate their ability to predict the observed suspended sediment profiles. Three suspended sediment particle conditions were evaluated: (1) individual particle sizes in the 4-11 ?? (62.5-0.5 ??m) size range with the reference concentration Ca at z = 20 cm (C??); (2) individual particle sizes in the 4-6 ?? size range, flocs representing the 7-11 ?? size range with the reference concentration Ca at z = 20 cm (Cf); and (3) individual particle sizes in the 4-6 ?? size range, flocs representing the 7-11 ?? size range with the reference concentration predicted as a function of the bed sediment size distribution and the square of the excess shear stress. An analysis was also carried out on the sensitivity of the suspended sediment distribution equation to deviations in the primary variables ??s, U*, and Ca. In addition, computations of mass flux were made in order to show vertical variations in mass flux for varying flow conditions. ?? 1986.

Extreme Mean and Its Applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.

1979-01-01

Extreme value statistics obtained from normally distributed data are considered. An extreme mean is defined as the mean of p-th probability truncated normal distribution. An unbiased estimate of this extreme mean and its large sample distribution are derived. The distribution of this estimate even for very large samples is found to be nonnormal. Further, as the sample size increases, the variance of the unbiased estimate converges to the Cramer-Rao lower bound. The computer program used to obtain the density and distribution functions of the standardized unbiased estimate, and the confidence intervals of the extreme mean for any data are included for ready application. An example is included to demonstrate the usefulness of extreme mean application.

Classical verification of quantum circuits containing few basis changes

NASA Astrophysics Data System (ADS)

Demarie, Tommaso F.; Ouyang, Yingkai; Fitzsimons, Joseph F.

2018-04-01

We consider the task of verifying the correctness of quantum computation for a restricted class of circuits which contain at most two basis changes. This contains circuits giving rise to the second level of the Fourier hierarchy, the lowest level for which there is an established quantum advantage. We show that when the circuit has an outcome with probability at least the inverse of some polynomial in the circuit size, the outcome can be checked in polynomial time with bounded error by a completely classical verifier. This verification procedure is based on random sampling of computational paths and is only possible given knowledge of the likely outcome.

Decomposition and model selection for large contingency tables.

PubMed

Dahinden, Corinne; Kalisch, Markus; Bühlmann, Peter

2010-04-01

Large contingency tables summarizing categorical variables arise in many areas. One example is in biology, where large numbers of biomarkers are cross-tabulated according to their discrete expression level. Interactions of the variables are of great interest and are generally studied with log-linear models. The structure of a log-linear model can be visually represented by a graph from which the conditional independence structure can then be easily read off. However, since the number of parameters in a saturated model grows exponentially in the number of variables, this generally comes with a heavy computational burden. Even if we restrict ourselves to models of lower-order interactions or other sparse structures, we are faced with the problem of a large number of cells which play the role of sample size. This is in sharp contrast to high-dimensional regression or classification procedures because, in addition to a high-dimensional parameter, we also have to deal with the analogue of a huge sample size. Furthermore, high-dimensional tables naturally feature a large number of sampling zeros which often leads to the nonexistence of the maximum likelihood estimate. We therefore present a decomposition approach, where we first divide the problem into several lower-dimensional problems and then combine these to form a global solution. Our methodology is computationally feasible for log-linear interaction models with many categorical variables each or some of them having many levels. We demonstrate the proposed method on simulated data and apply it to a bio-medical problem in cancer research.

Adaptive Annealed Importance Sampling for Multimodal Posterior Exploration and Model Selection with Application to Extrasolar Planet Detection

NASA Astrophysics Data System (ADS)

Liu, Bin

2014-07-01

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior. To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

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

Chacko, M; Aldoohan, S

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended undermore » simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.« less

Jitter Correction

NASA Technical Reports Server (NTRS)

Waegell, Mordecai J.; Palacios, David M.

2011-01-01

Jitter_Correct.m is a MATLAB function that automatically measures and corrects inter-frame jitter in an image sequence to a user-specified precision. In addition, the algorithm dynamically adjusts the image sample size to increase the accuracy of the measurement. The Jitter_Correct.m function takes an image sequence with unknown frame-to-frame jitter and computes the translations of each frame (column and row, in pixels) relative to a chosen reference frame with sub-pixel accuracy. The translations are measured using a Cross Correlation Fourier transformation method in which the relative phase of the two transformed images is fit to a plane. The measured translations are then used to correct the inter-frame jitter of the image sequence. The function also dynamically expands the image sample size over which the cross-correlation is measured to increase the accuracy of the measurement. This increases the robustness of the measurement to variable magnitudes of inter-frame jitter

Parameter recovery, bias and standard errors in the linear ballistic accumulator model.

PubMed

Visser, Ingmar; Poessé, Rens

2017-05-01

The linear ballistic accumulator (LBA) model (Brown & Heathcote, , Cogn. Psychol., 57, 153) is increasingly popular in modelling response times from experimental data. An R package, glba, has been developed to fit the LBA model using maximum likelihood estimation which is validated by means of a parameter recovery study. At sufficient sample sizes parameter recovery is good, whereas at smaller sample sizes there can be large bias in parameters. In a second simulation study, two methods for computing parameter standard errors are compared. The Hessian-based method is found to be adequate and is (much) faster than the alternative bootstrap method. The use of parameter standard errors in model selection and inference is illustrated in an example using data from an implicit learning experiment (Visser et al., , Mem. Cogn., 35, 1502). It is shown that typical implicit learning effects are captured by different parameters of the LBA model. © 2017 The British Psychological Society.

A random-sum Wilcoxon statistic and its application to analysis of ROC and LROC data.

PubMed

Tang, Liansheng Larry; Balakrishnan, N

2011-01-01

The Wilcoxon-Mann-Whitney statistic is commonly used for a distribution-free comparison of two groups. One requirement for its use is that the sample sizes of the two groups are fixed. This is violated in some of the applications such as medical imaging studies and diagnostic marker studies; in the former, the violation occurs since the number of correctly localized abnormal images is random, while in the latter the violation is due to some subjects not having observable measurements. For this reason, we propose here a random-sum Wilcoxon statistic for comparing two groups in the presence of ties, and derive its variance as well as its asymptotic distribution for large sample sizes. The proposed statistic includes the regular Wilcoxon rank-sum statistic. Finally, we apply the proposed statistic for summarizing location response operating characteristic data from a liver computed tomography study, and also for summarizing diagnostic accuracy of biomarker data.

Multiple defocused coherent diffraction imaging: method for simultaneously reconstructing objects and probe using X-ray free-electron lasers.

PubMed

Hirose, Makoto; Shimomura, Kei; Suzuki, Akihiro; Burdet, Nicolas; Takahashi, Yukio

2016-05-30

The sample size must be less than the diffraction-limited focal spot size of the incident beam in single-shot coherent X-ray diffraction imaging (CXDI) based on a diffract-before-destruction scheme using X-ray free electron lasers (XFELs). This is currently a major limitation preventing its wider applications. We here propose multiple defocused CXDI, in which isolated objects are sequentially illuminated with a divergent beam larger than the objects and the coherent diffraction pattern of each object is recorded. This method can simultaneously reconstruct both objects and a probe from the coherent X-ray diffraction patterns without any a priori knowledge. We performed a computer simulation of the prposed method and then successfully demonstrated it in a proof-of-principle experiment at SPring-8. The prposed method allows us to not only observe broad samples but also characterize focused XFEL beams.

Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach

NASA Astrophysics Data System (ADS)

Lo, Min-Tzu; Lee, Wen-Chung

2014-05-01

Many risk factors/interventions in epidemiologic/biomedical studies are of minuscule effects. To detect such weak associations, one needs a study with a very large sample size (the number of subjects, n). The n of a study can be increased but unfortunately only to an extent. Here, we propose a novel method which hinges on increasing sample size in a different direction-the total number of variables (p). We construct a p-based `multiple perturbation test', and conduct power calculations and computer simulations to show that it can achieve a very high power to detect weak associations when p can be made very large. As a demonstration, we apply the method to analyze a genome-wide association study on age-related macular degeneration and identify two novel genetic variants that are significantly associated with the disease. The p-based method may set a stage for a new paradigm of statistical tests.

Continuous-Variable Instantaneous Quantum Computing is Hard to Sample.

PubMed

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.

Fast calculation method for computer-generated cylindrical holograms.

PubMed

Yamaguchi, Takeshi; Fujii, Tomohiko; Yoshikawa, Hiroshi

2008-07-01

Since a general flat hologram has a limited viewable area, we usually cannot see the other side of a reconstructed object. There are some holograms that can solve this problem. A cylindrical hologram is well known to be viewable in 360 deg. Most cylindrical holograms are optical holograms, but there are few reports of computer-generated cylindrical holograms. The lack of computer-generated cylindrical holograms is because the spatial resolution of output devices is not great enough; therefore, we have to make a large hologram or use a small object to fulfill the sampling theorem. In addition, in calculating the large fringe, the calculation amount increases in proportion to the hologram size. Therefore, we propose what we believe to be a new calculation method for fast calculation. Then, we print these fringes with our prototype fringe printer. As a result, we obtain a good reconstructed image from a computer-generated cylindrical hologram.

Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms

PubMed Central

Rechner, Steffen; Berger, Annabell

2016-01-01

We present the software library marathon, which is designed to support the analysis of sampling algorithms that are based on the Markov-Chain Monte Carlo principle. The main application of this library is the computation of properties of so-called state graphs, which represent the structure of Markov chains. We demonstrate applications and the usefulness of marathon by investigating the quality of several bounding methods on four well-known Markov chains for sampling perfect matchings and bipartite graphs. In a set of experiments, we compute the total mixing time and several of its bounds for a large number of input instances. We find that the upper bound gained by the famous canonical path method is often several magnitudes larger than the total mixing time and deteriorates with growing input size. In contrast, the spectral bound is found to be a precise approximation of the total mixing time. PMID:26824442

Lead isotope data bank; 2,624 samples and analyses cited

USGS Publications Warehouse

Doe, Bruce R.

1976-01-01

The Lead Isotope Data Bank (LIDB) was initiated to facilitate plotting data. Therefore, the Bank reflects data most often used in plotting rather than comprises a comprehensive tabulation of lead isotope data. Up until now, plotting was done using card decks processed by computer with tapes plotted by a Gerber plotter and more recently a CRT using a batch mode. Lack of a uniform format for sample identification was not a great impediment. With increase in the size of the bank, hand sorting is becoming prohibitive and ·plans are underway to put the bank into a uniform format on DISK with a card backup so that it may be accessed by use of IRIS on the DECK 10 computer at the U.S.G.S. facility in Denver. Plots will be constructed on a CRT. Entry of the bank into the IRIS accessing program is scheduled for completion in FY 1976

A k-Vector Approach to Sampling, Interpolation, and Approximation

NASA Astrophysics Data System (ADS)

Mortari, Daniele; Rogers, Jonathan

2013-12-01

The k-vector search technique is a method designed to perform extremely fast range searching of large databases at computational cost independent of the size of the database. k-vector search algorithms have historically found application in satellite star-tracker navigation systems which index very large star catalogues repeatedly in the process of attitude estimation. Recently, the k-vector search algorithm has been applied to numerous other problem areas including non-uniform random variate sampling, interpolation of 1-D or 2-D tables, nonlinear function inversion, and solution of systems of nonlinear equations. This paper presents algorithms in which the k-vector search technique is used to solve each of these problems in a computationally-efficient manner. In instances where these tasks must be performed repeatedly on a static (or nearly-static) data set, the proposed k-vector-based algorithms offer an extremely fast solution technique that outperforms standard methods.

Water Oxidation Catalysis via Size-Selected Iridium Clusters

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

Halder, Avik; Liu, Cong; LIU, ZHUN

The detailed mechanism and efficacy of four electron electrochemical water oxidation depend critically upon the detailed atomic structure of each catalytic site, which are numerous and diverse in most metal oxides anodes. In order to limit the diversity of sites, arrays of discrete iridium clusters with identical metal atom number (Ir-2, Ir-4, or Ir-8) were deposited in submonolayer coverage on conductive oxide supports, and the electrochemical properties and activity of each was evaluated. Exceptional electroactivity for the oxygen evolving reaction (OER) was observed for all cluster samples in acidic electrolyte. Reproducible cluster-size-dependent trends in redox behavior were also resolved. First-principlesmore » computational models of the individual discrete-size clusters allow correlation of catalytic-site structure and multiplicity with redox behavior.« less

LASER BIOLOGY: Optomechanical tests of hydrated biological tissues subjected to laser shaping

NASA Astrophysics Data System (ADS)

Omel'chenko, A. I.; Sobol', E. N.

2008-03-01

The mechanical properties of a matrix are studied upon changing the size and shape of biological tissues during dehydration caused by weak laser-induced heating. The cartilage deformation, dehydration dynamics, and hydraulic conductivity are measured upon laser heating. The hydrated state and the shape of samples of separated fascias and cartilaginous tissues were controlled by using computer-aided processing of tissue images in polarised light.

Coronary CT angiography using 64 detector rows: methods and design of the multi-centre trial CORE-64.

PubMed

Miller, Julie M; Dewey, Marc; Vavere, Andrea L; Rochitte, Carlos E; Niinuma, Hiroyuki; Arbab-Zadeh, Armin; Paul, Narinder; Hoe, John; de Roos, Albert; Yoshioka, Kunihiro; Lemos, Pedro A; Bush, David E; Lardo, Albert C; Texter, John; Brinker, Jeffery; Cox, Christopher; Clouse, Melvin E; Lima, João A C

2009-04-01

Multislice computed tomography (MSCT) for the noninvasive detection of coronary artery stenoses is a promising candidate for widespread clinical application because of its non-invasive nature and high sensitivity and negative predictive value as found in several previous studies using 16 to 64 simultaneous detector rows. A multi-centre study of CT coronary angiography using 16 simultaneous detector rows has shown that 16-slice CT is limited by a high number of nondiagnostic cases and a high false-positive rate. A recent meta-analysis indicated a significant interaction between the size of the study sample and the diagnostic odds ratios suggestive of small study bias, highlighting the importance of evaluating MSCT using 64 simultaneous detector rows in a multi-centre approach with a larger sample size. In this manuscript we detail the objectives and methods of the prospective "CORE-64" trial ("Coronary Evaluation Using Multidetector Spiral Computed Tomography Angiography using 64 Detectors"). This multi-centre trial was unique in that it assessed the diagnostic performance of 64-slice CT coronary angiography in nine centres worldwide in comparison to conventional coronary angiography. In conclusion, the multi-centre, multi-institutional and multi-continental trial CORE-64 has great potential to ultimately assess the per-patient diagnostic performance of coronary CT angiography using 64 simultaneous detector rows.

Computation of fluid flow and pore-space properties estimation on micro-CT images of rock samples

NASA Astrophysics Data System (ADS)

Starnoni, M.; Pokrajac, D.; Neilson, J. E.

2017-09-01

Accurate determination of the petrophysical properties of rocks, namely REV, mean pore and grain size and absolute permeability, is essential for a broad range of engineering applications. Here, the petrophysical properties of rocks are calculated using an integrated approach comprising image processing, statistical correlation and numerical simulations. The Stokes equations of creeping flow for incompressible fluids are solved using the Finite-Volume SIMPLE algorithm. Simulations are then carried out on three-dimensional digital images obtained from micro-CT scanning of two rock formations: one sandstone and one carbonate. Permeability is predicted from the computed flow field using Darcy's law. It is shown that REV, REA and mean pore and grain size are effectively estimated using the two-point spatial correlation function. Homogeneity and anisotropy are also evaluated using the same statistical tools. A comparison of different absolute permeability estimates is also presented, revealing a good agreement between the numerical value and the experimentally determined one for the carbonate sample, but a large discrepancy for the sandstone. Finally, a new convergence criterion for the SIMPLE algorithm, and more generally for the family of pressure-correction methods, is presented. This criterion is based on satisfaction of bulk momentum balance, which makes it particularly useful for pore-scale modelling of reservoir rocks.

Density-Dependent Quantized Least Squares Support Vector Machine for Large Data Sets.

PubMed

Nan, Shengyu; Sun, Lei; Chen, Badong; Lin, Zhiping; Toh, Kar-Ann

2017-01-01

Based on the knowledge that input data distribution is important for learning, a data density-dependent quantization scheme (DQS) is proposed for sparse input data representation. The usefulness of the representation scheme is demonstrated by using it as a data preprocessing unit attached to the well-known least squares support vector machine (LS-SVM) for application on big data sets. Essentially, the proposed DQS adopts a single shrinkage threshold to obtain a simple quantization scheme, which adapts its outputs to input data density. With this quantization scheme, a large data set is quantized to a small subset where considerable sample size reduction is generally obtained. In particular, the sample size reduction can save significant computational cost when using the quantized subset for feature approximation via the Nyström method. Based on the quantized subset, the approximated features are incorporated into LS-SVM to develop a data density-dependent quantized LS-SVM (DQLS-SVM), where an analytic solution is obtained in the primal solution space. The developed DQLS-SVM is evaluated on synthetic and benchmark data with particular emphasis on large data sets. Extensive experimental results show that the learning machine incorporating DQS attains not only high computational efficiency but also good generalization performance.

Geometrical characterization of perlite-metal syntactic foam

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

Borovinšek, Matej, E-mail: matej.borovinsek@um.si

This paper introduces an improved method for the detailed geometrical characterization of perlite-metal syntactic foam. This novel metallic foam is created by infiltrating a packed bed of expanded perlite particles with liquid aluminium alloy. The geometry of the solidified metal is thus defined by the perlite particle shape, size and morphology. The method is based on a segmented micro-computed tomography data and allows for automated determination of the distributions of pore size, sphericity, orientation and location. The pore (i.e. particle) size distribution and pore orientation is determined by a multi-criteria k-nearest neighbour algorithm for pore identification. The results indicate amore » weak density gradient parallel to the casting direction and a slight preference of particle orientation perpendicular to the casting direction. - Highlights: •A new method for identification of pores in porous materials was developed. •It was applied on perlite-metal syntactic foam samples. •A porosity decrease in the axial direction of the samples was determined. •Pore shape analysis showed a high percentage of spherical pores. •Orientation analysis showed that more pores are oriented in the radial direction.« less

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

PubMed

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

2014-11-10

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

Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

NASA Astrophysics Data System (ADS)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

A Computationally-Efficient Inverse Approach to Probabilistic Strain-Based Damage Diagnosis

NASA Technical Reports Server (NTRS)

Warner, James E.; Hochhalter, Jacob D.; Leser, William P.; Leser, Patrick E.; Newman, John A

2016-01-01

This work presents a computationally-efficient inverse approach to probabilistic damage diagnosis. Given strain data at a limited number of measurement locations, Bayesian inference and Markov Chain Monte Carlo (MCMC) sampling are used to estimate probability distributions of the unknown location, size, and orientation of damage. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. The approach is experimentally validated on cracked test specimens where full field strains are determined using digital image correlation (DIC). Access to full field DIC data allows for testing of different hypothetical sensor arrangements, facilitating the study of strain-based diagnosis effectiveness as the distance between damage and measurement locations increases. The ability of the framework to effectively perform both probabilistic damage localization and characterization in cracked plates is demonstrated and the impact of measurement location on uncertainty in the predictions is shown. Furthermore, the analysis time to produce these predictions is orders of magnitude less than a baseline Bayesian approach with the FE method by utilizing surrogate modeling and effective numerical sampling approaches.

The Relationship Between Computer Experience and Computerized Cognitive Test Performance Among Older Adults

PubMed Central

2013-01-01

Objective. This study compared the relationship between computer experience and performance on computerized cognitive tests and a traditional paper-and-pencil cognitive test in a sample of older adults (N = 634). Method. Participants completed computer experience and computer attitudes questionnaires, three computerized cognitive tests (Useful Field of View (UFOV) Test, Road Sign Test, and Stroop task) and a paper-and-pencil cognitive measure (Trail Making Test). Multivariate analysis of covariance was used to examine differences in cognitive performance across the four measures between those with and without computer experience after adjusting for confounding variables. Results. Although computer experience had a significant main effect across all cognitive measures, the effect sizes were similar. After controlling for computer attitudes, the relationship between computer experience and UFOV was fully attenuated. Discussion. Findings suggest that computer experience is not uniquely related to performance on computerized cognitive measures compared with paper-and-pencil measures. Because the relationship between computer experience and UFOV was fully attenuated by computer attitudes, this may imply that motivational factors are more influential to UFOV performance than computer experience. Our findings support the hypothesis that computer use is related to cognitive performance, and this relationship is not stronger for computerized cognitive measures. Implications and directions for future research are provided. PMID:22929395

4D Imaging of Salt Precipitation during Evaporation from Saline Porous Media Influenced by the Particle Size Distribution

NASA Astrophysics Data System (ADS)

Norouzi Rad, M.; Shokri, N.

2014-12-01

Understanding the physics of water evaporation from saline porous media is important in many processes such as evaporation from porous media, vegetation, plant growth, biodiversity in soil, and durability of building materials. To investigate the effect of particle size distribution on the dynamics of salt precipitation in saline porous media during evaporation, we applied X-ray micro-tomography technique. Six samples of quartz sand with different grain size distributions were used in the present study enabling us to constrain the effects of particle and pore sizes on salt precipitation patterns and dynamics. The pore size distributions were computed using the pore-scale X-ray images. The packed beds were saturated with NaCl solution of 3 Molal and the X-ray imaging was continued for one day with temporal resolution of 30 min resulting in pore scale information about the evaporation and precipitation dynamics. Our results show more precipitation at the early stage of the evaporation in the case of sand with the larger particle size due to the presence of fewer evaporation sites at the surface. The presence of more preferential evaporation sites at the surface of finer sands significantly modified the patterns and thickness of the salt crust deposited on the surface such that a thinner salt crust was formed in the case of sand with smaller particle size covering larger area at the surface as opposed to the thicker patchy crusts in samples with larger particle sizes. Our results provide new insights regarding the physics of salt precipitation in porous media during evaporation.

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

PubMed

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

2014-04-01

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

System-size convergence of point defect properties: The case of the silicon vacancy

NASA Astrophysics Data System (ADS)

Corsetti, Fabiano; Mostofi, Arash A.

2011-07-01

We present a comprehensive study of the vacancy in bulk silicon in all its charge states from 2+ to 2-, using a supercell approach within plane-wave density-functional theory, and systematically quantify the various contributions to the well-known finite size errors associated with calculating formation energies and stable charge state transition levels of isolated defects with periodic boundary conditions. Furthermore, we find that transition levels converge faster with respect to supercell size when only the Γ-point is sampled in the Brillouin zone, as opposed to a dense k-point sampling. This arises from the fact that defect level at the Γ-point quickly converges to a fixed value which correctly describes the bonding at the defect center. Our calculated transition levels with 1000-atom supercells and Γ-point only sampling are in good agreement with available experimental results. We also demonstrate two simple and accurate approaches for calculating the valence band offsets that are required for computing formation energies of charged defects, one based on a potential averaging scheme and the other using maximally-localized Wannier functions (MLWFs). Finally, we show that MLWFs provide a clear description of the nature of the electronic bonding at the defect center that verifies the canonical Watkins model.

New Insights into the Composition and Texture of Lunar Regolith Using Ultrafast Automated Electron-Beam Analysis

NASA Technical Reports Server (NTRS)

Rickman, Doug; Wentworth, Susan J.; Schrader, Christian M.; Stoeser, Doug; Botha, Pieter WSK; Butcher, Alan R.; Horsch, Hanna E.; Benedictus, Aukje; Gottlieb, Paul; McKay, David

2008-01-01

Sieved grain mounts of Apollo 16 drive tube samples have been examined using QEMSCAN - an innovative electron beam technology. By combining multiple energy-dispersive X-ray detectors, fully automated control, and off-line image processing, to produce digital mineral maps of particles exposed on polished surfaces, the result is an unprecedented quantity of mineralogical and petrographic data, on a particle-by-particle basis. Experimental analysis of four size fractions (500-250 microns, 150-90 microns, 75-45 microns and < 20 microns), prepared from two samples (64002,374 and 64002,262), has produced a robust and uniform dataset which allows for the quantification of mineralogy; texture; particle shape, size and density; and the digital classification of distinct particle types in each measured sample. These preliminary data show that there is a decrease in plagioclase modal content and an opposing increase in glass modal content, with decreasing particle size. These findings, together with data on trace phases (metals, sulphides, phosphates, and oxides), provide not only new insights into the make-up of lunar regolith at the Apollo 16 landing site, but also key physical parameters which can be used to design lunar simulants, and compute Figures of Merit for each material produced.

Insensitivity to Flaws Leads to Damage Tolerance in Brittle Architected Meta-Materials

NASA Astrophysics Data System (ADS)

Montemayor, L. C.; Wong, W. H.; Zhang, Y.-W.; Greer, J. R.

2016-02-01

Cellular solids are instrumental in creating lightweight, strong, and damage-tolerant engineering materials. By extending feature size down to the nanoscale, we simultaneously exploit the architecture and material size effects to substantially enhance structural integrity of architected meta-materials. We discovered that hollow-tube alumina nanolattices with 3D kagome geometry that contained pre-fabricated flaws always failed at the same load as the pristine specimens when the ratio of notch length (a) to sample width (w) is no greater than 1/3, with no correlation between failure occurring at or away from the notch. Samples with (a/w) > 0.3, and notch length-to-unit cell size ratios of (a/l) > 5.2, failed at a lower peak loads because of the higher sample compliance when fewer unit cells span the intact region. Finite element simulations show that the failure is governed by purely tensile loading for (a/w) < 0.3 for the same (a/l); bending begins to play a significant role in failure as (a/w) increases. This experimental and computational work demonstrates that the discrete-continuum duality of architected structural meta-materials may give rise to their damage tolerance and insensitivity of failure to the presence of flaws even when made entirely of intrinsically brittle materials.

Computer measurement of particle sizes in electron microscope images

NASA Technical Reports Server (NTRS)

Hall, E. L.; Thompson, W. B.; Varsi, G.; Gauldin, R.

1976-01-01

Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.

Computer aided lung cancer diagnosis with deep learning algorithms

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Zheng, Bin; Qian, Wei

2016-03-01

Deep learning is considered as a popular and powerful method in pattern recognition and classification. However, there are not many deep structured applications used in medical imaging diagnosis area, because large dataset is not always available for medical images. In this study we tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database. The nodules on each computed tomography (CT) slice were segmented according to marks provided by the radiologists. After down sampling and rotating we acquired 174412 samples with 52 by 52 pixel each and the corresponding truth files. Three deep learning algorithms were designed and implemented, including Convolutional Neural Network (CNN), Deep Belief Networks (DBNs), Stacked Denoising Autoencoder (SDAE). To compare the performance of deep learning algorithms with traditional computer aided diagnosis (CADx) system, we designed a scheme with 28 image features and support vector machine. The accuracies of CNN, DBNs, and SDAE are 0.7976, 0.8119, and 0.7929, respectively; the accuracy of our designed traditional CADx is 0.7940, which is slightly lower than CNN and DBNs. We also noticed that the mislabeled nodules using DBNs are 4% larger than using traditional CADx, this might be resulting from down sampling process lost some size information of the nodules.

Molecular simulation of small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2012-11-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Challenges of Big Data Analysis.

PubMed

Fan, Jianqing; Han, Fang; Liu, Han

2014-06-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

Challenges of Big Data Analysis

PubMed Central

Fan, Jianqing; Han, Fang; Liu, Han

2014-01-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions. PMID:25419469

Sampling efficiency of modified 37-mm sampling cassettes using computational fluid dynamics.

PubMed

Anthony, T Renée; Sleeth, Darrah; Volckens, John

2016-01-01

In the U.S., most industrial hygiene practitioners continue to rely on the closed-face cassette (CFC) to assess worker exposures to hazardous dusts, primarily because ease of use, cost, and familiarity. However, mass concentrations measured with this classic sampler underestimate exposures to larger particles throughout the inhalable particulate mass (IPM) size range (up to aerodynamic diameters of 100 μm). To investigate whether the current 37-mm inlet cap can be redesigned to better meet the IPM sampling criterion, computational fluid dynamics (CFD) models were developed, and particle sampling efficiencies associated with various modifications to the CFC inlet cap were determined. Simulations of fluid flow (standard k-epsilon turbulent model) and particle transport (laminar trajectories, 1-116 μm) were conducted using sampling flow rates of 10 L min(-1) in slow moving air (0.2 m s(-1)) in the facing-the-wind orientation. Combinations of seven inlet shapes and three inlet diameters were evaluated as candidates to replace the current 37-mm inlet cap. For a given inlet geometry, differences in sampler efficiency between inlet diameters averaged less than 1% for particles through 100 μm, but the largest opening was found to increase the efficiency for the 116 μm particles by 14% for the flat inlet cap. A substantial reduction in sampler efficiency was identified for sampler inlets with side walls extending beyond the dimension of the external lip of the current 37-mm CFC. The inlet cap based on the 37-mm CFC dimensions with an expanded 15-mm entry provided the best agreement with facing-the-wind human aspiration efficiency. The sampler efficiency was increased with a flat entry or with a thin central lip adjacent to the new enlarged entry. This work provides a substantial body of sampling efficiency estimates as a function of particle size and inlet geometry for personal aerosol samplers.

A generalized threshold model for computing bed load grain size distribution

NASA Astrophysics Data System (ADS)

Recking, Alain

2016-12-01

For morphodynamic studies, it is important to compute not only the transported volumes of bed load, but also the size of the transported material. A few bed load equations compute fractional transport (i.e., both the volume and grain size distribution), but many equations compute only the bulk transport (a volume) with no consideration of the transported grain sizes. To fill this gap, a method is proposed to compute the bed load grain size distribution separately to the bed load flux. The method is called the Generalized Threshold Model (GTM), because it extends the flow competence method for threshold of motion of the largest transported grain size to the full bed surface grain size distribution. This was achieved by replacing dimensional diameters with their size indices in the standard hiding function, which offers a useful framework for computation, carried out for each indices considered in the range [1, 100]. New functions are also proposed to account for partial transport. The method is very simple to implement and is sufficiently flexible to be tested in many environments. In addition to being a good complement to standard bulk bed load equations, it could also serve as a framework to assist in analyzing the physics of bed load transport in future research.

PyRETIS: A well-done, medium-sized python library for rare events.

PubMed

Lervik, Anders; Riccardi, Enrico; van Erp, Titus S

2017-10-30

Transition path sampling techniques are becoming common approaches in the study of rare events at the molecular scale. More efficient methods, such as transition interface sampling (TIS) and replica exchange transition interface sampling (RETIS), allow the investigation of rare events, for example, chemical reactions and structural/morphological transitions, in a reasonable computational time. Here, we present PyRETIS, a Python library for performing TIS and RETIS simulations. PyRETIS directs molecular dynamics (MD) simulations in order to sample rare events with unbiased dynamics. PyRETIS is designed to be easily interfaced with any molecular simulation package and in the present release, it has been interfaced with GROMACS and CP2K, for classical and ab initio MD simulations, respectively. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identification of missing variants by combining multiple analytic pipelines.

PubMed

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

2018-04-16

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

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Design and testing of a shrouded probe for airborne aerosol sampling in a high velocity airstream

NASA Astrophysics Data System (ADS)

Cain, Stuart Arthur

1997-07-01

Tropospheric aerosols play an important role in many phenomena related to global climate and climate change and two important parameters, aerosol size distribution and concentration, have been the focus of a great deal of attention. To study these parameters it is necessary to obtain a representative sample of the ambient aerosol using an airborne aerosol sampling probe mounted on a suitably equipped aircraft. Recently, however, serious questions have been raised (Huebert et al., 1990; Baumgardner et al., 1991) concerning the current procedures and techniques used in airborne aerosol sampling. We believe that these questions can be answered by: (1) use of a shrouded aerosol sampling probe, (2) proper aerodynamic sampler design using numerical simulation techniques, (3) calculation of the sampler calibration curve to be used in determining free-stream aerosol properties from measurements made with the sampler and (4) wind tunnel tests to verify the design and investigate the performance of the sampler at small angles of attack (typical in airborne sampling applications due to wind gusts and aircraft fuel consumption). Our analysis is limited to the collection of insoluble particles representative of the global tropospheric 'background aerosol' (0.1-2.6 μm diameter) whose characteristics are least likely to be affected by the collection process. We begin with a survey of the most relevant problems associated with current airborne aerosol samplers and define the physical quantity that we wish to measure. This includes the derivation of a unique mathematical expression relating the free-stream aerosol size distribution to aerosol data obtained from the airborne measurements with the sampler. We follow with the presentation of the results of our application of Computational Fluid Dynamics (CFD) and Computational Particle Dynamics (CPD) to the design of a shrouded probe for airborne aerosol sampling of insoluble tropospheric particles in the size range 0.1 to 15 μm diameter at an altitude of 6069 m (20,000 ft) above sea level (asl). Our aircraft of choice is the National Center for Atmospheric Research (NCAR) EC-130 Geoscience Research aircraft whose cruising speed at a sampling altitude of 6069 m asl is 100 m/s. We calculate the aspiration efficiency of the sampler and estimate the transmission efficiency of the diffuser probe based on particle trajectory simulations. We conclude by presenting the results of a series of qualitative and quantitative wind tunnel tests of the airflow through a plexiglass prototype of the sampler to verify our numerical simulations and predict the performance of the sampler at angles of attack from 0o to 15o.

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

PubMed Central

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

2013-01-01

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

A computational framework for estimating statistical power and planning hypothesis-driven experiments involving one-dimensional biomechanical continua.

PubMed

Pataky, Todd C; Robinson, Mark A; Vanrenterghem, Jos

2018-01-03

Statistical power assessment is an important component of hypothesis-driven research but until relatively recently (mid-1990s) no methods were available for assessing power in experiments involving continuum data and in particular those involving one-dimensional (1D) time series. The purpose of this study was to describe how continuum-level power analyses can be used to plan hypothesis-driven biomechanics experiments involving 1D data. In particular, we demonstrate how theory- and pilot-driven 1D effect modeling can be used for sample-size calculations for both single- and multi-subject experiments. For theory-driven power analysis we use the minimum jerk hypothesis and single-subject experiments involving straight-line, planar reaching. For pilot-driven power analysis we use a previously published knee kinematics dataset. Results show that powers on the order of 0.8 can be achieved with relatively small sample sizes, five and ten for within-subject minimum jerk analysis and between-subject knee kinematics, respectively. However, the appropriate sample size depends on a priori justifications of biomechanical meaning and effect size. The main advantage of the proposed technique is that it encourages a priori justification regarding the clinical and/or scientific meaning of particular 1D effects, thereby robustly structuring subsequent experimental inquiry. In short, it shifts focus from a search for significance to a search for non-rejectable hypotheses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Random sampling of elementary flux modes in large-scale metabolic networks.

PubMed

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

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

PubMed

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

2012-07-11

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

In Situ 3D Coherent X-ray Diffraction Imaging of Shock Experiments: Possible?

NASA Astrophysics Data System (ADS)

Barber, John

2011-03-01

In traditional coherent X-ray diffraction imaging (CXDI), a 2D or quasi-2D object is illuminated by a beam of coherent X-rays to produce a diffraction pattern, which is then manipulated via a process known as iterative phase retrieval to reconstruct an image of the original 2D sample. Recently, there have been dramatic advances in methods for performing fully 3D CXDI of a sample from a single diffraction pattern [Raines et al, Nature 463 214-7 (2010)], and these methods have been used to image samples tens of microns in size using soft X-rays. In this work, I explore the theoretical possibility of applying 3D CXDI techniques to the in situ imaging of the interaction between a shock front and a polycrystal, a far more stringent problem. A delicate trade-off is required between photon energy, spot size, imaging resolution, and the dimensions of the experimental setup. In this talk, I will outline the experimental and computational requirements for performing such an experiment, and I will present images and movies from simulations of one such hypothetical experiment, including both the time-resolved X-ray diffraction patterns and the time-resolved sample imagery.

The widespread misuse of effect sizes.

PubMed

Dankel, Scott J; Mouser, J Grant; Mattocks, Kevin T; Counts, Brittany R; Jessee, Matthew B; Buckner, Samuel L; Loprinzi, Paul D; Loenneke, Jeremy P

2017-05-01

Studies comparing multiple groups (i.e., experimental and control) often examine the efficacy of an intervention by calculating within group effect sizes using Cohen's d. This method is inappropriate and largely impacted by the pre-test variability as opposed to the variability in the intervention itself. Furthermore, the percentage change is often analyzed, but this is highly impacted by the baseline values and can be potentially misleading. Thus, the objective of this study was to illustrate the common misuse of the effect size and percent change measures. Here we provide a realistic sample data set comparing two resistance training groups with the same pre-test to post-test change. Statistical tests that are commonly performed within the literature were computed. Analyzing the within group effect size favors the control group, while the percent change favors the experimental group. The most appropriate way to present the data would be to plot the individual responses or, for larger samples, provide the mean change and 95% confidence intervals of the mean change. This details the magnitude and variability within the response to the intervention itself in units that are easily interpretable. This manuscript demonstrates the common misuse of the effect size and details the importance for investigators to always report raw values, even when alternative statistics are performed. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

NASA Astrophysics Data System (ADS)

Komura, Yukihiro; Okabe, Yutaka

2014-03-01

We present sample CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm. We deal with the classical spin models; the Ising model, the q-state Potts model, and the classical XY model. As for the lattice, both the 2D (square) lattice and the 3D (simple cubic) lattice are treated. We already reported the idea of the GPU implementation for 2D models (Komura and Okabe, 2012). We here explain the details of sample programs, and discuss the performance of the present GPU implementation for the 3D Ising and XY models. We also show the calculated results of the moment ratio for these models, and discuss phase transitions. Catalogue identifier: AERM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5632 No. of bytes in distributed program, including test data, etc.: 14688 Distribution format: tar.gz Programming language: C, CUDA. Computer: System with an NVIDIA CUDA enabled GPU. Operating system: System with an NVIDIA CUDA enabled GPU. Classification: 23. External routines: NVIDIA CUDA Toolkit 3.0 or newer Nature of problem: Monte Carlo simulation of classical spin systems. Ising, q-state Potts model, and the classical XY model are treated for both two-dimensional and three-dimensional lattices. Solution method: GPU-based Swendsen-Wang multi-cluster spin flip Monte Carlo method. The CUDA implementation for the cluster-labeling is based on the work by Hawick et al. [1] and that by Kalentev et al. [2]. Restrictions: The system size is limited depending on the memory of a GPU. Running time: For the parameters used in the sample programs, it takes about a minute for each program. Of course, it depends on the system size, the number of Monte Carlo steps, etc. References: [1] K.A. Hawick, A. Leist, and D. P. Playne, Parallel Computing 36 (2010) 655-678 [2] O. Kalentev, A. Rai, S. Kemnitzb, and R. Schneider, J. Parallel Distrib. Comput. 71 (2011) 615-620

A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms

NASA Astrophysics Data System (ADS)

Schuster, G. L.; Espinosa, R.; Ziemba, L. D.; Beyersdorf, A. J.; Rocha Lima, A.; Anderson, B. E.; Martins, J. V.; Dubovik, O.; Ducos, F.; Fuertes, D.; Lapyonok, T.; Shook, M.; Derimian, Y.; Moore, R.

2016-12-01

We have developed a method for validating Aerosol Robotic Network (AERONET) retrieval algorithms by mimicking atmospheric extinction and radiance measurements in a laboratory experiment. This enables radiometric retrievals that utilize the same sampling volumes, relative humidities, and particle size ranges as observed by other in situ instrumentation in the experiment. We utilize three Cavity Attenuated Phase Shift (CAPS) monitors for extinction and UMBC's three-wavelength Polarized Imaging Nephelometer (PI-Neph) for angular scattering measurements. We subsample the PI-Neph radiance measurements to angles that correspond to AERONET almucantar scans, with solar zenith angles ranging from 50 to 77 degrees. These measurements are then used as input to the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, which retrieves size distributions, complex refractive indices, single-scatter albedos (SSA), and lidar ratios for the in situ samples. We obtained retrievals with residuals R < 10% for 100 samples. The samples that we tested include Arizona Test Dust, Arginotec NX, Senegal clay, Israel clay, montmorillonite, hematite, goethite, volcanic ash, ammonium nitrate, ammonium sulfate, and fullerene soot. Samples were alternately dried or humidified, and size distributions were limited to diameters of 1.0 or 2.5 um by using a cyclone. The SSA at 532 nm for these samples ranged from 0.59 to 1.00 when computed with CAPS extinction and PSAP absorption measurements. The GRASP retrieval provided SSAs that are highly correlated with the in situ SSAs, and the correlation coefficients ranged from 0.955 to 0.976, depending upon the simulated solar zenith angle. The GRASP SSAs exhibited an average absolute bias of +0.023 +/-0.01 with respect to the extinction and absorption measurements for the entire dataset. Although our apparatus was not capable of measuring backscatter lidar ratio, we did measure bistatic lidar ratios at a scattering angle of 173 deg. The GRASP bistatic lidar ratios had correlations of 0.488 to 0.735 (depending upon simulated SZA) with respect to in situ measurements, positive relative biases of 6-10%, and average absolute biases of 4.0-6.6 sr. We also compared the GRASP size distributions to aerodynamic particle size measurements.

Overview of the SAMPL5 host–guest challenge: Are we doing better?

PubMed Central

Yin, Jian; Henriksen, Niel M.; Slochower, David R.; Shirts, Michael R.; Chiu, Michael W.; Mobley, David L.; Gilson, Michael K.

2016-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein–ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host–guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host–guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host–guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements. PMID:27658802

Overview of the SAMPL5 host-guest challenge: Are we doing better?

PubMed

Yin, Jian; Henriksen, Niel M; Slochower, David R; Shirts, Michael R; Chiu, Michael W; Mobley, David L; Gilson, Michael K

2017-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein-ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host-guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host-guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host-guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements.

Computationally Efficient Multiconfigurational Reactive Molecular Dynamics

PubMed Central

Yamashita, Takefumi; Peng, Yuxing; Knight, Chris; Voth, Gregory A.

2012-01-01

It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as “multistate”. These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations. PMID:25100924

Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

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

Herbold, E. B.; Walton, O.; Homel, M. A.

2015-10-26

This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-­L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-­bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-­4 weeks of an FTE split amongst two staff scientists and one post-­doc. The DEM simulationsmore » emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-­particles square by 10-­particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.« less

Unlocking the spatial inversion of large scanning magnetic microscopy datasets

NASA Astrophysics Data System (ADS)

Myre, J. M.; Lascu, I.; Andrade Lima, E.; Feinberg, J. M.; Saar, M. O.; Weiss, B. P.

2013-12-01

Modern scanning magnetic microscopy provides the ability to perform high-resolution, ultra-high sensitivity moment magnetometry, with spatial resolutions better than 10^-4 m and magnetic moments as weak as 10^-16 Am^2. These microscopy capabilities have enhanced numerous magnetic studies, including investigations of the paleointensity of the Earth's magnetic field, shock magnetization and demagnetization of impacts, magnetostratigraphy, the magnetic record in speleothems, and the records of ancient core dynamos of planetary bodies. A common component among many studies utilizing scanning magnetic microscopy is solving an inverse problem to determine the non-negative magnitude of the magnetic moments that produce the measured component of the magnetic field. The two most frequently used methods to solve this inverse problem are classic fast Fourier techniques in the frequency domain and non-negative least squares (NNLS) methods in the spatial domain. Although Fourier techniques are extremely fast, they typically violate non-negativity and it is difficult to implement constraints associated with the space domain. NNLS methods do not violate non-negativity, but have typically been computation time prohibitive for samples of practical size or resolution. Existing NNLS methods use multiple techniques to attain tractable computation. To reduce computation time in the past, typically sample size or scan resolution would have to be reduced. Similarly, multiple inversions of smaller sample subdivisions can be performed, although this frequently results in undesirable artifacts at subdivision boundaries. Dipole interactions can also be filtered to only compute interactions above a threshold which enables the use of sparse methods through artificial sparsity. To improve upon existing spatial domain techniques, we present the application of the TNT algorithm, named TNT as it is a "dynamite" non-negative least squares algorithm which enhances the performance and accuracy of spatial domain inversions. We show that the TNT algorithm reduces the execution time of spatial domain inversions from months to hours and that inverse solution accuracy is improved as the TNT algorithm naturally produces solutions with small norms. Using sIRM and NRM measures of multiple synthetic and natural samples we show that the capabilities of the TNT algorithm allow very large samples to be inverted without the need for alternative techniques to make the problems tractable. Ultimately, the TNT algorithm enables accurate spatial domain analysis of scanning magnetic microscopy data on an accelerated time scale that renders spatial domain analyses tractable for numerous studies, including searches for the best fit of unidirectional magnetization direction and high-resolution step-wise magnetization and demagnetization.

On evaluating clustering procedures for use in classification

NASA Technical Reports Server (NTRS)

Pore, M. D.; Moritz, T. E.; Register, D. T.; Yao, S. S.; Eppler, W. G. (Principal Investigator)

1979-01-01

The problem of evaluating clustering algorithms and their respective computer programs for use in a preprocessing step for classification is addressed. In clustering for classification the probability of correct classification is suggested as the ultimate measure of accuracy on training data. A means of implementing this criterion and a measure of cluster purity are discussed. Examples are given. A procedure for cluster labeling that is based on cluster purity and sample size is presented.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation

PubMed Central

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-01-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037

X-ray tomography investigation of intensive sheared Al–SiC metal matrix composites

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

De Giovanni, Mario; Warnett, Jason M.; Williams, Mark A.

2015-12-15

X-ray computed tomography (XCT) was used to characterise three dimensional internal structure of Al–SiC metal matrix composites. The alloy composite was prepared by casting method with the application of intensive shearing to uniformly disperse SiC particles in the matrix. Visualisation of SiC clusters as well as porosity distribution were evaluated and compared with non-shearing samples. Results showed that the average particle size as well as agglomerate size is smaller in sheared sample compared to conventional cast samples. Further, it was observed that the volume fraction of porosity was reduced by 50% compared to conventional casting, confirming that the intensive shearingmore » helps in deagglomeration of particle clusters and decrease in porosity of Al–SiC metal matrix composites. - Highlights: • XCT was used to visualise 3D internal structure of Al-SiC MMC. • Al-SiC MMC was prepared by casting with the application of intensive shearing. • SiC particles and porosity distribution were evaluated. • Results show shearing deagglomerates particle clusters and reduces porosity in MMC.« less

BODY SIZE-SPECIFIC EFFECTIVE DOSE CONVERSION COEFFICIENTS FOR CT SCANS.

PubMed

Romanyukha, Anna; Folio, Les; Lamart, Stephanie; Simon, Steven L; Lee, Choonsik

2016-12-01

Effective dose from computed tomography (CT) examinations is usually estimated using the scanner-provided dose-length product and using conversion factors, also known as k-factors, which correspond to scan regions and differ by age according to five categories: 0, 1, 5, 10 y and adult. However, patients often deviate from the standard body size on which the conversion factor is based. In this study, a method for deriving body size-specific k-factors is presented, which can be determined from a simple regression curve based on patient diameter at the centre of the scan range. Using the International Commission on Radiological Protection reference paediatric and adult computational phantoms paired with Monte Carlo simulation of CT X-ray beams, the authors derived a regression-based k-factor model for the following CT scan types: head-neck, head, neck, chest, abdomen, pelvis, abdomen-pelvis (AP) and chest-abdomen-pelvis (CAP). The resulting regression functions were applied to a total of 105 paediatric and 279 adult CT scans randomly sampled from patients who underwent chest, AP and CAP scans at the National Institutes of Health Clinical Center. The authors have calculated and compared the effective doses derived from the conventional age-specific k-factors with the values computed using their body size-specific k-factor. They found that by using the age-specific k-factor, paediatric patients tend to have underestimates (up to 3-fold) of effective dose, while underweight and overweight adult patients tend to have underestimates (up to 2.6-fold) and overestimates (up to 4.6-fold) of effective dose, respectively, compared with the effective dose determined from their body size-dependent factors. The authors present these size-specific k-factors as an alternative to the existing age-specific factors. The body size-specific k-factor will assess effective dose more precisely and on a more individual level than the conventional age-specific k-factors and, hence, improve awareness of the true exposure, which is important for the clinical community to understand. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Exact sampling hardness of Ising spin models

NASA Astrophysics Data System (ADS)

Fefferman, B.; Foss-Feig, M.; Gorshkov, A. V.

2017-09-01

We study the complexity of classically sampling from the output distribution of an Ising spin model, which can be implemented naturally in a variety of atomic, molecular, and optical systems. In particular, we construct a specific example of an Ising Hamiltonian that, after time evolution starting from a trivial initial state, produces a particular output configuration with probability very nearly proportional to the square of the permanent of a matrix with arbitrary integer entries. In a similar spirit to boson sampling, the ability to sample classically from the probability distribution induced by time evolution under this Hamiltonian would imply unlikely complexity theoretic consequences, suggesting that the dynamics of such a spin model cannot be efficiently simulated with a classical computer. Physical Ising spin systems capable of achieving problem-size instances (i.e., qubit numbers) large enough so that classical sampling of the output distribution is classically difficult in practice may be achievable in the near future. Unlike boson sampling, our current results only imply hardness of exact classical sampling, leaving open the important question of whether a much stronger approximate-sampling hardness result holds in this context. The latter is most likely necessary to enable a convincing experimental demonstration of quantum supremacy. As referenced in a recent paper [A. Bouland, L. Mancinska, and X. Zhang, in Proceedings of the 31st Conference on Computational Complexity (CCC 2016), Leibniz International Proceedings in Informatics (Schloss Dagstuhl-Leibniz-Zentrum für Informatik, Dagstuhl, 2016)], our result completes the sampling hardness classification of two-qubit commuting Hamiltonians.

Three-dimensional computed tomographic airway analysis of patients with obstructive sleep apnea treated by maxillomandibular advancement.

PubMed

Abramson, Zachary; Susarla, Srinivas M; Lawler, Matthew; Bouchard, Carl; Troulis, Maria; Kaban, Leonard B

2011-03-01

To evaluate changes in airway size and shape in patients with obstructive sleep apnea (OSA) after maxillomandibular advancement (MMA) and genial tubercle advancement (GTA). This was a retrospective cohort study, enrolling a sample of adults with polysomnography-confirmed OSA who underwent MMA + GTA. All subjects who had preoperative and postoperative 3-dimensional computed tomography (CT) scans to evaluate changes in airway size and shape after MMA + GTA were included. Preoperative and postoperative sleep- and breathing-related symptoms were recorded. Descriptive and bivariate statistics were computed. For all analyses, P < .05 was considered statistically significant. During the study period, 13 patients underwent MMA + GTA, of whom 11 (84.6%) met the inclusion criteria. There were 9 men and 2 women with a mean age of 39 years. The mean body mass index was 26.3; mean respiratory disturbance index (RDI), 48.8; and mean lowest oxygen saturation, 80.5%. After MMA + GTA, there were significant increases in lateral and anteroposterior airway diameters (P < .01), volume (P = .02), surface area (P < .01), and cross-sectional areas at multiple sites (P < .04). Airway length decreased (P < .01) and airway shape (P = .04) became more uniform. The mean change in RDI was -60%. Results of this preliminary study indicate that MMA + GTA appears to produce significant changes in airway size and shape that correlate with a decrease in RDI. Copyright © 2011 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Scaling and efficiency of PRISM in adaptive simulations of turbulent premixed flames

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

Tonse, Shaheen R.; Bell, J.B.; Brown, N.J.

1999-12-01

The dominant computational cost in modeling turbulent combustion phenomena numerically with high fidelity chemical mechanisms is the time required to solve the ordinary differential equations associated with chemical kinetics. One approach to reducing that computational cost is to develop an inexpensive surrogate model that accurately represents evolution of chemical kinetics. One such approach, PRISM, develops a polynomial representation of the chemistry evolution in a local region of chemical composition space. This representation is then stored for later use. As the computation proceeds, the chemistry evolution for other points within the same region are computed by evaluating these polynomials instead ofmore » calling an ordinary differential equation solver. If initial data for advancing the chemistry is encountered that is not in any region for which a polynomial is defined, the methodology dynamically samples that region and constructs a new representation for that region. The utility of this approach is determined by the size of the regions over which the representation provides a good approximation to the kinetics and the number of these regions that are necessary to model the subset of composition space that is active during a simulation. In this paper, we assess the PRISM methodology in the context of a turbulent premixed flame in two dimensions. We consider a range of turbulent intensities ranging from weak turbulence that has little effect on the flame to strong turbulence that tears pockets of burning fluid from the main flame. For each case, we explore a range of sizes for the local regions and determine the scaling behavior as a function of region size and turbulent intensity.« less

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

PubMed

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

Computation of Effect Size for Moderating Effects of Categorical Variables in Multiple Regression

ERIC Educational Resources Information Center

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)…

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

Miller, Thomas Martin; Patton, Bruce W.; Weber, Charles F.

The primary goal of this project is to evaluate x-ray spectra generated within a scanning electron microscope (SEM) to determine elemental composition of small samples. This will be accomplished by performing Monte Carlo simulations of the electron and photon interactions in the sample and in the x-ray detector. The elemental inventories will be determined by an inverse process that progressively reduces the difference between the measured and simulated x-ray spectra by iteratively adjusting composition and geometric variables in the computational model. The intended benefit of this work will be to develop a method to perform quantitative analysis on substandard samplesmore » (heterogeneous phases, rough surfaces, small sizes, etc.) without involving standard elemental samples or empirical matrix corrections (i.e., true standardless quantitative analysis).« less

Comparison of VRX CT scanners geometries

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Melnyk, Roman; Duckworth, Christopher N.; Russ, Stephan; Jordan, Lawrence M.; Laughter, Joseph S.

2001-06-01

A technique called Variable-Resolution X-ray (VRX) detection greatly increases the spatial resolution in computed tomography (CT) and digital radiography (DR) as the field size decreases. The technique is based on a principle called `projective compression' that allows both the resolution element and the sampling distance of a CT detector to scale with the subject or field size. For very large (40 - 50 cm) field sizes, resolution exceeding 2 cy/mm is possible and for very small fields, microscopy is attainable with resolution exceeding 100 cy/mm. This paper compares the benefits obtainable with two different VRX detector geometries: the single-arm geometry and the dual-arm geometry. The analysis is based on Monte Carlo simulations and direct calculations. The results of this study indicate that the dual-arm system appears to have more advantages than the single-arm technique.

Comparison of fluvial suspended-sediment concentrations and particle-size distributions measured with in-stream laser diffraction and in physical samples

USGS Publications Warehouse

Czuba, Jonathan A.; Straub, Timothy D.; Curran, Christopher A.; Landers, Mark N.; Domanski, Marian M.

2015-01-01

Laser-diffraction technology, recently adapted for in-stream measurement of fluvial suspended-sediment concentrations (SSCs) and particle-size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In-Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8-415 µm in 32 log-spaced size classes. Measured SSCs and PSDs from the LISST-SL were compared to a suite of 22 datasets (262 samples in all) of concurrent suspended-sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010-12 at 16 U.S. Geological Survey streamflow-gaging stations in Illinois and Washington (basin areas: 38 – 69,264 km2). An unrealistically low computed effective density (mass SSC / volumetric SSC) of 1.24 g/ml (95% confidence interval: 1.05-1.45 g/ml) provided the best-fit value (R2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over 2 orders of magnitude of SSC (12-2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST-SL) despite being substantially lower than the sediment particle density of 2.67 g/ml (range: 2.56-2.87 g/ml, 23 samples). The PSDs measured by the LISST-SL were in good agreement with those derived from physical samples over the LISST-SL's measureable size range. Technical and operational limitations of the LISST-SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST-SL is briefly described to motivate its potential for advancing our understanding of suspended-sediment transport by rivers.

Comparative study of various pixel photodiodes for digital radiography: Junction structure, corner shape and noble window opening

NASA Astrophysics Data System (ADS)

Kang, Dong-Uk; Cho, Minsik; Lee, Dae Hee; Yoo, Hyunjun; Kim, Myung Soo; Bae, Jun Hyung; Kim, Hyoungtaek; Kim, Jongyul; Kim, Hyunduk; Cho, Gyuseong

2012-05-01

Recently, large-size 3-transistors (3-Tr) active pixel complementary metal-oxide silicon (CMOS) image sensors have been being used for medium-size digital X-ray radiography, such as dental computed tomography (CT), mammography and nondestructive testing (NDT) for consumer products. We designed and fabricated 50 µm × 50 µm 3-Tr test pixels having a pixel photodiode with various structures and shapes by using the TSMC 0.25-m standard CMOS process to compare their optical characteristics. The pixel photodiode output was continuously sampled while a test pixel was continuously illuminated by using 550-nm light at a constant intensity. The measurement was repeated 300 times for each test pixel to obtain reliable results on the mean and the variance of the pixel output at each sampling time. The sampling rate was 50 kHz, and the reset period was 200 msec. To estimate the conversion gain, we used the mean-variance method. From the measured results, the n-well/p-substrate photodiode, among 3 photodiode structures available in a standard CMOS process, showed the best performance at a low illumination equivalent to the typical X-ray signal range. The quantum efficiencies of the n+/p-well, n-well/p-substrate, and n+/p-substrate photodiodes were 18.5%, 62.1%, and 51.5%, respectively. From a comparison of pixels with rounded and rectangular corners, we found that a rounded corner structure could reduce the dark current in large-size pixels. A pixel with four rounded corners showed a reduced dark current of about 200fA compared to a pixel with four rectangular corners in our pixel sample size. Photodiodes with round p-implant openings showed about 5% higher dark current, but about 34% higher sensitivities, than the conventional photodiodes.

Numerical optimization techniques for bound circulation distribution for minimum induced drag of Nonplanar wings: Computer program documentation

NASA Technical Reports Server (NTRS)

Kuhlman, J. M.; Ku, T. J.

1981-01-01

A two dimensional advanced panel far-field potential flow model of the undistorted, interacting wakes of multiple lifting surfaces was developed which allows the determination of the spanwise bound circulation distribution required for minimum induced drag. This model was implemented in a FORTRAN computer program, the use of which is documented in this report. The nonplanar wakes are broken up into variable sized, flat panels, as chosen by the user. The wake vortex sheet strength is assumed to vary linearly over each of these panels, resulting in a quadratic variation of bound circulation. Panels are infinite in the streamwise direction. The theory is briefly summarized herein; sample results are given for multiple, nonplanar, lifting surfaces, and the use of the computer program is detailed in the appendixes.

A variable-step-size robust delta modulator.

NASA Technical Reports Server (NTRS)

Song, C. L.; Garodnick, J.; Schilling, D. L.

1971-01-01

Description of an analytically obtained optimum adaptive delta modulator-demodulator configuration. The device utilizes two past samples to obtain a step size which minimizes the mean square error for a Markov-Gaussian source. The optimum system is compared, using computer simulations, with a linear delta modulator and an enhanced Abate delta modulator. In addition, the performance is compared to the rate distortion bound for a Markov source. It is shown that the optimum delta modulator is neither quantization nor slope-overload limited. The highly nonlinear equations obtained for the optimum transmitter and receiver are approximated by piecewise-linear equations in order to obtain system equations which can be transformed into hardware. The derivation of the experimental system is presented.

Birth order, family configuration, and verbal achievement.

PubMed

Breland, H M

1974-12-01

Two samples of National Merit Scholarship participants test in 1962 and the entire population of almost 800,000 participants tested in 1965 were examined. Consistent effects in all 3 groups were observed with respect to both birth order and family size (1st born and those of smaller families scored higher). Control of both socioeconomic variables and maternal age, by analysis of variance as well as by analysis of covariance, failed to alter the relationships. Stepdown analyses suggested that the effects were due to a verbal component and that no differences were attributable to nonverbal factors. Mean test scores were computed for detailed sibship configurations based on birth order, family size, sibling spacing, and sibling sex.

Optical properties of graphene nanoflakes: Shape matters.

PubMed

Mansilla Wettstein, Candela; Bonafé, Franco P; Oviedo, M Belén; Sánchez, Cristián G

2016-06-14

In recent years there has been significant debate on whether the edge type of graphene nanoflakes (GNFs) or graphene quantum dots (GQDs) are relevant for their electronic structure, thermal stability, and optical properties. Using computer simulations, we have proven that there is a fundamental difference in the absorption spectra between samples of the same shape, similar size but different edge type, namely, armchair or zigzag edges. These can be explained by the presence of electronic structures near the Fermi level which are localized on the edges. These features are also evident from the dependence of band gap on the GNF size, which shows three very distinct trends for different shapes and edge geometries.

Optical properties of graphene nanoflakes: Shape matters

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

Mansilla Wettstein, Candela; Bonafé, Franco P.; Sánchez, Cristián G., E-mail: cgsanchez@fcq.unc.edu.ar

In recent years there has been significant debate on whether the edge type of graphene nanoflakes (GNFs) or graphene quantum dots (GQDs) are relevant for their electronic structure, thermal stability, and optical properties. Using computer simulations, we have proven that there is a fundamental difference in the absorption spectra between samples of the same shape, similar size but different edge type, namely, armchair or zigzag edges. These can be explained by the presence of electronic structures near the Fermi level which are localized on the edges. These features are also evident from the dependence of band gap on the GNFmore » size, which shows three very distinct trends for different shapes and edge geometries.« less

The graphic cell method: a new look at digitizing geologic maps

USGS Publications Warehouse

Hanley, J.T.

1982-01-01

The graphic cell method is an alternative method of digitizing areal geologic information. It involves a discrete-point sampling scheme in which the computer establishes a matrix of cells over the map. Each cell and the whole cell is assigned the identity or value of the geologic information that is recognized at its center. Cell size may be changed to suit the needs of the user. The computer program resolves the matrix and identifies potential errors such as multiple assignments. Input includes the digitized boundaries of each geologic formation. This method should eliminate a primary bottleneck in the creation and testing of geomathematical models in such disciplines as resource appraisal. ?? 1982.

Advanced ETC/LSS computerized analytical models, CO2 concentration. Volume 1: Summary document

NASA Technical Reports Server (NTRS)

Taylor, B. N.; Loscutoff, A. V.

1972-01-01

Computer simulations have been prepared for the concepts of C02 concentration which have the potential for maintaining a C02 partial pressure of 3.0 mmHg, or less, in a spacecraft environment. The simulations were performed using the G-189A Generalized Environmental Control computer program. In preparing the simulations, new subroutines to model the principal functional components for each concept were prepared and integrated into the existing program. Sample problems were run to demonstrate the methods of simulation and performance characteristics of the individual concepts. Comparison runs for each concept can be made for parametric values of cabin pressure, crew size, cabin air dry and wet bulb temperatures, and mission duration.

Procedures for gathering ground truth information for a supervised approach to a computer-implemented land cover classification of LANDSAT-acquired multispectral scanner data

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1978-01-01

Procedures for gathering ground truth information for a supervised approach to a computer-implemented land cover classification of LANDSAT acquired multispectral scanner data are provided in a step by step manner. Criteria for determining size, number, uniformity, and predominant land cover of training sample sites are established. Suggestions are made for the organization and orientation of field team personnel, the procedures used in the field, and the format of the forms to be used. Estimates are made of the probable expenditures in time and costs. Examples of ground truth forms and definitions and criteria of major land cover categories are provided in appendixes.

Viewpoints: A New Computer Program for Interactive Exploration of Large Multivariate Space Science and Astrophysics Data.

NASA Astrophysics Data System (ADS)

Levit, Creon; Gazis, P.

2006-06-01

The graphics processing units (GPUs) built in to all professional desktop and laptop computers currently on the market are capable of transforming, filtering, and rendering hundreds of millions of points per second. We present a prototype open-source cross-platform (windows, linux, Apple OSX) application which leverages some of the power latent in the GPU to enable smooth interactive exploration and analysis of large high-dimensional data using a variety of classical and recent techniques. The targeted application area is the interactive analysis of complex, multivariate space science and astrophysics data sets, with dimensionalities that may surpass 100 and sample sizes that may exceed 10^6-10^8.

Correlated histogram representation of Monte Carlo derived medical accelerator photon-output phase space

DOEpatents

Schach Von Wittenau, Alexis E.

2003-01-01

A method is provided to represent the calculated phase space of photons emanating from medical accelerators used in photon teletherapy. The method reproduces the energy distributions and trajectories of the photons originating in the bremsstrahlung target and of photons scattered by components within the accelerator head. The method reproduces the energy and directional information from sources up to several centimeters in radial extent, so it is expected to generalize well to accelerators made by different manufacturers. The method is computationally both fast and efficient overall sampling efficiency of 80% or higher for most field sizes. The computational cost is independent of the number of beams used in the treatment plan.

Accurate and fast multiple-testing correction in eQTL studies.

PubMed

Sul, Jae Hoon; Raj, Towfique; de Jong, Simone; de Bakker, Paul I W; Raychaudhuri, Soumya; Ophoff, Roel A; Stranger, Barbara E; Eskin, Eleazar; Han, Buhm

2015-06-04

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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

PubMed

Ozçift, Akin

2011-05-01

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

Stochastic Investigation of Natural Frequency for Functionally Graded Plates

NASA Astrophysics Data System (ADS)

Karsh, P. K.; Mukhopadhyay, T.; Dey, S.

2018-03-01

This paper presents the stochastic natural frequency analysis of functionally graded plates by applying artificial neural network (ANN) approach. Latin hypercube sampling is utilised to train the ANN model. The proposed algorithm for stochastic natural frequency analysis of FGM plates is validated and verified with original finite element method and Monte Carlo simulation (MCS). The combined stochastic variation of input parameters such as, elastic modulus, shear modulus, Poisson ratio, and mass density are considered. Power law is applied to distribute the material properties across the thickness. The present ANN model reduces the sample size and computationally found efficient as compared to conventional Monte Carlo simulation.

Variance of discharge estimates sampled using acoustic Doppler current profilers from moving boats

USGS Publications Warehouse

Garcia, Carlos M.; Tarrab, Leticia; Oberg, Kevin; Szupiany, Ricardo; Cantero, Mariano I.

2012-01-01

This paper presents a model for quantifying the random errors (i.e., variance) of acoustic Doppler current profiler (ADCP) discharge measurements from moving boats for different sampling times. The model focuses on the random processes in the sampled flow field and has been developed using statistical methods currently available for uncertainty analysis of velocity time series. Analysis of field data collected using ADCP from moving boats from three natural rivers of varying sizes and flow conditions shows that, even though the estimate of the integral time scale of the actual turbulent flow field is larger than the sampling interval, the integral time scale of the sampled flow field is on the order of the sampling interval. Thus, an equation for computing the variance error in discharge measurements associated with different sampling times, assuming uncorrelated flow fields is appropriate. The approach is used to help define optimal sampling strategies by choosing the exposure time required for ADCPs to accurately measure flow discharge.

Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery

USGS Publications Warehouse

Mosbrucker, Adam; Spicer, Kurt R.; Christianson, Tami; Uhrich, Mark A.

2015-01-01

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

Ideal Particle Sizes for Inhaled Steroids Targeting Vocal Granulomas: Preliminary Study Using Computational Fluid Dynamics.

PubMed

Perkins, Elizabeth L; Basu, Saikat; Garcia, Guilherme J M; Buckmire, Robert A; Shah, Rupali N; Kimbell, Julia S

2018-03-01

Objectives Vocal fold granulomas are benign lesions of the larynx commonly caused by gastroesophageal reflux, intubation, and phonotrauma. Current medical therapy includes inhaled corticosteroids to target inflammation that leads to granuloma formation. Particle sizes of commonly prescribed inhalers range over 1 to 4 µm. The study objective was to use computational fluid dynamics to investigate deposition patterns over a range of particle sizes of inhaled corticosteroids targeting the larynx and vocal fold granulomas. Study Design Retrospective, case-specific computational study. Setting Tertiary academic center. Subjects/Methods A 3-dimensional anatomically realistic computational model of a normal adult airway from mouth to trachea was constructed from 3 computed tomography scans. Virtual granulomas of varying sizes and positions along the vocal fold were incorporated into the base model. Assuming steady-state, inspiratory, turbulent airflow at 30 L/min, computational fluid dynamics was used to simulate respiratory transport and deposition of inhaled corticosteroid particles ranging over 1 to 20 µm. Results Laryngeal deposition in the base model peaked for particle sizes 8 to 10 µm (2.8%-3.5%). Ideal sizes ranged over 6 to 10, 7 to 13, and 7 to 14 µm for small, medium, and large granuloma sizes, respectively. Glottic deposition was maximal at 10.8% for 9-µm-sized particles for the large posterior granuloma, 3 times the normal model (3.5%). Conclusion As the virtual granuloma size increased and the location became more posterior, glottic deposition and ideal particle size generally increased. This preliminary study suggests that inhalers with larger particle sizes, such as fluticasone propionate dry-powder inhaler, may improve laryngeal drug deposition. Most commercially available inhalers have smaller particles than suggested here.

ADAPTIVE ANNEALED IMPORTANCE SAMPLING FOR MULTIMODAL POSTERIOR EXPLORATION AND MODEL SELECTION WITH APPLICATION TO EXTRASOLAR PLANET DETECTION

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

Liu, Bin, E-mail: bins@ieee.org

2014-07-01

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior.more » To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.« less

Application of a sediment-transport model to estimate bridge scour at selected sites in Colorado, 1991-93

USGS Publications Warehouse

Vaill, J.E.

1995-01-01

A bridge-scour study by the U.S. Geological Survey, in cooperation with the Colorado Department of Transportation, was begun in 1991 to evaluate bridges in the State for potential scour during floods. A part of that study was to apply a computer model for sediment-transport routing to simulate channel aggradation or degradation and pier scour during floods at three bridge sites in Colorado. Stream-channel reaches upstream and downstream from the bridges were simulated using the Bridge Stream Tube model for Alluvial River Simulation (BRI-STARS). Synthetic flood hydrographs for the 500-year floods were developed for Surveyor Creek near Platner and for the Rio Grande at Wagon Wheel Gap. A part of the recorded mean daily hydrograph for the peak flow of record was used for the Yampa River near Maybell. The recorded hydrograph for the peak flow of record exceeded the computed 500-year-flood magnitude for this stream by about 22 percent. Bed-material particle-size distributions were determined from samples collected at Surveyor Creek and the Rio Grande. Existing data were used for the Yampa River. The model was used to compute a sediment-inflow hydrograph using particle-size data collected and a specified sediment-transport equation at each site. Particle sizes ranged from less than 0.5 to 16 millimeters for Surveyor Creek, less than 4 to 128 millimeters for the Yampa River, and 22.5 to 150 millimeters for the Rio Grande. Computed scour at the peak steamflows ranged from -2.32 feet at Surveyor Creek near Platner to +0.63 foot at the Rio Grande at Wagon Wheel Gap. Pier- scour depths computed at the peak streamflows ranged from 4.46 feet at the Rio Grande at Wagon Wheel Gap to 5.94 feet at the Yampa River near Maybell. The number of streamtubes used in the model varied at each site.

Porosity dependence of terahertz emission of porous silicon investigated using reflection geometry terahertz time-domain spectroscopy

NASA Astrophysics Data System (ADS)

Mabilangan, Arvin I.; Lopez, Lorenzo P.; Faustino, Maria Angela B.; Muldera, Joselito E.; Cabello, Neil Irvin F.; Estacio, Elmer S.; Salvador, Arnel A.; Somintac, Armando S.

2016-12-01

Porosity dependent terahertz emission of porous silicon (PSi) was studied. The PSi samples were fabricated via electrochemical etching of boron-doped (100) silicon in a solution containing 48% hydrofluoric acid, deionized water and absolute ethanol in a 1:3:4 volumetric ratio. The porosity was controlled by varying the supplied anodic current for each sample. The samples were then optically characterized via normal incidence reflectance spectroscopy to obtain values for their respective refractive indices and porosities. Absorbance of each sample was also computed using the data from its respective reflectance spectrum. Terahertz emission of each sample was acquired through terahertz - time domain spectroscopy. A decreasing trend in the THz signal power was observed as the porosity of each PSi was increased. This was caused by the decrease in the absorption strength as the silicon crystallite size in the PSi was minimized.

X-ray simulations method for the large field of view

NASA Astrophysics Data System (ADS)

Schelokov, I. A.; Grigoriev, M. V.; Chukalina, M. V.; Asadchikov, V. E.

2018-03-01

In the standard approach, X-ray simulation is usually limited to the step of spatial sampling to calculate the convolution of integrals of the Fresnel type. Explicitly the sampling step is determined by the size of the last Fresnel zone in the beam aperture. In other words, the spatial sampling is determined by the precision of integral convolution calculations and is not connected with the space resolution of an optical scheme. In the developed approach the convolution in the normal space is replaced by computations of the shear strain of ambiguity function in the phase space. The spatial sampling is then determined by the space resolution of an optical scheme. The sampling step can differ in various directions because of the source anisotropy. The approach was used to simulate original images in the X-ray Talbot interferometry and showed that the simulation can be applied to optimize the methods of postprocessing.

A Scoping Review of Digital Gaming Research Involving Older Adults Aged 85 and Older.

PubMed

Marston, Hannah R; Freeman, Shannon; Bishop, Kristen A; Beech, Christian L

2016-06-01

Interest in the use of digital game technologies by older adults is growing across disciplines from health and gerontology to computer science and game studies. The objective of this scoping review was to examine research evidence involving the oldest old (persons 85 years of age or greater) and digital game technology. PubMed, CINHAL, and Scopus were searched, and 46 articles were included in this review. Results highlighted that 60 percent of articles were published in gerontological journals, whereas only 8.7 percent were published in computer science journals. No studies focused directly on the oldest old population. Few studies included sample sizes greater than 100 participants. Seven primary and 34 secondary themes were identified, of which Hardware Technology and Assessment were the most common. Existing evidence demonstrates the paucity of studies engaging older adults 85 years of age and above regarding the use of digital gaming and highlights a new understudied cohort for further research focus. Recommendations for future research include intentional recruitment and proportionate representation of participants ≥85 years of age, large sample sizes, and explicit mention of specific numbers of participants ≥85 years of age, which are necessary to advance knowledge in this area. Integrating a rigorous and robust mixed-methods approach including theoretical perspectives would lend itself to further in-depth understanding and knowledge generation in this field.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

PubMed

Ivanova, Anastasia; Qaqish, Bahjat; Schoenfeld, David A

2011-10-15

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice. Copyright © 2011 John Wiley & Sons, Ltd.

Sample size and allocation of effort in point count sampling of birds in bottomland hardwood forests

USGS Publications Warehouse

Smith, W.P.; Twedt, D.J.; Cooper, R.J.; Wiedenfeld, D.A.; Hamel, P.B.; Ford, R.P.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

To examine sample size requirements and optimum allocation of effort in point count sampling of bottomland hardwood forests, we computed minimum sample sizes from variation recorded during 82 point counts (May 7-May 16, 1992) from three localities containing three habitat types across three regions of the Mississippi Alluvial Valley (MAV). Also, we estimated the effect of increasing the number of points or visits by comparing results of 150 four-minute point counts obtained from each of four stands on Delta Experimental Forest (DEF) during May 8-May 21, 1991 and May 30-June 12, 1992. For each stand, we obtained bootstrap estimates of mean cumulative number of species each year from all possible combinations of six points and six visits. ANOVA was used to model cumulative species as a function of number of points visited, number of visits to each point, and interaction of points and visits. There was significant variation in numbers of birds and species between regions and localities (nested within region); neither habitat, nor the interaction between region and habitat, was significant. For a = 0.05 and a = 0.10, minimum sample size estimates (per factor level) varied by orders of magnitude depending upon the observed or specified range of desired detectable difference. For observed regional variation, 20 and 40 point counts were required to accommodate variability in total individuals (MSE = 9.28) and species (MSE = 3.79), respectively, whereas ? 25 percent of the mean could be achieved with five counts per factor level. Sample size sufficient to detect actual differences of Wood Thrush (Hylocichla mustelina) was >200, whereas the Prothonotary Warbler (Protonotaria citrea) required <10 counts. Differences in mean cumulative species were detected among number of points visited and among number of visits to a point. In the lower MAV, mean cumulative species increased with each added point through five points and with each additional visit through four visits. Although no interaction was detected between number of points and number of visits, when paired reciprocals were compared, more points invariably yielded a significantly greater cumulative number of species than more visits to a point. Still, 36 point counts per stand during each of two breeding seasons detected only 52 percent of the known available species pool in DEF.

How bandwidth selection algorithms impact exploratory data analysis using kernel density estimation.

PubMed

Harpole, Jared K; Woods, Carol M; Rodebaugh, Thomas L; Levinson, Cheri A; Lenze, Eric J

2014-09-01

Exploratory data analysis (EDA) can reveal important features of underlying distributions, and these features often have an impact on inferences and conclusions drawn from data. Graphical analysis is central to EDA, and graphical representations of distributions often benefit from smoothing. A viable method of estimating and graphing the underlying density in EDA is kernel density estimation (KDE). This article provides an introduction to KDE and examines alternative methods for specifying the smoothing bandwidth in terms of their ability to recover the true density. We also illustrate the comparison and use of KDE methods with 2 empirical examples. Simulations were carried out in which we compared 8 bandwidth selection methods (Sheather-Jones plug-in [SJDP], normal rule of thumb, Silverman's rule of thumb, least squares cross-validation, biased cross-validation, and 3 adaptive kernel estimators) using 5 true density shapes (standard normal, positively skewed, bimodal, skewed bimodal, and standard lognormal) and 9 sample sizes (15, 25, 50, 75, 100, 250, 500, 1,000, 2,000). Results indicate that, overall, SJDP outperformed all methods. However, for smaller sample sizes (25 to 100) either biased cross-validation or Silverman's rule of thumb was recommended, and for larger sample sizes the adaptive kernel estimator with SJDP was recommended. Information is provided about implementing the recommendations in the R computing language. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A generalized least squares regression approach for computing effect sizes in single-case research: application examples.

PubMed

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

2011-06-01

A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of treatment effect from baseline to treatment phases in standard deviation units. In this paper, the method is applied to two published examples using common single case designs (i.e., withdrawal and multiple-baseline). The results from these studies are described, and the method is compared to ten desirable criteria for single-case effect sizes. Based on the results of this application, we conclude with observations about the use of GLS as a support to visual analysis, provide recommendations for future research, and describe implications for practice. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Sublattice parallel replica dynamics.

PubMed

Martínez, Enrique; Uberuaga, Blas P; Voter, Arthur F

2014-06-01

Exascale computing presents a challenge for the scientific community as new algorithms must be developed to take full advantage of the new computing paradigm. Atomistic simulation methods that offer full fidelity to the underlying potential, i.e., molecular dynamics (MD) and parallel replica dynamics, fail to use the whole machine speedup, leaving a region in time and sample size space that is unattainable with current algorithms. In this paper, we present an extension of the parallel replica dynamics algorithm [A. F. Voter, Phys. Rev. B 57, R13985 (1998)] by combining it with the synchronous sublattice approach of Shim and Amar [ and , Phys. Rev. B 71, 125432 (2005)], thereby exploiting event locality to improve the algorithm scalability. This algorithm is based on a domain decomposition in which events happen independently in different regions in the sample. We develop an analytical expression for the speedup given by this sublattice parallel replica dynamics algorithm and compare it with parallel MD and traditional parallel replica dynamics. We demonstrate how this algorithm, which introduces a slight additional approximation of event locality, enables the study of physical systems unreachable with traditional methodologies and promises to better utilize the resources of current high performance and future exascale computers.

JAX Colony Management System (JCMS): an extensible colony and phenotype data management system.

PubMed

Donnelly, Chuck J; McFarland, Mike; Ames, Abigail; Sundberg, Beth; Springer, Dave; Blauth, Peter; Bult, Carol J

2010-04-01

The Jackson Laboratory Colony Management System (JCMS) is a software application for managing data and information related to research mouse colonies, associated biospecimens, and experimental protocols. JCMS runs directly on computers that run one of the PC Windows operating systems, but can be accessed via web browser interfaces from any computer running a Windows, Macintosh, or Linux operating system. JCMS can be configured for a single user or multiple users in small- to medium-size work groups. The target audience for JCMS includes laboratory technicians, animal colony managers, and principal investigators. The application provides operational support for colony management and experimental workflows, sample and data tracking through transaction-based data entry forms, and date-driven work reports. Flexible query forms allow researchers to retrieve database records based on user-defined criteria. Recent advances in handheld computers with integrated barcode readers, middleware technologies, web browsers, and wireless networks add to the utility of JCMS by allowing real-time access to the database from any networked computer.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

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

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

HYDES: A generalized hybrid computer program for studying turbojet or turbofan engine dynamics

NASA Technical Reports Server (NTRS)

Szuch, J. R.

1974-01-01

This report describes HYDES, a hybrid computer program capable of simulating one-spool turbojet, two-spool turbojet, or two-spool turbofan engine dynamics. HYDES is also capable of simulating two- or three-stream turbofans with or without mixing of the exhaust streams. The program is intended to reduce the time required for implementing dynamic engine simulations. HYDES was developed for running on the Lewis Research Center's Electronic Associates (EAI) 690 Hybrid Computing System and satisfies the 16384-word core-size and hybrid-interface limits of that machine. The program could be modified for running on other computing systems. The use of HYDES to simulate a single-spool turbojet and a two-spool, two-stream turbofan engine is demonstrated. The form of the required input data is shown and samples of output listings (teletype) and transient plots (x-y plotter) are provided. HYDES is shown to be capable of performing both steady-state design and off-design analyses and transient analyses.

Estimation of local stresses and elastic properties of a mortar sample by FFT computation of fields on a 3D image

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

Escoda, J.; Departement Materiaux et Mecanique des Composants, Electricite de France, Moret-sur-Loing; Willot, F., E-mail: francois.willot@ensmp.f

2011-05-15

This study concerns the prediction of the elastic properties of a 3D mortar image, obtained by micro-tomography, using a combined image segmentation and numerical homogenization approach. The microstructure is obtained by segmentation of the 3D image into aggregates, voids and cement paste. Full-fields computations of the elastic response of mortar are undertaken using the Fast Fourier Transform method. Emphasis is made on highly-contrasted properties between aggregates and matrix, to anticipate needs for creep or damage computation. The representative volume element, i.e. the volume size necessary to compute the effective properties with a prescribed accuracy, is given. Overall, the volumes usedmore » in this work were sufficient to estimate the effective response of mortar with a precision of 5%, 6% and 10% for contrast ratios of 100, 1000 and 10,000, resp. Finally, a statistical and local characterization of the component of the stress field parallel to the applied loading is carried out.« less

Static versus dynamic sampling for data mining

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

John, G.H.; Langley, P.

1996-12-31

As data warehouses grow to the point where one hundred gigabytes is considered small, the computational efficiency of data-mining algorithms on large databases becomes increasingly important. Using a sample from the database can speed up the datamining process, but this is only acceptable if it does not reduce the quality of the mined knowledge. To this end, we introduce the {open_quotes}Probably Close Enough{close_quotes} criterion to describe the desired properties of a sample. Sampling usually refers to the use of static statistical tests to decide whether a sample is sufficiently similar to the large database, in the absence of any knowledgemore » of the tools the data miner intends to use. We discuss dynamic sampling methods, which take into account the mining tool being used and can thus give better samples. We describe dynamic schemes that observe a mining tool`s performance on training samples of increasing size and use these results to determine when a sample is sufficiently large. We evaluate these sampling methods on data from the UCI repository and conclude that dynamic sampling is preferable.« less

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

PubMed

Linder, Nina; Turkki, Riku; Walliander, Margarita; Mårtensson, Andreas; Diwan, Vinod; Rahtu, Esa; Pietikäinen, Matti; Lundin, Mikael; Lundin, Johan

2014-01-01

Microscopy is the gold standard for diagnosis of malaria, however, manual evaluation of blood films is highly dependent on skilled personnel in a time-consuming, error-prone and repetitive process. In this study we propose a method using computer vision detection and visualization of only the diagnostically most relevant sample regions in digitized blood smears. Giemsa-stained thin blood films with P. falciparum ring-stage trophozoites (n = 27) and uninfected controls (n = 20) were digitally scanned with an oil immersion objective (0.1 µm/pixel) to capture approximately 50,000 erythrocytes per sample. Parasite candidate regions were identified based on color and object size, followed by extraction of image features (local binary patterns, local contrast and Scale-invariant feature transform descriptors) used as input to a support vector machine classifier. The classifier was trained on digital slides from ten patients and validated on six samples. The diagnostic accuracy was tested on 31 samples (19 infected and 12 controls). From each digitized area of a blood smear, a panel with the 128 most probable parasite candidate regions was generated. Two expert microscopists were asked to visually inspect the panel on a tablet computer and to judge whether the patient was infected with P. falciparum. The method achieved a diagnostic sensitivity and specificity of 95% and 100% as well as 90% and 100% for the two readers respectively using the diagnostic tool. Parasitemia was separately calculated by the automated system and the correlation coefficient between manual and automated parasitemia counts was 0.97. We developed a decision support system for detecting malaria parasites using a computer vision algorithm combined with visualization of sample areas with the highest probability of malaria infection. The system provides a novel method for blood smear screening with a significantly reduced need for visual examination and has a potential to increase the throughput in malaria diagnostics.

A diffusive information preservation method for small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2013-06-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Parameterization of Cloud Optical Properties for a Mixture of Ice Particles for use in Atmospheric Models

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lee, Kyu-Tae; Yang, Ping; Lau, William K. M. (Technical Monitor)

2002-01-01

Based on the single-scattering optical properties that are pre-computed using an improve geometric optics method, the bulk mass absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the mean effective particle size of a mixture of ice habits. The parameterization has been applied to compute fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. Compared to the parameterization for a single habit of hexagonal column, the solar heating of clouds computed with the parameterization for a mixture of habits is smaller due to a smaller cosingle-scattering albedo. Whereas the net downward fluxes at the TOA and surface are larger due to a larger asymmetry factor. The maximum difference in the cloud heating rate is approx. 0.2 C per day, which occurs in clouds with an optical thickness greater than 3 and the solar zenith angle less than 45 degrees. Flux difference is less than 10 W per square meters for the optical thickness ranging from 0.6 to 10 and the entire range of the solar zenith angle. The maximum flux difference is approximately 3%, which occurs around an optical thickness of 1 and at high solar zenith angles.

Construction of pore network models for Berea and Fontainebleau sandstones using non-linear programing and optimization techniques

NASA Astrophysics Data System (ADS)

Sharqawy, Mostafa H.

2016-12-01

Pore network models (PNM) of Berea and Fontainebleau sandstones were constructed using nonlinear programming (NLP) and optimization methods. The constructed PNMs are considered as a digital representation of the rock samples which were based on matching the macroscopic properties of the porous media and used to conduct fluid transport simulations including single and two-phase flow. The PNMs consisted of cubic networks of randomly distributed pores and throats sizes and with various connectivity levels. The networks were optimized such that the upper and lower bounds of the pore sizes are determined using the capillary tube bundle model and the Nelder-Mead method instead of guessing them, which reduces the optimization computational time significantly. An open-source PNM framework was employed to conduct transport and percolation simulations such as invasion percolation and Darcian flow. The PNM model was subsequently used to compute the macroscopic properties; porosity, absolute permeability, specific surface area, breakthrough capillary pressure, and primary drainage curve. The pore networks were optimized to allow for the simulation results of the macroscopic properties to be in excellent agreement with the experimental measurements. This study demonstrates that non-linear programming and optimization methods provide a promising method for pore network modeling when computed tomography imaging may not be readily available.

Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2013-01-01

Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589

Partitioning heritability by functional annotation using genome-wide association summary statistics.

PubMed

Finucane, Hilary K; Bulik-Sullivan, Brendan; Gusev, Alexander; Trynka, Gosia; Reshef, Yakir; Loh, Po-Ru; Anttila, Verneri; Xu, Han; Zang, Chongzhi; Farh, Kyle; Ripke, Stephan; Day, Felix R; Purcell, Shaun; Stahl, Eli; Lindstrom, Sara; Perry, John R B; Okada, Yukinori; Raychaudhuri, Soumya; Daly, Mark J; Patterson, Nick; Neale, Benjamin M; Price, Alkes L

2015-11-01

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

The anomalous demagnetization behaviour of chondritic meteorites

NASA Astrophysics Data System (ADS)

Morden, S. J.

1992-06-01

Alternating field (AF) demagnetization of chondritic samples often shows anomalous results such as large directional and intensity changes; 'saw-tooth' intensity vs. demagnetizing field curves are also prevalent. An attempt to explain this behaviour is presented, using a computer model in which individual 'mineral grains' can be 'magnetized' in a variety of different ways. A simulated demagnetization can then be carried out to examine the results. It was found that the experimental behaviour of chondrites can be successfully mimicked by loading the computer model with a series of randomly orientated and sized vectors. The parameters of the model can be changed to reflect different trends seen in experimental data. Many published results can be modelled using this method. A known magnetic mineralogy can be modelled, and an unknown mineralogy deduced from AF demagnetization curves. Only by comparing data from mutually orientated samples can true stable regions for palaeointensity measurements be identified, calling into question some previous estimates of field strength from meteorites.

Pearson-type goodness-of-fit test with bootstrap maximum likelihood estimation.

PubMed

Yin, Guosheng; Ma, Yanyuan

2013-01-01

The Pearson test statistic is constructed by partitioning the data into bins and computing the difference between the observed and expected counts in these bins. If the maximum likelihood estimator (MLE) of the original data is used, the statistic generally does not follow a chi-squared distribution or any explicit distribution. We propose a bootstrap-based modification of the Pearson test statistic to recover the chi-squared distribution. We compute the observed and expected counts in the partitioned bins by using the MLE obtained from a bootstrap sample. This bootstrap-sample MLE adjusts exactly the right amount of randomness to the test statistic, and recovers the chi-squared distribution. The bootstrap chi-squared test is easy to implement, as it only requires fitting exactly the same model to the bootstrap data to obtain the corresponding MLE, and then constructs the bin counts based on the original data. We examine the test size and power of the new model diagnostic procedure using simulation studies and illustrate it with a real data set.

Illuminator, a desktop program for mutation detection using short-read clonal sequencing.

PubMed

Carr, Ian M; Morgan, Joanne E; Diggle, Christine P; Sheridan, Eamonn; Markham, Alexander F; Logan, Clare V; Inglehearn, Chris F; Taylor, Graham R; Bonthron, David T

2011-10-01

Current methods for sequencing clonal populations of DNA molecules yield several gigabases of data per day, typically comprising reads of < 100 nt. Such datasets permit widespread genome resequencing and transcriptome analysis or other quantitative tasks. However, this huge capacity can also be harnessed for the resequencing of smaller (gene-sized) target regions, through the simultaneous parallel analysis of multiple subjects, using sample "tagging" or "indexing". These methods promise to have a huge impact on diagnostic mutation analysis and candidate gene testing. Here we describe a software package developed for such studies, offering the ability to resolve pooled samples carrying barcode tags and to align reads to a reference sequence using a mutation-tolerant process. The program, Illuminator, can identify rare sequence variants, including insertions and deletions, and permits interactive data analysis on standard desktop computers. It facilitates the effective analysis of targeted clonal sequencer data without dedicated computational infrastructure or specialized training. Copyright © 2011 Elsevier Inc. All rights reserved.

Applying deep neural networks to HEP job classification

NASA Astrophysics Data System (ADS)

Wang, L.; Shi, J.; Yan, X.

2015-12-01

The cluster of IHEP computing center is a middle-sized computing system which provides 10 thousands CPU cores, 5 PB disk storage, and 40 GB/s IO throughput. Its 1000+ users come from a variety of HEP experiments. In such a system, job classification is an indispensable task. Although experienced administrator can classify a HEP job by its IO pattern, it is unpractical to classify millions of jobs manually. We present how to solve this problem with deep neural networks in a supervised learning way. Firstly, we built a training data set of 320K samples by an IO pattern collection agent and a semi-automatic process of sample labelling. Then we implemented and trained DNNs models with Torch. During the process of model training, several meta-parameters was tuned with cross-validations. Test results show that a 5- hidden-layer DNNs model achieves 96% precision on the classification task. By comparison, it outperforms a linear model by 8% precision.

Computational prediction of probabilistic ignition threshold of pressed granular Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) under shock loading

NASA Astrophysics Data System (ADS)

Kim, Seokpum; Miller, Christopher; Horie, Yasuyuki; Molek, Christopher; Welle, Eric; Zhou, Min

2016-09-01

The probabilistic ignition thresholds of pressed granular Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine explosives with average grain sizes between 70 μm and 220 μm are computationally predicted. The prediction uses material microstructure and basic constituent properties and does not involve curve fitting with respect to or prior knowledge of the attributes being predicted. The specific thresholds predicted are James-type relations between the energy flux and energy fluence for given probabilities of ignition. Statistically similar microstructure sample sets are computationally generated and used based on the features of micrographs of materials used in actual experiments. The predicted thresholds are in general agreement with measurements from shock experiments in terms of trends. In particular, it is found that grain size significantly affects the ignition sensitivity of the materials, with smaller sizes leading to lower energy thresholds required for ignition. For example, 50% ignition threshold of the material with an average grain size of 220 μm is approximately 1.4-1.6 times that of the material with an average grain size of 70 μm in terms of energy fluence. The simulations account for the controlled loading of thin-flyer shock experiments with flyer velocities between 1.5 and 4.0 km/s, constituent elasto-viscoplasticity, fracture, post-fracture contact and friction along interfaces, bulk inelastic heating, interfacial frictional heating, and heat conduction. The constitutive behavior of the materials is described using a finite deformation elasto-viscoplastic formulation and the Birch-Murnaghan equation of state. The ignition thresholds are determined via an explicit analysis of the size and temperature states of hotspots in the materials and a hotspot-based ignition criterion. The overall ignition threshold analysis and the microstructure-level hotspot analysis also lead to the definition of a macroscopic ignition parameter (J) and a microscopic ignition risk parameter (R) which are statistically related. The relationships between these parameters are established and delineated.

Comparative analyses of basal rate of metabolism in mammals: data selection does matter.

PubMed

Genoud, Michel; Isler, Karin; Martin, Robert D

2018-02-01

Basal rate of metabolism (BMR) is a physiological parameter that should be measured under strictly defined experimental conditions. In comparative analyses among mammals BMR is widely used as an index of the intensity of the metabolic machinery or as a proxy for energy expenditure. Many databases with BMR values for mammals are available, but the criteria used to select metabolic data as BMR estimates have often varied and the potential effect of this variability has rarely been questioned. We provide a new, expanded BMR database reflecting compliance with standard criteria (resting, postabsorptive state; thermal neutrality; adult, non-reproductive status for females) and examine potential effects of differential selectivity on the results of comparative analyses. The database includes 1739 different entries for 817 species of mammals, compiled from the original sources. It provides information permitting assessment of the validity of each estimate and presents the value closest to a proper BMR for each entry. Using different selection criteria, several alternative data sets were extracted and used in comparative analyses of (i) the scaling of BMR to body mass and (ii) the relationship between brain mass and BMR. It was expected that results would be especially dependent on selection criteria with small sample sizes and with relatively weak relationships. Phylogenetically informed regression (phylogenetic generalized least squares, PGLS) was applied to the alternative data sets for several different clades (Mammalia, Eutheria, Metatheria, or individual orders). For Mammalia, a 'subsampling procedure' was also applied, in which random subsamples of different sample sizes were taken from each original data set and successively analysed. In each case, two data sets with identical sample size and species, but comprising BMR data with different degrees of reliability, were compared. Selection criteria had minor effects on scaling equations computed for large clades (Mammalia, Eutheria, Metatheria), although less-reliable estimates of BMR were generally about 12-20% larger than more-reliable ones. Larger effects were found with more-limited clades, such as sciuromorph rodents. For the relationship between BMR and brain mass the results of comparative analyses were found to depend strongly on the data set used, especially with more-limited, order-level clades. In fact, with small sample sizes (e.g. <100) results often appeared erratic. Subsampling revealed that sample size has a non-linear effect on the probability of a zero slope for a given relationship. Depending on the species included, results could differ dramatically, especially with small sample sizes. Overall, our findings indicate a need for due diligence when selecting BMR estimates and caution regarding results (even if seemingly significant) with small sample sizes. © 2017 Cambridge Philosophical Society.

Design of the value of imaging in enhancing the wellness of your heart (VIEW) trial and the impact of uncertainty on power.

PubMed

Ambrosius, Walter T; Polonsky, Tamar S; Greenland, Philip; Goff, David C; Perdue, Letitia H; Fortmann, Stephen P; Margolis, Karen L; Pajewski, Nicholas M

2012-04-01

Although observational evidence has suggested that the measurement of coronary artery calcium (CAC) may improve risk stratification for cardiovascular events and thus help guide the use of lipid-lowering therapy, this contention has not been evaluated within the context of a randomized trial. The Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) trial is proposed as a randomized study in participants at low intermediate risk of future coronary heart disease (CHD) events to evaluate whether CAC testing leads to improved patient outcomes. To describe the challenges encountered in designing a prototypical screening trial and to examine the impact of uncertainty on power. The VIEW trial was designed as an effectiveness clinical trial to examine the benefit of CAC testing to guide therapy on a primary outcome consisting of a composite of nonfatal myocardial infarction, probable or definite angina with revascularization, resuscitated cardiac arrest, nonfatal stroke (not transient ischemic attack (TIA)), CHD death, stroke death, other atherosclerotic death, or other cardiovascular disease (CVD) death. Many critical choices were faced in designing the trial, including (1) the choice of primary outcome, (2) the choice of therapy, (3) the target population with corresponding ethical issues, (4) specifications of assumptions for sample size calculations, and (5) impact of uncertainty in these assumptions on power/sample size determination. We have proposed a sample size of 30,000 (800 events), which provides 92.7% power. Alternatively, sample sizes of 20,228 (539 events), 23,138 (617 events), and 27,078 (722 events) provide 80%, 85%, and 90% power. We have also allowed for uncertainty in our assumptions by computing average power integrated over specified prior distributions. This relaxation of specificity indicates a reduction in power, dropping to 89.9% (95% confidence interval (CI): 89.8-89.9) for a sample size of 30,000. Samples sizes of 20,228, 23,138, and 27,078 provide power of 78.0% (77.9-78.0), 82.5% (82.5-82.6), and 87.2% (87.2-87.3), respectively. These power estimates are dependent on form and parameters of the prior distributions. Despite the pressing need for a randomized trial to evaluate the utility of CAC testing, conduct of such a trial requires recruiting a large patient population, making efficiency of critical importance. The large sample size is primarily due to targeting a study population at relatively low risk of a CVD event. Our calculations also illustrate the importance of formally considering uncertainty in power calculations of large trials as standard power calculations may tend to overestimate power.

Design of the Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) Trial and the Impact of Uncertainty on Power

PubMed Central

Ambrosius, Walter T.; Polonsky, Tamar S.; Greenland, Philip; Goff, David C.; Perdue, Letitia H.; Fortmann, Stephen P.; Margolis, Karen L.; Pajewski, Nicholas M.

2014-01-01

Background Although observational evidence has suggested that the measurement of CAC may improve risk stratification for cardiovascular events and thus help guide the use of lipid-lowering therapy, this contention has not been evaluated within the context of a randomized trial. The Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) trial is proposed as a randomized study in participants at low intermediate risk of future coronary heart disease (CHD) events to evaluate whether coronary artery calcium (CAC) testing leads to improved patient outcomes. Purpose To describe the challenges encountered in designing a prototypical screening trial and to examine the impact of uncertainty on power. Methods The VIEW trial was designed as an effectiveness clinical trial to examine the benefit of CAC testing to guide therapy on a primary outcome consisting of a composite of non-fatal myocardial infarction, probable or definite angina with revascularization, resuscitated cardiac arrest, non-fatal stroke (not transient ischemic attack (TIA)), CHD death, stroke death, other atherosclerotic death, or other cardiovascular disease (CVD) death. Many critical choices were faced in designing the trial, including: (1) the choice of primary outcome, (2) the choice of therapy, (3) the target population with corresponding ethical issues, (4) specifications of assumptions for sample size calculations, and (5) impact of uncertainty in these assumptions on power/sample size determination. Results We have proposed a sample size of 30,000 (800 events) which provides 92.7% power. Alternatively, sample sizes of 20,228 (539 events), 23,138 (617 events) and 27,078 (722 events) provide 80, 85, and 90% power. We have also allowed for uncertainty in our assumptions by computing average power integrated over specified prior distributions. This relaxation of specificity indicates a reduction in power, dropping to 89.9% (95% confidence interval (CI): 89.8 to 89.9) for a sample size of 30,000. Samples sizes of 20,228, 23,138, and 27,078 provide power of 78.0% (77.9 to 78.0), 82.5% (82.5 to 82.6), and 87.2% (87.2 to 87.3), respectively. Limitations These power estimates are dependent on form and parameters of the prior distributions. Conclusions Despite the pressing need for a randomized trial to evaluate the utility of CAC testing, conduct of such a trial requires recruiting a large patient population, making efficiency of critical importance. The large sample size is primarily due to targeting a study population at relatively low risk of a CVD event. Our calculations also illustrate the importance of formally considering uncertainty in power calculations of large trials as standard power calculations may tend to overestimate power. PMID:22333998

Quantum Computation of Fluid Dynamics

DTIC Science & Technology

1998-02-16

state of the quantum computer’s "memory". With N qubits, the quantum state IT) resides in an exponentially large Hilbert space with 2 N dimensions. A new...size of the Hilbert space in which the entanglement occurs. And to make matters worse, even if a quantum computer was constructed with a large number of...number of qubits "* 2 N is the size of the full Hilbert space "* 2 B is the size of the on-site submanifold, denoted 71 "* B is the size of the

Measurement and Analysis of Porosity in Al-10Si-1Mg Components Additively Manufactured by Selective Laser Melting

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

Rao, Suraj; Cunningham, Ross; Ozturk, Tugce

Aluminum alloys are candidate materials for weight critical applications because of their excellent strength and stiffness to weight ratio. However, defects such as voids decrease the strength and fatigue life of these alloys, which can limit the application of Selective Laser Melting. In this study, the average volume fraction, average size, and size distribution of pores in Al10-Si-1Mg samples built using Selective Laser Melting have been characterized. Synchrotron high energy X-rays were used to perform computed tomography on volumes of order one cubic millimeter with a resolution of approximately 1.5 μm. Substantial variations in the pore size distributions were foundmore » as a function of process conditions. Even under conditions that ensured that all locations were melted at least once, a significant number density was found of pores above 5 μm in diameter.« less

Preliminary investigation on the effects of primary airflow to coal particle distribution in coal-fired boilers

NASA Astrophysics Data System (ADS)

Noor, N. A. W. Mohd; Hassan, H.; Hashim, M. F.; Hasini, H.; Munisamy, K. M.

2017-04-01

This paper presents an investigation on the effects of primary airflow to coal fineness in coal-fired boilers. In coal fired power plant, coal is pulverized in a pulverizer, and it is then transferred to boiler for combustion. Coal need to be ground to its desired size to obtain maximum combustion efficiency. Coarse coal particle size may lead to many performance problems such as formation of clinker. In this study, the effects of primary airflow to coal particles size and coal flow distribution were investigated by using isokinetic coal sampling and computational fluid dynamic (CFD) modelling. Four different primary airflows were tested and the effects to resulting coal fineness were recorded. Results show that the optimum coal fineness distribution is obtained at design primary airflow. Any reduction or increase of air flow rate results in undesirable coal fineness distribution.

Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors.

PubMed

Ranasinghe, P; Wathurapatha, W S; Perera, Y S; Lamabadusuriya, D A; Kulatunga, S; Jayawardana, N; Katulanda, P

2016-03-09

Computer vision syndrome (CVS) is a group of visual symptoms experienced in relation to the use of computers. Nearly 60 million people suffer from CVS globally, resulting in reduced productivity at work and reduced quality of life of the computer worker. The present study aims to describe the prevalence of CVS and its associated factors among a nationally-representative sample of Sri Lankan computer workers. Two thousand five hundred computer office workers were invited for the study from all nine provinces of Sri Lanka between May and December 2009. A self-administered questionnaire was used to collect socio-demographic data, symptoms of CVS and its associated factors. A binary logistic regression analysis was performed in all patients with 'presence of CVS' as the dichotomous dependent variable and age, gender, duration of occupation, daily computer usage, pre-existing eye disease, not using a visual display terminal (VDT) filter, adjusting brightness of screen, use of contact lenses, angle of gaze and ergonomic practices knowledge as the continuous/dichotomous independent variables. A similar binary logistic regression analysis was performed in all patients with 'severity of CVS' as the dichotomous dependent variable and other continuous/dichotomous independent variables. Sample size was 2210 (response rate-88.4%). Mean age was 30.8 ± 8.1 years and 50.8% of the sample were males. The 1-year prevalence of CVS in the study population was 67.4%. Female gender (OR: 1.28), duration of occupation (OR: 1.07), daily computer usage (1.10), pre-existing eye disease (OR: 4.49), not using a VDT filter (OR: 1.02), use of contact lenses (OR: 3.21) and ergonomics practices knowledge (OR: 1.24) all were associated with significantly presence of CVS. The duration of occupation (OR: 1.04) and presence of pre-existing eye disease (OR: 1.54) were significantly associated with the presence of 'severe CVS'. Sri Lankan computer workers had a high prevalence of CVS. Female gender, longer duration of occupation, higher daily computer usage, pre-existing eye disease, not using a VDT filter, use of contact lenses and higher ergonomics practices knowledge all were associated with significantly with the presence of CVS. The factors associated with the severity of CVS were the duration of occupation and presence of pre-existing eye disease.

SAHARA: A package of PC computer programs for estimating both log-hyperbolic grain-size parameters and standard moments

NASA Astrophysics Data System (ADS)

Christiansen, Christian; Hartmann, Daniel

This paper documents a package of menu-driven POLYPASCAL87 computer programs for handling grouped observations data from both sieving (increment data) and settling tube procedures (cumulative data). The package is designed deliberately for use on IBM-compatible personal computers. Two of the programs solve the numerical problem of determining the estimates of the four (main) parameters of the log-hyperbolic distribution and their derivatives. The package also contains a program for determining the mean, sorting, skewness. and kurtosis according to the standard moments. Moreover, the package contains procedures for smoothing and grouping of settling tube data. A graphic part of the package plots the data in a log-log plot together with the estimated log-hyperbolic curve. Along with the plot follows all estimated parameters. Another graphic option is a plot of the log-hyperbolic shape triangle with the (χ,ζ) position of the sample.

Computer code for preliminary sizing analysis of axial-flow turbines

NASA Technical Reports Server (NTRS)

Glassman, Arthur J.

1992-01-01

This mean diameter flow analysis uses a stage average velocity diagram as the basis for the computational efficiency. Input design requirements include power or pressure ratio, flow rate, temperature, pressure, and rotative speed. Turbine designs are generated for any specified number of stages and for any of three types of velocity diagrams (symmetrical, zero exit swirl, or impulse) or for any specified stage swirl split. Exit turning vanes can be included in the design. The program output includes inlet and exit annulus dimensions, exit temperature and pressure, total and static efficiencies, flow angles, and last stage absolute and relative Mach numbers. An analysis is presented along with a description of the computer program input and output with sample cases. The analysis and code presented herein are modifications of those described in NASA-TN-D-6702. These modifications improve modeling rigor and extend code applicability.

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets

PubMed Central

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

Background As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Methods Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Results Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Conclusions Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. PMID:24464852

Quantitative and Qualitative Aspects of Gas-Metal-Oxide Mass Transfer in High-Temperature Confocal Scanning Laser Microscopy

NASA Astrophysics Data System (ADS)

Piva, Stephano P. T.; Pistorius, P. Chris; Webler, Bryan A.

2018-05-01

During high-temperature confocal scanning laser microscopy (HT-CSLM) of liquid steel samples, thermal Marangoni flow and rapid mass transfer between the sample and its surroundings occur due to the relatively small sample size (diameter around 5 mm) and large temperature gradients. The resulting evaporation and steel-slag reactions tend to change the chemical composition in the metal. Such mass transfer effects can change observed nonmetallic inclusions. This work quantifies oxide-metal-gas mass transfer of solutes during HT-CSLM experiments using computational simulations and experimental data for (1) dissolution of MgO inclusions in the presence and absence of slag and (2) Ca, Mg-silicate inclusion changes upon exposure of a Si-Mn-killed steel to an oxidizing gas atmosphere.

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

PubMed

Bergh, Daniel

2015-01-01

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

Explanation of Two Anomalous Results in Statistical Mediation Analysis.

PubMed

Fritz, Matthew S; Taylor, Aaron B; Mackinnon, David P

2012-01-01

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M , a , increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y , b , was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a . Implications of these findings are discussed.

Birds in space and time: genetic changes accompanying anthropogenic habitat fragmentation in the endangered black-capped vireo (Vireo atricapilla)

PubMed Central

Athrey, Giridhar; Barr, Kelly R; Lance, Richard F; Leberg, Paul L

2012-01-01

Anthropogenic alterations in the natural environment can be a potent evolutionary force. For species that have specific habitat requirements, habitat loss can result in substantial genetic effects, potentially impeding future adaptability and evolution. The endangered black-capped vireo (Vireo atricapilla) suffered a substantial contraction of breeding habitat and population size during much of the 20th century. In a previous study, we reported significant differentiation between remnant populations, but failed to recover a strong genetic signal of bottlenecks. In this study, we used a combination of historical and contemporary sampling from Oklahoma and Texas to (i) determine whether population structure and genetic diversity have changed over time and (ii) evaluate alternate demographic hypotheses using approximate Bayesian computation (ABC). We found lower genetic diversity and increased differentiation in contemporary samples compared to historical samples, indicating nontrivial impacts of fragmentation. ABC analysis suggests a bottleneck having occurred in the early part of the 20th century, resulting in a magnitude decline in effective population size. Genetic monitoring with temporally spaced samples, such as used in this study, can be highly informative for assessing the genetic impacts of anthropogenic fragmentation on threatened or endangered species, as well as revealing the dynamics of small populations over time. PMID:23028396

Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

An experimental platform for triaxial high-pressure/high-temperature testing of rocks using computed tomography

NASA Astrophysics Data System (ADS)

Glatz, Guenther; Lapene, Alexandre; Castanier, Louis M.; Kovscek, Anthony R.

2018-04-01

A conventional high-pressure/high-temperature experimental apparatus for combined geomechanical and flow-through testing of rocks is not X-ray compatible. Additionally, current X-ray transparent systems for computed tomography (CT) of cm-sized samples are limited to design temperatures below 180 °C. We describe a novel, high-temperature (>400 °C), high-pressure (>2000 psi/>13.8 MPa confining, >10 000 psi/>68.9 MPa vertical load) triaxial core holder suitable for X-ray CT scanning. The new triaxial system permits time-lapse imaging to capture the role of effective stress on fluid distribution and porous medium mechanics. System capabilities are demonstrated using ultimate compressive strength (UCS) tests of Castlegate sandstone. In this case, flooding the porous medium with a radio-opaque gas such as krypton before and after the UCS test improves the discrimination of rock features such as fractures. The results of high-temperature tests are also presented. A Uintah Basin sample of immature oil shale is heated from room temperature to 459 °C under uniaxial compression. The sample contains kerogen that pyrolyzes as temperature rises, releasing hydrocarbons. Imaging reveals the formation of stress bands as well as the evolution and connectivity of the fracture network within the sample as a function of time.

An experimental platform for triaxial high-pressure/high-temperature testing of rocks using computed tomography.

PubMed

Glatz, Guenther; Lapene, Alexandre; Castanier, Louis M; Kovscek, Anthony R

2018-04-01

A conventional high-pressure/high-temperature experimental apparatus for combined geomechanical and flow-through testing of rocks is not X-ray compatible. Additionally, current X-ray transparent systems for computed tomography (CT) of cm-sized samples are limited to design temperatures below 180 °C. We describe a novel, high-temperature (>400 °C), high-pressure (>2000 psi/>13.8 MPa confining, >10 000 psi/>68.9 MPa vertical load) triaxial core holder suitable for X-ray CT scanning. The new triaxial system permits time-lapse imaging to capture the role of effective stress on fluid distribution and porous medium mechanics. System capabilities are demonstrated using ultimate compressive strength (UCS) tests of Castlegate sandstone. In this case, flooding the porous medium with a radio-opaque gas such as krypton before and after the UCS test improves the discrimination of rock features such as fractures. The results of high-temperature tests are also presented. A Uintah Basin sample of immature oil shale is heated from room temperature to 459 °C under uniaxial compression. The sample contains kerogen that pyrolyzes as temperature rises, releasing hydrocarbons. Imaging reveals the formation of stress bands as well as the evolution and connectivity of the fracture network within the sample as a function of time.

A Multi-Wavelength View of Planet Forming Regions: Unleashing the Full Power of ALMA

NASA Astrophysics Data System (ADS)

Tazzari, Marco

2017-11-01

Observations at sub-mm/mm wavelengths allow us to probe the solids in the interior of protoplanetary disks, where the bulk of the dust is located and planet formation is expected to occur. However, the actual size of dust grains is still largely unknown due to the limited angular resolution and sensitivity of past observations. The upgraded VLA and, especially, the ALMA observatories provide now powerful tools to resolve grain growth in disks, making the time ripe for developing a multi-wavelength analysis of sub-mm/mm observations of disks. In my contribution I will present a novel analysis method for multi-wavelength ALMA/VLA observations which, based on the self-consistent modelling of the sub-mm/mm disk continuum emission, allows us to constrain simultaneously the size distribution of dust grains and the disk's physical structure (Tazzari et al. 2016, A&A 588 A53). I will also present the recent analysis of spatially resolved ALMA Band 7 observations of a large sample of disks in the Lupus star forming region, from which we obtained a tentative evidence of a disk size-disk mass correlation (Tazzari et al. 2017, arXiv:1707.01499). Finally, I will introduce galario, a GPU Accelerated Library for the Analysis of Radio Interferometry Observations. Fitting the observed visibilities in the uv-plane is computationally demanding: with galario we solve this problem for the current as well as for the full-science ALMA capabilities by leveraging on the computing power of GPUs, providing the computational breakthrough needed to fully exploit the new wealth of information delivered by ALMA.

Velocity profile, water-surface slope, and bed-material size for selected streams in Colorado

USGS Publications Warehouse

Marchand, J.P.; Jarrett, R.D.; Jones, L.L.

1984-01-01

Existing methods for determining the mean velocity in a vertical sampling section do not address the conditions present in high-gradient, shallow-depth streams common to mountainous regions such as Colorado. The report presents velocity-profile data that were collected for 11 streamflow-gaging stations in Colorado using both a standard Price type AA current meter and a prototype Price Model PAA current meter. Computational results are compiled that will enable mean velocities calculated from measurements by the two current meters to be compared with each other and with existing methods for determining mean velocity. Water-surface slope, bed-material size, and flow-characteristic data for the 11 sites studied also are presented. (USGS)

A variable resolution x-ray detector for computed tomography: I. Theoretical basis and experimental verification.

PubMed

DiBianca, F A; Gupta, V; Zeman, H D

2000-08-01

A computed tomography imaging technique called variable resolution x-ray (VRX) detection provides detector resolution ranging from that of clinical body scanning to that of microscopy (1 cy/mm to 100 cy/mm). The VRX detection technique is based on a new principle denoted as "projective compression" that allows the detector resolution element to scale proportionally to the image field size. Two classes of VRX detector geometry are considered. Theoretical aspects related to x-ray physics and data sampling are presented. Measured resolution parameters (line-spread function and modulation-transfer function) are presented and discussed. A VRX image that resolves a pair of 50 micron tungsten hairs spaced 30 microns apart is shown.

Efficient matrix approach to optical wave propagation and Linear Canonical Transforms.

PubMed

Shakir, Sami A; Fried, David L; Pease, Edwin A; Brennan, Terry J; Dolash, Thomas M

2015-10-05

The Fresnel diffraction integral form of optical wave propagation and the more general Linear Canonical Transforms (LCT) are cast into a matrix transformation form. Taking advantage of recent efficient matrix multiply algorithms, this approach promises an efficient computational and analytical tool that is competitive with FFT based methods but offers better behavior in terms of aliasing, transparent boundary condition, and flexibility in number of sampling points and computational window sizes of the input and output planes being independent. This flexibility makes the method significantly faster than FFT based propagators when only a single point, as in Strehl metrics, or a limited number of points, as in power-in-the-bucket metrics, are needed in the output observation plane.

Computed microtomography and X-ray fluorescence analysis for comprehensive analysis of structural changes in bone.

PubMed

Buzmakov, Alexey; Chukalina, Marina; Nikolaev, Dmitry; Schaefer, Gerald; Gulimova, Victoria; Saveliev, Sergey; Tereschenko, Elena; Seregin, Alexey; Senin, Roman; Prun, Victor; Zolotov, Denis; Asadchikov, Victor

2013-01-01

This paper presents the results of a comprehensive analysis of structural changes in the caudal vertebrae of Turner's thick-toed geckos by computer microtomography and X-ray fluorescence analysis. We present algorithms used for the reconstruction of tomographic images which allow to work with high noise level projections that represent typical conditions dictated by the nature of the samples. Reptiles, due to their ruggedness, small size, belonging to the amniote and a number of other valuable features, are an attractive model object for long-orbital experiments on unmanned spacecraft. Issues of possible changes in their bone tissue under the influence of spaceflight are the subject of discussions between biologists from different laboratories around the world.

Characterization and Computational Modeling of Minor Phases in Alloy LSHR

NASA Technical Reports Server (NTRS)

Jou, Herng-Jeng; Olson, Gregory; Gabb, Timothy; Garg, Anita; Miller, Derek

2012-01-01

The minor phases of powder metallurgy disk superalloy LSHR were studied. Samples were consistently heat treated at three different temperatures for long times to approach equilibrium. Additional heat treatments were also performed for shorter times, to assess minor phase kinetics in non-equilibrium conditions. Minor phases including MC carbides, M23C6 carbides, M3B2 borides, and sigma were identified. Their average sizes and total area fractions were determined. CALPHAD thermodynamics databases and PrecipiCalc(TradeMark), a computational precipitation modeling tool, were employed with Ni-base thermodynamics and diffusion databases to model and simulate the phase microstructural evolution observed in the experiments with an objective to identify the model limitations and the directions of model enhancement.

New NAS Parallel Benchmarks Results

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; Saphir, William; VanderWijngaart, Rob; Woo, Alex; Kutler, Paul (Technical Monitor)

1997-01-01

NPB2 (NAS (NASA Advanced Supercomputing) Parallel Benchmarks 2) is an implementation, based on Fortran and the MPI (message passing interface) message passing standard, of the original NAS Parallel Benchmark specifications. NPB2 programs are run with little or no tuning, in contrast to NPB vendor implementations, which are highly optimized for specific architectures. NPB2 results complement, rather than replace, NPB results. Because they have not been optimized by vendors, NPB2 implementations approximate the performance a typical user can expect for a portable parallel program on distributed memory parallel computers. Together these results provide an insightful comparison of the real-world performance of high-performance computers. New NPB2 features: New implementation (CG), new workstation class problem sizes, new serial sample versions, more performance statistics.

System design of the annular suspension and pointing system /ASPS/

NASA Technical Reports Server (NTRS)

Cunningham, D. C.; Gismondi, T. P.; Wilson, G. W.

1978-01-01

This paper presents the control system design for the Annular Suspension and Pointing System. Actuator sizing and configuration of the system are explained, and the control laws developed for linearizing and compensating the magnetic bearings, roll induction motor and gimbal torquers are given. Decoupling, feedforward and error compensation for the vernier and gimbal controllers is developed. The algorithm for computing the strapdown attitude reference is derived, and the allowable sampling rates, time delays and quantization of control signals are specified.

Morphology of methane hydrate host sediments

USGS Publications Warehouse

Jones, K.W.; Feng, H.; Tomov, S.; Winters, W.J.; Eaton, M.; Mahajan, D.

2005-01-01

The morphological features including porosity and grains of methane hydrate host sediments were investigated using synchrotron computed microtomography (CMT) technique. The sediment sample was obtained during Ocean Drilling Program Leg 164 on the Blake Ridge at water depth of 2278.5 m. The CMT experiment was performed at the Brookhaven National Synchrotron Light Source facility. The analysis gave ample porosity, specific surface area, mean particle size, and tortuosity. The method was found to be highly effective for the study of methane hydrate host sediments.

Multiprocessor Z-Buffer Architecture for High-Speed, High Complexity Computer Image Generation.

DTIC Science & Technology

1983-12-01

Oversampling 50 17. "Poking Through" Effects 51 18. Sampling Paths 52 19. Triangle Variables 54 20. Intelligent Tiling Algorithm 61 21. Tiler Functional Blocks...64 * 22. HSD Interface 65 23. Tiling Machine Setup 67 24. Tiling Machine 68 25. Tile Accumulate 69 26. A lx$ Sorting Machine 77 27. A 2x8 Sorting...Delay 227 87. Effect of Triangle Size on Tiler Throughput Rates 229 88. Tiling Machine Setup Stage Performance for Oversample Mode 234 89. Tiling

Determining Representative Elementary Volume For Multiple Petrophysical Parameters using a Convex Hull Analysis of Digital Rock Data

NASA Astrophysics Data System (ADS)

Shah, S.; Gray, F.; Yang, J.; Crawshaw, J.; Boek, E.

2016-12-01

Advances in 3D pore-scale imaging and computational methods have allowed an exceptionally detailed quantitative and qualitative analysis of the fluid flow in complex porous media. A fundamental problem in pore-scale imaging and modelling is how to represent and model the range of scales encountered in porous media, starting from the smallest pore spaces. In this study, a novel method is presented for determining the representative elementary volume (REV) of a rock for several parameters simultaneously. We calculate the two main macroscopic petrophysical parameters, porosity and single-phase permeability, using micro CT imaging and Lattice Boltzmann (LB) simulations for 14 different porous media, including sandpacks, sandstones and carbonates. The concept of the `Convex Hull' is then applied to calculate the REV for both parameters simultaneously using a plot of the area of the convex hull as a function of the sub-volume, capturing the different scales of heterogeneity from the pore-scale imaging. The results also show that the area of the convex hull (for well-chosen parameters such as the log of the permeability and the porosity) decays exponentially with sub-sample size suggesting a computationally efficient way to determine the system size needed to calculate the parameters to high accuracy (small convex hull area). Finally we propose using a characteristic length such as the pore size to choose an efficient absolute voxel size for the numerical rock.

HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS

PubMed Central

Wang, Shuang; Zhang, Yuchen; Dai, Wenrui; Lauter, Kristin; Kim, Miran; Tang, Yuzhe; Xiong, Hongkai; Jiang, Xiaoqian

2016-01-01

Motivation: Genome-wide association studies (GWAS) have been widely used in discovering the association between genotypes and phenotypes. Human genome data contain valuable but highly sensitive information. Unprotected disclosure of such information might put individual’s privacy at risk. It is important to protect human genome data. Exact logistic regression is a bias-reduction method based on a penalized likelihood to discover rare variants that are associated with disease susceptibility. We propose the HEALER framework to facilitate secure rare variants analysis with a small sample size. Results: We target at the algorithm design aiming at reducing the computational and storage costs to learn a homomorphic exact logistic regression model (i.e. evaluate P-values of coefficients), where the circuit depth is proportional to the logarithmic scale of data size. We evaluate the algorithm performance using rare Kawasaki Disease datasets. Availability and implementation: Download HEALER at http://research.ucsd-dbmi.org/HEALER/ Contact: shw070@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26446135

Design of focused and restrained subsets from extremely large virtual libraries.

PubMed

Jamois, Eric A; Lin, Chien T; Waldman, Marvin

2003-11-01

With the current and ever-growing offering of reagents along with the vast palette of organic reactions, virtual libraries accessible to combinatorial chemists can reach sizes of billions of compounds or more. Extracting practical size subsets for experimentation has remained an essential step in the design of combinatorial libraries. A typical approach to computational library design involves enumeration of structures and properties for the entire virtual library, which may be unpractical for such large libraries. This study describes a new approach termed as on the fly optimization (OTFO) where descriptors are computed as needed within the subset optimization cycle and without intermediate enumeration of structures. Results reported herein highlight the advantages of coupling an ultra-fast descriptor calculation engine to subset optimization capabilities. We also show that enumeration of properties for the entire virtual library may not only be unpractical but also wasteful. Successful design of focused and restrained subsets can be achieved while sampling only a small fraction of the virtual library. We also investigate the stability of the method and compare results obtained from simulated annealing (SA) and genetic algorithms (GA).

Perspective: Size selected clusters for catalysis and electrochemistry

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

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro

We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

Perspective: Size selected clusters for catalysis and electrochemistry

DOE PAGES

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; ...

2018-03-15

We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

Perspective: Size selected clusters for catalysis and electrochemistry

NASA Astrophysics Data System (ADS)

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; Vajda, Stefan

2018-03-01

Size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization, and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions, and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modeling based on density functional theory sampling of local minima and energy barriers or ab initio molecular dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Finally, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.

Disease-Concordant Twins Empower Genetic Association Studies.

PubMed

Tan, Qihua; Li, Weilong; Vandin, Fabio

2017-01-01

Genome-wide association studies with moderate sample sizes are underpowered, especially when testing SNP alleles with low allele counts, a situation that may lead to high frequency of false-positive results and lack of replication in independent studies. Related individuals, such as twin pairs concordant for a disease, should confer increased power in genetic association analysis because of their genetic relatedness. We conducted a computer simulation study to explore the power advantage of the disease-concordant twin design, which uses singletons from disease-concordant twin pairs as cases and ordinary healthy samples as controls. We examined the power gain of the twin-based design for various scenarios (i.e., cases from monozygotic and dizygotic twin pairs concordant for a disease) and compared the power with the ordinary case-control design with cases collected from the unrelated patient population. Simulation was done by assigning various allele frequencies and allelic relative risks for different mode of genetic inheritance. In general, for achieving a power estimate of 80%, the sample sizes needed for dizygotic and monozygotic twin cases were one half and one fourth of the sample size of an ordinary case-control design, with variations depending on genetic mode. Importantly, the enriched power for dizygotic twins also applies to disease-concordant sibling pairs, which largely extends the application of the concordant twin design. Overall, our simulation revealed a high value of disease-concordant twins in genetic association studies and encourages the use of genetically related individuals for highly efficiently identifying both common and rare genetic variants underlying human complex diseases without increasing laboratory cost. © 2016 John Wiley & Sons Ltd/University College London.

Children and computer use in the home: workstations, behaviors and parental attitudes.

PubMed

Kimmerly, Lisa; Odell, Dan

2009-01-01

This study examines the home computer use of 26 children (aged 6-18) in ten upper middle class families using direct observation, typing tests, questionnaires and semi-structured interviews. The goals of the study were to gather information on how children use computers in the home and to understand how both parents and children perceive this computer use. Large variations were seen in computing skills, behaviors, and opinions, as well as equipment and workstation setups. Typing speed averaged over 40 words per minute for children over 13 years old, and less than 10 words per minute for children younger than 10. The results show that for this sample, Repetitive Stress Injury (RSI) concerns ranked very low among parents, whereas security and privacy concerns ranked much higher. Meanwhile, children's behaviors and workstations were observed to place children in awkward working postures. Photos showing common postures are presented. The greatest opportunity to improve children's work postures appears to be in providing properly-sized work surfaces and chairs, as well as education. Possible explanations for the difference between parental perception of computing risks and the physical reality of children's observed ergonomics are discussed and ideas for further research are proposed.

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

Whitledge, T.E.; Malloy, S.C.; Patton, C.J.

This manual was assembled for use as a guide for analyzing the nutrient content of seawater samples collected in the marine coastal zone of the Northeast United States and the Bering Sea. Some modifications (changes in dilution or sample pump tube sizes) may be necessary to achieve optimum measurements in very pronounced oligotrophic, eutrophic or brackish areas. Information is presented under the following section headings: theory and mechanics of automated analysis; continuous flow system description; operation of autoanalyzer system; cookbook of current nutrient methods; automated analyzer and data analysis software; computer interfacing and hardware modifications; and trouble shooting. The threemore » appendixes are entitled: references and additional reading; manifold components and chemicals; and software listings. (JGB)« less

Micromachined chemical jet dispenser

DOEpatents

Swierkowski, S.P.

1999-03-02

A dispenser is disclosed for chemical fluid samples that need to be precisely ejected in size, location, and time. The dispenser is a micro-electro-mechanical systems (MEMS) device fabricated in a bonded silicon wafer and a substrate, such as glass or silicon, using integrated circuit-like fabrication technology which is amenable to mass production. The dispensing is actuated by ultrasonic transducers that efficiently produce a pressure wave in capillaries that contain the chemicals. The 10-200 {micro}m diameter capillaries can be arranged to focus in one spot or may be arranged in a larger dense linear array (ca. 200 capillaries). The dispenser is analogous to some ink jet print heads for computer printers but the fluid is not heated, thus not damaging certain samples. Major applications are in biological sample handling and in analytical chemical procedures such as environmental sample analysis, medical lab analysis, or molecular biology chemistry experiments. 4 figs.

Micromachined chemical jet dispenser

DOEpatents

Swierkowski, Steve P.

1999-03-02

A dispenser for chemical fluid samples that need to be precisely ejected in size, location, and time. The dispenser is a micro-electro-mechanical systems (MEMS) device fabricated in a bonded silicon wafer and a substrate, such as glass or silicon, using integrated circuit-like fabrication technology which is amenable to mass production. The dispensing is actuated by ultrasonic transducers that efficiently produce a pressure wave in capillaries that contain the chemicals. The 10-200 .mu.m diameter capillaries can be arranged to focus in one spot or may be arranged in a larger dense linear array (.about.200 capillaries). The dispenser is analogous to some ink jet print heads for computer printers but the fluid is not heated, thus not damaging certain samples. Major applications are in biological sample handling and in analytical chemical procedures such as environmental sample analysis, medical lab analysis, or molecular biology chemistry experiments.

Impairments of colour vision induced by organic solvents: a meta-analysis study.

PubMed

Paramei, Galina V; Meyer-Baron, Monika; Seeber, Andreas

2004-09-01

The impairment of colour discrimination induced by occupational exposure to toluene, styrene and mixtures of organic solvents is reviewed and analysed using a meta-analytical approach. Thirty-nine studies were surveyed covering a wide range of exposure conditions. Those studies using the Lanthony Panel D-15 desaturated test (D-15d) were further considered. From these for 15 samples data on colour discrimination ability (Colour Confusion Index, CCI) and exposure levels were provided, required for the meta-analysis. In accordance with previously reported higher CCI values for the exposed groups, the computations yielded positive effect sizes for 13 of the 15 samples, indicating that in the great majority of the studies the exposed groups showed inferior colour discrimination. However, the meta-analysis showed great variation in effect sizes across the studies. Possible reasons for inconsistency among the reported findings are discussed. These pertain to exposure-related parameters, as well as to confounders such as conditions of test administration and characteristics of subject samples. Those factors vary considerably among the studies and might have greatly contributed to divergence in measured colour vision capacity, thereby obscuring consistent effects of organic solvents on colour discrimination.

Genetics of wellbeing and its components satisfaction with life, happiness, and quality of life: a review and meta-analysis of heritability studies.

PubMed

Bartels, Meike

2015-03-01

Wellbeing is a major topic of research across several disciplines, reflecting the increasing recognition of its strong value across major domains in life. Previous twin-family studies have revealed that individual differences in wellbeing are accounted for by both genetic as well as environmental factors. A systematic literature search identified 30 twin-family studies on wellbeing or a related measure such as satisfaction with life or happiness. Review of these studies showed considerable variation in heritability estimates (ranging from 0 to 64 %), which makes it difficult to draw firm conclusions regarding the genetic influences on wellbeing. For overall wellbeing twelve heritability estimates, from 10 independent studies, were meta-analyzed by computing a sample size weighted average heritability. Ten heritability estimates, derived from 9 independent samples, were used for the meta-analysis of satisfaction with life. The weighted average heritability of wellbeing, based on a sample size of 55,974 individuals, was 36 % (34-38), while the weighted average heritability for satisfaction with life was 32 % (29-35) (n = 47,750). With this result a more robust estimate of the relative influence of genetic effects on wellbeing is provided.

Effect of Layer Thickness and Printing Orientation on Mechanical Properties and Dimensional Accuracy of 3D Printed Porous Samples for Bone Tissue Engineering

PubMed Central

Farzadi, Arghavan; Solati-Hashjin, Mehran; Asadi-Eydivand, Mitra; Abu Osman, Noor Azuan

2014-01-01

Powder-based inkjet 3D printing method is one of the most attractive solid free form techniques. It involves a sequential layering process through which 3D porous scaffolds can be directly produced from computer-generated models. 3D printed products' quality are controlled by the optimal build parameters. In this study, Calcium Sulfate based powders were used for porous scaffolds fabrication. The printed scaffolds of 0.8 mm pore size, with different layer thickness and printing orientation, were subjected to the depowdering step. The effects of four layer thicknesses and printing orientations, (parallel to X, Y and Z), on the physical and mechanical properties of printed scaffolds were investigated. It was observed that the compressive strength, toughness and Young's modulus of samples with 0.1125 and 0.125 mm layer thickness were more than others. Furthermore, the results of SEM and μCT analyses showed that samples with 0.1125 mm layer thickness printed in X direction have more dimensional accuracy and significantly close to CAD software based designs with predefined pore size, porosity and pore interconnectivity. PMID:25233468

MD-based computational design of new engineered Ni-based nanocatalysts: An in-depth study of the underlying mechanism

NASA Astrophysics Data System (ADS)

Kardani, Arash; Mehrafrooz, Behzad; Montazeri, Abbas

2018-03-01

Porous nickel-based nanocatalysts have attracted great attention thanks to their high surface-to-volume ratio and desired mechanical properties. One of the major challenges associated with their applications is weakening their shear properties due to their contact with the high fluid flow values at elevated service temperatures. On the other hand, their shear behavior is dominantly influenced by the size and distribution of pores available in their structure. In this study, different nickel samples containing periodic distribution surface porosities with 2 nm diameter are examined via molecular dynamics simulation. Moreover, to explore the effects of porosities distribution, the obtained results are compared with those of the samples having concentrated pores at the bigger size of 10nm. Accordingly, shear loading conditions are imposed to capture the dependency of the shear characteristics of the samples on the location and on the geometrical factors of the aforementioned porosities. Surprisingly, it is revealed that the existence of randomly distributed pores can lead to an enhancement of their yield strain compared to that of non-porous counterparts. The underlying mechanism governing this special behavior is thoroughly studied employing several case studies.

Design and Analysis of an Isokinetic Sampling Probe for Submicron Particle Measurements at High Altitude

NASA Technical Reports Server (NTRS)

Heath, Christopher M.

2012-01-01

An isokinetic dilution probe has been designed with the aid of computational fluid dynamics to sample sub-micron particles emitted from aviation combustion sources. The intended operational range includes standard day atmospheric conditions up to 40,000-ft. With dry nitrogen as the diluent, the probe is intended to minimize losses from particle microphysics and transport while rapidly quenching chemical kinetics. Initial results indicate that the Mach number ratio of the aerosol sample and dilution streams in the mixing region is an important factor for successful operation. Flow rate through the probe tip was found to be highly sensitive to the static pressure at the probe exit. Particle losses through the system were estimated to be on the order of 50% with minimal change in the overall particle size distribution apparent. Following design refinement, experimental testing and validation will be conducted in the Particle Aerosol Laboratory, a research facility located at the NASA Glenn Research Center to study the evolution of aviation emissions at lower stratospheric conditions. Particle size distributions and number densities from various combustion sources will be used to better understand particle-phase microphysics, plume chemistry, evolution to cirrus, and environmental impacts of aviation.

Methods for Investigating Mercury Speciation, Transport, Methylation, and Bioaccumulation in Watersheds Affected by Historical Mining

NASA Astrophysics Data System (ADS)

Alpers, C. N.; Marvin-DiPasquale, M. C.; Fleck, J.; Ackerman, J. T.; Eagles-Smith, C.; Stewart, A. R.; Windham-Myers, L.

2016-12-01

Many watersheds in the western U.S. have mercury (Hg) contamination from historical mining of Hg and precious metals (gold and silver), which were concentrated using Hg amalgamation (mid 1800's to early 1900's). Today, specialized sampling and analytical protocols for characterizing Hg and methylmercury (MeHg) in water, sediment, and biota generate high-quality data to inform management of land, water, and biological resources. Collection of vertically and horizontally integrated water samples in flowing streams and use of a Teflon churn splitter or cone splitter ensure that samples and subsamples are representative. Both dissolved and particulate components of Hg species in water are quantified because each responds to different hydrobiogeochemical processes. Suspended particles trapped on pre-combusted (Hg-free) glass- or quartz-fiber filters are analyzed for total mercury (THg), MeHg, and reactive divalent mercury. Filtrates are analyzed for THg and MeHg to approximate the dissolved fraction. The sum of concentrations in particulate and filtrate fractions represents whole water, equivalent to an unfiltered sample. This approach improves upon analysis of filtered and unfiltered samples and computation of particulate concentration by difference; volume filtered is adjusted based on suspended-sediment concentration to minimize particulate non-detects. Information from bed-sediment sampling is enhanced by sieving into multiple size fractions and determining detailed grain-size distribution. Wet sieving ensures particle disaggregation; sieve water is retained and fines are recovered by centrifugation. Speciation analysis by sequential extraction and examination of heavy mineral concentrates by scanning electron microscopy provide additional information regarding Hg mineralogy and geochemistry. Biomagnification of MeHg in food webs is tracked using phytoplankton, zooplankton, aquatic and emergent vegetation, invertebrates, fish, and birds. Analysis of zooplankton in multiple size fractions from multiple depths in reservoirs can provide insight into food-web dynamics. The presentation will highlight application of these methods in several Hg-contaminated watersheds, with emphasis on understanding seasonal variability in designing effective sampling strategies.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

PubMed Central

Kurkcuoglu, Zeynep; Bahar, Ivet; Doruker, Pemra

2016-01-01

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events. PMID:27494296

Comparing Server Energy Use and Efficiency Using Small Sample Sizes

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

Coles, Henry C.; Qin, Yong; Price, Phillip N.

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 andmore » 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 group is similar to all other components as a group. However, some differences were observed. The Supermicro server used 27 percent more power at idle compared to the other brands. The Intel server had a power supply control feature called cold redundancy, and the data suggest that cold redundancy can provide energy savings at low power levels. Test and evaluation methods that might be used by others having limited resources for IT equipment evaluation are explained in the report.« less

Pore formation during dehydration of a polycrystalline gypsum sample observed and quantified in a time-series synchrotron X-ray micro-tomography experiment

NASA Astrophysics Data System (ADS)

Fusseis, F.; Schrank, C.; Liu, J.; Karrech, A.; Llana-Fúnez, S.; Xiao, X.; Regenauer-Lieb, K.

2012-03-01

We conducted an in-situ X-ray micro-computed tomography heating experiment at the Advanced Photon Source (USA) to dehydrate an unconfined 2.3 mm diameter cylinder of Volterra Gypsum. We used a purpose-built X-ray transparent furnace to heat the sample to 388 K for a total of 310 min to acquire a three-dimensional time-series tomography dataset comprising nine time steps. The voxel size of 2.2 μm3 proved sufficient to pinpoint reaction initiation and the organization of drainage architecture in space and time. We observed that dehydration commences across a narrow front, which propagates from the margins to the centre of the sample in more than four hours. The advance of this front can be fitted with a square-root function, implying that the initiation of the reaction in the sample can be described as a diffusion process. Novel parallelized computer codes allow quantifying the geometry of the porosity and the drainage architecture from the very large tomographic datasets (20483 voxels) in unprecedented detail. We determined position, volume, shape and orientation of each resolvable pore and tracked these properties over the duration of the experiment. We found that the pore-size distribution follows a power law. Pores tend to be anisotropic but rarely crack-shaped and have a preferred orientation, likely controlled by a pre-existing fabric in the sample. With on-going dehydration, pores coalesce into a single interconnected pore cluster that is connected to the surface of the sample cylinder and provides an effective drainage pathway. Our observations can be summarized in a model in which gypsum is stabilized by thermal expansion stresses and locally increased pore fluid pressures until the dehydration front approaches to within about 100 μm. Then, the internal stresses are released and dehydration happens efficiently, resulting in new pore space. Pressure release, the production of pores and the advance of the front are coupled in a feedback loop.

Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation.

PubMed

Chan, Yvonne L; Schanzenbach, David; Hickerson, Michael J

2014-09-01

Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

PASCO: Structural panel analysis and sizing code: Users manual - Revised

NASA Technical Reports Server (NTRS)

Anderson, M. S.; Stroud, W. J.; Durling, B. J.; Hennessy, K. W.

1981-01-01

A computer code denoted PASCO is described for analyzing and sizing uniaxially stiffened composite panels. Buckling and vibration analyses are carried out with a linked plate analysis computer code denoted VIPASA, which is included in PASCO. Sizing is based on nonlinear mathematical programming techniques and employs a computer code denoted CONMIN, also included in PASCO. Design requirements considered are initial buckling, material strength, stiffness and vibration frequency. A user's manual for PASCO is presented.

Aerosol sampling system for collection of Capstone depleted uranium particles in a high-energy environment.

PubMed

Holmes, Thomas D; Guilmette, Raymond A; Cheng, Yung Sung; Parkhurst, Mary Ann; Hoover, Mark D

2009-03-01

The Capstone Depleted Uranium (DU) Aerosol Study was undertaken to obtain aerosol samples resulting from a large-caliber DU penetrator striking an Abrams or Bradley test vehicle. The sampling strategy was designed to (1) optimize the performance of the samplers and maintain their integrity in the extreme environment created during perforation of an armored vehicle by a DU penetrator, (2) collect aerosols as a function of time post perforation, and (3) obtain size-classified samples for analysis of chemical composition, particle morphology, and solubility in lung fluid. This paper describes the experimental setup and sampling methodologies used to achieve these objectives. Custom-designed arrays of sampling heads were secured to the inside of the target in locations approximating the breathing zones of the crew locations in the test vehicles. Each array was designed to support nine filter cassettes and nine cascade impactors mounted with quick-disconnect fittings. Shielding and sampler placement strategies were used to minimize sampler loss caused by the penetrator impact and the resulting fragments of eroded penetrator and perforated armor. A cyclone train was used to collect larger quantities of DU aerosol for measurement of chemical composition and solubility. A moving filter sample was used to obtain semicontinuous samples for DU concentration determination. Control for the air samplers was provided by five remotely located valve control and pressure monitoring units located inside and around the test vehicle. These units were connected to a computer interface chassis and controlled using a customized LabVIEW engineering computer control program. The aerosol sampling arrays and control systems for the Capstone study provided the needed aerosol samples for physicochemical analysis, and the resultant data were used for risk assessment of exposure to DU aerosol.

Aerosol Sampling System for Collection of Capstone Depleted Uranium Particles in a High-Energy Environment

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

Holmes, Thomas D.; Guilmette, Raymond A.; Cheng, Yung-Sung

2009-03-01

The Capstone Depleted Uranium Aerosol Study was undertaken to obtain aerosol samples resulting from a kinetic-energy cartridge with a large-caliber depleted uranium (DU) penetrator striking an Abrams or Bradley test vehicle. The sampling strategy was designed to (1) optimize the performance of the samplers and maintain their integrity in the extreme environment created during perforation of an armored vehicle by a DU penetrator, (2) collect aerosols as a function of time post-impact, and (3) obtain size-classified samples for analysis of chemical composition, particle morphology, and solubility in lung fluid. This paper describes the experimental setup and sampling methodologies used tomore » achieve these objectives. Custom-designed arrays of sampling heads were secured to the inside of the target in locations approximating the breathing zones of the vehicle commander, loader, gunner, and driver. Each array was designed to support nine filter cassettes and nine cascade impactors mounted with quick-disconnect fittings. Shielding and sampler placement strategies were used to minimize sampler loss caused by the penetrator impact and the resulting fragments of eroded penetrator and perforated armor. A cyclone train was used to collect larger quantities of DU aerosol for chemical composition and solubility. A moving filter sample was used to obtain semicontinuous samples for depleted uranium concentration determination. Control for the air samplers was provided by five remotely located valve control and pressure monitoring units located inside and around the test vehicle. These units were connected to a computer interface chassis and controlled using a customized LabVIEW engineering computer control program. The aerosol sampling arrays and control systems for the Capstone study provided the needed aerosol samples for physicochemical analysis, and the resultant data were used for risk assessment of exposure to DU aerosol.« less

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

PubMed

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

2017-06-01

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

Methods to estimate effective population size using pedigree data: Examples in dog, sheep, cattle and horse

PubMed Central

2013-01-01

Background Effective population sizes of 140 populations (including 60 dog breeds, 40 sheep breeds, 20 cattle breeds and 20 horse breeds) were computed using pedigree information and six different computation methods. Simple demographical information (number of breeding males and females), variance of progeny size, or evolution of identity by descent probabilities based on coancestry or inbreeding were used as well as identity by descent rate between two successive generations or individual identity by descent rate. Results Depending on breed and method, effective population sizes ranged from 15 to 133 056, computation method and interaction between computation method and species showing a significant effect on effective population size (P < 0.0001). On average, methods based on number of breeding males and females and variance of progeny size produced larger values (4425 and 356, respectively), than those based on identity by descent probabilities (average values between 93 and 203). Since breeding practices and genetic substructure within dog breeds increased inbreeding, methods taking into account the evolution of inbreeding produced lower effective population sizes than those taking into account evolution of coancestry. The correlation level between the simplest method (number of breeding males and females, requiring no genealogical information) and the most sophisticated one ranged from 0.44 to 0.60 according to species. Conclusions When choosing a method to compute effective population size, particular attention should be paid to the species and the specific genetic structure of the population studied. PMID:23281913

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

PubMed Central

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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

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

PubMed

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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

The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration.

PubMed

Baranes, Adrien F; Oudeyer, Pierre-Yves; Gottlieb, Jacqueline

2014-01-01

Devising efficient strategies for exploration in large open-ended spaces is one of the most difficult computational problems of intelligent organisms. Because the available rewards are ambiguous or unknown during the exploratory phase, subjects must act in intrinsically motivated fashion. However, a vast majority of behavioral and neural studies to date have focused on decision making in reward-based tasks, and the rules guiding intrinsically motivated exploration remain largely unknown. To examine this question we developed a paradigm for systematically testing the choices of human observers in a free play context. Adult subjects played a series of short computer games of variable difficulty, and freely choose which game they wished to sample without external guidance or physical rewards. Subjects performed the task in three distinct conditions where they sampled from a small or a large choice set (7 vs. 64 possible levels of difficulty), and where they did or did not have the possibility to sample new games at a constant level of difficulty. We show that despite the absence of external constraints, the subjects spontaneously adopted a structured exploration strategy whereby they (1) started with easier games and progressed to more difficult games, (2) sampled the entire choice set including extremely difficult games that could not be learnt, (3) repeated moderately and high difficulty games much more frequently than was predicted by chance, and (4) had higher repetition rates and chose higher speeds if they could generate new sequences at a constant level of difficulty. The results suggest that intrinsically motivated exploration is shaped by several factors including task difficulty, novelty and the size of the choice set, and these come into play to serve two internal goals-maximize the subjects' knowledge of the available tasks (exploring the limits of the task set), and maximize their competence (performance and skills) across the task set.

Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations.

PubMed

Knapp, Bernhard; Demharter, Samuel; Esmaielbeiki, Reyhaneh; Deane, Charlotte M

2015-11-01

The interaction between T-cell receptors (TCRs) and major histocompatibility complex (MHC)-bound epitopes is one of the most important processes in the adaptive human immune response. Several hypotheses on TCR triggering have been proposed. Many of them involve structural and dynamical adjustments in the TCR/peptide/MHC interface. Molecular Dynamics (MD) simulations are a computational technique that is used to investigate structural dynamics at atomic resolution. Such simulations are used to improve understanding of signalling on a structural level. Here we review how MD simulations of the TCR/peptide/MHC complex have given insight into immune system reactions not achievable with current experimental methods. Firstly, we summarize methods of TCR/peptide/MHC complex modelling and TCR/peptide/MHC MD trajectory analysis methods. Then we classify recently published simulations into categories and give an overview of approaches and results. We show that current studies do not come to the same conclusions about TCR/peptide/MHC interactions. This discrepancy might be caused by too small sample sizes or intrinsic differences between each interaction process. As computational power increases future studies will be able to and should have larger sample sizes, longer runtimes and additional parts of the immunological synapse included. © The Author 2015. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Clinical manifestations that predict abnormal brain computed tomography (CT) in children with minor head injury.

PubMed

Alharthy, Nesrin; Al Queflie, Sulaiman; Alyousef, Khalid; Yunus, Faisel

2015-01-01

Computed tomography (CT) used in pediatric pediatrics brain injury (TBI) to ascertain neurological manifestations. Nevertheless, this practice is associated with adverse effects. Reports in the literature suggest incidents of morbidity and mortality in children due to exposure to radiation. Hence, it is found imperative to search for a reliable alternative. The aim of this study is to find a reliable clinical alternative to detect an intracranial injury without resorting to the CT. Retrospective cross-sectional study was undertaken in patients (1-14 years) with blunt head injury and having a Glasgow Coma Scale (GCS) of 13-15 who had CT performed on them. Using statistical analysis, the correlation between clinical examination and positive CT manifestation is analyzed for different age-groups and various mechanisms of injury. No statistically significant association between parameteres such as Loss of Consciousness, 'fall' as mechanism of injury, motor vehicle accidents (MVA), more than two discrete episodes of vomiting and the CT finding of intracranial injury could be noted. Analyzed data have led to believe that GCS of 13 at presentation is the only important clinical predictor of intracranial injury. Retrospective data, small sample size and limited number of factors for assessing clinical manifestation might present constraints on the predictive rule that was derived from this review. Such limitations notwithstanding, the decision to determine which patients should undergo neuroimaging is encouraged to be based on clinical judgments. Further analysis with higher sample sizes may be required to authenticate and validate findings.

Assessment of the accuracy of portion size reports using computer-based food photographs aids in the development of an automated self-administered 24-hour recall.

PubMed

Subar, Amy F; Crafts, Jennifer; Zimmerman, Thea Palmer; Wilson, Michael; Mittl, Beth; Islam, Noemi G; McNutt, Suzanne; Potischman, Nancy; Buday, Richard; Hull, Stephen G; Baranowski, Tom; Guenther, Patricia M; Willis, Gordon; Tapia, Ramsey; Thompson, Frances E

2010-01-01

To assess the accuracy of portion-size estimates and participant preferences using various presentations of digital images. Two observational feeding studies were conducted. In both, each participant selected and consumed foods for breakfast and lunch, buffet style, serving themselves portions of nine foods representing five forms (eg, amorphous, pieces). Serving containers were weighed unobtrusively before and after selection as was plate waste. The next day, participants used a computer software program to select photographs representing portion sizes of foods consumed the previous day. Preference information was also collected. In Study 1 (n=29), participants were presented with four different types of images (aerial photographs, angled photographs, images of mounds, and household measures) and two types of screen presentations (simultaneous images vs an empty plate that filled with images of food portions when clicked). In Study 2 (n=20), images were presented in two ways that varied by size (large vs small) and number (4 vs 8). Convenience sample of volunteers of varying background in an office setting. Repeated-measures analysis of variance of absolute differences between actual and reported portions sizes by presentation methods. Accuracy results were largely not statistically significant, indicating that no one image type was most accurate. Accuracy results indicated the use of eight vs four images was more accurate. Strong participant preferences supported presenting simultaneous vs sequential images. These findings support the use of aerial photographs in the automated self-administered 24-hour recall. For some food forms, images of mounds or household measures are as accurate as images of food and, therefore, are a cost-effective alternative to photographs of foods. Copyright 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

Assessment of the Accuracy of Portion Size Reports Using Computer-Based Food Photographs Aids in the Development of an Automated Self-Administered 24-Hour Recall

PubMed Central

Subar, Amy F.; Crafts, Jennifer; Zimmerman, Thea Palmer; Wilson, Michael; Mittl, Beth; Islam, Noemi G.; Mcnutt, Suzanne; Potischman, Nancy; Buday, Richard; Hull, Stephen G.; Baranowski, Tom; Guenther, Patricia M.; Willis, Gordon; Tapia, Ramsey; Thompson, Frances E.

2013-01-01

Objective To assess the accuracy of portion-size estimates and participant preferences using various presentations of digital images. Design Two observational feeding studies were conducted. In both, each participant selected and consumed foods for breakfast and lunch, buffet style, serving themselves portions of nine foods representing five forms (eg, amorphous, pieces). Serving containers were weighed unobtrusively before and after selection as was plate waste. The next day, participants used a computer software program to select photographs representing portion sizes of foods consumed the previous day. Preference information was also collected. In Study 1 (n=29), participants were presented with four different types of images (aerial photographs, angled photographs, images of mounds, and household measures) and two types of screen presentations (simultaneous images vs an empty plate that filled with images of food portions when clicked). In Study 2 (n=20), images were presented in two ways that varied by size (large vs small) and number (4 vs 8). Subjects/setting Convenience sample of volunteers of varying background in an office setting. Statistical analyses performed Repeated-measures analysis of variance of absolute differences between actual and reported portions sizes by presentation methods. Results Accuracy results were largely not statistically significant, indicating that no one image type was most accurate. Accuracy results indicated the use of eight vs four images was more accurate. Strong participant preferences supported presenting simultaneous vs sequential images. Conclusions These findings support the use of aerial photographs in the automated self-administered 24-hour recall. For some food forms, images of mounds or household measures are as accurate as images of food and, therefore, are a cost-effective alternative to photographs of foods. PMID:20102828

A hybrid computational strategy to address WGS variant analysis in >5000 samples.

PubMed

Huang, Zhuoyi; Rustagi, Navin; Veeraraghavan, Narayanan; Carroll, Andrew; Gibbs, Richard; Boerwinkle, Eric; Venkata, Manjunath Gorentla; Yu, Fuli

2016-09-10

The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

PubMed

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Bayesian methods for the design and interpretation of clinical trials in very rare diseases

PubMed Central

Hampson, Lisa V; Whitehead, John; Eleftheriou, Despina; Brogan, Paul

2014-01-01

This paper considers the design and interpretation of clinical trials comparing treatments for conditions so rare that worldwide recruitment efforts are likely to yield total sample sizes of 50 or fewer, even when patients are recruited over several years. For such studies, the sample size needed to meet a conventional frequentist power requirement is clearly infeasible. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose a Bayesian approach for the conduct of rare-disease trials comparing an experimental treatment with a control where patient responses are classified as a success or failure. A systematic elicitation from clinicians of their beliefs concerning treatment efficacy is used to establish Bayesian priors for unknown model parameters. The process of determining the prior is described, including the possibility of formally considering results from related trials. As sample sizes are small, it is possible to compute all possible posterior distributions of the two success rates. A number of allocation ratios between the two treatment groups can be considered with a view to maximising the prior probability that the trial concludes recommending the new treatment when in fact it is non-inferior to control. Consideration of the extent to which opinion can be changed, even by data from the best feasible design, can help to determine whether such a trial is worthwhile. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24957522

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

PubMed

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

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

Predicting and Tracking Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer's Disease: Structural Brain Biomarkers.

PubMed

Marizzoni, Moira; Ferrari, Clarissa; Jovicich, Jorge; Albani, Diego; Babiloni, Claudio; Cavaliere, Libera; Didic, Mira; Forloni, Gianluigi; Galluzzi, Samantha; Hoffmann, Karl-Titus; Molinuevo, José Luis; Nobili, Flavio; Parnetti, Lucilla; Payoux, Pierre; Ribaldi, Federica; Rossini, Paolo Maria; Schönknecht, Peter; Soricelli, Andrea; Hensch, Tilman; Tsolaki, Magda; Visser, Pieter Jelle; Wiltfang, Jens; Richardson, Jill C; Bordet, Régis; Blin, Olivier; Frisoni, Giovanni B

2018-06-09

Early Alzheimer's disease (AD) detection using cerebrospinal fluid (CSF) biomarkers has been recommended as enrichment strategy for trials involving mild cognitive impairment (MCI) patients. To model a prodromal AD trial for identifying MRI structural biomarkers to improve subject selection and to be used as surrogate outcomes of disease progression. APOE ɛ4 specific CSF Aβ42/P-tau cut-offs were used to identify MCI with prodromal AD (Aβ42/P-tau positive) in the WP5-PharmaCog (E-ADNI) cohort. Linear mixed models were performed 1) with baseline structural biomarker, time, and biomarker×time interaction as factors to predict longitudinal changes in ADAS-cog13, 2) with Aβ42/P-tau status, time, and Aβ42/P-tau status×time interaction as factors to explain the longitudinal changes in MRI measures, and 3) to compute sample size estimation for a trial implemented with the selected biomarkers. Only baseline lateral ventricle volume was able to identify a subgroup of prodromal AD patients who declined faster (interaction, p = 0.003). Lateral ventricle volume and medial temporal lobe measures were the biomarkers most sensitive to disease progression (interaction, p≤0.042). Enrichment through ventricular volume reduced the sample size that a clinical trial would require from 13 to 76%, depending on structural outcome variable. The biomarker needing the lowest sample size was the hippocampal subfield GC-ML-DG (granule cells of molecular layer of the dentate gyrus) (n = 82 per arm to demonstrate a 20% atrophy reduction). MRI structural biomarkers can enrich prodromal AD with fast progressors and significantly decrease group size in clinical trials of disease modifying drugs.

Comparison between Monte Carlo simulation and measurement with a 3D polymer gel dosimeter for dose distributions in biological samples

NASA Astrophysics Data System (ADS)

Furuta, T.; Maeyama, T.; Ishikawa, K. L.; Fukunishi, N.; Fukasaku, K.; Takagi, S.; Noda, S.; Himeno, R.; Hayashi, S.

2015-08-01

In this research, we used a 135 MeV/nucleon carbon-ion beam to irradiate a biological sample composed of fresh chicken meat and bones, which was placed in front of a PAGAT gel dosimeter, and compared the measured and simulated transverse-relaxation-rate (R2) distributions in the gel dosimeter. We experimentally measured the three-dimensional R2 distribution, which records the dose induced by particles penetrating the sample, by using magnetic resonance imaging. The obtained R2 distribution reflected the heterogeneity of the biological sample. We also conducted Monte Carlo simulations using the PHITS code by reconstructing the elemental composition of the biological sample from its computed tomography images while taking into account the dependence of the gel response on the linear energy transfer. The simulation reproduced the experimental distal edge structure of the R2 distribution with an accuracy under about 2 mm, which is approximately the same as the voxel size currently used in treatment planning.

Comparison between Monte Carlo simulation and measurement with a 3D polymer gel dosimeter for dose distributions in biological samples.

PubMed

Furuta, T; Maeyama, T; Ishikawa, K L; Fukunishi, N; Fukasaku, K; Takagi, S; Noda, S; Himeno, R; Hayashi, S

2015-08-21

In this research, we used a 135 MeV/nucleon carbon-ion beam to irradiate a biological sample composed of fresh chicken meat and bones, which was placed in front of a PAGAT gel dosimeter, and compared the measured and simulated transverse-relaxation-rate (R2) distributions in the gel dosimeter. We experimentally measured the three-dimensional R2 distribution, which records the dose induced by particles penetrating the sample, by using magnetic resonance imaging. The obtained R2 distribution reflected the heterogeneity of the biological sample. We also conducted Monte Carlo simulations using the PHITS code by reconstructing the elemental composition of the biological sample from its computed tomography images while taking into account the dependence of the gel response on the linear energy transfer. The simulation reproduced the experimental distal edge structure of the R2 distribution with an accuracy under about 2 mm, which is approximately the same as the voxel size currently used in treatment planning.

Molecular dynamics simulations using temperature-enhanced essential dynamics replica exchange.

PubMed

Kubitzki, Marcus B; de Groot, Bert L

2007-06-15

Today's standard molecular dynamics simulations of moderately sized biomolecular systems at full atomic resolution are typically limited to the nanosecond timescale and therefore suffer from limited conformational sampling. Efficient ensemble-preserving algorithms like replica exchange (REX) may alleviate this problem somewhat but are still computationally prohibitive due to the large number of degrees of freedom involved. Aiming at increased sampling efficiency, we present a novel simulation method combining the ideas of essential dynamics and REX. Unlike standard REX, in each replica only a selection of essential collective modes of a subsystem of interest (essential subspace) is coupled to a higher temperature, with the remainder of the system staying at a reference temperature, T(0). This selective excitation along with the replica framework permits efficient approximate ensemble-preserving conformational sampling and allows much larger temperature differences between replicas, thereby considerably enhancing sampling efficiency. Ensemble properties and sampling performance of the method are discussed using dialanine and guanylin test systems, with multi-microsecond molecular dynamics simulations of these test systems serving as references.

Field observations of display placement requirements and character size for presbyopic and prepresbyopic computer users.

PubMed

Bartha, Michael C; Allie, Paul; Kokot, Douglas; Roe, Cynthia Purvis

2015-01-01

Computer users continue to report eye and upper body discomfort even as workstation flexibility has improved. Research shows a relationship between character size, viewing distance, and reading performance. Few reports exist regarding text height viewed under normal office work conditions and eye discomfort. This paper reports self-selected computer display placement, text characteristics, and subjective comfort for older and younger computer workers under real-world conditions. Computer workers were provided with monitors and adjustable display support(s). In Study 1, older workers wearing progressive-addition lenses (PALs) were observed. In study 2, older workers wearing multifocal lenses and younger workers were observed. Workers wearing PALs experienced less eye and body discomfort with adjustable displays, and less eye and neck discomfort for text visual angles near or greater than ergonomic recommendations. Older workers wearing multifocal correction positioned displays much lower than younger workers. In general, computer users did not adjust character size to ensure that fovial images of text fell within the recommended range. Ergonomic display placement recommendations should be different for computer users wearing multifocal correction for presbyopia. Ergonomic training should emphasize adjusting text size for user comfort.

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets.

PubMed

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Comparison of fluvial suspended-sediment concentrations and particle-size distributions measured with in-stream laser diffraction and in physical samples

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Straub, Timothy D.; Curran, Christopher A.; Landers, Mark N.; Domanski, Marian M.

2015-01-01

Laser-diffraction technology, recently adapted for in-stream measurement of fluvial suspended-sediment concentrations (SSCs) and particle-size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8 to 415 μm in 32 log-spaced size classes. Measured SSCs and PSDs from the LISST-SL were compared to a suite of 22 data sets (262 samples in all) of concurrent suspended-sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010-2012 at 16 U.S. Geological Survey streamflow-gaging stations in Illinois and Washington (basin areas: 38-69,264 km2). An unrealistically low computed effective density (mass SSC/volumetric SSC) of 1.24 g/mL (95% confidence interval: 1.05-1.45 g/mL) provided the best-fit value (R2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over two orders of magnitude of SSC (12-2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST-SL) despite being substantially lower than the sediment particle density of 2.67 g/mL (range: 2.56-2.87 g/mL, 23 samples). The PSDs measured by the LISST-SL were in good agreement with those derived from physical samples over the LISST-SL's measureable size range. Technical and operational limitations of the LISST-SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST-SL is briefly described to motivate its potential for advancing our understanding of suspended-sediment transport by rivers.

Cell wall microstructure, pore size distribution and absolute density of hemp shiv

PubMed Central

Lawrence, M.; Ansell, M. P.; Hussain, A.

2018-01-01

This paper, for the first time, fully characterizes the intrinsic physical parameters of hemp shiv including cell wall microstructure, pore size distribution and absolute density. Scanning electron microscopy revealed microstructural features similar to hardwoods. Confocal microscopy revealed three major layers in the cell wall: middle lamella, primary cell wall and secondary cell wall. Computed tomography improved the visualization of pore shape and pore connectivity in three dimensions. Mercury intrusion porosimetry (MIP) showed that the average accessible porosity was 76.67 ± 2.03% and pore size classes could be distinguished into micropores (3–10 nm) and macropores (0.1–1 µm and 20–80 µm). The absolute density was evaluated by helium pycnometry, MIP and Archimedes' methods. The results show that these methods can lead to misinterpretation of absolute density. The MIP method showed a realistic absolute density (1.45 g cm−3) consistent with the density of the known constituents, including lignin, cellulose and hemi-cellulose. However, helium pycnometry and Archimedes’ methods gave falsely low values owing to 10% of the volume being inaccessible pores, which require sample pretreatment in order to be filled by liquid or gas. This indicates that the determination of the cell wall density is strongly dependent on sample geometry and preparation. PMID:29765652

Cell wall microstructure, pore size distribution and absolute density of hemp shiv

NASA Astrophysics Data System (ADS)

Jiang, Y.; Lawrence, M.; Ansell, M. P.; Hussain, A.

2018-04-01

This paper, for the first time, fully characterizes the intrinsic physical parameters of hemp shiv including cell wall microstructure, pore size distribution and absolute density. Scanning electron microscopy revealed microstructural features similar to hardwoods. Confocal microscopy revealed three major layers in the cell wall: middle lamella, primary cell wall and secondary cell wall. Computed tomography improved the visualization of pore shape and pore connectivity in three dimensions. Mercury intrusion porosimetry (MIP) showed that the average accessible porosity was 76.67 ± 2.03% and pore size classes could be distinguished into micropores (3-10 nm) and macropores (0.1-1 µm and 20-80 µm). The absolute density was evaluated by helium pycnometry, MIP and Archimedes' methods. The results show that these methods can lead to misinterpretation of absolute density. The MIP method showed a realistic absolute density (1.45 g cm-3) consistent with the density of the known constituents, including lignin, cellulose and hemi-cellulose. However, helium pycnometry and Archimedes' methods gave falsely low values owing to 10% of the volume being inaccessible pores, which require sample pretreatment in order to be filled by liquid or gas. This indicates that the determination of the cell wall density is strongly dependent on sample geometry and preparation.

The liquid-liquid transition in supercooled ST2 water: a comparison between umbrella sampling and well-tempered metadynamics.

PubMed

Palmer, Jeremy C; Car, Roberto; Debenedetti, Pablo G

2013-01-01

We investigate the metastable phase behaviour of the ST2 water model under deeply supercooled conditions. The phase behaviour is examined using umbrella sampling (US) and well-tempered metadynamics (WT-MetaD) simulations to compute the reversible free energy surface parameterized by density and bond-orientation order. We find that free energy surfaces computed with both techniques clearly show two liquid phases in coexistence, in agreement with our earlier US and grand canonical Monte Carlo calculations [Y. Liu, J. C. Palmer, A. Z. Panagiotopoulos and P. G. Debenedetti, J Chem Phys, 2012, 137, 214505; Y. Liu, A. Z. Panagiotopoulos and P. G. Debenedetti, J Chem Phys, 2009, 131, 104508]. While we demonstrate that US and WT-MetaD produce consistent results, the latter technique is estimated to be more computationally efficient by an order of magnitude. As a result, we show that WT-MetaD can be used to study the finite-size scaling behaviour of the free energy barrier separating the two liquids for systems containing 192, 300 and 400 ST2 molecules. Although our results are consistent with the expected N(2/3) scaling law, we conclude that larger systems must be examined to provide conclusive evidence of a first-order phase transition and associated second critical point.

Enhanced algorithms for stochastic programming

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

Krishna, Alamuru S.

1993-09-01

In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean ofmore » a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.« less

Optimal iodine staining of cardiac tissue for X-ray computed tomography.

PubMed

Butters, Timothy D; Castro, Simon J; Lowe, Tristan; Zhang, Yanmin; Lei, Ming; Withers, Philip J; Zhang, Henggui

2014-01-01

X-ray computed tomography (XCT) has been shown to be an effective imaging technique for a variety of materials. Due to the relatively low differential attenuation of X-rays in biological tissue, a high density contrast agent is often required to obtain optimal contrast. The contrast agent, iodine potassium iodide ([Formula: see text]), has been used in several biological studies to augment the use of XCT scanning. Recently I2KI was used in XCT scans of animal hearts to study cardiac structure and to generate 3D anatomical computer models. However, to date there has been no thorough study into the optimal use of I2KI as a contrast agent in cardiac muscle with respect to the staining times required, which has been shown to impact significantly upon the quality of results. In this study we address this issue by systematically scanning samples at various stages of the staining process. To achieve this, mouse hearts were stained for up to 58 hours and scanned at regular intervals of 6-7 hours throughout this process. Optimal staining was found to depend upon the thickness of the tissue; a simple empirical exponential relationship was derived to allow calculation of the required staining time for cardiac samples of an arbitrary size.

Diagnostic performance of multidetector computed tomography in distinguishing unilateral from bilateral abnormalities in primary hyperaldosteronism: comparison of multidetector computed tomography with adrenal vein sampling.

PubMed

Raman, Siva P; Lessne, Mark; Kawamoto, Satomi; Chen, Yifei; Salvatori, Roberto; Prescott, Jason D; Fishman, Elliot K

2015-01-01

The management of patients with primary hyperaldosteronism (PH) varies depending on whether the unregulated aldosterone secretion localizes to a single unilateral adrenal gland, traditionally determined using adrenal vein sampling (AVS). This study seeks to determine if the performance of multidetector computed tomography (MDCT) examinations performed using the latest scanner technology can reasonably match the results of AVS, and potentially avoid AVS in some patients. Computed tomographic scans in 56 patients with PH were independently reviewed by 2 radiologists for the presence of adrenal nodules and qualitative adrenal thickening. Results were correlated with AVS results. Of 35 patients with MDCT evidence of unilateral nodules, the imaging findings correctly predicted AVS localization in only 23 (65.7%) cases. When stratified by size, MDCT was accurate in only 71.4% of cases for nodules measuring 10 mm or less, and only 55.0% of cases for nodules measuring 11 to 20 mm. Of the 12 cases where MDCT did not correctly localize, AVS localized to the contralateral adrenal gland in 4 cases, whereas AVS suggested no lateralization in 8 cases. In patients with normal bilateral adrenal glands on MDCT, 2/7 (28.6%) of cases demonstrated unilateral localization on AVS, and in patients with bilateral adrenal nodules, only 3/14 (21.4%) did not demonstrate lateralization on AVS. Multidetector computed tomography, even when performed with the latest generation of MDCT scanners, does not offer sufficient diagnostic accuracy to replace AVS in patients with PH.

A comprehensive and scalable database search system for metaproteomics.

PubMed

Chatterjee, Sandip; Stupp, Gregory S; Park, Sung Kyu Robin; Ducom, Jean-Christophe; Yates, John R; Su, Andrew I; Wolan, Dennis W

2016-08-16

Mass spectrometry-based shotgun proteomics experiments rely on accurate matching of experimental spectra against a database of protein sequences. Existing computational analysis methods are limited in the size of their sequence databases, which severely restricts the proteomic sequencing depth and functional analysis of highly complex samples. The growing amount of public high-throughput sequencing data will only exacerbate this problem. We designed a broadly applicable metaproteomic analysis method (ComPIL) that addresses protein database size limitations. Our approach to overcome this significant limitation in metaproteomics was to design a scalable set of sequence databases assembled for optimal library querying speeds. ComPIL was integrated with a modified version of the search engine ProLuCID (termed "Blazmass") to permit rapid matching of experimental spectra. Proof-of-principle analysis of human HEK293 lysate with a ComPIL database derived from high-quality genomic libraries was able to detect nearly all of the same peptides as a search with a human database (~500x fewer peptides in the database), with a small reduction in sensitivity. We were also able to detect proteins from the adenovirus used to immortalize these cells. We applied our method to a set of healthy human gut microbiome proteomic samples and showed a substantial increase in the number of identified peptides and proteins compared to previous metaproteomic analyses, while retaining a high degree of protein identification accuracy and allowing for a more in-depth characterization of the functional landscape of the samples. The combination of ComPIL with Blazmass allows proteomic searches to be performed with database sizes much larger than previously possible. These large database searches can be applied to complex meta-samples with unknown composition or proteomic samples where unexpected proteins may be identified. The protein database, proteomic search engine, and the proteomic data files for the 5 microbiome samples characterized and discussed herein are open source and available for use and additional analysis.

Use of nanotomographic images for structure analysis of carbonate rocks

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

Nagata, Rodrigo; Appoloni, Carlos Roberto

Carbonate rocks store more than 50% of world's petroleum. These rocks' structures are highly complex and vary depending on many factors regarding their formation, e.g., lithification and diagenesis. In order to perform an effective extraction of petroleum it is necessary to know petrophysical parameters, such as total porosity, pore size and permeability of the reservoir rocks. Carbonate rocks usually have a range of pore sizes that goes from nanometers to meters or even dozen of meters. The nanopores and micropores might play an important role in the pores connectivity of carbonate rocks. X-ray computed tomography (CT) has been widely usedmore » to analyze petrophysical parameters in recent years. This technique has the capability to generate 2D images of the samples' inner structure and also allows the 3D reconstruction of the actual analyzed volume. CT is a powerful technique, but its results depend on the spatial resolution of the generated image. Spatial resolution is a measurement parameter that indicates the smallest object that can be detected. There are great difficulties to generate images with nanoscale resolution (nanotomographic images). In this work three carbonate rocks, one dolomite and two limestones (that will be called limestone A and limestone B) were analyzed by nanotomography. The measurements were performed with the SkyScan2011 nanotomograph, operated at 60 kV and 200 μA to measure the dolomite sample and 40 kV and 200 μA to measure the limestone samples. Each sample was measured with a given spatial resolution (270 nm for the dolomite sample, 360 nm for limestone A and 450 nm for limestone B). The achieved results for total porosity were: 3.09 % for dolomite, 0.65% for limestone A and 3.74% for limestone B. This paper reports the difficulties to acquire nanotomographic images and further analysis about the samples' pore sizes.« less

Verification of ARMA identification for modelling temporal correlation of GPS observations using the toolbox ARMASA

NASA Astrophysics Data System (ADS)

Luo, Xiaoguang; Mayer, Michael; Heck, Bernhard

2010-05-01

One essential deficiency of the stochastic model used in many GNSS (Global Navigation Satellite Systems) software products consists in neglecting temporal correlation of GNSS observations. Analysing appropriately detrended time series of observation residuals resulting from GPS (Global Positioning System) data processing, the temporal correlation behaviour of GPS observations can be sufficiently described by means of so-called autoregressive moving average (ARMA) processes. Using the toolbox ARMASA which is available free of charge in MATLAB® Central (open exchange platform for the MATLAB® and SIMULINK® user community), a well-fitting time series model can be identified automatically in three steps. Firstly, AR, MA, and ARMA models are computed up to some user-specified maximum order. Subsequently, for each model type, the best-fitting model is selected using the combined (for AR processes) resp. generalised (for MA and ARMA processes) information criterion. The final model identification among the best-fitting AR, MA, and ARMA models is performed based on the minimum prediction error characterising the discrepancies between the given data and the fitted model. The ARMA coefficients are computed using Burg's maximum entropy algorithm (for AR processes), Durbin's first (for MA processes) and second (for ARMA processes) methods, respectively. This paper verifies the performance of the automated ARMA identification using the toolbox ARMASA. For this purpose, a representative data base is generated by means of ARMA simulation with respect to sample size, correlation level, and model complexity. The model error defined as a transform of the prediction error is used as measure for the deviation between the true and the estimated model. The results of the study show that the recognition rates of underlying true processes increase with increasing sample sizes and decrease with rising model complexity. Considering large sample sizes, the true underlying processes can be correctly recognised for nearly 80% of the analysed data sets. Additionally, the model errors of first-order AR resp. MA processes converge clearly more rapidly to the corresponding asymptotical values than those of high-order ARMA processes.

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

Size-exclusion chromatography system for macromolecular interaction analysis

DOEpatents

Stevens, Fred J.

1988-01-01

A low pressure, microcomputer controlled system employing high performance liquid chromatography (HPLC) allows for precise analysis of the interaction of two reversibly associating macromolecules such as proteins. Since a macromolecular complex migrates faster than its components during size-exclusion chromatography, the difference between the elution profile of a mixture of two macromolecules and the summation of the elution profiles of the two components provides a quantifiable indication of the degree of molecular interaction. This delta profile is used to qualitatively reveal the presence or absence of significant interaction or to rank the relative degree of interaction in comparing samples and, in combination with a computer simulation, is further used to quantify the magnitude of the interaction in an arrangement wherein a microcomputer is coupled to analytical instrumentation in a novel manner.

A GPU-paralleled implementation of an enhanced face recognition algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Liu, Xiyang; Shao, Shuai; Zan, Jiguo

2013-03-01

Face recognition algorithm based on compressed sensing and sparse representation is hotly argued in these years. The scheme of this algorithm increases recognition rate as well as anti-noise capability. However, the computational cost is expensive and has become a main restricting factor for real world applications. In this paper, we introduce a GPU-accelerated hybrid variant of face recognition algorithm named parallel face recognition algorithm (pFRA). We describe here how to carry out parallel optimization design to take full advantage of many-core structure of a GPU. The pFRA is tested and compared with several other implementations under different data sample size. Finally, Our pFRA, implemented with NVIDIA GPU and Computer Unified Device Architecture (CUDA) programming model, achieves a significant speedup over the traditional CPU implementations.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

SIproc: an open-source biomedical data processing platform for large hyperspectral images.

PubMed

Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

2017-04-10

There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

A Fast Projection-Based Algorithm for Clustering Big Data.

PubMed

Wu, Yun; He, Zhiquan; Lin, Hao; Zheng, Yufei; Zhang, Jingfen; Xu, Dong

2018-06-07

With the fast development of various techniques, more and more data have been accumulated with the unique properties of large size (tall) and high dimension (wide). The era of big data is coming. How to understand and discover new knowledge from these data has attracted more and more scholars' attention and has become the most important task in data mining. As one of the most important techniques in data mining, clustering analysis, a kind of unsupervised learning, could group a set data into objectives(clusters) that are meaningful, useful, or both. Thus, the technique has played very important role in knowledge discovery in big data. However, when facing the large-sized and high-dimensional data, most of the current clustering methods exhibited poor computational efficiency and high requirement of computational source, which will prevent us from clarifying the intrinsic properties and discovering the new knowledge behind the data. Based on this consideration, we developed a powerful clustering method, called MUFOLD-CL. The principle of the method is to project the data points to the centroid, and then to measure the similarity between any two points by calculating their projections on the centroid. The proposed method could achieve linear time complexity with respect to the sample size. Comparison with K-Means method on very large data showed that our method could produce better accuracy and require less computational time, demonstrating that the MUFOLD-CL can serve as a valuable tool, at least may play a complementary role to other existing methods, for big data clustering. Further comparisons with state-of-the-art clustering methods on smaller datasets showed that our method was fastest and achieved comparable accuracy. For the convenience of most scholars, a free soft package was constructed.

The Scherrer equation and the dynamical theory of X-ray diffraction.

PubMed

Muniz, Francisco Tiago Leitão; Miranda, Marcus Aurélio Ribeiro; Morilla Dos Santos, Cássio; Sasaki, José Marcos

2016-05-01

The Scherrer equation is a widely used tool to determine the crystallite size of polycrystalline samples. However, it is not clear if one can apply it to large crystallite sizes because its derivation is based on the kinematical theory of X-ray diffraction. For large and perfect crystals, it is more appropriate to use the dynamical theory of X-ray diffraction. Because of the appearance of polycrystalline materials with a high degree of crystalline perfection and large sizes, it is the authors' belief that it is important to establish the crystallite size limit for which the Scherrer equation can be applied. In this work, the diffraction peak profiles are calculated using the dynamical theory of X-ray diffraction for several Bragg reflections and crystallite sizes for Si, LaB6 and CeO2. The full width at half-maximum is then extracted and the crystallite size is computed using the Scherrer equation. It is shown that for crystals with linear absorption coefficients below 2117.3 cm(-1) the Scherrer equation is valid for crystallites with sizes up to 600 nm. It is also shown that as the size increases only the peaks at higher 2θ angles give good results, and if one uses peaks with 2θ > 60° the limit for use of the Scherrer equation would go up to 1 µm.

Inactivation of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice by pulsed light. Influence of initial contamination and required reduction levels.

PubMed

Ferrario, Mariana I; Guerrero, Sandra N

The purpose of this study was to analyze the response of different initial contamination levels of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice as affected by pulsed light treatment (PL, batch mode, xenon lamp, 3pulses/s, 0-71.6J/cm 2 ). Biphasic and Weibull frequency distribution models were used to characterize the relationship between inoculum size and treatment time with the reductions achieved after PL exposure. Additionally, a second order polynomial model was computed to relate required PL processing time to inoculum size and requested log reductions. PL treatment caused up to 3.0-3.5 log reductions, depending on the initial inoculum size. Inactivation curves corresponding to PL-treated samples were adequately characterized by both Weibull and biphasic models (R adj 2 94-96%), and revealed that lower initial inoculum sizes were associated with higher inactivation rates. According to the polynomial model, the predicted time for PL treatment increased exponentially with inoculum size. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances.

PubMed

Ma, Ji; Sun, Da-Wen; Qu, Jia-Huan; Liu, Dan; Pu, Hongbin; Gao, Wen-Hong; Zeng, Xin-An

2016-01-01

With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.

Asymptotic Distributions of Coalescence Times and Ancestral Lineage Numbers for Populations with Temporally Varying Size

PubMed Central

Chen, Hua; Chen, Kun

2013-01-01

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n − An(t) follows a Poisson distribution, and as m → n, n(n−1)Tm/2N(0) follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference. PMID:23666939

Asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size.

PubMed

Chen, Hua; Chen, Kun

2013-07-01

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n - An(t) follows a Poisson distribution, and as m → n, $$n\\left(n-1\\right){T}_{m}/2N\\left(0\\right)$$ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference.

The effect of size, orientation and alloying on the deformation of AZ31 nanopillars

NASA Astrophysics Data System (ADS)

Aitken, Zachary H.; Fan, Haidong; El-Awady, Jaafar A.; Greer, Julia R.

2015-03-01

We conducted uniaxial compression of single crystalline Mg alloy, AZ31 (Al 3 wt% and Zn 1 wt%) nanopillars with diameters between 300 and 5000 nm with two distinct crystallographic orientations: (1) along the [0001] c-axis and (2) at an acute angle away from the c-axis, nominally oriented for basal slip. We observe single slip deformation for sub-micron samples nominally oriented for basal slip with the deformation commencing via a single set of parallel shear offsets. Samples compressed along the c-axis display an increase in yield strength compared to basal samples as well as significant hardening with the deformation being mostly homogeneous. We find that the "smaller is stronger" size effect in single crystals dominates any improvement in strength that may have arisen from solid solution strengthening. We employ 3D-discrete dislocation dynamics (DDD) to simulate compression along the [0001] and [ 11 2 bar 2 ] directions to elucidate the mechanisms of slip and evolution of dislocation microstructure. These simulations show qualitatively similar stress-strain signatures to the experimentally obtained stress-strain data. Simulations of compression parallel to the [ 11 2 bar 2 ] direction reveal the activation and motion of only -type dislocations and virtually no dislocation junction formation. Computations of compression along [0001] show the activation and motion of both and dislocations along with a significant increase in the formation of junctions corresponding to the interaction of intersecting pyramidal planes. Both experiments and simulation show a size effect, with a differing exponent for basal and pyramidal slip. We postulate that this anisotropy in size effect is a result of the underlying anisotropic material properties only. We discuss these findings in the context of the effective resolved shear stress relative to the unit Burgers vector for each type of slip, which reveal that the mechanism that governs size effect in this Mg-alloy is equivalent in both orientations.

Effect of heterogeneity on the characterization of cell membrane compartments: I. Uniform size and permeability.

PubMed

Hall, Damien

2010-03-15

Observations of the motion of individual molecules in the membrane of a number of different cell types have led to the suggestion that the outer membrane of many eukaryotic cells may be effectively partitioned into microdomains. A major cause of this suggested partitioning is believed to be due to the direct/indirect association of the cytosolic face of the cell membrane with the cortical cytoskeleton. Such intimate association is thought to introduce effective hydrodynamic barriers into the membrane that are capable of frustrating molecular Brownian motion over distance scales greater than the average size of the compartment. To date, the standard analytical method for deducing compartment characteristics has relied on observing the random walk behavior of a labeled lipid or protein at various temporal frequencies and different total lengths of time. Simple theoretical arguments suggest that the presence of restrictive barriers imparts a characteristic turnover to a plot of mean squared displacement versus sampling period that can be interpreted to yield the average dimensions of the compartment expressed as the respective side lengths of a rectangle. In the following series of articles, we used computer simulation methods to investigate how well the conventional analytical strategy coped with heterogeneity in size, shape, and barrier permeability of the cell membrane compartments. We also explored questions relating to the necessary extent of sampling required (with regard to both the recorded time of a single trajectory and the number of trajectories included in the measurement bin) for faithful representation of the actual distribution of compartment sizes found using the SPT technique. In the current investigation, we turned our attention to the analytical characterization of diffusion through cell membrane compartments having both a uniform size and permeability. For this ideal case, we found that (i) an optimum sampling time interval existed for the analysis and (ii) the total length of time for which a trajectory was recorded was a key factor. Copyright (c) 2009 Elsevier Inc. All rights reserved.

The multimedia computer for office-based patient education: a systematic review.

PubMed

Wofford, James L; Smith, Edward D; Miller, David P

2005-11-01

Use of the multimedia computer for education is widespread in schools and businesses, and yet computer-assisted patient education is rare. In order to explore the potential use of computer-assisted patient education in the office setting, we performed a systematic review of randomized controlled trials (search date April 2004 using MEDLINE and Cochrane databases). Of the 26 trials identified, outcome measures included clinical indicators (12/26, 46.1%), knowledge retention (12/26, 46.1%), health attitudes (15/26, 57.7%), level of shared decision-making (5/26, 19.2%), health services utilization (4/26, 17.6%), and costs (5/26, 19.2%), respectively. Four trials targeted patients with breast cancer, but the clinical issues were otherwise diverse. Reporting of the testing of randomization (76.9%) and appropriate analysis of main effect variables (70.6%) were more common than reporting of a reliable randomization process (35.3%), blinding of outcomes assessment (17.6%), or sample size definition (29.4%). We concluded that the potential for improving the efficiency of the office through computer-assisted patient education has been demonstrated, but better proof of the impact on clinical outcomes is warranted before this strategy is accepted in the office setting.

Influence of computational domain size on the pattern formation of the phase field crystals

NASA Astrophysics Data System (ADS)

Starodumov, Ilya; Galenko, Peter; Alexandrov, Dmitri; Kropotin, Nikolai

2017-04-01

Modeling of crystallization process by the phase field crystal method (PFC) represents one of the important directions of modern computational materials science. This method makes it possible to research the formation of stable or metastable crystal structures. In this paper, we study the effect of computational domain size on the crystal pattern formation obtained as a result of computer simulation by the PFC method. In the current report, we show that if the size of a computational domain is changed, the result of modeling may be a structure in metastable phase instead of pure stable state. The authors present a possible theoretical justification for the observed effect and provide explanations on the possible modification of the PFC method to account for this phenomenon.

Central Fetal Monitoring With and Without Computer Analysis: A Randomized Controlled Trial.

PubMed

Nunes, Inês; Ayres-de-Campos, Diogo; Ugwumadu, Austin; Amin, Pina; Banfield, Philip; Nicoll, Antony; Cunningham, Simon; Sousa, Paulo; Costa-Santos, Cristina; Bernardes, João

2017-01-01

To evaluate whether intrapartum fetal monitoring with computer analysis and real-time alerts decreases the rate of newborn metabolic acidosis or obstetric intervention when compared with visual analysis. A randomized clinical trial carried out in five hospitals in the United Kingdom evaluated women with singleton, vertex fetuses of 36 weeks of gestation or greater during labor. Continuous central fetal monitoring by computer analysis and online alerts (experimental arm) was compared with visual analysis (control arm). Fetal blood sampling and electrocardiographic ST waveform analysis were available in both arms. The primary outcome was incidence of newborn metabolic acidosis (pH less than 7.05 and base deficit greater than 12 mmol/L). Prespecified secondary outcomes included operative delivery, use of fetal blood sampling, low 5-minute Apgar score, neonatal intensive care unit admission, hypoxic-ischemic encephalopathy, and perinatal death. A sample size of 3,660 per group (N=7,320) was planned to be able to detect a reduction in the rate of metabolic acidosis from 2.8% to 1.8% (two-tailed α of 0.05 with 80% power). From August 2011 through July 2014, 32,306 women were assessed for eligibility and 7,730 were randomized: 3,961 to computer analysis and online alerts, and 3,769 to visual analysis. Baseline characteristics were similar in both groups. Metabolic acidosis occurred in 16 participants (0.40%) in the experimental arm and 22 participants (0.58%) in the control arm (relative risk 0.69 [0.36-1.31]). No statistically significant differences were found in the incidence of secondary outcomes. Compared with visual analysis, computer analysis of fetal monitoring signals with real-time alerts did not significantly reduce the rate of metabolic acidosis or obstetric intervention. A lower-than-expected rate of newborn metabolic acidosis was observed in both arms of the trial. ISRCTN Registry, http://www.isrctn.com, ISRCTN42314164.

Non-Destructive Characterization of UO2+x Nuclear Fuels

DOE PAGES

Pokharel, Reeju; Brown, Donald W.; Clausen, Bjørn; ...

2017-10-27

This article describes the effect of fabrication conditions on as-sintered microstructures of various stoichiometric ratios of uranium dioxide, UO 2+x, with the aim of enhancing the understanding of fabrication process and developing and validating a predictive microstructurebased model for fuel performance. We demonstrate the ability of novel, non-destructive methods such as near-field high-energy X-ray diffraction microscopy (nf-HEDM) and micro-computed tomography (μ-CT) to probe bulk samples of high-Z materials by non-destructively characterizing three samples: UO 2.00, UO 2.11, and UO 2.16, which were sintered at 1450°C for 4 hours. The measured 3D microstructures revealed that grain size and porosity were influencedmore » by deviation from stoichiometry.« less

Optimal flexible sample size design with robust power.

PubMed

Zhang, Lanju; Cui, Lu; Yang, Bo

2016-08-30

It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Fossils out of sequence: Computer simulations and strategies for dealing with stratigraphic disorder

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

Cutler, A.H.; Flessa, K.W.

Microstratigraphic resolution is limited by vertical mixing and reworking of fossils. Stratigraphic disorder is the degree to which fossils within a stratigraphic sequence are not in proper chronological order. Stratigraphic disorder arises through in situ vertical mixing of fossils and reworking of older fossils into younger deposits. The authors simulated the effects of mixing and reworking by simple computer models, and measured stratigraphic disorder using rank correlation between age and stratigraphic position (Spearman and Kendall coefficients). Mixing was simulated by randomly transposing pairs of adjacent fossils in a sequence. Reworking was simulated by randomly inserting older fossils into a youngermore » sequence. Mixing is an inefficient means of producing disorder; after 500 mixing steps stratigraphic order is still significant at the 99% to 95% level, depending on the coefficient used. Reworking disorders sequences very efficiently: significant order begins to be lost when reworked shells make up 35% of the sequence. Thus a sequence can be dominated by undisturbed, autochthonous shells and still be disordered. The effects of mixing-produced disorder can be minimized by increasing sample size at each horizon. Increased spacing between samples is of limited utility in dealing with disordered sequences: while widely separated samples are more likely to be stratigraphically ordered, the smaller number of samples makes the detection of trends problematic.« less