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

Science.gov (United States)

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

2010-06-30

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

TWO-STAGE CHARACTER CLASSIFICATION : A COMBINED APPROACH OF CLUSTERING AND SUPPORT VECTOR CLASSIFIERS

NARCIS (Netherlands)

Vuurpijl, L.; Schomaker, L.

2000-01-01

This paper describes a two-stage classification method for (1) classification of isolated characters and (2) verification of the classification result. Character prototypes are generated using hierarchical clustering. For those prototypes known to sometimes produce wrong classification results, a

Cluster randomization and political philosophy.

Science.gov (United States)

Chwang, Eric

2012-11-01

In this paper, I will argue that, while the ethical issues raised by cluster randomization can be challenging, they are not new. My thesis divides neatly into two parts. In the first, easier part I argue that many of the ethical challenges posed by cluster randomized human subjects research are clearly present in other types of human subjects research, and so are not novel. In the second, more difficult part I discuss the thorniest ethical challenge for cluster randomized research--cases where consent is genuinely impractical to obtain. I argue that once again these cases require no new analytic insight; instead, we should look to political philosophy for guidance. In other words, the most serious ethical problem that arises in cluster randomized research also arises in political philosophy. © 2011 Blackwell Publishing Ltd.

Quantification of physical activity using the QAPACE Questionnaire: a two stage cluster sample design survey of children and adolescents attending urban school.

Science.gov (United States)

Barbosa, Nicolas; Sanchez, Carlos E; Patino, Efrain; Lozano, Benigno; Thalabard, Jean C; LE Bozec, Serge; Rieu, Michel

2016-05-01

Quantification of physical activity as energy expenditure is important since youth for the prevention of chronic non communicable diseases in adulthood. It is necessary to quantify physical activity expressed in daily energy expenditure (DEE) in school children and adolescents between 8-16 years, by age, gender and socioeconomic level (SEL) in Bogotá. This is a Two Stage Cluster Survey Sample. From a universe of 4700 schools and 760000 students from three existing socioeconomic levels in Bogotá (low, medium and high). The random sample was 20 schools and 1840 students (904 boys and 936 girls). Foreshadowing desertion of participants and inconsistency in the questionnaire responses, the sample size was increased. Thus, 6 individuals of each gender for each of the nine age groups were selected, resulting in a total sample of 2160 individuals. Selected students filled the QAPACE questionnaire under supervision. The data was analyzed comparing means with multivariate general linear model. Fixed factors used were: gender (boys and girls), age (8 to 16 years old) and tri-strata SEL (low, medium and high); as independent variables were assessed: height, weight, leisure time, expressed in hours/day and dependent variable: daily energy expenditure DEE (kJ.kg-1.day-1): during leisure time (DEE-LT), during school time (DEE-ST), during vacation time (DEE-VT), and total mean DEE per year (DEEm-TY) RESULTS: Differences in DEE by gender, in boys, LT and all DEE, with the SEL all variables were significant; but age-SEL was only significant in DEE-VT. In girls, with the SEL all variables were significant. The post hoc multiple comparisons tests were significant with age using Fisher's Least Significant Difference (LSD) test in all variables. For both genders and for all SELs the values in girls had the higher value except SEL high (5-6) The boys have higher values in DEE-LT, DEE-ST, DEE-VT; except in DEEm-TY in SEL (5-6) In SEL (5-6) all DEEs for both genders are highest. For SEL

Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables

Directory of Open Access Journals (Sweden)

S. K. Barik

2012-01-01

Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.

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

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

2011-01-01

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

Effect of Behavior Modification on Outcome in Early- to Moderate-Stage Chronic Kidney Disease: A Cluster-Randomized Trial.

Science.gov (United States)

Yamagata, Kunihiro; Makino, Hirofumi; Iseki, Kunitoshi; Ito, Sadayoshi; Kimura, Kenjiro; Kusano, Eiji; Shibata, Takanori; Tomita, Kimio; Narita, Ichiei; Nishino, Tomoya; Fujigaki, Yoshihide; Mitarai, Tetsuya; Watanabe, Tsuyoshi; Wada, Takashi; Nakamura, Teiji; Matsuo, Seiichi

2016-01-01

Owing to recent changes in our understanding of the underlying cause of chronic kidney disease (CKD), the importance of lifestyle modification for preventing the progression of kidney dysfunction and complications has become obvious. In addition, effective cooperation between general physicians (GPs) and nephrologists is essential to ensure a better care system for CKD treatment. In this cluster-randomized study, we studied the effect of behavior modification on the outcome of early- to moderate-stage CKD. Stratified open cluster-randomized trial. A total of 489 GPs belonging to 49 local medical associations (clusters) in Japan. A total of 2,379 patients (1,195 in group A (standard intervention) and 1,184 in group B (advanced intervention)) aged between 40 and 74 years, who had CKD and were under consultation with GPs. All patients were managed in accordance with the current CKD guidelines. The group B clusters received three additional interventions: patients received both educational intervention for lifestyle modification and a CKD status letter, attempting to prevent their withdrawal from treatment, and the group B GPs received data sheets to facilitate reducing the gap between target and practice. The primary outcome measures were 1) the non-adherence rate of accepting continuous medical follow-up of the patients, 2) the collaboration rate between GPs and nephrologists, and 3) the progression of CKD. The rate of discontinuous clinical visits was significantly lower in group B (16.2% in group A vs. 11.5% in group B, p = 0.01). Significantly higher referral and co-treatment rates were observed in group B (pbehavior modification of CKD patients, namely, significantly lower discontinuous clinical visits, and behavior modification of both GPs and nephrologists, namely significantly higher referral and co-treatment rates, resulting in the retardation of CKD progression, especially in patients with proteinuric Stage 3 CKD. The University Hospital Medical Information

A two-stage Bayesian design with sample size reestimation and subgroup analysis for phase II binary response trials.

Science.gov (United States)

Zhong, Wei; Koopmeiners, Joseph S; Carlin, Bradley P

2013-11-01

Frequentist sample size determination for binary outcome data in a two-arm clinical trial requires initial guesses of the event probabilities for the two treatments. Misspecification of these event rates may lead to a poor estimate of the necessary sample size. In contrast, the Bayesian approach that considers the treatment effect to be random variable having some distribution may offer a better, more flexible approach. The Bayesian sample size proposed by (Whitehead et al., 2008) for exploratory studies on efficacy justifies the acceptable minimum sample size by a "conclusiveness" condition. In this work, we introduce a new two-stage Bayesian design with sample size reestimation at the interim stage. Our design inherits the properties of good interpretation and easy implementation from Whitehead et al. (2008), generalizes their method to a two-sample setting, and uses a fully Bayesian predictive approach to reduce an overly large initial sample size when necessary. Moreover, our design can be extended to allow patient level covariates via logistic regression, now adjusting sample size within each subgroup based on interim analyses. We illustrate the benefits of our approach with a design in non-Hodgkin lymphoma with a simple binary covariate (patient gender), offering an initial step toward within-trial personalized medicine. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluating the Validity of a Two-stage Sample in a Birth Cohort Established from Administrative Databases.

Science.gov (United States)

El-Zein, Mariam; Conus, Florence; Benedetti, Andrea; Parent, Marie-Elise; Rousseau, Marie-Claude

2016-01-01

When using administrative databases for epidemiologic research, a subsample of subjects can be interviewed, eliciting information on undocumented confounders. This article presents a thorough investigation of the validity of a two-stage sample encompassing an assessment of nonparticipation and quantification of the extent of bias. Established through record linkage of administrative databases, the Québec Birth Cohort on Immunity and Health (n = 81,496) aims to study the association between Bacillus Calmette-Guérin vaccination and asthma. Among 76,623 subjects classified in four Bacillus Calmette-Guérin-asthma strata, a two-stage sampling strategy with a balanced design was used to randomly select individuals for interviews. We compared stratum-specific sociodemographic characteristics and healthcare utilization of stage 2 participants (n = 1,643) with those of eligible nonparticipants (n = 74,980) and nonrespondents (n = 3,157). We used logistic regression to determine whether participation varied across strata according to these characteristics. The effect of nonparticipation was described by the relative odds ratio (ROR = ORparticipants/ORsource population) for the association between sociodemographic characteristics and asthma. Parental age at childbirth, area of residence, family income, and healthcare utilization were comparable between groups. Participants were slightly more likely to be women and have a mother born in Québec. Participation did not vary across strata by sex, parental birthplace, or material and social deprivation. Estimates were not biased by nonparticipation; most RORs were below one and bias never exceeded 20%. Our analyses evaluate and provide a detailed demonstration of the validity of a two-stage sample for researchers assembling similar research infrastructures.

Sample size reassessment for a two-stage design controlling the false discovery rate.

Science.gov (United States)

Zehetmayer, Sonja; Graf, Alexandra C; Posch, Martin

2015-11-01

Sample size calculations for gene expression microarray and NGS-RNA-Seq experiments are challenging because the overall power depends on unknown quantities as the proportion of true null hypotheses and the distribution of the effect sizes under the alternative. We propose a two-stage design with an adaptive interim analysis where these quantities are estimated from the interim data. The second stage sample size is chosen based on these estimates to achieve a specific overall power. The proposed procedure controls the power in all considered scenarios except for very low first stage sample sizes. The false discovery rate (FDR) is controlled despite of the data dependent choice of sample size. The two-stage design can be a useful tool to determine the sample size of high-dimensional studies if in the planning phase there is high uncertainty regarding the expected effect sizes and variability.

A simple and efficient alternative to implementing systematic random sampling in stereological designs without a motorized microscope stage.

Science.gov (United States)

Melvin, Neal R; Poda, Daniel; Sutherland, Robert J

2007-10-01

When properly applied, stereology is a very robust and efficient method to quantify a variety of parameters from biological material. A common sampling strategy in stereology is systematic random sampling, which involves choosing a random sampling [corrected] start point outside the structure of interest, and sampling relevant objects at [corrected] sites that are placed at pre-determined, equidistant intervals. This has proven to be a very efficient sampling strategy, and is used widely in stereological designs. At the microscopic level, this is most often achieved through the use of a motorized stage that facilitates the systematic random stepping across the structure of interest. Here, we report a simple, precise and cost-effective software-based alternative to accomplishing systematic random sampling under the microscope. We believe that this approach will facilitate the use of stereological designs that employ systematic random sampling in laboratories that lack the resources to acquire costly, fully automated systems.

Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

Science.gov (United States)

Morris, Tim P; Fisher, David J; Kenward, Michael G; Carpenter, James R

2018-04-30

Quantitative evidence synthesis through meta-analysis is central to evidence-based medicine. For well-documented reasons, the meta-analysis of individual patient data is held in higher regard than aggregate data. With access to individual patient data, the analysis is not restricted to a "two-stage" approach (combining estimates and standard errors) but can estimate parameters of interest by fitting a single model to all of the data, a so-called "one-stage" analysis. There has been debate about the merits of one- and two-stage analysis. Arguments for one-stage analysis have typically noted that a wider range of models can be fitted and overall estimates may be more precise. The two-stage side has emphasised that the models that can be fitted in two stages are sufficient to answer the relevant questions, with less scope for mistakes because there are fewer modelling choices to be made in the two-stage approach. For Gaussian data, we consider the statistical arguments for flexibility and precision in small-sample settings. Regarding flexibility, several of the models that can be fitted only in one stage may not be of serious interest to most meta-analysis practitioners. Regarding precision, we consider fixed- and random-effects meta-analysis and see that, for a model making certain assumptions, the number of stages used to fit this model is irrelevant; the precision will be approximately equal. Meta-analysts should choose modelling assumptions carefully. Sometimes relevant models can only be fitted in one stage. Otherwise, meta-analysts are free to use whichever procedure is most convenient to fit the identified model. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.

Directory of Open Access Journals (Sweden)

Jennifer L Smith

Full Text Available Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF, generally collected using the recommended gold-standard cluster randomized surveys (CRS. Integrated Threshold Mapping (ITM has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i the district prevalence of TF; (ii the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii the enrollment rate in schools.Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates

Text Clustering Algorithm Based on Random Cluster Core

Directory of Open Access Journals (Sweden)

Huang Long-Jun

2016-01-01

Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

Effect of Behavior Modification on Outcome in Early- to Moderate-Stage Chronic Kidney Disease: A Cluster-Randomized Trial.

Directory of Open Access Journals (Sweden)

Kunihiro Yamagata

Full Text Available Owing to recent changes in our understanding of the underlying cause of chronic kidney disease (CKD, the importance of lifestyle modification for preventing the progression of kidney dysfunction and complications has become obvious. In addition, effective cooperation between general physicians (GPs and nephrologists is essential to ensure a better care system for CKD treatment. In this cluster-randomized study, we studied the effect of behavior modification on the outcome of early- to moderate-stage CKD.Stratified open cluster-randomized trial.A total of 489 GPs belonging to 49 local medical associations (clusters in Japan.A total of 2,379 patients (1,195 in group A (standard intervention and 1,184 in group B (advanced intervention aged between 40 and 74 years, who had CKD and were under consultation with GPs.All patients were managed in accordance with the current CKD guidelines. The group B clusters received three additional interventions: patients received both educational intervention for lifestyle modification and a CKD status letter, attempting to prevent their withdrawal from treatment, and the group B GPs received data sheets to facilitate reducing the gap between target and practice.The primary outcome measures were 1 the non-adherence rate of accepting continuous medical follow-up of the patients, 2 the collaboration rate between GPs and nephrologists, and 3 the progression of CKD.The rate of discontinuous clinical visits was significantly lower in group B (16.2% in group A vs. 11.5% in group B, p = 0.01. Significantly higher referral and co-treatment rates were observed in group B (p<0.01. The average eGFR deterioration rate tended to be lower in group B (group A: 2.6±5.8 ml/min/1.73 m2/year, group B: 2.4±5.1 ml/min/1.73 m2/year, p = 0.07. A significant difference in eGFR deterioration rate was observed in subjects with Stage 3 CKD (group A: 2.4±5.9 ml/min/1.73 m2/year, group B: 1.9±4.4 ml/min/1.73 m2/year, p = 0.03.Our care

Adjuvant therapy in stage I and stage II epithelial ovarian cancer. Results of two prospective randomized trials

International Nuclear Information System (INIS)

Young, R.C.; Walton, L.A.; Ellenberg, S.S.; Homesley, H.D.; Wilbanks, G.D.; Decker, D.G.; Miller, A.; Park, R.; Major, F. Jr.

1990-01-01

About a third of patients with ovarian cancer present with localized disease; despite surgical resection, up to half the tumors recur. Since it has not been established whether adjuvant treatment can benefit such patients, we conducted two prospective, randomized national cooperative trials of adjuvant therapy in patients with localized ovarian carcinoma. All patients underwent surgical resection plus comprehensive staging and, 18 months later, surgical re-exploration. In the first trial, 81 patients with well-differentiated or moderately well differentiated cancers confined to the ovaries (Stages Iai and Ibi) were assigned to receive either no chemotherapy or melphalan (0.2 mg per kilogram of body weight per day for five days, repeated every four to six weeks for up to 12 cycles). After a median follow-up of more than six years, there were no significant differences between the patients given no chemotherapy and those treated with melphalan with respect to either five-year disease-free survival or overall survival. In the second trial, 141 patients with poorly differentiated Stage I tumors or with cancer outside the ovaries but limited to the pelvis (Stage II) were randomly assigned to treatment with either melphalan (in the same regimen as above) or a single intraperitoneal dose of 32P (15 mCi) at the time of surgery. In this trial (median follow-up, greater than 6 years) the outcomes for the two treatment groups were similar with respect to five-year disease-free survival (80 percent in both groups) and overall survival (81 percent with melphalan vs. 78 percent with 32P; P = 0.48). We conclude that in patients with localized ovarian cancer, comprehensive staging at the time of surgical resection can serve to identify those patients (as defined by the first trial) who can be followed without adjuvant chemotherapy

Topology in two dimensions. II - The Abell and ACO cluster catalogues

Science.gov (United States)

Plionis, Manolis; Valdarnini, Riccardo; Coles, Peter

1992-09-01

We apply a method for quantifying the topology of projected galaxy clustering to the Abell and ACO catalogues of rich clusters. We use numerical simulations to quantify the statistical bias involved in using high peaks to define the large-scale structure, and we use the results obtained to correct our observational determinations for this known selection effect and also for possible errors introduced by boundary effects. We find that the Abell cluster sample is consistent with clusters being identified with high peaks of a Gaussian random field, but that the ACO shows a slight meatball shift away from the Gaussian behavior over and above that expected purely from the high-peak selection. The most conservative explanation of this effect is that it is caused by some artefact of the procedure used to select the clusters in the two samples.

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

Science.gov (United States)

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.

A Smoothing Algorithm for a New Two-Stage Stochastic Model of Supply Chain Based on Sample Average Approximation

Directory of Open Access Journals (Sweden)

Liu Yang

2017-01-01

Full Text Available We construct a new two-stage stochastic model of supply chain with multiple factories and distributors for perishable product. By introducing a second-order stochastic dominance (SSD constraint, we can describe the preference consistency of the risk taker while minimizing the expected cost of company. To solve this problem, we convert it into a one-stage stochastic model equivalently; then we use sample average approximation (SAA method to approximate the expected values of the underlying random functions. A smoothing approach is proposed with which we can get the global solution and avoid introducing new variables and constraints. Meanwhile, we investigate the convergence of an optimal value from solving the transformed model and show that, with probability approaching one at exponential rate, the optimal value converges to its counterpart as the sample size increases. Numerical results show the effectiveness of the proposed algorithm and analysis.

A Two-Stage Method to Determine Optimal Product Sampling considering Dynamic Potential Market

Science.gov (United States)

Hu, Zhineng; Lu, Wei; Han, Bing

2015-01-01

This paper develops an optimization model for the diffusion effects of free samples under dynamic changes in potential market based on the characteristics of independent product and presents a two-stage method to figure out the sampling level. The impact analysis of the key factors on the sampling level shows that the increase of the external coefficient or internal coefficient has a negative influence on the sampling level. And the changing rate of the potential market has no significant influence on the sampling level whereas the repeat purchase has a positive one. Using logistic analysis and regression analysis, the global sensitivity analysis gives a whole analysis of the interaction of all parameters, which provides a two-stage method to estimate the impact of the relevant parameters in the case of inaccuracy of the parameters and to be able to construct a 95% confidence interval for the predicted sampling level. Finally, the paper provides the operational steps to improve the accuracy of the parameter estimation and an innovational way to estimate the sampling level. PMID:25821847

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

Science.gov (United States)

Liu, Jingxia; Colditz, Graham A

2018-05-01

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

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

Science.gov (United States)

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

2016-01-01

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

Single-cluster dynamics for the random-cluster model

NARCIS (Netherlands)

Deng, Y.; Qian, X.; Blöte, H.W.J.

2009-01-01

We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

Analysis of cost data in a cluster-randomized, controlled trial: comparison of methods

DEFF Research Database (Denmark)

Sokolowski, Ineta; Ørnbøl, Eva; Rosendal, Marianne

studies have used non-valid analysis of skewed data. We propose two different methods to compare mean cost in two groups. Firstly, we use a non-parametric bootstrap method where the re-sampling takes place on two levels in order to take into account the cluster effect. Secondly, we proceed with a log......-transformation of the cost data and apply the normal theory on these data. Again we try to account for the cluster effect. The performance of these two methods is investigated in a simulation study. The advantages and disadvantages of the different approaches are discussed.......  We consider health care data from a cluster-randomized intervention study in primary care to test whether the average health care costs among study patients differ between the two groups. The problems of analysing cost data are that most data are severely skewed. Median instead of mean...

40 CFR 761.308 - Sample selection by random number generation on any two-dimensional square grid.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample selection by random number... § 761.79(b)(3) § 761.308 Sample selection by random number generation on any two-dimensional square... area created in accordance with paragraph (a) of this section, select two random numbers: one each for...

Non-ideal magnetohydrodynamic simulations of the two-stage fragmentation model for cluster formation

International Nuclear Information System (INIS)

Bailey, Nicole D.; Basu, Shantanu

2014-01-01

We model molecular cloud fragmentation with thin-disk, non-ideal magnetohydrodynamic simulations that include ambipolar diffusion and partial ionization that transitions from primarily ultraviolet-dominated to cosmic-ray-dominated regimes. These simulations are used to determine the conditions required for star clusters to form through a two-stage fragmentation scenario. Recent linear analyses have shown that the fragmentation length scales and timescales can undergo a dramatic drop across the column density boundary that separates the ultraviolet- and cosmic-ray-dominated ionization regimes. As found in earlier studies, the absence of an ionization drop and regular perturbations leads to a single-stage fragmentation on pc scales in transcritical clouds, so that the nonlinear evolution yields the same fragment sizes as predicted by linear theory. However, we find that a combination of initial transcritical mass-to-flux ratio, evolution through a column density regime in which the ionization drop takes place, and regular small perturbations to the mass-to-flux ratio is sufficient to cause a second stage of fragmentation during the nonlinear evolution. Cores of size ∼0.1 pc are formed within an initial fragment of ∼pc size. Regular perturbations to the mass-to-flux ratio also accelerate the onset of runaway collapse.

Two-stage clustering (TSC: a pipeline for selecting operational taxonomic units for the high-throughput sequencing of PCR amplicons.

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Xiao-Tao Jiang

Full Text Available Clustering 16S/18S rRNA amplicon sequences into operational taxonomic units (OTUs is a critical step for the bioinformatic analysis of microbial diversity. Here, we report a pipeline for selecting OTUs with a relatively low computational demand and a high degree of accuracy. This pipeline is referred to as two-stage clustering (TSC because it divides tags into two groups according to their abundance and clusters them sequentially. The more abundant group is clustered using a hierarchical algorithm similar to that in ESPRIT, which has a high degree of accuracy but is computationally costly for large datasets. The rarer group, which includes the majority of tags, is then heuristically clustered to improve efficiency. To further improve the computational efficiency and accuracy, two preclustering steps are implemented. To maintain clustering accuracy, all tags are grouped into an OTU depending on their pairwise Needleman-Wunsch distance. This method not only improved the computational efficiency but also mitigated the spurious OTU estimation from 'noise' sequences. In addition, OTUs clustered using TSC showed comparable or improved performance in beta-diversity comparisons compared to existing OTU selection methods. This study suggests that the distribution of sequencing datasets is a useful property for improving the computational efficiency and increasing the clustering accuracy of the high-throughput sequencing of PCR amplicons. The software and user guide are freely available at http://hwzhoulab.smu.edu.cn/paperdata/.

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain; Kammoun, Abla

2017-01-01

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show

Two-sample discrimination of Poisson means

Science.gov (United States)

Lampton, M.

1994-01-01

This paper presents a statistical test for detecting significant differences between two random count accumulations. The null hypothesis is that the two samples share a common random arrival process with a mean count proportional to each sample's exposure. The model represents the partition of N total events into two counts, A and B, as a sequence of N independent Bernoulli trials whose partition fraction, f, is determined by the ratio of the exposures of A and B. The detection of a significant difference is claimed when the background (null) hypothesis is rejected, which occurs when the observed sample falls in a critical region of (A, B) space. The critical region depends on f and the desired significance level, alpha. The model correctly takes into account the fluctuations in both the signals and the background data, including the important case of small numbers of counts in the signal, the background, or both. The significance can be exactly determined from the cumulative binomial distribution, which in turn can be inverted to determine the critical A(B) or B(A) contour. This paper gives efficient implementations of these tests, based on lookup tables. Applications include the detection of clustering of astronomical objects, the detection of faint emission or absorption lines in photon-limited spectroscopy, the detection of faint emitters or absorbers in photon-limited imaging, and dosimetry.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

Directory of Open Access Journals (Sweden)

Lauren Hund

Full Text Available Lot quality assurance sampling (LQAS surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

Science.gov (United States)

Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Relative Efficiencies of a Three-Stage Versus a Two-Stage Sample Design For a New NLS Cohort Study. 22U-884-38.

Science.gov (United States)

Folsom, R. E.; Weber, J. H.

Two sampling designs were compared for the planned 1978 national longitudinal survey of high school seniors with respect to statistical efficiency and cost. The 1972 survey used a stratified two-stage sample of high schools and seniors within schools. In order to minimize interviewer travel costs, an alternate sampling design was proposed,…

Exploring biological network structure with clustered random networks

Directory of Open Access Journals (Sweden)

Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

A stratified two-stage sampling design for digital soil mapping in a Mediterranean basin

Science.gov (United States)

Blaschek, Michael; Duttmann, Rainer

2015-04-01

The quality of environmental modelling results often depends on reliable soil information. In order to obtain soil data in an efficient manner, several sampling strategies are at hand depending on the level of prior knowledge and the overall objective of the planned survey. This study focuses on the collection of soil samples considering available continuous secondary information in an undulating, 16 km²-sized river catchment near Ussana in southern Sardinia (Italy). A design-based, stratified, two-stage sampling design has been applied aiming at the spatial prediction of soil property values at individual locations. The stratification based on quantiles from density functions of two land-surface parameters - topographic wetness index and potential incoming solar radiation - derived from a digital elevation model. Combined with four main geological units, the applied procedure led to 30 different classes in the given test site. Up to six polygons of each available class were selected randomly excluding those areas smaller than 1ha to avoid incorrect location of the points in the field. Further exclusion rules were applied before polygon selection masking out roads and buildings using a 20m buffer. The selection procedure was repeated ten times and the set of polygons with the best geographical spread were chosen. Finally, exact point locations were selected randomly from inside the chosen polygon features. A second selection based on the same stratification and following the same methodology (selecting one polygon instead of six) was made in order to create an appropriate validation set. Supplementary samples were obtained during a second survey focusing on polygons that have either not been considered during the first phase at all or were not adequately represented with respect to feature size. In total, both field campaigns produced an interpolation set of 156 samples and a validation set of 41 points. The selection of sample point locations has been done using

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain

2017-03-06

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

Systematic Sampling and Cluster Sampling of Packet Delays

OpenAIRE

Lindh, Thomas

2006-01-01

Based on experiences of a traffic flow performance meter this papersuggests and evaluates cluster sampling and systematic sampling as methods toestimate average packet delays. Systematic sampling facilitates for exampletime analysis, frequency analysis and jitter measurements. Cluster samplingwith repeated trains of periodically spaced sampling units separated by randomstarting periods, and systematic sampling are evaluated with respect to accuracyand precision. Packet delay traces have been ...

Percolation and epidemics in random clustered networks

Science.gov (United States)

Miller, Joel C.

2009-08-01

The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied percolation or epidemics in clustered networks, but the networks often contain preferential contacts in high degree nodes. We introduce a class of random clustered networks and a class of random unclustered networks with the same preferential mixing. Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.

A pilot cluster randomized controlled trial of structured goal-setting following stroke.

Science.gov (United States)

Taylor, William J; Brown, Melanie; William, Levack; McPherson, Kathryn M; Reed, Kirk; Dean, Sarah G; Weatherall, Mark

2012-04-01

To determine the feasibility, the cluster design effect and the variance and minimal clinical importance difference in the primary outcome in a pilot study of a structured approach to goal-setting. A cluster randomized controlled trial. Inpatient rehabilitation facilities. People who were admitted to inpatient rehabilitation following stroke who had sufficient cognition to engage in structured goal-setting and complete the primary outcome measure. Structured goal elicitation using the Canadian Occupational Performance Measure. Quality of life at 12 weeks using the Schedule for Individualised Quality of Life (SEIQOL-DW), Functional Independence Measure, Short Form 36 and Patient Perception of Rehabilitation (measuring satisfaction with rehabilitation). Assessors were blinded to the intervention. Four rehabilitation services and 41 patients were randomized. We found high values of the intraclass correlation for the outcome measures (ranging from 0.03 to 0.40) and high variance of the SEIQOL-DW (SD 19.6) in relation to the minimally importance difference of 2.1, leading to impractically large sample size requirements for a cluster randomized design. A cluster randomized design is not a practical means of avoiding contamination effects in studies of inpatient rehabilitation goal-setting. Other techniques for coping with contamination effects are necessary.

[Automatic Sleep Stage Classification Based on an Improved K-means Clustering Algorithm].

Science.gov (United States)

Xiao, Shuyuan; Wang, Bei; Zhang, Jian; Zhang, Qunfeng; Zou, Junzhong

2016-10-01

Sleep stage scoring is a hotspot in the field of medicine and neuroscience.Visual inspection of sleep is laborious and the results may be subjective to different clinicians.Automatic sleep stage classification algorithm can be used to reduce the manual workload.However,there are still limitations when it encounters complicated and changeable clinical cases.The purpose of this paper is to develop an automatic sleep staging algorithm based on the characteristics of actual sleep data.In the proposed improved K-means clustering algorithm,points were selected as the initial centers by using a concept of density to avoid the randomness of the original K-means algorithm.Meanwhile,the cluster centers were updated according to the‘Three-Sigma Rule’during the iteration to abate the influence of the outliers.The proposed method was tested and analyzed on the overnight sleep data of the healthy persons and patients with sleep disorders after continuous positive airway pressure(CPAP)treatment.The automatic sleep stage classification results were compared with the visual inspection by qualified clinicians and the averaged accuracy reached 76%.With the analysis of morphological diversity of sleep data,it was proved that the proposed improved K-means algorithm was feasible and valid for clinical practice.

Modern survey sampling

CERN Document Server

Chaudhuri, Arijit

2014-01-01

Exposure to SamplingAbstract Introduction Concepts of Population, Sample, and SamplingInitial RamificationsAbstract Introduction Sampling Design, Sampling SchemeRandom Numbers and Their Uses in Simple RandomSampling (SRS)Drawing Simple Random Samples with and withoutReplacementEstimation of Mean, Total, Ratio of Totals/Means:Variance and Variance EstimationDetermination of Sample SizesA.2 Appendix to Chapter 2 A.More on Equal Probability Sampling A.Horvitz-Thompson EstimatorA.SufficiencyA.LikelihoodA.Non-Existence Theorem More Intricacies Abstract Introduction Unequal Probability Sampling StrategiesPPS Sampling Exploring Improved WaysAbstract Introduction Stratified Sampling Cluster SamplingMulti-Stage SamplingMulti-Phase Sampling: Ratio and RegressionEstimationviiviii ContentsControlled SamplingModeling Introduction Super-Population ModelingPrediction Approach Model-Assisted Approach Bayesian Methods Spatial SmoothingSampling on Successive Occasions: Panel Rotation Non-Response and Not-at-Homes Weighting Adj...

Personalized PageRank Clustering: A graph clustering algorithm based on random walks

Science.gov (United States)

A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

2013-11-01

Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

Science.gov (United States)

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

A two-arm cluster randomized control trial to determine the effectiveness of a pressure ulcer prevention bundle for critically ill patients.

Science.gov (United States)

Tayyib, Nahla; Coyer, Fiona; Lewis, Peter A

2015-05-01

This study tested the effectiveness of a pressure ulcer (PU) prevention bundle in reducing the incidence of PUs in critically ill patients in two Saudi intensive care units (ICUs). A two-arm cluster randomized experimental control trial. Participants in the intervention group received the PU prevention bundle, while the control group received standard skin care as per the local ICU policies. Data collected included demographic variables (age, diagnosis, comorbidities, admission trajectory, length of stay) and clinical variables (Braden Scale score, severity of organ function score, mechanical ventilation, PU presence, and staging). All patients were followed every two days from admission through to discharge, death, or up to a maximum of 28 days. Data were analyzed with descriptive correlation statistics, Kaplan-Meier survival analysis, and Poisson regression. The total number of participants recruited was 140: 70 control participants (with a total of 728 days of observation) and 70 intervention participants (784 days of observation). PU cumulative incidence was significantly lower in the intervention group (7.14%) compared to the control group (32.86%). Poisson regression revealed the likelihood of PU development was 70% lower in the intervention group. The intervention group had significantly less Stage I (p = .002) and Stage II PU development (p = .026). Significant improvements were observed in PU-related outcomes with the implementation of the PU prevention bundle in the ICU; PU incidence, severity, and total number of PUs per patient were reduced. Utilizing a bundle approach and standardized nursing language through skin assessment and translation of the knowledge to practice has the potential to impact positively on the quality of care and patient outcome. © 2015 Sigma Theta Tau International.

Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models.

Science.gov (United States)

Krivitsky, Pavel N; Handcock, Mark S; Raftery, Adrian E; Hoff, Peter D

2009-07-01

Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does.

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

Science.gov (United States)

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

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

Evaluation of cluster-randomized trials on maternal and child health research in developing countries

DEFF Research Database (Denmark)

Handlos, Line Neerup; Chakraborty, Hrishikesh; Sen, Pranab Kumar

2009-01-01

To summarize and evaluate all publications including cluster-randomized trials used for maternal and child health research in developing countries during the last 10 years. METHODS: All cluster-randomized trials published between 1998 and 2008 were reviewed, and those that met our criteria...... for inclusion were evaluated further. The criteria for inclusion were that the trial should have been conducted in maternal and child health care in a developing country and that the conclusions should have been made on an individual level. Methods of accounting for clustering in design and analysis were......, and the trials generally improved in quality. CONCLUSIONS: Shortcomings exist in the sample-size calculations and in the analysis of cluster-randomized trials conducted during maternal and child health research in developing countries. Even though there has been improvement over time, further progress in the way...

Core condensation in heavy halos: a two-stage theory for galaxy formation and clustering

Energy Technology Data Exchange (ETDEWEB)

White, S D.M.; Rees, M J [Cambridge Univ. Inst. of Astronomy (UK)

1978-05-01

It is suggested that most of the material in the Universe condensed at an early epoch into small 'dark' objects. Irrespective of their nature, these objects must subsequently have undergone hierarchical clustering, whose present scale is inferred from the large-scale distribution of galaxies. As each stage of the hierarchy forms and collapses, relaxation effects wipe out its substructure, and to a self-similar distribution of bound masses. The entire luminous content of galaxies, however, results from the cooling and fragmentation of residual gas within the transient potential wells provided by the dark matter. Every galaxy thus forms as a concentrated luminous core embedded in an extensive dark halo. The observed sizes of galaxies and their survival through later stages of the hierarchy seem inexplicable without invoking substantial dissipation; this dissipation allows the galaxies to become sufficiently concentrated to survive the disruption of their halos in groups and clusters of galaxies. A specific model is proposed in which ..cap omega.. approximately equals 0.2, the dark matter makes up 80 per cent of the total mass, and half the residual gas has been converted into luminous galaxies by the present time. This model is consistent with the inferred proportions of dark matter and gas in rich clusters, with the observed luminosity density of the Universe and with the observed radii of galaxies; further, it predicts the characteristic luminosities of bright galaxies can give a luminosity function of the observed shape.

The covariance matrix of the Potts model: A random cluster analysis

International Nuclear Information System (INIS)

Borgs, C.; Chayes, J.T.

1996-01-01

We consider the covariance matrix, G mn = q 2 x ,m); δ(σ y ,n)>, of the d-dimensional q-states Potts model, rewriting it in the random cluster representation of Fortuin and Kasteleyn. In many of the q ordered phases, we identify the eigenvalues of this matrix both in terms of representations of the unbroken symmetry group of the model and in terms of random cluster connectivities and covariances, thereby attributing algebraic significance to these stochastic geometric quantities. We also show that the correlation length and the correlation length corresponding to the decay rate of one on the eigenvalues in the same as the inverse decay rate of the diameter of finite clusters. For dimension of d=2, we show that this correlation length and the correlation length of two-point function with free boundary conditions at the corresponding dual temperature are equal up to a factor of two. For systems with first-order transitions, this relation helps to resolve certain inconsistencies between recent exact and numerical work on correlation lengths at the self-dual point β o . For systems with second order transitions, this relation implies the equality of the correlation length exponents from above below threshold, as well as an amplitude ratio of two. In the course of proving the above results, we establish several properties of independent interest, including left continuity of the inverse correlation length with free boundary conditions and upper semicontinuity of the decay rate for finite clusters in all dimensions, and left continuity of the two-dimensional free boundary condition percolation probability at β o . We also introduce DLR equations for the random cluster model and use them to establish ergodicity of the free measure. In order to prove these results, we introduce a new class of events which we call decoupling events and two inequalities for these events

Spectral embedded clustering: a framework for in-sample and out-of-sample spectral clustering.

Science.gov (United States)

Nie, Feiping; Zeng, Zinan; Tsang, Ivor W; Xu, Dong; Zhang, Changshui

2011-11-01

Spectral clustering (SC) methods have been successfully applied to many real-world applications. The success of these SC methods is largely based on the manifold assumption, namely, that two nearby data points in the high-density region of a low-dimensional data manifold have the same cluster label. However, such an assumption might not always hold on high-dimensional data. When the data do not exhibit a clear low-dimensional manifold structure (e.g., high-dimensional and sparse data), the clustering performance of SC will be degraded and become even worse than K -means clustering. In this paper, motivated by the observation that the true cluster assignment matrix for high-dimensional data can be always embedded in a linear space spanned by the data, we propose the spectral embedded clustering (SEC) framework, in which a linearity regularization is explicitly added into the objective function of SC methods. More importantly, the proposed SEC framework can naturally deal with out-of-sample data. We also present a new Laplacian matrix constructed from a local regression of each pattern and incorporate it into our SEC framework to capture both local and global discriminative information for clustering. Comprehensive experiments on eight real-world high-dimensional datasets demonstrate the effectiveness and advantages of our SEC framework over existing SC methods and K-means-based clustering methods. Our SEC framework significantly outperforms SC using the Nyström algorithm on unseen data.

Economic Design of Acceptance Sampling Plans in a Two-Stage Supply Chain

Directory of Open Access Journals (Sweden)

Lie-Fern Hsu

2012-01-01

Full Text Available Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer's and consumer's quality and risk requirements. However, all the available QC tables and computer software determine the sampling plan on a noneconomic basis. In this paper, we design an economic model to determine the optimal sampling plan in a two-stage supply chain that minimizes the producer's and the consumer's total quality cost while satisfying both the producer's and consumer's quality and risk requirements. Numerical examples show that the optimal sampling plan is quite sensitive to the producer's product quality. The product's inspection, internal failure, and postsale failure costs also have an effect on the optimal sampling plan.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

Science.gov (United States)

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

The Hubble Space Telescope Medium Deep Survey Cluster Sample: Methodology and Data

Science.gov (United States)

Ostrander, E. J.; Nichol, R. C.; Ratnatunga, K. U.; Griffiths, R. E.

1998-12-01

We present a new, objectively selected, sample of galaxy overdensities detected in the Hubble Space Telescope Medium Deep Survey (MDS). These clusters/groups were found using an automated procedure that involved searching for statistically significant galaxy overdensities. The contrast of the clusters against the field galaxy population is increased when morphological data are used to search around bulge-dominated galaxies. In total, we present 92 overdensities above a probability threshold of 99.5%. We show, via extensive Monte Carlo simulations, that at least 60% of these overdensities are likely to be real clusters and groups and not random line-of-sight superpositions of galaxies. For each overdensity in the MDS cluster sample, we provide a richness and the average of the bulge-to-total ratio of galaxies within each system. This MDS cluster sample potentially contains some of the most distant clusters/groups ever detected, with about 25% of the overdensities having estimated redshifts z > ~0.9. We have made this sample publicly available to facilitate spectroscopic confirmation of these clusters and help more detailed studies of cluster and galaxy evolution. We also report the serendipitous discovery of a new cluster close on the sky to the rich optical cluster Cl l0016+16 at z = 0.546. This new overdensity, HST 001831+16208, may be coincident with both an X-ray source and a radio source. HST 001831+16208 is the third cluster/group discovered near to Cl 0016+16 and appears to strengthen the claims of Connolly et al. of superclustering at high redshift.

Teen Dating Violence Prevention: Cluster-Randomized Trial of Teen Choices, an Online, Stage-Based Program for Healthy, Nonviolent Relationships.

Science.gov (United States)

Levesque, Deborah A; Johnson, Janet L; Welch, Carol A; Prochaska, Janice M; Paiva, Andrea L

2016-07-01

Teen dating violence is a serious public health problem. A cluster-randomized trial was conducted to assess the efficacy of Teen Choices , a 3-session online program that delivers assessments and individualized guidance matched to dating history, dating violence experiences, and stage of readiness for using healthy relationship skills. For high risk victims of dating violence, the program addresses readiness to keep oneself safe in relationships. Twenty high schools were randomly assigned to the Teen Choices condition ( n =2,000) or a Comparison condition ( n =1,901). Emotional and physical dating violence victimization and perpetration were assessed at 6 and 12 months in the subset of participants (total n =2,605) who reported a past-year history of dating violence at baseline, and/or who dated during the study. The Teen Choices program was associated with significantly reduced odds of all four types of dating violence (adjusted ORs ranging from .45 to .63 at 12 months follow-up). For three of the four violence outcomes, participants with a past-year history of that type of violence benefited significantly more from the intervention than students without a past-year history. The Teen Choices program provides an effective and practicable strategy for intervention for teen dating violence prevention.

Evaluation of stability of k-means cluster ensembles with respect to random initialization.

Science.gov (United States)

Kuncheva, Ludmila I; Vetrov, Dmitry P

2006-11-01

Many clustering algorithms, including cluster ensembles, rely on a random component. Stability of the results across different runs is considered to be an asset of the algorithm. The cluster ensembles considered here are based on k-means clusterers. Each clusterer is assigned a random target number of clusters, k and is started from a random initialization. Here, we use 10 artificial and 10 real data sets to study ensemble stability with respect to random k, and random initialization. The data sets were chosen to have a small number of clusters (two to seven) and a moderate number of data points (up to a few hundred). Pairwise stability is defined as the adjusted Rand index between pairs of clusterers in the ensemble, averaged across all pairs. Nonpairwise stability is defined as the entropy of the consensus matrix of the ensemble. An experimental comparison with the stability of the standard k-means algorithm was carried out for k from 2 to 20. The results revealed that ensembles are generally more stable, markedly so for larger k. To establish whether stability can serve as a cluster validity index, we first looked at the relationship between stability and accuracy with respect to the number of clusters, k. We found that such a relationship strongly depends on the data set, varying from almost perfect positive correlation (0.97, for the glass data) to almost perfect negative correlation (-0.93, for the crabs data). We propose a new combined stability index to be the sum of the pairwise individual and ensemble stabilities. This index was found to correlate better with the ensemble accuracy. Following the hypothesis that a point of stability of a clustering algorithm corresponds to a structure found in the data, we used the stability measures to pick the number of clusters. The combined stability index gave best results.

Smoothing the redshift distributions of random samples for the baryon acoustic oscillations: applications to the SDSS-III BOSS DR12 and QPM mock samples

Science.gov (United States)

Wang, Shao-Jiang; Guo, Qi; Cai, Rong-Gen

2017-12-01

We investigate the impact of different redshift distributions of random samples on the baryon acoustic oscillations (BAO) measurements of D_V(z)r_d^fid/r_d from the two-point correlation functions of galaxies in the Data Release 12 of the Baryon Oscillation Spectroscopic Survey (BOSS). Big surveys, such as BOSS, usually assign redshifts to the random samples by randomly drawing values from the measured redshift distributions of the data, which would necessarily introduce fiducial signals of fluctuations into the random samples, weakening the signals of BAO, if the cosmic variance cannot be ignored. We propose a smooth function of redshift distribution that fits the data well to populate the random galaxy samples. The resulting cosmological parameters match the input parameters of the mock catalogue very well. The significance of BAO signals has been improved by 0.33σ for a low-redshift sample and by 0.03σ for a constant-stellar-mass sample, though the absolute values do not change significantly. Given the precision of the measurements of current cosmological parameters, it would be appreciated for the future improvements on the measurements of galaxy clustering.

Systematic versus random sampling in stereological studies.

Science.gov (United States)

West, Mark J

2012-12-01

The sampling that takes place at all levels of an experimental design must be random if the estimate is to be unbiased in a statistical sense. There are two fundamental ways by which one can make a random sample of the sections and positions to be probed on the sections. Using a card-sampling analogy, one can pick any card at all out of a deck of cards. This is referred to as independent random sampling because the sampling of any one card is made without reference to the position of the other cards. The other approach to obtaining a random sample would be to pick a card within a set number of cards and others at equal intervals within the deck. Systematic sampling along one axis of many biological structures is more efficient than random sampling, because most biological structures are not randomly organized. This article discusses the merits of systematic versus random sampling in stereological studies.

A semi-supervised method to detect seismic random noise with fuzzy GK clustering

International Nuclear Information System (INIS)

Hashemi, Hosein; Javaherian, Abdolrahim; Babuska, Robert

2008-01-01

We present a new method to detect random noise in seismic data using fuzzy Gustafson–Kessel (GK) clustering. First, using an adaptive distance norm, a matrix is constructed from the observed seismic amplitudes. The next step is to find centres of ellipsoidal clusters and construct a partition matrix which determines the soft decision boundaries between seismic events and random noise. The GK algorithm updates the cluster centres in order to iteratively minimize the cluster variance. Multiplication of the fuzzy membership function with values of each sample yields new sections; we name them 'clustered sections'. The seismic amplitude values of the clustered sections are given in a way to decrease the level of noise in the original noisy seismic input. In pre-stack data, it is essential to study the clustered sections in a f–k domain; finding the quantitative index for weighting the post-stack data needs a similar approach. Using the knowledge of a human specialist together with the fuzzy unsupervised clustering, the method is a semi-supervised random noise detection. The efficiency of this method is investigated on synthetic and real seismic data for both pre- and post-stack data. The results show a significant improvement of the input noisy sections without harming the important amplitude and phase information of the original data. The procedure for finding the final weights of each clustered section should be carefully done in order to keep almost all the evident seismic amplitudes in the output section. The method interactively uses the knowledge of the seismic specialist in detecting the noise

Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion

Science.gov (United States)

Scott, Charles J. C.; Thom, Alex J. W.

2017-09-01

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behavior of a coupled cluster wavefunction representation, we propose new approaches based on an intuitive, well-defined condition for sampling weights and on sampling the expansion in cluster operators of different excitation levels. We term these modifications even and truncated selections, respectively. Utilising both approaches demonstrates dramatically improved calculation stability as well as reduced computational and memory costs. These modifications are particularly effective at higher truncation levels owing to the large number of terms within the cluster expansion that can be neglected, as demonstrated by the reduction of the number of terms to be sampled when truncating at triple excitations by 77% and hextuple excitations by 98%.

A cluster randomized trial of strategies to increase uptake amongst young women invited for their first cervical screen: The STRATEGIC trial.

Science.gov (United States)

Kitchener, H; Gittins, M; Cruickshank, M; Moseley, C; Fletcher, S; Albrow, R; Gray, A; Brabin, L; Torgerson, D; Crosbie, E J; Sargent, A; Roberts, C

2018-06-01

Objectives To measure the feasibility and effectiveness of interventions to increase cervical screening uptake amongst young women. Methods A two-phase cluster randomized trial conducted in general practices in the NHS Cervical Screening Programme. In Phase 1, women in practices randomized to intervention due for their first invitation to cervical screening received a pre-invitation leaflet and, separately, access to online booking. In Phase 2, non-attenders at six months were randomized to one of: vaginal self-sample kits sent unrequested or offered; timed appointments; nurse navigator; or the choice between nurse navigator or self-sample kits. Primary outcome was uplift in intervention vs. control practices, at 3 and 12 months post invitation. Results Phase 1 randomized 20,879 women. Neither pre-invitation leaflet nor online booking increased screening uptake by three months (18.8% pre-invitation leaflet vs. 19.2% control and 17.8% online booking vs. 17.2% control). Uptake was higher amongst human papillomavirus vaccinees at three months (OR 2.07, 95% CI 1.69-2.53, p < 0.001). Phase 2 randomized 10,126 non-attenders, with 32-34 clusters for each intervention and 100 clusters as controls. Sending self-sample kits increased uptake at 12 months (OR 1.51, 95% CI 1.20-1.91, p = 0.001), as did timed appointments (OR 1.41, 95% CI 1.14-1.74, p = 0.001). The offer of a nurse navigator, a self-sample kits on request, and choice between timed appointments and nurse navigator were ineffective. Conclusions Amongst non-attenders, self-sample kits sent and timed appointments achieved an uplift in screening over the short term; longer term impact is less certain. Prior human papillomavirus vaccination was associated with increased screening uptake.

The Design of Cluster Randomized Trials with Random Cross-Classifications

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Moerbeek, Mirjam; Safarkhani, Maryam

2018-01-01

Data from cluster randomized trials do not always have a pure hierarchical structure. For instance, students are nested within schools that may be crossed by neighborhoods, and soldiers are nested within army units that may be crossed by mental health-care professionals. It is important that the random cross-classification is taken into account…

An intervention to improve program implementation: findings from a two-year cluster randomized trial of Assets-Getting To Outcomes

Science.gov (United States)

2013-01-01

Background Studies have shown that communities have not always been able to implement evidence-based prevention programs with quality and achieve outcomes demonstrated by prevention science. Implementation support interventions are needed to bridge this gap between science and practice. The purpose of this article is to present two-year outcomes from an evaluation of the Assets Getting To Outcomes (AGTO) intervention in 12 Maine communities engaged in promoting Developmental Assets, a positive youth development approach to prevention. AGTO is an implementation support intervention that consists of: a manual of text and tools; face-to-face training, and onsite technical assistance, focused on activities shown to be associated with obtaining positive results across any prevention program. Methods This study uses a nested and cross-sectional, cluster randomized controlled design. Participants were coalition members and program staff from 12 communities in Maine. Each coalition nominated up to five prevention programs to participate. At random, six coalitions and their respective 30 programs received the two-year AGTO intervention and the other six maintained routine operations. The study assessed prevention practitioner capacity (efficacy and behaviors), practitioner exposure to and use of AGTO, practitioner perceptions of AGTO, and prevention program performance. Capacity of coalition members and performance of their programs were compared between the two groups across the baseline, one-, and two-year time points. Results We found no significant differences between AGTO and control group’s prevention capacity. However, within the AGTO group, significant differences were found between those with greater exposure to and use of AGTO. Programs that received the highest number of technical assistance hours showed the most program improvement. Conclusions This study is the first of its kind to show that use of an implementation support intervention-AGTO -yielded

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR

Directory of Open Access Journals (Sweden)

Bochaton Audrey

2007-06-01

Full Text Available Abstract Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

Science.gov (United States)

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be

A combined heating cooling stage for cluster thermalization in the gas phase

International Nuclear Information System (INIS)

Ievlev, D.N.; Kuester, A.; Enders, A.; Malinowski, N.; Schaber, H.; Kern, K.

2003-01-01

We report on the design and performance of a combined heating/cooling stage for the thermalization of clusters in a gas phase time-of-flight mass spectrometer. With this setup the cluster temperature can sensitively be adjusted within the range from 100 up to 800 K and higher. The unique combination of a heating stage with a subsequent cooling stage allows us to perform thermodynamic investigations on clusters at very high temperatures without quality losses in the spectra due to delayed fragmentation in the drift tube of the mass spectrometer. The performance of the setup is demonstrated by the example of (C 60 ) n clusters

Cluster Tails for Critical Power-Law Inhomogeneous Random Graphs

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van der Hofstad, Remco; Kliem, Sandra; van Leeuwaarden, Johan S. H.

2018-04-01

Recently, the scaling limit of cluster sizes for critical inhomogeneous random graphs of rank-1 type having finite variance but infinite third moment degrees was obtained in Bhamidi et al. (Ann Probab 40:2299-2361, 2012). It was proved that when the degrees obey a power law with exponent τ \\in (3,4), the sequence of clusters ordered in decreasing size and multiplied through by n^{-(τ -2)/(τ -1)} converges as n→ ∞ to a sequence of decreasing non-degenerate random variables. Here, we study the tails of the limit of the rescaled largest cluster, i.e., the probability that the scaling limit of the largest cluster takes a large value u, as a function of u. This extends a related result of Pittel (J Combin Theory Ser B 82(2):237-269, 2001) for the Erdős-Rényi random graph to the setting of rank-1 inhomogeneous random graphs with infinite third moment degrees. We make use of delicate large deviations and weak convergence arguments.

A Two-Stage Estimation Method for Random Coefficient Differential Equation Models with Application to Longitudinal HIV Dynamic Data.

Science.gov (United States)

Fang, Yun; Wu, Hulin; Zhu, Li-Xing

2011-07-01

We propose a two-stage estimation method for random coefficient ordinary differential equation (ODE) models. A maximum pseudo-likelihood estimator (MPLE) is derived based on a mixed-effects modeling approach and its asymptotic properties for population parameters are established. The proposed method does not require repeatedly solving ODEs, and is computationally efficient although it does pay a price with the loss of some estimation efficiency. However, the method does offer an alternative approach when the exact likelihood approach fails due to model complexity and high-dimensional parameter space, and it can also serve as a method to obtain the starting estimates for more accurate estimation methods. In addition, the proposed method does not need to specify the initial values of state variables and preserves all the advantages of the mixed-effects modeling approach. The finite sample properties of the proposed estimator are studied via Monte Carlo simulations and the methodology is also illustrated with application to an AIDS clinical data set.

Two-stage revision of septic knee prosthesis with articulating knee spacers yields better infection eradication rate than one-stage or two-stage revision with static spacers.

Science.gov (United States)

Romanò, C L; Gala, L; Logoluso, N; Romanò, D; Drago, L

2012-12-01

The best method for treating chronic periprosthetic knee infection remains controversial. Randomized, comparative studies on treatment modalities are lacking. This systematic review of the literature compares the infection eradication rate after two-stage versus one-stage revision and static versus articulating spacers in two-stage procedures. We reviewed full-text papers and those with an abstract in English published from 1966 through 2011 that reported the success rate of infection eradication after one-stage or two-stage revision with two different types of spacers. In all, 6 original articles reporting the results after one-stage knee exchange arthoplasty (n = 204) and 38 papers reporting on two-stage revision (n = 1,421) were reviewed. The average success rate in the eradication of infection was 89.8% after a two-stage revision and 81.9% after a one-stage procedure at a mean follow-up of 44.7 and 40.7 months, respectively. The average infection eradication rate after a two-stage procedure was slightly, although significantly, higher when an articulating spacer rather than a static spacer was used (91.2 versus 87%). The methodological limitations of this study and the heterogeneous material in the studies reviewed notwithstanding, this systematic review shows that, on average, a two-stage procedure is associated with a higher rate of eradication of infection than one-stage revision for septic knee prosthesis and that articulating spacers are associated with a lower recurrence of infection than static spacers at a comparable mean duration of follow-up. IV.

Randomization-Based Inference about Latent Variables from Complex Samples: The Case of Two-Stage Sampling

Science.gov (United States)

Li, Tiandong

2012-01-01

In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…

A cross-sectional, randomized cluster sample survey of household vulnerability to extreme heat among slum dwellers in ahmedabad, india.

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Tran, Kathy V; Azhar, Gulrez S; Nair, Rajesh; Knowlton, Kim; Jaiswal, Anjali; Sheffield, Perry; Mavalankar, Dileep; Hess, Jeremy

2013-06-18

Extreme heat is a significant public health concern in India; extreme heat hazards are projected to increase in frequency and severity with climate change. Few of the factors driving population heat vulnerability are documented, though poverty is a presumed risk factor. To facilitate public health preparedness, an assessment of factors affecting vulnerability among slum dwellers was conducted in summer 2011 in Ahmedabad, Gujarat, India. Indicators of heat exposure, susceptibility to heat illness, and adaptive capacity, all of which feed into heat vulnerability, was assessed through a cross-sectional household survey using randomized multistage cluster sampling. Associations between heat-related morbidity and vulnerability factors were identified using multivariate logistic regression with generalized estimating equations to account for clustering effects. Age, preexisting medical conditions, work location, and access to health information and resources were associated with self-reported heat illness. Several of these variables were unique to this study. As sociodemographics, occupational heat exposure, and access to resources were shown to increase vulnerability, future interventions (e.g., health education) might target specific populations among Ahmedabad urban slum dwellers to reduce vulnerability to extreme heat. Surveillance and evaluations of future interventions may also be worthwhile.

Poor Prognosis Indicated by Venous Circulating Tumor Cell Clusters in Early-Stage Lung Cancers.

Science.gov (United States)

Murlidhar, Vasudha; Reddy, Rishindra M; Fouladdel, Shamileh; Zhao, Lili; Ishikawa, Martin K; Grabauskiene, Svetlana; Zhang, Zhuo; Lin, Jules; Chang, Andrew C; Carrott, Philip; Lynch, William R; Orringer, Mark B; Kumar-Sinha, Chandan; Palanisamy, Nallasivam; Beer, David G; Wicha, Max S; Ramnath, Nithya; Azizi, Ebrahim; Nagrath, Sunitha

2017-09-15

Early detection of metastasis can be aided by circulating tumor cells (CTC), which also show potential to predict early relapse. Because of the limited CTC numbers in peripheral blood in early stages, we investigated CTCs in pulmonary vein blood accessed during surgical resection of tumors. Pulmonary vein (PV) and peripheral vein (Pe) blood specimens from patients with lung cancer were drawn during the perioperative period and assessed for CTC burden using a microfluidic device. From 108 blood samples analyzed from 36 patients, PV had significantly higher number of CTCs compared with preoperative Pe ( P ontology analysis revealed enrichment of cell migration and immune-related pathways in CTC clusters, suggesting survival advantage of clusters in circulation. Clusters display characteristics of therapeutic resistance, indicating the aggressive nature of these cells. Thus, CTCs isolated from early stages of lung cancer are predictive of poor prognosis and can be interrogated to determine biomarkers predictive of recurrence. Cancer Res; 77(18); 5194-206. ©2017 AACR . ©2017 American Association for Cancer Research.

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

Science.gov (United States)

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

A Random Walk Approach to Query Informative Constraints for Clustering.

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Abin, Ahmad Ali

2017-08-09

This paper presents a random walk approach to the problem of querying informative constraints for clustering. The proposed method is based on the properties of the commute time, that is the expected time taken for a random walk to travel between two nodes and return, on the adjacency graph of data. Commute time has the nice property of that, the more short paths connect two given nodes in a graph, the more similar those nodes are. Since computing the commute time takes the Laplacian eigenspectrum into account, we use this property in a recursive fashion to query informative constraints for clustering. At each recursion, the proposed method constructs the adjacency graph of data and utilizes the spectral properties of the commute time matrix to bipartition the adjacency graph. Thereafter, the proposed method benefits from the commute times distance on graph to query informative constraints between partitions. This process iterates for each partition until the stop condition becomes true. Experiments on real-world data show the efficiency of the proposed method for constraints selection.

BWIP-RANDOM-SAMPLING, Random Sample Generation for Nuclear Waste Disposal

International Nuclear Information System (INIS)

Sagar, B.

1989-01-01

1 - Description of program or function: Random samples for different distribution types are generated. Distribution types as required for performance assessment modeling of geologic nuclear waste disposal are provided. These are: - Uniform, - Log-uniform (base 10 or natural), - Normal, - Lognormal (base 10 or natural), - Exponential, - Bernoulli, - User defined continuous distribution. 2 - Method of solution: A linear congruential generator is used for uniform random numbers. A set of functions is used to transform the uniform distribution to the other distributions. Stratified, rather than random, sampling can be chosen. Truncated limits can be specified on many distributions, whose usual definition has an infinite support. 3 - Restrictions on the complexity of the problem: Generation of correlated random variables is not included

Sampling Methods in Cardiovascular Nursing Research: An Overview.

Science.gov (United States)

Kandola, Damanpreet; Banner, Davina; O'Keefe-McCarthy, Sheila; Jassal, Debbie

2014-01-01

Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. The selection of specific participant samples is an important part of the research design and process. The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. There are two main categories of sampling methods: probability and non-probability. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Each approach offers distinct advantages and disadvantages and must be considered critically. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research.

A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image

Directory of Open Access Journals (Sweden)

Fei Wang

2017-01-01

Full Text Available An Intensified Charge-Coupled Device (ICCD image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a Different from the independent identically distributed (i.i.d. noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge

OpenAIRE

Catarino, Rosa; Vassilakos, Pierre; Bilancioni, Aline; Vanden Eynde, Mathieu; Meyer-Hamme, Ulrike; Menoud, Pierre-Alain; Guerry, Fr?d?ric; Petignat, Patrick

2015-01-01

Background Human papillomavirus (HPV) self-sampling (self-HPV) is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab. Methods A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed f...

A sero-survey of rinderpest in nomadic pastoral systems in central and southern Somalia from 2002 to 2003, using a spatially integrated random sampling approach.

Science.gov (United States)

Tempia, S; Salman, M D; Keefe, T; Morley, P; Freier, J E; DeMartini, J C; Wamwayi, H M; Njeumi, F; Soumaré, B; Abdi, A M

2010-12-01

A cross-sectional sero-survey, using a two-stage cluster sampling design, was conducted between 2002 and 2003 in ten administrative regions of central and southern Somalia, to estimate the seroprevalence and geographic distribution of rinderpest (RP) in the study area, as well as to identify potential risk factors for the observed seroprevalence distribution. The study was also used to test the feasibility of the spatially integrated investigation technique in nomadic and semi-nomadic pastoral systems. In the absence of a systematic list of livestock holdings, the primary sampling units were selected by generating random map coordinates. A total of 9,216 serum samples were collected from cattle aged 12 to 36 months at 562 sampling sites. Two apparent clusters of RP seroprevalence were detected. Four potential risk factors associated with the observed seroprevalence were identified: the mobility of cattle herds, the cattle population density, the proximity of cattle herds to cattle trade routes and cattle herd size. Risk maps were then generated to assist in designing more targeted surveillance strategies. The observed seroprevalence in these areas declined over time. In subsequent years, similar seroprevalence studies in neighbouring areas of Kenya and Ethiopia also showed a very low seroprevalence of RP or the absence of antibodies against RP. The progressive decline in RP antibody prevalence is consistent with virus extinction. Verification of freedom from RP infection in the Somali ecosystem is currently in progress.

A systematic review of the usage of flow diagram in cluster randomized trials

Directory of Open Access Journals (Sweden)

Kostić M.

2014-01-01

Full Text Available Flow diagram represent an integral part of consolidated standards of reporting trials (CONSORT. Its use in reporting cluster randomization trials is highly recommended. The aim of this article is to present frequency of the use of flow diagram in cluster randomized trials in accordance with standards of reporting. The team has researched Medline database and singled-out 474 studies with cluster randomization for analysis. The studies were reviewed to identify the use of graphic representation, compliance with standards of reporting and the date when study was published. Depending from its duration, studies were divided on completed, and those still ongoing. Usage of CONSORT is recorded in 145 (31% literature units. Frequency of flow diagram was statistically much higher in studies which were in compliance with standards (86,2%, in comparison to those which did not use CONSORT guidelines (71,4%, as well as in completed studies (81,2% in comparison to pilot project studies (54,3%. Number of cluster randomized trials gathered through MEDLINE's search of key words 'cluster randomized trial [ti]' and 'cluster randomised trial [ti]', as well as the use of CONSORT in the reports of cluster randomized trials, are showing linear growth over time (p<0,001. Frequency of flow diagram is higher in the reports of cluster randomized trials that were done in accordance with the standards of reporting.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys

OpenAIRE

Hund, Lauren; Bedrick, Edward J.; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we comp...

Ab initio random structure search for 13-atom clusters of fcc elements

International Nuclear Information System (INIS)

Chou, J P; Hsing, C R; Wei, C M; Cheng, C; Chang, C M

2013-01-01

The 13-atom metal clusters of fcc elements (Al, Rh, Ir, Ni, Pd, Pt, Cu, Ag, Au) were studied by density functional theory calculations. The global minima were searched for by the ab initio random structure searching method. In addition to some new lowest-energy structures for Pd 13 and Au 13 , we found that the effective coordination numbers of the lowest-energy clusters would increase with the ratio of the dimer-to-bulk bond length. This correlation, together with the electronic structures of the lowest-energy clusters, divides the 13-atom clusters of these fcc elements into two groups (except for Au 13 , which prefers a two-dimensional structure due to the relativistic effect). Compact-like clusters that are composed exclusively of triangular motifs are preferred for elements without d-electrons (Al) or with (nearly) filled d-band electrons (Ni, Pd, Cu, Ag). Non-compact clusters composed mainly of square motifs connected by some triangular motifs (Rh, Ir, Pt) are favored for elements with unfilled d-band electrons. (paper)

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

Science.gov (United States)

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

The clustering of local maxima in random noise

International Nuclear Information System (INIS)

Coles, P.

1989-01-01

A mixture of analytic and numerical techniques is used to study the clustering properties of local maxima of random noise. Technical complexities restrict us to the case of 1D noise, but the results obtained should give a reasonably accurate picture of the behaviour of cosmological density peaks in noise defined on a 3D domain. We give estimates of the two-point correlation function of local maxima, for both Gaussian and non-Gaussian noise and show that previous approximations are not accurate. (author)

Can group-based reassuring information alter low back pain behavior? A cluster-randomized controlled trial

DEFF Research Database (Denmark)

Frederiksen, Pernille; Indahl, Aage; Andersen, Lars L

2017-01-01

-randomized controlled trial. METHODS: Publically employed workers (n = 505) from 11 Danish municipality centers were randomized at center-level (cluster) to either intervention (two 1-hour group-based talks at the workplace) or control. The talks provided reassuring information together with a simple non...

Clustering for high-dimension, low-sample size data using distance vectors

OpenAIRE

Terada, Yoshikazu

2013-01-01

In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that contain information of the cluster structure in high-dimensional space. Based on this fact, we propose an efficient and simple clustering approach, called distance vector clustering, for HDLSS data. Under the assumptions given in the work of Hall et al. (2005), w...

Combining evidence from multiple electronic health care databases: performances of one-stage and two-stage meta-analysis in matched case-control studies.

Science.gov (United States)

La Gamba, Fabiola; Corrao, Giovanni; Romio, Silvana; Sturkenboom, Miriam; Trifirò, Gianluca; Schink, Tania; de Ridder, Maria

2017-10-01

Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential. Copyright © 2017 John Wiley & Sons, Ltd.

Selection bias and subject refusal in a cluster-randomized controlled trial

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Rochelle Yang

2017-07-01

Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1

Cluster emission at pre-equilibrium stage in Heavy Nuclear Reactions. A Model considering the Thermodynamics of Small Systems

International Nuclear Information System (INIS)

Bermudez Martinez, A.; Damiani, D.; Guzman Martinez, F.; Rodriguez Hoyos, O.; Rodriguez Manso, A.

2015-01-01

Cluster emission at pre-equilibrium stage, in heavy ion fusion reactions of 12 C and 16 O nuclei with 116 Sn, 208 Pb, 238 U are studied. the energy of the projectile nuclei was chosen at 0.25GeV, 0.5GeV and 1GeV. A cluster formation model is developed in order to calculate the cluster size. Thermodynamics of small systems was used in order to examine the cluster behavior inside the nuclear media. This model is based on considering two phases inside the compound nucleus, on one hand the nuclear media phase, and on the other hand the cluster itself. The cluster acts like an instability inside the compound nucleus, provoking an exchange of nucleons with the nuclear media through its surface. The processes were simulated using Monte Carlo methods. We obtained that the cluster emission probability shows great dependence on the cluster size. This project is aimed to implement cluster emission processes, during the pre-equilibrium stage, in the frame of CRISP code (Collaboration Rio-Sao Paulo). (Author)

A Smoothing Algorithm for a New Two-Stage Stochastic Model of Supply Chain Based on Sample Average Approximation

OpenAIRE

Liu Yang; Yao Xiong; Xiao-jiao Tong

2017-01-01

We construct a new two-stage stochastic model of supply chain with multiple factories and distributors for perishable product. By introducing a second-order stochastic dominance (SSD) constraint, we can describe the preference consistency of the risk taker while minimizing the expected cost of company. To solve this problem, we convert it into a one-stage stochastic model equivalently; then we use sample average approximation (SAA) method to approximate the expected values of the underlying r...

Single-stage laparoscopic common bile duct exploration and cholecystectomy versus two-stage endoscopic stone extraction followed by laparoscopic cholecystectomy for patients with concomitant gallbladder stones and common bile duct stones: a randomized controlled trial.

Science.gov (United States)

Bansal, Virinder Kumar; Misra, Mahesh C; Rajan, Karthik; Kilambi, Ragini; Kumar, Subodh; Krishna, Asuri; Kumar, Atin; Pandav, Chandrakant S; Subramaniam, Rajeshwari; Arora, M K; Garg, Pramod Kumar

2014-03-01

The ideal method for managing concomitant gallbladder stones and common bile duct (CBD) stones is debatable. The currently preferred method is two-stage endoscopic stone extraction followed by laparoscopic cholecystectomy (LC). This prospective randomized trial compared the success and cost effectiveness of single- and two-stage management of patients with concomitant gallbladder and CBD stones. Consecutive patients with concomitant gallbladder and CBD stones were randomized to either single-stage laparoscopic CBD exploration and cholecystectomy (group 1) or endoscopic retrograde cholangiopancreatography (ERCP) for endoscopic extraction of CBD stones followed by LC (group 2). Success was defined as complete clearance of CBD and cholecystectomy by the intended method. Cost effectiveness was measured using the incremental cost-effectiveness ratio. Intention-to-treat analysis was performed to compare outcomes. From February 2009 to October 2012, 168 patients were randomized: 84 to the single-stage procedure (group 1) and 84 to the two-stage procedure (group 2). Both groups were matched with regard to demographic and clinical parameters. The success rates of laparoscopic CBD exploration and ERCP for clearance of CBD were similar (91.7 vs. 88.1 %). The overall success rate also was comparable: 88.1 % in group 1 and 79.8 % in group 2 (p = 0.20). Direct choledochotomy was performed in 83 of the 84 patients. The mean operative time was significantly longer in group 1 (135.7 ± 36.6 vs. 72.4 ± 27.6 min; p ≤ 0.001), but the overall hospital stay was significantly shorter (4.6 ± 2.4 vs. 5.3 ± 6.2 days; p = 0.03). Group 2 had a significantly greater number of procedures per patient (p gallbladder and CBD stones had similar success and complication rates, but the single-stage strategy was better in terms of shorter hospital stay, need for fewer procedures, and cost effectiveness.

Two-stage electrolysis to enrich tritium in environmental water

International Nuclear Information System (INIS)

Shima, Nagayoshi; Muranaka, Takeshi

2007-01-01

We present a two-stage electrolyzing procedure to enrich tritium in environmental waters. Tritium is first enriched rapidly through a commercially-available electrolyser with a large 50A current, and then through a newly-designed electrolyser that avoids the memory effect, with a 6A current. Tritium recovery factor obtained by such a two-stage electrolysis was greater than that obtained when using the commercially-available device solely. Water samples collected in 2006 in lakes and along the Pacific coast of Aomori prefecture, Japan, were electrolyzed using the two-stage method. Tritium concentrations in these samples ranged from 0.2 to 0.9 Bq/L and were half or less, that in samples collected at the same sites in 1992. (author)

On Angular Sampling Methods for 3-D Spatial Channel Models

DEFF Research Database (Denmark)

Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum

2015-01-01

This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....

Ethical and policy issues in cluster randomized trials: rationale and design of a mixed methods research study

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Chaudhry Shazia H

2009-07-01

Full Text Available Abstract Background Cluster randomized trials are an increasingly important methodological tool in health research. In cluster randomized trials, intact social units or groups of individuals, such as medical practices, schools, or entire communities – rather than individual themselves – are randomly allocated to intervention or control conditions, while outcomes are then observed on individual cluster members. The substantial methodological differences between cluster randomized trials and conventional randomized trials pose serious challenges to the current conceptual framework for research ethics. The ethical implications of randomizing groups rather than individuals are not addressed in current research ethics guidelines, nor have they even been thoroughly explored. The main objectives of this research are to: (1 identify ethical issues arising in cluster trials and learn how they are currently being addressed; (2 understand how ethics reviews of cluster trials are carried out in different countries (Canada, the USA and the UK; (3 elicit the views and experiences of trial participants and cluster representatives; (4 develop well-grounded guidelines for the ethical conduct and review of cluster trials by conducting an extensive ethical analysis and organizing a consensus process; (5 disseminate the guidelines to researchers, research ethics boards (REBs, journal editors, and research funders. Methods We will use a mixed-methods (qualitative and quantitative approach incorporating both empirical and conceptual work. Empirical work will include a systematic review of a random sample of published trials, a survey and in-depth interviews with trialists, a survey of REBs, and in-depth interviews and focus group discussions with trial participants and gatekeepers. The empirical work will inform the concurrent ethical analysis which will lead to a guidance document laying out principles, policy options, and rationale for proposed guidelines. An

Clustering problems for geochemical data

International Nuclear Information System (INIS)

Kane, V.E.; Larson, N.M.

1977-01-01

The Union Carbide Corporation, Nuclear Division, Uranium Resource Evaluation Project uses a two-stage sampling program to identify potential uranium districts. Cluster analysis techniques are used in locating high density sampling areas as well as in identifying potential uranium districts. Problems are considered involving the analysis of multivariate censored data, laboratory measurement error, and data standardization

Random clustering ferns for multimodal object recognition

OpenAIRE

Villamizar Vergel, Michael Alejandro; Garrell Zulueta, Anais; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc

2017-01-01

The final publication is available at link.springer.com We propose an efficient and robust method for the recognition of objects exhibiting multiple intra-class modes, where each one is associated with a particular object appearance. The proposed method, called random clustering ferns, combines synergically a single and real-time classifier, based on the boosted assembling of extremely randomized trees (ferns), with an unsupervised and probabilistic approach in order to recognize efficient...

Measurement Error Correction Formula for Cluster-Level Group Differences in Cluster Randomized and Observational Studies

Science.gov (United States)

Cho, Sun-Joo; Preacher, Kristopher J.

2016-01-01

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

A Bayesian Justification for Random Sampling in Sample Survey

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Glen Meeden

2012-07-01

Full Text Available In the usual Bayesian approach to survey sampling the sampling design, plays a minimal role, at best. Although a close relationship between exchangeable prior distributions and simple random sampling has been noted; how to formally integrate simple random sampling into the Bayesian paradigm is not clear. Recently it has been argued that the sampling design can be thought of as part of a Bayesian's prior distribution. We will show here that under this scenario simple random sample can be given a Bayesian justification in survey sampling.

Cluster-randomized xylitol toothpaste trial for early childhood caries prevention.

Science.gov (United States)

Chi, Donald L; Tut, Ohnmar; Milgrom, Peter

2014-01-01

The purpose of this study was to assess the efficacy of supervised tooth-brushing with xylitol toothpaste to prevent early childhood caries (ECC) and reduce mutans streptococci. In this cluster-randomized efficacy trial, 196 four- to five-year-old children in four Head Start classrooms in the Marshall Islands were randomly assigned to supervised toothbrushing with 1,400 ppm/31 percent fluoride xylitol or 1,450 ppm fluoride sorbitol toothpaste. We hypothesized that there would be no difference in efficacy between the two types of toothpaste. The primary outcome was the surface-level primary molar caries increment (d(2-3)mfs) after six months. A single examiner was blinded to classroom assignments. Two classrooms were assigned to the fluoride-xylitol group (85 children), and two classrooms were assigned to the fluoride-sorbitol group (83 children). The child-level analyses accounted for clustering. There was no difference between the two groups in baseline or end-of-trial mean d(2-3)mfs. The mean d(2-3)mfs increment was greater in the fluoride-xylitol group compared to the fluoride-sorbitol group (2.5 and 1.4 d(2-3)mfs, respectively), but the difference was not significant (95% confidence interval: -0.17, 2.37; P=.07). No adverse effects were reported. After six months, brushing with a low-strength xylitol/fluoride tooth-paste is no more efficacious in reducing ECC than a fluoride-only toothpaste in a high caries-risk child population.

Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes

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Heinz Gallaun

2015-09-01

Full Text Available Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.

Effect of food additives on hyperphosphatemia among patients with end-stage renal disease: a randomized controlled trial.

Science.gov (United States)

Sullivan, Catherine; Sayre, Srilekha S; Leon, Janeen B; Machekano, Rhoderick; Love, Thomas E; Porter, David; Marbury, Marquisha; Sehgal, Ashwini R

2009-02-11

High dietary phosphorus intake has deleterious consequences for renal patients and is possibly harmful for the general public as well. To prevent hyperphosphatemia, patients with end-stage renal disease limit their intake of foods that are naturally high in phosphorus. However, phosphorus-containing additives are increasingly being added to processed and fast foods. The effect of such additives on serum phosphorus levels is unclear. To determine the effect of limiting the intake of phosphorus-containing food additives on serum phosphorus levels among patients with end-stage renal disease. Cluster randomized controlled trial at 14 long-term hemodialysis facilities in northeast Ohio. Two hundred seventy-nine patients with elevated baseline serum phosphorus levels (>5.5 mg/dL) were recruited between May and October 2007. Two shifts at each of 12 large facilities and 1 shift at each of 2 small facilities were randomly assigned to an intervention or control group. Intervention participants (n=145) received education on avoiding foods with phosphorus additives when purchasing groceries or visiting fast food restaurants. Control participants (n=134) continued to receive usual care. Change in serum phosphorus level after 3 months. At baseline, there was no significant difference in serum phosphorus levels between the 2 groups. After 3 months, the decline in serum phosphorus levels was 0.6 mg/dL larger among intervention vs control participants (95% confidence interval, -1.0 to -0.1 mg/dL). Intervention participants also had statistically significant increases in reading ingredient lists (Pfood knowledge scores (P = .13). Educating end-stage renal disease patients to avoid phosphorus-containing food additives resulted in modest improvements in hyperphosphatemia. clinicaltrials.gov Identifier: NCT00583570.

Sleep stages identification in patients with sleep disorder using k-means clustering

Science.gov (United States)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

Ferromagnetic clusters induced by a nonmagnetic random disorder in diluted magnetic semiconductors

Energy Technology Data Exchange (ETDEWEB)

Bui, Dinh-Hoi [Institute of Research and Development, Duy Tan University, K7/25 Quang Trung, Danang (Viet Nam); Physics Department, Hue University’s College of Education, 34 Le Loi, Hue (Viet Nam); Phan, Van-Nham, E-mail: phanvannham@dtu.edu.vn [Institute of Research and Development, Duy Tan University, K7/25 Quang Trung, Danang (Viet Nam)

2016-12-15

In this work, we analyze the nonmagnetic random disorder leading to a formation of ferromagnetic clusters in diluted magnetic semiconductors. The nonmagnetic random disorder arises from randomness in the host lattice. Including the disorder to the Kondo lattice model with random distribution of magnetic dopants, the ferromagnetic–paramagnetic transition in the system is investigated in the framework of dynamical mean-field theory. At a certain low temperature one finds a fraction of ferromagnetic sites transiting to the paramagnetic state. Enlarging the nonmagnetic random disorder strength, the paramagnetic regimes expand resulting in the formation of the ferromagnetic clusters.

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

Science.gov (United States)

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Expanding Comparative Literature into Comparative Sciences Clusters with Neutrosophy and Quad-stage Method

Directory of Open Access Journals (Sweden)

Fu Yuhua

2016-08-01

Full Text Available By using Neutrosophy and Quad-stage Method, the expansions of comparative literature include: comparative social sciences clusters, comparative natural sciences clusters, comparative interdisciplinary sciences clusters, and so on. Among them, comparative social sciences clusters include: comparative literature, comparative history, comparative philosophy, and so on; comparative natural sciences clusters include: comparative mathematics, comparative physics, comparative chemistry, comparative medicine, comparative biology, and so on.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

Science.gov (United States)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

Science.gov (United States)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Projection correlation between two random vectors.

Science.gov (United States)

Zhu, Liping; Xu, Kai; Li, Runze; Zhong, Wei

2017-12-01

We propose the use of projection correlation to characterize dependence between two random vectors. Projection correlation has several appealing properties. It equals zero if and only if the two random vectors are independent, it is not sensitive to the dimensions of the two random vectors, it is invariant with respect to the group of orthogonal transformations, and its estimation is free of tuning parameters and does not require moment conditions on the random vectors. We show that the sample estimate of the projection correction is [Formula: see text]-consistent if the two random vectors are independent and root-[Formula: see text]-consistent otherwise. Monte Carlo simulation studies indicate that the projection correlation has higher power than the distance correlation and the ranks of distances in tests of independence, especially when the dimensions are relatively large or the moment conditions required by the distance correlation are violated.

Two-stage revision surgery with preformed spacers and cementless implants for septic hip arthritis: a prospective, non-randomized cohort study

Directory of Open Access Journals (Sweden)

Logoluso Nicola

2011-05-01

Full Text Available Abstract Background Outcome data on two-stage revision surgery for deep infection after septic hip arthritis are limited and inconsistent. This study presents the medium-term results of a new, standardized two-stage arthroplasty with preformed hip spacers and cementless implants in a consecutive series of adult patients with septic arthritis of the hip treated according to a same protocol. Methods Nineteen patients (20 hips were enrolled in this prospective, non-randomized cohort study between 2000 and 2008. The first stage comprised femoral head resection, debridement, and insertion of a preformed, commercially available, antibiotic-loaded cement hip spacer. After eradication of infection, a cementless total hip arthroplasty was implanted in the second stage. Patients were assessed for infection recurrence, pain (visual analog scale [VAS] and hip joint function (Harris Hip score. Results The mean time between first diagnosis of infection and revision surgery was 5.8 ± 9.0 months; the average duration of follow up was 56.6 (range, 24 - 104 months; all 20 hips were successfully converted to prosthesis an average 22 ± 5.1 weeks after spacer implantation. Reinfection after total hip joint replacement occurred in 1 patient. The mean VAS pain score improved from 48 (range, 35 - 84 pre-operatively to 18 (range, 0 - 38 prior to spacer removal and to 8 (range, 0 - 15 at the last follow-up assessment after prosthesis implantation. The average Harris Hip score improved from 27.5 before surgery to 61.8 between the two stages to 92.3 at the final follow-up assessment. Conclusions Satisfactory outcomes can be obtained with two-stage revision hip arthroplasty using preformed spacers and cementless implants for prosthetic hip joint infections of various etiologies.

Employing post-DEA cross-evaluation and cluster analysis in a sample of Greek NHS hospitals.

Science.gov (United States)

Flokou, Angeliki; Kontodimopoulos, Nick; Niakas, Dimitris

2011-10-01

To increase Data Envelopment Analysis (DEA) discrimination of efficient Decision Making Units (DMUs), by complementing "self-evaluated" efficiencies with "peer-evaluated" cross-efficiencies and, based on these results, to classify the DMUs using cluster analysis. Healthcare, which is deprived of such studies, was chosen as the study area. The sample consisted of 27 small- to medium-sized (70-500 beds) NHS general hospitals distributed throughout Greece, in areas where they are the sole NHS representatives. DEA was performed on 2005 data collected from the Ministry of Health and the General Secretariat of the National Statistical Service. Three inputs -hospital beds, physicians and other health professionals- and three outputs -case-mix adjusted hospitalized cases, surgeries and outpatient visits- were included in input-oriented, constant-returns-to-scale (CRS) and variable-returns-to-scale (VRS) models. In a second stage (post-DEA), aggressive and benevolent cross-efficiency formulations and clustering were employed, to validate (or not) the initial DEA scores. The "maverick index" was used to sort the peer-appraised hospitals. All analyses were performed using custom-made software. Ten benchmark hospitals were identified by DEA, but using the aggressive and benevolent formulations showed that two and four of them respectively were at the lower end of the maverick index list. On the other hand, only one 100% efficient (self-appraised) hospital was at the higher end of the list, using either formulation. Cluster analysis produced a hierarchical "tree" structure which dichotomized the hospitals in accordance to the cross-evaluation results, and provided insight on the two-dimensional path to improving efficiency. This is, to our awareness, the first study in the healthcare domain to employ both of these post-DEA techniques (cross efficiency and clustering) at the hospital (i.e. micro) level. The potential benefit for decision-makers is the capability to examine high

An unbiased estimator of the variance of simple random sampling using mixed random-systematic sampling

OpenAIRE

Padilla, Alberto

2009-01-01

Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. By means of a mixed random - systematic sample, an unbiased estimator o...

The Transeurope Footrace Project: longitudinal data acquisition in a cluster randomized mobile MRI observational cohort study on 44 endurance runners at a 64-stage 4,486km transcontinental ultramarathon

Directory of Open Access Journals (Sweden)

Schütz Uwe HW

2012-07-01

Full Text Available Abstract Background The TransEurope FootRace 2009 (TEFR09 was one of the longest transcontinental ultramarathons with an extreme endurance physical load of running nearly 4,500 km in 64 days. The aim of this study was to assess the wide spectrum of adaptive responses in humans regarding the different tissues, organs and functional systems being exposed to such chronic physical endurance load with limited time for regeneration and resulting negative energy balance. A detailed description of the TEFR project and its implemented measuring methods in relation to the hypotheses are presented. Methods The most important research tool was a 1.5 Tesla magnetic resonance imaging (MRI scanner mounted on a mobile unit following the ultra runners from stage to stage each day. Forty-four study volunteers (67% of the participants were cluster randomized into two groups for MRI measurements (22 subjects each according to the project protocol with its different research modules: musculoskeletal system, brain and pain perception, cardiovascular system, body composition, and oxidative stress and inflammation. Complementary to the diverse daily mobile MR-measurements on different topics (muscle and joint MRI, T2*-mapping of cartilage, MR-spectroscopy of muscles, functional MRI of the brain, cardiac and vascular cine MRI, whole body MRI other methods were also used: ice-water pain test, psychometric questionnaires, bioelectrical impedance analysis (BIA, skinfold thickness and limb circumference measurements, daily urine samples, periodic blood samples and electrocardiograms (ECG. Results Thirty volunteers (68% reached the finish line at North Cape. The mean total race speed was 8.35 km/hour. Finishers invested 552 hours in total. The completion rate for planned MRI investigations was more than 95%: 741 MR-examinations with 2,637 MRI sequences (more than 200,000 picture data, 5,720 urine samples, 244 blood samples, 205 ECG, 1,018 BIA, 539 anthropological

Cluster-randomized xylitol toothpaste trial for early childhood caries prevention

Science.gov (United States)

Chi, Donald L.; Tut, Ohnmar K.; Milgrom, Peter

2013-01-01

Purpose We assessed the efficacy of supervised toothbrushing with xylitol toothpaste to prevent early childhood caries (ECC) and to reduce mutans streptococci (MS). Methods In this cluster-randomized efficacy trial, 4 Head Start classrooms in the Marshall Islands were randomly assigned to supervised toothbrushing with 1,400ppm/31% fluoride-xylitol (Epic Dental, Provo, UT) or 1,450ppm fluoride-sorbitol toothpaste (Colgate-Palmolive, New York, NY) (N=196 children, ages 4–5 yrs). We hypothesized no difference in efficacy between the two types of toothpaste. The primary outcome was primary molar d2-3mfs increment after 6 mos. A single examiner was blinded to classroom assignments. Two classrooms were assigned to the fluoride-xylitol group (85 children) and 2 classrooms to the fluoride-sorbitol group (83 children). The child-level analyses accounted for clustering. Results There was no difference between the two groups in baseline or end-of-trial mean d2-3mfs. The mean d2-3mfs increment was greater in the fluoride-xylitol group compared to the fluoride-sorbitol group (2.5 and 1.4 d2-3mfs, respectively), but the difference was not significant (95% CI:−0.17, 2.37;P=0.07). No adverse effects were reported. Conclusion After 6 mos, brushing with a low strength xylitol/fluoride toothpaste is no more efficacious in reducing ECC than a fluoride only toothpaste in a high caries risk child population. PMID:24709430

Production of complex particles in low energy spallation and in fragmentation reactions by in-medium random clusterization

International Nuclear Information System (INIS)

Lacroix, D.; Durand, D.

2005-09-01

Rules for in-medium complex particle production in nuclear reactions are proposed. These rules have been implemented in two models to simulate nucleon-nucleus and nucleus-nucleus reactions around the Fermi energy. Our work emphasizes the effect of randomness in cluster formation, the importance of the nucleonic Fermi motion as well as the role of conservation laws. The concepts of total available phase-space and explored phase-space under constraint imposed by the reaction are clarified. The compatibility of experimental observations with a random clusterization is illustrated in a schematic scenario of a proton-nucleus collision. The role of randomness under constraint is also illustrated in the nucleus-nucleus case. (authors)

Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

Science.gov (United States)

Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard

2012-06-01

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Bond percolation on a class of correlated and clustered random graphs

International Nuclear Information System (INIS)

Allard, A; Hébert-Dufresne, L; Noël, P-A; Marceau, V; Dubé, L J

2012-01-01

We introduce a formalism for computing bond percolation properties of a class of correlated and clustered random graphs. This class of graphs is a generalization of the configuration model where nodes of different types are connected via different types of hyperedges, edges that can link more than two nodes. We argue that the multitype approach coupled with the use of clustered hyperedges can reproduce a wide spectrum of complex patterns, and thus enhances our capability to model real complex networks. As an illustration of this claim, we use our formalism to highlight unusual behaviours of the size and composition of the components (small and giant) in a synthetic, albeit realistic, social network. (paper)

Sampling large random knots in a confined space

International Nuclear Information System (INIS)

Arsuaga, J; Blackstone, T; Diao, Y; Hinson, K; Karadayi, E; Saito, M

2007-01-01

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e n 2 )). We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n 2 ). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications

Sampling large random knots in a confined space

Science.gov (United States)

Arsuaga, J.; Blackstone, T.; Diao, Y.; Hinson, K.; Karadayi, E.; Saito, M.

2007-09-01

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e^{n^2}) . We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n2). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications.

Sampling large random knots in a confined space

Energy Technology Data Exchange (ETDEWEB)

Arsuaga, J [Department of Mathematics, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132 (United States); Blackstone, T [Department of Computer Science, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132 (United States); Diao, Y [Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223 (United States); Hinson, K [Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223 (United States); Karadayi, E [Department of Mathematics, University of South Florida, 4202 E Fowler Avenue, Tampa, FL 33620 (United States); Saito, M [Department of Mathematics, University of South Florida, 4202 E Fowler Avenue, Tampa, FL 33620 (United States)

2007-09-28

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e{sup n{sup 2}}). We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n{sup 2}). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications.

A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos

KAUST Repository

Wu, Baoyuan

2016-10-25

Face clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face clustering and face tracking from real world videos. The motivation for the proposed research is that face clustering and face tracking can provide useful information and constraints to each other, thus can bootstrap and improve the performances of each other. To this end, we introduce a Coupled Hidden Markov Random Field (CHMRF) to simultaneously model face clustering, face tracking, and their interactions. We provide an effective algorithm based on constrained clustering and optimal tracking for the joint optimization of cluster labels and face tracking. We demonstrate significant improvements over state-of-the-art results in face clustering and tracking on several videos.

Air quality comparison between two European ceramic tile clusters

Science.gov (United States)

Minguillón, M. C.; Monfort, E.; Escrig, A.; Celades, I.; Guerra, L.; Busani, G.; Sterni, A.; Querol, X.

2013-08-01

The European ceramic tile industry is mostly concentrated in two clusters, one in Castelló (Spain) and another one in Modena (Italy). Industrial clusters may have problems to accomplish the EU air quality regulations because of the concentration of some specific pollutants and, hence, the feasibility of the industrial clusters can be jeopardised. The present work assesses the air quality in these ceramic clusters in 2008, when the new EU emission regulations where put into force. PM10 samples were collected at two sampling sites in the Modena ceramic cluster and one sampling site in the Castelló ceramic cluster. PM10 annual average concentrations were 12-14 μg m-3 higher in Modena than in Castelló, and were close to or exceeded the European limit. Air quality in Modena was mainly influenced by road traffic and, in a lower degree, the metalmechanical industry, as evidenced by the high concentrations of Mn, Cu, Zn, Sn and Sb registered. The stagnant weather conditions from Modena hindering dispersion of pollutants also contributed to the relatively high pollution levels. In Castelló, the influence of the ceramic industry is evidenced by the high concentrations of Ti, Se, Tl and Pb, whereas this influence is not seen in Modena. The difference in the impact of the ceramic industry on the air quality in the two areas was attributed to: better abatement systems in the spray-drier facilities in Modena, higher coverage of the areas for storage and handling of dusty raw materials in Modena, presence of two open air quarries in the Castelló region, low degree of abatement systems in the ceramic tile kilns in Castelló, and abundance of ceramic frit, glaze and pigment manufacture in Castelló as opposed to scarce manufacture of these products in Modena. The necessity of additional measures to fulfil the EU air quality requirements in the Modena region is evidenced, despite the high degree of environmental measures implemented in the ceramic industry. The Principal

Meaningful Effect Sizes, Intraclass Correlations, and Proportions of Variance Explained by Covariates for Planning Two- and Three-Level Cluster Randomized Trials of Social and Behavioral Outcomes.

Science.gov (United States)

Dong, Nianbo; Reinke, Wendy M; Herman, Keith C; Bradshaw, Catherine P; Murray, Desiree W

2016-09-30

There is a need for greater guidance regarding design parameters and empirical benchmarks for social and behavioral outcomes to inform assumptions in the design and interpretation of cluster randomized trials (CRTs). We calculated the empirical reference values on critical research design parameters associated with statistical power for children's social and behavioral outcomes, including effect sizes, intraclass correlations (ICCs), and proportions of variance explained by a covariate at different levels (R 2 ). Children from kindergarten to Grade 5 in the samples from four large CRTs evaluating the effectiveness of two classroom- and two school-level preventive interventions. Teacher ratings of students' social and behavioral outcomes using the Teacher Observation of Classroom Adaptation-Checklist and the Social Competence Scale-Teacher. Two types of effect size benchmarks were calculated: (1) normative expectations for change and (2) policy-relevant demographic performance gaps. The ICCs and R 2 were calculated using two-level hierarchical linear modeling (HLM), where students are nested within schools, and three-level HLM, where students were nested within classrooms, and classrooms were nested within schools. Comprehensive tables of benchmarks and ICC values are provided to inform prevention researchers in interpreting the effect size of interventions and conduct power analyses for designing CRTs of children's social and behavioral outcomes. The discussion also provides a demonstration for how to use the parameter reference values provided in this article to calculate the sample size for two- and three-level CRTs designs. © The Author(s) 2016.

MAPS OF MASSIVE CLUMPS IN THE EARLY STAGE OF CLUSTER FORMATION: TWO MODES OF CLUSTER FORMATION, COEVAL OR NON-COEVAL?

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Aya E.; Saito, Masao; Mauersberger, Rainer; Kawabe, Ryohei [Joint ALMA Observatory, Alonso de Cordova 3107, Vitacura, Santiago (Chile); Kurono, Yasutaka; Naoi, Takahiro, E-mail: ahiguchi@alma.cl [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan)

2013-03-10

We present maps of seven young massive molecular clumps within five target regions in C{sup 18}O (J = 1-0) line emission, using the Nobeyama 45 m telescope. These clumps, which are not associated with clusters, lie at distances between 0.7 and 2.1 kpc. We find C{sup 18}O clumps with radii of 0.5-1.7 pc, masses of 470-4200 M{sub Sun }, and velocity widths of 1.4-3.3 km s{sup -1}. All of the clumps are massive and approximately in virial equilibrium, suggesting they will potentially form clusters. Three of our target regions are associated with H II regions (CWHRs), while the other two are unassociated with H II regions (CWOHRs). The C{sup 18}O clumps can be classified into two morphological types: CWHRs with a filamentary or shell-like structure and spherical CWOHRs. The two CWOHRs have systematic velocity gradients. Using the publicly released WISE database, Class I and Class II protostellar candidates are identified within the C{sup 18}O clumps. The fraction of Class I candidates among all YSO candidates (Class I+Class II) is {>=}50% in CWHRs and {<=}50% in CWOHRs. We conclude that effects from the H II regions can be seen in (1) the spatial distributions of the clumps: filamentary or shell-like structure running along the H II regions; (2) the velocity structures of the clumps: large velocity dispersion along shells; and (3) the small age spreads of YSOs. The small spreads in age of the YSOs show that the presence of H II regions tends to trigger coeval cluster formation.

k-Means: Random Sampling Procedure

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. k-Means: Random Sampling Procedure. Optimal 1-Mean is. Approximation of Centroid (Inaba et al). S = random sample of size O(1/ ); Centroid of S is a (1+ )-approx centroid of P with constant probability.

HICOSMO - X-ray analysis of a complete sample of galaxy clusters

Science.gov (United States)

Schellenberger, G.; Reiprich, T.

2017-10-01

Galaxy clusters are known to be the largest virialized objects in the Universe. Based on the theory of structure formation one can use them as cosmological probes, since they originate from collapsed overdensities in the early Universe and witness its history. The X-ray regime provides the unique possibility to measure in detail the most massive visible component, the intra cluster medium. Using Chandra observations of a local sample of 64 bright clusters (HIFLUGCS) we provide total (hydrostatic) and gas mass estimates of each cluster individually. Making use of the completeness of the sample we quantify two interesting cosmological parameters by a Bayesian cosmological likelihood analysis. We find Ω_{M}=0.3±0.01 and σ_{8}=0.79±0.03 (statistical uncertainties) using our default analysis strategy combining both, a mass function analysis and the gas mass fraction results. The main sources of biases that we discuss and correct here are (1) the influence of galaxy groups (higher incompleteness in parent samples and a differing behavior of the L_{x} - M relation), (2) the hydrostatic mass bias (as determined by recent hydrodynamical simulations), (3) the extrapolation of the total mass (comparing various methods), (4) the theoretical halo mass function and (5) other cosmological (non-negligible neutrino mass), and instrumental (calibration) effects.

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge.

Science.gov (United States)

Catarino, Rosa; Vassilakos, Pierre; Bilancioni, Aline; Vanden Eynde, Mathieu; Meyer-Hamme, Ulrike; Menoud, Pierre-Alain; Guerry, Frédéric; Petignat, Patrick

2015-01-01

Human papillomavirus (HPV) self-sampling (self-HPV) is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab. A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed first: self-HPV using dry swabs (s-DRY) or vaginal specimen collection using a cytobrush applied to an FTA cartridge (s-FTA). After self-HPV, a physician collected a cervical sample using liquid-based medium (Dr-WET). HPV types were identified by real-time PCR. Agreement between collection methods was measured using the kappa statistic. HPV prevalence for high-risk types was 62.3% (95%CI: 53.7-70.2) detected by s-DRY, 56.2% (95%CI: 47.6-64.4) by Dr-WET, and 54.6% (95%CI: 46.1-62.9) by s-FTA. There was overall agreement of 70.8% between s-FTA and s-DRY samples (kappa = 0.34), and of 82.3% between self-HPV and Dr-WET samples (kappa = 0.56). Detection sensitivities for low-grade squamous intraepithelial lesion or worse (LSIL+) were: 64.0% (95%CI: 44.5-79.8) for s-FTA, 84.6% (95%CI: 66.5-93.9) for s-DRY, and 76.9% (95%CI: 58.0-89.0) for Dr-WET. The preferred self-collection method among patients was s-DRY (40.8% vs. 15.4%). Regarding costs, FTA card was five times more expensive than the swab (~5 US dollars (USD)/per card vs. ~1 USD/per swab). Self-HPV using dry swabs is sensitive for detecting LSIL+ and less expensive than s-FTA. International Standard Randomized Controlled Trial Number (ISRCTN): 43310942.

Analyzing indirect effects in cluster randomized trials. The effect of estimation method, number of groups and group sizes on accuracy and power.

Directory of Open Access Journals (Sweden)

Joop eHox

2014-02-01

Full Text Available Cluster randomized trials assess the effect of an intervention that is carried out at the group or cluster level. Ajzen’s theory of planned behaviour is often used to model the effect of the intervention as an indirect effect mediated in turn by attitude, norms and behavioural intention. Structural equation modelling (SEM is the technique of choice to estimate indirect effects and their significance. However, this is a large sample technique, and its application in a cluster randomized trial assumes a relatively large number of clusters. In practice, the number of clusters in these studies tends to be relatively small, e.g. much less than fifty. This study uses simulation methods to find the lowest number of clusters needed when multilevel SEM is used to estimate the indirect effect. Maximum likelihood estimation is compared to Bayesian analysis, with the central quality criteria being accuracy of the point estimate and the confidence interval. We also investigate the power of the test for the indirect effect. We conclude that Bayes estimation works well with much smaller cluster level sample sizes such as 20 cases than maximum likelihood estimation; although the bias is larger the coverage is much better. When only 5 to 10 clusters are available per treatment condition even with Bayesian estimation problems occur.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

Science.gov (United States)

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Generation and Analysis of Constrained Random Sampling Patterns

DEFF Research Database (Denmark)

Pierzchlewski, Jacek; Arildsen, Thomas

2016-01-01

Random sampling is a technique for signal acquisition which is gaining popularity in practical signal processing systems. Nowadays, event-driven analog-to-digital converters make random sampling feasible in practical applications. A process of random sampling is defined by a sampling pattern, which...... indicates signal sampling points in time. Practical random sampling patterns are constrained by ADC characteristics and application requirements. In this paper, we introduce statistical methods which evaluate random sampling pattern generators with emphasis on practical applications. Furthermore, we propose...... algorithm generates random sampling patterns dedicated for event-driven-ADCs better than existed sampling pattern generators. Finally, implementation issues of random sampling patterns are discussed....

On the limiting characteristics of quantum random number generators at various clusterings of photocounts

Science.gov (United States)

Molotkov, S. N.

2017-03-01

Various methods for the clustering of photocounts constituting a sequence of random numbers are considered. It is shown that the clustering of photocounts resulting in the Fermi-Dirac distribution makes it possible to achieve the theoretical limit of the random number generation rate.

Health plan auditing: 100-percent-of-claims vs. random-sample audits.

Science.gov (United States)

Sillup, George P; Klimberg, Ronald K

2011-01-01

The objective of this study was to examine the relative efficacy of two different methodologies for auditing self-funded medical claim expenses: 100-percent-of-claims auditing versus random-sampling auditing. Multiple data sets of claim errors or 'exceptions' from two Fortune-100 corporations were analysed and compared to 100 simulated audits of 300- and 400-claim random samples. Random-sample simulations failed to identify a significant number and amount of the errors that ranged from $200,000 to $750,000. These results suggest that health plan expenses of corporations could be significantly reduced if they audited 100% of claims and embraced a zero-defect approach.

E-learning or educational leaflet: does it make a difference in oral health promotion? A clustered randomized trial.

Science.gov (United States)

Al Bardaweel, Susan; Dashash, Mayssoon

2018-05-10

The early recognition of technology together with great ability to use computers and smart systems have promoted researchers to investigate the possibilities of utilizing technology for improving health care in children. The aim of this study was to compare between the traditional educational leaflets and E-applications in improving oral health knowledge, oral hygiene and gingival health in schoolchildren of Damascus city, Syria. A clustered randomized controlled trial at two public primary schools was performed. About 220 schoolchildren aged 10-11 years were included in this study and grouped into two clusters. Children in Leaflet cluster received oral health education through leaflets, while children in E-learning cluster received oral health education through an E-learning program. A questionnaire was designed to register information related to oral health knowledge and to record Plaque and Gingival indices. Questionnaire administration and clinical assessment were undertaken at baseline, 6 and at 12 weeks of oral health education. Data was analysed using one way repeated measures ANOVA, post hoc Bonferroni test and independent samples t-test. Leaflet cluster (107 participants) had statistically significant better oral health knowledge than E-learning cluster (104 participants) at 6 weeks (P E-learning cluster:100 participants). The mean knowledge gain compared to baseline was higher in Leaflet cluster than in E-learning cluster. A significant reduction in the PI means at 6 weeks and 12 weeks was observed in both clusters (P E-learning cluster at 6 weeks (P E-learning cluster at 6 weeks (P < 0.05) and 12 weeks (P < 0.05). Traditional educational leaflets are an effective tool in the improvement of both oral health knowledge as well as clinical indices of oral hygiene and care among Syrian children. Leaflets can be used in school-based oral health education for a positive outcome. Australian New Zealand Clinical Trials Registry ( ACTRN

Precipitation and clustering in the early stages of ageing in Inconel 718

International Nuclear Information System (INIS)

Alam, Talukder; Chaturvedi, Mahesh; Ringer, Simon P.; Cairney, Julie M.

2010-01-01

Research highlights: → IN718 could be age hardened rapidly by secondary phase formation. → Co-located phases were observed in the earliest stage of detection. → Clustering of Ti/Al and Nb atoms was observed prior to precipitation. - Abstract: In this report we investigate the onset and evolution of precipitation in the early stages of ageing in the alloy WE 91, a variant of the Ni-Fe-Cr superalloy Inconel 718 (IN718). Transmission electron microscopy and atom probe tomography were used to study the size and volume fraction of γ' and γ'' precipitates and the extent of pre-precipitate clustering of Al/Ti and Nb. Co-located γ' and γ'' precipitates were observed from the shortest ageing times that precipitates could be visualised using atom probe. At shorter times, prior to the observation of precipitates, clustering of Al/Ti and Nb was shown to occur. The respective volume fraction of the γ' and γ'' precipitates and the clustering of Al/Ti and Nb suggest that γ'' nucleates prior to γ' during ageing at 706 deg. C for this alloy.

Cluster II quartet take the stage together

Science.gov (United States)

1999-11-01

This is the only occasion on which all four of ESA's Cluster II spacecraft will be on display together in Europe. Four Spacecraft, One Mission The unique event takes place near the end of the lengthy assembly and test programme, during which each individual spacecraft is being assembled in sequence, one after the other. Two have already completed their assembly and systems testing and are about to be stored in special containers at IABG prior to shipment to the Baikonur launch site in Kazakhstan next spring. In the case of the other two, flight models 5 and 8, installation of the science payloads has finished, but their exhaustive series of environmental tests at IABG have yet to begin. Following delivery to the launch site next April, the satellites will be launched in pairs in June and July 2000. Two Soyuz rockets, each with a newly designed Fregat upper stage, are being provided by the Russian-French Starsem company. This will be the first time ESA satellites have been launched from the former Soviet Union. Cluster II is a replacement for the original Cluster mission, which was lost during the maiden launch of Ariane 5 in June 1996. ESA, given the mission's importance in its overall strategy in the area of the Sun-Earth connection, decided to rebuild this unique project. ESA member states supported that proposal. On 3 April 1997, the Agency's Science Programme Committee agreed. Cluster II was born. European Teamwork Scientific institutions and industrial enterprises in almost all the 14 ESA member states and the United States are taking part in the Cluster II project. Construction of the eight Cluster / Cluster II spacecraft has been a major undertaking for European industry. Built into each 1200 kg satellite are six propellant tanks, two pressure tanks, eight thrusters, 80 metres of pipework, about 5 km of wiring, 380 connectors and more than 14 000 electrical contacts. All the spacecraft were assembled in the giant clean room at the Friedrichshafen plant of

Universal Prevention for Anxiety and Depressive Symptoms in Children: A Meta-analysis of Randomized and Cluster-Randomized Trials.

Science.gov (United States)

Ahlen, Johan; Lenhard, Fabian; Ghaderi, Ata

2015-12-01

Although under-diagnosed, anxiety and depression are among the most prevalent psychiatric disorders in children and adolescents, leading to severe impairment, increased risk of future psychiatric problems, and a high economic burden to society. Universal prevention may be a potent way to address these widespread problems. There are several benefits to universal relative to targeted interventions because there is limited knowledge as to how to screen for anxiety and depression in the general population. Earlier meta-analyses of the prevention of depression and anxiety symptoms among children suffer from methodological inadequacies such as combining universal, selective, and indicated interventions in the same analyses, and comparing cluster-randomized trials with randomized trials without any correction for clustering effects. The present meta-analysis attempted to determine the effectiveness of universal interventions to prevent anxiety and depressive symptoms after correcting for clustering effects. A systematic search of randomized studies in PsychINFO, Cochrane Library, and Google Scholar resulted in 30 eligible studies meeting inclusion criteria, namely peer-reviewed, randomized or cluster-randomized trials of universal interventions for anxiety and depressive symptoms in school-aged children. Sixty-three percent of the studies reported outcome data regarding anxiety and 87 % reported outcome data regarding depression. Seventy percent of the studies used randomization at the cluster level. There were small but significant effects regarding anxiety (.13) and depressive (.11) symptoms as measured at immediate posttest. At follow-up, which ranged from 3 to 48 months, effects were significantly larger than zero regarding depressive (.07) but not anxiety (.11) symptoms. There was no significant moderation effect of the following pre-selected variables: the primary aim of the intervention (anxiety or depression), deliverer of the intervention, gender distribution

Two-stage nonrecursive filter/decimator

International Nuclear Information System (INIS)

Yoder, J.R.; Richard, B.D.

1980-08-01

A two-stage digital filter/decimator has been designed and implemented to reduce the sampling rate associated with the long-term computer storage of certain digital waveforms. This report describes the design selection and implementation process and serves as documentation for the system actually installed. A filter design with finite-impulse response (nonrecursive) was chosen for implementation via direct convolution. A newly-developed system-test statistic validates the system under different computer-operating environments

Acceptance sampling using judgmental and randomly selected samples

Energy Technology Data Exchange (ETDEWEB)

Sego, Landon H.; Shulman, Stanley A.; Anderson, Kevin K.; Wilson, John E.; Pulsipher, Brent A.; Sieber, W. Karl

2010-09-01

We present a Bayesian model for acceptance sampling where the population consists of two groups, each with different levels of risk of containing unacceptable items. Expert opinion, or judgment, may be required to distinguish between the high and low-risk groups. Hence, high-risk items are likely to be identifed (and sampled) using expert judgment, while the remaining low-risk items are sampled randomly. We focus on the situation where all observed samples must be acceptable. Consequently, the objective of the statistical inference is to quantify the probability that a large percentage of the unsampled items in the population are also acceptable. We demonstrate that traditional (frequentist) acceptance sampling and simpler Bayesian formulations of the problem are essentially special cases of the proposed model. We explore the properties of the model in detail, and discuss the conditions necessary to ensure that required samples sizes are non-decreasing function of the population size. The method is applicable to a variety of acceptance sampling problems, and, in particular, to environmental sampling where the objective is to demonstrate the safety of reoccupying a remediated facility that has been contaminated with a lethal agent.

Energy Balance 4 Kids with Play: Results from a Two-Year Cluster-Randomized Trial.

Science.gov (United States)

Madsen, Kristine; Linchey, Jennifer; Gerstein, Dana; Ross, Michelle; Myers, Esther; Brown, Katie; Crawford, Patricia

2015-08-01

Identifying sustainable approaches to improving the physical activity (PA) and nutrition environments in schools is an important public health goal. This study examined the impact of Energy Balance for Kids with Play (EB4K with Play), a school-based intervention developed by the Academy of Nutrition and Dietetics Foundation and Playworks, on students' PA, dietary habits and knowledge, and weight status over 2 years. This cluster-randomized, controlled trial took place in four intervention and two control schools over 2 years (n=879; third- to fifth-grade students). PA (fourth and fifth grades only), dietary knowledge and behaviors, school policies, and BMI z-score were assessed at baseline (fall 2011), midpoint (spring 2012), and endpoint (fall 2012 for accelerometers; spring 2013 for all other outcomes). At endpoint, there were no group differences in change in PA or dietary behaviors, although BMI z-score decreased overall by -0.07 (p=0.05). Students' dietary knowledge significantly increased, as did the amount of vegetables schools served. Post-hoc analyses stratified by grade revealed that, relative to control students, fourth-grade intervention students reduced school-day sedentary time by 15 minutes (p=0.023) and third-grade intervention students reduced BMI z-score by -0.2 (0.05; pchildren's dietary knowledge and may improve weight status and decrease sedentary behaviors among younger children. Future iterations should examine programming specific for different age groups.

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.

Science.gov (United States)

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.

A cluster-randomized trial of a college health center-based alcohol and sexual violence intervention (GIFTSS): Design, rationale, and baseline sample.

Science.gov (United States)

Abebe, Kaleab Z; Jones, Kelley A; Rofey, Dana; McCauley, Heather L; Clark, Duncan B; Dick, Rebecca; Gmelin, Theresa; Talis, Janine; Anderson, Jocelyn; Chugani, Carla; Algarroba, Gabriela; Antonio, Ashley; Bee, Courtney; Edwards, Clare; Lethihet, Nadia; Macak, Justin; Paley, Joshua; Torres, Irving; Van Dusen, Courtney; Miller, Elizabeth

2018-02-01

Sexual violence (SV) on college campuses is common, especially alcohol-related SV. This is a 2-arm cluster randomized controlled trial to test a brief intervention to reduce risk for alcohol-related sexual violence (SV) among students receiving care from college health centers (CHCs). Intervention CHC staff are trained to deliver universal SV education to all students seeking care, to facilitate patient and provider comfort in discussing SV and related abusive experiences (including the role of alcohol). Control sites provide participants with information about drinking responsibly. Across 28 participating campuses (12 randomized to intervention and 16 to control), 2292 students seeking care at CHCs complete surveys prior to their appointment (baseline), immediately after (exit), 4months later (T2) and one year later (T3). The primary outcome is change in recognition of SV and sexual risk. Among those reporting SV exposure at baseline, changes in SV victimization, disclosure, and use of SV services are additional outcomes. Intervention effects will be assessed using generalized linear mixed models that account for clustering of repeated observations both within CHCs and within students. Slightly more than half of the participating colleges have undergraduate enrollment of ≥3000 students; two-thirds are public and almost half are urban. Among participants there were relatively more Asian (10 v 1%) and Black/African American (13 v 7%) and fewer White (58 v 74%) participants in the intervention compared to control. This study will offer the first formal assessment for SV prevention in the CHC setting. Clinical Trials #: NCT02355470. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Two generalizations of Kohonen clustering

Science.gov (United States)

Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

1993-01-01

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

Inadequacy of ethical conduct and reporting of stepped wedge cluster randomized trials: Results from a systematic review.

Science.gov (United States)

Taljaard, Monica; Hemming, Karla; Shah, Lena; Giraudeau, Bruno; Grimshaw, Jeremy M; Weijer, Charles

2017-08-01

Background/aims The use of the stepped wedge cluster randomized design is rapidly increasing. This design is commonly used to evaluate health policy and service delivery interventions. Stepped wedge cluster randomized trials have unique characteristics that complicate their ethical interpretation. The 2012 Ottawa Statement provides comprehensive guidance on the ethical design and conduct of cluster randomized trials, and the 2010 CONSORT extension for cluster randomized trials provides guidelines for reporting. Our aims were to assess the adequacy of the ethical conduct and reporting of stepped wedge trials to date, focusing on research ethics review and informed consent. Methods We conducted a systematic review of stepped wedge cluster randomized trials in health research published up to 2014 in English language journals. We extracted details of study intervention and data collection procedures, as well as reporting of research ethics review and informed consent. Two reviewers independently extracted data from each trial; discrepancies were resolved through discussion. We identified the presence of any research participants at the cluster level and the individual level. We assessed ethical conduct by tabulating reporting of research ethics review and informed consent against the presence of research participants. Results Of 32 identified stepped wedge trials, only 24 (75%) reported review by a research ethics committee, and only 16 (50%) reported informed consent from any research participants-yet, all trials included research participants at some level. In the subgroup of 20 trials with research participants at cluster level, only 4 (20%) reported informed consent from such participants; in 26 trials with individual-level research participants, only 15 (58%) reported their informed consent. Interventions (regardless of whether targeting cluster- or individual-level participants) were delivered at the group level in more than two-thirds of trials; nine trials (28

A Coupled Hidden Conditional Random Field Model for Simultaneous Face Clustering and Naming in Videos

KAUST Repository

Zhang, Yifan

2016-08-18

For face naming in TV series or movies, a typical way is using subtitles/script alignment to get the time stamps of the names, and tagging them to the faces. We study the problem of face naming in videos when subtitles are not available. To this end, we divide the problem into two tasks: face clustering which groups the faces depicting a certain person into a cluster, and name assignment which associates a name to each face. Each task is formulated as a structured prediction problem and modeled by a hidden conditional random field (HCRF) model. We argue that the two tasks are correlated problems whose outputs can provide prior knowledge of the target prediction for each other. The two HCRFs are coupled in a unified graphical model called coupled HCRF where the joint dependence of the cluster labels and face name association is naturally embedded in the correlation between the two HCRFs. We provide an effective algorithm to optimize the two HCRFs iteratively and the performance of the two tasks on real-world data set can be both improved.

Sampling problems for randomly broken sticks

Energy Technology Data Exchange (ETDEWEB)

Huillet, Thierry [Laboratoire de Physique Theorique et Modelisation, CNRS-UMR 8089 et Universite de Cergy-Pontoise, 5 mail Gay-Lussac, 95031, Neuville sur Oise (France)

2003-04-11

Consider the random partitioning model of a population (represented by a stick of length 1) into n species (fragments) with identically distributed random weights (sizes). Upon ranking the fragments' weights according to ascending sizes, let S{sub m:n} be the size of the mth smallest fragment. Assume that some observer is sampling such populations as follows: drop at random k points (the sample size) onto this stick and record the corresponding numbers of visited fragments. We shall investigate the following sampling problems: (1) what is the sample size if the sampling is carried out until the first visit of the smallest fragment (size S{sub 1:n})? (2) For a given sample size, have all the fragments of the stick been visited at least once or not? This question is related to Feller's random coupon collector problem. (3) In what order are new fragments being discovered and what is the random number of samples separating the discovery of consecutive new fragments until exhaustion of the list? For this problem, the distribution of the size-biased permutation of the species' weights, as the sequence of their weights in their order of appearance is needed and studied.

The Effect of Cluster-Based Instruction on Mathematic Achievement in Inclusive Schools

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Gunarhadi, Sunardi; Anwar, Mohammad; Andayani, Tri Rejeki; Shaari, Abdull Sukor

2016-01-01

The research aimed to investigate the effect of Cluster-Based Instruction (CBI) on the academic achievement of Mathematics in inclusive schools. The sample was 68 students in two intact classes, including those with learning disabilities, selected using a cluster random technique among 17 inclusive schools in the regency of Surakarta. The two…

Assessment of heavy metals in Averrhoa bilimbi and A. carambola fruit samples at two developmental stages.

Science.gov (United States)

Soumya, S L; Nair, Bindu R

2016-05-01

Though the fruits of Averrhoa bilimbi and A. carambola are economically and medicinally important, they remain underutilized. The present study reports heavy metal quantitation in the fruit samples of A. bilimbi and A. carambola (Oxalidaceae), collected at two stages of maturity. Heavy metals are known to interfere with the functioning of vital cellular components. Although toxic, some elements are considered essential for human health, in trace quantities. Heavy metals such as Cr, Mn, Co, Cu, Zn, As, Se, Pb, and Cd were analyzed by atomic absorption spectroscopy (AAS). The samples under investigation included, A. bilimbi unripe (BU) and ripe (BR), A. carambola sour unripe (CSU) and ripe (CSR), and A. carambola sweet unripe (CTU) and ripe (CTR). Heavy metal analysis showed that relatively higher level of heavy metals was present in BR samples compared to the rest of the samples. The highest amount of As and Se were recorded in BU samples while Mn content was highest in CSU samples and Co in CSR. Least amounts of Cr, Zn, Se, Cd, and Pb were noted in CTU while, Mn, Cu, and As were least in CTR. Thus, the sweet types of A. carambola (CTU, CTR) had comparatively lower heavy metal content. There appears to be no reason for concern since different fruit samples of Averrhoa studied presently showed the presence of various heavy metals in trace quantities.

Precipitation and clustering in the early stages of ageing in Inconel 718

Energy Technology Data Exchange (ETDEWEB)

Alam, Talukder, E-mail: talukder.alam@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, University of Sydney, NSW 2006 (Australia); Chaturvedi, Mahesh [Department of Mechanical and Industrial Engineering, University of Manitoba, Winnipeg, MB R3T 5V6 (Canada); Ringer, Simon P.; Cairney, Julie M. [Australian Centre for Microscopy and Microanalysis, University of Sydney, NSW 2006 (Australia)

2010-11-15

Research highlights: {yields} IN718 could be age hardened rapidly by secondary phase formation. {yields} Co-located phases were observed in the earliest stage of detection. {yields} Clustering of Ti/Al and Nb atoms was observed prior to precipitation. - Abstract: In this report we investigate the onset and evolution of precipitation in the early stages of ageing in the alloy WE 91, a variant of the Ni-Fe-Cr superalloy Inconel 718 (IN718). Transmission electron microscopy and atom probe tomography were used to study the size and volume fraction of {gamma}' and {gamma}'' precipitates and the extent of pre-precipitate clustering of Al/Ti and Nb. Co-located {gamma}' and {gamma}'' precipitates were observed from the shortest ageing times that precipitates could be visualised using atom probe. At shorter times, prior to the observation of precipitates, clustering of Al/Ti and Nb was shown to occur. The respective volume fraction of the {gamma}' and {gamma}'' precipitates and the clustering of Al/Ti and Nb suggest that {gamma}'' nucleates prior to {gamma}' during ageing at 706 deg. C for this alloy.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

Science.gov (United States)

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge.

Directory of Open Access Journals (Sweden)

Rosa Catarino

Full Text Available Human papillomavirus (HPV self-sampling (self-HPV is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab.A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed first: self-HPV using dry swabs (s-DRY or vaginal specimen collection using a cytobrush applied to an FTA cartridge (s-FTA. After self-HPV, a physician collected a cervical sample using liquid-based medium (Dr-WET. HPV types were identified by real-time PCR. Agreement between collection methods was measured using the kappa statistic.HPV prevalence for high-risk types was 62.3% (95%CI: 53.7-70.2 detected by s-DRY, 56.2% (95%CI: 47.6-64.4 by Dr-WET, and 54.6% (95%CI: 46.1-62.9 by s-FTA. There was overall agreement of 70.8% between s-FTA and s-DRY samples (kappa = 0.34, and of 82.3% between self-HPV and Dr-WET samples (kappa = 0.56. Detection sensitivities for low-grade squamous intraepithelial lesion or worse (LSIL+ were: 64.0% (95%CI: 44.5-79.8 for s-FTA, 84.6% (95%CI: 66.5-93.9 for s-DRY, and 76.9% (95%CI: 58.0-89.0 for Dr-WET. The preferred self-collection method among patients was s-DRY (40.8% vs. 15.4%. Regarding costs, FTA card was five times more expensive than the swab (~5 US dollars (USD/per card vs. ~1 USD/per swab.Self-HPV using dry swabs is sensitive for detecting LSIL+ and less expensive than s-FTA.International Standard Randomized Controlled Trial Number (ISRCTN: 43310942.

Preoperative staging of lung cancer with PET/CT: cost-effectiveness evaluation alongside a randomized controlled trial

DEFF Research Database (Denmark)

Søgaard, Rikke; Fischer, Barbara Malene B; Mortensen, Jann

2011-01-01

PURPOSE: Positron emission tomography (PET)/CT has become a widely used technology for preoperative staging of non-small cell lung cancer (NSCLC). Two recent randomized controlled trials (RCT) have established its efficacy over conventional staging, but no studies have assessed its cost-effective......PURPOSE: Positron emission tomography (PET)/CT has become a widely used technology for preoperative staging of non-small cell lung cancer (NSCLC). Two recent randomized controlled trials (RCT) have established its efficacy over conventional staging, but no studies have assessed its cost......-effectiveness. The objective of this study was to assess the cost-effectiveness of PET/CT as an adjunct to conventional workup for preoperative staging of NSCLC. METHODS: The study was conducted alongside an RCT in which 189 patients were allocated to conventional staging (n = 91) or conventional staging + PET/CT (n = 98......) and followed for 1 year after which the numbers of futile thoracotomies in each group were monitored. A full health care sector perspective was adapted for costing resource use. The outcome parameter was defined as the number needed to treat (NNT)-here number of PET/CT scans needed-to avoid one futile...

Myeloid clusters are associated with a pro-metastatic environment and poor prognosis in smoking-related early stage non-small cell lung cancer.

Directory of Open Access Journals (Sweden)

Wang Zhang

Full Text Available This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients.Uninvolved regional lymph node sections from 67 patients with stage I-III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment.CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01. Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049 and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055. The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively.Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted.

A cluster expansion approach to exponential random graph models

International Nuclear Information System (INIS)

Yin, Mei

2012-01-01

The exponential family of random graphs are among the most widely studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice gas model with a finite Banach space norm. The system may then be treated using cluster expansion methods from statistical mechanics. In particular, we derive a convergent power series expansion for the limiting free energy in the case of small parameters. Since the free energy is the generating function for the expectations of other random variables, this characterizes the structure and behavior of the limiting network in this parameter region

Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

Science.gov (United States)

Wang, Wei; Griswold, Michael E

2016-11-30

The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Edge Principal Components and Squash Clustering: Using the Special Structure of Phylogenetic Placement Data for Sample Comparison

Science.gov (United States)

Matsen IV, Frederick A.; Evans, Steven N.

2013-01-01

Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate “average” of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome. PMID:23505415

Mismatch of Posttraumatic Stress Disorder (PTSD) Symptoms and DSM-IV Symptom Clusters in a Cancer Sample: Exploratory Factor Analysis of the PTSD Checklist-Civilian Version

Science.gov (United States)

Shelby, Rebecca A.; Golden-Kreutz, Deanna M.; Andersen, Barbara L.

2007-01-01

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994a) conceptualization of posttraumatic stress disorder (PTSD) includes three symptom clusters: reexperiencing, avoidance/numbing, and arousal. The PTSD Checklist-Civilian Version (PCL-C) corresponds to the DSM-IV PTSD symptoms. In the current study, we conducted exploratory factor analysis (EFA) of the PCL-C with two aims: (a) to examine whether the PCL-C evidenced the three-factor solution implied by the DSM-IV symptom clusters, and (b) to identify a factor solution for the PCL-C in a cancer sample. Women (N = 148) with Stage II or III breast cancer completed the PCL-C after completion of cancer treatment. We extracted two-, three-, four-, and five-factor solutions using EFA. Our data did not support the DSM-IV PTSD symptom clusters. Instead, EFA identified a four-factor solution including reexperiencing, avoidance, numbing, and arousal factors. Four symptom items, which may be confounded with illness and cancer treatment-related symptoms, exhibited poor factor loadings. Using these symptom items in cancer samples may lead to overdiagnosis of PTSD and inflated rates of PTSD symptoms. PMID:16281232

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

Science.gov (United States)

Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

2015-10-01

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

Science.gov (United States)

Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

2016-01-01

Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

Chronic infections in hip arthroplasties: comparing risk of reinfection following one-stage and two-stage revision: a systematic review and meta-analysis

Directory of Open Access Journals (Sweden)

Lange J

2012-03-01

Full Text Available Jeppe Lange1,2, Anders Troelsen3, Reimar W Thomsen4, Kjeld Søballe1,51Lundbeck Foundation Centre for Fast-Track Hip and Knee Surgery, Aarhus C, 2Center for Planned Surgery, Silkeborg Regional Hospital, Silkeborg, 3Department of Orthopaedics, Hvidovre Hospital, Hvidovre, 4Department of Clinical Epidemiology, Aarhus University Hospital, Aalborg, 5Department of Orthopaedics, Aarhus University Hospital, Aarhus C, DenmarkBackground: Two-stage revision is regarded by many as the best treatment of chronic infection in hip arthroplasties. Some international reports, however, have advocated one-stage revision. No systematic review or meta-analysis has ever compared the risk of reinfection following one-stage and two-stage revisions for chronic infection in hip arthroplasties.Methods: The review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Relevant studies were identified using PubMed and Embase. We assessed studies that included patients with a chronic infection of a hip arthroplasty treated with either one-stage or two-stage revision and with available data on occurrence of reinfections. We performed a meta-analysis estimating absolute risk of reinfection using a random-effects model.Results: We identified 36 studies eligible for inclusion. None were randomized controlled trials or comparative studies. The patients in these studies had received either one-stage revision (n = 375 or two-stage revision (n = 929. Reinfection occurred with an estimated absolute risk of 13.1% (95% confidence interval: 10.0%–17.1% in the one-stage cohort and 10.4% (95% confidence interval: 8.5%–12.7% in the two-stage cohort. The methodological quality of most included studies was considered low, with insufficient data to evaluate confounding factors.Conclusions: Our results may indicate three additional reinfections per 100 reimplanted patients when performing a one-stage versus two-stage revision. However, the

Occurrence of Radio Minihalos in a Mass-limited Sample of Galaxy Clusters

Energy Technology Data Exchange (ETDEWEB)

Giacintucci, Simona; Clarke, Tracy E. [Naval Research Laboratory, 4555 Overlook Avenue SW, Code 7213, Washington, DC 20375 (United States); Markevitch, Maxim [NASA/Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Cassano, Rossella; Venturi, Tiziana; Brunetti, Gianfranco, E-mail: simona.giacintucci@nrl.navy.mil [INAF—Istituto di Radioastronomia, via Gobetti 101, I-40129 Bologna (Italy)

2017-06-01

We investigate the occurrence of radio minihalos—diffuse radio sources of unknown origin observed in the cores of some galaxy clusters—in a statistical sample of 58 clusters drawn from the Planck Sunyaev–Zel’dovich cluster catalog using a mass cut ( M {sub 500} > 6 × 10{sup 14} M {sub ⊙}). We supplement our statistical sample with a similarly sized nonstatistical sample mostly consisting of clusters in the ACCEPT X-ray catalog with suitable X-ray and radio data, which includes lower-mass clusters. Where necessary (for nine clusters), we reanalyzed the Very Large Array archival radio data to determine whether a minihalo is present. Our total sample includes all 28 currently known and recently discovered radio minihalos, including six candidates. We classify clusters as cool-core or non-cool-core according to the value of the specific entropy floor in the cluster center, rederived or newly derived from the Chandra X-ray density and temperature profiles where necessary (for 27 clusters). Contrary to the common wisdom that minihalos are rare, we find that almost all cool cores—at least 12 out of 15 (80%)—in our complete sample of massive clusters exhibit minihalos. The supplementary sample shows that the occurrence of minihalos may be lower in lower-mass cool-core clusters. No minihalos are found in non-cool cores or “warm cores.” These findings will help test theories of the origin of minihalos and provide information on the physical processes and energetics of the cluster cores.

Design, rationale, and baseline demographics of SEARCH I: a prospective cluster-randomized study

Directory of Open Access Journals (Sweden)

Albers F

2012-07-01

Full Text Available Frank Albers,1 Asif Shaikh,2 Ahmar Iqbal,31Medical Affairs Respiratory, 2Clinical Development and Medical Affairs, Field Based Medicine-Respiratory, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA; 3Respiratory Medical Affairs, Pfizer Inc, New York, NY, USAAbstract: Questionnaires are available to identify patients at risk for several chronic diseases, including COPD, but are infrequently utilized in primary care. COPD is often underdiagnosed, while at the same time the US Preventive Services Task Force recommends against spirometric screening for COPD in asymptomatic adults. Use of a symptom-based questionnaire and subsequent handheld spirometric device depending on the answers to the questionnaire is a promising approach to identify patients at risk for COPD. Screening, Evaluating and Assessing Rate CHanges of diagnosing respiratory conditions in primary care 1 (SEARCH I was a prospective cluster-randomized study in 168 US primary care practices evaluating the effect of the COPD-Population Screener (COPD-PS™ questionnaire. The effect of this questionnaire alone or sequentially with the handheld copd-6TM device was evaluated on new diagnoses of COPD and on respiratory diagnostic practice patterns (including referrals for pulmonary function testing, referrals to pulmonologists, new diagnoses of COPD, and new respiratory medication prescriptions. Participating practices entered a total of 9704 consecutive consenting subjects aged ≥ 40 years attending primary care clinics. Study arm results were compared for new COPD diagnosis rates between usual care and (1 COPD-PS plus copd-6 and (2 COPD-PS alone. A cluster-randomization design allowed comparison of the intervention effects at the practice level instead of individuals being the subjects of the intervention. Regional principal investigators controlled the flow of study information to sub-investigators at participating practices to reduce observation bias (Hawthorne effect. The

SIMS analysis using a new novel sample stage

International Nuclear Information System (INIS)

Miwa, Shiro; Nomachi, Ichiro; Kitajima, Hideo

2006-01-01

We have developed a novel sample stage for Cameca IMS-series instruments that allows us to adjust the tilt of the sample holder and to vary the height of the sample surface from outside the vacuum chamber. A third function of the stage is the capability to cool sample to -150 deg. C using liquid nitrogen. Using this stage, we can measure line profiles of 10 mm in length without any variation in the secondary ion yields. By moving the sample surface toward the input lens, the primary ion beam is well focused when the energy of the primary ions is reduced. Sample cooling is useful for samples such as organic materials that are easily damaged by primary ions or electrons

SIMS analysis using a new novel sample stage

Energy Technology Data Exchange (ETDEWEB)

Miwa, Shiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan)]. E-mail: Shiro.Miwa@jp.sony.com; Nomachi, Ichiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan); Kitajima, Hideo [Nanotechnos Corp., 5-4-30 Nishihashimoto, Sagamihara 229-1131 (Japan)

2006-07-30

We have developed a novel sample stage for Cameca IMS-series instruments that allows us to adjust the tilt of the sample holder and to vary the height of the sample surface from outside the vacuum chamber. A third function of the stage is the capability to cool sample to -150 deg. C using liquid nitrogen. Using this stage, we can measure line profiles of 10 mm in length without any variation in the secondary ion yields. By moving the sample surface toward the input lens, the primary ion beam is well focused when the energy of the primary ions is reduced. Sample cooling is useful for samples such as organic materials that are easily damaged by primary ions or electrons.

Cluster-cluster correlations in the two-dimensional stationary Ising-model

International Nuclear Information System (INIS)

Klassmann, A.

1997-01-01

In numerical integration of the Cahn-Hillard equation, which describes Oswald rising in a two-phase matrix, N. Masbaum showed that spatial correlations between clusters scale with respect to the mean cluster size (itself a function of time). T. B. Liverpool showed by Monte Carlo simulations for the Ising model that the analogous correlations have a similar form. Both demonstrated that immediately around each cluster there is some depletion area followed by something like a ring of clusters of the same size as the original one. More precisely, it has been shown that the distribution of clusters around a given cluster looks like a sinus-curve decaying exponentially with respect to the distance to a constant value

One-stage versus two-stage exchange arthroplasty for infected total knee arthroplasty: a systematic review.

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Nagra, Navraj S; Hamilton, Thomas W; Ganatra, Sameer; Murray, David W; Pandit, Hemant

2016-10-01

Infection complicating total knee arthroplasty (TKA) has serious implications. Traditionally the debate on whether one- or two-stage exchange arthroplasty is the optimum management of infected TKA has favoured two-stage procedures; however, a paradigm shift in opinion is emerging. This study aimed to establish whether current evidence supports one-stage revision for managing infected TKA based on reinfection rates and functional outcomes post-surgery. MEDLINE/PubMed and CENTRAL databases were reviewed for studies that compared one- and two-stage exchange arthroplasty TKA in more than ten patients with a minimum 2-year follow-up. From an initial sample of 796, five cohort studies with a total of 231 patients (46 single-stage/185 two-stage; median patient age 66 years, range 61-71 years) met inclusion criteria. Overall, there were no significant differences in risk of reinfection following one- or two-stage exchange arthroplasty (OR -0.06, 95 % confidence interval -0.13, 0.01). Subgroup analysis revealed that in studies published since 2000, one-stage procedures have a significantly lower reinfection rate. One study investigated functional outcomes and reported that one-stage surgery was associated with superior functional outcomes. Scarcity of data, inconsistent study designs, surgical technique and antibiotic regime disparities limit recommendations that can be made. Recent studies suggest one-stage exchange arthroplasty may provide superior outcomes, including lower reinfection rates and superior function, in select patients. Clinically, for some patients, one-stage exchange arthroplasty may represent optimum treatment; however, patient selection criteria and key components of surgical and post-operative anti-microbial management remain to be defined. III.

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

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Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2018-03-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2}). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3}) and the level sets of the Gaussian free field ({d≥ 3}). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.

Toward cost-efficient sampling methods

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Luo, Peng; Li, Yongli; Wu, Chong; Zhang, Guijie

2015-09-01

The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper proposes two new sampling methods based on the idea that a small part of vertices with high node degree could possess the most structure information of a complex network. The two proposed sampling methods are efficient in sampling high degree nodes so that they would be useful even if the sampling rate is low, which means cost-efficient. The first new sampling method is developed on the basis of the widely used stratified random sampling (SRS) method and the second one improves the famous snowball sampling (SBS) method. In order to demonstrate the validity and accuracy of two new sampling methods, we compare them with the existing sampling methods in three commonly used simulation networks that are scale-free network, random network, small-world network, and also in two real networks. The experimental results illustrate that the two proposed sampling methods perform much better than the existing sampling methods in terms of achieving the true network structure characteristics reflected by clustering coefficient, Bonacich centrality and average path length, especially when the sampling rate is low.

Estimating HIES Data through Ratio and Regression Methods for Different Sampling Designs

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Faqir Muhammad

2007-01-01

Full Text Available In this study, comparison has been made for different sampling designs, using the HIES data of North West Frontier Province (NWFP for 2001-02 and 1998-99 collected from the Federal Bureau of Statistics, Statistical Division, Government of Pakistan, Islamabad. The performance of the estimators has also been considered using bootstrap and Jacknife. A two-stage stratified random sample design is adopted by HIES. In the first stage, enumeration blocks and villages are treated as the first stage Primary Sampling Units (PSU. The sample PSU’s are selected with probability proportional to size. Secondary Sampling Units (SSU i.e., households are selected by systematic sampling with a random start. They have used a single study variable. We have compared the HIES technique with some other designs, which are: Stratified Simple Random Sampling. Stratified Systematic Sampling. Stratified Ranked Set Sampling. Stratified Two Phase Sampling. Ratio and Regression methods were applied with two study variables, which are: Income (y and Household sizes (x. Jacknife and Bootstrap are used for variance replication. Simple Random Sampling with sample size (462 to 561 gave moderate variances both by Jacknife and Bootstrap. By applying Systematic Sampling, we received moderate variance with sample size (467. In Jacknife with Systematic Sampling, we obtained variance of regression estimator greater than that of ratio estimator for a sample size (467 to 631. At a sample size (952 variance of ratio estimator gets greater than that of regression estimator. The most efficient design comes out to be Ranked set sampling compared with other designs. The Ranked set sampling with jackknife and bootstrap, gives minimum variance even with the smallest sample size (467. Two Phase sampling gave poor performance. Multi-stage sampling applied by HIES gave large variances especially if used with a single study variable.

A COMPARISON OF TWO FUZZY CLUSTERING TECHNIQUES

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Samarjit Das

2013-10-01

Full Text Available - In fuzzy clustering, unlike hard clustering, depending on the membership value, a single object may belong exactly to one cluster or partially to more than one cluster. Out of a number of fuzzy clustering techniques Bezdek’s Fuzzy C-Means and GustafsonKessel clustering techniques are well known where Euclidian distance and Mahalanobis distance are used respectively as a measure of similarity. We have applied these two fuzzy clustering techniques on a dataset of individual differences consisting of fifty feature vectors of dimension (feature three. Based on some validity measures we have tried to see the performances of these two clustering techniques from three different aspects- first, by initializing the membership values of the feature vectors considering the values of the three features separately one at a time, secondly, by changing the number of the predefined clusters and thirdly, by changing the size of the dataset.

One-stage and two-stage penile buccal mucosa urethroplasty

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G. Barbagli

2016-03-01

Full Text Available The paper provides the reader with the detailed description of current techniques of one-stage and two-stage penile buccal mucosa urethroplasty. The paper provides the reader with the preoperative patient evaluation paying attention to the use of diagnostic tools. The one-stage penile urethroplasty using buccal mucosa graft with the application of glue is preliminary showed and discussed. Two-stage penile urethroplasty is then reported. A detailed description of first-stage urethroplasty according Johanson technique is reported. A second-stage urethroplasty using buccal mucosa graft and glue is presented. Finally postoperative course and follow-up are addressed.

Teaching basic life support with an automated external defibrillator using the two-stage or the four-stage teaching technique.

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Bjørnshave, Katrine; Krogh, Lise Q; Hansen, Svend B; Nebsbjerg, Mette A; Thim, Troels; Løfgren, Bo

2018-02-01

Laypersons often hesitate to perform basic life support (BLS) and use an automated external defibrillator (AED) because of self-perceived lack of knowledge and skills. Training may reduce the barrier to intervene. Reduced training time and costs may allow training of more laypersons. The aim of this study was to compare BLS/AED skills' acquisition and self-evaluated BLS/AED skills after instructor-led training with a two-stage versus a four-stage teaching technique. Laypersons were randomized to either two-stage or four-stage teaching technique courses. Immediately after training, the participants were tested in a simulated cardiac arrest scenario to assess their BLS/AED skills. Skills were assessed using the European Resuscitation Council BLS/AED assessment form. The primary endpoint was passing the test (17 of 17 skills adequately performed). A prespecified noninferiority margin of 20% was used. The two-stage teaching technique (n=72, pass rate 57%) was noninferior to the four-stage technique (n=70, pass rate 59%), with a difference in pass rates of -2%; 95% confidence interval: -18 to 15%. Neither were there significant differences between the two-stage and four-stage groups in the chest compression rate (114±12 vs. 115±14/min), chest compression depth (47±9 vs. 48±9 mm) and number of sufficient rescue breaths between compression cycles (1.7±0.5 vs. 1.6±0.7). In both groups, all participants believed that their training had improved their skills. Teaching laypersons BLS/AED using the two-stage teaching technique was noninferior to the four-stage teaching technique, although the pass rate was -2% (95% confidence interval: -18 to 15%) lower with the two-stage teaching technique.

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use: a randomized clustered trial

NARCIS (Netherlands)

Malmberg, M.; Kleinjan, M.; Overbeek, G.; Vermulst, A.; Monshouwer, K.; Lammers, J.; Vollebergh, W.A.M.; Engels, R.C.M.E.

2014-01-01

Aim: To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design: Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting: General population of 11-15-year-old

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use : A randomized clustered trial

NARCIS (Netherlands)

Malmberg, Monique; Kleinjan, Marloes; Overbeek, Geertjan; Vermulst, Ad; Monshouwer, Karin; Lammers, Jeroen; Vollebergh, Wilma A M; Engels, Rutger C M E

2014-01-01

Aim: To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design: Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting: General population of 11-15-year-old

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use: a randomized clustered trial

NARCIS (Netherlands)

Malmberg, M.; Kleinjan, M.; Overbeek, G.J.; Vermulst, A.A.; Monshouwer, K.; Lammers, J.; Vollebergh, W.A.M.; Engels, R.C.M.E.

2014-01-01

Aim To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting General population of 11-15-year-old adolescents

Independent random sampling methods

CERN Document Server

Martino, Luca; Míguez, Joaquín

2018-01-01

This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the li...

Cluster-sample surveys and lot quality assurance sampling to evaluate yellow fever immunisation coverage following a national campaign, Bolivia, 2007.

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Pezzoli, Lorenzo; Pineda, Silvia; Halkyer, Percy; Crespo, Gladys; Andrews, Nick; Ronveaux, Olivier

2009-03-01

To estimate the yellow fever (YF) vaccine coverage for the endemic and non-endemic areas of Bolivia and to determine whether selected districts had acceptable levels of coverage (>70%). We conducted two surveys of 600 individuals (25 x 12 clusters) to estimate coverage in the endemic and non-endemic areas. We assessed 11 districts using lot quality assurance sampling (LQAS). The lot (district) sample was 35 individuals with six as decision value (alpha error 6% if true coverage 70%; beta error 6% if true coverage 90%). To increase feasibility, we divided the lots into five clusters of seven individuals; to investigate the effect of clustering, we calculated alpha and beta by conducting simulations where each cluster's true coverage was sampled from a normal distribution with a mean of 70% or 90% and standard deviations of 5% or 10%. Estimated coverage was 84.3% (95% CI: 78.9-89.7) in endemic areas, 86.8% (82.5-91.0) in non-endemic and 86.0% (82.8-89.1) nationally. LQAS showed that four lots had unacceptable coverage levels. In six lots, results were inconsistent with the estimated administrative coverage. The simulations suggested that the effect of clustering the lots is unlikely to have significantly increased the risk of making incorrect accept/reject decisions. Estimated YF coverage was high. Discrepancies between administrative coverage and LQAS results may be due to incorrect population data. Even allowing for clustering in LQAS, the statistical errors would remain low. Catch-up campaigns are recommended in districts with unacceptable coverage.

On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model

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Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin

2018-01-01

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.

A two-stage flow-based intrusion detection model for next-generation networks.

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Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014

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He Yulei

2016-03-01

Full Text Available Multiple imputation is a popular approach to handling missing data. Although it was originally motivated by survey nonresponse problems, it has been readily applied to other data settings. However, its general behavior still remains unclear when applied to survey data with complex sample designs, including clustering. Recently, Lewis et al. (2014 compared single- and multiple-imputation analyses for certain incomplete variables in the 2008 National Ambulatory Medicare Care Survey, which has a nationally representative, multistage, and clustered sampling design. Their study results suggested that the increase of the variance estimate due to multiple imputation compared with single imputation largely disappears for estimates with large design effects. We complement their empirical research by providing some theoretical reasoning. We consider data sampled from an equally weighted, single-stage cluster design and characterize the process using a balanced, one-way normal random-effects model. Assuming that the missingness is completely at random, we derive analytic expressions for the within- and between-multiple-imputation variance estimators for the mean estimator, and thus conveniently reveal the impact of design effects on these variance estimators. We propose approximations for the fraction of missing information in clustered samples, extending previous results for simple random samples. We discuss some generalizations of this research and its practical implications for data release by statistical agencies.

Experimental studies of two-stage centrifugal dust concentrator

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Vechkanova, M. V.; Fadin, Yu M.; Ovsyannikov, Yu G.

2018-03-01

The article presents data of experimental results of two-stage centrifugal dust concentrator, describes its design, and shows the development of a method of engineering calculation and laboratory investigations. For the experiments, the authors used quartz, ceramic dust and slag. Experimental dispersion analysis of dust particles was obtained by sedimentation method. To build a mathematical model of the process, dust collection was built using central composite rotatable design of the four factorial experiment. A sequence of experiments was conducted in accordance with the table of random numbers. Conclusion were made.

The Influence of Social Network Characteristics on Peer Clustering in Smoking: A Two-Wave Panel Study of 19- and 23-Year-Old Swedes.

Science.gov (United States)

Miething, Alexander; Rostila, Mikael; Edling, Christofer; Rydgren, Jens

2016-01-01

The present study examines how the composition of social networks and perceived relationship content influence peer clustering in smoking, and how the association changes during the transition from late adolescence to early adulthood. The analysis was based on a Swedish two-wave survey sample comprising ego-centric network data. Respondents were 19 years old in the initial wave, and 23 when the follow-up sample was conducted. 17,227 ego-alter dyads were included in the analyses, which corresponds to an average response rate of 48.7 percent. Random effects logistic regression models were performed to calculate gender-specific average marginal effects of social network characteristics on smoking. The association of egos' and alters' smoking behavior was confirmed and found to be stronger when correlated in the female sample. For females, the associations decreased between age 19 and 23. Interactions between network characteristics and peer clustering in smoking showed that intense social interactions with smokers increase egos' smoking probability. The influence of network structures on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. The study confirmed peer clustering in smoking and revealed that females' smoking behavior in particular is determined by social interactions. Female smokers' propensity to interact with other smokers was found to be associated with the quality of peer relationships, frequent social interactions, and network density. The influence of social networks on peer clustering in smoking decreased during the transition from late adolescence to early adulthood.

Space density and clustering properties of a new sample of emission-line galaxies

International Nuclear Information System (INIS)

Wasilewski, A.J.

1982-01-01

A moderate-dispersion objective-prism survey for low-redshift emission-line galaxies has been carried out in an 825 sq. deg. region of sky with the Burrell Schmidt telescope of Case Western Reserve University. A 4 0 prism (300 A/mm at H#betta#) was used with the Illa-J emulsion to show that a new sample of emission-line galaxies is available even in areas already searched with the excess uv-continuum technique. The new emission-line galaxies occur quite commonly in systems with peculiar morphology indicating gravitational interaction with a close companion or other disturbance. About 10 to 15% of the sample are Seyfert galaxies. It is suggested that tidal interaction involving matter infall play a significant role in the generation of an emission-line spectrum. The space density of the new galaxies is found to be similar to the space density of the Makarian galaxies. Like the Markarian sample, the galaxies in the present survey represent about 10% of all galaxies in the absolute magnitude range M/sub p/ = -16 to -22. The observations also indicate that current estimates of dwarf galaxy space densities may be too low. The clustering properties of the new galaxies have been investigated using two approaches: cluster contour maps and the spatial correlation function. These tests suggest that there is weak clustering and possibly superclustering within the sample itself and that the galaxies considered here are about as common in clusters of ordinary galaxies as in the field

The global kernel k-means algorithm for clustering in feature space.

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Tzortzis, Grigorios F; Likas, Aristidis C

2009-07-01

Kernel k-means is an extension of the standard k -means clustering algorithm that identifies nonlinearly separable clusters. In order to overcome the cluster initialization problem associated with this method, we propose the global kernel k-means algorithm, a deterministic and incremental approach to kernel-based clustering. Our method adds one cluster at each stage, through a global search procedure consisting of several executions of kernel k-means from suitable initializations. This algorithm does not depend on cluster initialization, identifies nonlinearly separable clusters, and, due to its incremental nature and search procedure, locates near-optimal solutions avoiding poor local minima. Furthermore, two modifications are developed to reduce the computational cost that do not significantly affect the solution quality. The proposed methods are extended to handle weighted data points, which enables their application to graph partitioning. We experiment with several data sets and the proposed approach compares favorably to kernel k -means with random restarts.

Cluster tails for critical power-law inhomogeneous random graphs

NARCIS (Netherlands)

van der Hofstad, R.; Kliem, S.; van Leeuwaarden, J.S.H.

2018-01-01

Recently, the scaling limit of cluster sizes for critical inhomogeneous random graphs of rank-1 type having finite variance but infinite third moment degrees was obtained in Bhamidi et al. (Ann Probab 40:2299–2361, 2012). It was proved that when the degrees obey a power law with exponent τ∈ (3 , 4)

Optics of two-stage photovoltaic concentrators with dielectric second stages

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Ning, Xiaohui; O'Gallagher, Joseph; Winston, Roland

1987-04-01

Two-stage photovoltaic concentrators with Fresnel lenses as primaries and dielectric totally internally reflecting nonimaging concentrators as secondaries are discussed. The general design principles of such two-stage systems are given. Their optical properties are studied and analyzed in detail using computer ray trace procedures. It is found that the two-stage concentrator offers not only a higher concentration or increased acceptance angle, but also a more uniform flux distribution on the photovoltaic cell than the point focusing Fresnel lens alone. Experimental measurements with a two-stage prototype module are presented and compared to the analytical predictions.

Optics of two-stage photovoltaic concentrators with dielectric second stages.

Science.gov (United States)

Ning, X; O'Gallagher, J; Winston, R

1987-04-01

Two-stage photovoltaic concentrators with Fresnel lenses as primaries and dielectric totally internally reflecting nonimaging concentrators as secondaries are discussed. The general design principles of such two-stage systems are given. Their optical properties are studied and analyzed in detail using computer ray trace procedures. It is found that the two-stage concentrator offers not only a higher concentration or increased acceptance angle, but also a more uniform flux distribution on the photovoltaic cell than the point focusing Fresnel lens alone. Experimental measurements with a two-stage prototype module are presented and compared to the analytical predictions.

Spatially explicit population estimates for black bears based on cluster sampling

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Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

Efficacy of a workplace osteoporosis prevention intervention: a cluster randomized trial.

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Tan, Ai May; LaMontagne, Anthony D; English, Dallas R; Howard, Peter

2016-08-24

Osteoporosis is a debilitating disease. Adequate calcium consumption and physical activity are the two major modifiable risk factors. This paper describes the major outcomes and efficacy of a workplace-based targeted behaviour change intervention to improve the dietary and physical activity behaviours of working women in sedentary occupations in Singapore. A cluster-randomized design was used, comparing the efficacy of a tailored intervention to standard care. Workplaces were the units of randomization and intervention. Sixteen workplaces were recruited from a pool of 97, and randomly assigned to intervention and control arms (eight workplaces in each). Women meeting specified inclusion criteria were then recruited to participate. Workplaces in the intervention arm received three participatory workshops and organization-wide educational activities. Workplaces in the control/standard care arm received print resources. Outcome measures were calcium intake (milligrams/day) and physical activity level (duration: minutes/week), measured at baseline, 4 weeks and 6 months post intervention. Adjusted cluster-level analyses were conducted comparing changes in intervention versus control groups, following intention-to-treat principles and CONSORT guidelines. Workplaces in the intervention group reported a significantly greater increase in calcium intake and duration of load-bearing moderate to vigorous physical activity (MVPA) compared with the standard care control group. Four weeks after intervention, the difference in adjusted mean calcium intake was 343.2 mg/day (95 % CI = 337.4 to 349.0, p workplace-based intervention substantially improved calcium intake and load-bearing moderate to vigorous physical activity 6 months after the intervention began. Australia New Zealand Clinical Trial Registry ACTRN12616000079448 . Registered 25 January 2016 (retrospectively registered).

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

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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), ...

Single-stage-to-orbit versus two-stage-two-orbit: A cost perspective

Science.gov (United States)

Hamaker, Joseph W.

1996-03-01

This paper considers the possible life-cycle costs of single-stage-to-orbit (SSTO) and two-stage-to-orbit (TSTO) reusable launch vehicles (RLV's). The analysis parametrically addresses the issue such that the preferred economic choice comes down to the relative complexity of the TSTO compared to the SSTO. The analysis defines the boundary complexity conditions at which the two configurations have equal life-cycle costs, and finally, makes a case for the economic preference of SSTO over TSTO.

The dilute random field Ising model by finite cluster approximation

International Nuclear Information System (INIS)

Benyoussef, A.; Saber, M.

1987-09-01

Using the finite cluster approximation, phase diagrams of bond and site diluted three-dimensional simple cubic Ising models with a random field have been determined. The resulting phase diagrams have the same general features for both bond and site dilution. (author). 7 refs, 4 figs

Effectiveness of a selective intervention program targeting personality risk factors for alcohol misuse among young adolescents: results of a cluster randomized controlled trial

NARCIS (Netherlands)

Lammers, J.; Goossens, F.; Conrod, P.; Engels, R.C.M.E.; Wiers, R.W.H.J.; Kleinjan, M.

2015-01-01

Aim The effectiveness of Preventure was tested on drinking behaviour of young adolescents in secondary education in the Netherlands. Design A cluster randomized controlled trial was carried out, with participants assigned randomly to a two-session coping skills intervention or a control

ATCA observations of the MACS-Planck Radio Halo Cluster Project. II. Radio observations of an intermediate redshift cluster sample

Science.gov (United States)

Martinez Aviles, G.; Johnston-Hollitt, M.; Ferrari, C.; Venturi, T.; Democles, J.; Dallacasa, D.; Cassano, R.; Brunetti, G.; Giacintucci, S.; Pratt, G. W.; Arnaud, M.; Aghanim, N.; Brown, S.; Douspis, M.; Hurier, J.; Intema, H. T.; Langer, M.; Macario, G.; Pointecouteau, E.

2018-04-01

Aim. A fraction of galaxy clusters host diffuse radio sources whose origins are investigated through multi-wavelength studies of cluster samples. We investigate the presence of diffuse radio emission in a sample of seven galaxy clusters in the largely unexplored intermediate redshift range (0.3 http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A94

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

Science.gov (United States)

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

2015-06-15

Assessing levels of pasture larval contamination is frequently used to study the population dynamics of the free-living stages of parasitic nematodes of livestock. Direct quantification of infective larvae (L3) on herbage is the most applied method to measure pasture larval contamination. However, herbage collection remains labour intensive and there is a lack of studies addressing the variation induced by the sampling method and the required sample size. The aim of this study was (1) to compare two different sampling methods in terms of pasture larval count results and time required to sample, (2) to assess the amount of variation in larval counts at the level of sample plot, pasture and season, respectively and (3) to calculate the required sample size to assess pasture larval contamination with a predefined precision using random plots across pasture. Eight young stock pastures of different commercial dairy herds were sampled in three consecutive seasons during the grazing season (spring, summer and autumn). On each pasture, herbage samples were collected through both a double-crossed W-transect with samples taken every 10 steps (method 1) and four random located plots of 0.16 m(2) with collection of all herbage within the plot (method 2). The average (± standard deviation (SD)) pasture larval contamination using sampling methods 1 and 2 was 325 (± 479) and 305 (± 444)L3/kg dry herbage (DH), respectively. Large discrepancies in pasture larval counts of the same pasture and season were often seen between methods, but no significant difference (P = 0.38) in larval counts between methods was found. Less time was required to collect samples with method 2. This difference in collection time between methods was most pronounced for pastures with a surface area larger than 1 ha. The variation in pasture larval counts from samples generated by random plot sampling was mainly due to the repeated measurements on the same pasture in the same season (residual variance

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

Science.gov (United States)

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.

Understanding the cluster randomised crossover design: a graphical illustraton of the components of variation and a sample size tutorial.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Hemming, Karla; Pilcher, David; Forbes, Andrew B

2017-08-15

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of

Dependence of the clustering properties of galaxies on stellar velocity dispersion in the Main galaxy sample of SDSS DR10

Science.gov (United States)

Deng, Xin-Fa; Song, Jun; Chen, Yi-Qing; Jiang, Peng; Ding, Ying-Ping

2014-08-01

Using two volume-limited Main galaxy samples of the Sloan Digital Sky Survey Data Release 10 (SDSS DR10), we investigate the dependence of the clustering properties of galaxies on stellar velocity dispersion by cluster analysis. It is found that in the luminous volume-limited Main galaxy sample, except at r=1.2, richer and larger systems can be more easily formed in the large stellar velocity dispersion subsample, while in the faint volume-limited Main galaxy sample, at r≥0.9, an opposite trend is observed. According to statistical analyses of the multiplicity functions, we conclude in two volume-limited Main galaxy samples: small stellar velocity dispersion galaxies preferentially form isolated galaxies, close pairs and small group, while large stellar velocity dispersion galaxies preferentially inhabit the dense groups and clusters. However, we note the difference between two volume-limited Main galaxy samples: in the faint volume-limited Main galaxy sample, at r≥0.9, the small stellar velocity dispersion subsample has a higher proportion of galaxies in superclusters ( n≥200) than the large stellar velocity dispersion subsample.

Minimal spanning trees, filaments and galaxy clustering

International Nuclear Information System (INIS)

Barrow, J.D.; Sonoda, D.H.

1985-01-01

A graph theoretical technique for assessing intrinsic patterns in point data sets is described. A unique construction, the minimal spanning tree, can be associated with any point data set given all the inter-point separations. This construction enables the skeletal pattern of galaxy clustering to be singled out in quantitative fashion and differs from other statistics applied to these data sets. This technique is described and applied to two- and three-dimensional distributions of galaxies and also to comparable random samples and numerical simulations. The observed CfA and Zwicky data exhibit characteristic distributions of edge-lengths in their minimal spanning trees which are distinct from those found in random samples. (author)

A versatile ultra high vacuum sample stage with six degrees of freedom

Energy Technology Data Exchange (ETDEWEB)

Ellis, A. W.; Tromp, R. M. [IBM T.J. Watson Research Center, 1101 Kitchawan Road, P.O. Box 218, Yorktown Heights, New York 10598 (United States)

2013-07-15

We describe the design and practical realization of a versatile sample stage with six degrees of freedom. The stage was designed for use in a Low Energy Electron Microscope, but its basic design features will be useful for numerous other applications. The degrees of freedom are X, Y, and Z, two tilts, and azimuth. All motions are actuated in an ultrahigh vacuum base pressure environment by piezoelectric transducers with integrated position sensors. The sample can be load-locked. During observation, the sample is held at a potential of −15 kV, at temperatures between room temperature and 1500 °C, and in background gas pressures up to 1 × 10{sup −4} Torr.

Implementation of client versus care-provider strategies to improve external cephalic version rates: a cluster randomized controlled trial

NARCIS (Netherlands)

Vlemmix, Floortje; Rosman, Ageeth N.; Rijnders, Marlies E.; Beuckens, Antje; Opmeer, Brent C.; Mol, Ben W. J.; Kok, Marjolein; Fleuren, Margot A. H.

2015-01-01

To determine the effectiveness of a client or care-provider strategy to improve the implementation of external cephalic version. Cluster randomized controlled trial. Twenty-five clusters; hospitals and their referring midwifery practices randomly selected in the Netherlands. Singleton breech

Implementation of client versus care-provider strategies to improve external cephalic version rates: a cluster randomized controlled trial

NARCIS (Netherlands)

Vlemmix, F.; Rosman, A.N.; Rijnders, M.E.; Beuckens, A.; Opmeer, B.C.; Mol, B.W.J.; Kok, M.; Fleuren, M.A.H.

2015-01-01

Onjective: To determine the effectiveness of a client or care-provider strategy to improve the implementation of external cephalic version. Design: Cluster randomized controlled trial.Setting: Twenty-five clusters; hospitals and their referring midwifery practices randomly selected in the

Effectiveness of a multifaceted implementation strategy on physicians? referral behavior to an evidence-based psychosocial intervention in dementia: a cluster randomized controlled trial

OpenAIRE

D?pp, Carola ME; Graff, Maud JL; Teerenstra, Steven; Nijhuis-van der Sanden, Maria WG; Olde Rikkert, Marcel GM; Vernooij-Dassen, Myrra JFJ

2013-01-01

BACKGROUND: To evaluate the effectiveness of a multifaceted implementation strategy on physicians' referral rate to and knowledge on the community occupational therapy in dementia program (COTiD program). METHODS: A cluster randomized controlled trial with 28 experimental and 17 control clusters was conducted. Cluster included a minimum of one physician, one manager, and two occupational therapists. In the control group physicians and managers received no interventions and occupational therap...

A two-stage approach for multi-objective decision making with applications to system reliability optimization

International Nuclear Information System (INIS)

Li Zhaojun; Liao Haitao; Coit, David W.

2009-01-01

This paper proposes a two-stage approach for solving multi-objective system reliability optimization problems. In this approach, a Pareto optimal solution set is initially identified at the first stage by applying a multiple objective evolutionary algorithm (MOEA). Quite often there are a large number of Pareto optimal solutions, and it is difficult, if not impossible, to effectively choose the representative solutions for the overall problem. To overcome this challenge, an integrated multiple objective selection optimization (MOSO) method is utilized at the second stage. Specifically, a self-organizing map (SOM), with the capability of preserving the topology of the data, is applied first to classify those Pareto optimal solutions into several clusters with similar properties. Then, within each cluster, the data envelopment analysis (DEA) is performed, by comparing the relative efficiency of those solutions, to determine the final representative solutions for the overall problem. Through this sequential solution identification and pruning process, the final recommended solutions to the multi-objective system reliability optimization problem can be easily determined in a more systematic and meaningful way.

Coarse Point Cloud Registration by Egi Matching of Voxel Clusters

Science.gov (United States)

Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo

2016-06-01

Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.

Comparisons of single-stage and two-stage approaches to genomic selection.

Science.gov (United States)

Schulz-Streeck, Torben; Ogutu, Joseph O; Piepho, Hans-Peter

2013-01-01

Genomic selection (GS) is a method for predicting breeding values of plants or animals using many molecular markers that is commonly implemented in two stages. In plant breeding the first stage usually involves computation of adjusted means for genotypes which are then used to predict genomic breeding values in the second stage. We compared two classical stage-wise approaches, which either ignore or approximate correlations among the means by a diagonal matrix, and a new method, to a single-stage analysis for GS using ridge regression best linear unbiased prediction (RR-BLUP). The new stage-wise method rotates (orthogonalizes) the adjusted means from the first stage before submitting them to the second stage. This makes the errors approximately independently and identically normally distributed, which is a prerequisite for many procedures that are potentially useful for GS such as machine learning methods (e.g. boosting) and regularized regression methods (e.g. lasso). This is illustrated in this paper using componentwise boosting. The componentwise boosting method minimizes squared error loss using least squares and iteratively and automatically selects markers that are most predictive of genomic breeding values. Results are compared with those of RR-BLUP using fivefold cross-validation. The new stage-wise approach with rotated means was slightly more similar to the single-stage analysis than the classical two-stage approaches based on non-rotated means for two unbalanced datasets. This suggests that rotation is a worthwhile pre-processing step in GS for the two-stage approaches for unbalanced datasets. Moreover, the predictive accuracy of stage-wise RR-BLUP was higher (5.0-6.1%) than that of componentwise boosting.

Improving Language Comprehension in Preschool Children with Language Difficulties: A Cluster Randomized Trial

Science.gov (United States)

Hagen, Åste M.; Melby-Lervåg, Monica; Lervåg, Arne

2017-01-01

Background: Children with language comprehension difficulties are at risk of educational and social problems, which in turn impede employment prospects in adulthood. However, few randomized trials have examined how such problems can be ameliorated during the preschool years. Methods: We conducted a cluster randomized trial in 148 preschool…

Possible two-stage 87Sr evolution in the Stockdale Rhyolite

International Nuclear Information System (INIS)

Compston, W.; McDougall, I.; Wyborn, D.

1982-01-01

The Rb-Sr total-rock data for the Stockdale Rhyolite, of significance for the Palaeozoic time scale, are more scattered about a single-stage isochron than expected from experimental error. Two-stage 87 Sr evolution for several of the samples is explored to explain this, as an alternative to variation in the initial 87 Sr/ 86 Sr which is customarily used in single-stage dating models. The deletion of certain samples having very high Rb/Sr removes most of the excess scatter and leads to an estimate of 430 +- 7 m.y. for the age of extrusion. There is a younger alignment of Rb-Sr data within each sampling site at 412 +- 7 m.y. We suggest that the Stockdale Rhyolite is at least 430 m.y. old, that its original range in Rb/Sr was smaller than now observed, and that it experienced a net loss in Sr during later hydrothermal alteration at ca. 412 m.y. (orig.)

Cluster lot quality assurance sampling: effect of increasing the number of clusters on classification precision and operational feasibility.

Science.gov (United States)

Okayasu, Hiromasa; Brown, Alexandra E; Nzioki, Michael M; Gasasira, Alex N; Takane, Marina; Mkanda, Pascal; Wassilak, Steven G F; Sutter, Roland W

2014-11-01

To assess the quality of supplementary immunization activities (SIAs), the Global Polio Eradication Initiative (GPEI) has used cluster lot quality assurance sampling (C-LQAS) methods since 2009. However, since the inception of C-LQAS, questions have been raised about the optimal balance between operational feasibility and precision of classification of lots to identify areas with low SIA quality that require corrective programmatic action. To determine if an increased precision in classification would result in differential programmatic decision making, we conducted a pilot evaluation in 4 local government areas (LGAs) in Nigeria with an expanded LQAS sample size of 16 clusters (instead of the standard 6 clusters) of 10 subjects each. The results showed greater heterogeneity between clusters than the assumed standard deviation of 10%, ranging from 12% to 23%. Comparing the distribution of 4-outcome classifications obtained from all possible combinations of 6-cluster subsamples to the observed classification of the 16-cluster sample, we obtained an exact match in classification in 56% to 85% of instances. We concluded that the 6-cluster C-LQAS provides acceptable classification precision for programmatic action. Considering the greater resources required to implement an expanded C-LQAS, the improvement in precision was deemed insufficient to warrant the effort. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Hot Zone Identification: Analyzing Effects of Data Sampling on Spam Clustering

Directory of Open Access Journals (Sweden)

Rasib Khan

2014-03-01

Full Text Available Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process of mining the spam data involves going through every email in the data mine and clustering them based on their different attributes. However, given the size of the data mine, it takes an exceptionally long time to execute the clustering mechanism each time. In this paper, we have illustrated sampling as an efficient tool for data reduction, while preserving the information within the clusters, which would thus allow the spam forensic experts to quickly and effectively identify the ‘hot zone’ from the spam campaigns. We have provided detailed comparative analysis of the quality of the clusters after sampling, the overall distribution of clusters on the spam data, and timing measurements for our sampling approach. Additionally, we present different strategies which allowed us to optimize the sampling process using data-preprocessing and using the database engine's computational resources, and thus improving the performance of the clustering process.

Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

Science.gov (United States)

Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

2017-01-01

Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

Identification of Clusters of Foot Pain Location in a Community Sample.

Science.gov (United States)

Gill, Tiffany K; Menz, Hylton B; Landorf, Karl B; Arnold, John B; Taylor, Anne W; Hill, Catherine L

2017-12-01

To identify foot pain clusters according to pain location in a community-based sample of the general population. This study analyzed data from the North West Adelaide Health Study. Data were obtained between 2004 and 2006, using computer-assisted telephone interviewing, clinical assessment, and self-completed questionnaire. The location of foot pain was assessed using a diagram during the clinical assessment. Hierarchical cluster analysis was undertaken to identify foot pain location clusters, which were then compared in relation to demographics, comorbidities, and podiatry services utilization. There were 558 participants with foot pain (mean age 54.4 years, 57.5% female). Five clusters were identified: 1 with predominantly arch and ball pain (26.8%), 1 with rearfoot pain (20.9%), 1 with heel pain (13.3%), and 2 with predominantly forefoot, toe, and nail pain (28.3% and 10.7%). Each cluster was distinct in age, sex, and comorbidity profile. Of the two clusters with predominantly forefoot, toe, and nail pain, one of them had a higher proportion of men and those classified as obese, had diabetes mellitus, and used podiatry services (30%), while the other was comprised of a higher proportion of women who were overweight and reported less use of podiatry services (17.5%). Five clusters of foot pain according to pain location were identified, all with distinct age, sex, and comorbidity profiles. These findings may assist in the identification of individuals at risk for developing foot pain and in the development of targeted preventive strategies and treatments. © 2017, American College of Rheumatology.

Hydration of Atmospheric Molecular Clusters: Systematic Configurational Sampling.

Science.gov (United States)

Kildgaard, Jens; Mikkelsen, Kurt V; Bilde, Merete; Elm, Jonas

2018-05-09

We present a new systematic configurational sampling algorithm for investigating the potential energy surface of hydrated atmospheric molecular clusters. The algo- rithm is based on creating a Fibonacci sphere around each atom in the cluster and adding water molecules to each point in 9 different orientations. To allow the sam- pling of water molecules to existing hydrogen bonds, the cluster is displaced along the hydrogen bond and a water molecule is placed in between in three different ori- entations. Generated redundant structures are eliminated based on minimizing the root mean square distance (RMSD) of different conformers. Initially, the clusters are sampled using the semiempirical PM6 method and subsequently using density func- tional theory (M06-2X and ωB97X-D) with the 6-31++G(d,p) basis set. Applying the developed algorithm we study the hydration of sulfuric acid with up to 15 water molecules. We find that the additions of the first four water molecules "saturate" the sulfuric acid molecule and are more thermodynamically favourable than the addition of water molecule 5-15. Using the large generated set of conformers, we assess the performance of approximate methods (ωB97X-D, M06-2X, PW91 and PW6B95-D3) in calculating the binding energies and assigning the global minimum conformation compared to high level CCSD(T)-F12a/VDZ-F12 reference calculations. The tested DFT functionals systematically overestimates the binding energies compared to cou- pled cluster calculations, and we find that this deficiency can be corrected by a simple scaling factor.

Comparative effectiveness of one-stage versus two-stage basilic vein transposition arteriovenous fistulas.

Science.gov (United States)

Ghaffarian, Amir A; Griffin, Claire L; Kraiss, Larry W; Sarfati, Mark R; Brooke, Benjamin S

2018-02-01

Basilic vein transposition (BVT) fistulas may be performed as either a one-stage or two-stage operation, although there is debate as to which technique is superior. This study was designed to evaluate the comparative clinical efficacy and cost-effectiveness of one-stage vs two-stage BVT. We identified all patients at a single large academic hospital who had undergone creation of either a one-stage or two-stage BVT between January 2007 and January 2015. Data evaluated included patient demographics, comorbidities, medication use, reasons for abandonment, and interventions performed to maintain patency. Costs were derived from the literature, and effectiveness was expressed in quality-adjusted life-years (QALYs). We analyzed primary and secondary functional patency outcomes as well as survival during follow-up between one-stage and two-stage BVT procedures using multivariate Cox proportional hazards models and Kaplan-Meier analysis with log-rank tests. The incremental cost-effectiveness ratio was used to determine cost savings. We identified 131 patients in whom 57 (44%) one-stage BVT and 74 (56%) two-stage BVT fistulas were created among 8 different vascular surgeons during the study period that each performed both procedures. There was no significant difference in the mean age, male gender, white race, diabetes, coronary disease, or medication profile among patients undergoing one- vs two-stage BVT. After fistula transposition, the median follow-up time was 8.3 months (interquartile range, 3-21 months). Primary patency rates of one-stage BVT were 56% at 12-month follow-up, whereas primary patency rates of two-stage BVT were 72% at 12-month follow-up. Patients undergoing two-stage BVT also had significantly higher rates of secondary functional patency at 12 months (57% for one-stage BVT vs 80% for two-stage BVT) and 24 months (44% for one-stage BVT vs 73% for two-stage BVT) of follow-up (P < .001 using log-rank test). However, there was no significant difference

Comparison of population-averaged and cluster-specific models for the analysis of cluster randomized trials with missing binary outcomes: a simulation study

Directory of Open Access Journals (Sweden)

Ma Jinhui

2013-01-01

Full Text Available Abstracts Background The objective of this simulation study is to compare the accuracy and efficiency of population-averaged (i.e. generalized estimating equations (GEE and cluster-specific (i.e. random-effects logistic regression (RELR models for analyzing data from cluster randomized trials (CRTs with missing binary responses. Methods In this simulation study, clustered responses were generated from a beta-binomial distribution. The number of clusters per trial arm, the number of subjects per cluster, intra-cluster correlation coefficient, and the percentage of missing data were allowed to vary. Under the assumption of covariate dependent missingness, missing outcomes were handled by complete case analysis, standard multiple imputation (MI and within-cluster MI strategies. Data were analyzed using GEE and RELR. Performance of the methods was assessed using standardized bias, empirical standard error, root mean squared error (RMSE, and coverage probability. Results GEE performs well on all four measures — provided the downward bias of the standard error (when the number of clusters per arm is small is adjusted appropriately — under the following scenarios: complete case analysis for CRTs with a small amount of missing data; standard MI for CRTs with variance inflation factor (VIF 50. RELR performs well only when a small amount of data was missing, and complete case analysis was applied. Conclusion GEE performs well as long as appropriate missing data strategies are adopted based on the design of CRTs and the percentage of missing data. In contrast, RELR does not perform well when either standard or within-cluster MI strategy is applied prior to the analysis.

A clustering algorithm for sample data based on environmental pollution characteristics

Science.gov (United States)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

Does poverty alleviation decrease depression symptoms in post-conflict settings? A cluster-randomized trial of microenterprise assistance in Northern Uganda.

Science.gov (United States)

Green, E P; Blattman, C; Jamison, J; Annan, J

2016-01-01

By 2009, two decades of war and widespread displacement left the majority of the population of Northern Uganda impoverished. This study used a cluster-randomized design to test the hypothesis that a poverty alleviation program would improve economic security and reduce symptoms of depression in a sample of mostly young women. Roughly 120 villages in Northern Uganda were invited to participate. Community committees were asked to identify the most vulnerable women (and some men) to participate. The implementing agency screened all proposed participants, and a total of 1800 were enrolled. Following a baseline survey, villages were randomized to a treatment or wait-list control group. Participants in treatment villages received training, start-up capital, and follow-up support. Participants, implementers, and data collectors were not blinded to treatment status. Villages were randomized to the treatment group (60 villages with 896 participants) or the wait-list control group (60 villages with 904 participants) with an allocation ration of 1:1. All clusters participated in the intervention and were included in the analysis. The intent-to-treat analysis included 860 treatment participants and 866 control participants (4.1% attrition). Sixteen months after the program, monthly cash earnings doubled from UGX 22 523 to 51 124, non-household and non-farm businesses doubled, and cash savings roughly quadrupled. There was no measurable effect on a locally derived measure of symptoms of depression. Despite finding large increases in business, income, and savings among the treatment group, we do not find support for an indirect effect of poverty alleviation on symptoms of depression.

Design considerations for single-stage and two-stage pneumatic pellet injectors

International Nuclear Information System (INIS)

Gouge, M.J.; Combs, S.K.; Fisher, P.W.; Milora, S.L.

1988-09-01

Performance of single-stage pneumatic pellet injectors is compared with several models for one-dimensional, compressible fluid flow. Agreement is quite good for models that reflect actual breech chamber geometry and incorporate nonideal effects such as gas friction. Several methods of improving the performance of single-stage pneumatic pellet injectors in the near term are outlined. The design and performance of two-stage pneumatic pellet injectors are discussed, and initial data from the two-stage pneumatic pellet injector test facility at Oak Ridge National Laboratory are presented. Finally, a concept for a repeating two-stage pneumatic pellet injector is described. 27 refs., 8 figs., 3 tabs

Genetic algorithm based two-mode clustering of metabolomics data

NARCIS (Netherlands)

Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

2008-01-01

Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

Assessment of Random Assignment in Training and Test Sets using Generalized Cluster Analysis Technique

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Sorana D. BOLBOACĂ

2011-06-01

Full Text Available Aim: The properness of random assignment of compounds in training and validation sets was assessed using the generalized cluster technique. Material and Method: A quantitative Structure-Activity Relationship model using Molecular Descriptors Family on Vertices was evaluated in terms of assignment of carboquinone derivatives in training and test sets during the leave-many-out analysis. Assignment of compounds was investigated using five variables: observed anticancer activity and four structure descriptors. Generalized cluster analysis with K-means algorithm was applied in order to investigate if the assignment of compounds was or not proper. The Euclidian distance and maximization of the initial distance using a cross-validation with a v-fold of 10 was applied. Results: All five variables included in analysis proved to have statistically significant contribution in identification of clusters. Three clusters were identified, each of them containing both carboquinone derivatives belonging to training as well as to test sets. The observed activity of carboquinone derivatives proved to be normal distributed on every. The presence of training and test sets in all clusters identified using generalized cluster analysis with K-means algorithm and the distribution of observed activity within clusters sustain a proper assignment of compounds in training and test set. Conclusion: Generalized cluster analysis using the K-means algorithm proved to be a valid method in assessment of random assignment of carboquinone derivatives in training and test sets.

Ca II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. I. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF CLUSTERS

International Nuclear Information System (INIS)

Parisi, M. C.; Claria, J. J.; Grocholski, A. J.; Geisler, D.; Sarajedini, A.

2009-01-01

We have obtained near-infrared spectra covering the Ca II triplet lines for a large number of stars associated with 16 Small Magellanic Cloud (SMC) clusters using the VLT + FORS2. These data compose the largest available sample of SMC clusters with spectroscopically derived abundances and velocities. Our clusters span a wide range of ages and provide good areal coverage of the galaxy. Cluster members are selected using a combination of their positions relative to the cluster center as well as their location in the color-magnitude diagram, abundances, and radial velocities (RVs). We determine mean cluster velocities to typically 2.7 km s -1 and metallicities to 0.05 dex (random errors), from an average of 6.4 members per cluster. By combining our clusters with previously published results, we compile a sample of 25 clusters on a homogeneous metallicity scale and with relatively small metallicity errors, and thereby investigate the metallicity distribution, metallicity gradient, and age-metallicity relation (AMR) of the SMC cluster system. For all 25 clusters in our expanded sample, the mean metallicity [Fe/H] = -0.96 with σ = 0.19. The metallicity distribution may possibly be bimodal, with peaks at ∼-0.9 dex and -1.15 dex. Similar to the Large Magellanic Cloud (LMC), the SMC cluster system gives no indication of a radial metallicity gradient. However, intermediate age SMC clusters are both significantly more metal-poor and have a larger metallicity spread than their LMC counterparts. Our AMR shows evidence for three phases: a very early (>11 Gyr) phase in which the metallicity reached ∼-1.2 dex, a long intermediate phase from ∼10 to 3 Gyr in which the metallicity only slightly increased, and a final phase from 3 to 1 Gyr ago in which the rate of enrichment was substantially faster. We find good overall agreement with the model of Pagel and Tautvaisiene, which assumes a burst of star formation at 4 Gyr. Finally, we find that the mean RV of the cluster system

Handling missing data in cluster randomized trials: A demonstration of multiple imputation with PAN through SAS

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Jiangxiu Zhou

2014-09-01

Full Text Available The purpose of this study is to demonstrate a way of dealing with missing data in clustered randomized trials by doing multiple imputation (MI with the PAN package in R through SAS. The procedure for doing MI with PAN through SAS is demonstrated in detail in order for researchers to be able to use this procedure with their own data. An illustration of the technique with empirical data was also included. In this illustration thePAN results were compared with pairwise deletion and three types of MI: (1 Normal Model (NM-MI ignoring the cluster structure; (2 NM-MI with dummy-coded cluster variables (fixed cluster structure; and (3 a hybrid NM-MI which imputes half the time ignoring the cluster structure, and the other half including the dummy-coded cluster variables. The empirical analysis showed that using PAN and the other strategies produced comparable parameter estimates. However, the dummy-coded MI overestimated the intraclass correlation, whereas MI ignoring the cluster structure and the hybrid MI underestimated the intraclass correlation. When compared with PAN, the p-value and standard error for the treatment effect were higher with dummy-coded MI, and lower with MI ignoring the clusterstructure, the hybrid MI approach, and pairwise deletion. Previous studies have shown that NM-MI is not appropriate for handling missing data in clustered randomized trials. This approach, in addition to the pairwise deletion approach, leads to a biased intraclass correlation and faultystatistical conclusions. Imputation in clustered randomized trials should be performed with PAN. We have demonstrated an easy way for using PAN through SAS.

Systematic adaptive cluster sampling for the assessment of rare tree species in Nepal

NARCIS (Netherlands)

Acharya, B.; Bhattarai, G.; Gier, de A.; Stein, A.

2000-01-01

Sampling to assess rare tree species poses methodic problems, because they may cluster and many plots with no such trees are to be expected. We used systematic adaptive cluster sampling (SACS) to sample three rare tree species in a forest area of about 40 ha in Nepal. We checked its applicability

Two-Stage Series-Resonant Inverter

Science.gov (United States)

Stuart, Thomas A.

1994-01-01

Two-stage inverter includes variable-frequency, voltage-regulating first stage and fixed-frequency second stage. Lightweight circuit provides regulated power and is invulnerable to output short circuits. Does not require large capacitor across ac bus, like parallel resonant designs. Particularly suitable for use in ac-power-distribution system of aircraft.

Numerical simulation of two-dimensional late-stage coarsening for nucleation and growth

International Nuclear Information System (INIS)

Akaiwa, N.; Meiron, D.I.

1995-01-01

Numerical simulations of two-dimensional late-stage coarsening for nucleation and growth or Ostwald ripening are performed at area fractions 0.05 to 0.4 using the monopole and dipole approximations of a boundary integral formulation for the steady state diffusion equation. The simulations are performed using two different initial spatial distributions. One is a random spatial distribution, and the other is a random spatial distribution with depletion zones around the particles. We characterize the spatial correlations of particles by the radial distribution function, the pair correlation functions, and the structure function. Although the initial spatial correlations are different, we find time-independent scaled correlation functions in the late stage of coarsening. An important feature of the late-stage spatial correlations is that depletion zones exist around particles. A log-log plot of the structure function shows that the slope at small wave numbers is close to 4 and is -3 at very large wave numbers for all area fractions. At large wave numbers we observe oscillations in the structure function. We also confirm the cubic growth law of the average particle radius. The rate constant of the cubic growth law and the particle size distribution functions are also determined. We find qualitatively good agreement between experiments and the present simulations. In addition, the present results agree well with simulation results using the Cahn-Hilliard equation

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

Science.gov (United States)

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

2006-01-01

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

Sample size estimation and sampling techniques for selecting a representative sample

Directory of Open Access Journals (Sweden)

Aamir Omair

2014-01-01

Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

Discriminative motif discovery via simulated evolution and random under-sampling.

Directory of Open Access Journals (Sweden)

Tao Song

Full Text Available Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

Discriminative motif discovery via simulated evolution and random under-sampling.

Science.gov (United States)

Song, Tao; Gu, Hong

2014-01-01

Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

A HIGH FIDELITY SAMPLE OF COLD FRONT CLUSTERS FROM THE CHANDRA ARCHIVE

International Nuclear Information System (INIS)

Owers, Matt S.; Nulsen, Paul E. J.; Markevitch, Maxim; Couch, Warrick J.

2009-01-01

This paper presents a sample of 'cold front' clusters selected from the Chandra archive. The clusters are selected based purely on the existence of surface brightness edges in their Chandra images which are modeled as density jumps. A combination of the derived density and temperature jumps across the fronts is used to select nine robust examples of cold front clusters: 1ES0657 - 558, Abell 1201, Abell 1758N, MS1455.0+2232, Abell 2069, Abell 2142, Abell 2163, RXJ1720.1+2638, and Abell 3667. This sample is the subject of an ongoing study aimed at relating cold fronts to cluster merger activity, and understanding how the merging environment affects the cluster constituents. Here, temperature maps are presented along with the Chandra X-ray images. A dichotomy is found in the sample in that there exists a subsample of cold front clusters which are clearly mergers based on their X-ray morphologies, and a second subsample of clusters which harbor cold fronts, but have surprisingly relaxed X-ray morphologies, and minimal evidence for merger activity at other wavelengths. For this second subsample, the existence of a cold front provides the sole evidence for merger activity at X-ray wavelengths. We discuss how cold fronts can provide additional information which may be used to constrain merger histories, and also the possibility of using cold fronts to distinguish major and minor mergers.

Two-stage anaerobic digestion of cheese whey

Energy Technology Data Exchange (ETDEWEB)

Lo, K V; Liao, P H

1986-01-01

A two-stage digestion of cheese whey was studied using two anaerobic rotating biological contact reactors. The second-stage reactor receiving partially treated effluent from the first-stage reactor could be operated at a hydraulic retention time of one day. The results indicated that two-stage digestion is a feasible alternative for treating whey. 6 references.

A Clustered Randomized Controlled Trial of the Positive Prevention PLUS Adolescent Pregnancy Prevention Program.

Science.gov (United States)

LaChausse, Robert G

2016-09-01

To determine the impact of Positive Prevention PLUS, a school-based adolescent pregnancy prevention program on delaying sexual intercourse, birth control use, and pregnancy. I randomly assigned a diverse sample of ninth grade students in 21 suburban public high schools in California into treatment (n = 2483) and control (n = 1784) groups that participated in a clustered randomized controlled trial. Between October 2013 and May 2014, participants completed baseline and 6-month follow-up surveys regarding sexual behavior and pregnancy. Participants in the treatment group were offered Positive Prevention PLUS, an 11-lesson adolescent pregnancy prevention program. The program had statistically significant impacts on delaying sexual intercourse and increasing the use of birth control. However, I detected no program effect on pregnancy rates at 6-month follow-up. The Positive Prevention PLUS program demonstrated positive impacts on adolescent sexual behavior. This suggests that programs that focus on having students practice risk reduction skills may delay sexual activity and increase birth control use.

Random Sampling of Correlated Parameters – a Consistent Solution for Unfavourable Conditions

Energy Technology Data Exchange (ETDEWEB)

Žerovnik, G., E-mail: gasper.zerovnik@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Trkov, A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Kodeli, I.A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Capote, R. [International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Smith, D.L. [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, CA 92118-3073 (United States)

2015-01-15

Two methods for random sampling according to a multivariate lognormal distribution – the correlated sampling method and the method of transformation of correlation coefficients – are briefly presented. The methods are mathematically exact and enable consistent sampling of correlated inherently positive parameters with given information on the first two distribution moments. Furthermore, a weighted sampling method to accelerate the convergence of parameters with extremely large relative uncertainties is described. However, the method is efficient only for a limited number of correlated parameters.

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

Science.gov (United States)

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

2017-02-01

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

On the robustness of two-stage estimators

KAUST Repository

Zhelonkin, Mikhail

2012-04-01

The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general two-stage M-estimator, and provide their interpretations. We illustrate our results in the case of the two-stage maximum likelihood estimator and the two-stage least squares estimator. © 2011.

A spatial scan statistic for nonisotropic two-level risk cluster.

Science.gov (United States)

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2012-01-30

Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the hand-foot-mouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster. Copyright © 2011 John Wiley & Sons, Ltd.

Cluster analysis and its application to healthcare claims data: a study of end-stage renal disease patients who initiated hemodialysis.

Science.gov (United States)

Liao, Minlei; Li, Yunfeng; Kianifard, Farid; Obi, Engels; Arcona, Stephen

2016-03-02

Cluster analysis (CA) is a frequently used applied statistical technique that helps to reveal hidden structures and "clusters" found in large data sets. However, this method has not been widely used in large healthcare claims databases where the distribution of expenditure data is commonly severely skewed. The purpose of this study was to identify cost change patterns of patients with end-stage renal disease (ESRD) who initiated hemodialysis (HD) by applying different clustering methods. A retrospective, cross-sectional, observational study was conducted using the Truven Health MarketScan® Research Databases. Patients aged ≥18 years with ≥2 ESRD diagnoses who initiated HD between 2008 and 2010 were included. The K-means CA method and hierarchical CA with various linkage methods were applied to all-cause costs within baseline (12-months pre-HD) and follow-up periods (12-months post-HD) to identify clusters. Demographic, clinical, and cost information was extracted from both periods, and then examined by cluster. A total of 18,380 patients were identified. Meaningful all-cause cost clusters were generated using K-means CA and hierarchical CA with either flexible beta or Ward's methods. Based on cluster sample sizes and change of cost patterns, the K-means CA method and 4 clusters were selected: Cluster 1: Average to High (n = 113); Cluster 2: Very High to High (n = 89); Cluster 3: Average to Average (n = 16,624); or Cluster 4: Increasing Costs, High at Both Points (n = 1554). Median cost changes in the 12-month pre-HD and post-HD periods increased from $185,070 to $884,605 for Cluster 1 (Average to High), decreased from $910,930 to $157,997 for Cluster 2 (Very High to High), were relatively stable and remained low from $15,168 to $13,026 for Cluster 3 (Average to Average), and increased from $57,909 to $193,140 for Cluster 4 (Increasing Costs, High at Both Points). Relatively stable costs after starting HD were associated with more stable scores

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study.

Science.gov (United States)

Verweij, Karin J H; Treur, Jorien L; Vink, Jacqueline M

2018-07-01

Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use. Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy. Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing. Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use. © 2018 Society for the Study of Addiction.

Nonlinear random resistor diode networks and fractal dimensions of directed percolation clusters.

Science.gov (United States)

Stenull, O; Janssen, H K

2001-07-01

We study nonlinear random resistor diode networks at the transition from the nonpercolating to the directed percolating phase. The resistor-like bonds and the diode-like bonds under forward bias voltage obey a generalized Ohm's law V approximately I(r). Based on general grounds such as symmetries and relevance we develop a field theoretic model. We focus on the average two-port resistance, which is governed at the transition by the resistance exponent straight phi(r). By employing renormalization group methods we calculate straight phi(r) for arbitrary r to one-loop order. Then we address the fractal dimensions characterizing directed percolation clusters. Via considering distinct values of the nonlinearity r, we determine the dimension of the red bonds, the chemical path, and the backbone to two-loop order.

Sensitivity Analysis in Two-Stage DEA

Directory of Open Access Journals (Sweden)

Athena Forghani

2015-07-01

Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.

Sensitivity Analysis in Two-Stage DEA

Directory of Open Access Journals (Sweden)

Athena Forghani

2015-12-01

Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.

Dynamical evolution of clusters with two stellar groups

Energy Technology Data Exchange (ETDEWEB)

Angeletti, L; Giannone, P. (Rome Univ. (Italy))

1977-08-01

The generalization of the fluid-dynamical approach from one-component star clusters to clusters with several stellar groups (as far as the star masses are concerned) has been applied to the study of two-component clusters. Rather extreme values of stellar masses and masses of groups were chosen in order to emphasize the different dynamical evolutions and asymptotic behaviors. Escape of stars from clusters and the problem of equipartition of kinetic energy among the two star groups are discussed. Comparisons of the main features of the results with those obtained by other authors have shown a good agreement. Some characteristic properties of the last computed models with an age of 18x10/sup 9/ yr have been pointed out and discussed in relation with some observed features of galactic globular clusters.

Two stage-type railgun accelerator

International Nuclear Information System (INIS)

Ogino, Mutsuo; Azuma, Kingo.

1995-01-01

The present invention provides a two stage-type railgun accelerator capable of spiking a flying body (ice pellet) formed by solidifying a gaseous hydrogen isotope as a fuel to a thermonuclear reactor at a higher speed into a central portion of plasmas. Namely, the two stage-type railgun accelerator accelerates the flying body spiked from a initial stage accelerator to a portion between rails by Lorentz force generated when electric current is supplied to the two rails by way of a plasma armature. In this case, two sets of solenoids are disposed for compressing the plasma armature in the longitudinal direction of the rails. The first and the second sets of solenoid coils are previously supplied with electric current. After passing of the flying body, the armature formed into plasmas by a gas laser disposed at the back of the flying body is compressed in the longitudinal direction of the rails by a magnetic force of the first and the second sets of solenoid coils to increase the plasma density. A current density is also increased simultaneously. Then, the first solenoid coil current is turned OFF to accelerate the flying body in two stages by the compressed plasma armature. (I.S.)

Improving the collection of knowledge, attitude and practice data with community surveys: a comparison of two second-stage sampling methods.

Science.gov (United States)

Davis, Rosemary H; Valadez, Joseph J

2014-12-01

Second-stage sampling techniques, including spatial segmentation, are widely used in community health surveys when reliable household sampling frames are not available. In India, an unresearched technique for household selection is used in eight states, which samples the house with the last marriage or birth as the starting point. Users question whether this last-birth or last-marriage (LBLM) approach introduces bias affecting survey results. We conducted two simultaneous population-based surveys. One used segmentation sampling; the other used LBLM. LBLM sampling required modification before assessment was possible and a more systematic approach was tested using last birth only. We compared coverage proportions produced by the two independent samples for six malaria indicators and demographic variables (education, wealth and caste). We then measured the level of agreement between the caste of the selected participant and the caste of the health worker making the selection. No significant difference between methods was found for the point estimates of six malaria indicators, education, caste or wealth of the survey participants (range of P: 0.06 to >0.99). A poor level of agreement occurred between the caste of the health worker used in household selection and the caste of the final participant, (Κ = 0.185), revealing little association between the two, and thereby indicating that caste was not a source of bias. Although LBLM was not testable, a systematic last-birth approach was tested. If documented concerns of last-birth sampling are addressed, this new method could offer an acceptable alternative to segmentation in India. However, inter-state caste variation could affect this result. Therefore, additional assessment of last birth is required before wider implementation is recommended. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

A cluster randomized controlled trial of a clinical pathway for hospital treatment of heart failure: study design and population

Directory of Open Access Journals (Sweden)

Gardini Andrea

2007-11-01

Full Text Available Abstract Background The hospital treatment of heart failure frequently does not follow published guidelines, potentially contributing to the high morbidity, mortality and economic cost of this disorder. Consequently the development of clinical pathways has the potential to reduce the current variability in care, enhance guideline adherence, and improve outcomes for patients. Despite enthusiasm and diffusion, the widespread acceptance of clinical pathways remain questionable because very little prospective controlled data demonstrated their effectiveness. The Experimental Prospective Study on the Effectiveness and Efficiency of the Implementation of Clinical Pathways was designed in order to conduct a rigorous evaluation of clinical pathways in hospital treatment of acute heart failure. The primary objective of the trial was to evaluate the effectiveness of the implementation of clinical pathways for hospital treatment of heart failure in Italian hospitals. Methods/design Two-arm, cluster-randomized trial. 14 community hospitals were randomized either to arm 1 (clinical pathway: appropriate use of practice guidelines and supplies of drugs and ancillary services, new organization and procedures, patient education, etc. or to arm 2 (no intervention, usual care. 424 patients sample (212 in each group, 80% of power at the 5% significance level (two-sided. The primary outcome measure is in-hospital mortality. We will also analyze the impact of the clinical pathways comparing the length and the appropriateness of the stay, the rate of unscheduled readmissions, the customers' satisfaction and the costs treating the patients with the pathways and with the current practice along all the observation period. The quality of the care will be assessed by monitoring the use of diagnostic and therapeutic procedures during hospital stay and by measuring key quality indicators at discharge. Discussion This paper examines the design of the evaluation of a complex

The effectiveness of xylitol in a school-based cluster-randomized clinical trial.

Science.gov (United States)

Lee, Wonik; Spiekerman, Charles; Heima, Masahiro; Eggertsson, Hafsteinn; Ferretti, Gerald; Milgrom, Peter; Nelson, Suchitra

2015-01-01

The purpose of this double-blind, cluster-randomized clinical trial was to examine the effects of xylitol gummy bear snacks on dental caries progression in primary and permanent teeth of inner-city school children. A total of 562 children aged 5-6 years were recruited from five elementary schools in East Cleveland, Ohio. Children were randomized by classroom to receive xylitol (7.8 g/day) or placebo (inulin fiber 20 g/day) gummy bears. Gummy bears were given three times per day for the 9-month kindergarten year within a supervised school environment. Children in both groups also received oral health education, toothbrush and fluoridated toothpaste, topical fluoride varnish treatment and dental sealants. The numbers of new decayed, missing, and filled surfaces for primary teeth (dmfs) and permanent teeth (DMFS) from baseline to the middle of 2nd grade (exit exam) were compared between the treatment (xylitol/placebo) groups using an optimally-weighted permutation test for cluster-randomized data. The mean new d(3-6)mfs at the exit exam was 5.0 ± 7.6 and 4.0 ± 6.5 for the xylitol and placebo group, respectively. Similarly, the mean new D(3-6)MFS was 0.38 ± 0.88 and 0.48 ± 1.39 for the xylitol and placebo group, respectively. The adjusted mean difference between the two groups was not statistically significant: new d(3-6)mfs: mean 0.4, 95% CI -0.25, 0.8), and new D(3-6)MFS: mean 0.16, 95% CI -0.16, 0.43. Xylitol consumption did not have additional benefit beyond other preventive measures. Caries progression in the permanent teeth of both groups was minimal, suggesting that other simultaneous prevention modalities may have masked the possible beneficial effects of xylitol in this trial. © 2014 S. Karger AG, Basel.

Clustering of samples and elements based on multi-variable chemical data

International Nuclear Information System (INIS)

Op de Beeck, J.

1984-01-01

Clustering and classification are defined in the context of multivariable chemical analysis data. Classical multi-variate techniques, commonly used to interpret such data, are shown to be based on probabilistic and geometrical principles which are not justified for analytical data, since in that case one assumes or expects a system of more or less systematically related objects (samples) as defined by measurements on more or less systematically interdependent variables (elements). For the specific analytical problem of data set concerning a large number of trace elements determined in a large number of samples, a deterministic cluster analysis can be used to develop the underlying classification structure. Three main steps can be distinguished: diagnostic evaluation and preprocessing of the raw input data; computation of a symmetric matrix with pairwise standardized dissimilarity values between all possible pairs of samples and/or elements; and ultrametric clustering strategy to produce the final classification as a dendrogram. The software packages designed to perform these tasks are discussed and final results are given. Conclusions are formulated concerning the dangers of using multivariate, clustering and classification software packages as a black-box

Possible two-stage /sup 87/Sr evolution in the Stockdale Rhyolite

Energy Technology Data Exchange (ETDEWEB)

Compston, W.; McDougall, I. (Australian National Univ., Canberra. Research School of Earth Sciences); Wyborn, D. (Department of Minerals and Energy, Canberra (Australia). Bureau of Mineral Resources)

1982-12-01

The Rb-Sr total-rock data for the Stockdale Rhyolite, of significance for the Palaeozoic time scale, are more scattered about a single-stage isochron than expected from experimental error. Two-stage /sup 87/Sr evolution for several of the samples is explored to explain this, as an alternative to variation in the initial /sup 87/Sr//sup 86/Sr which is customarily used in single-stage dating models. The deletion of certain samples having very high Rb/Sr removes most of the excess scatter and leads to an estimate of 430 +- 7 m.y. for the age of extrusion. There is a younger alignment of Rb-Sr data within each sampling site at 412 +- 7 m.y. We suggest that the Stockdale Rhyolite is at least 430 m.y. old, that its original range in Rb/Sr was smaller than now observed, and that it experienced a net loss in Sr during later hydrothermal alteration at ca. 412 m.y.

Effects of regularly consuming dietary fibre rich soluble cocoa products on bowel habits in healthy subjects: a free-living, two-stage, randomized, crossover, single-blind intervention

Directory of Open Access Journals (Sweden)

Sarriá Beatriz

2012-04-01

Full Text Available Abstract Background Dietary fibre is both preventive and therapeutic for bowel functional diseases. Soluble cocoa products are good sources of dietary fibre that may be supplemented with this dietary component. This study assessed the effects of regularly consuming two soluble cocoa products (A and B with different non-starch polysaccharides levels (NSP, 15.1 and 22.0% w/w, respectively on bowel habits using subjective intestinal function and symptom questionnaires, a daily diary and a faecal marker in healthy individuals. Methods A free-living, two-stage, randomized, crossover, single-blind intervention was carried out in 44 healthy men and women, between 18-55 y old, who had not taken dietary supplements, laxatives, or antibiotics six months before the start of the study. In the four-week-long intervention stages, separated by a three-week-wash-out stage, two servings of A and B, that provided 2.26 vs. 6.60 g/day of NSP respectively, were taken. In each stage, volunteers' diet was recorded using a 72-h food intake report. Results Regularly consuming cocoa A and B increased fibre intake, although only cocoa B significantly increased fibre intake (p Conclusions Regular consumption of the cocoa products increases dietary fibre intake to recommended levels and product B improves bowel habits. The use of both objective and subjective assessments to evaluate the effects of food on bowel habits is recommended.

Two-stage implant systems.

Science.gov (United States)

Fritz, M E

1999-06-01

Since the advent of osseointegration approximately 20 years ago, there has been a great deal of scientific data developed on two-stage integrated implant systems. Although these implants were originally designed primarily for fixed prostheses in the mandibular arch, they have been used in partially dentate patients, in patients needing overdentures, and in single-tooth restorations. In addition, this implant system has been placed in extraction sites, in bone-grafted areas, and in maxillary sinus elevations. Often, the documentation of these procedures has lagged. In addition, most of the reports use survival criteria to describe results, often providing overly optimistic data. It can be said that the literature describes a true adhesion of the epithelium to the implant similar to adhesion to teeth, that two-stage implants appear to have direct contact somewhere between 50% and 70% of the implant surface, that the microbial flora of the two-stage implant system closely resembles that of the natural tooth, and that the microbiology of periodontitis appears to be closely related to peri-implantitis. In evaluations of the data from implant placement in all of the above-noted situations by means of meta-analysis, it appears that there is a strong case that two-stage dental implants are successful, usually showing a confidence interval of over 90%. It also appears that the mandibular implants are more successful than maxillary implants. Studies also show that overdenture therapy is valid, and that single-tooth implants and implants placed in partially dentate mouths have a success rate that is quite good, although not quite as high as in the fully edentulous dentition. It would also appear that the potential causes of failure in the two-stage dental implant systems are peri-implantitis, placement of implants in poor-quality bone, and improper loading of implants. There are now data addressing modifications of the implant surface to alter the percentage of

Standardized Effect Size Measures for Mediation Analysis in Cluster-Randomized Trials

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Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric

2015-01-01

This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…

Two-step two-stage fission gas release model

International Nuclear Information System (INIS)

Kim, Yong-soo; Lee, Chan-bock

2006-01-01

Based on the recent theoretical model, two-step two-stage model is developed which incorporates two stage diffusion processes, grain lattice and grain boundary diffusion, coupled with the two step burn-up factor in the low and high burn-up regime. FRAPCON-3 code and its in-pile data sets have been used for the benchmarking and validation of this model. Results reveals that its prediction is in better agreement with the experimental measurements than that by any model contained in the FRAPCON-3 code such as ANS 5.4, modified ANS5.4, and Forsberg-Massih model over whole burn-up range up to 70,000 MWd/MTU. (author)

Family-based clusters of cognitive test performance in familial schizophrenia

Directory of Open Access Journals (Sweden)

Partonen Timo

2004-07-01

Full Text Available Abstract Background Cognitive traits derived from neuropsychological test data are considered to be potential endophenotypes of schizophrenia. Previously, these traits have been found to form a valid basis for clustering samples of schizophrenia patients into homogeneous subgroups. We set out to identify such clusters, but apart from previous studies, we included both schizophrenia patients and family members into the cluster analysis. The aim of the study was to detect family clusters with similar cognitive test performance. Methods Test scores from 54 randomly selected families comprising at least two siblings with schizophrenia spectrum disorders, and at least two unaffected family members were included in a complete-linkage cluster analysis with interactive data visualization. Results A well-performing, an impaired, and an intermediate family cluster emerged from the analysis. While the neuropsychological test scores differed significantly between the clusters, only minor differences were observed in the clinical variables. Conclusions The visually aided clustering algorithm was successful in identifying family clusters comprising both schizophrenia patients and their relatives. The present classification method may serve as a basis for selecting phenotypically more homogeneous groups of families in subsequent genetic analyses.

Identifying seizure clusters in patients with psychogenic nonepileptic seizures.

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Baird, Grayson L; Harlow, Lisa L; Machan, Jason T; Thomas, Dave; LaFrance, W C

2017-08-01

The present study explored how seizure clusters may be defined for those with psychogenic nonepileptic seizures (PNES), a topic for which there is a paucity of literature. The sample was drawn from a multisite randomized clinical trial for PNES; seizure data are from participants' seizure diaries. Three possible cluster definitions were examined: 1) common clinical definition, where ≥3 seizures in a day is considered a cluster, along with two novel statistical definitions, where ≥3 seizures in a day are considered a cluster if the observed number of seizures statistically exceeds what would be expected relative to a patient's: 1) average seizure rate prior to the trial, 2) observed seizure rate for the previous seven days. Prevalence of clusters was 62-68% depending on cluster definition used, and occurrence rate of clusters was 6-19% depending on cluster definition. Based on these data, clusters seem to be common in patients with PNES, and more research is needed to identify if clusters are related to triggers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

HICOSMO - cosmology with a complete sample of galaxy clusters - I. Data analysis, sample selection and luminosity-mass scaling relation

Science.gov (United States)

Schellenberger, G.; Reiprich, T. H.

2017-08-01

The X-ray regime, where the most massive visible component of galaxy clusters, the intracluster medium, is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to characterize these objects. The aim of this project is to analyse a complete sample of galaxy clusters in detail and constrain cosmological parameters, like the matter density, Ωm, or the amplitude of initial density fluctuations, σ8. The purely X-ray flux-limited sample (HIFLUGCS) consists of the 64 X-ray brightest galaxy clusters, which are excellent targets to study the systematic effects, that can bias results. We analysed in total 196 Chandra observations of the 64 HIFLUGCS clusters, with a total exposure time of 7.7 Ms. Here, we present our data analysis procedure (including an automated substructure detection and an energy band optimization for surface brightness profile analysis) that gives individually determined, robust total mass estimates. These masses are tested against dynamical and Planck Sunyaev-Zeldovich (SZ) derived masses of the same clusters, where good overall agreement is found with the dynamical masses. The Planck SZ masses seem to show a mass-dependent bias to our hydrostatic masses; possible biases in this mass-mass comparison are discussed including the Planck selection function. Furthermore, we show the results for the (0.1-2.4) keV luminosity versus mass scaling relation. The overall slope of the sample (1.34) is in agreement with expectations and values from literature. Splitting the sample into galaxy groups and clusters reveals, even after a selection bias correction, that galaxy groups exhibit a significantly steeper slope (1.88) compared to clusters (1.06).

Two stages of economic development

OpenAIRE

Gong, Gang

2016-01-01

This study suggests that the development process of a less-developed country can be divided into two stages, which demonstrate significantly different properties in areas such as structural endowments, production modes, income distribution, and the forces that drive economic growth. The two stages of economic development have been indicated in the growth theory of macroeconomics and in the various "turning point" theories in development economics, including Lewis's dual economy theory, Kuznet...

Effectiveness of a self-management program for dual sensory impaired seniors in aged care settings: study protocol for a cluster randomized controlled trial.

Science.gov (United States)

Roets-Merken, Lieve M; Graff, Maud J L; Zuidema, Sytse U; Hermsen, Pieter G J M; Teerenstra, Steven; Kempen, Gertrudis I J M; Vernooij-Dassen, Myrra J F J

2013-10-07

Five to 25 percent of residents in aged care settings have a combined hearing and visual sensory impairment. Usual care is generally restricted to single sensory impairment, neglecting the consequences of dual sensory impairment on social participation and autonomy. The aim of this study is to evaluate the effectiveness of a self-management program for seniors who acquired dual sensory impairment at old age. In a cluster randomized, single-blind controlled trial, with aged care settings as the unit of randomization, the effectiveness of a self-management program will be compared to usual care. A minimum of 14 and maximum of 20 settings will be randomized to either the intervention cluster or the control cluster, aiming to include a total of 132 seniors with dual sensory impairment. Each senior will be linked to a licensed practical nurse working at the setting. During a five to six month intervention period, nurses at the intervention clusters will be trained in a self-management program to support and empower seniors to use self-management strategies. In two separate diaries, nurses keep track of the interviews with the seniors and their reflections on their own learning process. Nurses of the control clusters offer care as usual. At senior level, the primary outcome is the social participation of the seniors measured using the Hearing Handicap Questionnaire and the Activity Card Sort, and secondary outcomes are mood, autonomy and quality of life. At nurse level, the outcome is job satisfaction. Effectiveness will be evaluated using linear mixed model analysis. The results of this study will provide evidence for the effectiveness of the Self-Management Program for seniors with dual sensory impairment living in aged care settings. The findings are expected to contribute to the knowledge on the program's potential to enhance social participation and autonomy of the seniors, as well as increasing the job satisfaction of the licensed practical nurses. Furthermore, an

Mutation Clusters from Cancer Exome.

Science.gov (United States)

Kakushadze, Zura; Yu, Willie

2017-08-15

We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

Effects of pushing techniques during the second stage of labor: A randomized controlled trial.

Science.gov (United States)

Koyucu, Refika Genç; Demirci, Nurdan

2017-10-01

Spontaneous pushing is a method that is used in the management of the second stage of labor and suggested to be more physiological for the mother and infant. The present study aims to evaluate the effects of pushing techniques on the mother and newborn. This randomized prospective study was performed between June 2013-March 2014 in a tertiary maternity clinic in Istanbul. 80 low risk, nulliparous cases were randomized to pushing groups. Valsalva pushing group was told to hold their breath while pushing. No visual-verbal instructions were given to spontaneous pushing group and they were encouraged to push without preventing respiration. Demographic data, second stage period, perineal laceration rates, fetal heart rate patterns, presence of meconium stained amniotic liquid, newborn APGAR scores, POP-Q examination and Q-tip test results were evaluated in these cases. The second stage of labor was significantly longer with spontaneous pushing. Decrease in Hb levels in valsalva pushing group was determined to be higher than spontaneous pushing group. An increased urethral mobility was observed in valsalva pushing group. Although the duration of the second stage of labor was longer compared to valsalva pushing technique, women were able to give birth without requiring any verbal or visual instruction, without exceeding the limit value of two hours and without affecting fetal wellness and neonatal results. Copyright © 2017. Published by Elsevier B.V.

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

International Nuclear Information System (INIS)

Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico; Portegies Zwart, Simon

2013-01-01

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noise introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.

FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model.

Directory of Open Access Journals (Sweden)

Mingjun Wang

Full Text Available Single amino acid variants (SAVs are the most abundant form of known genetic variations associated with human disease. Successful prediction of the functional impact of SAVs from sequences can thus lead to an improved understanding of the underlying mechanisms of why a SAV may be associated with certain disease. In this work, we constructed a high-quality structural dataset that contained 679 high-quality protein structures with 2,048 SAVs by collecting the human genetic variant data from multiple resources and dividing them into two categories, i.e., disease-associated and neutral variants. We built a two-stage random forest (RF model, termed as FunSAV, to predict the functional effect of SAVs by combining sequence, structure and residue-contact network features with other additional features that were not explored in previous studies. Importantly, a two-step feature selection procedure was proposed to select the most important and informative features that contribute to the prediction of disease association of SAVs. In cross-validation experiments on the benchmark dataset, FunSAV achieved a good prediction performance with the area under the curve (AUC of 0.882, which is competitive with and in some cases better than other existing tools including SIFT, SNAP, Polyphen2, PANTHER, nsSNPAnalyzer and PhD-SNP. The sourcecodes of FunSAV and the datasets can be downloaded at http://sunflower.kuicr.kyoto-u.ac.jp/sjn/FunSAV.

Placental cord drainage in the third stage of labor: Randomized clinical trial.

Science.gov (United States)

Vasconcelos, Fernanda Barros; Katz, Leila; Coutinho, Isabela; Lins, Vanessa Laranjeiras; de Amorim, Melania Maria

2018-01-01

An open randomized clinical trial was developed at Instituto de Medicina Integral Prof. Fernando Figueira (IMIP) in Recife and at Petronila Campos Municipal Hospital in São Lourenço da Mata, both in Pernambuco, northeastern Brazil, including 226 low-risk pregnant women bearing a single, full-term, live fetus after delayed cord clamping, 113 randomized to placental cord drainage and 113 to a control group not submitted to this procedure. Women incapable of understanding the study objectives and those who went on to have an instrumental or cesarean delivery were excluded. Duration of the third stage of labor did not differ between the two groups (14.2±12.9 versus 13.7±12.1 minutes (mean ± SD), p = 0.66). Likewise, there was no significant difference in mean blood loss (248±254 versus 208±187ml, p = 0.39) or in postpartum hematocrit levels (32.3±4.06 versus 32.8±4.25mg/dl, p = 0.21). Furthermore, no differences were found between the groups for any of the secondary outcomes (postpartum hemorrhage >500 or >1000ml, therapeutic use of oxytocin, third stage >30 or 60 minutes, digital evacuation of the uterus or curettage, symptoms of postpartum anemia and maternal satisfaction). Placental cord drainage had no effect in reducing duration or blood loss during the third stage of labor. ClinicalTrials.gov: www.clinicaltrial.gov, NCT01655576.

The Quality Initiative in Rectal Cancer (QIRC trial: study protocol of a cluster randomized controlled trial in surgery

Directory of Open Access Journals (Sweden)

Thabane Lehana

2008-02-01

Full Text Available Abstract Background Two unfortunate outcomes for patients treated surgically for rectal cancer are placement of a permanent colostomy and local tumor recurrence. Total mesorectal excision is a new technique for rectal cancer surgery that can lead to improved patient outcomes. We describe a cluster randomized controlled trial that is testing if the above patient outcomes can be improved through a knowledge translation strategy called the Quality Initiative in Rectal Cancer (QIRC strategy. The strategy is designed to optimize the use of total mesorectal excision techniques. Methods and Design Hospitals were randomized to the QIRC strategy (experimental group versus normal practice environment (control group. Participating hospitals, and the respective surgeon group operating in them, are from Ontario, Canada and have an annual procedure volume for major rectal cancer resections of 15 or greater. Patients were eligible if they underwent major rectal surgery for a diagnosis of primary rectal cancer. The surgeon-directed QIRC interventions included a workshop, use of opinion leaders, operative demonstrations, a post-operative questionnaire, and, audit and feedback. For an operative demonstration participating surgeons invited a study team surgeon to assist them with a case of rectal cancer surgery. The intent was to demonstrate total mesorectal excision techniques. Control arm surgeons received no intervention. Sample size calculations were two-sided, considered the clustering of data at the hospital level, and were driven by requirements for the outcome local recurrence. To detect an improvement in local recurrence from 20% to 8% with confidence we required 16 hospitals and 672 patients – 8 hospitals and 336 patients in each arm. Outcomes data are collected via chart review for at least 30 months after surgery. Analyses will use an intention-to-treat principle and will consider the clustering of data. Data collection will be complete by the end of

Characterisation of the early stages of solute clustering in 1Ni-1.3Mn welds containing Cu

Energy Technology Data Exchange (ETDEWEB)

Hyde, J.M., E-mail: jonathan.hyde@materials.ox.ac.uk [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); National Nuclear Laboratory Ltd, B168 Harwell, Didcot, Oxon OX11 0QJ (United Kingdom); Burke, M.G. [Bechtel Bettis Inc., 814 Pittsburgh-McKeesport Blvd, West Mifflin, Pittsburgh 15122-0079 (United States); Boothby, R.M.; English, C.A. [National Nuclear Laboratory Ltd, B168 Harwell, Didcot, Oxon OX11 0QJ (United Kingdom)

2009-04-15

Microstructural characterisation of neutron irradiated low alloy steels is important for developing mechanistic understanding of irradiation embrittlement. This work is focused on the early stages of irradiation-induced clustering in a low Cu (0.03 wt%), high Ni ({approx}1 wt%) weld. The weld was irradiated at a very high dose rate and then examined by atom probe (energy-compensated position-sensitive atom probe (ECOPoSAP) and local electrode atom probe (LEAP)) with supporting microstructural information obtained by small angle neutron scattering (SANS) and positron annihilation (PALA). It was demonstrated that extreme care must be taken optimising parameters used to characterise the extent of clustering. This is particularly important during the early stages of irradiation-damage when the clusters are poorly defined and significant compositional variations are present in what is traditionally described as matrix. Analysis of the irradiated materials showed increasing clustering of Cu, Mn, Ni and Si with dose. In the low Cu steel the results showed that initially the irradiation damage results in clustering of Mn, Ni and Si, but at very high doses, at very high dose rates, redistribution of Si is significantly more advanced than that for Mn and Ni.

Sample size calculations for cluster randomised crossover trials in Australian and New Zealand intensive care research.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Pilcher, David; Bellomo, Rinaldo; Forbes, Andrew B

2018-06-01

The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. We show sample size calculations for a two-intervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design). The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design. The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.

Two stages of Kondo effect and competition between RKKY and Kondo in Gd-based intermetallic compound

International Nuclear Information System (INIS)

Vaezzadeh, Mehdi; Yazdani, Ahmad; Vaezzadeh, Majid; Daneshmand, Gissoo; Kanzeghi, Ali

2006-01-01

The magnetic behavior of Gd-based intermetallic compound (Gd 2 Al (1-x) Au x ) in the form of the powder and needle, is investigated. All the samples are an orthorhombic crystal structure. Only the compound with x=0.4 shows the Kondo effect (other compounds have a normal behavior). Although, for the compound in the form of powder, with x=0.4, the susceptibility measurement χ(T) shows two different stages. Moreover for (T>T K2 ) a fall of the value of χ(T) is observable, which indicates a weak presence of ferromagnetic phase. About the two stages of Kondo effect, we observe at the first (T K1 ) an increase of χ(T) and in the second stage (T K2 ) a new remarkable decrease of χ(T) (T K1 >T K2 ). For the sample in the form of needles, the first stage is observable only under high magnetic field. This first stage could be corresponds to a narrow resonance between Kondo cloud and itinerant electron. The second stage, which is remarkably visible for the sample in the form of the powder, can be attribute to a complete polarization of Kondo cloud. Observation of these two Kondo stages could be due to the weak presence of RKKY contribution

Born series for (2 cluster) → (2 cluster) scattering of two, three, and four particle Schroedinger operators

International Nuclear Information System (INIS)

Hagedorn, G.A.

1979-01-01

We investigate elastic and inelastic (2 cluster)→(2 cluster)scattering for classes of two, three, and four body Schroedinger operators H=H 0 +ΣVij. Formulas are derived for those generalized eigenfunctions of H which correspond asymptotically in the past to two freely moving clusters. With these eigenfunctions, we establish a formula for the (2 cluster)→(2 cluster) T-matrix and prove the convergence of a Born series for the T-matrix at high energy. (orig.) [de

Effectiveness of a multi-level implementation strategy for ASD interventions: study protocol for two linked cluster randomized trials.

Science.gov (United States)

Brookman-Frazee, Lauren; Stahmer, Aubyn C

2018-05-09

The Centers for Disease Control (2018) estimates that 1 in 59 children has autism spectrum disorder, and the annual cost of ASD in the U.S. is estimated to be $236 billion. Evidence-based interventions have been developed and demonstrate effectiveness in improving child outcomes. However, research on generalizable methods to scale up these practices in the multiple service systems caring for these children has been limited and is critical to meet this growing public health need. This project includes two, coordinated studies testing the effectiveness of the Translating Evidence-based Interventions (EBI) for ASD: Multi-Level Implementation Strategy (TEAMS) model. TEAMS focuses on improving implementation leadership, organizational climate, and provider attitudes and motivation in order to improve two key implementation outcomes-provider training completion and intervention fidelity and subsequent child outcomes. The TEAMS Leadership Institute applies implementation leadership strategies and TEAMS Individualized Provider Strategies for training applies motivational interviewing strategies to facilitate provider and organizational behavior change. A cluster randomized implementation/effectiveness Hybrid, type 3, trial with a dismantling design will be used to understand the effectiveness of TEAMS and the mechanisms of change across settings and participants. Study #1 will test the TEAMS model with AIM HI (An Individualized Mental Health Intervention for ASD) in publicly funded mental health services. Study #2 will test TEAMS with CPRT (Classroom Pivotal Response Teaching) in education settings. Thirty-seven mental health programs and 37 school districts will be randomized, stratified by county and study, to one of four groups (Standard Provider Training Only, Standard Provider Training + Leader Training, Enhanced Provider Training, Enhanced Provider Training + Leader Training) to test the effectiveness of combining standard, EBI-specific training with the two TEAMS

Plasmon response in K, Na and Li clusters: systematics using the separable random-phase approximation with pseudo-Hamiltonians

International Nuclear Information System (INIS)

Kleinig, W.; Nesterenko, V.O.; Reinhard, P.-G.; Serra, Ll.

1998-01-01

The systematics of the plasmon response in spherical K, Na and Li clusters in a wide size region (8≤N≤440) is studied. We have considered two simplifying approximations whose validity has been established previously. First, a separable approach to the random-phase approximation is used. This involves an expansion of the residual interaction into a sum of separable terms until convergence is reached. Second, the electron-ion interaction is modelled by using the pseudo-Hamiltonian jellium model (MHJM) which includes nonlocal effects by means of realistic atomic pseudo-Hamiltonians. In cases where nonlocal effects are negligible the Structure Averaged Jellium Model (SAJM) has been used. Good agreement with available experimental data is achieved for K, Na (using the SAJM) and small Li clusters (invoking the PHJM). The trends for peak position and width are generally well reproduced, even up to details of the Landau fragmentation in several clusters. Less good agreement, however, is found for large Li clusters. This remains an open question

Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis.

Science.gov (United States)

Jamshidy, Ladan; Mozaffari, Hamid Reza; Faraji, Payam; Sharifi, Roohollah

2016-01-01

Introduction . One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods . A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL) regions by a stereomicroscope using a standard method. Results . The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion . The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.

Small Launch Vehicle Design Approaches: Clustered Cores Compared with Multi-Stage Inline Concepts

Science.gov (United States)

Waters, Eric D.; Beers, Benjamin; Esther, Elizabeth; Philips, Alan; Threet, Grady E., Jr.

2013-01-01

In an effort to better define small launch vehicle design options two approaches were investigated from the small launch vehicle trade space. The primary focus was to evaluate a clustered common core design against a purpose built inline vehicle. Both designs focused on liquid oxygen (LOX) and rocket propellant grade kerosene (RP-1) stages with the terminal stage later evaluated as a LOX/methane (CH4) stage. A series of performance optimization runs were done in order to minimize gross liftoff weight (GLOW) including alternative thrust levels, delivery altitude for payload, vehicle length to diameter ratio, alternative engine feed systems, re-evaluation of mass growth allowances, passive versus active guidance systems, and rail and tower launch methods. Additionally manufacturability, cost, and operations also play a large role in the benefits and detriments for each design. Presented here is the Advanced Concepts Office's Earth to Orbit Launch Team methodology and high level discussion of the performance trades and trends of both small launch vehicle solutions along with design philosophies that shaped both concepts. Without putting forth a decree stating one approach is better than the other; this discussion is meant to educate the community at large and let the reader determine which architecture is truly the most economical; since each path has such a unique set of limitations and potential payoffs.

Comparison of single-stage and temperature-phased two-stage anaerobic digestion of oily food waste

International Nuclear Information System (INIS)

Wu, Li-Jie; Kobayashi, Takuro; Li, Yu-You; Xu, Kai-Qin

2015-01-01

Highlights: • A single-stage and two two-stage anaerobic systems were synchronously operated. • Similar methane production 0.44 L/g VS_a_d_d_e_d from oily food waste was achieved. • The first stage of the two-stage process became inefficient due to serious pH drop. • Recycle favored the hythan production in the two-stage digestion. • The conversion of unsaturated fatty acids was enhanced by recycle introduction. - Abstract: Anaerobic digestion is an effective technology to recover energy from oily food waste. A single-stage system and temperature-phased two-stage systems with and without recycle for anaerobic digestion of oily food waste were constructed to compare the operation performances. The synchronous operation indicated the similar ability to produce methane in the three systems, with a methane yield of 0.44 L/g VS_a_d_d_e_d. The pH drop to less than 4.0 in the first stage of two-stage system without recycle resulted in poor hydrolysis, and methane or hydrogen was not produced in this stage. Alkalinity supplement from the second stage of two-stage system with recycle improved pH in the first stage to 5.4. Consequently, 35.3% of the particulate COD in the influent was reduced in the first stage of two-stage system with recycle according to a COD mass balance, and hydrogen was produced with a percentage of 31.7%, accordingly. Similar solids and organic matter were removed in the single-stage system and two-stage system without recycle. More lipid degradation and the conversion of long-chain fatty acids were achieved in the single-stage system. Recycling was proved to be effective in promoting the conversion of unsaturated long-chain fatty acids into saturated fatty acids in the two-stage system.

GLACE: freezing the environment of line--emitting cluster galaxies

Science.gov (United States)

Pintos--Castro, I.; Sánchez--Portal, M.; Cepa, J.; Povi, M.; Santos, J.; Altieri, B.; Bongiovanni, A.; Ederoclite, A.; Oteo, I.; Pérez García, A.; Pérez--Martínez, R.; Polednikova, J.; Ramón--Pérez, M.

2015-05-01

GLACE is performing a survey of emission-line galaxies in clusters with the main aim of studying the effect of the environment in the star formation activity. The innovation of this work is the use of tunable filters in scan mode to obtain low resolution spectra of the desired emission lines. Although the survey is in its initial stage, we have analysed two line datasets in two different clusters: Hα in Cl0024 at z=0.4 and [O II] in RXJ1257 at z = 0.9. The first is a well known intermediate redshift cluster that has been used to test the observational strategy. We reached the planned SFRs and we could deblend the [N II] component, thus being able to discriminate the AGN population from the star-forming galaxies. Also the spectral resolution is allowing us to exploit the data for dynamical analysis. The second target is a recently discovered cluster, that we have studied regarding its FIR and [O II] emission. The [O II] observations are revealing a fainter and less massive sample, when compared with the FIR emitters, showing two different populations of star-forming galaxies. The cluster emitters have shown that no evident correlation exist between the SFR (or sSFR) and the environment. Nevertheless, we have found that both samples, FIR- and [O II]-emitters, are concentrated in the areas of intermediate to even high local density. Additionally, we explored the morphological properties of the cluster galaxies using the non-parametric galSVM code.

Improving mental health among ultra-poor children: Two-year outcomes of a cluster-randomized trial in Burkina Faso.

Science.gov (United States)

Ismayilova, Leyla; Karimli, Leyla; Sanson, Jo; Gaveras, Eleni; Nanema, Rachel; Tô-Camier, Alexice; Chaffin, Josh

2018-07-01

There is limited evidence about interventions improving child mental health in francophone West Africa. Behavioral mental health interventions alone may have limited effects on children's emotional well-being in families living in abject poverty, especially in low-income countries. This study tests the effects of economic intervention, alone and in combination with a family-focused component, on the mental health of children from ultra-poor households in rural Burkina Faso. The three-arm cluster randomized trial included children in the age range of 10-15 years old (N = 360), from twelve villages in Nord region of Burkina Faso (ClinicalTrial.gov ID: NCT02415933). Villages were randomized (4 villages/120 households per arm) to the waitlist arm, the economic intervention utilizing the Graduation approach (Trickle Up/TU arm), or to the economic strengthening plus family coaching component (TU + arm). Intervention effects were tested using repeated-measures mixed-effects regressions that account for the clustered nature of the data. Children from the TU + arm showed a reduction in depressive symptoms at 12 months (medium effect size Cohen's d = -0.41, p = .001) and 24 months (d = -0.39, p = .025), compared to the control condition and the economic intervention alone (at 12 months d = -0.22, p = .020). Small effect size improvements in self-esteem were detected in the TU + group, compared to the control arm at 12 months (d = 0.21) and to the TU arm at 24 months (d = 0.21). Trauma symptoms significantly reduced in the TU + group at 12 months (Incidence Risk Ratio/IRR = 0.62, 95% CI = 0.41, 0.92, p = .042), compared to the control group. Integrating psychosocial intervention involving all family members with economic empowerment strategies may be an innovative approach for improving emotional well-being among children living in extreme poverty. Copyright © 2018 Elsevier Ltd. All rights reserved.

Cluster Randomized Trail of the uptake of a take-home Infant dose ...

African Journals Online (AJOL)

Objective: To test whether a single take home dose of infant nevirapine increased infant uptake without decreasing institutional deliveries. Design: Cluster randomized post-test only study with control group. Setting: Ten hospitals in urban areas of Coast, Rift Valley, and Western provinces, Kenya. Participants: Pregnant ...

The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data

Science.gov (United States)

Husein, A. M.; Harahap, M.; Aisyah, S.; Purba, W.; Muhazir, A.

2018-03-01

Medication planning aim to get types, amount of medicine according to needs, and avoid the emptiness medicine based on patterns of disease. In making the medicine planning is still rely on ability and leadership experience, this is due to take a long time, skill, difficult to obtain a definite disease data, need a good record keeping and reporting, and the dependence of the budget resulted in planning is not going well, and lead to frequent lack and excess of medicines. In this research, we propose Adaptive Neuro Fuzzy Inference System (ANFIS) method to predict medication needs in 2016 and 2017 based on medical data in 2015 and 2016 from two source of hospital. The framework of analysis using two approaches. The first phase is implementing ANFIS to a data source, while the second approach we keep using ANFIS, but after the process of clustering from K-Means algorithm, both approaches are calculated values of Root Mean Square Error (RMSE) for training and testing. From the testing result, the proposed method with better prediction rates based on the evaluation analysis of quantitative and qualitative compared with existing systems, however the implementation of K-Means Algorithm against ANFIS have an effect on the timing of the training process and provide a classification accuracy significantly better without clustering.

Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

Directory of Open Access Journals (Sweden)

Sylvia Jane Annatje Sumarauw

2007-06-01

Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

Evaluation of immunization coverage by lot quality assurance sampling compared with 30-cluster sampling in a primary health centre in India.

Science.gov (United States)

Singh, J; Jain, D C; Sharma, R S; Verghese, T

1996-01-01

The immunization coverage of infants, children and women residing in a primary health centre (PHC) area in Rajasthan was evaluated both by lot quality assurance sampling (LQAS) and by the 30-cluster sampling method recommended by WHO's Expanded Programme on Immunization (EPI). The LQAS survey was used to classify 27 mutually exclusive subunits of the population, defined as residents in health subcentre areas, on the basis of acceptable or unacceptable levels of immunization coverage among infants and their mothers. The LQAS results from the 27 subcentres were also combined to obtain an overall estimate of coverage for the entire population of the primary health centre, and these results were compared with the EPI cluster survey results. The LQAS survey did not identify any subcentre with a level of immunization among infants high enough to be classified as acceptable; only three subcentres were classified as having acceptable levels of tetanus toxoid (TT) coverage among women. The estimated overall coverage in the PHC population from the combined LQAS results showed that a quarter of the infants were immunized appropriately for their ages and that 46% of their mothers had been adequately immunized with TT. Although the age groups and the periods of time during which the children were immunized differed for the LQAS and EPI survey populations, the characteristics of the mothers were largely similar. About 57% (95% CI, 46-67) of them were found to be fully immunized with TT by 30-cluster sampling, compared with 46% (95% CI, 41-51) by stratified random sampling. The difference was not statistically significant. The field work to collect LQAS data took about three times longer, and cost 60% more than the EPI survey. The apparently homogeneous and low level of immunization coverage in the 27 subcentres makes this an impractical situation in which to apply LQAS, and the results obtained were therefore not particularly useful. However, if LQAS had been applied by local

Assessing the feasibility of interrupting the transmission of soil-transmitted helminths through mass drug administration: The DeWorm3 cluster randomized trial protocol.

Science.gov (United States)

Ásbjörnsdóttir, Kristjana Hrönn; Ajjampur, Sitara S Rao; Anderson, Roy M; Bailey, Robin; Gardiner, Iain; Halliday, Katherine E; Ibikounle, Moudachirou; Kalua, Khumbo; Kang, Gagandeep; Littlewood, D Timothy J; Luty, Adrian J F; Means, Arianna Rubin; Oswald, William; Pullan, Rachel L; Sarkar, Rajiv; Schär, Fabian; Szpiro, Adam; Truscott, James E; Werkman, Marleen; Yard, Elodie; Walson, Judd L

2018-01-01

Current control strategies for soil-transmitted helminths (STH) emphasize morbidity control through mass drug administration (MDA) targeting preschool- and school-age children, women of childbearing age and adults in certain high-risk occupations such as agricultural laborers or miners. This strategy is effective at reducing morbidity in those treated but, without massive economic development, it is unlikely it will interrupt transmission. MDA will therefore need to continue indefinitely to maintain benefit. Mathematical models suggest that transmission interruption may be achievable through MDA alone, provided that all age groups are targeted with high coverage. The DeWorm3 Project will test the feasibility of interrupting STH transmission using biannual MDA targeting all age groups. Study sites (population ≥80,000) have been identified in Benin, Malawi and India. Each site will be divided into 40 clusters, to be randomized 1:1 to three years of twice-annual community-wide MDA or standard-of-care MDA, typically annual school-based deworming. Community-wide MDA will be delivered door-to-door, while standard-of-care MDA will be delivered according to national guidelines. The primary outcome is transmission interruption of the STH species present at each site, defined as weighted cluster-level prevalence ≤2% by quantitative polymerase chain reaction (qPCR), 24 months after the final round of MDA. Secondary outcomes include the endline prevalence of STH, overall and by species, and the endline prevalence of STH among children under five as an indicator of incident infections. Secondary analyses will identify cluster-level factors associated with transmission interruption. Prevalence will be assessed using qPCR of stool samples collected from a random sample of cluster residents at baseline, six months after the final round of MDA and 24 months post-MDA. A smaller number of individuals in each cluster will be followed with annual sampling to monitor trends in

An inexact mixed risk-aversion two-stage stochastic programming model for water resources management under uncertainty.

Science.gov (United States)

Li, W; Wang, B; Xie, Y L; Huang, G H; Liu, L

2015-02-01

Uncertainties exist in the water resources system, while traditional two-stage stochastic programming is risk-neutral and compares the random variables (e.g., total benefit) to identify the best decisions. To deal with the risk issues, a risk-aversion inexact two-stage stochastic programming model is developed for water resources management under uncertainty. The model was a hybrid methodology of interval-parameter programming, conditional value-at-risk measure, and a general two-stage stochastic programming framework. The method extends on the traditional two-stage stochastic programming method by enabling uncertainties presented as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. It could not only provide information on the benefits of the allocation plan to the decision makers but also measure the extreme expected loss on the second-stage penalty cost. The developed model was applied to a hypothetical case of water resources management. Results showed that that could help managers generate feasible and balanced risk-aversion allocation plans, and analyze the trade-offs between system stability and economy.

On the prior probabilities for two-stage Bayesian estimates

International Nuclear Information System (INIS)

Kohut, P.

1992-01-01

The method of Bayesian inference is reexamined for its applicability and for the required underlying assumptions in obtaining and using prior probability estimates. Two different approaches are suggested to determine the first-stage priors in the two-stage Bayesian analysis which avoid certain assumptions required for other techniques. In the first scheme, the prior is obtained through a true frequency based distribution generated at selected intervals utilizing actual sampling of the failure rate distributions. The population variability distribution is generated as the weighed average of the frequency distributions. The second method is based on a non-parametric Bayesian approach using the Maximum Entropy Principle. Specific features such as integral properties or selected parameters of prior distributions may be obtained with minimal assumptions. It is indicated how various quantiles may also be generated with a least square technique

Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G.

1993-11-01

The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

DEFF Research Database (Denmark)

Kent, Peter; Stochkendahl, Mette Jensen; Wulff Christensen, Henrik

2015-01-01

participation, psychological factors, biomarkers and imaging. However, such ‘whole person’ research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may...... potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it....

Nano-scale clusters formed in the early stage of phase decomposition of Al-Mg-Si alloys

Energy Technology Data Exchange (ETDEWEB)

Hirosawa, S.; Sato, T. [Dept. of Metallurgy and Ceramics Science, Tokyo Inst. of Tech. (Japan)

2005-07-01

The formation of nano-scale clusters (nanoclusters) prior to the precipitation of the strengthening {beta}'' phase significantly influences two-step aging behavior of Al-Mg-Si alloys. In this work, the existence of two kinds of nanoclusters has been verified in the early stage of phase decomposition by differential scanning calorimetry (DSC) and three-dimensional atom probe (3DAP). Pre-aging treatment at 373 K before natural aging was also found to form preferentially one of the two nanoclusters, resulting in the remarkable restoration of age-hardenability at paint-bake temperatures. Such microstructural control by means of optimized heat-treatments; i.e. nanocluster assist processing (NCAP), possesses great potential for enabling Al-Mg-Si alloys to be used more widely as a body-sheet material of automobiles. (orig.)

The effectiveness of non-pyrethroid insecticide-treated durable wall lining to control malaria in rural Tanzania: study protocol for a two-armed cluster randomized trial

Directory of Open Access Journals (Sweden)

George Mtove

2016-07-01

Full Text Available Abstract Background Despite considerable reductions in malaria achieved by scaling-up long-lasting insecticidal nets (LLINs and indoor residual spraying (IRS, maintaining sustained community protection remains operationally challenging. Increasing insecticide resistance also threatens to jeopardize the future of both strategies. Non-pyrethroid insecticide­treated wall lining (ITWL may represent an alternate or complementary control method and a potential tool to manage insecticide resistance. To date no study has demonstrated whether ITWL can reduce malaria transmission nor provide additional protection beyond the current best practice of universal coverage (UC of LLINs and prompt case management. Methods/design A two-arm cluster randomized controlled trial will be conducted in rural Tanzania to assess whether non-pyrethroid ITWL and UC of LLINs provide added protection against malaria infection in children, compared to UC of LLINs alone. Stratified randomization based on malaria prevalence will be used to select 22 village clusters per arm. All 44 clusters will receive LLINs and half will also have ITWL installed on interior house walls. Study children, aged 6 months to 11 years old, will be enrolled from each cluster and followed monthly to estimate cumulative incidence of malaria parasitaemia (primary endpoint, time to first malaria episode and prevalence of anaemia before and after intervention. Entomological inoculation rate will be estimated using indoor CDC light traps and outdoor tent traps followed by detection of Anopheles gambiae species, sporozoite infection, insecticide resistance and blood meal source. ITWL bioefficacy and durability will be monitored using WHO cone bioassays and household surveys, respectively. Social and cultural factors influencing community and household ITWL acceptability will be explored through focus-group discussions and in-depth interviews. Cost-effectiveness, compared between study arms, will be

Home-based versus mobile clinic HIV testing and counseling in rural Lesotho: a cluster-randomized trial.

Science.gov (United States)

Labhardt, Niklaus Daniel; Motlomelo, Masetsibi; Cerutti, Bernard; Pfeiffer, Karolin; Kamele, Mashaete; Hobbins, Michael A; Ehmer, Jochen

2014-12-01

The success of HIV programs relies on widely accessible HIV testing and counseling (HTC) services at health facilities as well as in the community. Home-based HTC (HB-HTC) is a popular community-based approach to reach persons who do not test at health facilities. Data comparing HB-HTC to other community-based HTC approaches are very limited. This trial compares HB-HTC to mobile clinic HTC (MC-HTC). The trial was powered to test the hypothesis of higher HTC uptake in HB-HTC campaigns than in MC-HTC campaigns. Twelve clusters were randomly allocated to HB-HTC or MC-HTC. The six clusters in the HB-HTC group received 30 1-d multi-disease campaigns (five villages per cluster) that delivered services by going door-to-door, whereas the six clusters in MC-HTC group received campaigns involving community gatherings in the 30 villages with subsequent service provision in mobile clinics. Time allocation and human resources were standardized and equal in both groups. All individuals accessing the campaigns with unknown HIV status or whose last HIV test was >12 wk ago and was negative were eligible. All outcomes were assessed at the individual level. Statistical analysis used multivariable logistic regression. Odds ratios and p-values were adjusted for gender, age, and cluster effect. Out of 3,197 participants from the 12 clusters, 2,563 (80.2%) were eligible (HB-HTC: 1,171; MC-HTC: 1,392). The results for the primary outcomes were as follows. Overall HTC uptake was higher in the HB-HTC group than in the MC-HTC group (92.5% versus 86.7%; adjusted odds ratio [aOR]: 2.06; 95% CI: 1.18-3.60; p = 0. 011). Among adolescents and adults ≥ 12 y, HTC uptake did not differ significantly between the two groups; however, in children versus 58.7%; aOR: 4.91; 95% CI: 2.41-10.0; pindividuals in the HB-HTC and in the MC-HTC arms, respectively, linked to HIV care within 1 mo after testing positive. Findings for secondary outcomes were as follows: HB-HTC reached more first-time testers

RandomSpot: A web-based tool for systematic random sampling of virtual slides.

Science.gov (United States)

Wright, Alexander I; Grabsch, Heike I; Treanor, Darren E

2015-01-01

This paper describes work presented at the Nordic Symposium on Digital Pathology 2014, Linköping, Sweden. Systematic random sampling (SRS) is a stereological tool, which provides a framework to quickly build an accurate estimation of the distribution of objects or classes within an image, whilst minimizing the number of observations required. RandomSpot is a web-based tool for SRS in stereology, which systematically places equidistant points within a given region of interest on a virtual slide. Each point can then be visually inspected by a pathologist in order to generate an unbiased sample of the distribution of classes within the tissue. Further measurements can then be derived from the distribution, such as the ratio of tumor to stroma. RandomSpot replicates the fundamental principle of traditional light microscope grid-shaped graticules, with the added benefits associated with virtual slides, such as facilitated collaboration and automated navigation between points. Once the sample points have been added to the region(s) of interest, users can download the annotations and view them locally using their virtual slide viewing software. Since its introduction, RandomSpot has been used extensively for international collaborative projects, clinical trials and independent research projects. So far, the system has been used to generate over 21,000 sample sets, and has been used to generate data for use in multiple publications, identifying significant new prognostic markers in colorectal, upper gastro-intestinal and breast cancer. Data generated using RandomSpot also has significant value for training image analysis algorithms using sample point coordinates and pathologist classifications.

Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis

Directory of Open Access Journals (Sweden)

Ladan Jamshidy

2016-01-01

Full Text Available Introduction. One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods. A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL regions by a stereomicroscope using a standard method. Results. The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion. The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.

Potts Model with Invisible Colors : Random-Cluster Representation and Pirogov–Sinai Analysis

NARCIS (Netherlands)

Enter, Aernout C.D. van; Iacobelli, Giulio; Taati, Siamak

We study a recently introduced variant of the ferromagnetic Potts model consisting of a ferromagnetic interaction among q “visible” colors along with the presence of r non-interacting “invisible” colors. We introduce a random-cluster representation for the model, for which we prove the existence of

Two stages of Kondo effect and competition between RKKY and Kondo in Gd-based intermetallic compound

Energy Technology Data Exchange (ETDEWEB)

Vaezzadeh, Mehdi [Department of Physics, K.N.Toosi University of Technology, P.O. Box 15875-4416, Tehran (Iran, Islamic Republic of)]. E-mail: mehdi@kntu.ac.ir; Yazdani, Ahmad [Tarbiat Modares University, P.O. Box 14155-4838, Tehran (Iran, Islamic Republic of); Vaezzadeh, Majid [Department of Physics, K.N.Toosi University of Technology, P.O. Box 15875-4416, Tehran (Iran, Islamic Republic of); Daneshmand, Gissoo [Department of Physics, K.N.Toosi University of Technology, P.O. Box 15875-4416, Tehran (Iran, Islamic Republic of); Kanzeghi, Ali [Department of Physics, K.N.Toosi University of Technology, P.O. Box 15875-4416, Tehran (Iran, Islamic Republic of)

2006-05-01

The magnetic behavior of Gd-based intermetallic compound (Gd{sub 2}Al{sub (1-x)}Au{sub x}) in the form of the powder and needle, is investigated. All the samples are an orthorhombic crystal structure. Only the compound with x=0.4 shows the Kondo effect (other compounds have a normal behavior). Although, for the compound in the form of powder, with x=0.4, the susceptibility measurement {chi}(T) shows two different stages. Moreover for (T>T{sub K2}) a fall of the value of {chi}(T) is observable, which indicates a weak presence of ferromagnetic phase. About the two stages of Kondo effect, we observe at the first (T{sub K1}) an increase of {chi}(T) and in the second stage (T{sub K2}) a new remarkable decrease of {chi}(T) (T{sub K1}>T{sub K2}). For the sample in the form of needles, the first stage is observable only under high magnetic field. This first stage could be corresponds to a narrow resonance between Kondo cloud and itinerant electron. The second stage, which is remarkably visible for the sample in the form of the powder, can be attribute to a complete polarization of Kondo cloud. Observation of these two Kondo stages could be due to the weak presence of RKKY contribution.

Two-Stage Centrifugal Fan

Science.gov (United States)

Converse, David

2011-01-01

Fan designs are often constrained by envelope, rotational speed, weight, and power. Aerodynamic performance and motor electrical performance are heavily influenced by rotational speed. The fan used in this work is at a practical limit for rotational speed due to motor performance characteristics, and there is no more space available in the packaging for a larger fan. The pressure rise requirements keep growing. The way to ordinarily accommodate a higher DP is to spin faster or grow the fan rotor diameter. The invention is to put two radially oriented stages on a single disk. Flow enters the first stage from the center; energy is imparted to the flow in the first stage blades, the flow is redirected some amount opposite to the direction of rotation in the fixed stators, and more energy is imparted to the flow in the second- stage blades. Without increasing either rotational speed or disk diameter, it is believed that as much as 50 percent more DP can be achieved with this design than with an ordinary, single-stage centrifugal design. This invention is useful primarily for fans having relatively low flow rates with relatively high pressure rise requirements.

Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to $k$-Clustering

OpenAIRE

Song, Zhao; Yang, Lin F.; Zhong, Peilin

2018-01-01

Sensitivity based sampling is crucial for constructing nearly-optimal coreset for $k$-means / median clustering. In this paper, we provide a novel data structure that enables sensitivity sampling over a dynamic data stream, where points from a high dimensional discrete Euclidean space can be either inserted or deleted. Based on this data structure, we provide a one-pass coreset construction for $k$-means %and M-estimator clustering using space $\\widetilde{O}(k\\mathrm{poly}(d))$ over $d$-dimen...

Two-stage single-volume exchange transfusion in severe hemolytic disease of the newborn.

Science.gov (United States)

Abbas, Wael; Attia, Nayera I; Hassanein, Sahar M A

2012-07-01

Evaluation of two-stage single-volume exchange transfusion (TSSV-ET) in decreasing the post-exchange rebound increase in serum bilirubin level, with subsequent reduction of the need for repeated exchange transfusions. The study included 104 neonates with hyperbilirubinemia needing exchange transfusion. They were randomly enrolled into two equal groups, each group comprised 52 neonates. TSSV-ET was performed for the 52 neonates and the traditional single-stage double-volume exchange transfusion (SSDV-ET) was performed to 52 neonates. TSSV-ET significantly lowered rebound serum bilirubin level (12.7 ± 1.1 mg/dL), compared to SSDV-ET (17.3 ± 1.7 mg/dL), p < 0.001. Need for repeated exchange transfusions was significantly lower in TSSV-ET group (13.5%), compared to 32.7% in SSDV-ET group, p < 0.05. No significant difference was found between the two groups as regards the morbidity (11.5% and 9.6%, respectively) and the mortality (1.9% for both groups). Two-stage single-volume exchange transfusion proved to be more effective in reducing rebound serum bilirubin level post-exchange and in decreasing the need for repeated exchange transfusions.

Symptom Clusters in People Living with HIV Attending Five Palliative Care Facilities in Two Sub-Saharan African Countries: A Hierarchical Cluster Analysis.

Science.gov (United States)

Moens, Katrien; Siegert, Richard J; Taylor, Steve; Namisango, Eve; Harding, Richard

2015-01-01

Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries. Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores. Among the sample (N=217) the mean age was 36.5 (SD 9.0), 73.2% were female, and 49.1% were on antiretroviral therapy (ART). The cluster analysis produced five symptom clusters identified as: 1) dermatological; 2) generalised anxiety and elimination; 3) social and image; 4) persistently present; and 5) a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, ppeople living with HIV with longitudinally collected symptom data to test cluster stability and identify common symptom trajectories is recommended.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Directory of Open Access Journals (Sweden)

Can Tolga

2009-09-01

Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

Multi-stage pulsed laser deposition of aluminum nitride at different temperatures

Energy Technology Data Exchange (ETDEWEB)

Duta, L. [National Institute for Lasers, Plasma, and Radiation Physics, 409 Atomistilor Street, 077125 Magurele (Romania); Stan, G.E. [National Institute of Materials Physics, 105 bis Atomistilor Street, 077125 Magurele (Romania); Stroescu, H.; Gartner, M.; Anastasescu, M. [Institute of Physical Chemistry “Ilie Murgulescu”, Romanian Academy, 202 Splaiul Independentei, 060021 Bucharest (Romania); Fogarassy, Zs. [Research Institute for Technical Physics and Materials Science, Hungarian Academy of Sciences, Konkoly Thege Miklos u. 29-33, H-1121 Budapest (Hungary); Mihailescu, N. [National Institute for Lasers, Plasma, and Radiation Physics, 409 Atomistilor Street, 077125 Magurele (Romania); Szekeres, A., E-mail: szekeres@issp.bas.bg [Institute of Solid State Physics, Bulgarian Academy of Sciences, Tzarigradsko Chaussee 72, Sofia 1784 (Bulgaria); Bakalova, S. [Institute of Solid State Physics, Bulgarian Academy of Sciences, Tzarigradsko Chaussee 72, Sofia 1784 (Bulgaria); Mihailescu, I.N., E-mail: ion.mihailescu@inflpr.ro [National Institute for Lasers, Plasma, and Radiation Physics, 409 Atomistilor Street, 077125 Magurele (Romania)

2016-06-30

Highlights: • Multi-stage pulsed laser deposition of aluminum nitride at different temperatures. • 800 °C seed film boosts the next growth of crystalline structures at lower temperature. • Two-stage deposited AlN samples exhibit randomly oriented wurtzite structures. • Band gap energy values increase with deposition temperature. • Correlation was observed between single- and multi-stage AlN films. - Abstract: We report on multi-stage pulsed laser deposition of aluminum nitride (AlN) on Si (1 0 0) wafers, at different temperatures. The first stage of deposition was carried out at 800 °C, the optimum temperature for AlN crystallization. In the second stage, the deposition was conducted at lower temperatures (room temperature, 350 °C or 450 °C), in ambient Nitrogen, at 0.1 Pa. The synthesized structures were analyzed by grazing incidence X-ray diffraction (GIXRD), transmission electron microscopy (TEM), atomic force microscopy and spectroscopic ellipsometry (SE). GIXRD measurements indicated that the two-stage deposited AlN samples exhibited a randomly oriented wurtzite structure with nanosized crystallites. The peaks were shifted to larger angles, indicative for smaller inter-planar distances. Remarkably, TEM images demonstrated that the high-temperature AlN “seed” layers (800 °C) promoted the growth of poly-crystalline AlN structures at lower deposition temperatures. When increasing the deposition temperature, the surface roughness of the samples exhibited values in the range of 0.4–2.3 nm. SE analyses showed structures which yield band gap values within the range of 4.0–5.7 eV. A correlation between the results of single- and multi-stage AlN depositions was observed.

Structuring communication relationships for interprofessional teamwork (SCRIPT: a cluster randomized controlled trial

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Kenaszchuk Chris

2007-09-01

Full Text Available Abstract Background Despite a burgeoning interest in using interprofessional approaches to promote effective collaboration in health care, systematic reviews find scant evidence of benefit. This protocol describes the first cluster randomized controlled trial (RCT to design and evaluate an intervention intended to improve interprofessional collaborative communication and patient-centred care. Objectives The objective is to evaluate the effects of a four-component, hospital-based staff communication protocol designed to promote collaborative communication between healthcare professionals and enhance patient-centred care. Methods The study is a multi-centre mixed-methods cluster randomized controlled trial involving twenty clinical teaching teams (CTTs in general internal medicine (GIM divisions of five Toronto tertiary-care hospitals. CTTs will be randomly assigned either to receive an intervention designed to improve interprofessional collaborative communication, or to continue usual communication practices. Non-participant naturalistic observation, shadowing, and semi-structured, qualitative interviews were conducted to explore existing patterns of interprofessional collaboration in the CTTs, and to support intervention development. Interviews and shadowing will continue during intervention delivery in order to document interactions between the intervention settings and adopters, and changes in interprofessional communication. The primary outcome is the rate of unplanned hospital readmission. Secondary outcomes are length of stay (LOS; adherence to evidence-based prescription drug therapy; patients' satisfaction with care; self-report surveys of CTT staff perceptions of interprofessional collaboration; and frequency of calls to paging devices. Outcomes will be compared on an intention-to-treat basis using adjustment methods appropriate for data from a cluster randomized design. Discussion Pre-intervention qualitative analysis revealed that a

AGN Clustering in the BAT Sample

Science.gov (United States)

Powell, Meredith; Cappelluti, Nico; Urry, Meg; Koss, Michael; BASS Team

2018-01-01

We characterize the environments of local growing supermassive black holes by measuring the clustering of AGN in the Swift-BAT Spectroscopic Survey (BASS). With 548 AGN in the redshift range 0.012MASS galaxies, we constrain the halo occupation distribution (HOD) of the full sample with unprecedented sensitivity, as well as in bins of obscuration with matched luminosity distributions. In doing so, we find that AGN tend to reside in galaxy groups, agreeing with previous studies of AGN throughout a large range of luminosity and redshift. We also find evidence that obscured AGN tend to reside in denser environments than unobscured AGN.

The Effectiveness of Healthy Start Home Visit Program: Cluster Randomized Controlled Trial

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Leung, Cynthia; Tsang, Sandra; Heung, Kitty

2015-01-01

Purpose: The study reported the effectiveness of a home visit program for disadvantaged Chinese parents with preschool children, using cluster randomized controlled trial design. Method: Participants included 191 parents and their children from 24 preschools, with 84 dyads (12 preschools) in the intervention group and 107 dyads (12 preschools) in…

Effect of Reassuring Information About Musculoskeletal and Mental Health Complaints at the Workplace: A Cluster Randomized Trial of the atWork Intervention.

Science.gov (United States)

Johnsen, Tone Langjordet; Eriksen, Hege Randi; Baste, Valborg; Indahl, Aage; Odeen, Magnus; Tveito, Torill Helene

2018-05-21

Purpose The purpose of this study was to investigate the possible difference between the Modified atWork intervention (MAW) and the Original atWork intervention (OAW) on sick leave and other health related outcomes. atWork is a group intervention using the workplace as an arena for distribution of evidence-based knowledge about musculoskeletal and mental health complaints. Methods A cluster randomized controlled trial with 93 kindergartens, comprising a total of 1011 employees, was conducted. Kindergartens were stratified by county and size and randomly allocated to MAW (45 clusters, 324 respondents) or OAW (48 clusters, 313 respondents). The randomization and intervention allocation processes were concealed. There was no blinding to group allocation. Primary outcome was register data on sick leave at cluster level. Secondary outcomes were health complaints, job satisfaction, social support, coping, and beliefs about musculoskeletal and mental health complaints, measured at the individual level. Results The MAW group reduced sick leave by 5.7% during the intervention year, while the OAW group had a 7.5% increase. Overall, the changes were not statistically significant, and no difference was detected between groups, based on 45 and 47 kindergartens. Compared to the OAW group, the MAW group had a smaller reduction for two of the statements concerning faulty beliefs about back pain, but believed less in the hereditary nature of depression. Conclusions The MAW did not have a different effect on sick leave at cluster level compared to the OAW. Trial registration https://Clinicaltrials.gov/ : NCT02396797. Registered March 23th, 2015.

Long term effectiveness on prescribing of two multifaceted educational interventions: results of two large scale randomized cluster trials.

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Nicola Magrini

Full Text Available INTRODUCTION: Information on benefits and risks of drugs is a key element affecting doctors' prescribing decisions. Outreach visits promoting independent information have proved moderately effective in changing prescribing behaviours. OBJECTIVES: Testing the short and long-term effectiveness on general practitioners' prescribing of small groups meetings led by pharmacists. METHODS: Two cluster open randomised controlled trials (RCTs were carried out in a large scale NHS setting. Ad hoc prepared evidence based material were used considering a therapeutic area approach--TEA, with information materials on osteoporosis or prostatic hyperplasia--and a single drug oriented approach--SIDRO, with information materials on me-too drugs of 2 different classes: barnidipine or prulifloxacin. In each study, all 115 Primary Care Groups in a Northern Italy area (2.2 million inhabitants, 1737 general practitioners were randomised to educational small groups meetings, in which available evidence was provided together with drug utilization data and clinical scenarios. Main outcomes were changes in the six-months prescription of targeted drugs. Longer term results (24 and 48 months were also evaluated. RESULTS: In the TEA trial, one of the four primary outcomes showed a reduction (prescription of alfuzosin compared to tamsulosin and terazosin in benign prostatic hyperplasia: prescribing ratio -8.5%, p = 0.03. Another primary outcome (prescription of risedronate showed a reduction at 24 and 48 months (-7.6%, p = 0.02; and -9,8%, p = 0.03, but not at six months (-5.1%, p = 0.36. In the SIDRO trial both primary outcomes showed a statistically significant reduction (prescription of barnidipine -9.8%, p = 0.02; prescription of prulifloxacin -11.1%, p = 0.04, which persisted or increased over time. INTERPRETATION: These two cluster RCTs showed the large scale feasibility of a complex educational program in a NHS setting, and its potentially

Relationship between damage clustering and mortality in systemic lupus erythematosus in early and late stages of the disease: cluster analyses in a large cohort from the Spanish Society of Rheumatology Lupus Registry.

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Pego-Reigosa, José María; Lois-Iglesias, Ana; Rúa-Figueroa, Íñigo; Galindo, María; Calvo-Alén, Jaime; de Uña-Álvarez, Jacobo; Balboa-Barreiro, Vanessa; Ibáñez Ruan, Jesús; Olivé, Alejandro; Rodríguez-Gómez, Manuel; Fernández Nebro, Antonio; Andrés, Mariano; Erausquin, Celia; Tomero, Eva; Horcada Rubio, Loreto; Uriarte Isacelaya, Esther; Freire, Mercedes; Montilla, Carlos; Sánchez-Atrio, Ana I; Santos-Soler, Gregorio; Zea, Antonio; Díez, Elvira; Narváez, Javier; Blanco-Alonso, Ricardo; Silva-Fernández, Lucía; Ruiz-Lucea, María Esther; Fernández-Castro, Mónica; Hernández-Beriain, José Ángel; Gantes-Mora, Marian; Hernández-Cruz, Blanca; Pérez-Venegas, José; Pecondón-Español, Ángela; Marras Fernández-Cid, Carlos; Ibáñez-Barcelo, Mónica; Bonilla, Gema; Torrente-Segarra, Vicenç; Castellví, Iván; Alegre, Juan José; Calvet, Joan; Marenco de la Fuente, José Luis; Raya, Enrique; Vázquez-Rodríguez, Tomás Ramón; Quevedo-Vila, Víctor; Muñoz-Fernández, Santiago; Otón, Teresa; Rahman, Anisur; López-Longo, Francisco Javier

2016-07-01

To identify patterns (clusters) of damage manifestations within a large cohort of SLE patients and evaluate the potential association of these clusters with a higher risk of mortality. This is a multicentre, descriptive, cross-sectional study of a cohort of 3656 SLE patients from the Spanish Society of Rheumatology Lupus Registry. Organ damage was ascertained using the Systemic Lupus International Collaborating Clinics Damage Index. Using cluster analysis, groups of patients with similar patterns of damage manifestations were identified. Then, overall clusters were compared as well as the subgroup of patients within every cluster with disease duration shorter than 5 years. Three damage clusters were identified. Cluster 1 (80.6% of patients) presented a lower amount of individuals with damage (23.2 vs 100% in clusters 2 and 3, P Cluster 2 (11.4% of patients) was characterized by musculoskeletal damage in all patients. Cluster 3 (8.0% of patients) was the only group with cardiovascular damage, and this was present in all patients. The overall mortality rate of patients in clusters 2 and 3 was higher than that in cluster 1 (P clusters. Both in early and late stages of the disease, there was a significant association of these clusters with an increased risk of mortality. Physicians should pay special attention to the early prevention of damage in these two systems. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A three-stage strategy for optimal price offering by a retailer based on clustering techniques

International Nuclear Information System (INIS)

Mahmoudi-Kohan, N.; Shayesteh, E.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

2010-01-01

In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

A three-stage strategy for optimal price offering by a retailer based on clustering techniques

Energy Technology Data Exchange (ETDEWEB)

Mahmoudi-Kohan, N.; Shayesteh, E. [Islamic Azad University (Garmsar Branch), Garmsar (Iran); Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K. [Tarbiat Modares University, Tehran (Iran)

2010-12-15

In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

Analysis of Aspects of Innovation in a Brazilian Cluster

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Adriana Valélia Saraceni

2012-09-01

Full Text Available Innovation through clustering has become very important on the increased significance that interaction represents on innovation and learning process concept. This study aims to identify whereas a case analysis on innovation process in a cluster represents on the learning process. Therefore, this study is developed in two stages. First, we used a preliminary case study verifying a cluster innovation analysis and it Innovation Index, for further, exploring a combined body of theory and practice. Further, the second stage is developed by exploring the learning process concept. Both stages allowed us building a theory model for the learning process development in clusters. The main results of the model development come up with a mechanism of improvement implementation on clusters when case studies are applied.

Complementary feeding: a Global Network cluster randomized controlled trial

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Pasha Omrana

2011-01-01

Full Text Available Abstract Background Inadequate and inappropriate complementary feeding are major factors contributing to excess morbidity and mortality in young children in low resource settings. Animal source foods in particular are cited as essential to achieve micronutrient requirements. The efficacy of the recommendation for regular meat consumption, however, has not been systematically evaluated. Methods/Design A cluster randomized efficacy trial was designed to test the hypothesis that 12 months of daily intake of beef added as a complementary food would result in greater linear growth velocity than a micronutrient fortified equi-caloric rice-soy cereal supplement. The study is being conducted in 4 sites of the Global Network for Women's and Children's Health Research located in Guatemala, Pakistan, Democratic Republic of the Congo (DRC and Zambia in communities with toddler stunting rates of at least 20%. Five clusters per country were randomized to each of the food arms, with 30 infants in each cluster. The daily meat or cereal supplement was delivered to the home by community coordinators, starting when the infants were 6 months of age and continuing through 18 months. All participating mothers received nutrition education messages to enhance complementary feeding practices delivered by study coordinators and through posters at the local health center. Outcome measures, obtained at 6, 9, 12, and 18 months by a separate assessment team, included anthropometry; dietary variety and diversity scores; biomarkers of iron, zinc and Vitamin B12 status (18 months; neurocognitive development (12 and 18 months; and incidence of infectious morbidity throughout the trial. The trial was supervised by a trial steering committee, and an independent data monitoring committee provided oversight for the safety and conduct of the trial. Discussion Findings from this trial will test the efficacy of daily intake of meat commencing at age 6 months and, if beneficial, will

Cluster Analysis of the Yale Global Tic Severity Scale (YGTSS): Symptom Dimensions and Clinical Correlates in an Outpatient Youth Sample

OpenAIRE

Kircanski, Katharina; Woods, Douglas W.; Chang, Susanna W.; Ricketts, Emily J.; Piacentini, John C.

2010-01-01

Tic disorders are heterogeneous, with symptoms varying widely both within and across patients. Exploration of symptom clusters may aid in the identification of symptom dimensions of empirical and treatment import. This article presents the results of two studies investigating tic symptom clusters using a sample of 99 youth (M age = 10.7, 81% male, 77% Caucasian) diagnosed with a primary tic disorder (Tourette?s disorder or chronic tic disorder), across two university-based outpatient clinics ...

Cluster Analysis of the Yale Global Tic Severity Scale (YGTSS): Symptom Dimensions and Clinical Correlates in an Outpatient Youth Sample

Science.gov (United States)

Kircanski, Katharina; Woods, Douglas W.; Chang, Susanna W.; Ricketts, Emily J.; Piacentini, John C.

2010-01-01

Tic disorders are heterogeneous, with symptoms varying widely both within and across patients. Exploration of symptom clusters may aid in the identification of symptom dimensions of empirical and treatment import. This article presents the results of two studies investigating tic symptom clusters using a sample of 99 youth (M age = 10.7, 81% male,…

Efficacy of a workplace osteoporosis prevention intervention: a cluster randomized trial

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Ai May Tan

2016-08-01

Full Text Available Abstract Background Osteoporosis is a debilitating disease. Adequate calcium consumption and physical activity are the two major modifiable risk factors. This paper describes the major outcomes and efficacy of a workplace-based targeted behaviour change intervention to improve the dietary and physical activity behaviours of working women in sedentary occupations in Singapore. Methods A cluster-randomized design was used, comparing the efficacy of a tailored intervention to standard care. Workplaces were the units of randomization and intervention. Sixteen workplaces were recruited from a pool of 97, and randomly assigned to intervention and control arms (eight workplaces in each. Women meeting specified inclusion criteria were then recruited to participate. Workplaces in the intervention arm received three participatory workshops and organization-wide educational activities. Workplaces in the control/standard care arm received print resources. Outcome measures were calcium intake (milligrams/day and physical activity level (duration: minutes/week, measured at baseline, 4 weeks and 6 months post intervention. Adjusted cluster-level analyses were conducted comparing changes in intervention versus control groups, following intention-to-treat principles and CONSORT guidelines. Results Workplaces in the intervention group reported a significantly greater increase in calcium intake and duration of load-bearing moderate to vigorous physical activity (MVPA compared with the standard care control group. Four weeks after intervention, the difference in adjusted mean calcium intake was 343.2 mg/day (95 % CI = 337.4 to 349.0, p < .0005 and the difference in adjusted mean load-bearing MVPA was 55.6 min/week (95 % CI = 54.5 to 56.6, p < .0005. Six months post intervention, the mean differences attenuated slightly to 290.5 mg/day (95 % CI = 285.3 to 295.7, p < .0005 and 50.9 min/week (95 % CI =49.3 to 52.6, p < .0005

Informing resource-poor populations and the delivery of entitled health and social services in rural India: a cluster randomized controlled trial.

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Pandey, Priyanka; Sehgal, Ashwini R; Riboud, Michelle; Levine, David; Goyal, Madhav

2007-10-24

A lack of awareness about entitled health and social services may contribute to poor delivery of such services in developing countries, especially among individuals of low socioeconomic status. To determine the impact of informing resource-poor rural populations about entitled services. Community-based, cluster randomized controlled trial conducted from May 2004 to May 2005 in 105 randomly selected village clusters in Uttar Pradesh state in India. Households (548 intervention and 497 control) were selected by a systematic sampling design, including both low-caste and mid- to high-caste households. Four to 6 public meetings were held in each intervention village cluster to disseminate information on entitled health services, entitled education services, and village governance requirements. No intervention took place in control village clusters. Visits by nurse midwife; prenatal examinations, tetanus vaccinations, and prenatal supplements received by pregnant women; vaccinations received by infants; excess school fees charged; occurrence of village council meetings; and development work in villages. At baseline, there were no significant differences in self-reported delivery of health and social services. After 1 year, intervention villagers reported better delivery of several services compared with control villagers: in a multivariate analysis, 30% more prenatal examinations (95% confidence interval [CI], 17%-43%; P India about entitled services enhanced the delivery of health and social services among both low- and mid- to high-caste households. Interventions that emphasize educating resource-poor populations about entitled services may improve the delivery of such services. clinicaltrials.gov Identifier: NCT00421291.

Creel survey sampling designs for estimating effort in short-duration Chinook salmon fisheries

Science.gov (United States)

McCormick, Joshua L.; Quist, Michael C.; Schill, Daniel J.

2013-01-01

Chinook Salmon Oncorhynchus tshawytscha sport fisheries in the Columbia River basin are commonly monitored using roving creel survey designs and require precise, unbiased catch estimates. The objective of this study was to examine the relative bias and precision of total catch estimates using various sampling designs to estimate angling effort under the assumption that mean catch rate was known. We obtained information on angling populations based on direct visual observations of portions of Chinook Salmon fisheries in three Idaho river systems over a 23-d period. Based on the angling population, Monte Carlo simulations were used to evaluate the properties of effort and catch estimates for each sampling design. All sampling designs evaluated were relatively unbiased. Systematic random sampling (SYS) resulted in the most precise estimates. The SYS and simple random sampling designs had mean square error (MSE) estimates that were generally half of those observed with cluster sampling designs. The SYS design was more efficient (i.e., higher accuracy per unit cost) than a two-cluster design. Increasing the number of clusters available for sampling within a day decreased the MSE of estimates of daily angling effort, but the MSE of total catch estimates was variable depending on the fishery. The results of our simulations provide guidelines on the relative influence of sample sizes and sampling designs on parameters of interest in short-duration Chinook Salmon fisheries.

Applications of Cluster Analysis to the Creation of Perfectionism Profiles: A Comparison of two Clustering Approaches

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Jocelyn H Bolin

2014-04-01

Full Text Available Although traditional clustering methods (e.g., K-means have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

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Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

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Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Clustering algorithm in initialization of multi-hop wireless sensor networks

NARCIS (Netherlands)

Guo, Peng; Tao, Jiang; Zhang, Kui; Chen, Hsiao-Hwa

2009-01-01

In most application scenarios of wireless sensor networks (WSN), sensor nodes are usually deployed randomly and do not have any knowledge about the network environment or even their ID's at the initial stage of their operations. In this paper, we address the clustering problems with a newly deployed

Directional clustering in highest energy cosmic rays

International Nuclear Information System (INIS)

Goldberg, Haim; Weiler, Thomas J.

2001-01-01

An unexpected degree of small-scale clustering is observed in highest-energy cosmic ray events. Some directional clustering can be expected due to purely statistical fluctuations for sources distributed randomly in the sky. This creates a background for events originating in clustered sources. We derive analytic formulas to estimate the probability of random cluster configurations, and use these formulas to study the strong potential of the HiRes, Auger, Telescope Array and EUSO-OWL-AirWatch facilities for deciding whether any observed clustering is most likely due to nonrandom sources. For a detailed comparison to data, our analytical approach cannot compete with Monte Carlo simulations, including experimental systematics. However, our derived formulas do offer two advantages: (i) easy assessment of the significance of any observed clustering, and most importantly, (ii) an explicit dependence of cluster probabilities on the chosen angular bin size

Randomized branch sampling to estimatefruit production in Pecan trees cv. ‘Barton’

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Filemom Manoel Mokochinski

Full Text Available ABSTRACT: Sampling techniques to quantify the production of fruits are still very scarce and create a gap in crop development research. This study was conducted in a rural property in the county of Cachoeira do Sul - RS to estimate the efficiency of randomized branch sampling (RBS in quantifying the production of pecan fruit at three different ages (5,7 and 10 years. Two selection techniques were tested: the probability proportional to the diameter (PPD and the uniform probability (UP techniques, which were performed on nine trees, three from each age and randomly chosen. The RBS underestimated fruit production for all ages, and its main drawback was the high sampling error (125.17% - PPD and 111.04% - UP. The UP was regarded as more efficient than the PPD, though both techniques estimated similar production and similar experimental errors. In conclusion, we reported that branch sampling was inaccurate for this case study, requiring new studies to produce estimates with smaller sampling error.

Genetic diversity of two Tunisian sheep breeds using random ...

African Journals Online (AJOL)

Random amplified polymorphic DNA (RAPD) markers were used to study genetic diversity and population structure in six sheep populations belonging to two native Tunisian breeds (the Barbarine and the Western thin tail). A total of 96 samples were typed using eight RAPD primers. 62 bands were scored, of which 44 ...

Protogalaxy interactions in newly formed clusters: Galaxy luminosities, colors, and intergalactic gas

International Nuclear Information System (INIS)

Silk, J.

1978-01-01

The role of protogalaxy interactions in galactic evolution is studied during the formation of galaxy clusters. In the early stages of the collapse, coalescent encounters of protogalaxies lead to the development of a galactic luminosity function. Once galaxies acquire appreciable random motions, mutual collisions between galaxies in rich clusters will trigger the collapse of interstellar clouds to form stars. This provides both a source for enriched intracluster gas and an interpretation of the correlation between luminosity and color for cluster elliptical galaxies. Other observational consequences that are considered include optical, X-ray, and diffuse nonthermal radio emission from newly formed clusters of galaxies

A Two-Stage Framework for 3D Face Reconstruction from RGBD Images.

Science.gov (United States)

Wang, Kangkan; Wang, Xianwang; Pan, Zhigeng; Liu, Kai

2014-08-01

This paper proposes a new approach for 3D face reconstruction with RGBD images from an inexpensive commodity sensor. The challenges we face are: 1) substantial random noise and corruption are present in low-resolution depth maps; and 2) there is high degree of variability in pose and face expression. We develop a novel two-stage algorithm that effectively maps low-quality depth maps to realistic face models. Each stage is targeted toward a certain type of noise. The first stage extracts sparse errors from depth patches through the data-driven local sparse coding, while the second stage smooths noise on the boundaries between patches and reconstructs the global shape by combining local shapes using our template-based surface refinement. Our approach does not require any markers or user interaction. We perform quantitative and qualitative evaluations on both synthetic and real test sets. Experimental results show that the proposed approach is able to produce high-resolution 3D face models with high accuracy, even if inputs are of low quality, and have large variations in viewpoint and face expression.

Evaluation of primary immunization coverage of infants under universal immunization programme in an urban area of bangalore city using cluster sampling and lot quality assurance sampling techniques.

Science.gov (United States)

K, Punith; K, Lalitha; G, Suman; Bs, Pradeep; Kumar K, Jayanth

2008-07-01

Is LQAS technique better than cluster sampling technique in terms of resources to evaluate the immunization coverage in an urban area? To assess and compare the lot quality assurance sampling against cluster sampling in the evaluation of primary immunization coverage. Population-based cross-sectional study. Areas under Mathikere Urban Health Center. Children aged 12 months to 23 months. 220 in cluster sampling, 76 in lot quality assurance sampling. Percentages and Proportions, Chi square Test. (1) Using cluster sampling, the percentage of completely immunized, partially immunized and unimmunized children were 84.09%, 14.09% and 1.82%, respectively. With lot quality assurance sampling, it was 92.11%, 6.58% and 1.31%, respectively. (2) Immunization coverage levels as evaluated by cluster sampling technique were not statistically different from the coverage value as obtained by lot quality assurance sampling techniques. Considering the time and resources required, it was found that lot quality assurance sampling is a better technique in evaluating the primary immunization coverage in urban area.

The Orientation of Gastric Biopsy Samples Improves the Inter-observer Agreement of the OLGA Staging System.

Science.gov (United States)

Cotruta, Bogdan; Gheorghe, Cristian; Iacob, Razvan; Dumbrava, Mona; Radu, Cristina; Bancila, Ion; Becheanu, Gabriel

2017-12-01

Evaluation of severity and extension of gastric atrophy and intestinal metaplasia is recommended to identify subjects with a high risk for gastric cancer. The inter-observer agreement for the assessment of gastric atrophy is reported to be low. The aim of the study was to evaluate the inter-observer agreement for the assessment of severity and extension of gastric atrophy using oriented and unoriented gastric biopsy samples. Furthermore, the quality of biopsy specimens in oriented and unoriented samples was analyzed. A total of 35 subjects with dyspeptic symptoms addressed for gastrointestinal endoscopy that agreed to enter the study were prospectively enrolled. The OLGA/OLGIM gastric biopsies protocol was used. From each subject two sets of biopsies were obtained (four from the antrum, two oriented and two unoriented, two from the gastric incisure, one oriented and one unoriented, four from the gastric body, two oriented and two unoriented). The orientation of the biopsy samples was completed using nitrocellulose filters (Endokit®, BioOptica, Milan, Italy). The samples were blindly examined by two experienced pathologists. Inter-observer agreement was evaluated using kappa statistic for inter-rater agreement. The quality of histopathology specimens taking into account the identification of lamina propria was analyzed in oriented vs. unoriented samples. The samples with detectable lamina propria mucosae were defined as good quality specimens. Categorical data was analyzed using chi-square test and a two-sided p value <0.05 was considered statistically significant. A total of 350 biopsy samples were analyzed (175 oriented / 175 unoriented). The kappa index values for oriented/unoriented OLGA 0/I/II/III and IV stages have been 0.62/0.13, 0.70/0.20, 0.61/0.06, 0.62/0.46, and 0.77/0.50, respectively. For OLGIM 0/I/II/III stages the kappa index values for oriented/unoriented samples were 0.83/0.83, 0.88/0.89, 0.70/0.88 and 0.83/1, respectively. No case of OLGIM IV

A new combined strategy to implement a community occupational therapy intervention: designing a cluster randomized controlled trial

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Adang Eddy

2011-03-01

Full Text Available Abstract Background Even effective interventions for people with dementia and their caregivers require specific implementation efforts. A pilot study showed that the highly effective community occupational therapy in dementia (COTiD program was not implemented optimally due to various barriers. To decrease these barriers and make implementation of the program more effective a combined implementation (CI strategy was developed. In our study we will compare the effectiveness of this CI strategy with the usual educational (ED strategy. Methods In this cluster randomized, single-blinded, controlled trial, each cluster consists of at least two occupational therapists, a manager, and a physician working at Dutch healthcare organizations that deliver community occupational therapy. Forty-five clusters, stratified by healthcare setting (nursing home, hospital, mental health service, have been allocated randomly to either the intervention group (CI strategy or the control group (ED strategy. The study population consists of the professionals included in each cluster and community-dwelling people with dementia and their caregivers. The primary outcome measures are the use of community OT, the adherence of OTs to the COTiD program, and the cost effectiveness of implementing the COTiD program in outpatient care. Secondary outcome measures are patient and caregiver outcomes and knowledge of managers, physicians and OTs about the COTiD program. Discussion Implementation research is fairly new in the field of occupational therapy, making this a unique study. This study does not only evaluate the effects of the CI-strategy on professionals, but also the effects of professionals' degree of implementation on client and caregiver outcomes. Clinical trials registration NCT01117285

Method for detecting clusters of possible uranium deposits

International Nuclear Information System (INIS)

Conover, W.J.; Bement, T.R.; Iman, R.L.

1978-01-01

When a two-dimensional map contains points that appear to be scattered somewhat at random, a question that often arises is whether groups of points that appear to cluster are merely exhibiting ordinary behavior, which one can expect with any random distribution of points, or whether the clusters are too pronounced to be attributable to chance alone. A method for detecting clusters along a straight line is applied to the two-dimensional map of 214 Bi anomalies observed as part of the National Uranium Resource Evaluation Program in the Lubbock, Texas, region. Some exact probabilities associated with this method are computed and compared with two approximate methods. The two methods for approximating probabilities work well in the cases examined and can be used when it is not feasible to obtain the exact probabilities

A random spatial sampling method in a rural developing nation

Science.gov (United States)

Michelle C. Kondo; Kent D.W. Bream; Frances K. Barg; Charles C. Branas

2014-01-01

Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population. We describe a stratified random sampling method...

A Cluster-Randomized Trial of Restorative Practices: An Illustration to Spur High-Quality Research and Evaluation.

Science.gov (United States)

Acosta, Joie D; Chinman, Matthew; Ebener, Patricia; Phillips, Andrea; Xenakis, Lea; Malone, Patrick S

2016-01-01

Restorative Practices in schools lack rigorous evaluation studies. As an example of rigorous school-based research, this paper describes the first randomized control trial of restorative practices to date, the Study of Restorative Practices. It is a 5-year, cluster-randomized controlled trial (RCT) of the Restorative Practices Intervention (RPI) in 14 middle schools in Maine to assess whether RPI impacts both positive developmental outcomes and problem behaviors and whether the effects persist during the transition from middle to high school. The two-year RPI intervention began in the 2014-2015 school year. The study's rationale and theoretical concerns are discussed along with methodological concerns including teacher professional development. The theoretical rationale and description of the methods from this study may be useful to others conducting rigorous research and evaluation in this area.

Two-Stage Performance Engineering of Container-based Virtualization

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Zheng Li

2018-02-01

Full Text Available Cloud computing has become a compelling paradigm built on compute and storage virtualization technologies. The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Given the recent booming of the container ecosystem, the container-based virtualization starts receiving more attention for being a promising alternative. Although the container technologies are generally considered to be lightweight, no virtualization solution is ideally resource-free, and the corresponding performance overheads will lead to negative impacts on the quality of Cloud services. To facilitate understanding container technologies from the performance engineering’s perspective, we conducted two-stage performance investigations into Docker containers as a concrete example. At the first stage, we used a physical machine with “just-enough” resource as a baseline to investigate the performance overhead of a standalone Docker container against a standalone virtual machine (VM. With findings contrary to the related work, our evaluation results show that the virtualization’s performance overhead could vary not only on a feature-by-feature basis but also on a job-to-job basis. Moreover, the hypervisor-based technology does not come with higher performance overhead in every case. For example, Docker containers particularly exhibit lower QoS in terms of storage transaction speed. At the ongoing second stage, we employed a physical machine with “fair-enough” resource to implement a container-based MapReduce application and try to optimize its performance. In fact, this machine failed in affording VM-based MapReduce clusters in the same scale. The performance tuning results show that the effects of different optimization strategies could largely be related to the data characteristics. For example, LZO compression can bring the most significant performance improvement when dealing with text data in our case.

The random cluster model and a new integration identity

International Nuclear Information System (INIS)

Chen, L C; Wu, F Y

2005-01-01

We evaluate the free energy of the random cluster model at its critical point for 0 -1 (√q/2) is a rational number. As a by-product, our consideration leads to a closed-form evaluation of the integral 1/(4π 2 ) ∫ 0 2π dΘ ∫ 0 2π dΦ ln[A+B+C - AcosΘ - BcosΦ - Ccos(Θ+Φ)] = -ln(2S) + (2/π)[Ti 2 (AS) + Ti 2 (BS) + Ti 2 (CS)], which arises in lattice statistics, where A, B, C ≥ 0 and S=1/√(AB + BC + CA)

A Cluster-Randomized Trial of Restorative Practices: An Illustration to Spur High-Quality Research and Evaluation

Science.gov (United States)

Acosta, Joie D.; Chinman, Matthew; Ebener, Patricia; Phillips, Andrea; Xenakis, Lea; Malone, Patrick S.

2016-01-01

Restorative practices in schools lack rigorous evaluation studies. As an example of rigorous school-based research, this article describes the first randomized control trial of restorative practices to date, the Study of Restorative Practices. It is a 5-year, cluster-randomized controlled trial (RCT) of the Restorative Practices Intervention (RPI)…

Unsupervised classification of multivariate geostatistical data: Two algorithms

Science.gov (United States)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

The Infant Feeding Activity and Nutrition Trial (INFANT an early intervention to prevent childhood obesity: Cluster-randomised controlled trial

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Campbell Karen

2008-03-01

Full Text Available Abstract Background Multiple factors combine to support a compelling case for interventions that target the development of obesity-promoting behaviours (poor diet, low physical activity and high sedentary behaviour from their inception. These factors include the rapidly increasing prevalence of fatness throughout childhood, the instigation of obesity-promoting behaviours in infancy, and the tracking of these behaviours from childhood through to adolescence and adulthood. The Infant Feeding Activity and Nutrition Trial (INFANT aims to determine the effectiveness of an early childhood obesity prevention intervention delivered to first-time parents. The intervention, conducted with parents over the infant's first 18 months of life, will use existing social networks (first-time parent's groups and an anticipatory guidance framework focusing on parenting skills which support the development of positive diet and physical activity behaviours, and reduced sedentary behaviours in infancy. Methods/Design This cluster-randomised controlled trial, with first-time parent groups as the unit of randomisation, will be conducted with a sample of 600 first-time parents and their newborn children who attend the first-time parents' group at Maternal and Child Health Centres. Using a two-stage sampling process, local government areas in Victoria, Australia will be randomly selected at the first stage. At the second stage, a proportional sample of first-time parent groups within selected local government areas will be randomly selected and invited to participate. Informed consent will be obtained and groups will then be randomly allocated to the intervention or control group. Discussion The early years hold promise as a time in which obesity prevention may be most effective. To our knowledge this will be the first randomised trial internationally to demonstrate whether an early health promotion program delivered to first-time parents in their existing social groups

An optimal design of cluster spacing intervals for staged fracturing in horizontal shale gas wells based on the optimal SRVs

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Lan Ren

2017-09-01

Full Text Available When horizontal well staged cluster fracturing is applied in shale gas reservoirs, the cluster spacing is essential to fracturing performance. If the cluster spacing is too small, the stimulated area between major fractures will be overlapped, and the efficiency of fracturing stimulation will be decreased. If the cluster spacing is too large, the area between major fractures cannot be stimulated completely and reservoir recovery extent will be adversely impacted. At present, cluster spacing design is mainly based on the static model with the potential reservoir stimulation area as the target, and there is no cluster spacing design method in accordance with the actual fracturing process and targets dynamic stimulated reservoir volume (SRV. In this paper, a dynamic SRV calculation model for cluster fracture propagation was established by analyzing the coupling mechanisms among fracture propagation, fracturing fluid loss and stress. Then, the cluster spacing was optimized to reach the target of the optimal SRVs. This model was applied for validation on site in the Jiaoshiba shale gasfield in the Fuling area of the Sichuan Basin. The key geological engineering parameters influencing the optimal cluster spacing intervals were analyzed. The reference charts for the optimal cluster spacing design were prepared based on the geological characteristics of south and north blocks in the Jiaoshiba shale gasfield. It is concluded that the cluster spacing optimal design method proposed in this paper is of great significance in overcoming the blindness in current cluster perforation design and guiding the optimal design of volume fracturing in shale gas reservoirs. Keywords: Shale gas, Horizontal well, Staged fracturing, Cluster spacing, Reservoir, Stimulated reservoir volume (SRV, Mathematical model, Optimal method, Sichuan basin, Jiaoshiba shale gasfield

The impact of nurse-driven targeted HIV screening in 8 emergency departments: study protocol for the DICI-VIH cluster-randomized two-period crossover trial.

Science.gov (United States)

Leblanc, Judith; Rousseau, Alexandra; Hejblum, Gilles; Durand-Zaleski, Isabelle; de Truchis, Pierre; Lert, France; Costagliola, Dominique; Simon, Tabassome; Crémieux, Anne-Claude

2016-02-01

In 2010, to reduce late HIV diagnosis, the French national health agency endorsed non-targeted HIV screening in health care settings. Despite these recommendations, non-targeted screening has not been implemented and only physician-directed diagnostic testing is currently performed. A survey conducted in 2010 in 29 French Emergency Departments (EDs) showed that non-targeted nurse-driven screening was feasible though only a few new HIV diagnoses were identified, predominantly among high-risk groups. A strategy targeting high-risk groups combined with current practice could be shown to be feasible, more efficient and cost-effective than current practice alone. DICI-VIH (acronym for nurse-driven targeted HIV screening) is a multicentre, cluster-randomized, two-period crossover trial. The primary objective is to compare the effectiveness of 2 strategies for diagnosing HIV among adult patients visiting EDs: nurse-driven targeted HIV screening combined with current practice (physician-directed diagnostic testing) versus current practice alone. Main secondary objectives are to compare access to specialist consultation and how early HIV diagnosis occurs in the course of the disease between the 2 groups, and to evaluate the implementation, acceptability and cost-effectiveness of nurse-driven targeted screening. The 2 strategies take place during 2 randomly assigned periods in 8 EDs of metropolitan Paris, where 42 % of France's new HIV patients are diagnosed every year. All patients aged 18 to 64, not presenting secondary to HIV exposure are included. During the intervention period, patients are invited to fill a 7-item questionnaire (country of birth, sexual partners and injection drug use) in order to select individuals who are offered a rapid test. If the rapid test is reactive, a follow-up visit with an infectious disease specialist is scheduled within 72 h. Assuming an 80 % statistical power and a 5 % type 1 error, with 1.04 and 3.38 new diagnoses per 10,000 patients in

Theory of boundary-free two-dimensional dust clusters

International Nuclear Information System (INIS)

Tsytovich, V.N.; Gousein-zade, N.G.; Morfill, G.E.

2006-01-01

It is shown theoretically that a stable two-dimensional (2D) grain cluster can exist in plasmas without external confinement if the shadow attraction of grains is taken into account. These are considered as boundary-free clusters. The equilibrium radius of the clusters is investigated numerically. It is found that it is rapidly decreasing with an increase of the attraction coefficient and with an increase of the number of grains N in the cluster. Comparison of energies of one shell cluster containing N grains with the energies of a cluster with N-1 grains in the shell and an additional one grain in the center as functions of the attraction coefficient is used to find the magic numbers for new shell creation. It is demonstrated that a dissociation of the cluster in several smaller clusters requires less energy than a removal of one of the grains from the cluster. The computations were performed for the Debye screening and for the nonlinear screening models and show that the structure of the clusters is sensitive to the type of screening. Frequencies of all collective modes of the 2D boundary-free clusters are calculated up to N=7 grains in the cluster for the case where all grains form one shell cluster and for the case where N=6 grains form one shell cluster and one of the grains is located at the center of the cluster. The frequencies of the modes increase with a decrease of the cluster radius. Stable and unstable modes are investigated as a function of the attraction coefficient. The presence of instability indicates that this type of equilibrium cluster does not correspond to the minimum energy in all directions and will be converted into another stable configuration. The universal magic number N m of grains in one shell cluster, such that for N=N m +1 the modes of the shell start to be unstable and the cluster converts to the cluster with N m grains in the shell and one grain in the center, is found for both the Yukawa screening and for the nonlinear screening

Evaluation of primary immunization coverage of infants under universal immunization programme in an urban area of Bangalore city using cluster sampling and lot quality assurance sampling techniques

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Punith K

2008-01-01

Full Text Available Research Question: Is LQAS technique better than cluster sampling technique in terms of resources to evaluate the immunization coverage in an urban area? Objective: To assess and compare the lot quality assurance sampling against cluster sampling in the evaluation of primary immunization coverage. Study Design: Population-based cross-sectional study. Study Setting: Areas under Mathikere Urban Health Center. Study Subjects: Children aged 12 months to 23 months. Sample Size: 220 in cluster sampling, 76 in lot quality assurance sampling. Statistical Analysis: Percentages and Proportions, Chi square Test. Results: (1 Using cluster sampling, the percentage of completely immunized, partially immunized and unimmunized children were 84.09%, 14.09% and 1.82%, respectively. With lot quality assurance sampling, it was 92.11%, 6.58% and 1.31%, respectively. (2 Immunization coverage levels as evaluated by cluster sampling technique were not statistically different from the coverage value as obtained by lot quality assurance sampling techniques. Considering the time and resources required, it was found that lot quality assurance sampling is a better technique in evaluating the primary immunization coverage in urban area.

Exergaming and older adult cognition: a cluster randomized clinical trial.

Science.gov (United States)

Anderson-Hanley, Cay; Arciero, Paul J; Brickman, Adam M; Nimon, Joseph P; Okuma, Naoko; Westen, Sarah C; Merz, Molly E; Pence, Brandt D; Woods, Jeffrey A; Kramer, Arthur F; Zimmerman, Earl A

2012-02-01

Dementia cases may reach 100 million by 2050. Interventions are sought to curb or prevent cognitive decline. Exercise yields cognitive benefits, but few older adults exercise. Virtual reality-enhanced exercise or "exergames" may elicit greater participation. To test the following hypotheses: (1) stationary cycling with virtual reality tours ("cybercycle") will enhance executive function and clinical status more than traditional exercise; (2) exercise effort will explain improvement; and (3) brain-derived neurotrophic growth factor (BDNF) will increase. Multi-site cluster randomized clinical trial (RCT) of the impact of 3 months of cybercycling versus traditional exercise, on cognitive function in older adults. Data were collected in 2008-2010; analyses were conducted in 2010-2011. 102 older adults from eight retirement communities enrolled; 79 were randomized and 63 completed. A recumbent stationary ergometer was utilized; virtual reality tours and competitors were enabled on the cybercycle. Executive function (Color Trails Difference, Stroop C, Digits Backward); clinical status (mild cognitive impairment; MCI); exercise effort/fitness; and plasma BDNF. Intent-to-treat analyses, controlling for age, education, and cluster randomization, revealed a significant group X time interaction for composite executive function (p=0.002). Cybercycling yielded a medium effect over traditional exercise (d=0.50). Cybercyclists had a 23% relative risk reduction in clinical progression to MCI. Exercise effort and fitness were comparable, suggesting another underlying mechanism. A significant group X time interaction for BDNF (p=0.05) indicated enhanced neuroplasticity among cybercyclists. Cybercycling older adults achieved better cognitive function than traditional exercisers, for the same effort, suggesting that simultaneous cognitive and physical exercise has greater potential for preventing cognitive decline. This study is registered at Clinicaltrials.gov NCT01167400. Copyright

Reinforcing Sampling Distributions through a Randomization-Based Activity for Introducing ANOVA

Science.gov (United States)

Taylor, Laura; Doehler, Kirsten

2015-01-01

This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course…

Targeted HIV Screening in Eight Emergency Departments: The DICI-VIH Cluster-Randomized Two-Period Crossover Trial.

Science.gov (United States)

Leblanc, Judith; Hejblum, Gilles; Costagliola, Dominique; Durand-Zaleski, Isabelle; Lert, France; de Truchis, Pierre; Verbeke, Geert; Rousseau, Alexandra; Piquet, Hélène; Simon, François; Pateron, Dominique; Simon, Tabassome; Crémieux, Anne-Claude

2017-10-30

This study compares the effectiveness and cost-effectiveness of nurse-driven targeted HIV screening alongside physician-directed diagnostic testing (intervention strategy) with diagnostic testing alone (control strategy) in 8 emergency departments. In this cluster-randomized, 2-period, crossover trial, 18- to 64-year-old patients presenting for reasons other than potential exposure to HIV were included. The strategy applied first was randomly assigned. During both periods, diagnostic testing was prescribed by physicians following usual care. During the intervention periods, patients were asked to complete a self-administered questionnaire. According to their answers, the triage nurse suggested performing a rapid test to patients belonging to a high-risk group. The primary outcome was the proportion of new diagnoses among included patients, which further refers to effectiveness. A secondary outcome was the intervention's incremental cost (health care system perspective) per additional diagnosis. During the intervention periods, 74,161 patients were included, 16,468 completed the questionnaire, 4,341 belonged to high-risk groups, and 2,818 were tested by nurses, yielding 13 new diagnoses. Combined with 9 diagnoses confirmed through 97 diagnostic tests, 22 new diagnoses were established. During the control periods, 74,166 patients were included, 92 were tested, and 6 received a new diagnosis. The proportion of new diagnoses among included patients was higher during the intervention than in the control periods (3.0 per 10,000 versus 0.8 per 10,000; difference 2.2 per 10,000, 95% CI 1.3 to 3.6; relative risk 3.7, 95% CI 1.4 to 9.8). The incremental cost was €1,324 per additional new diagnosis. The combined strategy of targeted screening and diagnostic testing was effective. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

[Acupotomy and acupuncture in the treatment of avascular necrosis of femoral head at the early and middle stages:a clinical randomized controlled trial].

Science.gov (United States)

Wang, Zhanyou; Zhou, Xuelong; Xie, Lishuang; Liang, Dongyue; Wang, Ying; Zhang, Hong-An; Zheng, Jinghong

2016-10-12

To compare the efficacy difference between acupotomy and acupuncture in the treatment of avascular necrosis of femoral head at the early and middle stages. The randomized controlled prospective study method was adopted. Sixty cases of avascular necrosis of femoral head at Ficat-ArletⅠto Ⅱ stages were randomized into an acupotomy group (32 cases) and an acupuncture group (28 cases) by the third part. In the acupotomy group, the acupotomy was adopted for the loose solution at the treatment sites of hip joint, once every two weeks, totally for 3 times. In the acupuncture group, ashi points around the hip joint were selected and stimulated with warm acupuncture therapy, once every day, for 6 weeks. Harris hip score was observed before and after treatment. The efficacy was evaluated in the two groups. Harris hip score was improved significantly after treatment in the two groups (both P avascular necrosis of femoral head at the early and middle stages.

Pressure ulcer multidisciplinary teams via telemedicine: a pragmatic cluster randomized stepped wedge trial in long term care.

Science.gov (United States)

Stern, Anita; Mitsakakis, Nicholas; Paulden, Mike; Alibhai, Shabbir; Wong, Josephine; Tomlinson, George; Brooker, Ann-Sylvia; Krahn, Murray; Zwarenstein, Merrick

2014-02-24

The study was conducted to determine the clinical and cost effectiveness of enhanced multi-disciplinary teams (EMDTs) vs. 'usual care' for the treatment of pressure ulcers in long term care (LTC) facilities in Ontario, Canada We conducted a multi-method study: a pragmatic cluster randomized stepped-wedge trial, ethnographic observation and in-depth interviews, and an economic evaluation. Long term care facilities (clusters) were randomly allocated to start dates of the intervention. An advance practice nurse (APN) with expertise in skin and wound care visited intervention facilities to educate staff on pressure ulcer prevention and treatment, supported by an off-site hospital based expert multi-disciplinary wound care team via email, telephone, or video link as needed. The primary outcome was rate of reduction in pressure ulcer surface area (cm2/day) measured on before and after standard photographs by an assessor blinded to facility allocation. Secondary outcomes were time to healing, probability of healing, pressure ulcer incidence, pressure ulcer prevalence, wound pain, hospitalization, emergency department visits, utility, and cost. 12 of 15 eligible LTC facilities were randomly selected to participate and randomized to start date of the intervention following the stepped wedge design. 137 residents with a total of 259 pressure ulcers (stage 2 or greater) were recruited over the 17 month study period. No statistically significant differences were found between control and intervention periods on any of the primary or secondary outcomes. The economic evaluation demonstrated a mean reduction in direct care costs of $650 per resident compared to 'usual care'. The qualitative study suggested that onsite support by APN wound specialists was welcomed, and is responsible for reduced costs through discontinuation of expensive non evidence based treatments. Insufficient allocation of nursing home staff time to wound care may explain the lack of impact on healing

40 CFR 761.306 - Sampling 1 meter square surfaces by random selection of halves.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sampling 1 meter square surfaces by...(b)(3) § 761.306 Sampling 1 meter square surfaces by random selection of halves. (a) Divide each 1 meter square portion where it is necessary to collect a surface wipe test sample into two equal (or as...

Cluster chemical ionization for improved confidence level in sample identification by gas chromatography/mass spectrometry.

Science.gov (United States)

Fialkov, Alexander B; Amirav, Aviv

2003-01-01

Upon the supersonic expansion of helium mixed with vapor from an organic solvent (e.g. methanol), various clusters of the solvent with the sample molecules can be formed. As a result of 70 eV electron ionization of these clusters, cluster chemical ionization (cluster CI) mass spectra are obtained. These spectra are characterized by the combination of EI mass spectra of vibrationally cold molecules in the supersonic molecular beam (cold EI) with CI-like appearance of abundant protonated molecules, together with satellite peaks corresponding to protonated or non-protonated clusters of sample compounds with 1-3 solvent molecules. Like CI, cluster CI preferably occurs for polar compounds with high proton affinity. However, in contrast to conventional CI, for non-polar compounds or those with reduced proton affinity the cluster CI mass spectrum converges to that of cold EI. The appearance of a protonated molecule and its solvent cluster peaks, plus the lack of protonation and cluster satellites for prominent EI fragments, enable the unambiguous identification of the molecular ion. In turn, the insertion of the proper molecular ion into the NIST library search of the cold EI mass spectra eliminates those candidates with incorrect molecular mass and thus significantly increases the confidence level in sample identification. Furthermore, molecular mass identification is of prime importance for the analysis of unknown compounds that are absent in the library. Examples are given with emphasis on the cluster CI analysis of carbamate pesticides, high explosives and unknown samples, to demonstrate the usefulness of Supersonic GC/MS (GC/MS with supersonic molecular beam) in the analysis of these thermally labile compounds. Cluster CI is shown to be a practical ionization method, due to its ease-of-use and fast instrumental conversion between EI and cluster CI, which involves the opening of only one valve located at the make-up gas path. The ease-of-use of cluster CI is analogous

Influence of Cu(NO32 initiation additive in two-stage mode conditions of coal pyrolytic decomposition

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Larionov Kirill

2017-01-01

Full Text Available Two-stage process (pyrolysis and oxidation of brown coal sample with Cu(NO32 additive pyrolytic decomposition was studied. Additive was introduced by using capillary wetness impregnation method with 5% mass concentration. Sample reactivity was studied by thermogravimetric analysis with staged gaseous medium supply (argon and air at heating rate 10 °C/min and intermediate isothermal soaking. The initiative additive introduction was found to significantly reduce volatile release temperature and accelerate thermal decomposition of sample. Mass-spectral analysis results reveal that significant difference in process characteristics is connected to volatile matter release stage which is initiated by nitrous oxide produced during copper nitrate decomposition.

Effects of Nurse-Led Multifactorial Care to Prevent Disability in Community-Living Older People : Cluster Randomized Trial

NARCIS (Netherlands)

Suijker, Jacqueline J.; van Rijn, Marjon; Buurman, Bianca M.; ter Riet, Gerben; van Charante, Eric P. Moll; de Rooij, Sophia E.

2016-01-01

Background To evaluate the effects of nurse-led multifactorial care to prevent disability in community-living older people. Methods In a cluster randomized trail, 11 practices (n = 1,209 participants) were randomized to the intervention group, and 13 practices (n = 1,074 participants) were

Two-stage free electron laser research

Science.gov (United States)

Segall, S. B.

1984-10-01

KMS Fusion, Inc. began studying the feasibility of two-stage free electron lasers for the Office of Naval Research in June, 1980. At that time, the two-stage FEL was only a concept that had been proposed by Luis Elias. The range of parameters over which such a laser could be successfully operated, attainable power output, and constraints on laser operation were not known. The primary reason for supporting this research at that time was that it had the potential for producing short-wavelength radiation using a relatively low voltage electron beam. One advantage of a low-voltage two-stage FEL would be that shielding requirements would be greatly reduced compared with single-stage short-wavelength FEL's. If the electron energy were kept below about 10 MeV, X-rays, generated by electrons striking the beam line wall, would not excite neutron resonance in atomic nuclei. These resonances cause the emission of neutrons with subsequent induced radioactivity. Therefore, above about 10 MeV, a meter or more of concrete shielding is required for the system, whereas below 10 MeV, a few millimeters of lead would be adequate.

Coupling methods for multistage sampling

OpenAIRE

Chauvet, Guillaume

2015-01-01

Multistage sampling is commonly used for household surveys when there exists no sampling frame, or when the population is scattered over a wide area. Multistage sampling usually introduces a complex dependence in the selection of the final units, which makes asymptotic results quite difficult to prove. In this work, we consider multistage sampling with simple random without replacement sampling at the first stage, and with an arbitrary sampling design for further stages. We consider coupling ...

Clustering of low-valence particles: structure and kinetics.

Science.gov (United States)

Markova, Olga; Alberts, Jonathan; Munro, Edwin; Lenne, Pierre-François

2014-08-01

We compute the structure and kinetics of two systems of low-valence particles with three or six freely oriented bonds in two dimensions. The structure of clusters formed by trivalent particles is complex with loops and holes, while hexavalent particles self-organize into regular and compact structures. We identify the elementary structures which compose the clusters of trivalent particles. At initial stages of clustering, the clusters of trivalent particles grow with a power-law time dependence. Yet at longer times fusion and fission of clusters equilibrates and clusters form a heterogeneous phase with polydispersed sizes. These results emphasize the role of valence in the kinetics and stability of finite-size clusters.

Dynamic connectivity algorithms for Monte Carlo simulations of the random-cluster model

International Nuclear Information System (INIS)

Elçi, Eren Metin; Weigel, Martin

2014-01-01

We review Sweeny's algorithm for Monte Carlo simulations of the random cluster model. Straightforward implementations suffer from the problem of computational critical slowing down, where the computational effort per edge operation scales with a power of the system size. By using a tailored dynamic connectivity algorithm we are able to perform all operations with a poly-logarithmic computational effort. This approach is shown to be efficient in keeping online connectivity information and is of use for a number of applications also beyond cluster-update simulations, for instance in monitoring droplet shape transitions. As the handling of the relevant data structures is non-trivial, we provide a Python module with a full implementation for future reference.

Recruitment to online therapies for depression: pilot cluster randomized controlled trial.

Science.gov (United States)

Jones, Ray B; Goldsmith, Lesley; Hewson, Paul; Williams, Christopher J

2013-03-05

Raising awareness of online cognitive behavioral therapy (CBT) could benefit many people with depression, but we do not know how purchasing online advertising compares to placing free links from relevant local websites in increasing uptake. To pilot a cluster randomized controlled trial (RCT) comparing purchase of Google AdWords with placing free website links in raising awareness of online CBT resources for depression in order to better understand research design issues. We compared two online interventions with a control without intervention. The pilot RCT had 4 arms, each with 4 British postcode areas: (A) geographically targeted AdWords, (B) adverts placed on local websites by contacting website owners and requesting links be added, (C) both interventions, (D) control. Participants were directed to our research project website linking to two freely available online CBT resource sites (Moodgym and Living Life To The Full (LLTTF)) and two other depression support sites. We used data from (1) AdWords, (2) Google Analytics for our project website and for LLTTF, and (3) research project website. We compared two outcomes: (1) numbers with depression accessing the research project website, and then chose an onward link to one of the two CBT websites, and (2) numbers registering with LLTTF. We documented costs, and explored intervention and assessment methods to make general recommendations to inform researchers aiming to use similar methodologies in future studies. Trying to place local website links appeared much less cost effective than AdWords and although may prove useful for service delivery, was not worth pursuing in the context of the current study design. Our AdWords intervention was effective in recruiting people to the project website but our location targeting "leaked" and was not as geographically specific as claimed. The impact on online CBT was also diluted by offering participants other choices of destinations. Measuring the impact on LLTTF use was

Recruitment to Online Therapies for Depression: Pilot Cluster Randomized Controlled Trial

OpenAIRE

Jones, Ray B; Goldsmith, Lesley; Hewson, Paul; Williams, Christopher J

2013-01-01

Background Raising awareness of online cognitive behavioral therapy (CBT) could benefit many people with depression, but we do not know how purchasing online advertising compares to placing free links from relevant local websites in increasing uptake. Objective To pilot a cluster randomized controlled trial (RCT) comparing purchase of Google AdWords with placing free website links in raising awareness of online CBT resources for depression in order to better understand research design issues....

Making birthing safe for Pakistan women: a cluster randomized trial

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Khan Muhammad

2012-07-01

Full Text Available Abstract Background Two out of three neonatal deaths occur in just 10 countries and Pakistan stands third among them. Maternal mortality is also high with most deaths occurring during labor, birth, and first few hours after birth. Enhanced access and utilization of skilled delivery and emergency obstetric care is the demonstrated strategy in reducing maternal and neonatal mortality. This trial aims to compare reduction in neonate mortality and utilization of available safe birthing and Emergency Obstetric and Neonatal Care services among pregnant mothers receiving ‘structured birth planning’, and/or ‘transport facilitation’ compared to routine care. Methods A pragmatic cluster randomized trial, with qualitative and economic studies, will be conducted in Jhang, Chiniot and Khanewal districts of Punjab, Pakistan, from February 2011 to May 2013. At least 29,295 pregnancies will be registered in the three arms, seven clusters per arm; 1 structured birth planning and travel facilitation, 2 structured birth planning, and 3 control arm. Trial will be conducted through the Lady Health Worker program. Main outcomes are difference in neonatal mortality and service utilization; maternal mortality being the secondary outcome. Cluster level analysis will be done according to intention-to-treat. Discussion A nationwide network of about 100,000 lady health workers is already involved in antenatal and postnatal care of pregnant women. They also act as “gatekeepers” for the child birthing services. This gate keeping role mainly includes counseling and referral for skill birth attendance and travel arrangements for emergency obstetric care (if required. The review of current arrangements and practices show that the care delivery process needs enhancement to include adequate information provision as well as informed “decision” making and planned “action” by the pregnant women. The proposed three-year research is to develop, through national

Effectiveness of a group diabetes education programme in underserved communities in South Africa: pragmatic cluster randomized control trial.