Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data

PubMed Central

Tian, Ting; McLachlan, Geoffrey J.; Dieters, Mark J.; Basford, Kaye E.

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances. PMID:26689369

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

PubMed

Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Role of competition between polarity sites in establishing a unique front

PubMed Central

Wu, Chi-Fang; Chiou, Jian-Geng; Minakova, Maria; Woods, Benjamin; Tsygankov, Denis; Zyla, Trevin R; Savage, Natasha S; Elston, Timothy C; Lew, Daniel J

2015-01-01

Polarity establishment in many cells is thought to occur via positive feedback that reinforces even tiny asymmetries in polarity protein distribution. Cdc42 and related GTPases are activated and accumulate in a patch of the cortex that defines the front of the cell. Positive feedback enables spontaneous polarization triggered by stochastic fluctuations, but as such fluctuations can occur at multiple locations, how do cells ensure that they make only one front? In polarizing cells of the model yeast Saccharomyces cerevisiae, positive feedback can trigger growth of several Cdc42 clusters at the same time, but this multi-cluster stage rapidly evolves to a single-cluster state, which then promotes bud emergence. By manipulating polarity protein dynamics, we show that resolution of multi-cluster intermediates occurs through a greedy competition between clusters to recruit and retain polarity proteins from a shared intracellular pool. DOI: http://dx.doi.org/10.7554/eLife.11611.001 PMID:26523396

A multi-stage drop-the-losers design for multi-arm clinical trials.

PubMed

Wason, James; Stallard, Nigel; Bowden, Jack; Jennison, Christopher

2017-02-01

Multi-arm multi-stage trials can improve the efficiency of the drug development process when multiple new treatments are available for testing. A group-sequential approach can be used in order to design multi-arm multi-stage trials, using an extension to Dunnett's multiple-testing procedure. The actual sample size used in such a trial is a random variable that has high variability. This can cause problems when applying for funding as the cost will also be generally highly variable. This motivates a type of design that provides the efficiency advantages of a group-sequential multi-arm multi-stage design, but has a fixed sample size. One such design is the two-stage drop-the-losers design, in which a number of experimental treatments, and a control treatment, are assessed at a prescheduled interim analysis. The best-performing experimental treatment and the control treatment then continue to a second stage. In this paper, we discuss extending this design to have more than two stages, which is shown to considerably reduce the sample size required. We also compare the resulting sample size requirements to the sample size distribution of analogous group-sequential multi-arm multi-stage designs. The sample size required for a multi-stage drop-the-losers design is usually higher than, but close to, the median sample size of a group-sequential multi-arm multi-stage trial. In many practical scenarios, the disadvantage of a slight loss in average efficiency would be overcome by the huge advantage of a fixed sample size. We assess the impact of delay between recruitment and assessment as well as unknown variance on the drop-the-losers designs.

Three-Level Models for Indirect Effects in School- and Class-Randomized Experiments in Education

ERIC Educational Resources Information Center

Pituch, Keenan A.; Murphy, Daniel L.; Tate, Richard L.

2009-01-01

Due to the clustered nature of field data, multi-level modeling has become commonly used to analyze data arising from educational field experiments. While recent methodological literature has focused on multi-level mediation analysis, relatively little attention has been devoted to mediation analysis when three levels (e.g., student, class,…

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

PubMed Central

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

2007-01-01

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 the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

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

PubMed

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 advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

Testing use of payers to facilitate evidence-based practice adoption: protocol for a cluster-randomized trial

PubMed Central

2013-01-01

Background More effective methods are needed to implement evidence-based findings into practice. The Advancing Recovery Framework offers a multi-level approach to evidence-based practice implementation by aligning purchasing and regulatory policies at the payer level with organizational change strategies at the organizational level. Methods The Advancing Recovery Buprenorphine Implementation Study is a cluster-randomized controlled trial designed to increase use of the evidence-based practice buprenorphine medication to treat opiate addiction. Ohio Alcohol, Drug Addiction, and Mental Health Services Boards (ADAMHS), who are payers, and their addiction treatment organizations were recruited for a trial to assess the effects of payer and treatment organization changes (using the Advancing Recovery Framework) versus treatment organization changes alone on the use of buprenorphine. A matched-pair randomization, based on county characteristics, was applied, resulting in seven county ADAMHS boards and twenty-five treatment organizations in each arm. Opioid dependent patients are nested within cluster (treatment organization), and treatment organization clusters are nested within ADAMHS county board. The primary outcome is the percentage of individuals with an opioid dependence diagnosis who use buprenorphine during the 24-month intervention period and the 12-month sustainability period. The trial is currently in the baseline data collection stage. Discussion Although addiction treatment providers are under increasing pressure to implement evidence-based practices that have been proven to improve patient outcomes, adoption of these practices lags, compared to other areas of healthcare. Reasons frequently cited for the slow adoption of EBPs in addiction treatment include, regulatory issues, staff, or client resistance and lack of resources. Yet the way addiction treatment is funded, the payer’s role—has not received a lot of attention in research on EBP adoption. This research is unique because it investigates the role of payers in evidence-based practice implementation using a randomized controlled design instead of case examples. The testing of the Advancing Recovery Framework is designed to broaden the understanding of the impact payers have on evidence-based practice (EBP) adoption. Trial registration http://NCT01702142 (ClinicalTrials.gov registry, USA) PMID:23663749

Design of a Phase III cluster randomized trial to assess the efficacy and safety of a malaria transmission blocking vaccine.

PubMed

Delrieu, Isabelle; Leboulleux, Didier; Ivinson, Karen; Gessner, Bradford D

2015-03-24

Vaccines interrupting Plasmodium falciparum malaria transmission targeting sexual, sporogonic, or mosquito-stage antigens (SSM-VIMT) are currently under development to reduce malaria transmission. An international group of malaria experts was established to evaluate the feasibility and optimal design of a Phase III cluster randomized trial (CRT) that could support regulatory review and approval of an SSM-VIMT. The consensus design is a CRT with a sentinel population randomly selected from defined inner and buffer zones in each cluster, a cluster size sufficient to assess true vaccine efficacy in the inner zone, and inclusion of ongoing assessment of vaccine impact stratified by distance of residence from the cluster edge. Trials should be conducted first in areas of moderate transmission, where SSM-VIMT impact should be greatest. Sample size estimates suggest that such a trial is feasible, and within the range of previously supported trials of malaria interventions, although substantial issues to implementation exist. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference

ERIC Educational Resources Information Center

Schochet, Peter Z.

2013-01-01

This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Sampling Methods in Cardiovascular Nursing Research: An Overview.

PubMed

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.

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

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

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

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. PMID:19740439

Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging

PubMed Central

Doi, Ryoichi; Arif, Chusnul

2014-01-01

Red-green-blue (RGB) channels of RGB digital photographs were loaded with luminosity-adjusted R, G, and completely white grayscale images, respectively (RGwhtB method), or R, G, and R + G (RGB yellow) grayscale images, respectively (RGrgbyB method), to adjust the brightness of the entire area of multi-temporally acquired color digital photographs of a rice canopy. From the RGwhtB or RGrgbyB pseudocolor image, cyan, magenta, CMYK yellow, black, L*, a*, and b* grayscale images were prepared. Using these grayscale images and R, G, and RGB yellow grayscale images, the luminosity-adjusted pixels of the canopy photographs were statistically clustered. With the RGrgbyB and the RGwhtB methods, seven and five major color clusters were given, respectively. The RGrgbyB method showed clear differences among three rice growth stages, and the vegetative stage was further divided into two substages. The RGwhtB method could not clearly discriminate between the second vegetative and midseason stages. The relative advantages of the RGrgbyB method were attributed to the R, G, B, magenta, yellow, L*, and a* grayscale images that contained richer information to show the colorimetrical differences among objects than those of the RGwhtB method. The comparison of rice canopy colors at different time points was enabled by the pseudocolor imaging method. PMID:25302325

THE NORTH CAROLINA HERALD PILOT STUDY

EPA Science Inventory

The sampling design for the National Children's Study (NCS) calls for a population-based, multi-stage, clustered household sampling approach. The full sample is designed to be representative of both urban and rural births in the United States, 2007-2011. While other sur...

[Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

PubMed

Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

2015-05-01

The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

Continued smoking abstinence in diabetic patients in primary care: a cluster randomized controlled multicenter study.

PubMed

Pérez-Tortosa, Santiago; Roig, Lydia; Manresa, Josep M; Martin-Cantera, Carlos; Puigdomènech, Elisa; Roura, Pilar; Armengol, Angelina; Advani, Mamta

2015-01-01

To assess the effectiveness of an intensive smoking cessation intervention based on the transtheoretical model of change (TTM) in diabetic smokers attending primary care. A cluster randomized controlled clinical trial was designed in which the unit of randomization (intervention vs. usual care) was the primary care team. An intensive, individualized intervention using motivational interview and therapies and medications adapted to the patient's stage of change was delivered. The duration of the study was 1 year. A total of 722 people with diabetes who were smokers (345 in the intervention group and 377 in the control group) completed the study. After 1 year, continued abstinence was recorded in 90 (26.1%) patients in the intervention group and in 67 (17.8%) controls (p=0.007). In patients with smoking abstinence, there was a higher percentage in the precontemplation and contemplation stages at baseline in the intervention group than in controls (21.2% vs. 13.7%, p=0.024). When the precontemplation stage was taken as reference (OR=1.0), preparation/action stage at baseline showed a protective effect, decreasing 3.41 times odds of continuing smoking (OR=0.293 95% CI 0.179-0.479, p<0.001). Contemplation stage at baseline also showed a protective effect, decreasing the odds of continuing smoking (OR=0.518, 95% CI 0.318-0.845, p=0.008). An intensive intervention adapted to the individual stage of change delivered in primary care was feasible and effective, with a smoking cessation rate of 26.1% after 1 year. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Promoting state health department evidence-based cancer and chronic disease prevention: a multi-phase dissemination study with a cluster randomized trial component

PubMed Central

2013-01-01

Background Cancer and other chronic diseases reduce quality and length of life and productivity, and represent a significant financial burden to society. Evidence-based public health approaches to prevent cancer and other chronic diseases have been identified in recent decades and have the potential for high impact. Yet, barriers to implement prevention approaches persist as a result of multiple factors including lack of organizational support, limited resources, competing emerging priorities and crises, and limited skill among the public health workforce. The purpose of this study is to learn how best to promote the adoption of evidence based public health practice related to chronic disease prevention. Methods/design This paper describes the methods for a multi-phase dissemination study with a cluster randomized trial component that will evaluate the dissemination of public health knowledge about evidence-based prevention of cancer and other chronic diseases. Phase one involves development of measures of practitioner views on and organizational supports for evidence-based public health and data collection using a national online survey involving state health department chronic disease practitioners. In phase two, a cluster randomized trial design will be conducted to test receptivity and usefulness of dissemination strategies directed toward state health department chronic disease practitioners to enhance capacity and organizational support for evidence-based chronic disease prevention. Twelve state health department chronic disease units will be randomly selected and assigned to intervention or control. State health department staff and the university-based study team will jointly identify, refine, and select dissemination strategies within intervention units. Intervention (dissemination) strategies may include multi-day in-person training workshops, electronic information exchange modalities, and remote technical assistance. Evaluation methods include pre-post surveys, structured qualitative phone interviews, and abstraction of state-level chronic disease prevention program plans and progress reports. Trial registration clinicaltrials.gov: NCT01978054. PMID:24330729

Determinants of customers' intention to participate in a Korean restaurant health promotion program: an application of the theory of planned behavior.

PubMed

Hong, Kyungeui; Gittelsohn, Joel; Joung, Hyojee

2010-06-01

The purpose of this study was to investigate the effects of personal characteristics and theory of planned behavior (TPB) constructs on the intention to participate in a restaurant health promotion program. In total, 830 adults residing in Seoul were sampled by a multi-stage cluster and random sampling design. Data were collected from a structured self-administered questionnaire, which covered variables concerning demographics, health status and TPB constructs including attitude, subjective norm and perceived behavioral control. A path analysis combining personal characteristics and TPB constructs was used to investigate determinants of the customers' intention. Positive and negative attitudes, subjective norms and perceived behavioral control directly affected the intention to participate. Demographics and health status both directly and indirectly affected the intention to participate. This study identifies personal characteristics and TPB constructs that are important to planning and implementing a restaurant health promotion program.

Process Evaluation of a Multi-Component Intervention to Reduce Infectious Diseases and Improve Hygiene and Well-Being among School Children: The Hi Five Study

ERIC Educational Resources Information Center

Bonnesen, C. T.; Plauborg, R.; Denbaek, A. M.; Due, P.; Johansen, A.

2015-01-01

The Hi Five study was a three-armed cluster randomized controlled trial designed to reduce infections and improve hygiene and well-being among pupils. Participating schools (n = 43) were randomized into either control (n = 15) or one of two intervention groups (n = 28). The intervention consisted of three components: (i) a curriculum (ii)…

Study protocol of Prednisone in episodic Cluster Headache (PredCH): a randomized, double-blind, placebo-controlled parallel group trial to evaluate the efficacy and safety of oral prednisone as an add-on therapy in the prophylactic treatment of episodic cluster headache with verapamil

PubMed Central

2013-01-01

Background Episodic cluster headache (ECH) is a primary headache disorder that severely impairs patient’s quality of life. First-line therapy in the initiation of a prophylactic treatment is verapamil. Due to its delayed onset of efficacy and the necessary slow titration of dosage for tolerability reasons prednisone is frequently added by clinicians to the initial prophylactic treatment of a cluster episode. This treatment strategy is thought to effectively reduce the number and intensity of cluster attacks in the beginning of a cluster episode (before verapamil is effective). This study will assess the efficacy and safety of oral prednisone as an add-on therapy to verapamil and compare it to a monotherapy with verapamil in the initial prophylactic treatment of a cluster episode. Methods and design PredCH is a prospective, randomized, double-blind, placebo-controlled trial with parallel study arms. Eligible patients with episodic cluster headache will be randomized to a treatment intervention with prednisone or a placebo arm. The multi-center trial will be conducted in eight German headache clinics that specialize in the treatment of ECH. Discussion PredCH is designed to assess whether oral prednisone added to first-line agent verapamil helps reduce the number and intensity of cluster attacks in the beginning of a cluster episode as compared to monotherapy with verapamil. Trial registration German Clinical Trials Register DRKS00004716 PMID:23889923

Statistical segmentation of multidimensional brain datasets

NASA Astrophysics Data System (ADS)

Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

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

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

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

2013-12-01

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 noisemore » 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.« less

Probabilistic Analysis of Hierarchical Cluster Protocols for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kaj, Ingemar

Wireless sensor networks are designed to extract data from the deployment environment and combine sensing, data processing and wireless communication to provide useful information for the network users. Hundreds or thousands of small embedded units, which operate under low-energy supply and with limited access to central network control, rely on interconnecting protocols to coordinate data aggregation and transmission. Energy efficiency is crucial and it has been proposed that cluster based and distributed architectures such as LEACH are particularly suitable. We analyse the random cluster hierarchy in this protocol and provide a solution for low-energy and limited-loss optimization. Moreover, we extend these results to a multi-level version of LEACH, where clusters of nodes again self-organize to form clusters of clusters, and so on.

RECRUITING FOR A LONGITUDINAL STUDY OF CHILDREN'S HEALTH USING A HOUSEHOLD-BASED PROBABILITY SAMPLING APPROACH

EPA Science Inventory

The sampling design for the National Children¿s Study (NCS) calls for a population-based, multi-stage, clustered household sampling approach (visit our website for more information on the NCS : www.nationalchildrensstudy.gov). The full sample is designed to be representative of ...

Thermodynamics and Kinetics of Prenucleation Clusters, Classical and Non-Classical Nucleation

PubMed Central

Zahn, Dirk

2015-01-01

Recent observations of prenucleation species and multi-stage crystal nucleation processes challenge the long-established view on the thermodynamics of crystal formation. Here, we review and generalize extensions to classical nucleation theory. Going beyond the conventional implementation as has been used for more than a century now, nucleation inhibitors, precursor clusters and non-classical nucleation processes are rationalized as well by analogous concepts based on competing interface and bulk energy terms. This is illustrated by recent examples of species formed prior to/instead of crystal nucleation and multi-step nucleation processes. Much of the discussed insights were obtained from molecular simulation using advanced sampling techniques, briefly summarized herein for both nucleation-controlled and diffusion-controlled aggregate formation. PMID:25914369

Privacy Protection by Matrix Transformation

NASA Astrophysics Data System (ADS)

Yang, Weijia

Privacy preserving is indispensable in data mining. In this paper, we present a novel clustering method for distributed multi-party data sets using orthogonal transformation and data randomization techniques. Our method can not only protect privacy in face of collusion, but also achieve a higher level of accuracy compared to the existing methods.

Optimal Design for Regression Discontinuity Studies with Clustering

ERIC Educational Resources Information Center

Rhoads, Christopher; Dye, Charles

2014-01-01

Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

PubMed Central

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

PubMed

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

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

PubMed

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.

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

The three-zone composite productivity model for a multi-fractured horizontal shale gas well

NASA Astrophysics Data System (ADS)

Qi, Qian; Zhu, Weiyao

2018-02-01

Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interfere of the fractures.

A randomized controlled trial of acupuncture and moxibustion to treat Bell's palsy according to different stages: design and protocol.

PubMed

Chen, Xiaoqin; Li, Ying; Zheng, Hui; Hu, Kaming; Zhang, Hongxing; Zhao, Ling; Li, Yan; Liu, Lian; Mang, Lingling; Yu, Shuyuan

2009-07-01

Acupuncture to treat Bell's palsy is one of the most commonly used methods in China. There are a variety of acupuncture treatment options to treat Bell's palsy in clinical practice. Since Bell's palsy has three different path-stages (acute stage, resting stage and restoration stage), so whether acupuncture is effective in the different path-stages and which acupuncture treatment is the best method are major issues in acupuncture clinical trials about Bell's palsy. In this article, we report the design and protocol of a large sample multi-center randomized controlled trial to treat Bell's palsy with acupuncture. There are five acupuncture groups, with four according to different path-stages and one not. In total, 900 patients with Bell's palsy are enrolled in this study. These patients are randomly assigned to receive one of the following four treatment groups according to different path-stages, i.e. 1) staging acupuncture group, 2) staging acupuncture and moxibustion group, 3) staging electro-acupuncture group, 4) staging acupuncture along yangming musculature group or non-staging acupuncture control group. The outcome measurements in this trial are the effect comparison achieved among these five groups in terms of House-Brackmann scale (Global Score and Regional Score), Facial Disability Index scale, Classification scale of Facial Paralysis, and WHOQOL-BREF scale before randomization (baseline phase) and after randomization. The result of this trial will certify the efficacy of using staging acupuncture and moxibustion to treat Bell's palsy, and to approach a best acupuncture treatment among these five different methods for treating Bell's palsy.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata

PubMed Central

Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata.

PubMed

Diniz, Daniel G; Silva, Geane O; Naves, Thaís B; Fernandes, Taiany N; Araújo, Sanderson C; Diniz, José A P; de Farias, Luis H S; Sosthenes, Marcia C K; Diniz, Cristovam G; Anthony, Daniel C; da Costa Vasconcelos, Pedro F; Picanço Diniz, Cristovam W

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous.

A random cluster survey and a convenience sample give comparable estimates of immunity to vaccine preventable diseases in children of school age in Victoria, Australia.

PubMed

Kelly, Heath; Riddell, Michaela A; Gidding, Heather F; Nolan, Terry; Gilbert, Gwendolyn L

2002-08-19

We compared estimates of the age-specific population immunity to measles, mumps, rubella, hepatitis B and varicella zoster viruses in Victorian school children obtained by a national sero-survey, using a convenience sample of residual sera from diagnostic laboratories throughout Australia, with those from a three-stage random cluster survey. When grouped according to school age (primary or secondary school) there was no significant difference in the estimates of immunity to measles, mumps, hepatitis B or varicella. Compared with the convenience sample, the random cluster survey estimated higher immunity to rubella in samples from both primary (98.7% versus 93.6%, P = 0.002) and secondary school students (98.4% versus 93.2%, P = 0.03). Despite some limitations, this study suggests that the collection of a convenience sample of sera from diagnostic laboratories is an appropriate sampling strategy to provide population immunity data that will inform Australia's current and future immunisation policies. Copyright 2002 Elsevier Science Ltd.

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Moderating effect of intrinsic religiosity on the relationship between depression and cognitive function among community-dwelling older adults.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah

2018-04-01

Research has found that depression in later life is associated with cognitive impairment. Thus, the mechanism to reduce the effect of depression on cognitive function is warranted. In this paper, we intend to examine whether intrinsic religiosity mediates the association between depression and cognitive function. The study included 2322 nationally representative community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, cognitive function, depression and intrinsic religiosity. A four-step moderated hierarchical regression analysis was employed to test the moderating effect. Statistical analyses were performed using SPSS (version 15.0). Bivariate analyses showed that both depression and intrinsic religiosity had significant relationships with cognitive function. In addition, four-step moderated hierarchical regression analysis revealed that the intrinsic religiosity moderated the association between depression and cognitive function, after controlling for selected socio-demographic characteristics. Intrinsic religiosity might reduce the negative effect of depression on cognitive function. Professionals who are working with depressed older adults should seek ways to improve their intrinsic religiosity as one of the strategies to prevent cognitive impairment.

Weight gain prevention in the school worksite setting: Results of a multi-level cluster randomized trial

PubMed Central

Lemon, Stephenie C.; Wang, Monica L.; Wedick, Nicole M.; Estabrook, Barbara; Druker, Susan; Schneider, Kristin L.; Li, Wenjun; Pbert, Lori

2014-01-01

Objective To describe the effectiveness, reach and implementation of a weight gain prevention intervention among public school employees. Method A multi-level intervention was tested in a cluster randomized trial among 782 employees in 12 central Massachusetts public high schools from 2009 to 2012. The intervention targeted the nutrition and physical activity environment and policies, the social environment and individual knowledge, attitudes and skills. The intervention was compared to a materials only condition. The primary outcome measures were change in weight and body mass index (BMI) at 24-month follow-up. Implementation of physical environment, policy and social environment strategies at the school and interpersonal levels, and intervention participation at the individual level were assessed. Results At 24-month follow-up, there was a net change (difference of the difference) of −3.03 pounds (p=.04) and of −.48 BMI units (p=.05) between intervention and comparison conditions. The majority of intervention strategies were successfully implemented by all intervention schools, although establishing formal policies was challenging. Employee participation in programs targeting the physical and social environment was maintained over time. Conclusion This study supports that a multi-level intervention integrated within the organizational culture can be successfully implemented and prevent weight gain in public high school employees. PMID:24345602

A MULTI-CENTER CLUSTER-RANDOMIZED TRIAL OF A MULTI-FACTORIAL INTERVENTION TO IMPROVE ANTIHYPERTENSIVE MEDICATION ADHERENCE AND BLOOD PRESSURE CONTROL AMONG PATIENTS AT HIGH CARDIOVASCULAR RISK (The COM99 study)*

PubMed Central

Pladevall, Manel; Brotons, Carlos; Gabriel, Rafael; Arnau, Anna; Suarez, Carmen; de la Figuera, Mariano; Marquez, Emilio; Coca, Antonio; Sobrino, Javier; Divine, George; Heisler, Michele; Williams, L Keoki

2010-01-01

Background Medication non-adherence is common and results in preventable disease complications. This study assesses the effectiveness of a multifactorial intervention to improve both medication adherence and blood pressure control and to reduce cardiovascular events. Methods and Results In this multi-center, cluster-randomized trial, physicians from hospital-based hypertension clinics and primary care centers across Spain were randomized to receive and provide the intervention to their high-risk patients. Eligible patients were ≥50 years of age, had uncontrolled hypertension, and had an estimated 10-year cardiovascular risk greater than 30%. Physicians randomized to the intervention group counted patients’ pills, designated a family member to support adherence behavior, and provided educational information to patients. The primary outcome was blood pressure control at 6 months. Secondary outcomes included both medication adherence and a composite end-point of all cause mortality and cardiovascular-related hospitalizations. Seventy-nine physicians and 877 patients participated in the trial. The mean duration of follow-up was 39 months. Intervention patients were less likely to have an uncontrolled systolic blood pressure (odds ratio 0.62; 95% confidence interval [CI] 0.50–0.78) and were more likely to be adherent (OR 1.91; 95% CI 1.19–3.05) when compared with control group patients at 6 months. After five years 16% of the patients in the intervention group and 19% in the control group met the composite end-point (hazard ratio 0.97; 95% CI 0.67–1.39). Conclusions A multifactorial intervention to improve adherence to antihypertensive medication was effective in improving both adherence and blood pressure control, but it did not appear to improve long-term cardiovascular events. PMID:20823391

Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

ERIC Educational Resources Information Center

Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

2012-01-01

Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

Efficacy of Rich Vocabulary Instruction in Fourth- and Fifth-Grade Classrooms

ERIC Educational Resources Information Center

Vadasy, Patricia F.; Sanders, Elizabeth A.; Logan Herrera, Becky

2015-01-01

A multi-cohort cluster randomized trial was conducted to estimate effects of rich vocabulary classroom instruction on vocabulary and reading comprehension. A total of 1,232 fourth- and fifth-grade students from 61 classrooms in 24 schools completed the study. Students received instruction in 140 Tier Two vocabulary words featured in two…

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Improved estimation of random vibration loads in launch vehicles

NASA Technical Reports Server (NTRS)

Mehta, R.; Erwin, E.; Suryanarayan, S.; Krishna, Murali M. R.

1993-01-01

Random vibration induced load is an important component of the total design load environment for payload and launch vehicle components and their support structures. The current approach to random vibration load estimation is based, particularly at the preliminary design stage, on the use of Miles' equation which assumes a single degree-of-freedom (DOF) system and white noise excitation. This paper examines the implications of the use of multi-DOF system models and response calculation based on numerical integration using the actual excitation spectra for random vibration load estimation. The analytical study presented considers a two-DOF system and brings out the effects of modal mass, damping and frequency ratios on the random vibration load factor. The results indicate that load estimates based on the Miles' equation can be significantly different from the more accurate estimates based on multi-DOF models.

Multi-wavelength Morphological Study Of Star Forming Regions In Nearby Cluster-rich Lirgs

NASA Astrophysics Data System (ADS)

Vavilkin, Tatjana; Evans, A.; Mazzarella, J.; Surace, J.; Kim, D.; Howell, J.; Armus, L.; GOALS Team

2009-05-01

Luminous Infrared Galaxies (LIRGs) are believed to play an important role in star formation history of the universe. Many LIRGs undergo intense bursts of star formation as a result of interaction/merger process. Given the dusty nature of LIRGs, it is necessary to probe Luminous Infrared Galaxies at multiple wavelengths. The Great Observatories All-sky LIRG Survey (GOALS) combines data from NASA's Spitzer, Hubble, Chandra and GALEX observatories and offers a unique opportunity to gain insights into the physical processes in these highly dust enshrouded systems. We examine a sample of 11 nearby (z < 0.03) cluster-rich (> 200 clusters as seen in HST ACS images) LIRG systems at various interaction stages. The combined HST ACS optical imaging, Spitzer IRAC 8 micron channel and GALEX near-UV imaging allows us to access the properties of visible and obscured star forming regions. We study the spatial distribution of star forming regions at these wavelengths, correlate locations of young stellar clusters with PAH and UV emission regions and trace changes with merger stage.

Prevention of low back pain and its consequences among nurses’ aides in elderly care: a stepped-wedge multi-faceted cluster-randomized controlled trial

PubMed Central

2013-01-01

Background A high prevalence of low back pain has persisted over the years despite extensive primary prevention initiatives among nurses’ aides. Many single-faceted interventions addressing just one aspect of low back pain have been carried out at workplaces, but with low success rate. This may be due to the multi-factorial origin of low back pain. Participatory ergonomics, cognitive behavioral training and physical training have previously shown promising effects on prevention and rehabilitation of low back pain. Therefore, the main aim of this study is to examine whether a multi-faceted workplace intervention consisting of participatory ergonomics, physical training and cognitive behavioral training can prevent low back pain and its consequences among nurses’ aides. External resources for the participating workplace and a strong commitment from the management and the organization support the intervention. Methods/design To overcome implementation barriers within usual randomized controlled trial designed workplace interventions, this study uses a stepped-wedge cluster-randomized controlled trial design with 4 groups. The intervention is delivered to the groups at random along four successive time periods three months apart. The intervention lasts three months and integrates participatory ergonomics, physical training and cognitive behavioral training tailored to the target group. Local physiotherapists and occupational therapists conduct the intervention after having received standardized training. Primary outcomes are low back pain and its consequences measured monthly by text messages up to three months after initiation of the intervention. Discussion Intervention effectiveness trials for preventing low back pain and its consequences in workplaces with physically demanding work are few, primarily single-faceted, with strict adherence to a traditional randomized controlled trial design that may hamper implementation and compliance, and have mostly been unsuccessful. By using a stepped wedge design, and obtain high management commitment and support we intend to improve implementation and aim to establish the effectiveness of a multi-faceted intervention to prevent low back pain. This study will potentially provide knowledge of prevention of low back pain and its consequences among nurses’ aides. Results are expected to be published in 2015–2016. Trial registration The study is registered as ISRCTN78113519. PMID:24261985

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

PubMed Central

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible non-parametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. PMID:24633656

Extending cluster lot quality assurance sampling designs for surveillance programs.

PubMed

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Family Functioning, Identity Formation, and the Ability of Conflict Resolution among Adolescents

ERIC Educational Resources Information Center

Kiani, Behnaz; Hojatkhah, Seyed Mohsen; Torabi-Nami, Mohammad

2016-01-01

Family is perhaps the most influential system in individuals' life in which various behaviors are learnt. Family functioning refers to the ability of family to meet its responsibilities. The present correlation study used a multi-stage cluster sampling method to recruit 686 subjects including 338 males and 348 females from all high school students…

Young People's Expressed Needs for Comprehensive Sexuality Education in Ecuadorian Schools

ERIC Educational Resources Information Center

Castillo Nuñez, Jessica; Derluyn, Ilse; Valcke, Martin

2018-01-01

This study analyses the expressed sexuality education needs of young people from Azuay, a region of Ecuador characterised by a large proportion of young people whose parents have migrated abroad, a group often considered at risk to developing of sexual health problems. Multi-stage stratified cluster sampling was used to recruit young people aged…

The Relationship between Utilization of Computer Games and Spatial Abilities among High School Students

ERIC Educational Resources Information Center

Motamedi, Vahid; Yaghoubi, Razeyah Mohagheghyan

2015-01-01

This study aimed at investigating the relationship between computer game use and spatial abilities among high school students. The sample consisted of 300 high school male students selected through multi-stage cluster sampling. Data gathering tools consisted of a researcher made questionnaire (to collect information on computer game usage) and the…

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark

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

Gittens, Alex; Kottalam, Jey; Yang, Jiyan

We investigate the performance and scalability of the randomized CX low-rank matrix factorization and demonstrate its applicability through the analysis of a 1TB mass spectrometry imaging (MSI) dataset, using Apache Spark on an Amazon EC2 cluster, a Cray XC40 system, and an experimental Cray cluster. We implemented this factorization both as a parallelized C implementation with hand-tuned optimizations and in Scala using the Apache Spark high-level cluster computing framework. We obtained consistent performance across the three platforms: using Spark we were able to process the 1TB size dataset in under 30 minutes with 960 cores on all systems, with themore » fastest times obtained on the experimental Cray cluster. In comparison, the C implementation was 21X faster on the Amazon EC2 system, due to careful cache optimizations, bandwidth-friendly access of matrices and vector computation using SIMD units. We report these results and their implications on the hardware and software issues arising in supporting data-centric workloads in parallel and distributed environments.« less

Design of a cluster-randomized minority recruitment trial: RECRUIT.

PubMed

Tilley, Barbara C; Mainous, Arch G; Smith, Daniel W; McKee, M Diane; Amorrortu, Rossybelle P; Alvidrez, Jennifer; Diaz, Vanessa; Ford, Marvella E; Fernandez, Maria E; Hauser, Robert A; Singer, Carlos; Landa, Veronica; Trevino, Aron; DeSantis, Stacia M; Zhang, Yefei; Daniels, Elvan; Tabor, Derrick; Vernon, Sally W

2017-06-01

Racial/ethnic minority groups remain underrepresented in clinical trials. Many strategies to increase minority recruitment focus on minority communities and emphasize common diseases such as hypertension. Scant literature focuses on minority recruitment to trials of less common conditions, often conducted in specialty clinics and dependent on physician referrals. We identified trust/mistrust of specialist physician investigators and institutions conducting medical research and consequent participant reluctance to participate in clinical trials as key-shared barriers across racial/ethnic groups. We developed a trust-based continuous quality improvement intervention to build trust between specialist physician investigators and community minority-serving physicians and ultimately potential trial participants. To avoid the inherent biases of non-randomized studies, we evaluated the intervention in the national Randomized Recruitment Intervention Trial (RECRUIT). This report presents the design of RECRUIT. Specialty clinic follow-up continues through April 2017. We hypothesized that specialist physician investigators and coordinators trained in the trust-based continuous quality improvement intervention would enroll a greater proportion of minority participants in their specialty clinics than specialist physician investigators in control specialty clinics. Specialty clinic was the unit of randomization. Using continuous quality improvement, the specialist physician investigators and coordinators tailored recruitment approaches to their specialty clinic characteristics and populations. Primary analyses were adjusted for clustering by specialty clinic within parent trial and matching covariates. RECRUIT was implemented in four multi-site clinical trials (parent trials) supported by three National Institutes of Health institutes and included 50 associated specialty clinics from these parent trials. Using current data, we have 88% power or greater to detect a 0.15 or greater difference from the currently observed control proportion adjusting for clustering. We detected no differences in baseline matching criteria between intervention and control specialty clinics (all p values > 0.17). RECRUIT was the first multi-site randomized control trial to examine the effectiveness of a trust-based continuous quality improvement intervention to increase minority recruitment into clinical trials. RECRUIT's innovations included its focus on building trust between specialist investigators and minority-serving physicians, the use of continuous quality improvement to tailor the intervention to each specialty clinic's specific racial/ethnic populations and barriers to minority recruitment, and the use of specialty clinics from more than one parent multi-site trial to increase generalizability. The effectiveness of the RECRUIT intervention will be determined after the completion of trial data collection and planned analyses.

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-10-26

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

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

PubMed

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

2005-03-01

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

The impact of sharing arrangement institution on beef cattle breeding performance in Kupang District, East Nusa Tenggara Province, Indonesia

NASA Astrophysics Data System (ADS)

Nono, O. H.; Natawidjaja, R.; Arief, B.; Suryadi, D.; Kapa, M. M. J.

2018-02-01

The aim of this study was to analyse the impact of sharing arrangement systems to performance of beef cattle breeding. This research was conducted in Kupang Regency - East Nusa Tenggara Province, Indonesia. The study used multi stage cluster random sampling method to determine the sample area and respondents. The sample areas consisted of 2 sub-districts and 6 villages, while the total respondents were 117 people comprised 74 Participant Farmers (PF) of sharing arrangement systems (SAS) and 43 non-participant farmers (NPF). 23 investors were selected for the survey. The result of the study indicated that the performance of NPF in terms of revenue, net profit, and return on investment (ROI) was better than PF respondents. The value of ROI was between 16.69-32.23 %. This indicated that utilization of farm asset was not optimum yet. It was found that farm efficiency was 1.73 which indicated that SAS does not increase farm productivity.

Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

NASA Astrophysics Data System (ADS)

Wang, M.; Wang, J.; Wang, B. T.

2018-02-01

Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Teachers' Methodologies and Sources of Information on HIV/AIDS for Students with Visual Impairments in Selected Residential and Integrated Schools in Ghana

ERIC Educational Resources Information Center

Hayford, Samuel K.; Ocansey, Frederick

2017-01-01

This study reports part of a national survey on sources of information, education and communication materials on HIV/AIDS available to students with visual impairments in residential, segregated, and integrated schools in Ghana. A multi-staged stratified random sampling procedure and a purposive and simple random sampling approach, where…

Acculturation Stress, Drinking, and Intimate Partner Violence among Hispanic Couples in the U.S

ERIC Educational Resources Information Center

Caetano, Raul; Ramisetty-Mikler, Suhasini; Caetano Vaeth, Patrice A.; Harris, T. Robert

2007-01-01

This article examines the cross-sectional association between acculturation, acculturation stress, drinking, and intimate partner violence (IPV) among Hispanic couples in the U.S. The data being analyzed come from a multi-cluster random household sample of couples interviewed as part of the second wave of a 5-year national longitudinal study. The…

Mid-course multi-target tracking using continuous representation

NASA Technical Reports Server (NTRS)

Zak, Michail; Toomarian, Nikzad

1991-01-01

The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.

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

PubMed

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 (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 system achieved behavior 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 Network clinical trials registry UMIN000001159.

Effects of cluster location and cluster distribution on performance on the traveling salesman problem.

PubMed

MacGregor, James N

2015-10-01

Research on human performance in solving traveling salesman problems typically uses point sets as stimuli, and most models have proposed a processing stage at which stimulus dots are clustered. However, few empirical studies have investigated the effects of clustering on performance. In one recent study, researchers compared the effects of clustered, random, and regular stimuli, and concluded that clustering facilitates performance (Dry, Preiss, & Wagemans, 2012). Another study suggested that these results may have been influenced by the location rather than the degree of clustering (MacGregor, 2013). Two experiments are reported that mark an attempt to disentangle these factors. The first experiment tested several combinations of degree of clustering and cluster location, and revealed mixed evidence that clustering influences performance. In a second experiment, both factors were varied independently, showing that they interact. The results are discussed in terms of the importance of clustering effects, in particular, and perceptual factors, in general, during performance of the traveling salesman problem.

Coherent Power Analysis in Multilevel Studies Using Parameters from Surveys

ERIC Educational Resources Information Center

Rhoads, Christopher

2017-01-01

Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…

Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana.

PubMed

Berens, D G; Braun, C; González-Martínez, S C; Griebeler, E M; Nathan, R; Böhning-Gaese, K

2014-11-01

Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.

A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

NASA Astrophysics Data System (ADS)

Tamiminia, Haifa; Homayouni, Saeid; McNairn, Heather; Safari, Abdoreza

2017-06-01

Polarimetric Synthetic Aperture Radar (PolSAR) data, thanks to their specific characteristics such as high resolution, weather and daylight independence, have become a valuable source of information for environment monitoring and management. The discrimination capability of observations acquired by these sensors can be used for land cover classification and mapping. The aim of this paper is to propose an optimized kernel-based C-means clustering algorithm for agriculture crop mapping from multi-temporal PolSAR data. Firstly, several polarimetric features are extracted from preprocessed data. These features are linear polarization intensities, and several statistical and physical based decompositions such as Cloude-Pottier, Freeman-Durden and Yamaguchi techniques. Then, the kernelized version of hard and fuzzy C-means clustering algorithms are applied to these polarimetric features in order to identify crop types. The kernel function, unlike the conventional partitioning clustering algorithms, simplifies the non-spherical and non-linearly patterns of data structure, to be clustered easily. In addition, in order to enhance the results, Particle Swarm Optimization (PSO) algorithm is used to tune the kernel parameters, cluster centers and to optimize features selection. The efficiency of this method was evaluated by using multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Manitoba, Canada, during June and July in 2012. The results demonstrate more accurate crop maps using the proposed method when compared to the classical approaches, (e.g. 12% improvement in general). In addition, when the optimization technique is used, greater improvement is observed in crop classification, e.g. 5% in overall. Furthermore, a strong relationship between Freeman-Durden volume scattering component, which is related to canopy structure, and phenological growth stages is observed.

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

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

USGS Publications Warehouse

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

2009-01-01

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

Mediating Factors of a School-Based Multi-Component Smoking Prevention Intervention: The LdP Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Carreras, G.; Bosi, S.; Angelini, P.; Gorini, G.

2016-01-01

The aim of this study was to investigate factors mediating the effects of Luoghi di Prevenzione (LdP) smoking prevention intervention based on social competence and social influence approaches, and characterized by peer-led school-based interventions, out-of-school workshops, school lessons, and by enforcing the school anti-smoking policy.…

Apparatus for simultaneously disreefing a centrally reefed clustered parachute system

DOEpatents

Johnson, Donald W.

1988-01-01

A single multi-line cutter is connected to each of a cluster of parachutes by a separate short tether line that holds the parachutes, initially reefed by closed loop reefing lines, close to one another. The closed loop reefing lines and tether lines, one from each parachute, are disposed within the cutter to be simultaneously cut by its actuation when a central line attached between the payload and the cutter is stretched upon deployment of the cluster. A pyrotechnic or electronic time delay may be included in the cutter to delay the actual simultaneous cutting of all lines until the clustered parachutes attain a measure of stability prior to being disreefed. A second set of reefing lines and second tether lines may be provided for each parachute, to enable a two-stage, separately timed, step-by-step disreefing.

Apparatus for simultaneously disreefing a centrally reefed clustered parachute system

DOEpatents

Johnson, D.W.

1988-06-21

A single multi-line cutter is connected to each of a cluster of parachutes by a separate short tether line that holds the parachutes, initially reefed by closed loop reefing lines, close to one another. The closed loop reefing lines and tether lines, one from each parachute, are disposed within the cutter to be simultaneously cut by its actuation when a central line attached between the payload and the cutter is stretched upon deployment of the cluster. A pyrotechnic or electronic time delay may be included in the cutter to delay the actual simultaneous cutting of all lines until the clustered parachutes attain a measure of stability prior to being disreefed. A second set of reefing lines and second tether lines may be provided for each parachute, to enable a two-stage, separately timed, step-by-step disreefing. 13 figs.

Radiation breakage of DNA: a model based on random-walk chromatin structure

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Sachs, R. K.

2001-01-01

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

Subtypes of firesetters.

PubMed

Dalhuisen, Lydia; Koenraadt, Frans; Liem, Marieke

2017-02-01

Prior research has classified firesetters by motive. The multi-trajectory theory of adult firesetting (M-TTAF) takes a more aetiological perspective, differentiating between five hypothesised trajectories towards firesetting: antisocial cognition, grievance, fire interest, emotionally expressive/need for recognition and multifaceted trajectories. The objective of this study was to validate the five routes to firesetting as proposed in the M-TTAF. All 389 adult firesetters referred for forensic mental health assessment to one central clinic in the Netherlands between 1950 and 2012 were rated on variables linked to the M-TTAF. Cluster analysis was then applied. A reliable cluster solution emerged revealing five subtypes of firesetters - labelled instrumental, reward, multi-problem, disturbed relationship and disordered. Significant differences were observed regarding both offender and offence characteristics. Our five-cluster solution with five subtypes of firesetters partially validates the proposed M-TTAF trajectories and suggests that for offenders with and without mental disorder, this classification may be useful. If further validated with larger and more diverse samples, the M-TTAF could provide guidance on staging evidence-based treatment. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Duration of Sleep and ADHD Tendency among Adolescents in China

ERIC Educational Resources Information Center

Lam, Lawrence T.; Yang, L.

2008-01-01

Objective: This study investigates the association between duration of sleep and ADHD tendency among adolescents. Method: This population-based health survey uses a two-stage random cluster sampling design. Participants ages 13 to 17 are recruited from the total population of adolescents attending high school in one city of China. Duration of…

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

PubMed Central

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

2016-01-01

Objective 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. Method 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. Results 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. Conclusions The Teen Choices program provides an effective and practicable strategy for intervention for teen dating violence prevention. PMID:27482470

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

PubMed

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.

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.

Efficacy, Safety and Cost of Insecticide Treated Wall Lining, Insecticide Treated Bed Nets and Indoor Wall Wash with Lime for Visceral Leishmaniasis Vector Control in the Indian Sub-continent: A Multi-country Cluster Randomized Controlled Trial

PubMed Central

Das, Pradeep; Ghosh, Debashis; Priyanka, Jyoti; Matlashewski, Greg; Kroeger, Axel; Upfill-Brown, Alexander

2016-01-01

Background We investigated the efficacy, safety and cost of lime wash of household walls plus treatment of sand fly breeding places with bleach (i.e. environmental management or EM), insecticide impregnated durable wall lining (DWL), and bed net impregnation with slow release insecticide (ITN) for sand fly control in the Indian sub-continent. Methods This multi-country cluster randomized controlled trial had 24 clusters in each three sites with eight clusters per high, medium or low sand fly density stratum. Every cluster included 45–50 households. Five households from each cluster were randomly selected for entomological measurements including sand fly density and mortality at one, three, nine and twelve months post intervention. Household interviews were conducted for socioeconomic information and intervention acceptability assessment. Cost for each intervention was calculated. There was a control group without intervention. Findings Sand fly mortality [mean and 95%CI] ranged from 84% (81%-87%) at one month to 74% (71%-78%) at 12 months for DWL, 75% (71%-79%) at one month to 49% (43%-55%) at twelve months for ITN, and 44% (34%-53%) at one month to 22% (14%-29%) at twelve months for EM. Adjusted intervention effect on sand fly density measured by incidence rate ratio ranged from 0.28 (0.23–0.34) at one month to 0.62 (0.51–0.75) at 12 months for DWL; 0.72 (0.62–0.85) at one month to 1.02 (0.86–1.22) at 12 months for ITN; and 0.89 (0.76–1.03) at one months to 1.49 (1.26–1.74) at 12 months for EM. Household acceptance of EM was 74% compared to 94% for both DWL and ITN. Operational cost per household in USD was about 5, 8, and 2 for EM, DWL and ITN, respectively. Minimal adverse reactions were reported for EM and ITN while 36% of households with DWL reported transient itching. Interpretation DWL is the most effective, durable and acceptable control method followed by ITN. The Visceral Leishmaniasis (VL) Elimination Program in the Indian sub-continent should consider DWL and ITN for sand fly control in addition to IRS. PMID:27533097

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Enhancing Community Knowledge and Health Behaviors to Eliminate Blinding Trachoma in Mali Using Radio Messaging as a Strategy

ERIC Educational Resources Information Center

Bamani, Sanoussi; Toubali, Emily; Diarra, Sadio; Goita, Seydou; Berte, Zana; Coulibaly, Famolo; Sangare, Hama; Tuinsma, Marjon; Zhang, Yaobi; Dembele, Benoit; Melvin, Palesa; MacArthur, Chad

2013-01-01

The National Blindness Prevention Program in Mali has broadcast messages on the radio about trachoma as part of the country's trachoma elimination strategy since 2008. In 2011, a radio impact survey using multi-stage cluster sampling was conducted in the regions of Kayes and Segou to assess radio listening habits, coverage of the broadcasts,…

Private Universities in Kenya Seek Alternative Ways to Manage Change in Teacher Education Curriculum in Compliance with the Commission for University Education Reforms

ERIC Educational Resources Information Center

Amimo, Catherine Adhiambo

2016-01-01

This study investigated management of change in teacher education curriculum in Private universities in Kenya. The study employed a concurrent mixed methods design that is based on the use of both quantitative and qualitative approaches. A multi-stage sampling process which included purposive, convenience, cluster, and snowball sampling methods…

A multi-assets artificial stock market with zero-intelligence traders

NASA Astrophysics Data System (ADS)

Ponta, L.; Raberto, M.; Cincotti, S.

2011-01-01

In this paper, a multi-assets artificial financial market populated by zero-intelligence traders with finite financial resources is presented. The market is characterized by different types of stocks representing firms operating in different sectors of the economy. Zero-intelligence traders follow a random allocation strategy which is constrained by finite resources, past market volatility and allocation universe. Within this framework, stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Moreover, the cross-correlations between returns of different stocks are studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. It is worth noting that business sectors have been recovered in our framework without dividends as only consequence of random restrictions on the allocation universe of zero-intelligence traders. Furthermore, in the presence of dividend-paying stocks and in the case of cash inflow added to the market, the artificial stock market points out the same structural results obtained in the simulation without dividends. These results suggest a significative structural influence on statistical properties of multi-assets stock market.

Efficient Ab initio Modeling of Random Multicomponent Alloys

DOE PAGES

Jiang, Chao; Uberuaga, Blas P.

2016-03-08

Here, we present in this Letter a novel small set of ordered structures (SSOS) method that allows extremely efficient ab initio modeling of random multi-component alloys. Using inverse II-III spinel oxides and equiatomic quinary bcc (so-called high entropy) alloys as examples, we also demonstrate that a SSOS can achieve the same accuracy as a large supercell or a well-converged cluster expansion, but with significantly reduced computational cost. In particular, because of this efficiency, a large number of quinary alloy compositions can be quickly screened, leading to the identification of several new possible high entropy alloy chemistries. Furthermore, the SSOS methodmore » developed here can be broadly useful for the rapid computational design of multi-component materials, especially those with a large number of alloying elements, a challenging problem for other approaches.« less

Structured patient handoff on an internal medicine ward: A cluster randomized control trial.

PubMed

Tam, Penny; Nijjar, Aman P; Fok, Mark; Little, Chris; Shingina, Alexandra; Bittman, Jesse; Raghavan, Rashmi; Khan, Nadia A

2018-01-01

The effect of a multi-faceted handoff strategy in a high volume internal medicine inpatient setting on process and patient outcomes has not been clearly established. We set out to determine if a multi-faceted handoff intervention consisting of education, standardized handoff procedures, including fixed time and location for face-to-face handoff would result in improved rates of handoff compared with usual practice. We also evaluated resident satisfaction, health resource utilization and clinical outcomes. This was a cluster randomized controlled trial in a large academic tertiary care center with 18 inpatient internal medicine ward teams from January-April 2013. We randomized nine inpatient teams to an intervention where they received an education session standardizing who and how to handoff patients, with practice and feedback from facilitators. The control group of 9 teams continued usual non-standardized handoffs. The primary process outcome was the rate of patients handed over per 1000 patient nights. Other process outcomes included perceptions of inadequate handoff by overnight physicians, resource utilization overnight and hospital length of stay. Clinical outcomes included medical errors, frequency of patients requiring higher level of care overnight, and in-hospital mortality. The intervention group demonstrated a significant increase in the rate of patients handed over to the overnight physician (62.90/1000 person-nights vs. 46.86/1000 person-nights, p = 0.002). There was no significant difference in other process outcomes except resource utilization was increased in the intervention group (26.35/1000 person-days vs. 17.57/1000 person-days, p-value = 0.01). There was no significant difference between groups in medical errors (4.8% vs. 4.1%), need for higher level of care or in hospital mortality. Limitations include a dependence of accurate record keeping by the overnight physician, the possibility of cross-contamination in the handoff process, analysis at the cluster level and an overall low number of clinical events. Implementation of a multi-faceted resident handoff intervention did not result in a significant improvement in patient safety although did improve number of patients handed off. Novel methods to improve handoff need to be explored. Registered at ClinicalTrials.gov: NCT01796756.

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

PubMed Central

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

Objectives 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. Design Stratified open cluster-randomized trial. Setting A total of 489 GPs belonging to 49 local medical associations (clusters) in Japan. Participants 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. Intervention 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. Main outcome measure 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. Results 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). Conclusion Our care system achieved behavior 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. Trial registration The University Hospital Medical Information Network clinical trials registry UMIN000001159 PMID:26999730

Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

PubMed Central

Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

2012-01-01

Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

Vector nature of multi-soliton patterns in a passively mode-locked figure-eight fiber laser.

PubMed

Ning, Qiu-Yi; Liu, Hao; Zheng, Xu-Wu; Yu, Wei; Luo, Ai-Ping; Huang, Xu-Guang; Luo, Zhi-Chao; Xu, Wen-Cheng; Xu, Shan-Hui; Yang, Zhong-Min

2014-05-19

The vector nature of multi-soliton dynamic patterns was investigated in a passively mode-locked figure-eight fiber laser based on the nonlinear amplifying loop mirror (NALM). By properly adjusting the cavity parameters such as the pump power level and intra-cavity polarization controllers (PCs), in addition to the fundamental vector soliton, various vector multi-soliton regimes were observed, such as the random static distribution of vector multiple solitons, vector soliton cluster, vector soliton flow, and the state of vector multiple solitons occupying the whole cavity. Both the polarization-locked vector solitons (PLVSs) and the polarization-rotating vector solitons (PRVSs) were observed for fundamental soliton and each type of multi-soliton patterns. The obtained results further reveal the fundamental physics of multi-soliton patterns and demonstrate that the figure-eight fiber lasers are indeed a good platform for investigating the vector nature of different soliton types.

An Association between Bullying Behaviors and Alcohol Use among Middle School Students

ERIC Educational Resources Information Center

Peleg-Oren, Neta; Cardenas, Gabriel A.; Comerford, Mary; Galea, Sandro

2012-01-01

Although a high prevalence of bullying behaviors among adolescents has been documented, little is known about the association between bullying behaviors and alcohol use among perpetrators or victims. This study used data from a representative two-stage cluster random sample of 44, 532 middle school adolescents in Florida. We found a high…

Stage-dependent remodeling of the nuclear envelope and lamina during rabbit early embryonic development.

PubMed

Popken, Jens; Schmid, Volker J; Strauss, Axel; Guengoer, Tuna; Wolf, Eckhard; Zakhartchenko, Valeri

2016-04-22

Utilizing 3D structured illumination microscopy, we investigated the quality and quantity of nuclear invaginations and the distribution of nuclear pores during rabbit early embryonic development and identified the exact time point of nucleoporin 153 (NUP153) association with chromatin during mitosis. Contrary to bovine early embryonic nuclei, featuring almost exclusively nuclear invaginations containing a small volume of cytoplasm, nuclei in rabbit early embryonic stages show additionally numerous invaginations containing a large volume of cytoplasm. Small-volume invaginations frequently emanated from large-volume nuclear invaginations but not vice versa, indicating a different underlying mechanism. Large- and small-volume nuclear envelope invaginations required the presence of chromatin, as they were restricted to chromatin-positive areas. The chromatin-free contact areas between nucleolar precursor bodies (NPBs) and large-volume invaginations were free of nuclear pores. Small-volume invaginations were not in contact with NPBs. The number of invaginations and isolated intranuclear vesicles per nucleus peaked at the 4-cell stage. At this stage, the nuclear surface showed highly concentrated clusters of nuclear pores surrounded by areas free of nuclear pores. Isolated intranuclear lamina vesicles were usually NUP153 negative. Cytoplasmic, randomly distributed NUP153-positive clusters were highly abundant at the zygote stage and decreased in number until they were almost absent at the 8-cell stage and later. These large NUP153 clusters may represent a maternally provided NUP153 deposit, but they were not visible as clusters during mitosis. Major genome activation at the 8- to 16-cell stage may mark the switch from a necessity for a deposit to on-demand production. NUP153 association with chromatin is initiated during metaphase before the initiation of the regeneration of the lamina. To our knowledge, the present study demonstrates for the first time major remodeling of the nuclear envelope and its underlying lamina during rabbit preimplantation development.

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

PubMed

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.

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

Wang, Lin -Lin; Johnson, Duane D.; Tringides, Michael C.

Density functional theory is used to study structural energetics of Pb vacancy cluster formation on C 60/Pb/Si(111) to explain the unusually fast and error-free transformations between the “Devil's Staircase” (DS) phases on the Pb/Si(111) wetting layer at low temperature (~110K). The formation energies of vacancy clusters are calculated in C 60/Pb/Si(111) as Pb atoms are progressively ejected from the initial dense Pb wetting layer. Vacancy clusters larger than five Pb atoms are found to be stable with seven being the most stable, while vacancy clusters smaller than five are highly unstable, which agrees well with the observed ejection rate ofmore » ~5 Pb atoms per C 60. Furthermore, the high energy cost (~0.8 eV) for the small vacancy clusters to form indicates convincingly that the unusually fast transformation observed experimentally between the DS phases, upon C 60 adsorption at low temperature, cannot be the result of single-atom random walk diffusion but of correlated multi-atom processes.« less

[Cigarette consumer price and affordability in China: results from 2015 China adult survey].

PubMed

Wang, L L; Yang, Y; Nan, Y; Tu, M W; Wang, J J; Jiang, Y

2017-01-10

Objective: To analyze the change of cigarette consumption price, and understand the cigarette affordability in China. Methods: A total of 16 800 households were selected through multi-stage stratified cluster sampling. Then IPAQ was used to randomly select one family member to conduct the survey. Questionnaire from Global Tobacco Surveillance System with added country-specific questions was used. Results: Up to 50 % of current smokers would buy 20 cigarettes with price of 9.9 yuan (RMB) or less, and 25 % of current smokers would not buy 20 cigarettes with price exceed 5.5 yuan (RMB). Only 10 % would buy 20 cigarettes with price over 19.9 yuan (RMB). The calculated median monthly expenditure for cigarettes was 181.4 yuan (RMB). From 2010 to 2015, the proportion of annual expenditure for cigarettes in disposable income per capita declined from 10.5 % to 8.8 % in urban area and from 21.1 % to 17.3 % in rural area. Conclusion: During 2010-2015, the purchasing power of Chinese smokers increased in both urban area and rural area due to the decrease of cigarette consumption price.

[Influences of life event and coping style on left-behind middle school student mental health in a three-gorge area county].

PubMed

Wu, Rui; Li, Jianqiao; Liu, Qin; Wang, Hong

2014-07-01

To study the effects of life event and coping style on left-behind middle school student mental health. 1405 left-behind middle school students were selected by multi-stage cluster random sampling method and investigated with Middle School Student Mental Health Scale (MSSMHS), Multidimensional Life Events Rating Questionnaire for Middle School Students (MLERQ) and Trait Coping Style Questionnaire (TCSQ). The mental health detection rate of left-behind middle school students was 26.33%. Life event have significant influence on mental health (F = 447.624, P = 0.000). The main effect for negative coping style on mental health was significant (F = 263.669, P = 0.000). Positive coping style have effect on mental health but the main effect was not significant (F = 2.436, P = 0.119). The interaction effect of life event and negative coping style was significant (F = 23.173, P = 0.000). Life event and coping style has a certain effect on left-behind middle school student mental health, but its mechanism is complicated and still uncertain.

Analysis on leisure patterns of the pre-elderly adults.

PubMed

Cho, Gun-Sang; Yi, Eun-Surk

2013-01-01

The purpose of study is to analyze how leisure activities affect the near elders' preparation for successful and productive aging. To achieve the purpose of the study, this study was conducted in 2012 and the data was collected by using multi-stage stratified cluster random sampling method in the great city area (6 places), metropolitan area (7 places), medium-sized urban area (6 places), and rural area (6 places). Out of the total number of 1,000 copies of questionnaire distributed to pre-elders (Baby-boomers from 55 yr to 64 yr), 978 were collected and used for data analysis. According to the result, the more time, frequency and intensity in leisure and recreational participation, the higher the satisfaction level and the happiness level in their life. It means that leisure and recreational activities play an important role for their life. In other words, for pre-elders, leisure activities can be regarded as the important element for preparation of their old age. Therefore, the leisure and recreation for pre-elderly adults should not be recognized as a tool for improving the economic productivity but for reinforcing the recovery resilience.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications.

PubMed

Karyotis, Vasileios; Tsitseklis, Konstantinos; Sotiropoulos, Konstantinos; Papavassiliou, Symeon

2018-04-15

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications

PubMed Central

Sotiropoulos, Konstantinos

2018-01-01

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan–Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing. PMID:29662043

What Works in Gifted Education Mathematics Study: Impact of Pre-Differentiated and Enriched Curricula on General Education Teachers and Their Students. Research Monograph Series. RM13242

ERIC Educational Resources Information Center

Gubbins, E. Jean; McCoach, D. Betsy; Foreman, Jennifer L.; Gilson, Cindy M.; Bruce-Davis, Micah N.; Rubenstein, Lisa DaVia; Savino, Jennifer; Rambo, Karen; Waterman, Craig

2013-01-01

The present study seeks to determine how exposure to pre-differentiated and enriched curricula incorporating educative curriculum materials affects students' achievement as well as teacher and administrator responses to the intervention. A 2-year multi-site cluster randomized control trial study recruited a national sample of 4,530 grade 3…

Effect of behavioral stage-based nutrition education on management of osteodystrophy among hemodialysis patients, Lebanon.

PubMed

Karavetian, Mirey; de Vries, Nanne; Elzein, Hafez; Rizk, Rana; Bechwaty, Fida

2015-09-01

Assess the effect of intensive nutrition education by trained dedicated dietitians on osteodystrophy management among hemodialysis patients. Randomized controlled trial in 12 hospital-based hemodialysis units equally distributed over clusters 1 and 2. Cluster 1 patients were either assigned to usual care (n=96) or to individualized intensive staged-based nutrition education by a dedicated renal dietitian (n=88). Cluster 2 patients (n=210) received nutrition education from general hospital dietitians, educating their patients at their spare time from hospital duties. Main outcomes were: (1) dietary knowledge(%), (2) behavioral change, (3) serum phosphorus (mmol/L), each measured at T0 (baseline), T1 (post 6 month intervention) and T2 (post 6 month follow up). Significant improvement was found only among patients receiving intensive education from a dedicated dietitian at T1; the change regressed at T2 without statistical significance: knowledge (T0: 40.3; T1: 64; T2: 63) and serum phosphorus (T0: 1.79; T1: 1.65; T2: 1.70); behavioral stages changed significantly throughout the study (T0: Preparation, T1: Action, T2: Preparation). The intensive protocol showed to be the most effective. Integrating dedicated dietitians and stage-based education in hemodialysis units may improve the nutritional management of patients in Lebanon and countries with similar health care systems. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Computational Plume Modeling of COnceptual ARES Vehicle Stage Tests

NASA Technical Reports Server (NTRS)

Allgood, Daniel C.; Ahuja, Vineet

2007-01-01

The plume-induced environment of a conceptual ARES V vehicle stage test at the NASA Stennis Space Center (NASA-SSC) was modeled using computational fluid dynamics (CFD). A full-scale multi-element grid was generated for the NASA-SSC B-2 test stand with the ARES V stage being located in a proposed off-center forward position. The plume produced by the ARES V main power plant (cluster of five RS-68 LOX/LH2 engines) was simulated using a multi-element flow solver - CRUNCH. The primary objective of this work was to obtain a fundamental understanding of the ARES V plume and its impingement characteristics on the B-2 flame-deflector. The location, size and shape of the impingement region were quantified along with the un-cooled deflector wall pressures, temperatures and incident heating rates. Issues with the proposed tests were identified and several of these addressed using the CFD methodology. The final results of this modeling effort will provide useful data and boundary conditions in upcoming engineering studies that are directed towards determining the required facility modifications for ensuring safe and reliable stage testing in support of the Constellation Program.

Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing

PubMed Central

Abubaker, Ahmad; Baharum, Adam; Alrefaei, Mahmoud

2015-01-01

This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, “MOPSOSA”. The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-Objective Simulated Annealing (MOSA). Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets. PMID:26132309

Establishing the Baseline Height and Weight Status of New Hampshire Head Start Children, 2007-2008

ERIC Educational Resources Information Center

Blaney, David D.; Flynn, Regina T.; Martin, Nancy R.; Anderson, Ludmila

2010-01-01

We report on a standardized survey of height and weight status of children attending the New Hampshire Head Start Program during the 2007-2008 school year. Baseline prevalence estimates of overweight and obesity are needed for obesity prevention activities and intervention. We selected a random one-stage cluster sample and screened 629 children…

Growth of neurites toward neurite- neurite contact sites increases synaptic clustering and secretion and is regulated by synaptic activity.

PubMed

Cove, Joshua; Blinder, Pablo; Abi-Jaoude, Elia; Lafrenière-Roula, Myriam; Devroye, Luc; Baranes, Danny

2006-01-01

The integrative properties of dendrites are determined by several factors, including their morphology and the spatio-temporal patterning of their synaptic inputs. One of the great challenges is to discover the interdependency of these two factors and the mechanisms which sculpt dendrites' fine morphological details. We found a novel form of neurite growth behavior in neuronal cultures of the hippocampus and cortex, when axons and dendrites grew directly toward neurite-neurite contact sites and crossed them, forming multi-neurite intersections (MNIs). MNIs were found at a frequency higher than obtained by computer simulations of randomly distributed dendrites, involved many of the dendrites and were stable for days. They were formed specifically by neurites originating from different neurons and were extremely rare among neurites of individual neurons or among astrocytic processes. Axonal terminals were clustered at MNIs and exhibited higher synaptophysin content and release capability than in those located elsewhere. MNI formation, as well as enhancement of axonal terminal clustering and secretion at MNIs, was disrupted by inhibitors of synaptic activity. Thus, convergence of axons and dendrites to form MNIs is a non-random activity-regulated wiring behavior which shapes dendritic trees and affects the location, clustering level and strength of their presynaptic inputs.

A Separable Two-Dimensional Random Field Model of Binary Response Data from Multi-Day Behavioral Experiments.

PubMed

Malem-Shinitski, Noa; Zhang, Yingzhuo; Gray, Daniel T; Burke, Sara N; Smith, Anne C; Barnes, Carol A; Ba, Demba

2018-04-18

The study of learning in populations of subjects can provide insights into the changes that occur in the brain with aging, drug intervention, and psychiatric disease. We introduce a separable two-dimensional (2D) random field (RF) model for analyzing binary response data acquired during the learning of object-reward associations across multiple days. The method can quantify the variability of performance within a day and across days, and can capture abrupt changes in learning. We apply the method to data from young and aged macaque monkeys performing a reversal-learning task. The method provides an estimate of performance within a day for each age group, and a learning rate across days for each monkey. We find that, as a group, the older monkeys require more trials to learn the object discriminations than do the young monkeys, and that the cognitive flexibility of the younger group is higher. We also use the model estimates of performance as features for clustering the monkeys into two groups. The clustering results in two groups that, for the most part, coincide with those formed by the age groups. Simulation studies suggest that clustering captures inter-individual differences in performance levels. In comparison with generalized linear models, this method is better able to capture the inherent two-dimensional nature of the data and find between group differences. Applied to binary response data from groups of individuals performing multi-day behavioral experiments, the model discriminates between-group differences and identifies subgroups. Copyright © 2018. Published by Elsevier B.V.

Cluster growth mechanisms in Lennard-Jones fluids: A comparison between molecular dynamics and Brownian dynamics simulations

NASA Astrophysics Data System (ADS)

Jung, Jiyun; Lee, Jumin; Kim, Jun Soo

2015-03-01

We present a simulation study on the mechanisms of a phase separation in dilute fluids of Lennard-Jones (LJ) particles as a model of self-interacting molecules. Molecular dynamics (MD) and Brownian dynamics (BD) simulations of the LJ fluids are employed to model the condensation of a liquid droplet in the vapor phase and the mesoscopic aggregation in the solution phase, respectively. With emphasis on the cluster growth at late times well beyond the nucleation stage, we find that the growth mechanisms can be qualitatively different: cluster diffusion and coalescence in the MD simulations and Ostwald ripening in the BD simulations. We also show that the rates of the cluster growth have distinct scaling behaviors during cluster growth. This work suggests that in the solution phase the random Brownian nature of the solute dynamics may lead to the Ostwald ripening that is qualitatively different from the cluster coalescence in the vapor phase.

The Alignment effect of brightest cluster galaxies in the SDSS

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

Kim, R. S. J.; Annis, J.; Strauss, M. A.

2001-10-01

One of the most vital observational clues for unraveling the origin of Brightest Cluster Galaxies (BCG) is the observed alignment of the BCGs with their host cluster and its surroundings. We have examined the BCG-cluster alignment effect, using clusters of galaxies detected from the Sloan Digital Sky Survey (SDSS). We find that the BCGs are preferentially aligned with the principal axis of their hosts, to a much higher redshift (z >~ 0.3) than probed by previous studies (z <~ 0.1). The alignment effect strongly depends on the magnitude difference of the BCG and the second and third brightest cluster members:more » we find a strong alignment effect for the dominant BCGs, while less dominant BCGs do not show any departure from random alignment with respect to the cluster. We therefore claim that the alignment process originates from the same process that makes the BCG grow dominant, be it direct mergers in the early stage of cluster formation, or a later process that resembles the galactic cannibalism scenario. We do not find strong evidence for (or against) redshift evolution between 0« less

Individualization as Driving Force of Clustering Phenomena in Humans

PubMed Central

Mäs, Michael; Flache, Andreas; Helbing, Dirk

2010-01-01

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering. PMID:20975937

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Prescribing Patterns in Outpatient Clinics of Township Hospitals in China: A Comparative Study before and after the 2009 Health System Reform.

PubMed

Ding, Ding; Pan, Qingxia; Shan, Linghan; Liu, Chaojie; Gao, Lijun; Hao, Yanhua; Song, Jian; Ning, Ning; Cui, Yu; Li, Ye; Qi, Xinye; Liang, Chao; Wu, Qunhong; Liu, Guoxiang

2016-07-05

China introduced a series of health reforms in 2009, including a national essential medicines policy and a medical insurance system for primary care institutions. This study aimed to determine the changing prescribing patterns associated with those reforms in township hospitals. A multi-stage stratified random cluster sampling method was adopted to identify 29 township hospitals from six counties in three provinces. A total of 2899 prescriptions were collected from the participating township hospitals using a systematic random sampling strategy. Seven prescribing indicators were calculated and compared between 2008 and 2013, assessing use of medicines (antibiotics and adrenal corticosteroids) and polypharmacy, administration route of medicines (injections), and affordability of medicines. Significant changes in prescribing patterns were found. The average number of medicines and costs per-prescription dropped by about 50%. The percentage of prescriptions requiring antibiotics declined from 54% to 38%. The percentage of prescriptions requiring adrenal corticosteroid declined from 14% to 4%. The percentage of prescriptions requiring injections declined from 54% to 25%. Despite similar changing patterns, significant regional differences were observed. Significant changes in prescribing patterns are evident in township hospitals in China. Overprescription of antibiotics, injections and adrenal corticosteroids has been reduced. However, salient regional disparities still exist. Further studies are needed to determine potential shifts in the risk of the inappropriate use of medicines from primary care settings to metropolitan hospitals.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

[Amplicon density-weighted algorithms for analyzing dissimilarity and dynamic alterations of RAPD polymorphisms of Cordyceps sinensis].

PubMed

Yao, Yi-sang; Gao, Ling; Li, Yu-ling; Ma, Shao-li; Wu, Zi-mei; Tan, Ning-zhi; Wu, Jian-yong; Ni, Lu-qun; Zhu, Jia-shi

2014-08-18

To examine the dynamic maturational alterations of random amplified polymorphic DNA (RAPD) molecular marker polymorphism resulted from differential expressions of multiple fungi in the caterpillar body, stroma and ascocarp portion of Cordyceps sinensis (Cs). Used the fuzzy, integral RAPD molecular marker polymorphism method with 20 random primers; used density-weighted cluster algorithms and ZUNIX similarity equations; compared RAPD polymorphisms of the caterpillar body, stroma and ascocarp of Cs during maturation; and compared RAPD polymorphisms of Cs and Hirsutella sinensis (Hs). Density-unweighted algorithms neglected the differences in density of the DNA amplicons. Use of the density-weighted ZUNIX similarity equations and the clustering method integrated components of the amplicon density differences in similarity computations and clustering construction and prevented from the loss of the information of fungal genomes. An overall similarity 0.42 (< the overall dissimilarity 0.58) was observed for all compartments of Cs at different maturation stages. The similarities for the stromata or caterpillar bodies of Cs at 3 maturational stages were 0.57 or 0.50, respectively. During Cs maturation, there were dynamic Low→High→Low alterations of the RAPD polymorphisms between stromata and caterpillar bodies dissected from the same pieces of Cs. The polymorphic similarity was the highest (0.87) between the ascocarp and mature stroma, forming a clustering clade, while the premature stroma and caterpillar body formed another clade. These 2 clades merged into one cluster. Another clade containing the maturing stroma and caterpillar body merged with mature caterpillar body, forming another cluster. The RAPD polymorphic similarities between Hs and Cs samples were 0.55-0.69. Hs were separated from Cs clusters by the out-group control Paecilomyces militaris. The wealthy RAPD polymorphisms change dynamically in the Cs compartments with maturation. The different RAPD polymorphism for Hs from those for Cs supports the hypothesis of integrated micro-ecosystem Cs with multiple fungi, but does not support the "single fungal species" hypothesis for Cs and the anamorph-teleomorph connection between Hs and Cs.

Evaluation of Seeds of Science/Roots of Reading: Effective Tools for Developing Literacy through Science in the Early Grades-Light Energy Unit. CRESST Report 781

ERIC Educational Resources Information Center

Goldschmidt, Pete; Jung, Hyekyung

2011-01-01

This evaluation focuses on the Seeds of Science/Roots of Reading: Effective Tools for Developing Literacy through Science in the Early Grades ("Seeds/Roots") model of science-literacy integration. The evaluation is based on a cluster randomized design of 100 teachers, half of which were in the treatment group. Multi-level models are employed to…

Structuring Communication Relationships for Interprofessional Teamwork (SCRIPT): a cluster randomized controlled trial.

PubMed

Zwarenstein, Merrick; Reeves, Scott; Russell, Ann; Kenaszchuk, Chris; Conn, Lesley Gotlib; Miller, Karen-Lee; Lingard, Lorelei; Thorpe, Kevin E

2007-09-18

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. 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. 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. Pre-intervention qualitative analysis revealed that a substantial amount of interprofessional interaction lacks key core elements of collaborative communication such as self-introduction, description of professional role, and solicitation of other professional perspectives. Incorporating these findings, a four-component intervention was designed with a goal of creating a culture of communication in which the fundamentals of collaboration become a routine part of interprofessional interactions during unstructured work periods on GIM wards. Registered with National Institutes of Health as NCT00466297.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

PubMed

Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Development of Effective Teacher Program: Teamwork Building Program for Thailand's Municipal Schools

ERIC Educational Resources Information Center

Chantathai, Pimpka; Tesaputa, Kowat; Somprach, Kanokorn

2015-01-01

This research is aimed to formulate the effective teacher teamwork program in municipal schools in Thailand. Primary survey on current situation and problem was conducted to develop the plan to suggest potential programs. Samples were randomly selected from municipal schools by using multi-stage sampling method in order to investigate their…

Behavioural Problems of Juvenile Street Hawkers in Uyo Metropolis, Nigeria

ERIC Educational Resources Information Center

Udoh, Nsisong A.; Joseph, Eme U.

2012-01-01

The study sought the opinions of Faculty of Education Students of University of Uyo on the behavioural problems of juvenile street hawkers in Uyo metropolis. Five research hypotheses were formulated to guide the study. This cross-sectional survey employed multi-stage random sampling technique in selecting 200 regular undergraduate students in the…

The Impact of Education on Rural Women's Participation in Political and Economic Activities

ERIC Educational Resources Information Center

Bishaw, Alemayehu

2014-01-01

This study endeavored to investigate the impact of education on rural women's participation in political and economic activities. Six hundred rural women and 12 gender Activists were selected for this study from three Zones of Amhara Region, Ethiopia using multi-stage random sampling technique and purposeful sampling techniques respectively.…

Influence of exposure differences on city-to-city heterogeneity ...

EPA Pesticide Factsheets

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate. The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001–2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates. Associations between a 2-day (lag 0–1 days) moving average of PM2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from −3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m3 increase in PM2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effe

High energy neutrinos and gamma-ray emission from supernovae in compact star clusters

NASA Astrophysics Data System (ADS)

Bykov, A. M.; Ellison, D. C.; Gladilin, P. E.; Osipov, S. M.

2017-01-01

Compact clusters of young massive stars are observed in the Milky Way and in starburst galaxies. The compact clusters with multiple powerful winds of young massive stars and supernova shocks are favorable sites for high-energy particle acceleration. We argue that expanding young supernova (SN) shells in compact stellar clusters can be very efficient PeV CR accelerators. At a stage when a supernova shock is colliding with collective fast winds from massive stars in a compact cluster the Fermi mechanism allows particle acceleration to energies well above the standard limits of diffusive shock acceleration in an isolated SNR. The energy spectrum of protons in such an accelerator is a hard power-law with a broad spectral upturn above TeV before a break at multi-PeV energies, providing a large energy flux in the high-energy end of the spectrum. The acceleration stage in the colliding shock flow lasts for a few hundred years after the supernova explosion producing high-energy CRs that escape the accelerator and diffuse through the ambient matter producing γ-rays and neutrinos in inelastic nuclear collisions. In starburst galaxies a sizeable fraction of core collapse supernovae is expected to occur in compact star clusters and therefore their high energy gamma-ray and neutrino spectra in the PeV energy regime may differ strongly from that of our Galaxy. To test the model with individual sources we briefly discuss the recent H.E.S.S. detections of gamma-rays from two potential candidate sources, Westerlund 1 and HESS J1806-204 in the Milky Way. We argue that this model of compact star clusters, with typical parameters, could produce a neutrino flux sufficient to explain a fraction of the recently detected IceCube South Pole Observatory neutrinos.

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

PubMed Central

2012-01-01

Background Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in ‘real-world’ services. Methods/Design The Psychosis early Intervention and Assessment of Needs and Outcome (PIANO) trial is part of a larger research program (Genetics, Endophenotypes and Treatment: Understanding early Psychosis - GET UP) which aims to compare, at 9 months, the effectiveness of a multi-component psychosocial intervention versus treatment as usual (TAU) in a large epidemiologically based cohort of patients with FEP and their family members recruited from all public community mental health centers (CMHCs) located in two entire regions of Italy (Veneto and Emilia Romagna), and in the cities of Florence, Milan and Bolzano. The GET UP PIANO trial has a pragmatic cluster randomized controlled design. The randomized units (clusters) are the CMHCs, and the units of observation are the centers’ patients and their family members. Patients in the experimental group will receive TAU plus: 1) cognitive behavioral therapy sessions, 2) psycho-educational sessions for family members, and 3) case management. Patient enrolment will take place over a 1-year period. Several psychopathological, psychological, functioning, and service use variables will be assessed at baseline and follow-up. The primary outcomes are: 1) change from baseline to follow-up in positive and negative symptoms’ severity and subjective appraisal; 2) relapse occurrences between baseline and follow-up, that is, episodes resulting in admission and/or any case-note records of re-emergence of positive psychotic symptoms. The expected number of recruited patients is about 400, and that of relatives about 300. Owing to the implementation of the intervention at the CMHC level, the blinding of patients, clinicians, and raters is not possible, but every effort will be made to preserve the independency of the raters. We expect that this study will generate evidence on the best treatments for FEP, and will identify barriers that may hinder its feasibility in ‘real-world’ clinical settings, patient/family conditions that may render this intervention ineffective or inappropriate, and clinical, psychological, environmental, and service organization predictors of treatment effectiveness, compliance, and service satisfaction. Trial registration ClinicalTrials.gov Identifier NCT01436331 PMID:22647399

Reducing office workers’ sitting time: rationale and study design for the Stand Up Victoria cluster randomized trial

PubMed Central

2013-01-01

Background Excessive time spent in sedentary behaviours (sitting or lying with low energy expenditure) is associated with an increased risk for type 2 diabetes, cardiovascular disease and some cancers. Desk-based office workers typically accumulate high amounts of daily sitting time, often in prolonged unbroken bouts. The Stand Up Victoria study aims to determine whether a 3-month multi-component intervention in the office setting reduces workplace sitting, particularly prolonged, unbroken sitting time, and results in improvements in cardio-metabolic biomarkers and work-related outcomes, compared to usual practice. Methods/Design A two-arm cluster-randomized controlled trial (RCT), with worksites as the unit of randomization, will be conducted in 16 worksites located in Victoria, Australia. Work units from one organisation (Department of Human Services, Australian Government) will be allocated to either the multi-component intervention (organisational, environmental [height-adjustable workstations], and individual behavioural strategies) or to a usual practice control group. The recruitment target is 160 participants (office-based workers aged 18–65 years and working at least 0.6 full time equivalent) per arm. At each assessment (0- [baseline], 3- [post intervention], and 12-months [follow-up]), objective measurement via the activPAL3 activity monitor will be used to assess workplace: sitting time (primary outcome); prolonged sitting time (sitting time accrued in bouts of ≥30 minutes); standing time; sit-to-stand transitions; and, moving time. Additional outcomes assessed will include: non-workplace activity; cardio-metabolic biomarkers and health indicators (including fasting glucose, lipids and insulin; anthropometric measures; blood pressure; and, musculoskeletal symptoms); and, work-related outcomes (presenteeism, absenteeism, productivity, work performance). Incremental cost-effectiveness and identification of both workplace and individual-level mediators and moderators of change will also be evaluated. Discussion Stand Up Victoria will be the first cluster-RCT to evaluate the effectiveness of a multi-component intervention aimed at reducing prolonged workplace sitting in office workers. Strengths include the objective measurement of activity and assessment of the intervention on markers of cardio-metabolic health. Health- and work-related benefits, as well as the cost-effectiveness of the intervention, will help to inform future occupational practice. Trial registration ACTRN1211000742976 PMID:24209423

Analysis of k-means clustering approach on the breast cancer Wisconsin dataset.

PubMed

Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal

2016-11-01

Breast cancer is one of the most common cancers found worldwide and most frequently found in women. An early detection of breast cancer provides the possibility of its cure; therefore, a large number of studies are currently going on to identify methods that can detect breast cancer in its early stages. This study was aimed to find the effects of k-means clustering algorithm with different computation measures like centroid, distance, split method, epoch, attribute, and iteration and to carefully consider and identify the combination of measures that has potential of highly accurate clustering accuracy. K-means algorithm was used to evaluate the impact of clustering using centroid initialization, distance measures, and split methods. The experiments were performed using breast cancer Wisconsin (BCW) diagnostic dataset. Foggy and random centroids were used for the centroid initialization. In foggy centroid, based on random values, the first centroid was calculated. For random centroid, the initial centroid was considered as (0, 0). The results were obtained by employing k-means algorithm and are discussed with different cases considering variable parameters. The calculations were based on the centroid (foggy/random), distance (Euclidean/Manhattan/Pearson), split (simple/variance), threshold (constant epoch/same centroid), attribute (2-9), and iteration (4-10). Approximately, 92 % average positive prediction accuracy was obtained with this approach. Better results were found for the same centroid and the highest variance. The results achieved using Euclidean and Manhattan were better than the Pearson correlation. The findings of this work provided extensive understanding of the computational parameters that can be used with k-means. The results indicated that k-means has a potential to classify BCW dataset.

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins.

PubMed

Kenn, Michael; Ribarics, Reiner; Ilieva, Nevena; Cibena, Michael; Karch, Rudolf; Schreiner, Wolfgang

2016-04-26

The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gómez, D; Baly, A; Benítez, J R; Van der Stuyft, P

2010-01-01

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44 x 10(-3) v 0.29 x 10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial Registration Current Controlled Trials ISRCTN88405796.

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-06-09

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Cluster randomised trial. Guantanamo, Cuba. 32 circumscriptions (around 2000 inhabitants each). The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44x10(-3) v 0.29x10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Current Controlled Trials ISRCTN88405796.

Patterns of taxonomic, phylogenetic diversity during a long-term succession of forest on the Loess Plateau, China: insights into assembly process

PubMed Central

Chai, Yongfu; Yue, Ming; Liu, Xiao; Guo, Yaoxin; Wang, Mao; Xu, Jinshi; Zhang, Chenguang; Chen, Yu; Zhang, Lixia; Zhang, Ruichang

2016-01-01

Quantifying the drivers underlying the distribution of biodiversity during succession is a critical issue in ecology and conservation, and also can provide insights into the mechanisms of community assembly. Ninety plots were established in the Loess Plateau region of northern Shaanxi in China. The taxonomic and phylogenetic (alpha and beta) diversity were quantified within six succession stages. Null models were used to test whether phylogenetic distance observed differed from random expectations. Taxonomic beta diversity did not show a regular pattern, while phylogenetic beta diversity decreased throughout succession. The shrub stage occurred as a transition from phylogenetic overdispersion to clustering either for NRI (Net Relatedness Index) or betaNRI. The betaNTI (Nearest Taxon Index) values for early stages were on average phylogenetically random, but for the betaNRI analyses, these stages were phylogenetically overdispersed. Assembly of woody plants differed from that of herbaceous plants during late community succession. We suggest that deterministic and stochastic processes respectively play a role in different aspects of community phylogenetic structure for early succession stage, and that community composition of late succession stage is governed by a deterministic process. In conclusion, the long-lasting evolutionary imprints on the present-day composition of communities arrayed along the succession gradient. PMID:27272407

Patterns of taxonomic, phylogenetic diversity during a long-term succession of forest on the Loess Plateau, China: insights into assembly process.

PubMed

Chai, Yongfu; Yue, Ming; Liu, Xiao; Guo, Yaoxin; Wang, Mao; Xu, Jinshi; Zhang, Chenguang; Chen, Yu; Zhang, Lixia; Zhang, Ruichang

2016-06-08

Quantifying the drivers underlying the distribution of biodiversity during succession is a critical issue in ecology and conservation, and also can provide insights into the mechanisms of community assembly. Ninety plots were established in the Loess Plateau region of northern Shaanxi in China. The taxonomic and phylogenetic (alpha and beta) diversity were quantified within six succession stages. Null models were used to test whether phylogenetic distance observed differed from random expectations. Taxonomic beta diversity did not show a regular pattern, while phylogenetic beta diversity decreased throughout succession. The shrub stage occurred as a transition from phylogenetic overdispersion to clustering either for NRI (Net Relatedness Index) or betaNRI. The betaNTI (Nearest Taxon Index) values for early stages were on average phylogenetically random, but for the betaNRI analyses, these stages were phylogenetically overdispersed. Assembly of woody plants differed from that of herbaceous plants during late community succession. We suggest that deterministic and stochastic processes respectively play a role in different aspects of community phylogenetic structure for early succession stage, and that community composition of late succession stage is governed by a deterministic process. In conclusion, the long-lasting evolutionary imprints on the present-day composition of communities arrayed along the succession gradient.

Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering.

PubMed

Wang, Yang; Wu, Lin

2018-07-01

Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Flexible trial design in practice - stopping arms for lack-of-benefit and adding research arms mid-trial in STAMPEDE: a multi-arm multi-stage randomized controlled trial

PubMed Central

2012-01-01

Background Systemic Therapy for Advanced or Metastatic Prostate cancer: Evaluation of Drug Efficacy (STAMPEDE) is a randomized controlled trial that follows a novel multi-arm, multi-stage (MAMS) design. We describe methodological and practical issues arising with (1) stopping recruitment to research arms following a pre-planned intermediate analysis and (2) adding a new research arm during the trial. Methods STAMPEDE recruits men who have locally advanced or metastatic prostate cancer who are starting standard long-term hormone therapy. Originally there were five research and one control arms, each undergoing a pilot stage (focus: safety, feasibility), three intermediate ‘activity’ stages (focus: failure-free survival), and a final ‘efficacy’ stage (focus: overall survival). Lack-of-sufficient-activity guidelines support the pairwise interim comparisons of each research arm against the control arm; these pre-defined activity cut-off becomes increasingly stringent over the stages. Accrual of further patients continues to the control arm and to those research arms showing activity and an acceptable safety profile. The design facilitates adding new research arms should sufficiently interesting agents emerge. These new arms are compared only to contemporaneously recruited control arm patients using the same intermediate guidelines in a time-delayed manner. The addition of new research arms is subject to adequate recruitment rates to support the overall trial aims. Results (1) Stopping Existing Therapy: After the second intermediate activity analysis, recruitment was discontinued to two research arms for lack-of-sufficient activity. Detailed preparations meant that changes were implemented swiftly at 100 international centers and recruitment continued seamlessly into Activity Stage III with 3 remaining research arms and the control arm. Further regulatory and ethical approvals were not required because this was already included in the initial trial design. (2) Adding New Therapy: An application to add a new research arm was approved by the funder, (who also organized peer review), industrial partner and regulatory and ethical bodies. This was all done in advance of any decision to stop current therapies. Conclusions The STAMPEDE experience shows that recruitment to a MAMS trial and mid-flow changes its design are achievable with good planning. This benefits patients and the scientific community as research treatments are evaluated in a more efficient and cost-effective manner. Trial registration ISRCTN78818544, NCT00268476 First patient into trial: 17 October 2005 First patient into abiraterone comparison: 15 November 2011 PMID:22978443

Flexible trial design in practice - stopping arms for lack-of-benefit and adding research arms mid-trial in STAMPEDE: a multi-arm multi-stage randomized controlled trial.

PubMed

Sydes, Matthew R; Parmar, Mahesh K B; Mason, Malcolm D; Clarke, Noel W; Amos, Claire; Anderson, John; de Bono, Johann; Dearnaley, David P; Dwyer, John; Green, Charlene; Jovic, Gordana; Ritchie, Alastair W S; Russell, J Martin; Sanders, Karen; Thalmann, George; James, Nicholas D

2012-09-15

Systemic Therapy for Advanced or Metastatic Prostate cancer: Evaluation of Drug Efficacy (STAMPEDE) is a randomized controlled trial that follows a novel multi-arm, multi-stage (MAMS) design. We describe methodological and practical issues arising with (1) stopping recruitment to research arms following a pre-planned intermediate analysis and (2) adding a new research arm during the trial. STAMPEDE recruits men who have locally advanced or metastatic prostate cancer who are starting standard long-term hormone therapy. Originally there were five research and one control arms, each undergoing a pilot stage (focus: safety, feasibility), three intermediate 'activity' stages (focus: failure-free survival), and a final 'efficacy' stage (focus: overall survival). Lack-of-sufficient-activity guidelines support the pairwise interim comparisons of each research arm against the control arm; these pre-defined activity cut-off becomes increasingly stringent over the stages. Accrual of further patients continues to the control arm and to those research arms showing activity and an acceptable safety profile. The design facilitates adding new research arms should sufficiently interesting agents emerge. These new arms are compared only to contemporaneously recruited control arm patients using the same intermediate guidelines in a time-delayed manner. The addition of new research arms is subject to adequate recruitment rates to support the overall trial aims. (1) Stopping Existing Therapy: After the second intermediate activity analysis, recruitment was discontinued to two research arms for lack-of-sufficient activity. Detailed preparations meant that changes were implemented swiftly at 100 international centers and recruitment continued seamlessly into Activity Stage III with 3 remaining research arms and the control arm. Further regulatory and ethical approvals were not required because this was already included in the initial trial design.(2) Adding New Therapy: An application to add a new research arm was approved by the funder, (who also organized peer review), industrial partner and regulatory and ethical bodies. This was all done in advance of any decision to stop current therapies. The STAMPEDE experience shows that recruitment to a MAMS trial and mid-flow changes its design are achievable with good planning. This benefits patients and the scientific community as research treatments are evaluated in a more efficient and cost-effective manner. ISRCTN78818544, NCT00268476. First patient into trial: 17 October 2005. First patient into abiraterone comparison: 15 November 2011.

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

PubMed Central

Balagam, Rajesh; Igoshin, Oleg A.

2015-01-01

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

Surgical timing after chemoradiotherapy for rectal cancer, analysis of technique (STARRCAT): results of a feasibility multi-centre randomized controlled trial.

PubMed

Foster, J D; Ewings, P; Falk, S; Cooper, E J; Roach, H; West, N P; Williams-Yesson, B A; Hanna, G B; Francis, N K

2016-10-01

The optimal time of rectal resection after long-course chemoradiotherapy (CRT) remains unclear. A feasibility study was undertaken for a multi-centre randomized controlled trial evaluating the impact of the interval after chemoradiotherapy on the technical complexity of surgery. Patients with rectal cancer were randomized to either a 6- or 12-week interval between CRT and surgery between June 2012 and May 2014 (ISRCTN registration number: 88843062). For blinded technical complexity assessment, the Observational Clinical Human Reliability Analysis technique was used to quantify technical errors enacted within video recordings of operations. Other measured outcomes included resection completeness, specimen quality, radiological down-staging, tumour cell density down-staging and surgeon-reported technical complexity. Thirty-one patients were enrolled: 15 were randomized to 6 and 16-12 weeks across 7 centres. Fewer eligible patients were identified than had been predicted. Of 23 patients who underwent resection, mean 12.3 errors were observed per case at 6 weeks vs. 10.7 at 12 weeks (p = 0.401). Other measured outcomes were similar between groups. The feasibility of measurement of operative performance of rectal cancer surgery as an endpoint was confirmed in this exploratory study. Recruitment of sufficient numbers of patients represented a challenge, and a proportion of patients did not proceed to resection surgery. These results suggest that interval after CRT may not substantially impact upon surgical technical performance.

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

Semantic segmentation of 3D textured meshes for urban scene analysis

NASA Astrophysics Data System (ADS)

Rouhani, Mohammad; Lafarge, Florent; Alliez, Pierre

2017-01-01

Classifying 3D measurement data has become a core problem in photogrammetry and 3D computer vision, since the rise of modern multiview geometry techniques, combined with affordable range sensors. We introduce a Markov Random Field-based approach for segmenting textured meshes generated via multi-view stereo into urban classes of interest. The input mesh is first partitioned into small clusters, referred to as superfacets, from which geometric and photometric features are computed. A random forest is then trained to predict the class of each superfacet as well as its similarity with the neighboring superfacets. Similarity is used to assign the weights of the Markov Random Field pairwise-potential and to account for contextual information between the classes. The experimental results illustrate the efficacy and accuracy of the proposed framework.

C 60 -induced Devil's Staircase transformation on a Pb/Si(111) wetting layer

DOE PAGES

Wang, Lin -Lin; Johnson, Duane D.; Tringides, Michael C.

2015-12-03

Density functional theory is used to study structural energetics of Pb vacancy cluster formation on C 60/Pb/Si(111) to explain the unusually fast and error-free transformations between the “Devil's Staircase” (DS) phases on the Pb/Si(111) wetting layer at low temperature (~110K). The formation energies of vacancy clusters are calculated in C 60/Pb/Si(111) as Pb atoms are progressively ejected from the initial dense Pb wetting layer. Vacancy clusters larger than five Pb atoms are found to be stable with seven being the most stable, while vacancy clusters smaller than five are highly unstable, which agrees well with the observed ejection rate ofmore » ~5 Pb atoms per C 60. Furthermore, the high energy cost (~0.8 eV) for the small vacancy clusters to form indicates convincingly that the unusually fast transformation observed experimentally between the DS phases, upon C 60 adsorption at low temperature, cannot be the result of single-atom random walk diffusion but of correlated multi-atom processes.« less

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

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Study on the application of MRF and the D-S theory to image segmentation of the human brain and quantitative analysis of the brain tissue

NASA Astrophysics Data System (ADS)

Guan, Yihong; Luo, Yatao; Yang, Tao; Qiu, Lei; Li, Junchang

2012-01-01

The features of the spatial information of Markov random field image was used in image segmentation. It can effectively remove the noise, and get a more accurate segmentation results. Based on the fuzziness and clustering of pixel grayscale information, we find clustering center of the medical image different organizations and background through Fuzzy cmeans clustering method. Then we find each threshold point of multi-threshold segmentation through two dimensional histogram method, and segment it. The features of fusing multivariate information based on the Dempster-Shafer evidence theory, getting image fusion and segmentation. This paper will adopt the above three theories to propose a new human brain image segmentation method. Experimental result shows that the segmentation result is more in line with human vision, and is of vital significance to accurate analysis and application of tissues.

Causal Factors Influencing Adversity Quotient of Twelfth Grade and Third-Year Vocational Students

ERIC Educational Resources Information Center

Pangma, Rachapoom; Tayraukham, Sombat; Nuangchalerm, Prasart

2009-01-01

Problem statement: The aim of this research was to study the causal factors influencing students' adversity between twelfth grade and third-year vocational students in Sisaket province, Thailand. Six hundred and seventy two of twelfth grade and 376 third-year vocational students were selected by multi-stage random sampling techniques. Approach:…

Texas School Survey of Substance Abuse: Grades 7-12. 1992.

ERIC Educational Resources Information Center

Liu, Liang Y.; Fredlund, Eric V.

The 1992 Texas School Survey results for secondary students are based on data collected from a sample of 73,073 students in grades 7 through 12. Students were randomly selected from school districts throughout the state using a multi-stage probability design. The procedure ensured that students living in metropolitan and rural areas of Texas are…

Teacher Use of Data to Guide Instructional Practice in Elementary Schools

ERIC Educational Resources Information Center

Burrows, Debra C.

2011-01-01

This descriptive study focused on the degree to which data-driven decision making as envisioned by the NCLB legislation was actually occurring in the elementary schools studied. A multi-stage random sample of six Pennsylvania school districts out of 19 located within the service area of Pennsylvania Intermediate Unit #17, one of 29 regional…

Do Human-Figure Drawings of Children and Adolescents Mirror Their Cognitive Style and Self-Esteem?

ERIC Educational Resources Information Center

Dey, Anindita; Ghosh, Paromita

2016-01-01

The investigation probed relationships among human-figure drawing, field-dependent-independent cognitive style and self-esteem of 10-15 year olds. It also attempted to predict human-figure drawing scores of participants based on their field-dependence-independence and self-esteem. Area, stratified and multi-stage random sampling were used to…

Socio-Economic Background and Access to Internet as Correlates of Students' Achievement in Agricultural Science

ERIC Educational Resources Information Center

Adegoke, Sunday Paul; Osokoya, Modupe M.

2015-01-01

This study investigated access to internet and socio-economic background as correlates of students' achievement in Agricultural Science among selected Senior Secondary Schools Two Students in Ogbomoso South and North Local Government Areas. The study adopted multi-stage sampling technique. Simple random sampling was used to select 30 students from…

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

PubMed

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.

The effect of group counseling based on self-awareness skill on sexual risk-taking among girl students in Gorgan, Iran: a randomized trial.

PubMed

Kabiri, Golnoosh; Ziaei, Tayebe; Aval, Masumeh Rezaei; Vakili, Mohammad Ali

2017-09-15

Background Sexual puberty in adolescents occurs before their mental and emotional maturity and exposes them to high-risk sexual behaviors. Because sexual risk-taking occurs before adolescents become involved in a sexual relationship, this study was conducted to identify the effect of group counseling based on self-awareness skill on sexual risk-taking among female high school students in Gorgan in order to suggest some preventative measures. Methods The present parallel study is a randomized field trial conducted on 96 girl students who were studying in grades 10, 11 and 12 of high school with an age range of 14-18 years old. Sampling was done based on a multi-stage process. In the first stage, through the randomized clustering approach, four centers among six health centers were selected. In the second stage, 96 samples were collected through consecutive sampling. Finally, the samples were divided into two intervention and control groups (each one having 48 subjects) through the simple randomized approach. It has to be noted that no blinding was done in the present study. The data were collected using a demographic specifications form and the Iranian Adolescents Risk-Taking Scale (IARS). The consultation sessions based on self-awareness skill were explained to an intervention group through 60-min sessions over 7 weeks. The pretest was conducted for both groups and the posttest was completed 1 week and 1 month after the intervention by the intervention and control groups. Finally, after the loss of follow-up/drop out, a total of 80 subjects remained in the study; 42 subjects in the intervention group and 38 subjects in the control group. Data analyses were done using SPSS v.16 along with the Freidman non-parametric test and the Mann-Whitney and Wilcoxon tests. Results The results showed that the sexual risk-taking mean scores in the intervention group (10.54 ± 15.64) were reduced by applying 1-week (8.03 ± 12.82) and 1-month (4.91 ± 10.10) follow-ups after the intervention. This reduction was statistically significant (p = 14%). However, no statistically significant difference was observed in the control group. Conclusion Group counseling based on self-awareness skill decreased the sexual risk-taking in girl students of the high school. As prevention is prior to treatment, this method could be proposed as the prevention of high-risk sexual behavior to healthcare centers and educational environments and non-government organizations (NGOs) interacting with adolescents.

Design and methods of a strategic outcome study for chronic kidney disease: Frontier of Renal Outcome Modifications in Japan.

PubMed

Yamagata, Kunihiro; Makino, Hirofumi; Akizawa, Tadao; Iseki, Kunitoshi; Itoh, Sadayoshi; Kimura, Kenjiro; Koya, Daisuke; Narita, Ichiei; Mitarai, Tetsuya; Miyazaki, Masanobu; Tsubakihara, Yoshiharu; Watanabe, Tsuyoshi; Wada, Takashi; Sakai, Osamu

2010-04-01

The continuous increase in the number of people requiring dialysis is a major clinical and socioeconomical issue in Japan and other countries. This study was designed to encourage chronic kidney disease (CKD) patients to consult a physician, enhance cooperation between nephrologists and general practices, and prevent the progression of kidney disease. Subjects comprise CKD patients aged between 40 and 74 years consulting a general physician, and patients in CKD stage 3 with proteinuria and diabetes or hypertension. This trial is a stratified open cluster-randomized study with two intervention groups: group A (weak intervention) and group B (strong intervention). We have recruited 49 local medical associations (clusters) in 15 different prefectures, which were classified into four regions (strata) based on the level of increase rate of dialysis patients. The patients in group A clusters were instructed initially to undergo treatment in accordance with the current CKD treatment guide, whereas patients in group B clusters were not only instructed in the same fashion but also received support from an information technology (IT)-based system designed to help achieve the goals of CKD treatment, consultation support centers, and consultations by dietitians visiting the local general practice offices. We assessed the rates of continued consultation, collaboration between general practitioners and nephrologists, and progression of CKD (as expressed by CKD stage). Through this study, filling the evidence-practice gap by facilitating effective communication and supporting general physicians and nephrologists, we will establish a CKD care system and decrease the number of advanced-stage CKD patients.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

PubMed

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

Multi-focus image fusion and robust encryption algorithm based on compressive sensing

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Lan; Xiang, Tao; Wang, Yong

2017-06-01

Multi-focus image fusion schemes have been studied in recent years. However, little work has been done in multi-focus image transmission security. This paper proposes a scheme that can reduce data transmission volume and resist various attacks. First, multi-focus image fusion based on wavelet decomposition can generate complete scene images and optimize the perception of the human eye. The fused images are sparsely represented with DCT and sampled with structurally random matrix (SRM), which reduces the data volume and realizes the initial encryption. Then the obtained measurements are further encrypted to resist noise and crop attack through combining permutation and diffusion stages. At the receiver, the cipher images can be jointly decrypted and reconstructed. Simulation results demonstrate the security and robustness of the proposed scheme.

Application of the theory of reasoned action to promoting breakfast consumption.

PubMed

Hosseini, Zahra; Gharlipour Gharghani, Zabihollah; Mansoori, Anahita; Aghamolaei, Teamur; Mohammadi Nasrabadi, Maryam

2015-01-01

Breakfast is the most important daily meal, but neglected more than other meals by children and adolescents. The aim of this study was to evaluate the effectiveness of an educational intervention, based on the Theory of Reasoned Action (TRA) to increase breakfast consumption among school children in Bandar Abbas, Iran. In this quasi experimental study which was conducted in 2012, 88 students of four secondary schools in Bandar Abbas, south of Iran, were enrolled. Multi-stage cluster sampling was performed with random allocation of interventional and control groups. The study tool was a questionnaire which was filled by the students before and two months after the educational intervention. For data analysis, statistical tests including paired-samples t-test, independent samples t-test, Wilcoxon test, and Mann-Whitney test were used through SPSS v.18 software. The result of the study showed that application of TRA significantly increased scores of behavior of breakfast consumption (p<0.01). After the intervention, a significant increase was revealed in all nutrition intakes, except for fat and sugar (p<0.01). The findings support application of the TRA in improving the intention and behavior of breakfast consumption. Applying this theory for designing interventions to increase breakfast eating is recommended.

Analysis on leisure patterns of the pre-elderly adults

PubMed Central

Cho, Gun-Sang; Yi, Eun-Surk

2013-01-01

The purpose of study is to analyze how leisure activities affect the near elders’ preparation for successful and productive aging. To achieve the purpose of the study, this study was conducted in 2012 and the data was collected by using multi-stage stratified cluster random sampling method in the great city area (6 places), metropolitan area (7 places), medium-sized urban area (6 places), and rural area (6 places). Out of the total number of 1,000 copies of questionnaire distributed to pre-elders (Baby-boomers from 55 yr to 64 yr), 978 were collected and used for data analysis. According to the result, the more time, frequency and intensity in leisure and recreational participation, the higher the satisfaction level and the happiness level in their life. It means that leisure and recreational activities play an important role for their life. In other words, for pre-elders, leisure activities can be regarded as the important element for preparation of their old age. Therefore, the leisure and recreation for pre-elderly adults should not be recognized as a tool for improving the economic productivity but for reinforcing the recovery resilience. PMID:24278898

Cervical cancer screening among Lebanese women.

PubMed

Bou-Orm, I R; Sakr, R E; Adib, S M

2018-02-01

Cervical cancer is a very common malignancy amongst women worldwide. Pap smear is an effective and inexpensive screening test in asymptomatic women. The aim of this paper was to assess the prevalence of Pap smear screening for cervical cancer among Lebanese women and to determine associated sociodemographic and psychosocial characteristics. This national survey included 2255 women, selected by multi-stage random cluster sampling across Lebanon. A questionnaire about practices and perceptions related to cervical cancer screening was developed based on the "Health Belief Model". The weighted national prevalence of "ever-use" of the Pap smear for screening purposes was 35%. Most important determinants of screening behavior were: residence within Greater Beirut, higher socio-economic status and educational attainment, marriage status, presence of a health coverage, awareness of Pap smear usefulness, knowing someone who had already done it, and a balance between perceived benefits and perceived barriers to Pap smear screening. Regular information campaigns regarding the availability and effectiveness of the test should be devised, targeting in priority the sexually vulnerable women in Lebanon. Moreover, healthcare providers should be encouraged to discuss with their patients the opportunity of obtaining a Pap smear. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Thermodynamics and Kinetics of Prenucleation Clusters, Classical and Non-Classical Nucleation.

PubMed

Zahn, Dirk

2015-07-20

Recent observations of prenucleation species and multi-stage crystal nucleation processes challenge the long-established view on the thermodynamics of crystal formation. Here, we review and generalize extensions to classical nucleation theory. Going beyond the conventional implementation as has been used for more than a century now, nucleation inhibitors, precursor clusters and non-classical nucleation processes are rationalized as well by analogous concepts based on competing interface and bulk energy terms. This is illustrated by recent examples of species formed prior to/instead of crystal nucleation and multi-step nucleation processes. Much of the discussed insights were obtained from molecular simulation using advanced sampling techniques, briefly summarized herein for both nucleation-controlled and diffusion-controlled aggregate formation. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A Bayesian pick-the-winner design in a randomized phase II clinical trial.

PubMed

Chen, Dung-Tsa; Huang, Po-Yu; Lin, Hui-Yi; Chiappori, Alberto A; Gabrilovich, Dmitry I; Haura, Eric B; Antonia, Scott J; Gray, Jhanelle E

2017-10-24

Many phase II clinical trials evaluate unique experimental drugs/combinations through multi-arm design to expedite the screening process (early termination of ineffective drugs) and to identify the most effective drug (pick the winner) to warrant a phase III trial. Various statistical approaches have been developed for the pick-the-winner design but have been criticized for lack of objective comparison among the drug agents. We developed a Bayesian pick-the-winner design by integrating a Bayesian posterior probability with Simon two-stage design in a randomized two-arm clinical trial. The Bayesian posterior probability, as the rule to pick the winner, is defined as probability of the response rate in one arm higher than in the other arm. The posterior probability aims to determine the winner when both arms pass the second stage of the Simon two-stage design. When both arms are competitive (i.e., both passing the second stage), the Bayesian posterior probability performs better to correctly identify the winner compared with the Fisher exact test in the simulation study. In comparison to a standard two-arm randomized design, the Bayesian pick-the-winner design has a higher power to determine a clear winner. In application to two studies, the approach is able to perform statistical comparison of two treatment arms and provides a winner probability (Bayesian posterior probability) to statistically justify the winning arm. We developed an integrated design that utilizes Bayesian posterior probability, Simon two-stage design, and randomization into a unique setting. It gives objective comparisons between the arms to determine the winner.

Earth Science Data Fusion with Event Building Approach

NASA Technical Reports Server (NTRS)

Lukashin, C.; Bartle, Ar.; Callaway, E.; Gyurjyan, V.; Mancilla, S.; Oyarzun, R.; Vakhnin, A.

2015-01-01

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

2003-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

1990-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

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

NASA Technical Reports Server (NTRS)

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.

Temporal variation of aftershocks by means of multifractal characterization of their inter-event time and cluster analysis

NASA Astrophysics Data System (ADS)

Figueroa-Soto, A.; Zuñiga, R.; Marquez-Ramirez, V.; Monterrubio-Velasco, M.

2017-12-01

. The inter-event time characteristics of seismic aftershock sequences can provide important information to discern stages in the aftershock generation process. In order to investigate whether separate dynamic stages can be identified, (1) aftershock series after selected earthquake mainshocks, which took place at similar tectonic regimes were analyzed. To this end we selected two well-defined aftershock sequences from New Zealand and one aftershock sequence for Mexico, we (2) analyzed the fractal behavior of the logarithm of inter-event times (also called waiting times) of aftershocks by means of Holdeŕs exponent, and (3) their magnitude and spatial location based on a methodology proposed by Zaliapin and Ben Zion [2011] which accounts for the clustering properties of the sequence. In general, more than two coherent process stages can be identified following the main rupture, evidencing a type of "cascade" process which precludes implying a single generalized power law even though the temporal rate and average fractal character appear to be unique (as in a single Omorís p value). We found that aftershock processes indeed show multi-fractal characteristics, which may be related to different stages in the process of diffusion, as seen in the temporary-spatial distribution of aftershocks. Our method provides a way of defining the onset of the return to seismic background activity and the end of the main aftershock sequence.

Bringing Clouds into Our Lab! - The Influence of Turbulence on the Early Stage Rain Droplets

NASA Astrophysics Data System (ADS)

Yavuz, Mehmet Altug; Kunnen, Rudie; Heijst, Gertjan; Clercx, Herman

2015-11-01

We are investigating a droplet-laden flow in an air-filled turbulence chamber, forced by speaker-driven air jets. The speakers are running in a random manner; yet they allow us to control and define the statistics of the turbulence. We study the motion of droplets with tunable size (Stokes numbers ~ 0.13 - 9) in a turbulent flow, mimicking the early stages of raindrop formation. 3D Particle Tracking Velocimetry (PTV) together with Laser Induced Fluorescence (LIF) methods are chosen as the experimental method to track the droplets and collect data for statistical analysis. Thereby it is possible to study the spatial distribution of the droplets in turbulence using the so-called Radial Distribution Function (RDF), a statistical measure to quantify the clustering of particles. Additionally, 3D-PTV technique allows us to measure velocity statistics of the droplets and the influence of the turbulence on droplet trajectories, both individually and collectively. In this contribution, we will present the clustering probability quantified by the RDF for different Stokes numbers. We will explain the physics underlying the influence of turbulence on droplet cluster behavior. This study supported by FOM/NWO Netherlands.

A combined community- and facility-based approach to improve pregnancy outcomes in low-resource settings: a Global Network cluster randomized trial.

PubMed

Pasha, Omrana; McClure, Elizabeth M; Wright, Linda L; Saleem, Sarah; Goudar, Shivaprasad S; Chomba, Elwyn; Patel, Archana; Esamai, Fabian; Garces, Ana; Althabe, Fernando; Kodkany, Bhala; Mabeya, Hillary; Manasyan, Albert; Carlo, Waldemar A; Derman, Richard J; Hibberd, Patricia L; Liechty, Edward K; Krebs, Nancy; Hambidge, K Michael; Buekens, Pierre; Moore, Janet; Jobe, Alan H; Koso-Thomas, Marion; Wallace, Dennis D; Stalls, Suzanne; Goldenberg, Robert L

2013-10-03

Fetal and neonatal mortality rates in low-income countries are at least 10-fold greater than in high-income countries. These differences have been related to poor access to and poor quality of obstetric and neonatal care. This trial tested the hypothesis that teams of health care providers, administrators and local residents can address the problem of limited access to quality obstetric and neonatal care and lead to a reduction in perinatal mortality in intervention compared to control locations. In seven geographic areas in five low-income and one middle-income country, most with high perinatal mortality rates and substantial numbers of home deliveries, we performed a cluster randomized non-masked trial of a package of interventions that included community mobilization focusing on birth planning and hospital transport, community birth attendant training in problem recognition, and facility staff training in the management of obstetric and neonatal emergencies. The primary outcome was perinatal mortality at ≥28 weeks gestation or birth weight ≥1000 g. Despite extensive effort in all sites in each of the three intervention areas, no differences emerged in the primary or any secondary outcome between the intervention and control clusters. In both groups, the mean perinatal mortality was 40.1/1,000 births (P = 0.9996). Neither were there differences between the two groups in outcomes in the last six months of the project, in the year following intervention cessation, nor in the clusters that best implemented the intervention. This cluster randomized comprehensive, large-scale, multi-sector intervention did not result in detectable impact on the proposed outcomes. While this does not negate the importance of these interventions, we expect that achieving improvement in pregnancy outcomes in these settings will require substantially more obstetric and neonatal care infrastructure than was available at the sites during this trial, and without them provider training and community mobilization will not be sufficient. Our results highlight the critical importance of evaluating outcomes in randomized trials, as interventions that should be effective may not be. ClinicalTrials.gov NCT01073488.

Probing the non-thermal emission in Abell 2146 and the Perseus cluster with the JVLA

NASA Astrophysics Data System (ADS)

Gendron-Marsolais, Marie-Lou; Hlavacek-Larrondo, Julie; van Weeren, Reinout; Clarke, Tracy; Intema, Huib; Russell, Helen; Edge, Alastair; Fabian, Andy; Olamaie, Malak; Rumsey, Clare; King, Lindsay; McNamara, Brian; Fecteau-Beaucage, David; Hogan, Michael; Mezcua, Mar; Taylor, Gregory; Blundell, Katherine; Sanders, Jeremy

2018-01-01

Jets created from accretion onto supermassive black holes release relativistic particles on large distances. These strongly affect the intracluster medium when located in the center of a brightest cluster galaxy. The hierarchical merging of subclusters and groups, from which cluster originate, also generates perturbations into the intracluster medium through shocks and turbulence, constituting a potential source of reacceleration for these particles. I will present deep multi-configuration low radio frequency observations from the Karl G. Jansky Very Large Array of two unique clusters, probing the non-thermal emission from the old particle population of the AGN outflows.Recently awarded of 550 hours of Chandra observations, Abell 2146 is one of the rare clusters undergoing a spectacular merger in the plane of the sky. Our recent deep multi-configuration JVLA 1.4 GHz observations have revealed the presence of a structure extending to 850 kpc in size, consisting of one component associated with the upstream shock and classified as a radio relic, and one associated with the subcluster core, consistent with a radio halo bounded by the bow shock. Theses structures have some of the lowest radio powers detected thus far in any cluster. The flux measurements of the halo, its morphology and measurements of the dynamical state of the cluster suggest that the halo was recently created (~ 0.3 Gyr after core passage). This makes A2146 extremely interesting to study, allowing us to probe the complete evolutionary stages of halos.I will also present results on 230-470 MHz JVLA observations of the Perseus cluster. Our observations of this nearby relaxed cool core cluster have revealed a multitude of new structures associated with the mini-halo, extending to hundreds of kpc in size. Its irregular morphology seems to be have been influenced both by the AGN activity and by the sloshing motion of the cluster’ gas. In addition, it has a filamentary structure similar to that seen in radio relics found in merging clusters.These results both illustrate the high-quality images that can be obtained with the new JVLA at low radio-frequencies.

Quality of life and visual function in Nigeria: findings from the National Survey of Blindness and Visual Impairment.

PubMed

Tran, Hang My; Mahdi, Abdull M; Sivasubramaniam, Selvaraj; Gudlavalleti, Murthy V S; Gilbert, Clare E; Shah, Shaheen P; Ezelum, C C; Abubakar, Tafida; Bankole, Olufunmilayo O

2011-12-01

To assess associations of visual function (VF) and quality of life (QOL) by visual acuity (VA), causes of blindness and types of cataract procedures in Nigeria. Multi-stage stratified cluster random sampling was used to identify a nationally representative sample of persons aged ≥ 40 years. VF/QOL questionnaires were administered to participants with VA <6/60 in one or both eyes and/or Mehra-Minassian cataract grade 2B or 3 in one or both eyes and a random sample of those with bilateral VA ≥ 6/12. VF/QOL questionnaires were administered to 2076 participants. Spearman's rank correlation showed a strong correlation between decreasing VA and VF/QOL scores (p<0.0001) with greatest impact on social (p<0.0001) and mobility-related activities (p<0.0001). People who were blind due to glaucoma had lower VF and QOL scores than those who were blind due to cataract. Mean VF and QOL scores were lower after couching compared with conventional cataract surgery (mean VF score=51.0 vs 63.0 and mean QOL score=71.3 vs 79.3). Finally, VF and QOL scores were lower among populations with specific characteristics. Populations with the following characteristics should be targeted to improve VF and QOL: people who are blind, older people, women, manual labourers, people living in rural areas, those living in the northern geopolitical zones, those practising Islamic and Traditionalism faith, those not currently married and those who have undergone couching.

Lessons learned from a practice-based, multi-site intervention study with nurse participants

PubMed Central

Friese, Christopher R.; Mendelsohn-Victor, Kari; Ginex, Pamela; McMahon, Carol M.; Fauer, Alex J.; McCullagh, Marjorie C.

2016-01-01

Purpose To identify challenges and solutions to the efficient conduct of a multi-site, practice-based randomized controlled trial to improve nurses’ adherence to personal protective equipment use in ambulatory oncology settings. Design The Drug Exposure Feedback and Education for Nurses’ Safety (DEFENS) study is a clustered, randomized, controlled trial. Participating sites are randomized to web-based feedback on hazardous drug exposures in the sites plus tailored messages to address barriers versus a control intervention of a web-based continuing education video. Approach The study principal investigator, the study coordinator, and two site leaders identified challenges to study implementation and potential solutions, plus potential methods to prevent logistical challenges in future studies. Findings Noteworthy challenges included variation in human subjects protection policies, grants and contracts budgeting, infrastructure for nursing-led research, and information technology variation. Successful strategies included scheduled web conferences, site-based study champions, site visits by the principal investigator, and centrally-based document preparation. Strategies to improve efficiency in future studies include early and continued engagement with contract personnel in sites, and proposed changes to the common rule concerning human subjects. The DEFENS study successfully recruited 393 nurses across 12 sites. To date, 369 have completed surveys and 174 nurses have viewed educational materials. Conclusions Multi-site studies of nursing personnel are rare and challenging to existing infrastructure. These barriers can be overcome with strong engagement and planning. Clinical Relevance Leadership engagement, onsite staff support, and continuous communication can facilitate successful recruitment to a workplace-based randomized, controlled behavioral trial. PMID:28098951

Community involvement in dengue vector control: cluster randomised trial

PubMed Central

Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-01-01

Objective To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. Main outcome measures The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). Results All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44×10−3 v 0.29×10−3. At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). Conclusion A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial registration Current Controlled Trials ISRCTN88405796. PMID:19509031

Types of Bullying in the Senior High Schools in Ghana

ERIC Educational Resources Information Center

Antiri, Kwasi Otopa

2016-01-01

The main objective of the study was to examine the types of bullying that were taking place in the senior high schools in Ghana. A multi-stage sampling procedure, comprising purposive, simple random and snowball sampling technique, was used in the selection of the sample. A total of 354 respondents were drawn six schools in Ashanti, Central and…

Validating the Language Domain Subtest in a Developmental Assessment Scale for Preschool Children

ERIC Educational Resources Information Center

Wong, Anita M. -Y.; Leung, Cynthia; Siu, Elaine K. -L.; Lam, Catherine C. -C.

2012-01-01

This study reports on the validation of the language domain subtest of a developmental assessment scale for Cantonese Chinese preschool children. Three hundred and seventy eight multi-stage randomly selected children between 3;4 and 6;3 years of age were tested on the 104-item subtest. Fifty-four of these children, spreading across three age…

Estimating Treatment Effects from Contaminated Multi-Period Education Experiments: The Dynamic Impacts of Class Size Reductions. NBER Working Paper No. 15200

ERIC Educational Resources Information Center

Ding, Weili; Lehrer, Steven F.

2009-01-01

This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four year randomized…

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

NASA Astrophysics Data System (ADS)

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-06-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs.

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

PubMed Central

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-01-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs. PMID:26047353

A multi-populations multi-strategies differential evolution algorithm for structural optimization of metal nanoclusters

NASA Astrophysics Data System (ADS)

Fan, Tian-E.; Shao, Gui-Fang; Ji, Qing-Shuang; Zheng, Ji-Wen; Liu, Tun-dong; Wen, Yu-Hua

2016-11-01

Theoretically, the determination of the structure of a cluster is to search the global minimum on its potential energy surface. The global minimization problem is often nondeterministic-polynomial-time (NP) hard and the number of local minima grows exponentially with the cluster size. In this article, a multi-populations multi-strategies differential evolution algorithm has been proposed to search the globally stable structure of Fe and Cr nanoclusters. The algorithm combines a multi-populations differential evolution with an elite pool scheme to keep the diversity of the solutions and avoid prematurely trapping into local optima. Moreover, multi-strategies such as growing method in initialization and three differential strategies in mutation are introduced to improve the convergence speed and lower the computational cost. The accuracy and effectiveness of our algorithm have been verified by comparing the results of Fe clusters with Cambridge Cluster Database. Meanwhile, the performance of our algorithm has been analyzed by comparing the convergence rate and energy evaluations with the classical DE algorithm. The multi-populations, multi-strategies mutation and growing method in initialization in our algorithm have been considered respectively. Furthermore, the structural growth pattern of Cr clusters has been predicted by this algorithm. The results show that the lowest-energy structure of Cr clusters contains many icosahedra, and the number of the icosahedral rings rises with increasing size.

Decrease in musculoskeletal pain after 4 and 12 months of an aerobic exercise intervention: a worksite RCT among cleaners.

PubMed

Korshøj, Mette; Birk Jørgensen, Marie; Lidegaard, Mark; Mortensen, Ole Steen; Krustrup, Peter; Holtermann, Andreas; Søgaard, Karen

2017-07-01

Prevalence of musculoskeletal pain is high in jobs with high physical work demands. An aerobic exercise intervention targeting cardiovascular health was evaluated for its long term side effects on musculoskeletal pain. The objective was to investigate if aerobic exercise affects level of musculoskeletal pain from baseline to 4- and 12-months follow-up. One-hundred-and-sixteen cleaners aged 18-65 years were cluster-randomized. The aerobic exercise group ( n = 57) received worksite aerobic exercise (30 min twice a week) and the reference group ( n = 59) lectures in health promotion. Strata were formed according to closest manager (total 11 strata); clusters were set within strata (total 40 clusters, 20 in each group). Musculoskeletal pain data from eight body regions was collected at baseline and after 4- and 12-months follow-up. The participants stated highest pain in the last month on a scale from 0, stating no pain, up to 10, stating worst possible pain. A repeated-measure 2 × 2 multi-adjusted mixed-models design was applied to compare the between-groups differences in an intention to treat analysis. Participants were entered as a random effect nested in clusters to account for the cluster-based randomization. Clinically significant reductions (>30%, f  2 > 0.25) in the aerobic exercise group, compared to the reference group, in pain intensity in neck, shoulders, arms/wrists were found at 12-months follow-up, and a tendency ( p = 0.07, f  2 = 0.18) to an increase for the knees. At 4-months follow-up the only significant between-group change was an increase in hip pain. This study indicates that aerobic exercise reduces musculoskeletal pain in the upper extremities, but as an unintended side effect may increase pain in the lower extremities. Aerobic exercise interventions among workers standing or walking in the majority of the working hours should tailor exercise to only maintain the positive effect on musculoskeletal pain.

Impact of Multi-Micronutrient Fortified Rice on Hemoglobin, Iron and Vitamin A Status of Cambodian Schoolchildren: a Double-Blind Cluster-Randomized Controlled Trial.

PubMed

Perignon, Marlène; Fiorentino, Marion; Kuong, Khov; Dijkhuizen, Marjoleine A; Burja, Kurt; Parker, Megan; Chamnan, Chhoun; Berger, Jacques; Wieringa, Frank T

2016-01-07

In Cambodia, micronutrient deficiencies remain a critical public health problem. Our objective was to evaluate the impact of multi-micronutrient fortified rice (MMFR) formulations, distributed through a World Food Program school-meals program (WFP-SMP), on the hemoglobin concentrations and iron and vitamin A (VA) status of Cambodian schoolchildren. The FORISCA-UltraRice+NutriRice study was a double-blind, cluster-randomized, placebo-controlled trial. Sixteen schools participating in WFP-SMP were randomly assigned to receive extrusion-fortified rice (UltraRice Original, UltraRice New (URN), or NutriRice) or unfortified rice (placebo) six days a week for six months. Four additional schools not participating in WFP-SMP were randomly selected as controls. A total of 2440 schoolchildren (6-16 years old) participated in the biochemical study. Hemoglobin, iron status, estimated using inflammation-adjusted ferritin and transferrin receptors concentrations, and VA status, assessed using inflammation-adjusted retinol-binding protein concentration, were measured at the baseline, as well as at three and six months. Baseline prevalence of anemia, depleted iron stores, tissue iron deficiency, marginal VA status and VA deficiency were 15.6%, 1.4%, 51.0%, 7.9%, and 0.7%, respectively. The strongest risk factors for anemia were hemoglobinopathy, VA deficiency, and depleted iron stores (all p < 0.01). After six months, children receiving NutriRice and URN had 4 and 5 times less risk of low VA status, respectively, in comparison to the placebo group. Hemoglobin significantly increased (+0.8 g/L) after three months for the URN group in comparison to the placebo group; however, this difference was no longer significant after six months, except for children without inflammation. MMFR containing VA effectively improved the VA status of schoolchildren. The impact on hemoglobin and iron status was limited, partly by sub-clinical inflammation. MMFR combined with non-nutritional approaches addressing anemia and inflammation should be further investigated.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

PubMed Central

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-01-01

Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124

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

PubMed

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 © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

A multi-level intervention in worksites to increase fruit and vegetable access and intake: Rationale, design and methods of the 'Good to Go' cluster randomized trial.

PubMed

Risica, Patricia M; Gorham, Gemma; Dionne, Laura; Nardi, William; Ng, Doug; Middler, Reese; Mello, Jennifer; Akpolat, Rahmet; Gettens, Katelyn; Gans, Kim M

2018-02-01

Fruit and vegetable (F&V) consumption is an important contributor to chronic disease prevention. However, most Americans do not eat adequate amounts. The worksite is an advantageous setting to reach large, diverse segments of the population with interventions to increase F&V intake, but research gaps exist. No studies have evaluated the implementation of mobile F&V markets at worksites nor compared the effectiveness of such markets with or without nutrition education. This paper describes the protocol for Good to Go (GTG), a cluster randomized trial to evaluate F&V intake change in employees from worksites randomized into three experimental arms: discount, fresh F&V markets (Access Only arm); markets plus educational components including campaigns, cooking demonstrations, videos, newsletters, and a web site (Access Plus arm); and an attention placebo comparison intervention on physical activity and stress reduction (Comparison). Secondary aims include: 1) Process evaluation to determine costs, reach, fidelity, and dose as well as the relationship of these variables with changes in F&V intake; 2) Applying a mediating variable framework to examine relationships of psychosocial factors/determinants with changes in F&V consumption; and 3) Cost effectiveness analysis of the different intervention arms. The GTG study will fill important research gaps in the field by implementing a rigorous cluster randomized trial to evaluate the efficacy of an innovative environmental intervention providing access and availability to F&V at the worksite and whether this access intervention is further enhanced by accompanying educational interventions. GTG will provide an important contribution to public health research and practice. Trial registration number NCT02729675, ClinicalTrials.gov. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A multi-level intervention in worksites to increase fruit and vegetable access and intake: Rationale, design and methods of the ‘Good to Go’ cluster randomized trial

PubMed Central

Risica, Patricia M.; Gorham, Gemma; Dionne, Laura; Nardi, William; Ng, Doug; Middler, Reese; Mello, Jennifer; Akpolat, Rahmet; Gettens, Katelyn; Gans, Kim M.

2018-01-01

Background Fruit and vegetable (F&V) consumption is an important contributor to chronic disease prevention. However, most Americans do not eat adequate amounts. The worksite is an advantageous setting to reach large, diverse segments of the population with interventions to increase F&V intake, but research gaps exist. No studies have evaluated the implementation of mobile F&V markets at worksites nor compared the effectiveness of such markets with or without nutrition education. Methods This paper describes the protocol for Good to Go (GTG), a cluster randomized trial to evaluate F&V intake change in employees from worksites randomized into three experimental arms: discount, fresh F&V markets (Access Only arm); markets plus educational components including campaigns, cooking demonstrations, videos, newsletters, and a web site (Access Plus arm); and an attention placebo comparison intervention on physical activity and stress reduction (Comparison). Secondary aims include: 1) Process evaluation to determine costs, reach, fidelity, and dose as well as the relationship of these variables with changes in F&V intake; 2) Applying a mediating variable framework to examine relationships of psychosocial factors/determinants with changes in F&V consumption; and 3) Cost effectiveness analysis of the different intervention arms. Discussion The GTG study will fill important research gaps in the field by implementing a rigorous cluster randomized trial to evaluate the efficacy of an innovative environmental intervention providing access and availability to F&V at the worksite and whether this access intervention is further enhanced by accompanying educational interventions. GTG will provide an important contribution to public health research and practice. Trial registration number NCT02729675, ClinicalTrials.gov PMID:29242108

Cortical atrophy patterns in early Parkinson's disease patients using hierarchical cluster analysis.

PubMed

Uribe, Carme; Segura, Barbara; Baggio, Hugo Cesar; Abos, Alexandra; Garcia-Diaz, Anna Isabel; Campabadal, Anna; Marti, Maria Jose; Valldeoriola, Francesc; Compta, Yaroslau; Tolosa, Eduard; Junque, Carme

2018-05-01

Cortical brain atrophy detectable with MRI in non-demented advanced Parkinson's disease (PD) is well characterized, but its presence in early disease stages is still under debate. We aimed to investigate cortical atrophy patterns in a large sample of early untreated PD patients using a hypothesis-free data-driven approach. Seventy-seven de novo PD patients and 50 controls from the Parkinson's Progression Marker Initiative database with T1-weighted images in a 3-tesla Siemens scanner were included in this study. Mean cortical thickness was extracted from 360 cortical areas defined by the Human Connectome Project Multi-Modal Parcellation version 1.0, and a hierarchical cluster analysis was performed using Ward's linkage method. A general linear model with cortical thickness data was then used to compare clustering groups using FreeSurfer software. We identified two patterns of cortical atrophy. Compared with controls, patients grouped in pattern 1 (n = 33) were characterized by cortical thinning in bilateral orbitofrontal, anterior cingulate, and lateral and medial anterior temporal gyri. Patients in pattern 2 (n = 44) showed cortical thinning in bilateral occipital gyrus, cuneus, superior parietal gyrus, and left postcentral gyrus, and they showed neuropsychological impairment in memory and other cognitive domains. Even in the early stages of PD, there is evidence of cortical brain atrophy. Neuroimaging clustering analysis is able to detect two subgroups of cortical thinning, one with mainly anterior atrophy, and the other with posterior predominance and worse cognitive performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

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

PubMed Central

Zwarenstein, Merrick; Reeves, Scott; Russell, Ann; Kenaszchuk, Chris; Conn, Lesley Gotlib; Miller, Karen-Lee; Lingard, Lorelei; Thorpe, Kevin E

2007-01-01

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 substantial amount of interprofessional interaction lacks key core elements of collaborative communication such as self-introduction, description of professional role, and solicitation of other professional perspectives. Incorporating these findings, a four-component intervention was designed with a goal of creating a culture of communication in which the fundamentals of collaboration become a routine part of interprofessional interactions during unstructured work periods on GIM wards. Trial registration Registered with National Institutes of Health as NCT00466297. PMID:17877830

Prednisolone and acupuncture in Bell's palsy: study protocol for a randomized, controlled trial

PubMed Central

2011-01-01

Background There are a variety of treatment options for Bell's palsy. Evidence from randomized controlled trials indicates corticosteroids can be used as a proven therapy for Bell's palsy. Acupuncture is one of the most commonly used methods to treat Bell's palsy in China. Recent studies suggest that staging treatment is more suitable for Bell's palsy, according to different path-stages of this disease. The aim of this study is to compare the effects of prednisolone and staging acupuncture in the recovery of the affected facial nerve, and to verify whether prednisolone in combination with staging acupuncture is more effective than prednisolone alone for Bell's palsy in a large number of patients. Methods/Design In this article, we report the design and protocol of a large sample multi-center randomized controlled trial to treat Bell's palsy with prednisolone and/or acupuncture. In total, 1200 patients aged 18 to 75 years within 72 h of onset of acute, unilateral, peripheral facial palsy will be assessed. There are six treatment groups, with four treated according to different path-stages and two not. These patients are randomly assigned to be in one of the following six treatment groups, i.e. 1) placebo prednisolone group, 2) prednisolone group, 3) placebo prednisolone plus acute stage acupuncture group, 4) prednisolone plus acute stage acupuncture group, 5) placebo prednisolone plus resting stage acupuncture group, 6) prednisolone plus resting stage acupuncture group. The primary outcome is the time to complete recovery of facial function, assessed by Sunnybrook system and House-Brackmann scale. The secondary outcomes include the incidence of ipsilateral pain in the early stage of palsy (and the duration of this pain), the proportion of patients with severe pain, the occurrence of synkinesis, facial spasm or contracture, and the severity of residual facial symptoms during the study period. Discussion The result of this trial will assess the efficacy of using prednisolone and staging acupuncture to treat Bell's palsy, and to determine a best combination therapy with prednisolone and acupuncture for treating Bell's palsy. Trial Registration ClinicalTrials.gov: NCT01201642 PMID:21693007

Prednisolone and acupuncture in Bell's palsy: study protocol for a randomized, controlled trial.

PubMed

Xia, Feng; Han, Junliang; Liu, Xuedong; Wang, Jingcun; Jiang, Zhao; Wang, Kangjun; Wu, Songdi; Zhao, Gang

2011-06-21

There are a variety of treatment options for Bell's palsy. Evidence from randomized controlled trials indicates corticosteroids can be used as a proven therapy for Bell's palsy. Acupuncture is one of the most commonly used methods to treat Bell's palsy in China. Recent studies suggest that staging treatment is more suitable for Bell's palsy, according to different path-stages of this disease. The aim of this study is to compare the effects of prednisolone and staging acupuncture in the recovery of the affected facial nerve, and to verify whether prednisolone in combination with staging acupuncture is more effective than prednisolone alone for Bell's palsy in a large number of patients. In this article, we report the design and protocol of a large sample multi-center randomized controlled trial to treat Bell's palsy with prednisolone and/or acupuncture. In total, 1200 patients aged 18 to 75 years within 72 h of onset of acute, unilateral, peripheral facial palsy will be assessed. There are six treatment groups, with four treated according to different path-stages and two not. These patients are randomly assigned to be in one of the following six treatment groups, i.e. 1) placebo prednisolone group, 2) prednisolone group, 3) placebo prednisolone plus acute stage acupuncture group, 4) prednisolone plus acute stage acupuncture group, 5) placebo prednisolone plus resting stage acupuncture group, 6) prednisolone plus resting stage acupuncture group. The primary outcome is the time to complete recovery of facial function, assessed by Sunnybrook system and House-Brackmann scale. The secondary outcomes include the incidence of ipsilateral pain in the early stage of palsy (and the duration of this pain), the proportion of patients with severe pain, the occurrence of synkinesis, facial spasm or contracture, and the severity of residual facial symptoms during the study period. The result of this trial will assess the efficacy of using prednisolone and staging acupuncture to treat Bell's palsy, and to determine a best combination therapy with prednisolone and acupuncture for treating Bell's palsy. ClinicalTrials.gov: NCT01201642.

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

NASA Technical Reports Server (NTRS)

Tomberlin, T. J.

1985-01-01

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Enhancing evidence-based diabetes and chronic disease control among local health departments: a multi-phase dissemination study with a stepped-wedge cluster randomized trial component.

PubMed

Parks, Renee G; Tabak, Rachel G; Allen, Peg; Baker, Elizabeth A; Stamatakis, Katherine A; Poehler, Allison R; Yan, Yan; Chin, Marshall H; Harris, Jenine K; Dobbins, Maureen; Brownson, Ross C

2017-10-18

The rates of diabetes and prediabetes in the USA are growing, significantly impacting the quality and length of life of those diagnosed and financially burdening society. Premature death and disability can be prevented through implementation of evidence-based programs and policies (EBPPs). Local health departments (LHDs) are uniquely positioned to implement diabetes control EBPPs because of their knowledge of, and focus on, community-level needs, contexts, and resources. There is a significant gap, however, between known diabetes control EBPPs and actual diabetes control activities conducted by LHDs. The purpose of this study is to determine how best to support the use of evidence-based public health for diabetes (and related chronic diseases) control among local-level public health practitioners. This paper describes the methods for a two-phase study with a stepped-wedge cluster randomized trial that will evaluate dissemination strategies to increase the uptake of public health knowledge and EBPPs for diabetes control among LHDs. Phase 1 includes development of measures to assess practitioner views on and organizational supports for evidence-based public health, data collection using a national online survey of LHD chronic disease practitioners, and a needs assessment of factors influencing the uptake of diabetes control EBPPs among LHDs within one state in the USA. Phase 2 involves conducting a stepped-wedge cluster randomized trial to assess effectiveness of dissemination strategies with local-level practitioners at LHDs to enhance capacity and organizational support for evidence-based diabetes prevention and control. Twelve LHDs will be selected and randomly assigned to one of the three groups that cross over from usual practice to receive the intervention (dissemination) strategies at 8-month intervals; the intervention duration for groups ranges from 8 to 24 months. Intervention (dissemination) strategies may include multi-day in-person workshops, electronic information exchange methods, technical assistance through a knowledge broker, and organizational changes to support evidence-based public health approaches. Evaluation methods comprise surveys at baseline and the three crossover time points, abstraction of local-level diabetes and chronic disease control program plans and progress reports, and social network analysis to understand the relationships and contextual issues that influence EBPP adoption. ClinicalTrial.gov, NCT03211832.

Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

NASA Astrophysics Data System (ADS)

Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

A tripartite clustering analysis on microRNA, gene and disease model.

PubMed

Shen, Chengcheng; Liu, Ying

2012-02-01

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

CTX-M Enzymes: Origin and Diffusion

PubMed Central

Cantón, Rafael; González-Alba, José María; Galán, Juan Carlos

2012-01-01

CTX-M β-lactamases are considered a paradigm in the evolution of a resistance mechanism. Incorporation of different chromosomal blaCTX-M related genes from different species of Kluyvera has derived in different CTX-M clusters. In silico analyses have shown that this event has occurred at least nine times; in CTX-M-1 cluster (3), CTX-M-2 and CTX-M-9 clusters (2 each), and CTX-M-8 and CTX-M-25 clusters (1 each). This has been mainly produced by the participation of genetic mobilization units such as insertion sequences (ISEcp1 or ISCR1) and the later incorporation in hierarchical structures associated with multifaceted genetic structures including complex class 1 integrons and transposons. The capture of these blaCTX-M genes from the environment by highly mobilizable structures could have been a random event. Moreover, after incorporation within these structures, β-lactam selective force such as that exerted by cefotaxime and ceftazidime has fueled mutational events underscoring diversification of different clusters. Nevertheless, more variants of CTX-M enzymes, including those not inhibited by β-lactamase inhibitors such as clavulanic acid (IR-CTX-M variants), only obtained under in in vitro experiments, are still waiting to emerge in the clinical setting. Penetration and the later global spread of CTX-M producing organisms have been produced with the participation of the so-called “epidemic resistance plasmids” often carried in multi-drug resistant and virulent high-risk clones. All these facts but also the incorporation and co-selection of emerging resistance determinants within CTX-M producing bacteria, such as those encoding carbapenemases, depict the currently complex pandemic scenario of multi-drug resistant isolates. PMID:22485109

ACT2 peer-driven intervention increases enrollment into HIV/AIDS medical studies among African-Americans/Blacks and Hispanics: A cluster randomized controlled trial

PubMed Central

Gwadz, Marya; Cleland, Charles M.; Belkin, Mindy; Ritchie, Amanda; Leonard, Noelle; Riedel, Marion; Banfield, Angela; Colon, Pablo; Elharrar, Vanessa; Kagan, Jonathan; Mildvan, Donna

2014-01-01

African American/Black and Hispanic persons living with HIV/AIDS (“AABH-PLHA”) are under-represented in HIV/AIDS medical studies (HAMS). This paper evaluates the efficacy of a social/behavioral intervention to increase rates of screening for and enrollment into HAMS in these populations. Participants (N=540) were enrolled into a cluster randomized controlled trial of an intervention designed to overcome multi-level barriers to HAMS. Primary endpoints were rates of screening for and enrollment into therapeutic/treatment-oriented and observational studies. Intervention arm participants were 30 times more likely to be screened than controls (49.3% vs. 3.7%; p < .001). Half (55.5%) of those screened were eligible for HAMS, primarily observational studies. Nine out of ten found eligible enrolled (91.7%), almost all into observational studies (95.2%), compared to no enrollments among controls. Achieving appropriate representation of AABH-PLHA in HAMS necessitates modification of study inclusion criteria to increase the proportion found eligible for therapeutic HAMS, in addition to social/behavioral interventions. PMID:24961193

Improving the social and emotional climate of classrooms: a clustered randomized controlled trial testing the RULER Approach.

PubMed

Rivers, Susan E; Brackett, Marc A; Reyes, Maria R; Elbertson, Nicole A; Salovey, Peter

2013-02-01

The RULER Approach ("RULER") is a setting-level, social and emotional learning program that is grounded in theory and evidence. RULER is designed to modify the quality of classroom social interactions so that the climate becomes more supportive, empowering, and engaging. This is accomplished by integrating skill-building lessons and tools so that teachers and students develop their emotional literacy. In a clustered randomized control trial, we tested the hypothesis that RULER improves the social and emotional climate of classrooms. Depending upon condition assignment, 62 schools either integrated RULER into fifth- and sixth-grade English language arts (ELA) classrooms or served as comparison schools, using their standard ELA curriculum only. Multi-level modeling analyses showed that compared to classrooms in comparison schools, classrooms in RULER schools were rated as having higher degrees of warmth and connectedness between teachers and students, more autonomy and leadership among students, and teachers who focused more on students' interests and motivations. These findings suggest that RULER enhances classrooms in ways that can promote positive youth development.

Geographic analysis of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam.

PubMed

Ali, Mohammad; Thiem, Vu Dinh; Park, Jin-Kyung; Ochiai, Rion Leon; Canh, Do Gia; Danovaro-Holliday, M Carolina; Kaljee, Linda M; Clemens, John D; Acosta, Camilo J

2007-09-01

This paper identifies spatial patterns and predictors of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam. Data for this study result from the integration of demographic surveillance, vaccine record, and geographic data of the study area. A multi-level cross-classified (non-hierarchical) model was used for analyzing the non-nested nature of individual's ecological data. Vaccine uptake was unevenly distributed in space and there was spatial variability among predictors of vaccine uptake. Vaccine uptake was higher among students with younger, male, or not literate family heads. Students from households with higher per-capita income were less likely to participate in the trial. Residency south of the river or further from a hospital/polyclinic was associated with higher vaccine uptake. Younger students were more likely to be vaccinated than older students in high- or low-risk areas, but not in the entire study area. The findings are important for the management of vaccine campaigns during a trial and for interpretation of disease patterns during vaccine-efficacy evaluation.

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

PubMed

Lajnef, Tarek; Chaibi, Sahbi; Ruby, Perrine; Aguera, Pierre-Emmanuel; Eichenlaub, Jean-Baptiste; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

2015-07-30

Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System

NASA Astrophysics Data System (ADS)

Demirdjian, L.; Zhou, Y.; Huffman, G. J.

2016-12-01

This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.

Noncontact Sleep Study by Multi-Modal Sensor Fusion.

PubMed

Chung, Ku-Young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-07-21

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

PubMed Central

Chung, Ku-young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-01-01

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. PMID:28753994

Health-risk behaviour in Croatia.

PubMed

Bécue-Bertaut, Mónica; Kern, Josipa; Hernández-Maldonado, Maria-Luisa; Juresa, Vesna; Vuletic, Silvije

2008-02-01

To identify the health-risk behaviour of various homogeneous clusters of individuals. The study was conducted in 13 of the 20 Croatian counties and in Zagreb, the Croatian capital. In the first stage, general practices were selected in each county. The second-stage sample was created by drawing a random subsample of 10% of the patients registered at each selected general practice. The sample was divided into seven homogenous clusters using statistical methodology, combining multiple factor analysis with a hybrid clustering method. Seven homogeneous clusters were identified, three composed of males and four composed of females, based on statistically significant differences between selected characteristics (P<0.001). Although, in general, self-assessed health declined with age, significant variations were observed within specific age intervals. Higher levels of self-assessed health were associated with higher levels of education and/or socio-economic status. Many individuals, especially females, who self-reported poor health were heavy consumers of sleeping pills. Males and females reported different health-risk behaviours related to lifestyle, diet and use of the healthcare system. Heavy alcohol and tobacco use, unhealthy diet, risky physical activity and non-use of the healthcare system influenced self-assessed health in males. Females were slightly less satisfied with their health than males of the same age and educational level. Even highly educated females who took preventive healthcare tests and ate a healthy diet reported a less satisfactory self-assessed level of health than expected. Sociodemographic characteristics, life style, self-assessed health and use of the healthcare system were used in the identification of seven homogeneous population clusters. A comprehensive analysis of these clusters suggests health-related prevention and intervention efforts geared towards specific populations.

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

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

Liu, Z.; Bessa, M. A.; Liu, W.K.

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical andmore » concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.« less

Microscopic Spin Model for the STOCK Market with Attractor Bubbling on Regular and Small-World Lattices

NASA Astrophysics Data System (ADS)

Krawiecki, A.

A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the case of networks with a certain degree of randomness for a wide range of parameters the time series of the logarithmic price returns exhibit intermittent bursting typical of volatility clustering. Also the tails of distributions of returns obey a power scaling law with exponents comparable to those obtained from the empirical data.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

NASA Astrophysics Data System (ADS)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

Enhancing physical and social environments to reduce obesity among public housing residents: rationale, trial design, and baseline data for the Healthy Families study.

PubMed

Quintiliani, Lisa M; DeBiasse, Michele A; Branco, Jamie M; Bhosrekar, Sarah Gees; Rorie, Jo-Anna L; Bowen, Deborah J

2014-11-01

Intervention programs that change environments have the potential for greater population impact on obesity compared to individual-level programs. We began a cluster randomized, multi-component multi-level intervention to improve weight, diet, and physical activity among low-socioeconomic status public housing residents. Here we describe the rationale, intervention design, and baseline survey data. After approaching 12 developments, ten were randomized to intervention (n=5) or assessment-only control (n=5). All residents in intervention developments are welcome to attend any intervention component: health screenings, mobile food bus, walking groups, cooking demonstrations, and a social media campaign; all of which are facilitated by community health workers who are residents trained in health outreach. To evaluate weight and behavioral outcomes, a subgroup of female residents and their daughters age 8-15 were recruited into an evaluation cohort. In total, 211 households completed the survey (RR=46.44%). Respondents were Latino (63%), Black (24%), and had ≤ high school education (64%). Respondents reported ≤2 servings of fruits & vegetables/day (62%), visiting fast food restaurants 1+ times/week (32%), and drinking soft drinks daily or more (27%). The only difference between randomized groups was race/ethnicity, with more Black residents in the intervention vs. control group (28% vs. 19%, p=0.0146). Among low-socioeconomic status urban public housing residents, we successfully recruited and randomized families into a multi-level intervention targeting obesity. If successful, this intervention model could be adopted in other public housing developments or entities that also employ community health workers, such as food assistance programs or hospitals. Copyright © 2014 Elsevier Inc. All rights reserved.

Numerical insights into the early stages of nanoscale electrodeposition: nanocluster surface diffusion and aggregative growth.

PubMed

Mamme, Mesfin Haile; Köhn, Christoph; Deconinck, Johan; Ustarroz, Jon

2018-04-19

Fundamental understanding of the early stages of electrodeposition at the nanoscale is key to address the challenges in a wide range of applications. Despite having been studied for decades, a comprehensive understanding of the whole process is still out of reach. In this work, we introduce a novel modelling approach that couples a finite element method (FEM) with a random walk algorithm, to study the early stages of nanocluster formation, aggregation and growth, during electrochemical deposition. This approach takes into account not only electrochemical kinetics and transport of active species, but also the surface diffusion and aggregation of adatoms and small nanoclusters. The simulation results reveal that the relative surface mobility of the nanoclusters compared to that of the adatoms plays a crucial role in the early growth stages. The number of clusters, their size and their size dispersion are influenced more significantly by nanocluster mobility than by the applied overpotential itself. Increasing the overpotential results in shorter induction times and leads to aggregation prevalence at shorter times. A higher mobility results in longer induction times, a delayed transition from nucleation to aggregation prevalence, and as a consequence, a larger surface coverage of smaller clusters with a smaller size dispersion. As a consequence, it is shown that a classical first-order nucleation kinetics equation cannot describe the evolution of the number of clusters with time, N(t), in potentiostatic electrodeposition. Instead, a more accurate representation of N(t) is provided. We show that an evaluation of N(t), which neglects the effect of nanocluster mobility and aggregation, can induce errors of several orders of magnitude in the determination of nucleation rate constants. These findings are extremely important towards evaluating the elementary electrodeposition processes, considering not only adatoms, but also nanoclusters as building blocks.

Multi-stage versus single-stage inflation and deflation cycle for alternating low pressure air mattresses to prevent pressure ulcers in hospitalised patients: a randomised-controlled clinical trial.

PubMed

Demarré, L; Beeckman, D; Vanderwee, K; Defloor, T; Grypdonck, M; Verhaeghe, S

2012-04-01

The duration and the amount of pressure and shear must be reduced in order to minimize the risk of pressure ulcer development. Alternating low pressure air mattresses with multi-stage inflation and deflation cycle of the air cells have been developed to relieve pressure by sequentially inflating and deflating the air cells. Evidence about the effectiveness of this type of mattress in clinical practice is lacking. This study aimed to compare the effectiveness of an alternating low pressure air mattress that has a standard single-stage inflation and deflation cycle of the air cells with an alternating low pressure air mattress with multi-stage inflation and deflation cycle of the air cells. A randomised controlled trial was performed in a convenience sample of 25 wards in five hospitals in Belgium. In total, 610 patients were included and randomly assigned to the experimental group (n=298) or the control group (n=312). In the experimental group, patients were allocated to an alternating low pressure air mattress with multi-stage inflation and deflation cycle of the air cells. In the control group, patients were allocated to an alternating low pressure air mattress with a standard single-stage inflation and deflation cycle of the air cells. The outcome was defined as cumulative pressure ulcer incidence (Grade II-IV). An intention-to-treat analysis was performed. There was no significant difference in cumulative pressure ulcer incidence (Grade II-IV) between both groups (Exp.=5.7%, Contr.=5.8%, p=0.97). When patients developed a pressure ulcer, the median time was 5.0 days in the experimental group (IQR=3.0-8.5) and 8.0 days in the control group (IQR=3.0-8.5) (Mann-Whitney U-test=113, p=0.182). The probability to remain pressure ulcer free during the observation period in this trial did not differ significantly between the experimental group and the control group (log-rank χ(2)=0.013, df=1, p=0.911). An alternating low pressure air mattress with multi-stage inflation and deflation of the air cells does not result in a significantly lower pressure ulcer incidence compared to an alternating low pressure air mattress with a standard single-stage inflation and deflation cycle of the air cells. Both alternating mattress types are equally effective to prevent pressure ulcer development. © 2011 Elsevier Ltd. All rights reserved.

Predictors of primary care referrals to a vascular disease prevention lifestyle program among participants in a cluster randomised trial.

PubMed

Passey, Megan E; Laws, Rachel A; Jayasinghe, Upali W; Fanaian, Mahnaz; McKenzie, Suzanne; Powell-Davies, Gawaine; Lyle, David; Harris, Mark F

2012-08-03

Cardiovascular disease accounts for a large burden of disease, but is amenable to prevention through lifestyle modification. This paper examines patient and practice predictors of referral to a lifestyle modification program (LMP) offered as part of a cluster randomised controlled trial (RCT) of prevention of vascular disease in primary care. Data from the intervention arm of a cluster RCT which recruited 36 practices through two rural and three urban primary care organisations were used. In each practice, 160 eligible high risk patients were invited to participate. Practices were randomly allocated to intervention or control groups. Intervention practice staff were trained in screening, motivational interviewing and counselling and encouraged to refer high risk patients to a LMP involving individual and group sessions. Data include patient surveys; clinical audit; practice survey on capacity for preventive care; referral records from the LMP. Predictors of referral were examined using multi-level logistic regression modelling after adjustment for confounding factors. Of 301 eligible patients, 190 (63.1%) were referred to the LMP. Independent predictors of referral were baseline BMI ≥ 25 (OR 2.87 95%CI:1.10, 7.47), physical inactivity (OR 2.90 95%CI:1.36,6.14), contemplation/preparation/action stage of change for physical activity (OR 2.75 95%CI:1.07, 7.03), rural location (OR 12.50 95%CI:1.43, 109.7) and smaller practice size (1-3 GPs) (OR 16.05 95%CI:2.74, 94.24). Providing a well-structured evidence-based lifestyle intervention, free of charge to patients, with coordination and support for referral processes resulted in over 60% of participating high risk patients being referred for disease prevention. Contrary to expectations, referrals were more frequent from rural and smaller practices suggesting that these practices may be more ready to engage with these programs. ACTRN12607000423415.

Effectiveness of a community-based nutrition programme to improve child growth in rural Ethiopia: a cluster randomized trial.

PubMed

Kang, Yunhee; Kim, Sungtae; Sinamo, Sisay; Christian, Parul

2017-01-01

Few trials have shown that promoting complementary feeding among young children is effective in improving child linear growth in resource-challenged settings. We designed a community-based participatory nutrition promotion (CPNP) programme adapting a Positive Deviance/Hearth approach that engaged mothers in 2-week nutrition sessions using the principles of 'learning by doing' around child feeding. We aimed to test the effectiveness of the CPNP for improving child growth in rural Ethiopia. A cluster randomized trial was implemented by adding the CPNP to the existing government nutrition programmes (six clusters) vs. government programmes only (six clusters). A total of 1790 children aged 6 to 12 months (876 in the intervention and 914 in the control areas) were enrolled and assessed on anthropometry every 3 months for a year. Multi-level mixed-effect regression analysis of longitudinal outcome data (n = 1475) examined the programme impact on growth, adjusting for clustering and enrollment characteristics. Compared with children 6 to 24 months of age in the control area, those in the intervention area had a greater increase in z scores for length-for-age [difference (diff): 0.021 z score/month, 95% CI: 0.008, 0.034] and weight-for-length (diff: 0.042 z score/month, 95% CI: 0.024, 0.059). At the end of the 12-month follow-up, children in the intervention area showed an 8.1% (P = 0.02) and 6.3% (P = 0.046) lower prevalence of stunting and underweight, respectively, after controlling for differences in the prevalence at enrollment, compared with the control group. A novel CPNP programme was effective in improving child growth and reducing undernutrition in this setting. © 2016 John Wiley & Sons Ltd. © 2016 John Wiley & Sons Ltd.

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

PubMed

Nixon, R M; Thompson, S G

2003-09-15

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

DOE PAGES

Scott, Jamieson; Tong, Katie; William, Hamilton; ...

2014-10-31

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

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

Scott, Jamieson; Tong, Katie; William, Hamilton

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Results of a multi-media multiple behavior obesity prevention program for adolescents.

PubMed

Mauriello, Leanne M; Ciavatta, Mary Margaret H; Paiva, Andrea L; Sherman, Karen J; Castle, Patricia H; Johnson, Janet L; Prochaska, Janice M

2010-12-01

This study reports on effectiveness trial outcomes of Health in Motion, a computer tailored multiple behavior intervention for adolescents. Using school as level of assignment, students (n=1800) from eight high schools in four states (RI, TN, MA, and NY) were stratified and randomly assigned to no treatment or a multi-media intervention for physical activity, fruit and vegetable consumption, and limited TV viewing between 2006 and 2007. Intervention effects on continuous outcomes, on movement to action and maintenance stages, and on stability within action and maintenance stages were evaluated using random effects modeling. Effects were most pronounced for fruit and vegetable consumption and for total risks across all time points and for each behavior immediately post intervention. Co-variation of behavior change occurred within the treatment group, where individuals progressing to action or maintenance for one behavior were 1.4-4.2 times more likely to make similar progress on another behavior. Health in Motion is an innovative, multiple behavior obesity prevention intervention relevant for all adolescents that relies solely on interactive technology to deliver tailored feedback. The outcomes of the effectiveness trial demonstrate both an ability to initiate behavior change across multiple energy balance behaviors simultaneously and feasibility for ease of dissemination. Copyright © 2010 The Institute For Cancer Prevention. Published by Elsevier Inc. All rights reserved.

Bad seeds produce bad crops: a single stage-process of prostate tumor invasion

PubMed Central

Man, Yan-gao; Gardner, William A.

2008-01-01

It is a commonly held belief that prostate carcinogenesis is a multi-stage process and that tumor invasion is triggered by the overproduction of proteolytic enzymes. This belief is consistent with data from cell cultures and animal models, whereas is hard to interpret several critical facts, including the presence of cancer in “healthy” young men and cancer DNA phenotype in morphologically normal prostate tissues. These facts argue that alternative pathways may exist for prostate tumor invasion in some cases. Since degradation of the basal cell layer is the most distinct sign of invasion, our recent studies have attempted to identify pre-invasive lesions with focal basal cell layer alterations. Our studies revealed that about 30% of prostate cancer patients harbored normal appearing duct or acinar clusters with a high frequency of focal basal cell layer disruptions. These focally disrupted basal cell layers had significantly reduced cell proliferation and tumor suppressor expression, whereas significantly elevated degeneration, apoptosis, and infiltration of immunoreactive cells. In sharp contrast, associated epithelial cell had significantly elevated proliferation, expression of malignancy-signature markers, and physical continuity with invasive lesions. Based on these and other findings, we have proposed that these normal appearing duct or acinar clusters are derived from monoclonal proliferation of genetically damaged stem cells and could progress directly to invasion through two pathways: 1) clonal in situ transformation (CIST) and 2) multi-potential progenitor mediated “budding” (MPMB). These pathways may contribute to early onset of prostate cancer at young ages, and to clinically more aggressive prostate tumors. PMID:18725981

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

PubMed

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.

Effect of animal-assisted interventions on depression, agitation and quality of life in nursing home residents suffering from cognitive impairment or dementia: a cluster randomized controlled trial.

PubMed

Olsen, Christine; Pedersen, Ingeborg; Bergland, Astrid; Enders-Slegers, Marie-José; Patil, Grete; Ihlebaek, Camilla

2016-12-01

The prevalence of neuropsychiatric symptoms in cognitively impaired nursing home residents is known to be very high, with depression and agitation being the most common symptoms. The possible effects of a 12-week intervention with animal-assisted activities (AAA) in nursing homes were studied. The primary outcomes related to depression, agitation and quality of life (QoL). A prospective, cluster randomized multicentre trial with a follow-up measurement 3 months after end of intervention was used. Inclusion criteria were men and women aged 65 years or older, with a diagnosis of dementia or having a cognitive deficit. Ten nursing homes were randomized to either AAA with a dog or a control group with treatment as usual. In total, 58 participants were recruited: 28 in the intervention group and 30 in the control group. The intervention consisted of a 30-min session with AAA twice weekly for 12 weeks in groups of three to six participants, led by a qualified dog handler. Norwegian versions of the Cornell Scale for Depression, the Brief Agitation Rating Scale and the Quality of Life in Late-stage Dementia scale were used. A significant effect on depression and QoL was found for participants with severe dementia at follow-up. For QoL, a significant effect of AAA was also found immediately after the intervention. No effects on agitation were found. Animal-assisted activities may have a positive effect on symptoms of depression and QoL in older people with dementia, especially those in a late stage. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Effectiveness of a stepped primary care smoking cessation intervention: cluster randomized clinical trial (ISTAPS study).

PubMed

Cabezas, Carmen; Advani, Mamta; Puente, Diana; Rodriguez-Blanco, Teresa; Martin, Carlos

2011-09-01

To evaluate the effectiveness in primary care of a stepped smoking cessation intervention based on the transtheoretical model of change. Cluster randomized trial; unit of randomization: basic care unit (family physician and nurse who care for the same group of patients); and intention-to-treat analysis. All interested basic care units (n = 176) that worked in 82 primary care centres belonging to the Spanish Preventive Services and Health Promotion Research Network in 13 regions of Spain. A total of 2,827 smokers (aged 14-85 years) who consulted a primary care centre for any reason, provided written informed consent and had valid interviews. The outcome variable was the 1-year continuous abstinence rate at the 2-year follow-up. The main variable was the study group (intervention/control). Intervention involved 6-month implementation of recommendations from a Clinical Practice Guideline which included brief motivational interviews for smokers at the precontemplation-contemplation stage, brief intervention for smokers in preparation-action who do not want help, intensive intervention with pharmacotherapy for smokers in preparation-action who want help and reinforcing intervention in the maintenance stage. Control group involved usual care. Among others, characteristics of tobacco use and motivation to quit variables were also collected. The 1-year continuous abstinence rate at the 2-year follow-up was 8.1% in the intervention group and 5.8% in the control group (P = 0.014). In the multivariate logistic regression, the odds of quitting of the intervention versus control group was 1.50 (95% confidence interval = 1.05-2.14). A stepped smoking cessation intervention based on the transtheoretical model significantly increased smoking abstinence at a 2-year follow-up among smokers visiting primary care centres. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Topology for Dominance for Network of Multi-Agent System

NASA Astrophysics Data System (ADS)

Szeto, K. Y.

2007-05-01

The resource allocation problem in evolving two-dimensional point patterns is investigated for the existence of good strategies for the construction of initial configuration that leads to fast dominance of the pattern by one single species, which can be interpreted as market dominance by a company in the context of multi-agent systems in econophysics. For hexagonal lattice, certain special topological arrangements of the resource in two-dimensions, such as rings, lines and clusters have higher probability of dominance, compared to random pattern. For more complex networks, a systematic way to search for a stable and dominant strategy of resource allocation in the changing environment is found by means of genetic algorithm. Five typical features can be summarized by means of the distribution function for the local neighborhood of friends and enemies as well as the local clustering coefficients: (1) The winner has more triangles than the loser has. (2) The winner likes to form clusters as the winner tends to connect with other winner rather than with losers; while the loser tends to connect with winners rather than losers. (3) The distribution function of friends as well as enemies for the winner is broader than the corresponding distribution function for the loser. (4) The connectivity at which the peak of the distribution of friends for the winner occurs is larger than that of the loser; while the peak values for friends for winners is lower. (5) The connectivity at which the peak of the distribution of enemies for the winner occurs is smaller than that of the loser; while the peak values for enemies for winners is lower. These five features appear to be general, at least in the context of two-dimensional hexagonal lattices of various sizes, hierarchical lattice, Voronoi diagrams, as well as high-dimensional random networks. These general local topological properties of networks are relevant to strategists aiming at dominance in evolving patterns when the interaction between the agents is local.

Case Finding of Mild Cognitive Impairment and Dementia and Subsequent Care; Results of a Cluster RCT in Primary Care.

PubMed

van den Dungen, Pim; Moll van Charante, Eric P; van de Ven, Peter M; van Marwijk, Harm W J; van der Horst, Henriëtte E; van Hout, Hein P J

2016-01-01

Despite a call for earlier diagnosis of dementia, the diagnostic yield of case finding and its impact on the mental health of patients and relatives are unclear. This study assessed the effect of a two-component intervention of case finding and subsequent care on these outcomes. In a cluster RCT we assessed whether education of family physicians (FPs; trial stage 1) resulted in more mild cognitive impairment (MCI) and dementia diagnoses among older persons in whom FPs suspected cognitive decline and whether case finding by a practice nurse and the FP (trial stage 2) added to this number of diagnoses. In addition, we assessed mental health effects of case finding and subsequent care (trial stage 2). FPs of 15 primary care practices (PCPs = clusters) judged the cognitive status of all persons ≥ 65 years. The primary outcome, new MCI and dementia diagnoses by FPs after 12 months as indicated on a list, was assessed among all persons in whom FPs suspected cognitive impairment but without a formal diagnosis of dementia. The secondary outcome, mental health of patients and their relatives, was assessed among persons consenting to participate in trial stage 2. Trial stage 1 consisted of either intervention component 1: training FPs to diagnose MCI and dementia, or control: no training. Trial stage 2 consisted of either intervention component 2: case finding of MCI and dementia and care by a trained nurse and the FP, or control: care as usual. Seven PCPs were randomized to the intervention; eight to the control condition. MCI or dementia was diagnosed in 42.3% (138/326) of persons in the intervention, and in 30.5% (98/321) in the control group (estimated difference GEE: 10.8%, OR: 1.51, 95%-CI 0.60-3.76). Among patients and relatives who consented to stage 2 of the trial (n = 145; 25%), there were no differences in mental health between the intervention and control group. We found a non-significant increase in the number of new MCI diagnoses. As we cannot exclude a clinically relevant effect, a larger study is warranted to replicate ours. Nederlands Trial Register NTR3389.

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

Dependence of evolutionary cooperation on the additive noise to the enhancement level in the spatial public goods game

NASA Astrophysics Data System (ADS)

Jia, Chun-Xiao; Liu, Run-Ran; Rong, Zhihai

2017-03-01

Either in societies or economic cycles, the benefits of a group can be affected by various unpredictable factors. We study effects of additive spatiotemporal random variations on the evolution of cooperation by introducing them to the enhancement level of the spatial public goods game. Players are located on the sites of a two-dimensional lattice and gain their payoffs from games with their neighbors by choosing cooperation or defection. We observe that a moderate intensity of variations can best favor cooperation at low enhancement levels, which resembles classical coherence resonance. Whereas for high enhancement levels, we find that the random variations cannot increase the cooperation level, but hamper cooperation instead. This discrepancy is attributed to the different roles the additive variations played in the early and late stages of evolution. In the early stage of evolution, the additive variations increase the survival probability of the players with lower average payoffs. However, in the late stage of evolution, the additive variations can promote defectors to destroy the cooperative clusters that have been formed. Our results indicate that additive spatiotemporal noise may not be as universally beneficial for cooperation as the spatial prisoner's dilemma game.

Pulsed depressed collector

DOEpatents

Kemp, Mark A

2015-11-03

A high power RF device has an electron beam cavity, a modulator, and a circuit for feed-forward energy recovery from a multi-stage depressed collector to the modulator. The electron beam cavity include a cathode, an anode, and the multi-stage depressed collector, and the modulator is configured to provide pulses to the cathode. Voltages of the electrode stages of the multi-stage depressed collector are allowed to float as determined by fixed impedances seen by the electrode stages. The energy recovery circuit includes a storage capacitor that dynamically biases potentials of the electrode stages of the multi-stage depressed collector and provides recovered energy from the electrode stages of the multi-stage depressed collector to the modulator. The circuit may also include a step-down transformer, where the electrode stages of the multi-stage depressed collector are electrically connected to separate taps on the step-down transformer.

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Percolation of the site random-cluster model by Monte Carlo method

NASA Astrophysics Data System (ADS)

Wang, Songsong; Zhang, Wanzhou; Ding, Chengxiang

2015-08-01

We propose a site random-cluster model by introducing an additional cluster weight in the partition function of the traditional site percolation. To simulate the model on a square lattice, we combine the color-assignation and the Swendsen-Wang methods to design a highly efficient cluster algorithm with a small critical slowing-down phenomenon. To verify whether or not it is consistent with the bond random-cluster model, we measure several quantities, such as the wrapping probability Re, the percolating cluster density P∞, and the magnetic susceptibility per site χp, as well as two exponents, such as the thermal exponent yt and the fractal dimension yh of the percolating cluster. We find that for different exponents of cluster weight q =1.5 , 2, 2.5 , 3, 3.5 , and 4, the numerical estimation of the exponents yt and yh are consistent with the theoretical values. The universalities of the site random-cluster model and the bond random-cluster model are completely identical. For larger values of q , we find obvious signatures of the first-order percolation transition by the histograms and the hysteresis loops of percolating cluster density and the energy per site. Our results are helpful for the understanding of the percolation of traditional statistical models.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

A sequential-move game for enhancing safety and security cooperation within chemical clusters.

PubMed

Pavlova, Yulia; Reniers, Genserik

2011-02-15

The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided. Copyright © 2010 Elsevier B.V. All rights reserved.

Application of the theory of reasoned action to promoting breakfast consumption

PubMed Central

Hosseini, Zahra; Gharlipour Gharghani, Zabihollah; Mansoori, Anahita; Aghamolaei, Teamur; Mohammadi Nasrabadi, Maryam

2015-01-01

Background: Breakfast is the most important daily meal, but neglected more than other meals by children and adolescents. The aim of this study was to evaluate the effectiveness of an educational intervention, based on the Theory of Reasoned Action (TRA) to increase breakfast consumption among school children in Bandar Abbas, Iran. Methods: In this quasi experimental study which was conducted in 2012, 88 students of four secondary schools in Bandar Abbas, south of Iran, were enrolled. Multi-stage cluster sampling was performed with random allocation of interventional and control groups. The study tool was a questionnaire which was filled by the students before and two months after the educational intervention. For data analysis, statistical tests including paired-samples t-test, independent samples t-test, Wilcoxon test, and Mann-Whitney test were used through SPSS v.18 software. Results: The result of the study showed that application of TRA significantly increased scores of behavior of breakfast consumption (p<0.01). After the intervention, a significant increase was revealed in all nutrition intakes, except for fat and sugar (p<0.01). Conclusion: The findings support application of the TRA in improving the intention and behavior of breakfast consumption. Applying this theory for designing interventions to increase breakfast eating is recommended. PMID:26913252

Process evaluation of a tobacco prevention program in Indian schools—methods, results and lessons learnt

PubMed Central

Goenka, Shifalika; Tewari, Abha; Arora, Monika; Stigler, Melissa H.; Perry, Cheryl L.; Arnold, J. P. Saulina; Kulathinal, Sangita; Reddy, K. Srinath

2010-01-01

In India, 57% of men between 15 and 54 years and 10.8% of women between 15 and 49 years use tobacco. A wide variety of tobacco gets used and the poor and the underprivileged are the dominant victims of tobacco and its adverse consequences. Project MYTRI (Mobilizing Youth for Tobacco-Related Initiatives in India) was a tobacco prevention intervention program, a cluster-randomized trial in 32 Indian schools which aimed to decrease susceptibility to tobacco use among sixth- to ninth-grade students in urban settings in India. This culture-specific intervention, which addressed both smokeless and smoked forms of tobacco, was Indian in content and communication. We qualitatively developed indicators which would help accurately measure the dose of the intervention given, received and reached. A multi-staged process evaluation was done through both subjective and objective measures. Training the teachers critically contributed toward a rigorous implementation and also correlated with the outcomes, as did a higher proportion of students participating in the classroom discussions and better peer–leader–student communication. A sizeable proportion of subjective responses were ‘socially desirable’, making objective assessment a preferred methodology even for ‘dose received’. The peer-led health activism was successful. Teachers' manuals need to be concise. PMID:20884731

Use of smokeless tobacco among male students of Zahedan universities in Iran: a cross sectional study.

PubMed

Honarmand, Marieh; Farhadmollashahi, Leila; Bekyghasemi, Mahmoud

2013-01-01

Smokeless tobacco consumption is one of the causes of oral cancer. The aim of this study was to determine the prevalence of smokeless tobacco consumption among male students of Zahedan universities and associated factors in 2012. In this cross-sectional study, 431 students were selected from the universities of Zahedan using multi-stage random cluster sampling. The data collection tool was a questionnaire including questions about demographic information, history of smokeless tobacco consumption, and awareness of smokeless tobacco hazards. Data were analyzed by SPSS19 using Chi-square test and multinomial logistic regression, with p<0.05 considered significant. At the time of conducting this study, 102 students (23.7%) had already consumed smokeless tobacco and 49 students (11.4%) were current users (consuming at least once in 30 days before the study). There was a significant relationship between history of smokeless tobacco consumption, university/college, place of living, mean GPA, and mother's education level (p<0.05). Also there was a significant association between knowledge and prevalence of smokeless tobacco use (p<0.001). There is a relatively high prevalence of smokeless tobacco consumption among the male students of universities of Zahedan, which shows the need to emphasize the provision and implementation of prevention programs in universities.

Multi-exemplar affinity propagation.

PubMed

Wang, Chang-Dong; Lai, Jian-Huang; Suen, Ching Y; Zhu, Jun-Yong

2013-09-01

The affinity propagation (AP) clustering algorithm has received much attention in the past few years. AP is appealing because it is efficient, insensitive to initialization, and it produces clusters at a lower error rate than other exemplar-based methods. However, its single-exemplar model becomes inadequate when applied to model multisubclasses in some situations such as scene analysis and character recognition. To remedy this deficiency, we have extended the single-exemplar model to a multi-exemplar one to create a new multi-exemplar affinity propagation (MEAP) algorithm. This new model automatically determines the number of exemplars in each cluster associated with a super exemplar to approximate the subclasses in the category. Solving the model is NP-hard and we tackle it with the max-sum belief propagation to produce neighborhood maximum clusters, with no need to specify beforehand the number of clusters, multi-exemplars, and superexemplars. Also, utilizing the sparsity in the data, we are able to reduce substantially the computational time and storage. Experimental studies have shown MEAP's significant improvements over other algorithms on unsupervised image categorization and the clustering of handwritten digits.

Effect Sizes in Cluster-Randomized Designs

ERIC Educational Resources Information Center

Hedges, Larry V.

2007-01-01

Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…

Research of seafloor topographic analyses for a staged mineral exploration

NASA Astrophysics Data System (ADS)

Ikeda, M.; Kadoshima, K.; Koizumi, Y.; Yamakawa, T.; Asakawa, E.; Sumi, T.; Kose, M.

2016-12-01

J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-cost and high-efficiency exploration system for seafloor hydrothermal massive sulfide (SMS) deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We proposed the multi-stage approach, which is designed from the regional scaled to the detail scaled survey stages through semi-detail scaled, focusing a prospective area by seafloor topographic analyses. We applied this method to the area of more than 100km x 100km around Okinawa Trough, including some well-known mineralized deposits. In the regional scale survey, we assume survey areas are more than 100 km x 100km. Then the spatial resolution of topography data should be bigger than 100m. The 500 m resolution data which is interpolated into 250 m resolution was used for extracting depression and performing principal component analysis (PCA) by the wavelength obtained from frequency analysis. As the result, we have successfully extracted the areas having the topographic features quite similar to well-known mineralized deposits. In the semi-local survey stage, we use the topography data obtained by bathymetric survey using multi-narrow beam echo-sounder. The 30m-resolution data was used for extracting depression, relative-large mounds, hills, lineaments as fault, and also for performing frequency analysis. As the result, wavelength as principal component constituting in the target area was extracted by PCA of wavelength obtained from frequency analysis. Therefore, color image was composited by using the second principal component (PC2) to the forth principal component (PC4) in which the continuity of specific wavelength was observed, and consistent with extracted lineaments. In addition, well-known mineralized deposits were discriminated in the same clusters by using clustering from PC2 to PC4.We applied the results described above to a new area, and successfully extract the quite similar area in vicinity to one of the well-known mineralized deposits. So we are going to verify the extracted areas by using geophysical methods, such as vertical cable seismic and time-domain EM survey, developed in this SIP project.

Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support.

PubMed

Proctor, Enola; Luke, Douglas; Calhoun, Annaliese; McMillen, Curtis; Brownson, Ross; McCrary, Stacey; Padek, Margaret

2015-06-11

Little is known about how well or under what conditions health innovations are sustained and their gains maintained once they are put into practice. Implementation science typically focuses on uptake by early adopters of one healthcare innovation at a time. The later-stage challenges of scaling up and sustaining evidence-supported interventions receive too little attention. This project identifies the challenges associated with sustainability research and generates recommendations for accelerating and strengthening this work. A multi-method, multi-stage approach, was used: (1) identifying and recruiting experts in sustainability as participants, (2) conducting research on sustainability using concept mapping, (3) action planning during an intensive working conference of sustainability experts to expand the concept mapping quantitative results, and (4) consolidating results into a set of recommendations for research, methodological advances, and infrastructure building to advance understanding of sustainability. Participants comprised researchers, funders, and leaders in health, mental health, and public health with shared interest in the sustainability of evidence-based health care. Prompted to identify important issues for sustainability research, participants generated 91 distinct statements, for which a concept mapping process produced 11 conceptually distinct clusters. During the conference, participants built upon the concept mapping clusters to generate recommendations for sustainability research. The recommendations fell into three domains: (1) pursue high priority research questions as a unified agenda on sustainability; (2) advance methods for sustainability research; (3) advance infrastructure to support sustainability research. Implementation science needs to pursue later-stage translation research questions required for population impact. Priorities include conceptual consistency and operational clarity for measuring sustainability, developing evidence about the value of sustaining interventions over time, identifying correlates of sustainability along with strategies for sustaining evidence-supported interventions, advancing the theoretical base and research designs for sustainability research, and advancing the workforce capacity, research culture, and funding mechanisms for this important work.

Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

PubMed

Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

2017-04-01

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

The effects of multi-disciplinary psycho-social care on socio-economic problems in cancer patients: a cluster-randomized trial.

PubMed

Singer, Susanne; Roick, Julia; Meixensberger, Jürgen; Schiefke, Franziska; Briest, Susanne; Dietz, Andreas; Papsdorf, Kirsten; Mössner, Joachim; Berg, Thomas; Stolzenburg, Jens-Uwe; Niederwieser, Dietger; Keller, Annette; Kersting, Anette; Danker, Helge

2018-06-01

We examined whether multi-disciplinary stepped psycho-social care decreases financial problems and improves return-to-work in cancer patients. In a university hospital, wards were randomly allocated to either stepped or standard care. Stepped care comprised screening for financial problems, consultation between doctor and patient, and the provision of social service. Outcomes were financial problems at the time of discharge and return-to-work in patients < 65 years old half a year after baseline. The analysis employed mixed-effect multivariate regression modeling. Thirteen wards were randomized and 1012 patients participated (n = 570 in stepped care and n = 442 in standard care). Those who reported financial problems at baseline were less likely to have financial problems at discharge when they had received stepped care (odds ratio (OR) 0.2, 95% confidence interval (CI) 0.1, 0.7; p = 0.01). There was no evidence for an effect of stepped care on financial problems in patients without such problems at baseline (OR 1.1, CI 0.5, 2.6; p = 0.82). There were 399 patients < 65 years old who were not retired at baseline. In this group, there was no evidence for an effect of stepped care on being employed half a year after baseline (OR 0.7, CI 0.3, 2.0; p = 0.52). NCT01859429 CONCLUSIONS: Financial problems can be avoided more effectively with multi-disciplinary stepped psycho-social care than with standard care in patients who have such problems.

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects.

PubMed

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called "cluster randomization"). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Does routine psychosocial screening improve referral to psychosocial care providers and patient-radiotherapist communication? A cluster randomized controlled trial.

PubMed

Braeken, Anna P B M; Lechner, Lilian; Eekers, Daniëlle B P; Houben, Ruud M A; van Gils, Francis C J M; Ambergen, Ton; Kempen, Gertrudis I J M

2013-11-01

This study tests whether using a screening instrument improves referral to psychosocial care providers (e.g. psychologist) and facilitates patient-radiotherapist communication. A cluster randomized controlled trial was used. Fourteen radiotherapists were randomly allocated to the experimental or control group and 568 of their patients received care in accordance with the group to which their radiotherapist was allocated. Patients in the experimental group were asked to complete a screening instrument before and at the end of the radiation treatment period. All patients were requested to complete questionnaires concerning patient-physician communication after the first consultation and concerning psychosocial care 3 and 12 months post-intervention. Patients who completed the screening instrument were referred to social workers at an earlier stage than patients who did not (P<0.01). No effects were observed for numbers of referred patients, or for improved patient-radiotherapist communication. Our results suggest that a simple screening procedure can be valuable for the timely treatment of psychosocial problems in patients. Future efforts should be directed at appropriate timing of screening and enhancing physicians' awareness regarding the importance of identifying, discussing and treating psychosocial problems in cancer patients. Psychosocial screening can be enhanced by effective radiotherapist-patient communication. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role 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 improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has 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.

Rationale and design of the Helping Ease Renal failure with Bupi Yishen compared with the Angiotensin II Antagonist Losartan (HERBAAL) trial: a randomized controlled trial in non-diabetes stage 4 chronic kidney disease.

PubMed

Mao, Wei; Zhang, Lei; Zou, Chuan; Li, Chuang; Wu, Yifan; Su, Guobin; Guo, Xinfeng; Wu, Yuchi; Lu, Fuhua; Lin, Qizhan; Wang, Lixin; Bao, Kun; Xu, Peng; Zhao, Daixin; Peng, Yu; Liang, Hui; Lu, Zhaoyu; Gao, Yanxiang; Jie, Xina; Zhang, La; Wen, Zehuai; Liu, Xusheng

2015-09-08

Chronic kidney disease (CKD) is a global public health problem. Currently, as for advanced CKD populations, medication options limited in angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB), which were partially effective. A Chinese herbal compound, Bupi Yishen formula, has showed renal protective potential in experiments and retrospective studies. This study will evaluate the efficacy and safety of Bupi Yishen formula (BYF) in patients with CKD stage 4. In this double blind, double dummy, randomized controlled trial (RCT), there will be 554 non-diabetes stage 4 CKD patients from 16 hospitals included and randomized into two groups: Chinese medicine (CM) group or losartan group. All patients will receive basic conventional therapy. Patients in CM group will be treated with BYF daily while patients in control group will receive losartan 100 mg daily for one year. The primary outcome is the change in estimated glomerular filtration rate (eGFR) over 12 months. Secondary outcomes include the incidence of endpoint events, liver and kidney function, urinary protein creatinine ratio, cardiovascular function and quality of life. This study will be the first multi-center, double blind RCT to assess whether BYF, compared with losartan, will have beneficial effects on eGFR for non-diabetes stage 4 CKD patients. The results will help to provide evidence-based recommendations for clinicians. Chinese Clinical Trial Registry Number: ChiCTR-TRC-10001518 .

Knowledge, Attitude and Practices of Vector-Borne Disease Prevention during the Emergence of a New Arbovirus: Implications for the Control of Chikungunya Virus in French Guiana.

PubMed

Fritzell, Camille; Raude, Jocelyn; Adde, Antoine; Dusfour, Isabelle; Quenel, Philippe; Flamand, Claude

2016-11-01

During the last decade, French Guiana has been affected by major dengue fever outbreaks. Although this arbovirus has been a focus of many awareness campaigns, very little information is available about beliefs, attitudes and behaviors regarding vector-borne diseases among the population of French Guiana. During the first outbreak of the chikungunya virus, a quantitative survey was conducted among high school students to study experiences, practices and perceptions related to mosquito-borne diseases and to identify socio-demographic, cognitive and environmental factors that could be associated with the engagement in protective behaviors. A cross-sectional survey was administered in May 2014, with a total of 1462 students interviewed. Classrooms were randomly selected using a two-stage selection procedure with cluster samples. A multiple correspondence analysis (MCA) associated with a hierarchical cluster analysis and with an ordinal logistic regression was performed. Chikungunya was less understood and perceived as a more dreadful disease than dengue fever. The analysis identified three groups of individual protection levels against mosquito-borne diseases: "low" (30%), "moderate" (42%) and "high" (28%)". Protective health behaviors were found to be performed more frequently among students who were female, had a parent with a higher educational status, lived in an individual house, and had a better understanding of the disease. This study allowed us to estimate the level of protective practices against vector-borne diseases among students after the emergence of a new arbovirus. These results revealed that the adoption of protective behaviors is a multi-factorial process that depends on both sociocultural and cognitive factors. These findings may help public health authorities to strengthen communication and outreach strategies, thereby increasing the adoption of protective health behaviors, particularly in high-risk populations.

The improvement and simulation for LEACH clustering routing protocol

NASA Astrophysics Data System (ADS)

Ji, Ai-guo; Zhao, Jun-xiang

2017-01-01

An energy-balanced unequal multi-hop clustering routing protocol LEACH-EUMC is proposed in this paper. The candidate cluster head nodes are elected firstly, then they compete to be formal cluster head nodes by adding energy and distance factors, finally the date are transferred to sink through multi-hop. The results of simulation show that the improved algorithm is better than LEACH in network lifetime, energy consumption and the amount of data transmission.

Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

ERIC Educational Resources Information Center

Sanders, Elizabeth A.

2011-01-01

This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

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

NASA Astrophysics Data System (ADS)

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.

Cluster randomization and political philosophy.

PubMed

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.

Study protocol: a cluster randomized controlled trial to assess the effectiveness of a multi-pronged behavioural intervention to improve use of personal protective equipment among migrant workers exposed to organic solvents in small and medium-sized enterprises.

PubMed

Chen, Wen; Li, Tongyang; Zou, Guanyang; Li, Xudong; Shi, Leiyu; Feng, Shanshan; Shi, Jingrong; Zhou, Fangjing; Han, Siqi; Ling, Li

2016-07-16

In China, most of migrant workers work in the small and medium-sized enterprises (SMEs) and are a vulnerable group for occupational health. Migrant workers are at increased risk of occupational health risks due to poor occupational health behaviours such as the low use of personal protective equipment (PPE). However, there is a lack of solid evidence regarding how to improve the use of PPE among migrant workers in SMEs. The current study will assess the effectiveness of a multi-pronged behavioural intervention designed to promote PPE utilization among migrant workers exposed to organic solvents in SMEs. This is a single blind, three-arm cluster randomized trial with 60 SMEs equally randomized to receive a top-down intervention (i.e. general health education and mHealth intervention provided by researchers) or a comprehensive intervention (which includes both top-down intervention and peer education) or a control condition (participants will not receive the intervention, but study measures will be obtained). Interventions will be conducted at the SMEs level for 6 months and all eligible migrant workers in these SMEs will be enrolled into the trial. The primary outcome is effective use of PPE during the last week. The secondary outcomes are occupational health knowledge and attitude and participation in occupational health check-up. Data will be collected and assessed at baseline; 3 months post baseline and the end of the intervention. This theory- and evidence based intervention will contribute to the limited evidence of behaviour change intervention in improving PPE utilization of migrant workers in SMEs, and provide timely evidence for the development of basic occupational health services in China and elsewhere with similar industrialization contexts. ChiCTR-IOR-15006929 . Registered on 16 August 2015.

Study protocol for a multi-component kindergarten-based intervention to promote healthy diets in toddlers: a cluster randomized trial.

PubMed

Helland, Sissel H; Bere, Elling; Øverby, Nina Cecilie

2016-03-17

There is concern about the lack of diversity in children's diets, particularly low intakes of fruit and vegetables and high intakes of unhealthy processed food. This may be a factor in the rising prevalence of obesity. A reason for the lack of diversity in children's diets may be food neophobia. This study aimed to promote a healthy and varied diet among toddlers in kindergarten. The primary objectives were to reduce food neophobia in toddlers, and promote healthy feeding practices among kindergarten staff and parents. Secondary objectives were to increase food variety in toddlers' diets and reduce future overweight and obesity in these children. This is an ongoing, cluster randomized trial. The intervention finished in 2014, but follow-up data collection is not yet complete. Eighteen randomly selected kindergartens located in two counties in Norway with enrolled children born in 2012 participated in the intervention. The kindergartens were matched into pairs based on background information, and randomly assigned to the intervention or control groups. A 9-week multi-component intervention was implemented, with four main elements: 1) kindergarten staff implemented a pedagogical tool (Sapere method) in daily sessions to promote willingness to try new food; 2) kindergarten staff prepared and served the toddlers a cooked lunch from a menu corresponding to the pedagogical sessions; 3) kindergarten staff were encouraged to follow 10 meal principles on modeling, responsive feeding, repeated exposure, and enjoyable meals; and 4) parents were encouraged to read information and apply relevant feeding practices at home. The control group continued their usual practices. Preference taste tests were conducted to evaluate behavioral food neophobia, and children's height and weight were measured. Parents and staff completed questionnaires before and after the intervention. Data have not yet been analyzed. This study provides new knowledge about whether or not a Sapere-sensory education and healthy meal intervention targeting children, kindergarten staff, and parents will: reduce levels of food neophobia in toddlers; improve parental and kindergarten feeding practices; improve children's dietary variety; and reduce childhood overweight and obesity. ISRCTN74823448 DOI 10.1186/ISRCTN74823448.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

Community-centred eco-bio-social approach to control dengue vectors: an intervention study from Myanmar

PubMed Central

Wai, Khin Thet; Htun, Pe Than; Oo, Tin; Myint, Hla; Lin, Zaw; Kroeger, Axel; Sommerfeld, Johannes; Petzold, Max

2012-01-01

Objectives To build up and analyse the feasibility, process, and effectiveness of a partnership-driven ecosystem management intervention in reducing dengue vector breeding and constructing sustainable partnerships among multiple stakeholders. Methods A community-based intervention study was conducted from May 2009 to January 2010 in Yangon city. Six high-risk and six low-risk clusters were randomized and allocated as intervention and routine service areas, respectively. For each cluster, 100 households were covered. Bi-monthly entomological evaluations (i.e. larval and pupal surveys) and household acceptability surveys at the end of 6-month intervention period were conducted, supplemented by qualitative evaluations. Intervention description The strategies included eco-friendly multi-stakeholder partner groups (Thingaha) and ward-based volunteers, informed decision-making of householders, followed by integrated vector management approach. Findings Pupae per person index (PPI) decreased at the last evaluation by 5.7% (0.35–0.33) in high-risk clusters. But in low-risk clusters, PPI remarkably decreased by 63.6% (0.33–0.12). In routine service area, PPI also decreased due to availability of Temephos after Cyclone Nargis. As for total number of pupae in all containers, when compared to evaluation 1, there was a reduction of 18.6% in evaluation 2 and 44.1% in evaluation 3 in intervention area. However, in routine service area, more reduction was observed. All intervention tools were found as acceptable, being feasible to implement by multi-stakeholder partner groups. Conclusions The efficacy of community-controlled partnership-driven interventions was found to be superior to the vertical approach in terms of sustainability and community empowerment. PMID:23318238

Community-centred eco-bio-social approach to control dengue vectors: an intervention study from Myanmar.

PubMed

Wai, Khin Thet; Htun, Pe Than; Oo, Tin; Myint, Hla; Lin, Zaw; Kroeger, Axel; Sommerfeld, Johannes; Petzold, Max

2012-12-01

To build up and analyse the feasibility, process, and effectiveness of a partnership-driven ecosystem management intervention in reducing dengue vector breeding and constructing sustainable partnerships among multiple stakeholders. A community-based intervention study was conducted from May 2009 to January 2010 in Yangon city. Six high-risk and six low-risk clusters were randomized and allocated as intervention and routine service areas, respectively. For each cluster, 100 households were covered. Bi-monthly entomological evaluations (i.e. larval and pupal surveys) and household acceptability surveys at the end of 6-month intervention period were conducted, supplemented by qualitative evaluations. Intervention description: The strategies included eco-friendly multi-stakeholder partner groups (Thingaha) and ward-based volunteers, informed decision-making of householders, followed by integrated vector management approach. Pupae per person index (PPI) decreased at the last evaluation by 5·7% (0·35-0·33) in high-risk clusters. But in low-risk clusters, PPI remarkably decreased by 63·6% (0·33-0·12). In routine service area, PPI also decreased due to availability of Temephos after Cyclone Nargis. As for total number of pupae in all containers, when compared to evaluation 1, there was a reduction of 18·6% in evaluation 2 and 44·1% in evaluation 3 in intervention area. However, in routine service area, more reduction was observed. All intervention tools were found as acceptable, being feasible to implement by multi-stakeholder partner groups. The efficacy of community-controlled partnership-driven interventions was found to be superior to the vertical approach in terms of sustainability and community empowerment.

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects

PubMed Central

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies. PMID:28584874

The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions

PubMed Central

Esserman, Denise; Allore, Heather G.; Travison, Thomas G.

2016-01-01

Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an intervention to all within a group (e.g. school-level immunization). Because participants in the same cluster receive the same intervention, CRT may approximate clinical practice, and may produce generalizable findings. However, when not properly designed or interpreted, CRT may induce biased results. CRT designs have features that add complexity to statistical estimation and inference. Chief among these is the cluster-level correlation in response measurements induced by the randomization. A critical consideration is the experimental unit of inference; often it is desirable to consider intervention effects at the level of the individual rather than the cluster. Finally, given that the number of clusters available may be limited, simple forms of randomization may not achieve balance between intervention and control arms at either the cluster- or participant-level. In non-clustered clinical trials, balance of key factors may be easier to achieve because the sample can be homogenous by exclusion of participants with multiple chronic conditions (MCC). CRTs, which are often pragmatic, may eschew such restrictions. Failure to account for imbalance may induce bias and reducing validity. This article focuses on the complexities of randomization in the design of CRTs, such as the inclusion of patients with MCC, and imbalances in covariate factors across clusters. PMID:27478520

Experimental research on the stability and the multilongitudinal mode interference of bidirectional outputs of LD-pumped solid state ring laser

NASA Astrophysics Data System (ADS)

Wan, Shunping; Tian, Qian; Sun, Liqun; Yao, Minyan; Mao, Xianhui; Qiu, Hongyun

2004-05-01

This paper reports an experimental research on the stability of bidirectional outputs and multi-longitudinal mode interference of laser diode end-pumped Nd:YVO4 solid-state ring laser (DPSSL). The bidirectional, multi-longitudinal and TEM00 mode continuous wave outputs are obtained and the output powers are measured and their stabilities are analyzed respectively. The spectral characteristic of the outputs is measured. The interfering pattern of the bidirectional longitudinal mode outputs is obtained and analyzed in the condition of the ring cavity with rotation velocity. The movement of the interfering fringe of the multi-longitudinal modes is very sensitive to the deformation of the setup base and the fluctuation of the intracavity air, but is stationary or randomly dithers when the stage is rotating.

Time-Resolved Surveys of Stellar Clusters

NASA Astrophysics Data System (ADS)

Eyer, Laurent; Eggenberger, Patrick; Greco, Claudia; Saesen, Sophie; Anderson, Richard I.; Mowlavi, Nami

We describe the information that can be gained when a survey is done multi-epoch, and its particular impact in open cluster research. We first explain the irreplaceable information that multi-epoch observations are giving within astrometry, photometry and spectroscopy. Then we give three examples of results on open clusters from multi-epoch surveys, namely, the distance to the Pleiades, the angular momentum evolution of low mass stars and asteroseismology. Finally we mention several very large surveys, which are ongoing or planned for the future, Gaia, JASMINE, LSST, and VVV.

Relaxation channels of multi-photon excited xenon clusters

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

Serdobintsev, P. Yu.; Melnikov, A. S.; Department of Physics, St. Petersburg State University, Saint Petersburg 198904

2015-09-21

The relaxation processes of the xenon clusters subjected to multi-photon excitation by laser radiation with quantum energies significantly lower than the thresholds of excitation of atoms and ionization of clusters were studied. Results obtained by means of the photoelectron spectroscopy method showed that desorption processes of excited atoms play a significant role in the decay of two-photon excited xenon clusters. A number of excited states of xenon atoms formed during this process were discovered and identified.

Bayesian network meta-analysis for cluster randomized trials with binary outcomes.

PubMed

Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard

2017-06-01

Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services research, where, for example, medical practices are the units of randomization but the outcome is measured at the patient level. Combination of the results of cluster randomized trials is challenging. In this tutorial, we examine and compare different approaches for the incorporation of cluster randomized trials in a (network) meta-analysis. Furthermore, we provide practical insight on the implementation of the models. In simulation studies, it is shown that some of the examined approaches lead to unsatisfying results. However, there are alternatives which are suitable to combine cluster randomized trials in a network meta-analysis as they are unbiased and reach accurate coverage rates. In conclusion, the methodology can be extended in such a way that an adequate inclusion of the results obtained in cluster randomized trials becomes feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Percolation and epidemics in random clustered networks

NASA Astrophysics Data System (ADS)

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.

Using Cluster Bootstrapping to Analyze Nested Data with a Few Clusters

ERIC Educational Resources Information Center

Huang, Francis L.

2018-01-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…

Sydney Playground Project: A Cluster-Randomized Trial to Increase Physical Activity, Play, and Social Skills

ERIC Educational Resources Information Center

Bundy, Anita; Engelen, Lina; Wyver, Shirley; Tranter, Paul; Ragen, Jo; Bauman, Adrian; Baur, Louise; Schiller, Wendy; Simpson, Judy M.; Niehues, Anita N.; Perry, Gabrielle; Jessup, Glenda; Naughton, Geraldine

2017-01-01

Background: We assessed the effectiveness of a simple intervention for increasing children's physical activity, play, perceived competence/social acceptance, and social skills. Methods: A cluster-randomized controlled trial was conducted, in which schools were the clusters. Twelve Sydney (Australia) primary schools were randomly allocated to…

Design and Initial Results of a Multi-Phase Randomized Trial of Ceftriaxone in Amyotrophic Lateral Sclerosis

PubMed Central

Berry, James D.; Shefner, Jeremy M.; Conwit, Robin; Schoenfeld, David; Keroack, Myles; Felsenstein, Donna; Krivickas, Lisa; David, William S.; Vriesendorp, Francine; Pestronk, Alan; Caress, James B.; Katz, Jonathan; Simpson, Ericka; Rosenfeld, Jeffrey; Pascuzzi, Robert; Glass, Jonathan; Rezania, Kourosh; Rothstein, Jeffrey D.; Greenblatt, David J.; Cudkowicz, Merit E.

2013-01-01

Objectives Ceftriaxone increases expression of the astrocytic glutamate transporter, EAAT2, which might protect from glutamate-mediated excitotoxicity. A trial using a novel three stage nonstop design, incorporating Phases I-III, tested ceftriaxone in ALS. Stage 1 determined the cerebrospinal fluid pharmacokinetics of ceftriaxone in subjects with ALS. Stage 2 evaluated safety and tolerability for 20-weeks. Analysis of the pharmacokinetics, tolerability, and safety was used to determine the ceftriaxone dosage for Stage 3 efficacy testing. Methods In Stage 1, 66 subjects at ten clinical sites were enrolled and randomized equally into three study groups receiving intravenous placebo, ceftriaxone 2 grams daily or ceftriaxone 4 grams daily divided BID. Participants provided serum and cerebrospinal fluid for pharmacokinetic analysis on study day 7. Participants continued their assigned treatment in Stage 2. The Data and Safety Monitoring Board (DSMB) reviewed the data after the last participants completed 20 weeks on study drug. Results Stage 1 analysis revealed linear pharmacokinetics, and CSF trough levels for both dosage levels exceeding the pre-specified target trough level of 1 µM (0.55 µg/mL). Tolerability (Stages 1 and 2) results showed that ceftriaxone at dosages up to 4 grams/day was well tolerated at 20 weeks. Biliary adverse events were more common with ceftriaxone but not dose-dependent and improved with ursodeoxycholic (ursodiol) therapy. Conclusions The goals of Stages 1 and 2 of the ceftriaxone trial were successfully achieved. Based on the pre-specified decision rules, the DSMB recommended the use of ceftriaxone 4 g/d (divided BID) for Stage 3, which recently closed. Trial Registration ClinicalTrials.gov NCT00349622. PMID:23613806

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Cluster randomized trial in smoking cessation with intensive advice in diabetic patients in primary care. ITADI Study

PubMed Central

2010-01-01

Background It is a priority to achieve smoking cessation in diabetic smokers, given that this is a group of patients with elevated cardiovascular risk. Furthermore, tobacco has a multiplying effect on micro and macro vascular complications. Smoking abstinence rates increase as the intensity of the intervention, length of the intervention and number and diversity of contacts with the healthcare professional during the intervention increases. However, there are few published studies about smoking cessation in diabetics in primary care, a level of healthcare that plays an essential role in these patients. Therefore, the aim of the present study is to evaluate the effectiveness of an intensive smoking cessation intervention in diabetic patients in primary care. Methods/Design Cluster randomized trial, controlled and multicentric. Randomization unit: Primary Care Team. Study population: 546 diabetic smokers older than 14 years of age whose disease is controlled by one of the primary care teams in the study. Outcome Measures: Continuous tobacco abstinence (a person who has not smoked for at least six months and with a CO level of less than 6 ppm measured by a cooximeter) , evolution in the Prochaska and DiClemente's Transtheoretical Model of Change, number of cigarettes/day, length of the visit. Point of assessment: one- year post- inclusion in the study. Intervention: Brief motivational interview for diabetic smokers at the pre-contemplation and contemplation stage, intensive motivational interview with pharmacotherapy for diabetic smokers in the preparation-action stage and reinforcing intevention in the maintenance stage. Statistical Analysis: A descriptive analysis of all variables will be done, as well as a multilevel logistic regression and a Poisson regression. All analyses will be done with an intention to treatment basis and will be fitted for potential confounding factors and variables of clinical importance. Statistical packages: SPSS15, STATA10 y HLM6. Discussion The present study will try to describe the profile of a diabetic smoker who receives the most benefit from an intensive intervention in primary care. The results will be useful for primary care professionals in their usual clinical practice. Trial Registration Clinical Trials.gov Identifier: NCT00954967 PMID:20132540

Cluster randomized trial in smoking cessation with intensive advice in diabetic patients in primary care. ITADI Study.

PubMed

Roig, Lydia; Perez, Santiago; Prieto, Gemma; Martin, Carlos; Advani, Mamta; Armengol, Angelina; Roura, Pilar; Manresa, Josep Maria; Briones, Elena

2010-02-04

It is a priority to achieve smoking cessation in diabetic smokers, given that this is a group of patients with elevated cardiovascular risk. Furthermore, tobacco has a multiplying effect on micro and macro vascular complications. Smoking abstinence rates increase as the intensity of the intervention, length of the intervention and number and diversity of contacts with the healthcare professional during the intervention increases. However, there are few published studies about smoking cessation in diabetics in primary care, a level of healthcare that plays an essential role in these patients. Therefore, the aim of the present study is to evaluate the effectiveness of an intensive smoking cessation intervention in diabetic patients in primary care. Cluster randomized trial, controlled and multicentric. Randomization unit: Primary Care Team. 546 diabetic smokers older than 14 years of age whose disease is controlled by one of the primary care teams in the study. Continuous tobacco abstinence (a person who has not smoked for at least six months and with a CO level of less than 6 ppm measured by a cooximeter) , evolution in the Prochaska and DiClemente's Transtheoretical Model of Change, number of cigarettes/day, length of the visit. Point of assessment: one- year post- inclusion in the study. Brief motivational interview for diabetic smokers at the pre-contemplation and contemplation stage, intensive motivational interview with pharmacotherapy for diabetic smokers in the preparation-action stage and reinforcing intevention in the maintenance stage. A descriptive analysis of all variables will be done, as well as a multilevel logistic regression and a Poisson regression. All analyses will be done with an intention to treatment basis and will be fitted for potential confounding factors and variables of clinical importance. Statistical packages: SPSS15, STATA10 y HLM6. The present study will try to describe the profile of a diabetic smoker who receives the most benefit from an intensive intervention in primary care. The results will be useful for primary care professionals in their usual clinical practice. Clinical Trials.gov Identifier: NCT00954967.

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

Prediction models for clustered data: comparison of a random intercept and standard regression model.

PubMed

Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

2013-02-15

When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Adaptive functioning and its associated factors among girl children residing in slum areas of Bhubaneswar, India.

PubMed

Panigrahi, Ansuman; Das, Sai C; Sahoo, Prabhudarsan

2018-01-01

Adaptive functioning develops throughout early childhood, and its limitation is a reflection that the child has developmental or emotional problems or even mental retardation. Little is known about the adaptive functioning or developmental status of slum children. The present cross-sectional study was undertaken during the year 2014 to assess the status of adaptive functioning among girl children aged between 3 and 9 years residing in slum areas of Bhubaneswar and to explore the factors associated with poor adaptive functioning. Stratified multi-stage cluster random sampling technique was used to select the study population; 256 mother-child pairs from 256 households in selected slum areas were studied. Demographic information was collected, and adaptive functioning was assessed using the modified Vineland Social Maturity Scale. Univariate and multivariate analyses was carried out using Statistical Package for Social Sciences (SPSS) version 21. One-fifth (54, 21%) of the girls sampled had poor adaptive functioning, and 44 (17%) had poor cognitive functioning. Multivariate analysis revealed that the age of the child, parents' education, presence of stunting in children and attending school/early childhood centre were strong predictors of adaptive functioning in slum children. One-fifth of girls from slums are developmentally vulnerable; parental education, stunting and early childhood education or exposure to schooling are modifiable factors influencing children's adaptive functioning. Health, education and welfare sectors need to be aware of this so that a multi-pronged approach can be planned to properly address this issue in one of the most disadvantaged sections of the society. © 2017 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Betel-quid dependence domains and syndrome associated with betel-quid ingredients among chewers: an Asian multi-country evidence.

PubMed

Lee, Chien-Hung; Chiang, Shang-Lun; Ko, Albert Min-Shan; Hua, Chun-Hung; Tsai, Ming-Hsui; Warnakulasuriya, Saman; Ibrahim, Salah Osman; Sunarjo; Zain, Rosnah Binti; Ling, Tian-You; Huang, Chieh-Liang; Lane, Hsien-Yuan; Lin, Cheng-Chieh; Ko, Ying-Chin

2014-07-01

Betel-quid (BQ) contains biologically psychoactive ingredients; however, data are limited concerning the symptoms and syndrome of BQ dependence among chewers. The aims of this study were to evaluate the ingredients-associated BQ dependence syndrome and country-specific chewing features and behaviour for BQ dependence among chewers from six Asian communities. An intercountry Asian Betel-quid Consortium study. Six Asian general communities in Taiwan, Mainland China, Indonesia, Malaysia, Sri Lanka and Nepal. Six multi-stage random samples of BQ chewers in the Asian Betel-quid Consortium study (n = 2078). All chewers were evaluated for BQ dependence using the DSM-IV and ICD-10 criteria. The 12-month BQ dependence rate was 12.5-92.6% and 47.9-99.3% (P = 0.023) among tobacco-free and tobacco-added BQ chewers across the six Asian communities, with a higher dependence rate in chewers who used tobacco-free BQ with lime added than without (23.3-95.6% versus 4.0%, P ≤ 0.001). Taiwanese and Hunanese BQ chewers both notably endorsed the dependency domain of 'time spent chewing'. 'Tolerance' and 'withdrawal' were the major dependence domains associated with the Nepalese and Indonesian chewers, with high BQ dependence rates. Malaysian and Sri Lankan chewers formed a BQ dependence cluster linked closely to 'craving'. In Sri Lanka, the quantity consumed explained 90.5% (P < 0.001) of the excess dependence risk for tobacco-added use, and could be a mediator between tobacco-derived psychoactive effect and BQ dependence development. DSM-IV criteria for dependence apply to a significant proportion of betel quid users in Asian communities, more so if they use it with tobacco or lime. © 2014 Society for the Study of Addiction.

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

A priori evaluation of two-stage cluster sampling for accuracy assessment of large-area land-cover maps

USGS Publications Warehouse

Wickham, J.D.; Stehman, S.V.; Smith, J.H.; Wade, T.G.; Yang, L.

2004-01-01

Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster sample is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priorievaluation was used as a decision-making tool when implementing the NLCD design.

Storage assignment optimization in a multi-tier shuttle warehousing system

NASA Astrophysics Data System (ADS)

Wang, Yanyan; Mou, Shandong; Wu, Yaohua

2016-03-01

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Metal mixtures in urban and rural populations in the US: The Multi-Ethnic Study of Atherosclerosis and the Strong Heart Study.

PubMed

Pang, Yuanjie; Peng, Roger D; Jones, Miranda R; Francesconi, Kevin A; Goessler, Walter; Howard, Barbara V; Umans, Jason G; Best, Lyle G; Guallar, Eliseo; Post, Wendy S; Kaufman, Joel D; Vaidya, Dhananjay; Navas-Acien, Ana

2016-05-01

Natural and anthropogenic sources of metal exposure differ for urban and rural residents. We searched to identify patterns of metal mixtures which could suggest common environmental sources and/or metabolic pathways of different urinary metals, and compared metal-mixtures in two population-based studies from urban/sub-urban and rural/town areas in the US: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Strong Heart Study (SHS). We studied a random sample of 308 White, Black, Chinese-American, and Hispanic participants in MESA (2000-2002) and 277 American Indian participants in SHS (1998-2003). We used principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) to evaluate nine urinary metals (antimony [Sb], arsenic [As], cadmium [Cd], lead [Pb], molybdenum [Mo], selenium [Se], tungsten [W], uranium [U] and zinc [Zn]). For arsenic, we used the sum of inorganic and methylated species (∑As). All nine urinary metals were higher in SHS compared to MESA participants. PCA and CA revealed the same patterns in SHS, suggesting 4 distinct principal components (PC) or clusters (∑As-U-W, Pb-Sb, Cd-Zn, Mo-Se). In MESA, CA showed 2 large clusters (∑As-Mo-Sb-U-W, Cd-Pb-Se-Zn), while PCA showed 4 PCs (Sb-U-W, Pb-Se-Zn, Cd-Mo, ∑As). LDA indicated that ∑As, U, W, and Zn were the most discriminant variables distinguishing MESA and SHS participants. In SHS, the ∑As-U-W cluster and PC might reflect groundwater contamination in rural areas, and the Cd-Zn cluster and PC could reflect common sources from meat products or metabolic interactions. Among the metals assayed, ∑As, U, W and Zn differed the most between MESA and SHS, possibly reflecting disproportionate exposure from drinking water and perhaps food in rural Native communities compared to urban communities around the US. Copyright © 2016 Elsevier Inc. All rights reserved.

Supramolecular clusters between carbohydrates and concave pyridines. Detection in the gas phase by resonance-enhanced multi-photon ionization reflectron time-of-flight mass spectrometer.

PubMed

Liebig, Timo; Lüning, Ulrich; Grotemeyer, Jürgen

2006-01-01

For the first time the formation of supramolecular clusters between concave pyridines and different carbohydrates could be observed in the gas phase. The different clusters have been investigated by means of laser desorption into a supersonic beam followed by resonant multi photon excitation yielding mass spectra with high intensity of the different cluster. These preliminary results open a way for the investigations of the hydrogen bonds in these compounds.

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

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

Bui, Dinh-Hoi; Physics Department, Hue University’s College of Education, 34 Le Loi, Hue; Phan, Van-Nham, E-mail: phanvannham@dtu.edu.vn

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.

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

PubMed

Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar

2015-02-01

Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Under What Circumstances Does External Knowledge about the Correlation Structure Improve Power in Cluster Randomized Designs?

ERIC Educational Resources Information Center

Rhoads, Christopher

2014-01-01

Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

Study protocol for a cluster randomized trial of the Community of Voices choir intervention to promote the health and well-being of diverse older adults.

PubMed

Johnson, Julene K; Nápoles, Anna M; Stewart, Anita L; Max, Wendy B; Santoyo-Olsson, Jasmine; Freyre, Rachel; Allison, Theresa A; Gregorich, Steven E

2015-10-13

Older adults are the fastest growing segment of the United States population. There is an immediate need to identify novel, cost-effective community-based approaches that promote health and well-being for older adults, particularly those from diverse racial/ethnic and socioeconomic backgrounds. Because choral singing is multi-modal (requires cognitive, physical, and psychosocial engagement), it has the potential to improve health outcomes across several dimensions to help older adults remain active and independent. The purpose of this study is to examine the effect of a community choir program (Community of Voices) on health and well-being and to examine its costs and cost-effectiveness in a large sample of diverse, community-dwelling older adults. In this cluster randomized controlled trial, diverse adults age 60 and older were enrolled at Administration on Aging-supported senior centers and completed baseline assessments. The senior centers were randomly assigned to either start the choir immediately (intervention group) or wait 6 months to start (control). Community of Voices is a culturally tailored choir program delivered at the senior centers by professional music conductors that reflects three components of engagement (cognitive, physical, and psychosocial). We describe the nature of the study including the cluster randomized trial study design, sampling frame, sample size calculation, methods of recruitment and assessment, and primary and secondary outcomes. The study involves conducting a randomized trial of an intervention as delivered in "real-world" settings. The choir program was designed using a novel translational approach that integrated evidence-based research on the benefits of singing for older adults, community best practices related to community choirs for older adults, and the perspective of the participating communities. The practicality and relatively low cost of the choir intervention means it can be incorporated into a variety of community settings and adapted to diverse cultures and languages. If successful, this program will be a practical and acceptable community-based approach for promoting health and well-being of older adults. ClinicalTrials.gov NCT01869179 registered 9 January 2013.

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

Optimizing measurements of cluster velocities and temperatures for CCAT-prime and future surveys

NASA Astrophysics Data System (ADS)

Mittal, Avirukt; de Bernardis, Francesco; Niemack, Michael D.

2018-02-01

Galaxy cluster velocity correlations and mass distributions are sensitive probes of cosmology and the growth of structure. Upcoming microwave surveys will enable extraction of velocities and temperatures from many individual clusters for the first time. We forecast constraints on peculiar velocities, electron temperatures, and optical depths of galaxy clusters obtainable with upcoming multi-frequency measurements of the kinematic, thermal, and relativistic Sunyaev-Zeldovich effects. The forecasted constraints are compared for different measurement configurations with frequency bands between 90 GHz and 1 THz, and for different survey strategies for the 6-meter CCAT-prime telescope. We study methods for improving cluster constraints by removing emission from dusty star forming galaxies, and by using X-ray temperature priors from eROSITA. Cluster constraints are forecast for several model cluster masses. A sensitivity optimization for seven frequency bands is presented for a CCAT-prime first light instrument and a next generation instrument that takes advantage of the large optical throughput of CCAT-prime. We find that CCAT-prime observations are expected to enable measurement and separation of the SZ effects to characterize the velocity, temperature, and optical depth of individual massive clusters (~1015 Msolar). Submillimeter measurements are shown to play an important role in separating these components from dusty galaxy contamination. Using a modular instrument configuration with similar optical throughput for each detector array, we develop a rule of thumb for the number of detector arrays desired at each frequency to optimize extraction of these signals. Our results are relevant for a future "Stage IV" cosmic microwave background survey, which could enable galaxy cluster measurements over a larger range of masses and redshifts than will be accessible by other experiments.

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.

PubMed

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.

Toward the 21st Century: Preparing Proactive Visionary Transformational Leaders for Building Learning Communities through Multi-Technology. Leadership I Formative Evaluation of Cluster 54.

ERIC Educational Resources Information Center

Groff, Warren H.

This paper presents a description and formative evaluation of National (Multi-Tech) Cluster III, Nova University's third technology-intensive doctoral program in Child and Youth Studies (CYS) in which formal instruction occurs in clusters, or groups of professionals in different geographic locations who are connected via electronic communications…

No Effect of Insecticide Treated Curtain Deployment on Aedes Infestation in a Cluster Randomized Trial in a Setting of Low Dengue Transmission in Guantanamo, Cuba

PubMed Central

Lambert, Isora; Montada, Domingo; Baly, Alberto; Van der Stuyft, Patrick

2015-01-01

Objective & Methodology The current study evaluated the effectiveness and cost-effectiveness of Insecticide Treated Curtain (ITC) deployment for reducing dengue vector infestation levels in the Cuban context with intensive routine control activities. A cluster randomized controlled trial took place in Guantanamo city, east Cuba. Twelve neighborhoods (about 500 households each) were selected among the ones with the highest Aedes infestation levels in the previous two years, and were randomly allocated to the intervention and control arms. Long lasting ITC (PermaNet) were distributed in the intervention clusters in March 2009. Routine control activities were continued in the whole study area. In both study arms, we monitored monthly pre- and post-intervention House Index (HI, number of houses with at least 1 container with Aedes immature stages/100 houses inspected), during 12 and 18 months respectively. We evaluated the effect of ITC deployment on HI by fitting a generalized linear regression model with a negative binomial link function to these data. Principal Findings At distribution, the ITC coverage (% of households using ≥1 ITC) reached 98.4%, with a median of 3 ITC distributed/household. After 18 months, the coverage remained 97.4%. The local Aedes species was susceptible to deltamethrin (mosquito mortality rate of 99.7%) and the residual deltamethrin activity in the ITC was within acceptable levels (mosquito mortality rate of 73.1%) after one year of curtain use. Over the 18 month observation period after ITC distribution, the adjusted HI rate ratio, intervention versus control clusters, was 1.15 (95% CI 0.57 to 2.34). The annualized cost per household of ITC implementation was 3.8 USD, against 16.8 USD for all routine ACP activities. Conclusion Deployment of ITC in a setting with already intensive routine Aedes control actions does not lead to reductions in Aedes infestation levels. PMID:25794192

COSMOS--improving the quality of life in nursing home patients: protocol for an effectiveness-implementation cluster randomized clinical hybrid trial.

PubMed

Husebo, Bettina S; Flo, Elisabeth; Aarsland, Dag; Selbaek, Geir; Testad, Ingelin; Gulla, Christine; Aasmul, Irene; Ballard, Clive

2015-09-15

Nursing home patients have complex mental and physical health problems, disabilities and social needs, combined with widespread prescription of psychotropic drugs. Preservation of their quality of life is an important goal. This can only be achieved within nursing homes that offer competent clinical conditions of treatment and care. COmmunication, Systematic assessment and treatment of pain, Medication review, Occupational therapy, Safety (COSMOS) is an effectiveness-implementation hybrid trial that combines and implements organization of activities evidence-based interventions to improve staff competence and thereby the patients' quality of life, mental health and safety. The aim of this paper is to describe the development, content and implementation process of the COSMOS trial. COSMOS includes a 2-month pilot study with 128 participants distributed among nine Norwegian nursing homes, and a 4-month multicenter, cluster randomized effectiveness-implementation clinical hybrid trial with follow-up at month 9, including 571 patients from 67 nursing home units (one unit defined as one cluster). Clusters are randomized to COSMOS intervention or current best practice (control group). The intervention group will receive a 2-day education program including written guidelines, repeated theoretical and practical training (credited education of caregivers, physicians and nursing home managers), case discussions and role play. The 1-day midway evaluation, information and interviews of nursing staff and a telephone hotline all support the implementation process. Outcome measures include quality of life in late-stage dementia, neuropsychiatric symptoms, activities of daily living, pain, depression, sleep, medication, cost-utility analysis, hospital admission and mortality. Despite complex medical and psychosocial challenges, nursing home patients are often treated by staff possessing low level skills, lacking education and in facilities with a high staff turnover. Implementation of a research-based multicomponent intervention may improve staff's knowledge and competence and consequently the quality of life of nursing home patients in general and people with dementia in particular. ClinicalTrials.gov NCT02238652.

Multi-fault clustering and diagnosis of gear system mined by spectrum entropy clustering based on higher order cumulants

NASA Astrophysics Data System (ADS)

Shao, Renping; Li, Jing; Hu, Wentao; Dong, Feifei

2013-02-01

Higher order cumulants (HOC) is a new kind of modern signal analysis of theory and technology. Spectrum entropy clustering (SEC) is a data mining method of statistics, extracting useful characteristics from a mass of nonlinear and non-stationary data. Following a discussion on the characteristics of HOC theory and SEC method in this paper, the study of signal processing techniques and the unique merits of nonlinear coupling characteristic analysis in processing random and non-stationary signals are introduced. Also, a new clustering analysis and diagnosis method is proposed for detecting multi-damage on gear by introducing the combination of HOC and SEC into the damage-detection and diagnosis of the gear system. The noise is restrained by HOC and by extracting coupling features and separating the characteristic signal at different speeds and frequency bands. Under such circumstances, the weak signal characteristics in the system are emphasized and the characteristic of multi-fault is extracted. Adopting a data-mining method of SEC conducts an analysis and diagnosis at various running states, such as the speed of 300 r/min, 900 r/min, 1200 r/min, and 1500 r/min of the following six signals: no-fault, short crack-fault in tooth root, long crack-fault in tooth root, short crack-fault in pitch circle, long crack-fault in pitch circle, and wear-fault on tooth. Research shows that this combined method of detection and diagnosis can also identify the degree of damage of some faults. On this basis, the virtual instrument of the gear system which detects damage and diagnoses faults is developed by combining with advantages of MATLAB and VC++, employing component object module technology, adopting mixed programming methods, and calling the program transformed from an *.m file under VC++. This software system possesses functions of collecting and introducing vibration signals of gear, analyzing and processing signals, extracting features, visualizing graphics, detecting and diagnosing faults, detecting and monitoring, etc. Finally, the results of testing and verifying show that the developed system can effectively be used to detect and diagnose faults in an actual operating gear transmission system.

Multi-fault clustering and diagnosis of gear system mined by spectrum entropy clustering based on higher order cumulants.

PubMed

Shao, Renping; Li, Jing; Hu, Wentao; Dong, Feifei

2013-02-01

Higher order cumulants (HOC) is a new kind of modern signal analysis of theory and technology. Spectrum entropy clustering (SEC) is a data mining method of statistics, extracting useful characteristics from a mass of nonlinear and non-stationary data. Following a discussion on the characteristics of HOC theory and SEC method in this paper, the study of signal processing techniques and the unique merits of nonlinear coupling characteristic analysis in processing random and non-stationary signals are introduced. Also, a new clustering analysis and diagnosis method is proposed for detecting multi-damage on gear by introducing the combination of HOC and SEC into the damage-detection and diagnosis of the gear system. The noise is restrained by HOC and by extracting coupling features and separating the characteristic signal at different speeds and frequency bands. Under such circumstances, the weak signal characteristics in the system are emphasized and the characteristic of multi-fault is extracted. Adopting a data-mining method of SEC conducts an analysis and diagnosis at various running states, such as the speed of 300 r/min, 900 r/min, 1200 r/min, and 1500 r/min of the following six signals: no-fault, short crack-fault in tooth root, long crack-fault in tooth root, short crack-fault in pitch circle, long crack-fault in pitch circle, and wear-fault on tooth. Research shows that this combined method of detection and diagnosis can also identify the degree of damage of some faults. On this basis, the virtual instrument of the gear system which detects damage and diagnoses faults is developed by combining with advantages of MATLAB and VC++, employing component object module technology, adopting mixed programming methods, and calling the program transformed from an *.m file under VC++. This software system possesses functions of collecting and introducing vibration signals of gear, analyzing and processing signals, extracting features, visualizing graphics, detecting and diagnosing faults, detecting and monitoring, etc. Finally, the results of testing and verifying show that the developed system can effectively be used to detect and diagnose faults in an actual operating gear transmission system.

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

PubMed

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 (P<.001) and nutrition facts labels (P = .04) but no significant increase in food 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.

The clustering evolution of distant red galaxies in the GOODS-MUSIC sample

NASA Astrophysics Data System (ADS)

Grazian, A.; Fontana, A.; Moscardini, L.; Salimbeni, S.; Menci, N.; Giallongo, E.; de Santis, C.; Gallozzi, S.; Nonino, M.; Cristiani, S.; Vanzella, E.

2006-07-01

Aims.We study the clustering properties of Distant Red Galaxies (DRGs) to test whether they are the progenitors of local massive galaxies. Methods.We use the GOODS-MUSIC sample, a catalog of ~3000 Ks-selected galaxies based on VLT and HST observation of the GOODS-South field with extended multi-wavelength coverage (from 0.3 to 8~μm) and accurate estimates of the photometric redshifts to select 179 DRGs with J-Ks≥ 1.3 in an area of 135 sq. arcmin.Results.We first show that the J-Ks≥ 1.3 criterion selects a rather heterogeneous sample of galaxies, going from the targeted high-redshift luminous evolved systems, to a significant fraction of lower redshift (1

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion.

PubMed

Kojima, A; Hanada, M; Tobari, H; Nishikiori, R; Hiratsuka, J; Kashiwagi, M; Umeda, N; Yoshida, M; Ichikawa, M; Watanabe, K; Yamano, Y; Grisham, L R

2016-02-01

Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltage holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.

Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion

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

Kojima, A., E-mail: kojima.atsushi@jaea.go.jp; Hanada, M.; Tobari, H.

Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltagemore » holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.« less

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

NanoRocks: A Long-Term Microgravity Experiment to Stydy Planet Formation and Planetary Ring Particles

NASA Astrophysics Data System (ADS)

Brisset, J.; Colwell, J. E.; Dove, A.; Maukonen, D.; Brown, N.; Lai, K.; Hoover, B.

2015-12-01

We report on the results of the NanoRocks experiment on the International Space Station (ISS), which simulates collisions that occur in protoplanetary disks and planetary ring systems. A critical stage of the process of early planet formation is the growth of solid bodies from mm-sized chondrules and aggregates to km-sized planetesimals. To characterize the collision behavior of dust in protoplanetary conditions, experimental data is required, working hand in hand with models and numerical simulations. In addition, the collisional evolution of planetary rings takes place in the same collisional regime. The objective of the NanoRocks experiment is to study low-energy collisions of mm-sized particles of different shapes and materials. An aluminum tray (~8x8x2cm) divided into eight sample cells holding different types of particles gets shaken every 60 s providing particles with initial velocities of a few cm/s. In September 2014, NanoRocks reached ISS and 220 video files, each covering one shaking cycle, have already been downloaded from Station. The data analysis is focused on the dynamical evolution of the multi-particle systems and on the formation of cluster. We track the particles down to mean relative velocities less than 1 mm/s where we observe cluster formation. The mean velocity evolution after each shaking event allows for a determination of the mean coefficient of restitution for each particle set. These values can be used as input into protoplanetary disk and planetary rings simulations. In addition, the cluster analysis allows for a determination of the mean final cluster size and the average particle velocity of clustering onset. The size and shape of these particle clumps is crucial to understand the first stages of planet formation inside protoplanetary disks as well as many a feature of Saturn's rings. We report on the results from the ensemble of these collision experiments and discuss applications to planetesimal formation and planetary ring evolution.

Effects of the X:IT smoking intervention: a school-based cluster randomized trial.

PubMed

Andersen, Anette; Krølner, Rikker; Bast, Lotus Sofie; Thygesen, Lau Caspar; Due, Pernille

2015-12-01

Uptake of smoking in adolescence is still of major public health concern. Evaluations of school-based programmes for smoking prevention show mixed results. The aim of this study was to examine the effect of X:IT, a multi-component school-based programme to prevent adolescent smoking. Data from a Danish cluster randomized trial included 4041 year-7 students (mean age: 12.5) from 51 intervention and 43 control schools. Outcome measure 'current smoking' was dichotomized into smoking daily, weekly, monthly or more seldom vs do not smoke. Analyses were adjusted for baseline covariates: sex, family socioeconomic position (SEP), best friend's smoking and parental smoking. We performed multilevel, logistic regression analyses of available cases and intention-to-treat (ITT) analyses, replacing missing outcome values by multiple imputation. At baseline, 4.7% and 6.8% of the students at the intervention and the control schools smoked, respectively. After 1 year of the intervention, the prevalence was 7.9% and 10.7%, respectively. At follow-up, 553 students (13.7%) did not answer the question on smoking. Available case analyses: crude odds ratios (OR) for smoking at intervention schools compared with control schools: 0.65 (0.48-0.88) and adjusted: 0.70 (0.47-1.04). ITT analyses: crude OR for smoking at intervention schools compared with control schools: 0.67 (0.50-0.89) and adjusted: 0.61 (0.45-0.82). Students at intervention schools had a lower risk of smoking after a year of intervention in year 7. This multi-component intervention involving educational, parental and context-related intervention components seems to be efficient in lowering or postponing smoking uptake in Danish adolescents. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

A Cluster-Randomized Trial of Two Strategies to Improve Antibiotic Use for Patients with a Complicated Urinary Tract Infection

PubMed Central

Spoorenberg, Veroniek; Hulscher, Marlies E. J. L.; Geskus, Ronald B.; de Reijke, Theo M.; Opmeer, Brent C.; Prins, Jan M.; Geerlings, Suzanne E.

2015-01-01

Background Up to 50% of hospital antibiotic use is inappropriate and therefore improvement strategies are urgently needed. We compared the effectiveness of two strategies to improve the quality of antibiotic use in patients with a complicated urinary tract infection (UTI). Methods In a multicentre, cluster-randomized trial 19 Dutch hospitals (departments Internal Medicine and Urology) were allocated to either a multi-faceted strategy including feedback, educational sessions, reminders and additional/optional improvement actions, or a competitive feedback strategy, i.e. providing professionals with non-anonymous comparative feedback on the department’s appropriateness of antibiotic use. Retrospective baseline- and post-intervention measurements were performed in 2009 and 2012 in 50 patients per department, resulting in 1,964 and 2,027 patients respectively. Principal outcome measures were nine validated guideline-based quality indicators (QIs) that define appropriate antibiotic use in patients with a complicated UTI, and a QI sumscore that summarizes for each patient the appropriateness of antibiotic use. Results Performance scores on several individual QIs showed improvement from baseline to post-intervention measurements, but no significant differences were found between both strategies. The mean patient’s QI sum score improved significantly in both strategy groups (multi-faceted: 61.7% to 65.0%, P = 0.04 and competitive feedback: 62.8% to 66.7%, P = 0.01). Compliance with the strategies was suboptimal, but better compliance was associated with more improvement. Conclusion The effectiveness of both strategies was comparable and better compliance with the strategies was associated with more improvement. To increase effectiveness, improvement activities should be rigorously applied, preferably by a locally initiated multidisciplinary team. Trial Registration Nederlands Trial Register 1742 PMID:26637169

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

PubMed

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.

NCSTRL+: Adding Multi-Discipline and Multi-Genre Support to the Dienst Protocol Using Clusters and Buckets

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.; Zubair, Mohammad

1998-01-01

We describe NCSTRL+, a unified, canonical digital library for scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing buckets. We have extended Dienst, the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The bucket construct provides a mechanism for publishing and managing logically linked entities with multiple data forms as a single object. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

NASA Astrophysics Data System (ADS)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method

NASA Astrophysics Data System (ADS)

Sirait, Kamson; Tulus; Budhiarti Nababan, Erna

2017-12-01

Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE.

PubMed

Alexander, Brian M; Ba, Sujuan; Berger, Mitchel S; Berry, Donald A; Cavenee, Webster K; Chang, Susan M; Cloughesy, Timothy F; Jiang, Tao; Khasraw, Mustafa; Li, Wenbin; Mittman, Robert; Poste, George H; Wen, Patrick Y; Yung, W K Alfred; Barker, Anna D

2018-02-15

Glioblastoma (GBM) is a deadly disease with few effective therapies. Although much has been learned about the molecular characteristics of the disease, this knowledge has not been translated into clinical improvements for patients. At the same time, many new therapies are being developed. Many of these therapies have potential biomarkers to identify responders. The result is an enormous amount of testable clinical questions that must be answered efficiently. The GBM Adaptive Global Innovative Learning Environment (GBM AGILE) is a novel, multi-arm, platform trial designed to address these challenges. It is the result of the collective work of over 130 oncologists, statisticians, pathologists, neurosurgeons, imagers, and translational and basic scientists from around the world. GBM AGILE is composed of two stages. The first stage is a Bayesian adaptively randomized screening stage to identify effective therapies based on impact on overall survival compared with a common control. This stage also finds the population in which the therapy shows the most promise based on clinical indication and biomarker status. Highly effective therapies transition in an inferentially seamless manner in the identified population to a second confirmatory stage. The second stage uses fixed randomization to confirm the findings from the first stage to support registration. Therapeutic arms with biomarkers may be added to the trial over time, while others complete testing. The design of GBM AGILE enables rapid clinical testing of new therapies and biomarkers to speed highly effective therapies to clinical practice. Clin Cancer Res; 24(4); 737-43. ©2017 AACR . ©2017 American Association for Cancer Research.

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

A Comparison of Single Sample and Bootstrap Methods to Assess Mediation in Cluster Randomized Trials

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.; Kang, Joo Youn

2006-01-01

A Monte Carlo study examined the statistical performance of single sample and bootstrap methods that can be used to test and form confidence interval estimates of indirect effects in two cluster randomized experimental designs. The designs were similar in that they featured random assignment of clusters to one of two treatment conditions and…

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

PubMed Central

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X.

2015-01-01

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols. PMID:26712764

Prevalence of COPD in 6 Urban Clusters in Argentina: The EPOC.AR Study.

PubMed

Echazarreta, Andrés L; Arias, Sergio J; Del Olmo, Ricardo; Giugno, Eduardo R; Colodenco, Federico D; Arce, Santiago C; Bossio, Juan C; Armando, Gustavo; Soriano, Joan B

2018-05-01

The prevalence of chronic obstructive pulmonary disease (COPD) has not been studied in Argentina. To determine the prevalence and relevant clinical characteristics of COPD in a representative sample. We performed a cross-sectional study in a population of adults aged ≥ 40 years randomly selected by cluster sampling in 6 urban locations. Subjects answered a structured survey and performed pre- and post-bronchodilator spirometry (PBD). COPD was defined as FEV 1 /FVC ratio < 0.7 predicted value. The total prevalence was estimated for each cluster with its 95% confidence interval (CI). Of 4,599 surveys and 3,999 spirometries, 3,469 were considered of adequate quality (86.8%) for our study. The prevalence of COPD was 14.5% (CI: 13.4-15.7). The distribution of COPD cases according to FEV1 (GOLD 2017) was stage 1: 38% (CI: 34-43); stage 2: 52% (CI: 47-56); stage 3: 10% (CI: 7-13); and stage 4: 1% (CI: 0-2), and according to the refined ABCD (GOLD 2017) assessment: A: 52% (CI: 47-56); B: 43% (CI: 39-48); C: 1% (CI: 0-2); D: 4% (CI: 2-6). The rate of underdiagnosis was 77.4% (CI 73.7-81.1%) and diagnostic error 60.7% (CI 55.1-66.3%). A significant association was found between COPD and age (OR 3.77 in individuals 50-59 years of age and 19.23 in those > 80 years), male gender (OR 1.62; CI 1.31-2), smoking (OR 1.95; CI 1.49-2.54), low socioeconomic status (OR 1.33; CI 1.02-1.73), and previous tuberculosis (OR 3.3; CI 1.43-7.62). We estimate that more than 2.3 million Argentineans have COPD, with high rates of underdiagnosis and diagnostic error. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

The environmental management problem of Pohorje, Slovenia: A new group approach within ANP - SWOT framework.

PubMed

Grošelj, Petra; Zadnik Stirn, Lidija

2015-09-15

Environmental management problems can be dealt with by combining participatory methods, which make it possible to include various stakeholders in a decision-making process, and multi-criteria methods, which offer a formal model for structuring and solving a problem. This paper proposes a three-phase decision making approach based on the analytic network process and SWOT (strengths, weaknesses, opportunities and threats) analysis. The approach enables inclusion of various stakeholders or groups of stakeholders in particular stages of decision making. The structure of the proposed approach is composed of a network consisting of an objective cluster, a cluster of strategic goals, a cluster of SWOT factors and a cluster of alternatives. The application of the suggested approach is applied to a management problem of Pohorje, a mountainous area in Slovenia. Stakeholders from sectors that are important for Pohorje (forestry, agriculture, tourism and nature protection agencies) who can offer a wide range of expert knowledge were included in the decision-making process. The results identify the alternative of "sustainable development" as the most appropriate for development of Pohorje. The application in the paper offers an example of employing the new approach to an environmental management problem. This can also be applied to decision-making problems in various other fields. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pre-Visit Prioritization for Complex Patients with Diabetes: Randomized Trial Design and Implementation within an Integrated Health Care System

PubMed Central

Grant, Richard W; Uratsu, Connie S; Hansen, Karen R; Altschuler, Andrea; Kim, Eileen; Fireman, Bruce; Adams, Alyce S; Schmittdiel, Julie A; Heisler, Michele

2016-01-01

Background/Aims Despite robust evidence to guide clinical care, most patients with diabetes do not meet all goals of risk factor control. Improved patient-provider communication during time-limited primary care visits may represent one strategy for improving diabetes care. Methods We designed a controlled, cluster-randomized, multi-site intervention (Pre-Visit Prioritization for Complex Patients with Diabetes) that enables patients with poorly controlled type 2 diabetes to identify their top priorities prior to a scheduled visit and sends these priorities to the primary care physician progress note in the electronic medical record. In this paper, we describe strategies to address challenges to implementing our health IT-based intervention study within a large health care system. Results This study is being conducted in 30 primary care practices within a large integrated care delivery system in Northern California. Over a 12-week period (3/1/2015 – 6/6/2015), 146 primary care physicians consented to enroll in the study (90.1%) and approved contact with 2496 of their patients (97.6%). Implementation challenges included: (1) Navigating research vs. quality improvement requirements; (2) Addressing informed consent considerations; and (3) Introducing a new clinical tool into a highly time-constrained workflow. Strategies for successfully initiating this study included engagement with institutional leaders, Institutional Review Board members, and clinical stakeholders at multiple stages both before and after notice of Federal funding; flexibility by the research team in study design; and strong support from institutional leadership for “self-learning health system” research. Conclusions By paying careful attention to identifying and collaborating with a wide range of key clinical stakeholders, we have shown that researchers embedded within a learning care system can successfully apply rigorous clinical trial methods to test new care innovations. PMID:26820612

Rationale and Methodology for a Community-Based Study of Diabetic Retinopathy in an Indonesian Population with Type 2 Diabetes Mellitus: The Jogjakarta Eye Diabetic Study in the Community.

PubMed

Sasongko, Muhammad B; Agni, Angela N; Wardhana, Firman S; Kotha, Satya P; Gupta, Prateek; Widayanti, Tri W; Supanji; Widyaputri, Felicia; Widyaningrum, Rifa; Wong, Tien Y; Kawasaki, Ryo; Wang, Jie Jin; Pawiroranu, Suhardjo

2017-02-01

There are no available data about diabetic retinopathy (DR) in the Indonesian population. This report summarizes the rationale and study design of the Jogjakarta Eye Diabetic Study in the Community (JOGED.COM), a community-based study to estimate the prevalence and risk factors of DR in persons with type 2 diabetes in Jogjakarta, Indonesia. The JOGED.COM aimed to examine a cross-sectional sample of 1200 persons with type 2 diabetes aged 30 years and older residing in the study area. We identified 121 community health centers (CHCs) in Jogjakarta and listed 35 CHCs with non-communicable diseases facilities. Multi-stage, clustered random sampling was used to select 22 CHCs randomly. We included CHCs with coverage population >30,000, and excluded those classified as 100% rural. Lists of persons with diabetes confirmed by their family physician were provided from each CHC. Examinations procedures included detailed interviews, general and eye examinations, anthropometry and body composition scan, and dilated fundus photography. We collaborated with local health authorities, family physicians, and local health practitioners in the recruitment phase. A total of 1435 invitations were distributed, and 1184 people (82.5%) with type 2 diabetes participated in this study, of whom 1138 (79.3%) had completed data with gradable retinal images. JOGED.COM is the first epidemiologic study of DR in an Indonesian population. This study will provide key information about the prevalence and risk factors of DR in the community. These data are very important for future health promotion programs to reduce the burden of DR in the population.

Development of a food frequency questionnaire for Sri Lankan adults

PubMed Central

2012-01-01

Background Food Frequency Questionnaires (FFQs) are commonly used in epidemiologic studies to assess long-term nutritional exposure. Because of wide variations in dietary habits in different countries, a FFQ must be developed to suit the specific population. Sri Lanka is undergoing nutritional transition and diet-related chronic diseases are emerging as an important health problem. Currently, no FFQ has been developed for Sri Lankan adults. In this study, we developed a FFQ to assess the regular dietary intake of Sri Lankan adults. Methods A nationally representative sample of 600 adults was selected by a multi-stage random cluster sampling technique and dietary intake was assessed by random 24-h dietary recall. Nutrient analysis of the FFQ required the selection of foods, development of recipes and application of these to cooked foods to develop a nutrient database. We constructed a comprehensive food list with the units of measurement. A stepwise regression method was used to identify foods contributing to a cumulative 90% of variance to total energy and macronutrients. In addition, a series of photographs were included. Results We obtained dietary data from 482 participants and 312 different food items were recorded. Nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Conclusion We developed a FFQ and the related nutrient composition database for Sri Lankan adults. Culturally specific dietary tools are central to capturing the role of diet in risk for chronic disease in Sri Lanka. The next step will involve the verification of FFQ reproducibility and validity. PMID:22937734

Pre-Visit Prioritization for complex patients with diabetes: Randomized trial design and implementation within an integrated health care system.

PubMed

Grant, Richard W; Uratsu, Connie S; Estacio, Karen R; Altschuler, Andrea; Kim, Eileen; Fireman, Bruce; Adams, Alyce S; Schmittdiel, Julie A; Heisler, Michele

2016-03-01

Despite robust evidence to guide clinical care, most patients with diabetes do not meet all goals of risk factor control. Improved patient-provider communication during time-limited primary care visits may represent one strategy for improving diabetes care. We designed a controlled, cluster-randomized, multi-site intervention (Pre-Visit Prioritization for Complex Patients with Diabetes) that enables patients with poorly controlled type 2 diabetes to identify their top priorities prior to a scheduled visit and sends these priorities to the primary care physician progress note in the electronic medical record. In this paper, we describe strategies to address challenges to implementing our health IT-based intervention study within a large health care system. This study is being conducted in 30 primary care practices within a large integrated care delivery system in Northern California. Over a 12-week period (3/1/2015-6/6/2015), 146 primary care physicians consented to enroll in the study (90.1%) and approved contact with 2496 of their patients (97.6%). Implementation challenges included: (1) navigating research vs. quality improvement requirements; (2) addressing informed consent considerations; and (3) introducing a new clinical tool into a highly time-constrained workflow. Strategies for successfully initiating this study included engagement with institutional leaders, Institutional Review Board members, and clinical stakeholders at multiple stages both before and after notice of Federal funding; flexibility by the research team in study design; and strong support from institutional leadership for "self-learning health system" research. By paying careful attention to identifying and collaborating with a wide range of key clinical stakeholders, we have shown that researchers embedded within a learning care system can successfully apply rigorous clinical trial methods to test new care innovations. Copyright © 2016 Elsevier Inc. All rights reserved.

A long-term evaluation of the stage of change approach and compensable injury outcomes - a cluster-randomised trial.

PubMed

Rothmore, Paul; Aylward, Paul; Gray, Jodi; Karnon, Jonathan

2017-05-01

This study investigated the long-term injury outcomes for workers in companies from a range of industries which had been randomly allocated to receive ergonomics interventions tailored according to the stage of change (SOC) approach or standard ergonomics advice. Differences in compensable injury outcomes between the groups were analysed using logistic regression models. Questionnaire results from face-to-face interviews to assess musculoskeletal pain and discomfort (MSPD), job satisfaction and other factors were also analysed. Although not significant at the 0.05 level, after adjusting for workgroup clustering, workers in receipt of tailored advice were 55% (OR = 0.45, 95% CI = 0.19-1.08) less likely to report a compensable injury than those in receipt of standard ergonomics advice. Workload, job satisfaction and MSPD were significantly correlated with injury outcomes. The observed outcomes support the potential value of the SOC approach, as well as highlighting the need to consider workload, job satisfaction and MSPD when planning injury prevention programmes. Practitioner Summary: This study investigated compensable injury outcomes for workers who had received ergonomics advice tailored according to the stage of change (SOC) approach compared with standard ergonomics advice. The results support the potential value of the SOC approach and highlight the need to consider workload, job satisfaction and musculoskeletal pain and discomfort when planning injury prevention interventions.

Cancer genetics and reproduction.

PubMed

Hanson, Helen; Hodgson, Shirley

2010-02-01

Cancers of the reproductive organs (i.e., ovaries, uterus and testes), like other cancers, occur as a result of a multi-stage interaction of genetic and environmental factors. A small proportion of cancers of the reproductive organs occur as part of a recognised cancer syndrome, as a result of inheritance of mutations in highly penetrant cancer susceptibility genes (e.g., BRCA1, BRCA2, MLH1 or MSH2). Recognition of individuals and families with inherited cancer predisposition syndromes and individuals at high risk due to familial cancer clustering is fundamentally important for the management and treatment of the current cancer and for future prevention of further cancers for the individual and their extended family.

Inhomogeneity compensation for MR brain image segmentation using a multi-stage FCM-based approach.

PubMed

Szilágyi, László; Szilágyi, Sándor M; Dávid, László; Benyó, Zoltán

2008-01-01

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a multiple stage fuzzy c-means (FCM) based algorithm for the estimation and compensation of the slowly varying additive or multiplicative noise, supported by a pre-filtering technique for Gaussian and impulse noise elimination. The slowly varying behavior of the bias or gain field is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Enhancing local health department disaster response capacity with rapid community needs assessments: validation of a computerized program for binary attribute cluster sampling.

PubMed

Groenewold, Matthew R

2006-01-01

Local health departments are among the first agencies to respond to disasters or other mass emergencies. However, they often lack the ability to handle large-scale events. Plans including locally developed and deployed tools may enhance local response. Simplified cluster sampling methods can be useful in assessing community needs after a sudden-onset, short duration event. Using an adaptation of the methodology used by the World Health Organization Expanded Programme on Immunization (EPI), a Microsoft Access-based application for two-stage cluster sampling of residential addresses in Louisville/Jefferson County Metro, Kentucky was developed. The sampling frame was derived from geographically referenced data on residential addresses and political districts available through the Louisville/Jefferson County Information Consortium (LOJIC). The program randomly selected 30 clusters, defined as election precincts, from within the area of interest, and then, randomly selected 10 residential addresses from each cluster. The program, called the Rapid Assessment Tools Package (RATP), was tested in terms of accuracy and precision using data on a dichotomous characteristic of residential addresses available from the local tax assessor database. A series of 30 samples were produced and analyzed with respect to their precision and accuracy in estimating the prevalence of the study attribute. Point estimates with 95% confidence intervals were calculated by determining the proportion of the study attribute values in each of the samples and compared with the population proportion. To estimate the design effect, corresponding simple random samples of 300 addresses were taken after each of the 30 cluster samples. The sample proportion fell within +/-10 absolute percentage points of the true proportion in 80% of the samples. In 93.3% of the samples, the point estimate fell within +/-12.5%, and 96.7% fell within +/-15%. All of the point estimates fell within +/-20% of the true proportion. Estimates of the design effect ranged from 0.926 to 1.436 (mean = 1.157, median = 1.170) for the 30 samples. Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the RATP, a locally designed and deployed tool, may provide population-based estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts.

New Estimates of Design Parameters for Clustered Randomization Studies: Findings from North Carolina and Florida. Working Paper 43

ERIC Educational Resources Information Center

Xu, Zeyu; Nichols, Austin

2010-01-01

The gold standard in making causal inference on program effects is a randomized trial. Most randomization designs in education randomize classrooms or schools rather than individual students. Such "clustered randomization" designs have one principal drawback: They tend to have limited statistical power or precision. This study aims to…

SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Loikith, P.; Lee, H.; McGibbney, L. J.; Whitehall, K. D.

2014-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark. Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based ApacheTM Hadoop by 100x in memory and by 10x on disk, and makes iterative algorithms feasible. SciSpark will enable scalable model evaluation by executing large-scale comparisons of A-Train satellite observations to model grids on a cluster of 100 to 1000 compute nodes. This 2nd generation capability for NASA's Regional Climate Model Evaluation System (RCMES) will compute simple climate metrics at interactive speeds, and extend to quite sophisticated iterative algorithms such as machine-learning (ML) based clustering of temperature PDFs, and even graph-based algorithms for searching for Mesocale Convective Complexes. The goals of SciSpark are to: (1) Decrease the time to compute comparison statistics and plots from minutes to seconds; (2) Allow for interactive exploration of time-series properties over seasons and years; (3) Decrease the time for satellite data ingestion into RCMES to hours; (4) Allow for Level-2 comparisons with higher-order statistics or PDF's in minutes to hours; and (5) Move RCMES into a near real time decision-making platform. We will report on: the architecture and design of SciSpark, our efforts to integrate climate science algorithms in Python and Scala, parallel ingest and partitioning (sharding) of A-Train satellite observations from HDF files and model grids from netCDF files, first parallel runs to compute comparison statistics and PDF's, and first metrics quantifying parallel speedups and memory & disk usage.

Early stages of carbonate mineralization revealed from molecular simulations: Implications for biomineral formation

NASA Astrophysics Data System (ADS)

Wallace, A. F.; DeYoreo, J.; Banfield, J. F.

2011-12-01

The carbonate mineral constituents of many biomineralized products, formed both in and ex vivo, grow by a multi-stage crystallization process that involves the nucleation and structural reorganization of transient amorphous phases. The existence of transient phases and cluster species has significant implications for carbonate nucleation and growth in natural and engineered environments, both modern and ancient. The structure of these intermediate phases remains elusive, as does the nature of the disorder to order transition, however, these process details may strongly influence the interpretation of elemental and isotopic climate proxy data obtained from authigenic and biogenic carbonates. While molecular simulations have been applied to certain aspects of crystal growth, studies of metal carbonate nucleation are strongly inhibited by the presence of kinetic traps that prevent adequate sampling of the potential landscape upon which the growing clusters reside within timescales accessible by simulation. This research addresses this challenge by marrying the recent Kawska-Zahn (KZ) approach to simulation of crystal nucleation and growth from solution with replica-exchange molecular dynamics (REMD) techniques. REMD has been used previously to enhance sampling of protein conformations that occupy energy wells that are separated by sizable thermodynamic and kinetic barriers, and is used here to probe the initial formation and onset of order within hydrated calcium and iron carbonate cluster species during nucleation. Results to date suggest that growing clusters initiate as short linear ion chains that evolve into two- and three-dimensional structures with continued growth. The planar structures exhibit an obvious 2d lattice, while establishment of a 3d lattice is hindered by incomplete ion desolvation. The formation of a dehydrated core consisting of a single carbonate ion is observed when the clusters are ~0.75 nm. At the same size a distorted, but discernible calcite-type lattice is also apparent. Continued growth results in expansion of the dehydrated core, however, complete desolvation and incorporation of cations into the growing carbonate phase is not achieved until the cluster grows to ~1.2 nm. Exploration of the system free energy along the crystallization path reveals "special" cluster sizes that correlate with ion desolvation milestones. The formation of these species comprise critical bottlenecks on the energy landscape and for the establishment of order within the growing clusters.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

Quantifying opening-mode fracture spatial organization in horizontal wellbore image logs, core and outcrop: Application to Upper Cretaceous Frontier Formation tight gas sandstones, USA

NASA Astrophysics Data System (ADS)

Li, J. Z.; Laubach, S. E.; Gale, J. F. W.; Marrett, R. A.

2018-03-01

The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. East-west- and north-south-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from east-west-striking fractures in outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ∼35 m wide and spaced ∼50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; organization within clusters is likely fractal. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Clustered patterns correspond to fractures having core quartz deposition contemporaneous with fracture opening, circumstances that some models suggest might affect spacing patterns by interfering with fracture growth. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineates differences in fracture patterns that are not otherwise apparent but that may influence gas and water production, and therefore may be economically important.

When is informed consent required in cluster randomized trials in health research?

PubMed Central

2011-01-01

This article is part of a series of papers examining ethical issues in cluster randomized trials (CRTs) in health research. In the introductory paper in this series, we set out six areas of inquiry that must be addressed if the cluster trial is to be set on a firm ethical foundation. This paper addresses the second of the questions posed, namely, from whom, when, and how must informed consent be obtained in CRTs in health research? The ethical principle of respect for persons implies that researchers are generally obligated to obtain the informed consent of research subjects. Aspects of CRT design, including cluster randomization, cluster level interventions, and cluster size, present challenges to obtaining informed consent. Here we address five questions related to consent and CRTs: How can a study proceed if informed consent is not possible? Is consent to randomization always required? What information must be disclosed to potential subjects if their cluster has already been randomized? Is passive consent a valid substitute for informed consent? Do health professionals have a moral obligation to participate as subjects in CRTs designed to improve professional practice? We set out a framework based on the moral foundations of informed consent and international regulatory provisions to address each of these questions. First, when informed consent is not possible, a study may proceed if a research ethics committee is satisfied that conditions for a waiver of consent are satisfied. Second, informed consent to randomization may not be required if it is not possible to approach subjects at the time of randomization. Third, when potential subjects are approached after cluster randomization, they must be provided with a detailed description of the interventions in the trial arm to which their cluster has been randomized; detailed information on interventions in other trial arms need not be provided. Fourth, while passive consent may serve a variety of practical ends, it is not a substitute for valid informed consent. Fifth, while health professionals may have a moral obligation to participate as subjects in research, this does not diminish the necessity of informed consent to study participation. PMID:21906277

Dislocation creation and void nucleation in FCC ductile metals under tensile loading: a general microscopic picture.

PubMed

Pang, Wei-Wei; Zhang, Ping; Zhang, Guang-Cai; Xu, Ai-Guo; Zhao, Xian-Geng

2014-11-10

Numerous theoretical and experimental efforts have been paid to describe and understand the dislocation and void nucleation processes that are fundamental for dynamic fracture modeling of strained metals. To date an essential physical picture on the self-organized atomic collective motions during dislocation creation, as well as the essential mechanisms for the void nucleation obscured by the extreme diversity in structural configurations around the void nucleation core, is still severely lacking in literature. Here, we depict the origin of dislocation creation and void nucleation during uniaxial high strain rate tensile processes in face-centered-cubic (FCC) ductile metals. We find that the dislocations are created through three distinguished stages: (i) Flattened octahedral structures (FOSs) are randomly activated by thermal fluctuations; (ii) The double-layer defect clusters are formed by self-organized stacking of FOSs on the close-packed plane; (iii) The stacking faults are formed and the Shockley partial dislocations are created from the double-layer defect clusters. Whereas, the void nucleation is shown to follow a two-stage description. We demonstrate that our findings on the origin of dislocation creation and void nucleation are universal for a variety of FCC ductile metals with low stacking fault energies.

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

ERIC Educational Resources Information Center

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…

Molecular serotyping and antimicrobial resistance profiles of Actinobacillus pleuropneumoniae isolated from pigs in South Korea.

PubMed

Kim, Boram; Hur, Jin; Lee, Ji Yeong; Choi, Yoonyoung; Lee, John Hwa

2016-09-01

Actinobacillus pleuropneumoniae (APP) causes porcine pleuropneumonia (PP). Serotypes and antimicrobial resistance patterns in APP isolates from pigs in Korea were examined. Sixty-five APP isolates were genetically serotyped using standard and multiplex PCR (polymerase chain reaction). Antimicrobial susceptibilities were tested using the standardized disk-agar method. PCR was used to detect β-lactam, gentamicin and tetracycline-resistance genes. The random amplified polymorphic DNA (RAPD) patterns were determined by PCR. Korean pigs predominantly carried APP serotypes 1 and 5. Among 65 isolates, one isolate was sensitive to all 12 antimicrobials tested in this study. Sixty-two isolates was resistant to tetracycline and 53 isolates carried one or five genes including tet(B), tet(A), tet(H), tet(M)/tet(O), tet(C), tet(G) and/or tet(L)-1 markers. Among 64 strains, 9% and 26.6% were resistance to 10 and three or more antimicrobials, respectively. Thirteen different antimicrobial resistance patterns were observed and RAPD analysis revealed a separation of the isolates into two clusters: cluster II (6 strains resistant to 10 antimicrobials) and cluster I (the other 59 strains). Results show that APP serotypes 1 and 5 are the most common in Korea, and multi-drug resistant strains are prevalent. RAPD analysis demonstrated that six isolates resistant to 10 antimicrobials belonged to the same cluster.

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

2014-01-01

This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

Building Multi-Discipline, Multi-Format Digital Libraries Using Clusters and Buckets. Degree rewarded by Old Dominion Univ. on Aug. 1997

NASA Technical Reports Server (NTRS)

Nelson, Michael L.

1997-01-01

Our objective was to study the feasibility of extending the Dienst protocol to enable a multi-discipline, multi-format digital library. We implemented two new technologies: cluster functionality and publishing buckets. We have designed a possible implementation of clusters and buckets, and have prototyped some aspects of the resultant digital library. Currently, digital libraries are segregated by the disciplines they serve (computer science, aeronautics, etc.), and by the format of their holdings (reports, software, datasets, etc.). NCSTRL+ is a multi-discipline, multi-format digital library (DL) prototype created to explore the feasibility of the design and implementation issues involved with created a unified, canonical scientific and technical information (STI) DL. NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible DL that provides access to over 80 university departments and laboratories. We have extended the Dienst protocol (version 4.1.8), the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized DL based upon subject category classification, type of organization, and genre of material. The concept of buckets provides a mechanism for publishing and managing logically linked entities with multiple data formats.

A PRIOR EVALUATION OF TWO-STAGE CLUSTER SAMPLING FOR ACCURACY ASSESSMENT OF LARGE-AREA LAND-COVER MAPS

EPA Science Inventory

Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, withi...

Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

PubMed Central

Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

2016-01-01

A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.

2017-01-01

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

Background: The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. Methods: We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. Results: We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. Conclusions: There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. PMID:26174515

Which nets are being used: factors associated with mosquito net use in Amhara, Oromia and Southern Nations, Nationalities and Peoples' Regions of Ethiopia.

PubMed

Ngondi, Jeremiah M; Graves, Patricia M; Gebre, Teshome; Mosher, Aryc W; Shargie, Estifanos B; Emerson, Paul M; Richards, Frank O

2011-04-17

There has been recent large scale-up of malaria control interventions in Ethiopia where transmission is unstable. While household ownership of long-lasting insecticidal nets (LLIN) has increased greatly, there are concerns about inadequate net use. This study aimed to investigate factors associated with net use at two time points, before and after mass distribution of nets. Two cross sectional surveys were carried out in 2006 and 2007 in Amhara, Oromia and SNNP regions. The latter was a sub-sample of the national Malaria Indicator Survey (MIS 3R). Each survey wave used multi-stage cluster random sampling with 25 households per cluster (224 clusters with 5,730 households in Baseline 2006 and 245 clusters with 5,910 households in MIS 3R 2007). Net ownership was assessed by visual inspection while net utilization was reported as use of the net the previous night. This net level analysis was restricted to households owning at least one net of any type. Logistic regression models of association between net use and explanatory variables including net type, age, condition, cost and other household characteristics were undertaken using generalized linear latent and mixed models (GLLAMM). A total of 3,784 nets in 2,430 households were included in the baseline 2006 analysis while the MIS 3R 2007 analysis comprised 5,413 nets in 3,328 households. The proportion of nets used the previous night decreased from 85.1% to 56.0% between baseline 2006 and MIS 3R 2007, respectively. Factors independently associated with increased proportion of nets used were: LLIN net type (at baseline 2006); indoor residual spraying (at MIS 3R 2007); and increasing wealth index at both surveys. At both baseline 2006 and MIS 3R 2007, reduced proportion of nets used was independently associated with increasing net age, increasing damage of nets, increasing household net density, and increasing altitude (>2,000 m). This study identified modifiable factors affecting use of nets that were consistent across both surveys. While net replacement remains important, the findings suggest that: more education about use and care of nets; making nets more resistant to damage; and encouraging net mending are likely to maximize the huge investment in scale up of net ownership by ensuring they are used. Without this step, the widespread benefits of LLIN cannot be realized.

Search for Directed Networks by Different Random Walk Strategies

NASA Astrophysics Data System (ADS)

Zhu, Zi-Qi; Jin, Xiao-Ling; Huang, Zhi-Long

2012-03-01

A comparative study is carried out on the efficiency of five different random walk strategies searching on directed networks constructed based on several typical complex networks. Due to the difference in search efficiency of the strategies rooted in network clustering, the clustering coefficient in a random walker's eye on directed networks is defined and computed to be half of the corresponding undirected networks. The search processes are performed on the directed networks based on Erdös—Rényi model, Watts—Strogatz model, Barabási—Albert model and clustered scale-free network model. It is found that self-avoiding random walk strategy is the best search strategy for such directed networks. Compared to unrestricted random walk strategy, path-iteration-avoiding random walks can also make the search process much more efficient. However, no-triangle-loop and no-quadrangle-loop random walks do not improve the search efficiency as expected, which is different from those on undirected networks since the clustering coefficient of directed networks are smaller than that of undirected networks.

Unpacking the Black Box of the CSRP Intervention: The Mediating Roles of Teacher-child Relationship Quality and Self-regulation

PubMed Central

Jones, Stephanie M.; Bub, Kristen L.; Raver, C. Cybele

2014-01-01

This study examines the theory of change of the Chicago School Readiness Project (CSRP), testing a sequence of theory-derived mediating mechanisms including the quality of teacher-child relationships and children’s self-regulation. The CSRP is a multi-component teacher- and classroom-focused intervention, and its cluster-randomized efficacy trial was conducted in 35 Head Start-funded classrooms. A series of increasingly complex and conservative structural equation models indicate that the CSRP carries its effects on children’s academic and behavioral outcomes through changes in teacher-child relationship quality and children’s self-regulation. PMID:24729666

Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

NASA Astrophysics Data System (ADS)

Tamiminia, H.; Homayouni, S.; Safari, A.

2015-12-01

Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

Cluster Tails for Critical Power-Law Inhomogeneous Random Graphs

NASA Astrophysics Data System (ADS)

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.

Investigating the health profile of patients with end-stage renal failure receiving peritoneal dialysis: a cluster analysis.

PubMed

Chan, M F; Wong, Frances K Y; Chow, Susan K Y

2010-03-01

To determine whether the patients with end stage renal failure can be differentiated into several subtypes based on five main variables. There is a lack of interventional research linking to clinical outcomes among the patients with end stage renal failure in Hong Kong and with no clear evidence of differences in terms of their clinical/health outcomes and characteristics. A cross-sectional survey. Data were collected using a structured questionnaire. One hundred and fifty-three patients with end stage renal failure were recruited during 2007 at three renal centres in Hong Kong. Five main variables were employed: predisposing characteristic, enabling resources, quality of life, symptom control and self-care adherence. A cluster analysis yielded two clusters. Each cluster represented a different profile of patients with end stage renal failure. Cluster A consisted of 49.7% (n = 76) and Cluster B consisted of 50.3% (n = 77) of the patients. Cluster A patients, more of whom were women, were older, less educated, had higher quality of life scores, a better adherence rate and more had received nursing care supports than patients in Cluster B. We have identified two groupings of patients with end stage renal failure who were experiencing unique health profile. Nursing support services may have an effect on patient health outcomes but only on a group of patients whose profile is similar to the patients in Cluster A and not for patients in Cluster B. A clear profile may help health care professional make appropriate strategies to target a specific group of patients to improve patient outcomes. The identification of risk for future health-care use could enable better targeting of interventional strategies in these groups. The results of this study might provide health care professionals with a model to design specified interventions to improve life quality for each profile group.

Targeting Classrooms' Emotional Climate and Preschoolers' Socioemotional Adjustment: Implementation of the Chicago School Readiness Project

PubMed Central

Li-Grining, Christine P.; Raver, C. Cybele; Jones-Lewis, Darlene; Madison-Boyd, Sybil; Lennon, Jaclyn

2015-01-01

Children living in low-income families are more likely to experience less self-regulation, greater behavior problems, and lower academic achievement than higher income children. To help prevent children's later socioemotional and academic difficulties, the Chicago School Readiness Project (CSRP) team implemented a clustered, randomized controlled trial (RCT) in early childhood programs with Head Start funding. Head Start sites were randomly assigned to receive CSRP services, which were offered as part of a multi-component, classroom-based mental health intervention. Here, we provide an overview of the CSRP model, its components, and a descriptive portrait of its implementation. In so doing, we address various aspects of the implementation of three of its components: 1) the training of teachers, 2) MHCs' coaching of teachers, and 3) teachers' behavior management of children. We conclude with a discussion of factors potentially related to the implementation of CSRP and directions for future research. PMID:25321641

A comparative analysis of suicide attempts in left-behind children and non-left-behind children in rural China.

PubMed

Chang, Hongjuan; Yan, Qiuge; Tang, Lina; Huang, Juan; Ma, Yuqiao; Ye, Xiaozhou; Yu, Yizhen

2017-01-01

To estimate the prevalence of suicide attempts and explore the shared and unique factors influencing suicide risk in left-behind children (LBC) and non-left-behind children (NLBC) in rural China, this study collected data using a multi-stage cluster random sampling method from 13,952 children including 6,034 LBC and 7,918 NLBC. Sociodemographic characteristics, suicide attempts, neglect and physical abuse, negative life events, and loneliness were measured by self-reported questionnaires. Data were analyzed using logistic regression models. Gender and mother's education level were unique influential factors for NLBC while family structure type was a unique influential factor for LBC. The study provides two novel findings regarding NLBC specifically: 1. Children with optimal family socioeconomic status are more likely to report suicide attempts (odds ratio OR = 1)than are those in the general children population, OR 0.52 (95% CI: 0.39-0.70), and 2. Children with higher mother's education level are subject to higher suicide rates in high school, OR 1.67 (95% CI: 1.13-2.46), and post-secondary education, OR 2.14 (95% CI: 1.37-3.37). The unique characteristics of LBC and NLBC in China suggest that investigating risk factors and determining the factors that might be targeted in intervention programs are urgently needed currently.

Estimation of Nationwide Vaccination Coverage and Comparison of Interview and Telephone Survey Methodology for Estimating Vaccination Status

PubMed Central

Park, Boyoung; Lee, Yeon-Kyeng; Cho, Lisa Y.; Go, Un Yeong; Yang, Jae Jeong; Ma, Seung Hyun; Choi, Bo-Youl; Lee, Moo-Sik; Lee, Jin-Seok; Choi, Eun Hwa; Lee, Hoan Jong

2011-01-01

This study compared interview and telephone surveys to select the better method for regularly estimating nationwide vaccination coverage rates in Korea. Interview surveys using multi-stage cluster sampling and telephone surveys using stratified random sampling were conducted. Nationwide coverage rates were estimated in subjects with vaccination cards in the interview survey. The interview survey relative to the telephone survey showed a higher response rate, lower missing rate, higher validity and a less difference in vaccination coverage rates between card owners and non-owners. Primary vaccination coverage rate was greater than 90% except for the fourth dose of DTaP (diphtheria/tetanus/pertussis), the third dose of polio, and the third dose of Japanese B encephalitis (JBE). The DTaP4: Polio3: MMR1 fully vaccination rate was 62.0% and BCG1:HepB3:DTaP4:Polio3:MMR1 was 59.5%. For age-appropriate vaccination, the coverage rate was 50%-80%. We concluded that the interview survey was better than the telephone survey. These results can be applied to countries with incomplete registry and decreasing rates of landline telephone coverage due to increased cell phone usage and countries. Among mandatory vaccines, efforts to increase vaccination rate for the fourth dose of DTaP, the third dose of polio, JBE and regular vaccinations at recommended periods should be conducted in Korea. PMID:21655054

Assessments of Ebola knowledge, attitudes and practices in Forécariah, Guinea and Kambia, Sierra Leone, July–August 2015

PubMed Central

Bunnell, Rebecca; Robinson, Susan; Jalloh, Mohammad B.; Barry, Alpha Mamoudou; Corker, Jamaica; Sengeh, Paul; VanSteelandt, Amanda; Li, Wenshu; Dafae, Foday; Diallo, Alpha Ahmadou; Martel, Lise D.; Hersey, Sara; Marston, Barbara; Morgan, Oliver; Redd, John T.

2017-01-01

The border region of Forécariah (Guinea) and Kambia (Sierra Leone) was of immense interest to the West Africa Ebola response. Cross-sectional household surveys with multi-stage cluster sampling procedure were used to collect random samples from Kambia (n = 635) in July 2015 and Forécariah (n = 502) in August 2015 to assess public knowledge, attitudes and practices related to Ebola. Knowledge of the disease was high in both places, and handwashing with soap and water was the most widespread prevention practice. Acceptance of safe alternatives to traditional burials was significantly lower in Forécariah compared with Kambia. In both locations, there was a minority who held discriminatory attitudes towards survivors. Radio was the predominant source of information in both locations, but those from Kambia were more likely to have received Ebola information from community sources (mosques/churches, community meetings or health workers) compared with those in Forécariah. These findings contextualize the utility of Ebola health messaging during the epidemic and suggest the importance of continued partnership with community leaders, including religious leaders, as a prominent part of future public health protection. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’. PMID:28396475

Childcare needs of female street vendors in Mexico City.

PubMed

Hernandez, P; Zetina, A; Tapia, M; Ortiz, C; Soto, I C

1996-06-01

This article reports on strategies developed by female street vendors (vendedoras ambulantes) in Mexico City to ensure the care of their young children in the absence of a specific and operational government policy to fulfil this need. The information concerning child care and health was gathered by a survey of 426 street traders selected by multi-stage random cluster sampling in four of the administrative districts (delegaciones politicas) of Mexico City during 1990. It was found that, as mothers of young children, street vendors most frequently looked after their children personally on the street or left them with other members of the family. Related factors were availability of alternative child care providers in the family, the age of the children and working conditions of the mother. Children who remained on the streets with their mothers suffered more frequently from gastro-intestinal diseases and accidents than the national average. The incidence of acute respiratory diseases, however, was similar in the cases of maternal care in the street and care by family members in another environment. Existing public health measures show a greater concern for the health of food consumers than that of workers in this area. Current public policy seeks to regulate street vending activities and to concentrate traders in ad hoc areas and facilities. Our research results document the need for actions that can contribute to an improvement in the care and health conditions of these young children.

A comparative analysis of suicide attempts in left-behind children and non-left-behind children in rural China

PubMed Central

Chang, Hongjuan; Yan, Qiuge; Tang, Lina; Huang, Juan; Ma, Yuqiao; Ye, Xiaozhou; Yu, Yizhen

2017-01-01

To estimate the prevalence of suicide attempts and explore the shared and unique factors influencing suicide risk in left-behind children (LBC) and non-left-behind children (NLBC) in rural China, this study collected data using a multi-stage cluster random sampling method from 13,952 children including 6,034 LBC and 7,918 NLBC. Sociodemographic characteristics, suicide attempts, neglect and physical abuse, negative life events, and loneliness were measured by self-reported questionnaires. Data were analyzed using logistic regression models. Gender and mother's education level were unique influential factors for NLBC while family structure type was a unique influential factor for LBC. The study provides two novel findings regarding NLBC specifically: 1. Children with optimal family socioeconomic status are more likely to report suicide attempts (odds ratio OR = 1)than are those in the general children population, OR 0.52 (95% CI: 0.39–0.70), and 2. Children with higher mother’s education level are subject to higher suicide rates in high school, OR 1.67 (95% CI: 1.13–2.46), and post-secondary education, OR 2.14 (95% CI: 1.37–3.37). The unique characteristics of LBC and NLBC in China suggest that investigating risk factors and determining the factors that might be targeted in intervention programs are urgently needed currently. PMID:28594874

Assessments of Ebola knowledge, attitudes and practices in Forécariah, Guinea and Kambia, Sierra Leone, July-August 2015.

PubMed

Jalloh, Mohamed F; Bunnell, Rebecca; Robinson, Susan; Jalloh, Mohammad B; Barry, Alpha Mamoudou; Corker, Jamaica; Sengeh, Paul; VanSteelandt, Amanda; Li, Wenshu; Dafae, Foday; Diallo, Alpha Ahmadou; Martel, Lise D; Hersey, Sara; Marston, Barbara; Morgan, Oliver; Redd, John T

2017-05-26

The border region of Forécariah (Guinea) and Kambia (Sierra Leone) was of immense interest to the West Africa Ebola response. Cross-sectional household surveys with multi-stage cluster sampling procedure were used to collect random samples from Kambia ( n = 635) in July 2015 and Forécariah ( n = 502) in August 2015 to assess public knowledge, attitudes and practices related to Ebola. Knowledge of the disease was high in both places, and handwashing with soap and water was the most widespread prevention practice. Acceptance of safe alternatives to traditional burials was significantly lower in Forécariah compared with Kambia. In both locations, there was a minority who held discriminatory attitudes towards survivors. Radio was the predominant source of information in both locations, but those from Kambia were more likely to have received Ebola information from community sources (mosques/churches, community meetings or health workers) compared with those in Forécariah. These findings contextualize the utility of Ebola health messaging during the epidemic and suggest the importance of continued partnership with community leaders, including religious leaders, as a prominent part of future public health protection.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'. © 2017 The Author(s).

Predictors of adolescents' mental health problems in Saudi Arabia: findings from the Jeeluna® national study.

PubMed

Abou Abbas, Oraynab; AlBuhairan, Fadia

2017-01-01

Depression and anxiety among adolescents require further attention as they have profound harmful implications on several aspects of adolescents' wellbeing and can be associated with life threatening risk behaviors such as suicide. To examine the underlying risk factors for feeling so sad or hopeless and for feeling worried among adolescents in Saudi Arabia. Data from Jeeluna ® national survey was used. A cross-sectional, multi-stage, stratified, cluster random sampling technique was applied among a sample of students aged 10-19 years attending intermediate and secondary schools in Saudi Arabia. A self-administered questionnaire assessing several domains, including feeling so sad or hopeless and worried, was used to collect data. Logistic regression models were fitted to determine the different factors associated with mental health. A sample of 12,121 students was included in this study. Feeling so sad or hopeless and feeling worried were significantly more prevalent among females and older adolescents ( p  < 0.0001). The results showed that poor relationship with parents, negative body image, and chronic illness to be significantly associated with feeling so sad or hopeless and worried. Symptoms suggestive of mental health problems among adolescents in Saudi Arabia are prevalent and deserve special attention. Adopting effective strategies, including regular screening and intervention programs are highly needed to better address, detect, and control early signs of these problems.

Significant decline in the tuberculosis burden in the Philippines ten years after initiating DOTS.

PubMed

Tupasi, T E; Radhakrishna, S; Chua, J A; Mangubat, N V; Guilatco, R; Galipot, M; Ramos, G; Quelapio, M I D; Beltran, G; Legaspi, J; Vianzon, R G; Lagahid, J

2009-10-01

The Philippines ranks ninth among the 22 high-burden countries for tuberculosis (TB). To measure the burden of pulmonary tuberculosis (PTB) in the Philippines and determine the impact of the DOTS strategy. The 2007 nationwide TB prevalence survey covered 50 clusters selected by multi-stage stratified random sampling from Metro Manila and other urban and rural areas. Subjects aged >or=10 years were screened radiographically for PTB to identify subjects for sputum examination and determine the prevalence of bacteriologically confirmed PTB, i.e., smear- and/or culture-positive PTB. In subjects aged >or=10 years, the 2007 prevalence of radiographic PTB was 6.3% (95%CI 5.5-7.1), bacteriologically confirmed PTB was 6.6 per 1000 (95%CI 5.1-8.1) and sputum smear-positive PTB was 2.6/1000 (95%CI 1.7-3.6). For the total population, the corresponding estimates were respectively 4.7%, 4.9/1000 and 2.0/1000. Between 1997 and 2007, there was a 31% reduction in bacteriologically confirmed PTB (P < 0.02) and a 27% reduction in smear-positive PTB (P = 0.18). This decline occurred despite the increasing poverty in the population. The survey demonstrated a significant decline in the TB burden 10 years after the implementation of DOTS, facilitated by a strategic public-private partnership.

Design and methodology of a community-based cluster-randomized controlled trial for dietary behaviour change in rural Kerala.

PubMed

Daivadanam, Meena; Wahlstrom, Rolf; Sundari Ravindran, T K; Sarma, P S; Sivasankaran, S; Thankappan, K R

2013-07-17

Interventions targeting lifestyle-related risk factors and non-communicable diseases have contributed to the mainstream knowledge necessary for action. However, there are gaps in how this knowledge can be translated for practical day-to-day use in complex multicultural settings like that in India. Here, we describe the design of the Behavioural Intervention for Diet study, which was developed as a community-based intervention to change dietary behaviour among middle-income households in rural Kerala. This was a cluster-randomized controlled trial to assess the effectiveness of a sequential stage-matched intervention to bring about dietary behaviour change by targeting the procurement and consumption of five dietary components: fruits, vegetables, salt, sugar, and oil. Following a step-wise process of pairing and exclusion of outliers, six out of 22 administrative units in the northern part of Trivandrum district, Kerala state were randomly selected and allocated to intervention or control arms. Trained community volunteers carried out the data collection and intervention delivery. An innovative tool was developed to assess household readiness-to-change, and a household measurement kit and easy formulas were introduced to facilitate the practical side of behaviour change. The 1-year intervention included a household component with sequential stage-matched intervention strategies at 0, 6, and 12 months along with counselling sessions, telephonic reminders, and home visits and a community component with general awareness sessions in the intervention arm. Households in the control arm received information on recommended levels of intake of the five dietary components and general dietary information leaflets. Formative research provided the knowledge to contextualise the design of the study in accordance with socio-cultural aspects, felt needs of the community, and the ground realities associated with existing dietary procurement, preparation, and consumption patterns. The study also addressed two key issues, namely the central role of the household as the decision unit and the long-term sustainability through the use of existing local and administrative networks and community volunteers.

Effectiveness of individualized fall prevention program in geriatric rehabilitation hospital setting: a cluster randomized trial.

PubMed

Aizen, Efraim; Lutsyk, Galina; Wainer, Lea; Carmeli, Sarit

2015-10-01

There is no conclusive evidence that hospital fall prevention programs can reduce the number of falls. We aimed to investigate the effect of a targeted individualized falls prevention program in a geriatric rehabilitation hospital. This was a two-stage cluster-controlled trial carried out in five geriatric rehabilitation wards. Participants were 752 patients with mean age 83.2 years. The intervention was a two-phase targeted intervention falls prevention program. The intervention included an assessment of patient's risk by a risk assessment tool and an individual management that includes medical, behavioral, cognitive and environmental modifications. Patients with moderate risk received additionally orientation guidance, and mobility restriction. Patients determined as high risk were additionally placed under permanent personal supervision. Outcome measures were falls during hospital stay. In both stages of the trial, intervention and control wards were almost similar at baseline for individual patient characteristics. Overall, 37 falls occurred during the study. No significant difference was found in fall rates during follow-up between intervention and control wards: 1.306 falls per 1000 bed days in the intervention groups and 1.763-1.826 falls per 1000 bed days in the control groups. The adjusted hazard ratio for falls in the intervention groups was 1.36 (95 % confidence interval 0.89-1.77) (P = 0.08) in the first stage and 1.27 (95 % confidence interval 0.92-1.67) (P = 0.12) in the second stage. These results suggest that in a geriatric rehabilitation hospital a targeted individualized intervention falls prevention program is not effective in reducing falls.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

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

PubMed

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.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Huo-Luo-Xiao-Ling (HLXL)-Dan, a Traditional Chinese Medicine, for patients with osteoarthritis of the knee: a multi-site, randomized, double-blind, placebo-controlled phase II clinical trial.

PubMed

Lao, L; Hochberg, M; Lee, D Y W; Gilpin, A M K; Fong, H H S; Langenberg, P; Chen, K; Li, E K; Tam, L S; Berman, B

2015-12-01

To examine the efficacy and safety of Huo-Luo-Xiao-Ling (HLXL)-Dan, a Traditional Chinese Medicine (TCM), in patients with knee osteoarthritis (OA). A multi-site, randomized, double-blind, placebo-controlled phase II dose-escalation clinical trial was conducted. Eligible patients who fulfilled American College of Rheumatology criteria were randomized to receive either HLXL or placebo. Clinical assessments included measurement of knee pain and function with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), patient global assessment (PGA), and knee pain scores every 2 weeks. A Data and Safety Monitoring Board (DSMB) was established to review the data for ensuring the quality of the trial. In the first stage, 28 participants were randomized to receive either low-dose HLXL-Dan (2400 mg/day) or placebo for 6 weeks. The results showed no statistical difference between the two groups. The study was then re-designed following the recommendation of DSMB. Ninety-two patients were enrolled in the second stage and were randomized to receive either high-dose HLXL-Dan (4000 mg/day for week 1-2, and 5600 mg/day for week 3-8) or placebo for 8 weeks. All outcome assessments showed significant improvements for both groups after 8 weeks but no significant between-group differences. The change (mean ± SD) of WOMAC pain and WOMAC function scores of HLXL and placebo group after 8 weeks were -1.2 ± 1.7 vs -1.4 ± 1.5, and -1.1 ± 1.6 vs -1.3 ± 1.5 respectively. No serious adverse events were reported. Although safe to use, an 8-week treatment of HLXL-Dan was not superior to placebo for reduction in pain or functional improvement in patients with knee OA. Clinicaltrials.gov (NCT00755326). Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Effect Sizes in Three-Level Cluster-Randomized Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.

2011-01-01

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

Workplace health and safety intervention for child care staff: Rationale, design, and baseline results from the CARE cluster randomized control trial.

PubMed

Ward, Dianne S; Vaughn, Amber E; Hales, Derek; Viera, Anthony J; Gizlice, Ziya; Bateman, Lori A; Grummon, Anna H; Arandia, Gabriela; Linnan, Laura A

2018-05-01

Low-wage workers suffer disproportionately high rates of chronic disease and are important targets for workplace health and safety interventions. Child care centers offer an ideal opportunity to reach some of the lowest paid workers, but these settings have been ignored in workplace intervention studies. Caring and Reaching for Health (CARE) is a cluster-randomized controlled trial evaluating efficacy of a multi-level, workplace-based intervention set in child care centers that promotes physical activity and other health behaviors among staff. Centers are randomized (1:1) into the Healthy Lifestyles (intervention) or the Healthy Finances (attention control) program. Healthy Lifestyles is delivered over six months including a kick-off event and three 8-week health campaigns (magazines, goal setting, behavior monitoring, tailored feedback, prompts, center displays, director coaching). The primary outcome is minutes of moderate and vigorous physical activity (MVPA); secondary outcomes are health behaviors (diet, smoking, sleep, stress), physical assessments (body mass index (BMI), waist circumference, blood pressure, fitness), and workplace supports for health and safety. In total, 56 centers and 553 participants have been recruited and randomized. Participants are predominately female (96.7%) and either Non-Hispanic African American (51.6%) or Non-Hispanic White (36.7%). Most participants (63.4%) are obese. They accumulate 17.4 (±14.2) minutes/day of MVPA and consume 1.3 (±1.4) and 1.3 (±0.8) servings/day of fruits and vegetables, respectively. Also, 14.2% are smokers; they report 6.4 (±1.4) hours/night of sleep; and 34.9% are high risk for depression. Baseline data demonstrate several serious health risks, confirming the importance of workplace interventions in child care. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Effect of health promotion and fluoride varnish on dental caries among Australian Aboriginal children: results from a community-randomized controlled trial*

PubMed Central

Slade, Gary D; Bailie, Ross S; Roberts-Thomson, Kaye; Leach, Amanda J; Raye, Iris; Endean, Colin; Simmons, Bruce; Morris, Peter

2011-01-01

Objectives We tested a dental health program in remote Aboriginal communities of Australia's Northern Territory, hypothesizing that it would reduce dental caries in preschool children. Methods In this 2-year, prospective, cluster-randomized, concurrent controlled, open trial of the dental health program compared to no such program, 30 communities were allocated at random to intervention and control groups. All residents aged 18–47 months were invited to participate. Twice per year for 2 years in the 15 intervention communities, fluoride varnish was applied to children's teeth, water consumption and daily tooth cleaning with toothpaste were advocated, dental health was promoted in community settings, and primary health care workers were trained in preventive dental care. Data from dental examinations at baseline and after 2 years were used to compute net dental caries increment per child (d3mfs). A multi-level statistical model compared d3mfs between intervention and control groups with adjustment for the clustered randomization design; four other models used additional variables for adjustment. Results At baseline, 666 children were examined; 543 of them (82%) were re-examined 2 years later. The adjusted d3mfs increment was significantly lower in the intervention group compared to the control group by an average of 3.0 surfaces per child (95% CI = 1.2, 4.9), a prevented fraction of 31%. Adjustment for additional variables yielded caries reductions ranging from 2.3 to 3.5 surfaces per child and prevented fractions of 24–36%. Conclusions These results corroborate findings from other studies where fluoride varnish was efficacious in preventing dental caries in young children. PMID:20707872

Workplace health and safety intervention for child care staff: Rationale, design, and baseline results from the CARE cluster randomized control trial

PubMed Central

Ward, Dianne S.; Vaughn, Amber E.; Hales, Derek; Viera, Anthony J.; Gizlice, Ziya; Bateman, Lori A.; Grummon, Anna H.; Arandia, Gabriela; Linnan, Laura A.

2018-01-01

Background Low-wage workers suffer disproportionately high rates of chronic disease and are important targets for workplace health and safety interventions. Child care centers offer an ideal opportunity to reach some of the lowest paid workers, but these settings have been ignored in workplace intervention studies. Methods Caring and Reaching for Health (CARE) is a cluster-randomized controlled trial evaluating efficacy of a multi-level, workplace-based intervention set in child care centers that promotes physical activity and other health behaviors among staff. Centers are randomized (1:1) into the Healthy Lifestyles (intervention) or the Healthy Finances (attention control) program. Healthy Lifestyles is delivered over six months including a kick-off event and three 8-week health campaigns (magazines, goal setting, behavior monitoring, tailored feedback, prompts, center displays, director coaching). The primary outcome is minutes of moderate and vigorous physical activity (MVPA); secondary outcomes are health behaviors (diet, smoking, sleep, stress), physical assessments (body mass index (BMI), waist circumference, blood pressure, fitness), and workplace supports for health and safety. Results In total, 56 centers and 553 participants have been recruited and randomized. Participants are predominately female (96.7%) and either Non-Hispanic African American (51.6%) or Non-Hispanic White (36.7%). Most participants (63.4%) are obese. They accumulate 17.4 ( ± 14.2) minutes/day of MVPA and consume 1.3 ( ± 1.4) and 1.3 ( ± 0.8) servings/day of fruits and vegetables, respectively. Also, 14.2% are smokers; they report 6.4 ( ± 1.4) hours/night of sleep; and 34.9% are high risk for depression. Conclusions Baseline data demonstrate several serious health risks, confirming the importance of workplace interventions in child care. PMID:29501740

Design and simulation study of the immunization Data Quality Audit (DQA).

PubMed

Woodard, Stacy; Archer, Linda; Zell, Elizabeth; Ronveaux, Olivier; Birmingham, Maureen

2007-08-01

The goal of the Data Quality Audit (DQA) is to assess whether the Global Alliance for Vaccines and Immunization-funded countries are adequately reporting the number of diphtheria-tetanus-pertussis immunizations given, on which the "shares" are awarded. Given that this sampling design is a modified two-stage cluster sample (modified because a stratified, rather than a simple, random sample of health facilities is obtained from the selected clusters); the formula for the calculation of the standard error for the estimate is unknown. An approximated standard error has been proposed, and the first goal of this simulation is to assess the accuracy of the standard error. Results from the simulations based on hypothetical populations were found not to be representative of the actual DQAs that were conducted. Additional simulations were then conducted on the actual DQA data to better access the precision of the DQ with both the original and the increased sample sizes.

Cluster randomized evaluation of Adolescent Girls Empowerment Programme (AGEP): study protocol.

PubMed

Hewett, Paul C; Austrian, Karen; Soler-Hampejsek, Erica; Behrman, Jere R; Bozzani, Fiammetta; Jackson-Hachonda, Natalie A

2017-05-05

Adolescents in less developed countries such as Zambia often face multi-faceted challenges for achieving successful transitions through adolescence to early adulthood. The literature has noted the need to introduce interventions during this period, particularly for adolescent girls, with the perspective that such investments have significant economic, social and health returns to society. The Adolescent Girls Empowerment Programme (AGEP) was an intervention designed as a catalyst for change for adolescent girls through themselves, to their family and community. AGEP was a multi-sectoral intervention targeting over 10,000 vulnerable adolescent girls ages 10-19 in rural and urban areas, in four of the ten provinces of Zambia. At the core of AGEP were mentor-led, weekly girls' group meetings of 20 to 30 adolescent girls participating over two years. Three curricula - sexual and reproductive health and lifeskills, financial literacy, and nutrition - guided the meetings. An engaging and participatory pedagogical approach was used. Two additional program components, a health voucher and a bank account, were offered to some girls to provide direct mechanisms to improve access to health and financial services. Embedded within AGEP was a rigorous multi-arm randomised cluster trial with randomization to different combinations of programme arms. The study was powered to assess the impact across a set of key longer-term outcomes, including early marriage and first birth, contraceptive use, educational attainment and acquisition of HIV and HSV-2. Baseline behavioural surveys and biological specimen collection were initiated in 2013. Impact was evaluated immediately after the program ended in 2015 and will be evaluated again after two additional years of follow-up in 2017. The primary analysis is intent-to-treat. Qualitative data are being collected in 2013, 2015 and 2017 to inform the programme implementation and the quantitative findings. An economic evaluation will evaluate the incremental cost-effectiveness of each component of the intervention. The AGEP program and embedded evaluation will provide detailed information regarding interventions for adolescent girls in developing country settings. It will provide a rich information and data source on adolescent girls and its related findings will inform policy-makers, health professionals, donors and other stakeholders. ISRCTN29322231 . March 04 2016; retrospectively registered.

Multidimensional Normalization to Minimize Plate Effects of Suspension Bead Array Data.

PubMed

Hong, Mun-Gwan; Lee, Woojoo; Nilsson, Peter; Pawitan, Yudi; Schwenk, Jochen M

2016-10-07

Enhanced by the growing number of biobanks, biomarker studies can now be performed with reasonable statistical power by using large sets of samples. Antibody-based proteomics by means of suspension bead arrays offers one attractive approach to analyze serum, plasma, or CSF samples for such studies in microtiter plates. To expand measurements beyond single batches, with either 96 or 384 samples per plate, suitable normalization methods are required to minimize the variation between plates. Here we propose two normalization approaches utilizing MA coordinates. The multidimensional MA (multi-MA) and MA-loess both consider all samples of a microtiter plate per suspension bead array assay and thus do not require any external reference samples. We demonstrate the performance of the two MA normalization methods with data obtained from the analysis of 384 samples including both serum and plasma. Samples were randomized across 96-well sample plates, processed, and analyzed in assay plates, respectively. Using principal component analysis (PCA), we could show that plate-wise clusters found in the first two components were eliminated by multi-MA normalization as compared with other normalization methods. Furthermore, we studied the correlation profiles between random pairs of antibodies and found that both MA normalization methods substantially reduced the inflated correlation introduced by plate effects. Normalization approaches using multi-MA and MA-loess minimized batch effects arising from the analysis of several assay plates with antibody suspension bead arrays. In a simulated biomarker study, multi-MA restored associations lost due to plate effects. Our normalization approaches, which are available as R package MDimNormn, could also be useful in studies using other types of high-throughput assay data.

Cardiovascular risk factors in multi-ethnic middle school students: the HEALTHY primary prevention trial.

PubMed

Willi, S M; Hirst, K; Jago, R; Buse, J; Kaufman, F; El Ghormli, L; Bassin, S; Elliot, D; Hale, D E

2012-06-01

The objective of this study was to examine the effects of an integrated, multi-component, school-based intervention programme on cardiovascular disease (CVD) risk factors among a multi-ethnic cohort of middle school students. HEALTHY was a cluster randomized, controlled, primary prevention trial. Middle school was the unit of randomization and intervention. Half of the schools were assigned to an intervention programme consisting of changes in the total school food environment and physical education classes, enhanced by educational outreach and behaviour change activities and promoted by a social marketing campaign consisting of reinforcing messages and images. Outcome data reported (anthropometrics, blood pressure and fasting lipid levels) were collected on a cohort of students enrolled at the start of 6th grade (∼11-12 years old) and followed to end of 8th grade (∼13-14 years old). Forty-two middle schools were enrolled at seven field centres; 4363 students provided both informed consent and CVD data at baseline and end of study. The sample was 52.7% female, 54.5% Hispanic, 17.6% non-Hispanic Black, 19.4% non-Hispanic White and 8.5% other racial/ethnic combinations, and 49.6% were categorized as overweight or obese (body mass index ≥ 85th percentile) at baseline. A significant intervention effect was detected in the prevalence of hypertension in non-Hispanic Black and White males. The intervention produced no significant changes in lipid levels. The prevalence of some CVD risk factors is high in minority middle school youth, particularly males. A multi-component, school-based programme achieved only modest reductions in these risk factors; however, promising findings occurred in non-Hispanic Black and White males with hypertension. © 2012 The Authors. Pediatric Obesity © 2012 International Association for the Study of Obesity.

Analyses of advanced concepts in multi-stage gyro-amplifiers and startup in high power gyro-oscillators

NASA Astrophysics Data System (ADS)

Sinitsyn, Oleksandr V.

Gyrotrons are well recognized sources of high-power coherent electromagnetic radiation. The power that gyrotrons can radiate in the millimeter- and submillimeter-wavelength regions exceeds the power of classical microwave tubes by many orders of magnitude. In this work, the author considers some problems related to the operation of gyro-devices and methods of their solution. In particular, the self-excitation conditions for parasitic backward waves and effect of distributed losses on the small-signal gain of gyro-TWTs are analyzed. The corresponding small-signal theory describing two-stage gyro-traveling-wave tubes (gyro-TWTs) with the first stage having distributed losses is presented. The theory is illustrated by using it for the description of operation of a Ka-band gyro-TWT designed at the Naval Research Laboratory. Also, the results of nonlinear studies of this tube are presented and compared with the ones obtained by the use of MAGY, a multi-frequency, self-consistent code developed at the University of Maryland. An attempt to build a large signal theory of gyro-TWTs with tapered geometry and magnetic field profile is made and first results are obtained for a 250 GHz gyro-TWT. A comparative small-signal analysis of conventional four-cavity and three-stage clustered-cavity gyroklystrons is performed. The corresponding point-gap models for these devices are presented. The efficiency, gain, bandwidth and gain-bandwidth product are analyzed for each scheme. Advantages of the clustered-cavity over the conventional design are discussed. The startup scenarios in high-power gyrotrons and the most important physical effects associated with them are considered. The work presents the results of startup simulations for a 140 GHz, MW-class gyrotron developed by Communications and Power Industries (CPI) for electron-cyclotron resonance heating (ECRH) and current drive experiments on the "Wendelstein 7-X" stellarator plasma. Also presented are the results for a 110 GHz, 1.5 MW gyrotron currently being developed at CPI. The simulations are carried out for six competing modes and with the effects of electron velocity spread and voltage depression taken into account. Also, the slow stage of the startup in long-pulse gyrotrons is analyzed and attention is paid to the effects of ion compensation of the beam space charge, frequency deviation due to the cavity wall heating and beam current decrease due to cathode cooling. These effects are modeled with a simple nonlinear theory and the code MAGY.

Continuous Mass Measurement on Conveyor Belt

NASA Astrophysics Data System (ADS)

Tomobe, Yuki; Tasaki, Ryosuke; Yamazaki, Takanori; Ohnishi, Hideo; Kobayashi, Masaaki; Kurosu, Shigeru

The continuous mass measurement of packages on a conveyor belt will become greatly important. In the mass measurement, the sequence of products is generally random. An interesting possibility of raising throughput of the conveyor line without increasing the conveyor belt speed is offered by the use of two or three conveyor belt scales (called a multi-stage conveyor belt scale). The multi-stage conveyor belt scale can be created which will adjust the conveyor belt length to the product length. The conveyor belt scale usually has maximum capacities of less than 80kg and 140cm, and achieves measuring rates of more than 150 packages per minute and more. The output signals from the conveyor belt scale are always contaminated with noises due to vibrations of the conveyor and the product to be measured in motion. In this paper an employed digital filter is of Finite Impulse Response (FIR) type designed under the consideration on the dynamics of the conveyor system. The experimental results on the conveyor belt scale suggest that the filtering algorithms are effective enough to practical applications to some extent.

The clinical and cost-effectiveness of the BRinging Information and Guided Help Together (BRIGHT) intervention for the self-management support of people with stage 3 chronic kidney disease in primary care: study protocol for a randomized controlled trial

PubMed Central

2013-01-01

Background Improving the quality of care for people with vascular disease is a key priority. Chronic kidney disease (CKD) has recently been included as a target condition for general practices to add to registers of chronic conditions as part of the Quality and Outcome Framework. This paper outlines the implementation and evaluation of a self-management intervention involving an information guidebook, tailored access to local resources and telephone support for people with stage 3 chronic kidney disease. Methods/Design The study involves a multi-site, longitudinal patient-level randomized controlled trial. The study will evaluate the clinical use and cost-effectiveness of a complex self-management intervention for people with stage 3 chronic kidney disease in terms of self-management capacity, health-related quality of life and blood pressure control compared to care as usual. We describe the methods of the patient-level randomized controlled trial. Discussion The management of chronic kidney disease is a developing area of research. The BRinging Information and Guided Help Together (BRIGHT) trial aims to provide evidence that a complementary package of support for people with vascular disease that targets both clinical and social need broadens the opportunities of self-management support by addressing problems related to social disadvantage. Trial registration Trial registration reference: ISRCTN45433299 PMID:23356861

The Effects of Including Observed Means or Latent Means as Covariates in Multilevel Models for Cluster Randomized Trials

ERIC Educational Resources Information Center

Aydin, Burak; Leite, Walter L.; Algina, James

2016-01-01

We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…

Secure communications using quantum cryptography

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

Hughes, R.J.; Buttler, W.T.; Kwiat, P.G.

1997-08-01

The secure distribution of the secret random bit sequences known as {open_quotes}key{close_quotes} material, is an essential precursor to their use for the encryption and decryption of confidential communications. Quantum cryptography is an emerging technology for secure key distribution with single-photon transmissions, nor evade detection (eavesdropping raises the key error rate above a threshold value). We have developed experimental quantum cryptography systems based on the transmission of non-orthogonal single-photon states to generate shared key material over multi-kilometer optical fiber paths and over line-of-sight links. In both cases, key material is built up using the transmission of a single-photon per bit ofmore » an initial secret random sequence. A quantum-mechanically random subset of this sequence is identified, becoming the key material after a data reconciliation stage with the sender. In our optical fiber experiment we have performed quantum key distribution over 24-km of underground optical fiber using single-photon interference states, demonstrating that secure, real-time key generation over {open_quotes}open{close_quotes} multi-km node-to-node optical fiber communications links is possible. We have also constructed a quantum key distribution system for free-space, line-of-sight transmission using single-photon polarization states, which is currently undergoing laboratory testing. 7 figs.« less

Kelvin-Helmholtz Instability: Lessons Learned and Ways Forward

NASA Astrophysics Data System (ADS)

Masson, A.; Nykyri, K.

2018-06-01

The Kelvin-Helmholtz instability (KHI) is a ubiquitous phenomenon across the Universe, observed from 500 m deep in the oceans on Earth to the Orion molecular cloud. Over the past two decades, several space missions have enabled a leap forward in our understanding of this phenomenon at the Earth's magnetopause. Key results obtained by these missions are first presented, with a special emphasis on Cluster and THEMIS. In particular, as an ideal instability, the KHI was not expected to produce mass transport. Simulations, later confirmed by spacecraft observations, indicate that plasma transport in Kelvin-Helmholtz (KH) vortices can arise during non-linear stage of its development via secondary process. In addition to plasma transport, spacecraft observations have revealed that KHI can also lead to significant ion heating due to enhanced ion-scale wave activity driven by the KHI. Finally, we describe what are the upcoming observational opportunities in 2018-2020, thanks to a unique constellation of multi-spacecraft missions including: MMS, Cluster, THEMIS, Van Allen Probes and Swarm.

The Design of Cluster Randomized Trials with Random Cross-Classifications

ERIC Educational Resources Information Center

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…

The Size Distribution Of Cluster Galaxies

NASA Astrophysics Data System (ADS)

Kuchner, U.; Ziegler, B.; Bamford, S.; Verdugo, M.; Haeussler, B.

2017-06-01

We establish a sample of 560 spectroscopically confirmed cluster members of MACS J1206.2- 0847 at z = 0.45 and utilize multi-wavelength and multi-component Sersic profile fitting to provide luminosities and sizes for the key structural components bulge and disk. While the difference between field and cluster galaxy properties are mostly due to a preference for cluster members to be early-type (quiescent, bulge-dominated), we see evidence for an outer disk fading and a sharp rise in the number of red disks with smaller effective radii at the tidally active cluster region around R200. Even though red disks are already virialized according to their velocity distribution, they are clearly not part of the old population found in the innermost region; they represent an important population of transitional objects in clusters.

Perturbative universal state-selective correction for state-specific multi-reference coupled cluster methods

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

Brabec, Jiri; Banik, Subrata; Kowalski, Karol

2016-10-28

The implementation details of the universal state-selective (USS) multi-reference coupled cluster (MRCC) formalism with singles and doubles (USS(2)) are discussed on the example of several benchmark systems. We demonstrate that the USS(2) formalism is capable of improving accuracies of state specific multi-reference coupled-cluster (MRCC) methods based on the Brillouin-Wigner and Mukherjee’s sufficiency conditions. Additionally, it is shown that the USS(2) approach significantly alleviates problems associated with the lack of invariance of MRCC theories upon the rotation of active orbitals. We also discuss the perturbative USS(2) formulations that significantly reduce numerical overhead of the full USS(2) method.

Mindfulness-Based Stress Reduction in Post-treatment Breast Cancer Patients: Immediate and Sustained Effects Across Multiple Symptom Clusters.

PubMed

Reich, Richard R; Lengacher, Cecile A; Alinat, Carissa B; Kip, Kevin E; Paterson, Carly; Ramesar, Sophia; Han, Heather S; Ismail-Khan, Roohi; Johnson-Mallard, Versie; Moscoso, Manolete; Budhrani-Shani, Pinky; Shivers, Steve; Cox, Charles E; Goodman, Matthew; Park, Jong

2017-01-01

Breast cancer survivors (BCS) face adverse physical and psychological symptoms, often co-occurring. Biologic and psychological factors may link symptoms within clusters, distinguishable by prevalence and/or severity. Few studies have examined the effects of behavioral interventions or treatment of symptom clusters. The aim of this study was to identify symptom clusters among post-treatment BCS and determine symptom cluster improvement following the Mindfulness-Based Stress Reduction for Breast Cancer (MBSR(BC)) program. Three hundred twenty-two Stage 0-III post-treatment BCS were randomly assigned to either a six-week MBSR(BC) program or usual care. Psychological (depression, anxiety, stress, and fear of recurrence), physical (fatigue, pain, sleep, and drowsiness), and cognitive symptoms and quality of life were assessed at baseline, six, and 12 weeks, along with demographic and clinical history data at baseline. A three-step analytic process included the error-accounting models of factor analysis and structural equation modeling. Four symptom clusters emerged at baseline: pain, psychological, fatigue, and cognitive. From baseline to six weeks, the model demonstrated evidence of MBSR(BC) effectiveness in both the psychological (anxiety, depression, perceived stress and QOL, emotional well-being) (P = 0.007) and fatigue (fatigue, sleep, and drowsiness) (P < 0.001) clusters. Results between six and 12 weeks showed sustained effects, but further improvement was not observed. Our results provide clinical effectiveness evidence that MBSR(BC) works to improve symptom clusters, particularly for psychological and fatigue symptom clusters, with the greatest improvement occurring during the six-week program with sustained effects for several weeks after MBSR(BC) training. Name and URL of Registry: ClinicalTrials.gov. Registration number: NCT01177124. Copyright © 2016. Published by Elsevier Inc.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. This methodology shows promise for the identification of conditions in general populations and supports the current focus on the potential importance of bowel symptoms and the gut in mental health research.

Efficiency of static core turn-off in a system-on-a-chip with variation

DOEpatents

Cher, Chen-Yong; Coteus, Paul W; Gara, Alan; Kursun, Eren; Paulsen, David P; Schuelke, Brian A; Sheets, II, John E; Tian, Shurong

2013-10-29

A processor-implemented method for improving efficiency of a static core turn-off in a multi-core processor with variation, the method comprising: conducting via a simulation a turn-off analysis of the multi-core processor at the multi-core processor's design stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's design stage includes a first output corresponding to a first multi-core processor core to turn off; conducting a turn-off analysis of the multi-core processor at the multi-core processor's testing stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's testing stage includes a second output corresponding to a second multi-core processor core to turn off; comparing the first output and the second output to determine if the first output is referring to the same core to turn off as the second output; outputting a third output corresponding to the first multi-core processor core if the first output and the second output are both referring to the same core to turn off.

Myeloid Clusters Are Associated with a Pro-Metastatic Environment and Poor Prognosis in Smoking-Related Early Stage Non-Small Cell Lung Cancer

PubMed Central

Zhang, Wang; Pal, Sumanta K.; Liu, Xueli; Yang, Chunmei; Allahabadi, Sachin; Bhanji, Shaira; Figlin, Robert A.; Yu, Hua; Reckamp, Karen L.

2013-01-01

Background 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. Methods 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. Results 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). Conclusions 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. PMID:23717691

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

NASA Astrophysics Data System (ADS)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

A Multi-Discipline, Multi-Genre Digital Library for Research and Education

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

2004-01-01

We describe NCSTRL+, a unified, canonical digital library for educational and scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing "buckets". We have extended the Dienst protocol, the protocol underlying NCSTRL, to provide the ability to "cluster" independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The concept of "buckets" provides a mechanism for publishing and managing logically linked entities with multiple data formats. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks

NASA Astrophysics Data System (ADS)

Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang

2016-01-01

The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.

Development of nanoscale structure in LAT-based signaling complexes

PubMed Central

2016-01-01

ABSTRACT The adapter molecule linker for activation of T cells (LAT) plays a crucial role in forming signaling complexes induced by stimulation of the T cell receptor (TCR). These multi-molecular complexes are dynamic structures that activate highly regulated signaling pathways. Previously, we have demonstrated nanoscale structure in LAT-based complexes where the adapter SLP-76 (also known as LCP2) localizes to the periphery of LAT clusters. In this study, we show that initially LAT and SLP-76 are randomly dispersed throughout the clusters that form upon TCR engagement. The segregation of LAT and SLP-76 develops near the end of the spreading process. The local concentration of LAT also increases at the same time. Both changes require TCR activation and an intact actin cytoskeleton. These results demonstrate that the nanoscale organization of LAT-based signaling complexes is dynamic and indicates that different kinds of LAT-based complexes appear at different times during T cell activation. PMID:27875277

A school-based intervention improved dietary intake outcomes and reduced waist circumference in adolescents: a cluster randomized controlled trial.

PubMed

Ochoa-Avilés, Angélica; Verstraeten, Roosmarijn; Huybregts, Lieven; Andrade, Susana; Van Camp, John; Donoso, Silvana; Ramírez, Patricia Liliana; Lachat, Carl; Maes, Lea; Kolsteren, Patrick

2017-12-11

In Ecuador, adolescents' food intake does not comply with guidelines for a healthy diet. Together with abdominal obesity adolescent's inadequate diets are risk factors for non-communicable diseases. We report the effectiveness of a school-based intervention on the dietary intake and waist circumference among Ecuadorian adolescents. A pair-matched cluster randomized controlled trial including 1430 adolescents (12-14 years old) was conducted. The program aimed at improving the nutritional value of dietary intake, physical activity (primary outcomes), body mass index, waist circumference and blood pressure (secondary outcomes). This paper reports: (i) the effect on fruit and vegetable intake, added sugar intake, unhealthy snacking (consumption of unhealthy food items that are not in line with the dietary guidelines eaten during snack time; i.e. table sugar, sweets, salty snacks, fast food, soft drinks and packaged food), breakfast intake and waist circumference; and, (ii) dose and reach of the intervention. Dietary outcomes were estimated by means of two 24-h recall at baseline, after the first 17-months (stage one) and after the last 11-months (stage two) of implementation. Dose and reach were evaluated using field notes and attendance forms. Educational toolkits and healthy eating workshops with parents and food kiosks staff in the schools were implemented in two different stages. The overall effect was assessed using linear mixed models and regression spline mixed effect models were applied to evaluate the effect after each stage. Data from 1046 adolescents in 20 schools were analyzed. Participants from the intervention group consumed lower quantities of unhealthy snacks (-23.32 g; 95% CI: -45.25,-1.37) and less added sugar (-5.66 g; 95% CI: -9.63,-1.65) at the end of the trial. Daily fruit and vegetable intake decreased in both the intervention and control groups compared to baseline, albeit this decrease was 23.88 g (95% CI: 7.36, 40.40) lower in the intervention group. Waist circumference (-0.84 cm; 95% CI: -1.68, 0.28) was lower in the intervention group at the end of the program; the effect was mainly observed at stage one. Dose and reach were also higher at stage one. The trial had positive effects on risk factors for non-communicable diseases, i.e. decreased consumption of unhealthy snacks. The program strategies must be implemented at the national level through collaboration between the academia and policy makers to assure impact at larger scale. ClinicalTrial.gov-NCT01004367 .

Efficient sampling of complex network with modified random walk strategies

NASA Astrophysics Data System (ADS)

Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

2018-02-01

We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Cluster Randomized Test-Negative Design (CR-TND) Trials: A Novel and Efficient Method to Assess the Efficacy of Community Level Dengue Interventions.

PubMed

Anders, Katherine L; Cutcher, Zoe; Kleinschmidt, Immo; Donnelly, Christl A; Ferguson, Neil M; Indriani, Citra; O'Neill, Scott L; Jewell, Nicholas P; Simmons, Cameron P

2018-05-07

Cluster randomized trials are the gold standard for assessing efficacy of community-level interventions, such as vector control strategies against dengue. We describe a novel cluster randomized trial methodology with a test-negative design, which offers advantages over traditional approaches. It utilizes outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We use simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. This demonstrates that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. We also briefly discuss analytical considerations for an odds ratio-based effect estimate arising from clustered data, and outline potential approaches to analysis. We conclude that application of the test-negative design to certain cluster randomized trials could increase their efficiency and ease of implementation.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

PubMed

Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

2015-11-01

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

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

Liu, Hui; Song, Yongduan; Xue, Fangzheng

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than themore » SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.« less

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Relative benefit of a stage of change approach for the prevention of musculoskeletal pain and discomfort: a cluster randomised trial.

PubMed

Doda, Diana; Rothmore, Paul; Pisaniello, Dino; Briggs, Nancy; Stewart, Sasha; Mahmood, Mohammed; Hiller, Janet E

2015-11-01

To examine the benefit of a psychological Stage of Change (SOC) approach, relative to standard ergonomics advice, for the prevention of work-related musculoskeletal pain and discomfort (MSPD). A cluster randomised trial was conducted in South Australia across a broad range of workplaces. Repeated face-to-face interviews were conducted onsite to assess MSPD, safety climate, job satisfaction and other factors. Changes in MSPD across intervention groups and time were investigated using Generalised Estimating Equation (GEE) methods. 25 workgroups (involving 242 workers) were randomly allocated to either a standard intervention or an intervention tailored according to SOC. The prevalence of MSPD increased for both groups, but was only significant for the standard group, in respect of lower back MSPD. Workers receiving tailored interventions were 60% less likely to experience lower back MSPD. After adjusting for age, gender and job satisfaction, it was found that company safety climate and length of employment were significantly correlated to the time-intervention effect. There was no correlation with workload. Compared with standard ergonomics advice to management, there was evidence of a benefit of stage-matched intervention for MSPD prevention, particularly for low back pain. Organisational safety climate should be taken into account when planning prevention programmes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

ULTRA-DEEP GEMINI NEAR-INFRARED OBSERVATIONS OF THE BULGE GLOBULAR CLUSTER NGC 6624

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

Saracino, S.; Dalessandro, E.; Ferraro, F. R.

2016-11-20

We used ultra-deep J and K {sub s} images secured with the near-infrared (NIR) GSAOI camera assisted by the multi-conjugate adaptive optics system GeMS at the GEMINI South Telescope in Chile, to obtain a ( K {sub s} , J - K {sub s} ) color–magnitude diagram (CMD) for the bulge globular cluster NGC 6624. We obtained the deepest and most accurate NIR CMD from the ground for this cluster, by reaching K {sub s} ∼ 21.5, approximately 8 mag below the horizontal branch level. The entire extension of the Main Sequence (MS) is nicely sampled and at K {submore » s} ∼ 20 we detected the so-called MS “knee” in a purely NIR CMD. By taking advantage of the exquisite quality of the data, we estimated the absolute age of NGC 6624 ( t {sub age} = 12.0 ± 0.5 Gyr), which turns out to be in good agreement with previous studies in the literature. We also analyzed the luminosity and mass functions of MS stars down to M ∼ 0.45 M{sub ⊙}, finding evidence of a significant increase of low-mass stars at increasing distances from the cluster center. This is a clear signature of mass segregation, confirming that NGC 6624 is in an advanced stage of dynamical evolution.« less

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Stream Clustering of Growing Objects

NASA Astrophysics Data System (ADS)

Siddiqui, Zaigham Faraz; Spiliopoulou, Myra

We study incremental clustering of objects that grow and accumulate over time. The objects come from a multi-table stream e.g. streams of Customer and Transaction. As the Transactions stream accumulates, the Customers’ profiles grow. First, we use an incremental propositionalisation to convert the multi-table stream into a single-table stream upon which we apply clustering. For this purpose, we develop an online version of K-Means algorithm that can handle these swelling objects and any new objects that arrive. The algorithm also monitors the quality of the model and performs re-clustering when it deteriorates. We evaluate our method on the PKDD Challenge 1999 dataset.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2017-12-01

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.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use.

PubMed

Babbin, Steven F; Velicer, Wayne F; Paiva, Andrea L; Brick, Leslie Ann D; Redding, Colleen A

2015-01-01

Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N=4059) and alcohol (N=3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. Copyright © 2014. Published by Elsevier Ltd.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use

PubMed Central

Babbin, Steven F.; Velicer, Wayne F.; Paiva, Andrea L.; Brick, Leslie Ann D.; Redding, Colleen A.

2015-01-01

Introduction Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N= 4059) and alcohol (N= 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. PMID:25222849

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

PubMed

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

Adaptive fuzzy leader clustering of complex data sets in pattern recognition

NASA Technical Reports Server (NTRS)

Newton, Scott C.; Pemmaraju, Surya; Mitra, Sunanda

1992-01-01

A modular, unsupervised neural network architecture for clustering and classification of complex data sets is presented. The adaptive fuzzy leader clustering (AFLC) architecture is a hybrid neural-fuzzy system that learns on-line in a stable and efficient manner. The initial classification is performed in two stages: a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from fuzzy C-means system equations for the centroids and the membership values. The AFLC algorithm is applied to the Anderson Iris data and laser-luminescent fingerprint image data. It is concluded that the AFLC algorithm successfully classifies features extracted from real data, discrete or continuous.

Comparing Dynamic Treatment Regimes Using Repeated-Measures Outcomes: Modeling Considerations in SMART Studies

PubMed Central

Lu, Xi; Nahum-Shani, Inbal; Kasari, Connie; Lynch, Kevin G.; Oslin, David W.; Pelham, William E.; Fabiano, Gregory; Almirall, Daniel

2016-01-01

A dynamic treatment regime (DTR) is a sequence of decision rules, each of which recommends a treatment based on a patient’s past and current health status. Sequential, multiple assignment, randomized trials (SMARTs) are multi-stage trial designs that yield data specifically for building effective DTRs. Modeling the marginal mean trajectories of a repeated-measures outcome arising from a SMART presents challenges, because traditional longitudinal models used for randomized clinical trials do not take into account the unique design features of SMART. We discuss modeling considerations for various forms of SMART designs, emphasizing the importance of considering the timing of repeated measures in relation to the treatment stages in a SMART. For illustration, we use data from three SMART case studies with increasing level of complexity, in autism, child attention deficit hyperactivity disorder (ADHD), and adult alcoholism. In all three SMARTs we illustrate how to accommodate the design features along with the timing of the repeated measures when comparing DTRs based on mean trajectories of the repeated-measures outcome. PMID:26638988

Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies.

PubMed

Lu, Xi; Nahum-Shani, Inbal; Kasari, Connie; Lynch, Kevin G; Oslin, David W; Pelham, William E; Fabiano, Gregory; Almirall, Daniel

2016-05-10

A dynamic treatment regime (DTR) is a sequence of decision rules, each of which recommends a treatment based on a patient's past and current health status. Sequential, multiple assignment, randomized trials (SMARTs) are multi-stage trial designs that yield data specifically for building effective DTRs. Modeling the marginal mean trajectories of a repeated-measures outcome arising from a SMART presents challenges, because traditional longitudinal models used for randomized clinical trials do not take into account the unique design features of SMART. We discuss modeling considerations for various forms of SMART designs, emphasizing the importance of considering the timing of repeated measures in relation to the treatment stages in a SMART. For illustration, we use data from three SMART case studies with increasing level of complexity, in autism, child attention deficit hyperactivity disorder, and adult alcoholism. In all three SMARTs, we illustrate how to accommodate the design features along with the timing of the repeated measures when comparing DTRs based on mean trajectories of the repeated-measures outcome. Copyright © 2015 John Wiley & Sons, Ltd.

The Cluster Environment of Two High-mass Protostars

NASA Astrophysics Data System (ADS)

Montes, Virginie; Hofner, Peter

2017-06-01

Characterizing the environment and stellar population in which high-mass stars form is an important step to decide between the main massive star formation theories. In the monolithic collapse model, the mass of the core will determine the final stellar mass (e.g., McKee & Tan 2003). In contrast, in the competitive accretion model (e.g., Bonnell & Bate 2006), the mass of the high-mass star is related to the properties of the cluster. As dynamical processes substantially affect the appearance of a cluster, we study early stages of high-mass star formation. These regions often show extended emission from hot dust at infrared wavelengths, which can cause difficulties to define the cluster. We use a multi-wavelength technique to study nearby high-mass star clusters, based on X-ray observations with the Chandra X-Ray Telescope, in conjunction with infrared data and VLA data. The technique relies on the fact that YSOs are particularly bright in X-ray and that contamination is relatively small. X-ray observations allow us to determine the cluster size. The cluster membership and YSOs classification is established using infrared identification of the X-ray sources, and color-color and color-magnitude diagrams.In this talk, I will present our findings on the cluster study of two high-mass star forming regions: IRAS 20126+4104 and IRAS 16562-3959. While most massive stars appear to be formed in rich a cluster environment, those two sources are candidates for the formation of massive stars in a relatively poor cluster. In contrast to what was found in previous studies (Qiu et al. 2008), the dominant B0-type protostar in IRAS 20126+4104 is associated with a small cluster of low-mass stars. I will also show our current work on IRAS 16562-3959, which contains one of the most luminous O-type protostars in the Galaxy. In the vicinity of this particularly interesting region there is a multitude of small clusters, for which I will present how their stellar population differ from the high-mass star-forming cluster IRAS 16562-3959.

Amplified Fragment Length Polymorphism Fingerprinting of Pseudomonas Strains from a Poultry Processing Plant

PubMed Central

Geornaras, Ifigenia; Kunene, Nokuthula F.; von Holy, Alexander; Hastings, John W.

1999-01-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage. PMID:10473382

Amplified fragment length polymorphism fingerprinting of Pseudomonas strains from a poultry processing plant.

PubMed

Geornaras, I; Kunene, N F; von Holy, A; Hastings, J W

1999-09-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage.

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya.

PubMed Central

Kadohira, M.; McDermott, J. J.; Shoukri, M. M.; Kyule, M. N.

1997-01-01

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data. PMID:9042033

Prevalence and factors related to dental caries among pre-school children of Saddar town, Karachi, Pakistan: a cross-sectional study.

PubMed

Dawani, Narendar; Nisar, Nighat; Khan, Nazeer; Syed, Shahbano; Tanweer, Navara

2012-12-27

Dental caries is highly prevalent and a significant public health problem among children throughout the world. Epidemiological data regarding prevalence of dental caries amongst Pakistani pre-school children is very limited. The objective of this study is to determine the frequency of dental caries among pre-school children of Saddar Town, Karachi, Pakistan and the factors related to caries. A cross-sectional study of 1000 preschool children was conducted in Saddar town, Karachi. Two-stage cluster sampling was used to select the sample. At first stage, eight clusters were selected randomly from total 11 clusters. In second stage, from the eight selected clusters, preschools were identified and children between 3- to 6-years age group were assessed for dental caries. Caries prevalence was 51% with a mean dmft score being 2.08 (±2.97) of which decayed teeth constituted 1.95. The mean dmft of males was 2.3 (±3.08) and of females was 1.90 (±2.90). The mean dmft of 3, 4, 5 and 6-year olds was 1.65, 2.11, 2.16 and 3.11 respectively. A significant association was found between dental caries and following variables: age group of 4-years (p-value < 0.029, RR = 1.248, 95% Bias corrected CI 0.029-0.437) and 5-years (p-value < 0.009, RR = 1.545, 95% Bias corrected CI 0.047-0.739), presence of dental plaque (p-value < 0.003, RR = 0.744, 95% Bias corrected CI (-0.433)-(-0.169)), poor oral hygiene (p-value < 0.000, RR = 0.661, 95% Bias corrected CI (-0.532)-(-0.284)), as well as consumption of non-sweetened milk (p-value < 0.049, RR = 1.232, 95% Bias corrected CI 0.061-0.367). Half of the preschoolers had dental caries coupled with a high prevalence of unmet dental treatment needs. Association between caries experience and age of child, consumption of non-sweetened milk, dental plaque and poor oral hygiene had been established.

Risk factors of pre-eclampsia/eclampsia and its adverse outcomes in low- and middle-income countries: a WHO secondary analysis.

PubMed

Bilano, Ver Luanni; Ota, Erika; Ganchimeg, Togoobaatar; Mori, Rintaro; Souza, João Paulo

2014-01-01

Pre-eclampsia has an immense adverse impact on maternal and perinatal health especially in low- and middle-income settings. We aimed to estimate the associations between pre-eclampsia/eclampsia and its risk factors, and adverse maternal and perinatal outcomes. We performed a secondary analysis of the WHO Global Survey on Maternal and Perinatal Health. The survey was a multi-country, facility-based cross-sectional study. A global sample consisting of 24 countries from three regions and 373 health facilities was obtained via a stratified multi-stage cluster sampling design. Maternal and offspring data were extracted from records using standardized questionnaires. Multi-level logistic regression modelling was conducted with random effects at the individual, facility and country levels. Data for 276,388 mothers and their infants was analysed. The prevalence of pre-eclampsia/eclampsia in the study population was 10,754 (4%). At the individual level, sociodemographic characteristics of maternal age ≥30 years and low educational attainment were significantly associated with higher risk of pre-eclampsia/eclampsia. As for clinical and obstetric variables, high body mass index (BMI), nulliparity (AOR: 2.04; 95%CI 1.92-2.16), absence of antenatal care (AOR: 1.41; 95%CI 1.26-1.57), chronic hypertension (AOR: 7.75; 95%CI 6.77-8.87), gestational diabetes (AOR: 2.00; 95%CI 1.63-2.45), cardiac or renal disease (AOR: 2.38; 95%CI 1.86-3.05), pyelonephritis or urinary tract infection (AOR: 1.13; 95%CI 1.03-1.24) and severe anemia (AOR: 2.98; 95%CI 2.47-3.61) were found to be significant risk factors, while having >8 visits of antenatal care was protective (AOR: 0.90; 95%CI 0.83-0.98). Pre-eclampsia/eclampsia was found to be a significant risk factor for maternal death, perinatal death, preterm birth and low birthweight. Chronic hypertension, obesity and severe anemia were the highest risk factors of preeclampsia/eclampsia. Implementation of effective interventions prioritizing risk factors, provision of quality health services during pre-pregnancy and during pregnancy for joint efforts in the areas of maternal health are recommended.

Simulation-based team training for multi-professional obstetric care teams to improve patient outcome: a multicentre, cluster randomised controlled trial.

PubMed

Fransen, A F; van de Ven, J; Schuit, E; van Tetering, Aac; Mol, B W; Oei, S G

2017-03-01

To investigate whether simulation-based obstetric team training in a simulation centre improves patient outcome. Multicentre, open, cluster randomised controlled trial. Obstetric units in the Netherlands. Women with a singleton pregnancy beyond 24 weeks of gestation. Random allocation of obstetric units to a 1-day, multi-professional, simulation-based team training focusing on crew resource management (CRM) in a simulation centre or to no such team training. Intention-to-treat analyses were performed at the cluster level, including a measurement 1 year prior to the intervention. Primary outcome was a composite outcome of obstetric complications during the first year post-intervention, including low Apgar score, severe postpartum haemorrhage, trauma due to shoulder dystocia, eclampsia and hypoxic-ischaemic encephalopathy. Maternal and perinatal mortality were also registered. Each study group included 12 units with a median unit size of 1224 women, combining for a total of 28 657 women. In total, 471 medical professionals received the training course. The composite outcome of obstetric complications did not differ between study groups [odds ratio (OR) 1.0, 95% confidence interval (CI) 0.80-1.3]. Team training reduced trauma due to shoulder dystocia (OR 0.50, 95% CI 0.25-0.99) and increased invasive treatment for severe postpartum haemorrhage (OR 2.2, 95% CI 1.2-3.9) compared with no intervention. Other outcomes did not differ between study groups. A 1-day, off-site, simulation-based team training, focusing on teamwork skills, did not reduce a composite of obstetric complications. 1-day, off-site, simulation-based team training did not reduce a composite of obstetric complications. © 2016 Royal College of Obstetricians and Gynaecologists.

Multiphase flow models for hydraulic fracturing technology

NASA Astrophysics Data System (ADS)

Osiptsov, Andrei A.

2017-10-01

The technology of hydraulic fracturing of a hydrocarbon-bearing formation is based on pumping a fluid with particles into a well to create fractures in porous medium. After the end of pumping, the fractures filled with closely packed proppant particles create highly conductive channels for hydrocarbon flow from far-field reservoir to the well to surface. The design of the hydraulic fracturing treatment is carried out with a simulator. Those simulators are based on mathematical models, which need to be accurate and close to physical reality. The entire process of fracture placement and flowback/cleanup can be conventionally split into the following four stages: (i) quasi-steady state effectively single-phase suspension flow down the wellbore, (ii) particle transport in an open vertical fracture, (iii) displacement of fracturing fluid by hydrocarbons from the closed fracture filled with a random close pack of proppant particles, and, finally, (iv) highly transient gas-liquid flow in a well during cleanup. The stage (i) is relatively well described by the existing hydralics models, while the models for the other three stages of the process need revisiting and considerable improvement, which was the focus of the author’s research presented in this review paper. For stage (ii), we consider the derivation of a multi-fluid model for suspension flow in a narrow vertical hydraulic fracture at moderate Re on the scale of fracture height and length and also the migration of particles across the flow on the scale of fracture width. At the stage of fracture cleanaup (iii), a novel multi-continua model for suspension filtration is developed. To provide closure relationships for permeability of proppant packings to be used in this model, a 3D direct numerical simulation of single phase flow is carried out using the lattice-Boltzmann method. For wellbore cleanup (iv), we present a combined 1D model for highly-transient gas-liquid flow based on the combination of multi-fluid and drift-flux approaches. The derivation of the drift-flux model from conservation olaws is criticall revisited in order to define the list of underlying assumptions and to mark the applicability margins of the model. All these fundamental problems share the same technological application (hydraulic fracturing) and the same method of research, namely, the multi-fluid approach to multiphase flow modeling and the consistent use of asymptotic methods. Multi-fluid models are then discussed in comparison with semi-empirical (often postulated) models widely used in the industry.

Dynamic clustering scheme based on the coordination of management and control in multi-layer and multi-region intelligent optical network

NASA Astrophysics Data System (ADS)

Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi

2011-12-01

A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

A Technique of Two-Stage Clustering Applied to Environmental and Civil Engineering and Related Methods of Citation Analysis.

ERIC Educational Resources Information Center

Miyamoto, S.; Nakayama, K.

1983-01-01

A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…

Who wins? Study of long-run trader survival in an artificial stock market

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; M. Focardi, Sergio; Marchesi, Michele; Raberto, Marco

2003-06-01

We introduce a multi-asset artificial financial market with finite amount of cash and number of stocks. The background trading is characterized by a random trading strategy constrained by the finiteness of resources and by market volatility. Stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Three active trading strategies have been introduced and studied in two different market conditions: steady market and growing market with asset inflation. We show that the profitability of each strategy depends both on the periodicity of portfolio reallocation and on the market condition. The best performing strategy is the one that exploits the mean reversion characteristic of asset price processes.

Synchronization of multi-phase oscillators: an Axelrod-inspired model

NASA Astrophysics Data System (ADS)

Kuperman, M. N.; Zanette, D. H.

2009-07-01

Inspired by Axelrod’s model of culture dissemination, we introduce and analyze a model for a population of coupled oscillators where different levels of synchronization can be assimilated to different degrees of cultural organization. The state of each oscillator is represented by a set of phases, and the interaction - which occurs between homologous phases - is weighted by a decreasing function of the distance between individual states. Both ordered arrays and random networks are considered. We find that the transition between synchronization and incoherent behaviour is mediated by a clustering regime with rich organizational structure, where any two oscillators can be synchronized in some of their phases, while their remain unsynchronized in the others.

The Boost study: design of a school- and community-based randomised trial to promote fruit and vegetable consumption among teenagers

PubMed Central

2012-01-01

Background The aim of the Boost study was to produce a persistent increase in fruit and vegetable consumption among 13-year-olds. This paper describes the development, implementation and evaluation of a school-and community-based, multi-component intervention guided by theory, evidence, and best practice. Methods/design We used the Intervention Mapping protocol to guide the development of the intervention. Programme activities combined environmental and educational strategies and focused on increasing access to fruit and vegetables in three settings: School: Daily provision of free fruit and vegetables; a pleasant eating environment; classroom curricular activities; individually computer tailored messages; one-day-workshop for teachers. Families: school meeting; guided child-parent activities; newsletters. Local community: guided visits in grocery stores and local area as part of classroom curriculum; information sheets to sports-and youth clubs. The Boost study employed a cluster-randomised controlled study design and applied simple two-stage cluster sampling: A random sample of 10 municipalities followed by a random sample of 4 schools within each municipality (N = 40 schools). Schools were randomised into a total of 20 intervention-and 20 control schools. We included all year 7 pupils except those from school classes with special needs. Timeline: Baseline survey: August 2010. Delivery of intervention: September 2010-May 2011. First follow-up survey: May/June 2011. Second follow-up survey: May/June 2012. Primary outcome measures: Daily mean intake of fruit and vegetables and habitual fruit and vegetable intake measured by validated 24-hour recall-and food frequency questionnaires. Secondary outcome measures: determinants of fruit and vegetable intake, positive side-effects and unintended adverse effects. Implementation was monitored by thorough process evaluation. Discussion The baseline data file included 2,156 adolescents (95%). There was baseline equivalence between intervention-and control groups for sociodemographics, primary outcomes, and availability at home, school and sports-and youth clubs. Significantly larger proportions of pupils in the control group had parents born in Denmark. The study will provide insights into effective strategies to increase fruit and vegetable intake among teenagers. The study will gain knowledge on implementation processes, intervention effects in population subgroups with low intake, and opportunities for including local communities in interventions. Trial registration Current Controlled Trials ISRCTN11666034. PMID:22413782

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Technical Reports Server (NTRS)

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.

Facies Modeling Using 3D Pre-Stack Simultaneous Seismic Inversion and Multi-Attribute Probability Neural Network Transform in the Wattenberg Field, Colorado

NASA Astrophysics Data System (ADS)

Harryandi, Sheila

The Niobrara/Codell unconventional tight reservoir play at Wattenberg Field, Colorado has potentially two billion barrels of oil equivalent requiring hundreds of wells to access this resource. The Reservoir Characterization Project (RCP), in conjunction with Anadarko Petroleum Corporation (APC), began reservoir characterization research to determine how to increase reservoir recovery while maximizing operational efficiency. Past research results indicate that targeting the highest rock quality within the reservoir section for hydraulic fracturing is optimal for improving horizontal well stimulation through multi-stage hydraulic fracturing. The reservoir is highly heterogeneous, consisting of alternating chalks and marls. Modeling the facies within the reservoir is very important to be able to capture the heterogeneity at the well-bore scale; this heterogeneity is then upscaled from the borehole scale to the seismic scale to distribute the heterogeneity in the inter-well space. I performed facies clustering analysis to create several facies defining the reservoir interval in the RCP Wattenberg Field study area. Each facies can be expressed in terms of a range of rock property values from wells obtained by cluster analysis. I used the facies classification from the wells to guide the pre-stack seismic inversion and multi-attribute transform. The seismic data extended the facies information and rock quality information from the wells. By obtaining this information from the 3D facies model, I generated a facies volume capturing the reservoir heterogeneity throughout a ten square mile study-area within the field area. Recommendations are made based on the facies modeling, which include the location for future hydraulic fracturing/re-fracturing treatments to improve recovery from the reservoir, and potential deeper intervals for future exploration drilling targets.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

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

PubMed

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 <12 y, HTC uptake was higher in the HB-HTC arm (87.5% versus 58.7%; aOR: 4.91; 95% CI: 2.41-10.0; p<0.001). Out of those who took up HTC, 114 (4.9%) tested HIV-positive, 39 (3.6%) in the HB-HTC arm and 75 (6.2%) in the MC-HTC arm (aOR: 0.64; 95% CI: 0.48-0.86; p = 0.002). Ten (25.6%) and 19 (25.3%) individuals 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, particularly among adolescents and young adults, and had a higher proportion of men among participants. However, after adjusting for clustering, the difference in male participation was not significant anymore. Age distribution among participants and immunological and clinical stages among persons newly diagnosed HIV-positive did not differ significantly between the two groups. Major study limitations included the campaigns' restriction to weekdays and a relatively low HIV prevalence among participants, the latter indicating that both arms may have reached an underexposed population. This study demonstrates that both HB-HTC and MC-HTC can achieve high uptake of HTC. The choice between these two community-based strategies will depend on the objective of the activity: HB-HTC was better in reaching children, individuals who had never tested before, and men, while MC-HTC detected more new HIV infections. The low rate of linkage to care after a positive HIV test warrants future consideration of combining community-based HTC approaches with strategies to improve linkage to care for persons who test HIV-positive. ClinicalTrials.gov NCT01459120. Please see later in the article for the Editors' Summary.

The Effect of Single or Repeated Home Visits on the Hanging and Use of Insecticide-Treated Mosquito Nets following a Mass Distribution Campaign - A Cluster Randomized, Controlled Trial

PubMed Central

Kilian, Albert; Balayo, Connie; Feldman, Mitra; Koenker, Hannah; Lokko, Kojo; Ashton, Ruth A.; Bruce, Jane; Lynch, Matthew; Boulay, Marc

2015-01-01

Background Study objective was to evaluate the effectiveness of commonly used post-campaign hang-up visits on the hanging and use of campaign nets. Methods A cluster-randomized trial was carried out in Uganda following an ITN distribution campaign. Five clusters (parishes, consisting of ∼11 villages each) were randomly selected for each of the three study arms with between 7,534 and 9,401 households per arm. Arm 1 received one hang-up visit, while Arm 2 received two visits by volunteers four and seven months after the campaign. Visits consisted of assistance hanging the net and education on net use. The control arm was only exposed to messages during the campaign itself. Three cross-sectional surveys with a two-stage cluster sampling design, representative of the study populations, were carried out to capture the two key outcome variables of net hanging and ITN use. Sample size was calculated to detect at least a 15 percentage-points change in net use, and was 1811 at endline. The analysis used an intention-to-treat approach. Findings Both hanging and use of ITN increased during follow-up in a similar way in all three study arms. The proportion of the population using an ITN the previous night was 64.0% (95% CI 60.8, 67.2), for one additional visit, 68.2% (63.8, 72.2) for two visits and 64.0% (59.4, 68.5) for the control. The proportion of households with all campaign nets hanging increased from 55.7% to 72.5% at endline (p<0.0005 for trend), with no difference between study arms. Financial cost per household visited was estimated as USD 2.33 for the first visit and USD 2.24 for the second. Conclusions Behavior change communication provided during the campaign or through other channels was sufficient to induce high levels of net hanging and use and additional “hang-up” activities were not cost-effective. PMID:25774676

Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

PubMed

Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long

2017-07-30

The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.

Dislocation creation and void nucleation in FCC ductile metals under tensile loading: A general microscopic picture

PubMed Central

Pang, Wei-Wei; Zhang, Ping; Zhang, Guang-Cai; Xu, Ai-Guo; Zhao, Xian-Geng

2014-01-01

Numerous theoretical and experimental efforts have been paid to describe and understand the dislocation and void nucleation processes that are fundamental for dynamic fracture modeling of strained metals. To date an essential physical picture on the self-organized atomic collective motions during dislocation creation, as well as the essential mechanisms for the void nucleation obscured by the extreme diversity in structural configurations around the void nucleation core, is still severely lacking in literature. Here, we depict the origin of dislocation creation and void nucleation during uniaxial high strain rate tensile processes in face-centered-cubic (FCC) ductile metals. We find that the dislocations are created through three distinguished stages: (i) Flattened octahedral structures (FOSs) are randomly activated by thermal fluctuations; (ii) The double-layer defect clusters are formed by self-organized stacking of FOSs on the close-packed plane; (iii) The stacking faults are formed and the Shockley partial dislocations are created from the double-layer defect clusters. Whereas, the void nucleation is shown to follow a two-stage description. We demonstrate that our findings on the origin of dislocation creation and void nucleation are universal for a variety of FCC ductile metals with low stacking fault energies. PMID:25382029

General Framework for Effect Sizes in Cluster Randomized Experiments

ERIC Educational Resources Information Center

VanHoudnos, Nathan

2016-01-01

Cluster randomized experiments are ubiquitous in modern education research. Although a variety of modeling approaches are used to analyze these data, perhaps the most common methodology is a normal mixed effects model where some effects, such as the treatment effect, are regarded as fixed, and others, such as the effect of group random assignment…

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

ERIC Educational Resources Information Center

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…

The Walking School Bus and children's physical activity: A pilot cluster randomized controlled trial

USDA-ARS?s Scientific Manuscript database

To evaluate the impact of a "walking school bus" program on children's rates of active commuting to school and physical activity. We conducted a pilot cluster randomized controlled trial among 4th-graders from 8 schools in Houston, Texas (N = 149). Random allocation to treatment or control condition...

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

Multi-stage internal gear/turbine fuel pump

DOEpatents

Maier, Eugen; Raney, Michael Raymond

2004-07-06

A multi-stage internal gear/turbine fuel pump for a vehicle includes a housing having an inlet and an outlet and a motor disposed in the housing. The multi-stage internal gear/turbine fuel pump also includes a shaft extending axially and disposed in the housing. The multi-stage internal gear/turbine fuel pump further includes a plurality of pumping modules disposed axially along the shaft. One of the pumping modules is a turbine pumping module and another of the pumping modules is a gerotor pumping module for rotation by the motor to pump fuel from the inlet to the outlet.

Merger types forming the Virgo cluster in recent gigayears

NASA Astrophysics Data System (ADS)

Olchanski, M.; Sorce, J. G.

2018-06-01

Context. As our closest cluster-neighbor, the Virgo cluster of galaxies is intensely studied by observers to unravel the mysteries of galaxy evolution within clusters. At this stage, cosmological numerical simulations of the cluster are useful to efficiently test theories and calibrate models. However, it is not trivial to select the perfect simulacrum of the Virgo cluster to fairly compare in detail its observed and simulated galaxy populations that are affected by the type and history of the cluster. Aims: Determining precisely the properties of Virgo for a later selection of simulated clusters becomes essential. It is still not clear how to access some of these properties, such as the past history of the Virgo cluster from current observations. Therefore, directly producing effective simulacra of the Virgo cluster is inevitable. Methods: Efficient simulacra of the Virgo cluster can be obtained via simulations that resemble the local Universe down to the cluster scale. In such simulations, Virgo-like halos form in the proper local environment and permit assessing the most probable formation history of the cluster. Studies based on these simulations have already revealed that the Virgo cluster has had a quiet merging history over the last seven gigayears and that the cluster accretes matter along a preferential direction. Results: This paper reveals that in addition such Virgo halos have had on average only one merger larger than about a tenth of their mass at redshift zero within the last four gigayears. This second branch (by opposition to main branch) formed in a given sub-region and merged recently (within the last gigayear). These properties are not shared with a set of random halos within the same mass range. Conclusions: This study extends the validity of the scheme used to produce the Virgo simulacra down to the largest sub-halos of the Virgo cluster. It opens up great prospects for detailed comparisons with observations, including substructures and markers of past history, to be conducted with a large sample of high resolution "Virgos" and including baryons, in the near future.

A Physical Activity Intervention for Brazilian Students From Low Human Development Index Areas: A Cluster-Randomized Controlled Trial.

PubMed

Filho, Valter C Barbosa; da Silva, Kelly Samara; Mota, Jorge; Beck, Carmem; da Silva Lopes, Adair

2016-11-01

Promoting physical activity (PA) in low- and middle-income countries is an important public health topic as well as a challenge for practice. This study aimed to assess the effect of a school-based intervention on different PA-related variables among students. This cluster-randomized-controlled trial included 548 students in the intervention group and 537 in the control group (11-18 years-old) from 6 schools in neighborhoods with low Human Development Index (0.170-0.491) in Fortaleza, Brazil. The intervention included strategies focused on training teachers, opportunities for PA in the school environment and health education. Variables measured at baseline and again at the 4-months follow-up included the weekly time in different types of moderate-to-vigorous PA (MVPA), preference for PA during leisure-time, PA behavioral change stage and active commuting to school. Generalized linear models and binary logistic regressions were used. An intervention effect was found by increasing the weekly time in MVPA (effect size = 0.17), popular games (effect size = 0.35), and the amount of PA per week (effect size = 0.27) among students (all P < .05). The intervention was effective in promoting improvements in some PA outcomes, but the changes were not sufficient to increase the proportion of those meeting PA recommendations.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Patterns of workplace supervisor support desired by abused women.

PubMed

Perrin, Nancy A; Yragui, Nanette L; Hanson, Ginger C; Glass, Nancy

2011-07-01

The purpose of this study was to understand differences in patterns of supervisor support desired by female victims of intimate partner violence (IPV) and to examine whether the pattern of support desired at work is reflective of a woman's stage of change in the abusive relationship, IPV-related work interference, and IPV-related job reprimands or job loss. We conducted interviews in Spanish or English with adult women working in low-income jobs who had been physically or sexually abused by an intimate partner/ ex-partner in the past year ( N = 133). Cluster analysis revealed three distinct clusters that form a hierarchy of type of support wanted: those who desired limited support; those who desired confidential, time-off, and emotional support; and those who desired support in wide variety of ways from their supervisor. The clusters appeared to reflect stages of behavior change in an abusive relationship. Specifically, the limited-support cluster may represent an early precontemplation stage, with women reporting the least interference with work. The support-in-every-way cluster may represent later stages of change, in which women are breaking away from the abusive partner and report the greatest interference with work. Women in the confidential-, time-off-, and emotional-support cluster are in a transition stage in which they are considering change and are exploring options in their abusive relationship. Understanding the hierarchy of the type of support desired, and its relationship to stages of change in the abusive relationship and work interference, may provide a strong foundation for developing appropriate and effective workplace interventions to guide supervisors in providing support to women experiencing IPV.

Effectiveness of multi-drug regimen chemotherapy treatment in osteosarcoma patients: a network meta-analysis of randomized controlled trials.

PubMed

Wang, Xiaojie; Zheng, Hong; Shou, Tao; Tang, Chunming; Miao, Kun; Wang, Ping

2017-03-29

Osteosarcoma is the most common malignant bone tumour. Due to the high metastasis rate and drug resistance of this disease, multi-drug regimens are necessary to control tumour cells at various stages of the cell cycle, eliminate local or distant micrometastases, and reduce the emergence of drug-resistant cells. Many adjuvant chemotherapy protocols have shown different efficacies and controversial results. Therefore, we classified the types of drugs used for adjuvant chemotherapy and evaluated the differences between single- and multi-drug chemotherapy regimens using network meta-analysis. We searched electronic databases, including PubMed (MEDLINE), EmBase, and the Cochrane Library, through November 2016 using the keywords "osteosarcoma", "osteogenic sarcoma", "chemotherapy", and "random*" without language restrictions. The major outcome in the present analysis was progression-free survival (PFS), and the secondary outcome was overall survival (OS). We used a random effect network meta-analysis for mixed multiple treatment comparisons. We included 23 articles assessing a total of 5742 patients in the present systematic review. The analysis of PFS indicated that the T12 protocol (including adriamycin, bleomycin, cyclophosphamide, dactinomycin, methotrexate, cisplatin) plays a more critical role in osteosarcoma treatment (surface under the cumulative ranking (SUCRA) probability 76.9%), with a better effect on prolonging the PFS of patients when combined with ifosfamide (94.1%) or vincristine (81.9%). For the analysis of OS, we separated the regimens to two groups, reflecting the disconnection. The T12 protocol plus vincristine (94.7%) or the removal of cisplatinum (89.4%) is most likely the best regimen. We concluded that multi-drug regimens have a better effect on prolonging the PFS and OS of osteosarcoma patients, and the T12 protocol has a better effect on prolonging the PFS of osteosarcoma patients, particularly in combination with ifosfamide or vincristine. The OS analysis showed that the T12 protocol plus vincristine or the T12 protocol with the removal of cisplatinum might be a better regimen for improving the OS of patients. However, well-designed randomized controlled trials of chemotherapeutic protocols are still necessary.

High rates of ofloxacin resistance in Mycobacterium tuberculosis among both new and previously treated patients in Tamil Nadu, South India.

PubMed

Selvakumar, N; Kumar, Vanaja; Balaji, S; Prabuseenivasan, S; Radhakrishnan, R; Sekar, Gomathi; Chandrasekaran, V; Kannan, T; Thomas, Aleyamma; Arunagiri, S; Dewan, Puneet; Swaminathan, Soumya

2015-01-01

Periodic drug resistance surveillance provides useful information on trends of drug resistance and effectiveness of tuberculosis (TB) control measures. The present study determines the prevalence of drug resistance among new sputum smear positive (NSP) and previously treated (PT) pulmonary TB patients, diagnosed at public sector designated microscopy centers (DMCs) in the state of Tamil Nadu, India. In this single-stage cluster-sampling prevalence survey, 70 of 700 DMCs were randomly selected using a probability-proportional to size method. A cluster size of 24 for NSP and a varying size of 0 to 99 for PT cases were fixed for each selected DMC. Culture and drug susceptibility testing was done on Lowenstein-Jensen medium using the economic variant of proportion sensitivity test for isoniazid (INH), rifampicin (RMP), ofloxacin (OFX) and kanamycin (KAN). Human Immunodeficiency Virus (HIV) status was collected from patient records. From June 2011 to August 2012, 1524 NSP and 901 PT patients were enrolled. Any RMP resistance and any INH resistance were observed in 2.6% and 15.1%, and in 10.4% and 30% respectively in NSP and PT cases. Among PT patients, multi drug resistant TB (MDR-TB) was highest in the treatment failure (35%) group, followed by relapse (13%) and treatment after default (10%) groups. Extensively drug resistant TB (XDRTB) was seen in 4.3% of MDR-TB cases. Any OFX resistance was seen in 10.4% of NSP, 13.9% of PT and 29% of PT MDR-TB patients. The HIV status of the patient had no impact on drug resistance levels. RMP resistance was present in 2.6% of new and 15.1% of previously treated patients in Tamil Nadu. Rates of OFX resistance were high among NSP and PT patients, especially among those with MDR-TB, a matter of concern for development of new treatment regimens for TB.

High Rates of Ofloxacin Resistance in Mycobacterium tuberculosis among Both New and Previously Treated Patients in Tamil Nadu, South India

PubMed Central

Selvakumar, N.; Kumar, Vanaja; Balaji, S.; Prabuseenivasan, S.; Radhakrishnan, R.; Sekar, Gomathi; Chandrasekaran, V.; Kannan, T.; Thomas, Aleyamma; Arunagiri, S.; Dewan, Puneet; Swaminathan, Soumya

2015-01-01

Periodic drug resistance surveillance provides useful information on trends of drug resistance and effectiveness of tuberculosis (TB) control measures. The present study determines the prevalence of drug resistance among new sputum smear positive (NSP) and previously treated (PT) pulmonary TB patients, diagnosed at public sector designated microscopy centers (DMCs) in the state of Tamil Nadu, India. In this single-stage cluster-sampling prevalence survey, 70 of 700 DMCs were randomly selected using a probability-proportional to size method. A cluster size of 24 for NSP and a varying size of 0 to 99 for PT cases were fixed for each selected DMC. Culture and drug susceptibility testing was done on Lowenstein-Jensen medium using the economic variant of proportion sensitivity test for isoniazid (INH), rifampicin (RMP), ofloxacin (OFX) and kanamycin (KAN). Human Immunodeficiency Virus (HIV) status was collected from patient records. From June 2011 to August 2012, 1524 NSP and 901 PT patients were enrolled. Any RMP resistance and any INH resistance were observed in 2.6% and 15.1%, and in 10.4% and 30% respectively in NSP and PT cases. Among PT patients, multi drug resistant TB (MDR-TB) was highest in the treatment failure (35%) group, followed by relapse (13%) and treatment after default (10%) groups. Extensively drug resistant TB (XDRTB) was seen in 4.3% of MDR-TB cases. Any OFX resistance was seen in 10.4% of NSP, 13.9% of PT and 29% of PT MDR-TB patients. The HIV status of the patient had no impact on drug resistance levels. RMP resistance was present in 2.6% of new and 15.1% of previously treated patients in Tamil Nadu. Rates of OFX resistance were high among NSP and PT patients, especially among those with MDR-TB, a matter of concern for development of new treatment regimens for TB. PMID:25738956

Hybrid analysis for indicating patients with breast cancer using temperature time series.

PubMed

Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura

2016-07-01

Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an average accuracy of 95.38% was obtained. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

Receptor clustering affects signal transduction at the membrane level in the reaction-limited regime

NASA Astrophysics Data System (ADS)

Caré, Bertrand R.; Soula, Hédi A.

2013-01-01

Many types of membrane receptors are found to be organized as clusters on the cell surface. We investigate the potential effect of such receptor clustering on the intracellular signal transduction stage. We consider a canonical pathway with a membrane receptor (R) activating a membrane-bound intracellular relay protein (G). We use Monte Carlo simulations to recreate biochemical reactions using different receptor spatial distributions and explore the dynamics of the signal transduction. Results show that activation of G by R is severely impaired by R clustering, leading to an apparent blunted biological effect compared to control. Paradoxically, this clustering decreases the half maximal effective dose (ED50) of the transduction stage, increasing the apparent affinity. We study an example of inter-receptor interaction in order to account for possible compensatory effects of clustering and observe the parameter range in which such interactions slightly counterbalance the loss of activation of G. The membrane receptors’ spatial distribution affects the internal stages of signal amplification, suggesting a functional role for membrane domains and receptor clustering independently of proximity-induced receptor-receptor interactions.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Random walk with memory enhancement and decay

NASA Astrophysics Data System (ADS)

Tan, Zhi-Jie; Zou, Xian-Wu; Huang, Sheng-You; Zhang, Wei; Jin, Zhun-Zhi

2002-04-01

A model of random walk with memory enhancement and decay was presented on the basis of the characteristics of the biological intelligent walks. In this model, the movement of the walker is determined by the difference between the remaining information at the jumping-out site and jumping-in site. The amount of the memory information si(t) at a site i is enhanced with the increment of visiting times to that site, and decays with time t by the rate e-βt, where β is the memory decay exponent. When β=0, there exists a transition from Brownian motion (BM) to the compact growth of walking trajectory with the density of information energy u increasing. But for β>0, this transition does not appear and the walk with memory enhancement and decay can be considered as the BM of the mass center of the cluster composed of remembered sites in the late stage.

Simultaneous gains tuning in boiler/turbine PID-based controller clusters using iterative feedback tuning methodology.

PubMed

Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan

2012-09-01

Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-cellular natural killer (NK) cell clusters enhance NK cell activation through localizing IL-2 within the cluster

NASA Astrophysics Data System (ADS)

Kim, Miju; Kim, Tae-Jin; Kim, Hye Mi; Doh, Junsang; Lee, Kyung-Mi

2017-01-01

Multi-cellular cluster formation of natural killer (NK) cells occurs during in vivo priming and potentiates their activation to IL-2. However, the precise mechanism underlying this synergy within NK cell clusters remains unclear. We employed lymphocyte-laden microwell technologies to modulate contact-mediated multi-cellular interactions among activating NK cells and to quantitatively assess the molecular events occurring in multi-cellular clusters of NK cells. NK cells in social microwells, which allow cell-to-cell contact, exhibited significantly higher levels of IL-2 receptor (IL-2R) signaling compared with those in lonesome microwells, which prevent intercellular contact. Further, CD25, an IL-2R α chain, and lytic granules of NK cells in social microwells were polarized toward MTOC. Live cell imaging of lytic granules revealed their dynamic and prolonged polarization toward neighboring NK cells without degranulation. These results suggest that IL-2 bound on CD25 of one NK cells triggered IL-2 signaling of neighboring NK cells. These results were further corroborated by findings that CD25-KO NK cells exhibited lower proliferation than WT NK cells, and when mixed with WT NK cells, underwent significantly higher level of proliferation. These data highlights the existence of IL-2 trans-presentation between NK cells in the local microenvironment where the availability of IL-2 is limited.

State fusion entropy for continuous and site-specific analysis of landslide stability changing regularities

NASA Astrophysics Data System (ADS)

Liu, Yong; Qin, Zhimeng; Hu, Baodan; Feng, Shuai

2018-04-01

Stability analysis is of great significance to landslide hazard prevention, especially the dynamic stability. However, many existing stability analysis methods are difficult to analyse the continuous landslide stability and its changing regularities in a uniform criterion due to the unique landslide geological conditions. Based on the relationship between displacement monitoring data, deformation states and landslide stability, a state fusion entropy method is herein proposed to derive landslide instability through a comprehensive multi-attribute entropy analysis of deformation states, which are defined by a proposed joint clustering method combining K-means and a cloud model. Taking Xintan landslide as the detailed case study, cumulative state fusion entropy presents an obvious increasing trend after the landslide entered accelerative deformation stage and historical maxima match highly with landslide macroscopic deformation behaviours in key time nodes. Reasonable results are also obtained in its application to several other landslides in the Three Gorges Reservoir in China. Combined with field survey, state fusion entropy may serve for assessing landslide stability and judging landslide evolutionary stages.

Comparison of media literacy and usual education to prevent tobacco use: a cluster randomized trial

PubMed Central

Douglas, Erika L.; Land, Stephanie R.; Miller, Elizabeth; Fine, Michael J.

2014-01-01

BACKGROUND Media literacy programs have shown potential for reduction of adolescent tobacco use. We aimed to determine if an anti-smoking media literacy curriculum improves students’ media literacy and affects factors related to adolescent smoking. METHODS We recruited 1170 9th grade students from 64 classrooms in 3 public urban high schools. Students were randomized by classroom to a media literacy curriculum versus a standard educational program. In an intent-to-treat analysis, we used multi-level modeling to determine if changes in study outcomes were associated with the curricular intervention, controlling for baseline student covariates and the clustering of students within classrooms. RESULTS Among participants, mean age was 14.5 years and 51% were male, with no significant differences in baseline characteristics between groups. Smoking media literacy changed more among intervention participants compared with control participants (0.24 vs. 0.08, p < .001). Compared with controls, intervention students exhibited a greater reduction in the perceived prevalence of smoking (−14.0% vs. −4.6%, p < .001). Among those initially susceptible to smoking, intervention participants more commonly reverted to being non-susceptible post-intervention (24% vs. 16%, p = .08). CONCLUSIONS A school-based media literacy curriculum is more effective than a standard educational program in teaching media literacy and improving perceptions of the true prevalence of smoking among adolescents. PMID:25099425

Determining the Number of Clusters in a Data Set Without Graphical Interpretation

NASA Technical Reports Server (NTRS)

Aguirre, Nathan S.; Davies, Misty D.

2011-01-01

Cluster analysis is a data mining technique that is meant ot simplify the process of classifying data points. The basic clustering process requires an input of data points and the number of clusters wanted. The clustering algorithm will then pick starting C points for the clusters, which can be either random spatial points or random data points. It then assigns each data point to the nearest C point where "nearest usually means Euclidean distance, but some algorithms use another criterion. The next step is determining whether the clustering arrangement this found is within a certain tolerance. If it falls within this tolerance, the process ends. Otherwise the C points are adjusted based on how many data points are in each cluster, and the steps repeat until the algorithm converges,

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

ERIC Educational Resources Information Center

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)…

Integrated cluster- and case-based surveillance for detecting stage III zoonotic pathogens: an example of Nipah virus surveillance in Bangladesh.

PubMed

Naser, A M; Hossain, M J; Sazzad, H M S; Homaira, N; Gurley, E S; Podder, G; Afroj, S; Banu, S; Rollin, P E; Daszak, P; Ahmed, B-N; Rahman, M; Luby, S P

2015-07-01

This paper explores the utility of cluster- and case-based surveillance established in government hospitals in Bangladesh to detect Nipah virus, a stage III zoonotic pathogen. Physicians listed meningo-encephalitis cases in the 10 surveillance hospitals and identified a cluster when ⩾2 cases who lived within 30 min walking distance of one another developed symptoms within 3 weeks of each other. Physicians collected blood samples from the clustered cases. As part of case-based surveillance, blood was collected from all listed meningo-encephalitis cases in three hospitals during the Nipah season (January-March). An investigation team visited clustered cases' communities to collect epidemiological information and blood from the living cases. We tested serum using Nipah-specific IgM ELISA. Up to September 2011, in 5887 listed cases, we identified 62 clusters comprising 176 encephalitis cases. We collected blood from 127 of these cases. In 10 clusters, we identified a total of 62 Nipah cases: 18 laboratory-confirmed and 34 probable. We identified person-to-person transmission of Nipah virus in four clusters. From case-based surveillance, we identified 23 (4%) Nipah cases. Faced with thousands of encephalitis cases, integrated cluster surveillance allows targeted deployment of investigative resources to detect outbreaks by stage III zoonotic pathogens in resource-limited settings.

Defining and managing career challenges for mid-career and senior stage pediatric hematologist/oncologists.

PubMed

Frugé, Ernest; Margolin, Judith; Horton, Terzah; Venkateswaran, Lakshmi; Lee, Dean; Yee, Donald L; Mahoney, Donald

2010-12-01

A workshop at the 2008 ASPHO Annual Meeting functioned as the first step in a systematic needs assessment of the particular challenges to satisfaction and success in the middle and senior phases of career development for pediatric hematologist/oncologists (PHOs). The 61 ASPHO members who attended were randomly distributed to small discussion groups based on self-identified career stage. Groups completed challenge forms for each issue identified as pertinent to their own stage of professional development. A total of 71 forms with useable data were generated by the groups. The largest number of challenges described (26) clustered around themes of Work-Life Balance followed by Transition and Succession (18), Management and Finances (15), and Keeping up to Date (13). Mid-career groups were more likely to identify Work-Life Balance challenges while senior stage groups were more likely to articulate Succession and Management challenges. The article describes the demographics of the workshop participants, summarizes the content of challenge themes and the associated suggestions for management. It is hoped that this effort will assist educational and career planning efforts by individuals, institutions, and ASPHO as a professional society.

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

PubMed Central

2012-01-01

Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154

Leveraging contact network structure in the design of cluster randomized trials.

PubMed

Harling, Guy; Wang, Rui; Onnela, Jukka-Pekka; De Gruttola, Victor

2017-02-01

In settings like the Ebola epidemic, where proof-of-principle trials have provided evidence of efficacy but questions remain about the effectiveness of different possible modes of implementation, it may be useful to conduct trials that not only generate information about intervention effects but also themselves provide public health benefit. Cluster randomized trials are of particular value for infectious disease prevention research by virtue of their ability to capture both direct and indirect effects of intervention, the latter of which depends heavily on the nature of contact networks within and across clusters. By leveraging information about these networks-in particular the degree of connection across randomized units, which can be obtained at study baseline-we propose a novel class of connectivity-informed cluster trial designs that aim both to improve public health impact (speed of epidemic control) and to preserve the ability to detect intervention effects. We several designs for cluster randomized trials with staggered enrollment, in each of which the order of enrollment is based on the total number of ties (contacts) from individuals within a cluster to individuals in other clusters. Our designs can accommodate connectivity based either on the total number of external connections at baseline or on connections only to areas yet to receive the intervention. We further consider a "holdback" version of the designs in which control clusters are held back from re-randomization for some time interval. We investigate the performance of these designs in terms of epidemic control outcomes (time to end of epidemic and cumulative incidence) and power to detect intervention effect, by simulating vaccination trials during an SEIR-type epidemic outbreak using a network-structured agent-based model. We compare results to those of a traditional Stepped Wedge trial. In our simulation studies, connectivity-informed designs lead to a 20% reduction in cumulative incidence compared to comparable traditional study designs, but have little impact on epidemic length. Power to detect intervention effect is reduced in all connectivity-informed designs, but "holdback" versions provide power that is very close to that of a traditional Stepped Wedge approach. Incorporating information about cluster connectivity in the design of cluster randomized trials can increase their public health impact, especially in acute outbreak settings. Using this information helps control outbreaks-by minimizing the number of cross-cluster infections-with very modest cost in terms of power to detect effectiveness.

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with traditional spectral clustering and fast affinity propagation clustering. Experimental results have illustrated its superior performance in terms of quantitative and qualitative evaluations. PMID:28777353

Star Formation History In Merging Galaxies

NASA Astrophysics Data System (ADS)

Chien, Li-Hsin

2009-01-01

Interacting and merging galaxies are believed to play an important role in many aspects of galactic evolution. Their violent interactions can trigger starbursts, which lead to formation of young globular clusters. Therefore the ages of these young globular clusters can be interpreted to yield the timing of interaction-triggered events, and thus provide a key to reconstruct the star formation history in merging galaxies. The link between galaxy interaction and star formation is well established, but the triggers of star formation in interacting galaxies are still not understood. To date there are two competing formulas that describe the star formation mechanism--density-dependent and shock-induced rules. Numerical models implementing the two rules predict significantly different star formation histories in merging galaxies. My dissertation combines these two distinct areas of astrophysics, stellar evolution and galactic dynamics, to investigate the star formation history in galaxies at various merging stages. Begin with NGC 4676 as an example, I will briefly describe its model and illustrate the idea of using the ages of clusters to constrain the modeling. The ages of the clusters are derived from spectra that were taken with multi-object spectroscopy on Keck. Using NGC 7252 as a second example, I will present a state of the art dynamical model which predicts NGC7252's star formation history and other properties. I will then show a detailed comparison and analysis between the clusters and the modeling. In the end, I will address this important link as the key to answer the fundamental question of my thesis: what is the trigger of star formation in merging galaxies?

Two-year effects of a school-based prevention programme on adolescent cigarette smoking in Guangzhou, China: a cluster randomized trial

PubMed Central

Wen, Xiaozhong; Chen, Weiqing; Gans, Kim M; Colby, Suzanne M; Lu, Ciyong; Liang, Caihua; Ling, Wenhua

2010-01-01

Background The prevalence of adolescent smoking has been increasing rapidly in China. Theory-based smoking prevention programmes in schools may be an effective approach in preventing smoking among Chinese adolescents. Methods A school-level cluster randomized controlled trial was conducted among 7th and 8th grade students (N = 2343) in four junior high schools in southern China during 2004–06. The theory-based, multi-level intervention was compared with the standard health curriculum. Outcome measures comprised changes in students’ smoking-related knowledge, attitudes and behaviour. Results The mean knowledge scores from baseline to the 1- and 2-year follow-ups increased more in the intervention group than in the control group, whereas there was little change in attitude scores. At the 1-year follow-up (the total sample), the interventions reduced the probability of baseline experimental smokers’ escalating to regular smoker [7.9 vs 18.3%; adjusted odds ratio (OR) 0.34, 95% confidence interval (CI) 0.12–0.97, P = 0.043], but did not reduce the probability of baseline non-smokers’ initiating smoking (7.9 vs 10.6%; adjusted OR 0.86, 95% CI 0.54–1.38, P = 0.538). At the 2-year follow-up (only 7th grade students), similar proportions of baseline non-smokers initiated smoking in the intervention group and the control group (13.5 vs 13.1%), while a possibly lower proportion of baseline experimental smokers escalated to regular smoking in the intervention group than the control group (22.6 vs 40.0%; adjusted OR 0.43, 95% CI 0.12–1.57, P = 0.199). Conclusions This multi-level intervention programme had a moderate effect on inhibiting the escalation from experimental to regular smoking among Chinese adolescents, but had little effect on the initiation of smoking. The programme improved adolescents’ smoking-related knowledge, but did not change their attitudes towards smoking. PMID:20236984

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Palamuttam, R. S.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; Verma, R.; Waliser, D. E.; Lee, H.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark under a NASA AIST grant (PI Mattmann). Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based ApacheTM Hadoop by 100x in memory and by 10x on disk. SciSpark will enable scalable model evaluation by executing large-scale comparisons of A-Train satellite observations to model grids on a cluster of 10 to 1000 compute nodes. This 2nd generation capability for NASA's Regional Climate Model Evaluation System (RCMES) will compute simple climate metrics at interactive speeds, and extend to quite sophisticated iterative algorithms such as machine-learning based clustering of temperature PDFs, and even graph-based algorithms for searching for Mesocale Convective Complexes. We have implemented a parallel data ingest capability in which the user specifies desired variables (arrays) as several time-sorted lists of URL's (i.e. using OPeNDAP model.nc?varname, or local files). The specified variables are partitioned by time/space and then each Spark node pulls its bundle of arrays into memory to begin a computation pipeline. We also investigated the performance of several N-dim. array libraries (scala breeze, java jblas & netlib-java, and ND4J). We are currently developing science codes using ND4J and studying memory behavior on the JVM. On the pyspark side, many of our science codes already use the numpy and SciPy ecosystems. The talk will cover: the architecture of SciSpark, the design of the scientific RDD (sRDD) data structure, our efforts to integrate climate science algorithms in Python and Scala, parallel ingest and partitioning of A-Train satellite observations from HDF files and model grids from netCDF files, first parallel runs to compute comparison statistics and PDF's, and first metrics quantifying parallel speedups and memory & disk usage.

Stochastic summation of empirical Green's functions

USGS Publications Warehouse

Wennerberg, Leif

1990-01-01

Two simple strategies are presented that use random delay times for repeatedly summing the record of a relatively small earthquake to simulate the effects of a larger earthquake. The simulations do not assume any fault plane geometry or rupture dynamics, but realy only on the ω−2 spectral model of an earthquake source and elementary notions of source complexity. The strategies simulate ground motions for all frequencies within the bandwidth of the record of the event used as a summand. The first strategy, which introduces the basic ideas, is a single-stage procedure that consists of simply adding many small events with random time delays. The probability distribution for delays has the property that its amplitude spectrum is determined by the ratio of ω−2 spectra, and its phase spectrum is identically zero. A simple expression is given for the computation of this zero-phase scaling distribution. The moment rate function resulting from the single-stage simulation is quite simple and hence is probably not realistic for high-frequency (>1 Hz) ground motion of events larger than ML∼ 4.5 to 5. The second strategy is a two-stage summation that simulates source complexity with a few random subevent delays determined using the zero-phase scaling distribution, and then clusters energy around these delays to get an ω−2 spectrum for the sum. Thus, the two-stage strategy allows simulations of complex events of any size for which the ω−2 spectral model applies. Interestingly, a single-stage simulation with too few ω−2records to get a good fit to an ω−2 large-event target spectrum yields a record whose spectral asymptotes are consistent with the ω−2 model, but that includes a region in its spectrum between the corner frequencies of the larger and smaller events reasonably approximated by a power law trend. This spectral feature has also been discussed as reflecting the process of partial stress release (Brune, 1970), an asperity failure (Boatwright, 1984), or the breakdown of ω−2 scaling due to rupture significantly longer than the width of the seismogenic zone (Joyner, 1984).

Comparison between single-diode low-level laser therapy (LLLT) and LED multi-diode (cluster) therapy (LEDT) applications before high-intensity exercise.

PubMed

Leal Junior, Ernesto Cesar Pinto; Lopes-Martins, Rodrigo Alvaro Brandão; Baroni, Bruno Manfredini; De Marchi, Thiago; Rossi, Rafael Paolo; Grosselli, Douglas; Generosi, Rafael Abeche; de Godoi, Vanessa; Basso, Maira; Mancalossi, José Luis; Bjordal, Jan Magnus

2009-08-01

There is anecdotal evidence that low-level laser therapy (LLLT) may affect the development of muscular fatigue, minor muscle damage, and recovery after heavy exercises. Although manufacturers claim that cluster probes (LEDT) maybe more effective than single-diode lasers in clinical settings, there is a lack of head-to-head comparisons in controlled trials. This study was designed to compare the effect of single-diode LLLT and cluster LEDT before heavy exercise. This was a randomized, placebo-controlled, double-blind cross-over study. Young male volleyball players (n = 8) were enrolled and asked to perform three Wingate cycle tests after 4 x 30 sec LLLT or LEDT pretreatment of the rectus femoris muscle with either (1) an active LEDT cluster-probe (660/850 nm, 10/30 mW), (2) a placebo cluster-probe with no output, and (3) a single-diode 810-nm 200-mW laser. The active LEDT group had significantly decreased post-exercise creatine kinase (CK) levels (-18.88 +/- 41.48 U/L), compared to the placebo cluster group (26.88 +/- 15.18 U/L) (p < 0.05) and the active single-diode laser group (43.38 +/- 32.90 U/L) (p < 0.01). None of the pre-exercise LLLT or LEDT protocols enhanced performance on the Wingate tests or reduced post-exercise blood lactate levels. However, a non-significant tendency toward lower post-exercise blood lactate levels in the treated groups should be explored further. In this experimental set-up, only the active LEDT probe decreased post-exercise CK levels after the Wingate cycle test. Neither performance nor blood lactate levels were significantly affected by this protocol of pre-exercise LEDT or LLLT.

Clustering and Phase Transitions on a Neutral Landscape

NASA Astrophysics Data System (ADS)

Scott, Adam; King, Dawn; Maric, Nevena; Bahar, Sonya

2012-02-01

The problem of speciation and species aggregation on a neutral landscape, subject to random mutational fluctuations rather than selective drive, has been a focus of research since the seminal work of Kimura on genetic drift. These ideas have received increased attention due to the more recent development of a neutral ecological theory by Hubbell. De Aguiar et al. recently demonstrated, in a computational model, that speciation can occur under neutral conditions; this study bears some comparison with more mathematical studies of clustering on neutral landscapes in the context of branching and annihilating random walks. Here, we show that clustering can occur on a neutral landscape where the dimensions specify the simulated organisms' phenotypes. Unlike the De Aguiar et al. model, we simulate sympatric speciation: the organisms cluster phenotypically, but are not spatially separated. Moreover, we find that clustering occurs not only in the case of assortative mating, but also in the case of asexual fission. Clustering is not observed in a control case where organisms can mate randomly. We find that the population size and the number of clusters undergo phase-transition-like behavior as the maximum mutation size is varied.

High Performance Computing of Meshless Time Domain Method on Multi-GPU Cluster

NASA Astrophysics Data System (ADS)

Ikuno, Soichiro; Nakata, Susumu; Hirokawa, Yuta; Itoh, Taku

2015-01-01

High performance computing of Meshless Time Domain Method (MTDM) on multi-GPU using the supercomputer HA-PACS (Highly Accelerated Parallel Advanced system for Computational Sciences) at University of Tsukuba is investigated. Generally, the finite difference time domain (FDTD) method is adopted for the numerical simulation of the electromagnetic wave propagation phenomena. However, the numerical domain must be divided into rectangle meshes, and it is difficult to adopt the problem in a complexed domain to the method. On the other hand, MTDM can be easily adept to the problem because MTDM does not requires meshes. In the present study, we implement MTDM on multi-GPU cluster to speedup the method, and numerically investigate the performance of the method on multi-GPU cluster. To reduce the computation time, the communication time between the decomposed domain is hided below the perfect matched layer (PML) calculation procedure. The results of computation show that speedup of MTDM on 128 GPUs is 173 times faster than that of single CPU calculation.

Perception on the abortion laws in Sri Lanka: A community based study in the city of Colombo

PubMed

Suranga, M S; Silva, K T; Senanayake, L

2016-12-30

Abortion is legally permitted in Sri Lanka, only if it is performed to save the mother’s life. However, it is estimated that a large number of induced abortions take place in Sri Lanka. Knowledge and attitudes towards induced abortion in the society are key issues influencing the policy response towards changes in the law. This study aimed to assess the knowledge and attitudes of adults towards induced abortion in Sri Lanka. Six Grama Niladhari Divisions (GNDs) and five to eight housing clusters from each GND were selected from Thimbirigasyaya Divisional Secretariat Division using multi stage stratified random sampling. Fifty households were systematically selected from each GND. An interview was scheduled among 743 residents aged between 19 to 49 years of age after receiving written informed consent. Only 11% of the respondents knew the situations in which abortion was legal in Sri Lanka. Approximately one tenth of the respondents (11%) did not agree with the current law which allows an induced abortion only to save the life of the mother. However, a majority agreed to legalization of abortion for rape (65%), incest (55%) and pregnancies with lethal fetal abnormalities (53%). Less than one tenth of respondents agreed with legalisation of induced abortion for other reasons such as con-traceptive failure (6%), poor economic conditions (7%) and, on request (4%). Although the society rejects abortion on request majority are in favour of allowing abortions for rape, incest and fetuses with lethal abnormalities.

Visual difficulty and employment status in the world.

PubMed

Harrabi, Hanen; Aubin, Marie-Josee; Zunzunegui, Maria Victoria; Haddad, Slim; Freeman, Ellen E

2014-01-01

Using a world-wide, population-based dataset, we sought to examine the relationship between visual difficulty and employment status. The World Health Survey was conducted in 70 countries throughout the world in 2003 using a random, multi-stage, stratified, cluster sampling design. Far vision was assessed by asking about the level of difficulty in seeing and recognizing a person you know across the road (i.e. from a distance of about 20 meters). Responses included none, mild, moderate, severe, or extreme/unable. Participants were asked about their current job, and if they were not working, the reason why (unable to find job, ill health, homemaker, studies, unpaid work, other). The occupation in the last 12 months was obtained. Multinomial regression was used accounting for the complex survey design. Of those who wanted to work, 79% of those with severe visual difficulty and 64% of those with extreme visual difficulty were actually working. People who had moderate, severe, or extreme visual difficulty had a higher odds of not working due to an inability to find a job and of not working due to ill health after adjusting for demographic and health factors (P<0.05). As the major causes of visual impairment in the world are uncorrected refractive error and cataract, countries are losing a great deal of labor productivity by failing to provide for the vision health needs of their citizens and failing to help them integrate into the workforce.

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer

NASA Astrophysics Data System (ADS)

Moazami Goodarzi, Hamed; Kazemi, Mohammad Hosein

2018-05-01

Microgrid (MG) clustering is regarded as an important driver in improving the robustness of MGs. However, little research has been conducted on providing appropriate MG clustering. This article addresses this shortfall. It proposes a novel multi-objective optimization approach for finding optimal clustering of autonomous MGs by focusing on variables such as distributed generation (DG) droop parameters, the location and capacity of DG units, renewable energy sources, capacitors and powerline transmission. Power losses are minimized and voltage stability is improved while virtual cut-set lines with minimum power transmission for clustering MGs are obtained. A novel chaotic grey wolf optimizer (CGWO) algorithm is applied to solve the proposed multi-objective problem. The performance of the approach is evaluated by utilizing a 69-bus MG in several scenarios.

Westerlund 1: monolithic formation of a starburst cluster

NASA Astrophysics Data System (ADS)

Negueruela, Ignacio; Clark, J. Simon; Ritchie, Ben W.; Goodwin, Simon P.

2017-03-01

Westerlund 1 is in all likelihood the most massive young cluster in the Milky Way, with a mass on the order of 105 M ⊙. To determine its bulk properties we have made multi-epoch radial velocity measurements for a substantial fraction of its OB stars and evolved supergiants and obtained multi-object spectroscopy of candidate cluster members in its locale. The results of these two studies show that Westerlund 1 is apparently subvirial and appears completely isolated, with hardly any massive star in its vicinity that could be associated with it in terms of distance modulus or radial velocity. The cluster halo does not extend much further than five parsec away from the centre. All these properties are very unusual among starburst clusters in the Local Universe, which tend to form in the context of large star-forming regions.

Configuration of management accounting information system for multi-stage manufacturing

NASA Astrophysics Data System (ADS)

Mkrtychev, S. V.; Ochepovsky, A. V.; Enik, O. A.

2018-05-01

The article presents an approach to configuration of a management accounting information system (MAIS) that provides automated calculations and the registration of normative production losses in multi-stage manufacturing. The use of MAIS with the proposed configuration at the enterprises of textile and woodworking industries made it possible to increase the accuracy of calculations for normative production losses and to organize accounting thereof with the reference to individual stages of the technological process. Thus, high efficiency of multi-stage manufacturing control is achieved.

Efficacy of a Multi-Component Intervention to Reduce Workplace Sitting Time in Office Workers: A Cluster Randomized Controlled Trial.

PubMed

Maylor, Benjamin D; Edwardson, Charlotte L; Zakrzewski-Fruer, Julia K; Champion, Rachael B; Bailey, Daniel P

2018-05-30

The aim of this study was to investigate the efficacy of a work-based multicomponent intervention to reduce office workers' sitting time. Offices (n = 12; 89 workers) were randomized into an 8-week intervention (n = 48) incorporating organizational, individual, and environmental elements or control arm. Sitting time, physical activity, and cardiometabolic health were measured at baseline and after the intervention. Linear mixed modelling revealed no significant change in workplace sitting time, but changes in workplace prolonged sitting time (-39 min/shift), sit-upright transitions (7.8 per shift), and stepping time (12 min/shift) at follow-up were observed, in favor of the intervention group (P < 0.001). Results for cardiometabolic health markers were mixed. This short multicomponent workplace intervention was successful in reducing prolonged sitting and increasing physical activity in the workplace, although total sitting time was not reduced and the impact on cardiometabolic health was minimal.

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

PubMed Central

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

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

Feasibility of feature-based indexing, clustering, and search of clinical trials: A case study of breast cancer trials from ClinicalTrials.gov

PubMed Central

Boland, Mary Regina; Miotto, Riccardo; Gao, Junfeng; Weng, Chunhua

2013-01-01

Summary Background When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. Objectives This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. Methods We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. Results We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. Conclusions It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency. PMID:23666475

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov.

PubMed

Boland, M R; Miotto, R; Gao, J; Weng, C

2013-01-01

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

Sequential time interleaved random equivalent sampling for repetitive signal.

PubMed

Zhao, Yijiu; Liu, Jingjing

2016-12-01

Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.