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Sample records for hierarchical regressions showed

  1. Hierarchical Neural Regression Models for Customer Churn Prediction

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    Golshan Mohammadi

    2013-01-01

    Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

  2. Hierarchical regression analysis in structural Equation Modeling

    NARCIS (Netherlands)

    de Jong, P.F.

    1999-01-01

    In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main

  3. Entrepreneurial intention modeling using hierarchical multiple regression

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    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  4. Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

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    Choi, Kilchan

    2011-01-01

    This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

  5. Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

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    Guo Junqiao

    2008-09-01

    Full Text Available Abstract Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations.

  6. A Logistic Regression Model with a Hierarchical Random Error Term for Analyzing the Utilization of Public Transport

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    Chong Wei

    2015-01-01

    Full Text Available Logistic regression models have been widely used in previous studies to analyze public transport utilization. These studies have shown travel time to be an indispensable variable for such analysis and usually consider it to be a deterministic variable. This formulation does not allow us to capture travelers’ perception error regarding travel time, and recent studies have indicated that this error can have a significant effect on modal choice behavior. In this study, we propose a logistic regression model with a hierarchical random error term. The proposed model adds a new random error term for the travel time variable. This term structure enables us to investigate travelers’ perception error regarding travel time from a given choice behavior dataset. We also propose an extended model that allows constraining the sign of this error in the model. We develop two Gibbs samplers to estimate the basic hierarchical model and the extended model. The performance of the proposed models is examined using a well-known dataset.

  7. Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

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    Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

    2018-05-10

    Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

  8. Analyzing thresholds and efficiency with hierarchical Bayesian logistic regression.

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    Houpt, Joseph W; Bittner, Jennifer L

    2018-05-10

    Ideal observer analysis is a fundamental tool used widely in vision science for analyzing the efficiency with which a cognitive or perceptual system uses available information. The performance of an ideal observer provides a formal measure of the amount of information in a given experiment. The ratio of human to ideal performance is then used to compute efficiency, a construct that can be directly compared across experimental conditions while controlling for the differences due to the stimuli and/or task specific demands. In previous research using ideal observer analysis, the effects of varying experimental conditions on efficiency have been tested using ANOVAs and pairwise comparisons. In this work, we present a model that combines Bayesian estimates of psychometric functions with hierarchical logistic regression for inference about both unadjusted human performance metrics and efficiencies. Our approach improves upon the existing methods by constraining the statistical analysis using a standard model connecting stimulus intensity to human observer accuracy and by accounting for variability in the estimates of human and ideal observer performance scores. This allows for both individual and group level inferences. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR is an efficient tool for metamodelling of nonlinear dynamic models

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    Omholt Stig W

    2011-06-01

    Full Text Available Abstract Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs to variation in features of the trajectories of the state variables (outputs throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR, where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR and ordinary least squares (OLS regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback

  10. Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

    Science.gov (United States)

    Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

    2011-06-01

    Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for

  11. Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data.

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    Wilderjans, Tom Frans; Vande Gaer, Eva; Kiers, Henk A L; Van Mechelen, Iven; Ceulemans, Eva

    2017-03-01

    In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three reasons: first, multiple highly collinear predictors can be available, making it difficult to grasp their mutual relations as well as their relations to the criterion. In that case, it may be very useful to reduce the predictors to a few summary variables, on which one regresses the criterion and which at the same time yields insight into the predictor structure. Second, the population under study may consist of a few unknown subgroups that are characterized by different regression models. Third, the obtained data are often hierarchically structured, with for instance, observations being nested into persons or participants within groups or countries. Although some methods have been developed that partially meet these challenges (i.e., principal covariates regression (PCovR), clusterwise regression (CR), and structural equation models), none of these methods adequately deals with all of them simultaneously. To fill this gap, we propose the principal covariates clusterwise regression (PCCR) method, which combines the key idea's behind PCovR (de Jong & Kiers in Chemom Intell Lab Syst 14(1-3):155-164, 1992) and CR (Späth in Computing 22(4):367-373, 1979). The PCCR method is validated by means of a simulation study and by applying it to cross-cultural data regarding satisfaction with life.

  12. Should metacognition be measured by logistic regression?

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    Rausch, Manuel; Zehetleitner, Michael

    2017-03-01

    Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Predictive Ability of Pender's Health Promotion Model for Physical Activity and Exercise in People with Spinal Cord Injuries: A Hierarchical Regression Analysis

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    Keegan, John P.; Chan, Fong; Ditchman, Nicole; Chiu, Chung-Yi

    2012-01-01

    The main objective of this study was to validate Pender's Health Promotion Model (HPM) as a motivational model for exercise/physical activity self-management for people with spinal cord injuries (SCIs). Quantitative descriptive research design using hierarchical regression analysis (HRA) was used. A total of 126 individuals with SCI were recruited…

  14. Stepwise versus Hierarchical Regression: Pros and Cons

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    Lewis, Mitzi

    2007-01-01

    Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

  15. Regressão múltipla stepwise e hierárquica em Psicologia Organizacional: aplicações, problemas e soluções Stepwise and hierarchical multiple regression in organizational psychology: Applications, problemas and solutions

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    Gardênia Abbad

    2002-01-01

    Full Text Available Este artigo discute algumas aplicações das técnicas de análise de regressão múltipla stepwise e hierárquica, as quais são muito utilizadas em pesquisas da área de Psicologia Organizacional. São discutidas algumas estratégias de identificação e de solução de problemas relativos à ocorrência de erros do Tipo I e II e aos fenômenos de supressão, complementaridade e redundância nas equações de regressão múltipla. São apresentados alguns exemplos de pesquisas nas quais esses padrões de associação entre variáveis estiveram presentes e descritas as estratégias utilizadas pelos pesquisadores para interpretá-los. São discutidas as aplicações dessas análises no estudo de interação entre variáveis e na realização de testes para avaliação da linearidade do relacionamento entre variáveis. Finalmente, são apresentadas sugestões para lidar com as limitações das análises de regressão múltipla (stepwise e hierárquica.This article discusses applications of stepwise and hierarchical multiple regression analyses to research in organizational psychology. Strategies for identifying type I and II errors, and solutions to potential problems that may arise from such errors are proposed. In addition, phenomena such as suppression, complementarity, and redundancy are reviewed. The article presents examples of research where these phenomena occurred, and the manner in which they were explained by researchers. Some applications of multiple regression analyses to studies involving between-variable interactions are presented, along with tests used to analyze the presence of linearity among variables. Finally, some suggestions are provided for dealing with limitations implicit in multiple regression analyses (stepwise and hierarchical.

  16. What are hierarchical models and how do we analyze them?

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    Royle, Andy

    2016-01-01

    In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

  17. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  18. Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

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    Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

    2010-01-01

    Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization

  19. Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets.

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    Woosang Lim

    Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.

  20. Leadership styles across hierarchical levels in nursing departments.

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    Stordeur, S; Vandenberghe, C; D'hoore, W

    2000-01-01

    Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.

  1. Scale of association: hierarchical linear models and the measurement of ecological systems

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    Sean M. McMahon; Jeffrey M. Diez

    2007-01-01

    A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...

  2. Hierarchical Matching and Regression with Application to Photometric Redshift Estimation

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    Murtagh, Fionn

    2017-06-01

    This work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is motivated by the variety of cosmological objects such as elliptical, spiral, active, and merging galaxies at a wide range of redshifts. Our aim is matching and similarity-based analytics that takes account of discrete relationships in the data. The information structure of the data is represented by a hierarchy or tree where the branch structure, rather than just the proximity, is important. The representation is related to p-adic number theory. The clustering or binning of the data values, related to the precision of the measurements, has a central role in this methodology. If used for regression, our approach is a method of cluster-wise regression, generalizing nearest neighbour regression. Both to exemplify this analytics approach, and to demonstrate computational benefits, we address the well-known photometric redshift or `photo-z' problem, seeking to match Sloan Digital Sky Survey (SDSS) spectroscopic and photometric redshifts.

  3. Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

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    Calder, Eliza; Ogburn, Sarah; Spiller, Elaine; Rutarindwa, Regis; Berger, Jim

    2015-04-01

    In this work we present a method to constrain flow mobility input parameters for pyroclastic flow models using hierarchical Bayes modeling of standard mobility metrics such as H/L and flow volume etc. The advantage of hierarchical modeling is that it can leverage the information in global dataset for a particular mobility metric in order to reduce the uncertainty in modeling of an individual volcano, especially important where individual volcanoes have only sparse datasets. We use compiled pyroclastic flow runout data from Colima, Merapi, Soufriere Hills, Unzen and Semeru volcanoes, presented in an open-source database FlowDat (https://vhub.org/groups/massflowdatabase). While the exact relationship between flow volume and friction varies somewhat between volcanoes, dome collapse flows originating from the same volcano exhibit similar mobility relationships. Instead of fitting separate regression models for each volcano dataset, we use a variation of the hierarchical linear model (Kass and Steffey, 1989). The model presents a hierarchical structure with two levels; all dome collapse flows and dome collapse flows at specific volcanoes. The hierarchical model allows us to assume that the flows at specific volcanoes share a common distribution of regression slopes, then solves for that distribution. We present comparisons of the 95% confidence intervals on the individual regression lines for the data set from each volcano as well as those obtained from the hierarchical model. The results clearly demonstrate the advantage of considering global datasets using this technique. The technique developed is demonstrated here for mobility metrics, but can be applied to many other global datasets of volcanic parameters. In particular, such methods can provide a means to better contain parameters for volcanoes for which we only have sparse data, a ubiquitous problem in volcanology.

  4. Proposing a Hierarchical Utility Package with Reference to Mobile Advertising

    OpenAIRE

    Shalini N. Tripathi; Masood H. Siddiqui

    2011-01-01

    Mobile advertising is a powerful tool for direct and interactive marketing. However effective marketing requires examining consumers’ psyche. This study proposes a hierarchical utility package (in the consumers’ perception) with reference to mobile advertising, thus enhancing its acceptance. Confirmatory factor analysis revealed four consolidated utility dimensions (with reference to mobile advertising). Binary logistic regression was used to create a hierarchical utility package with res...

  5. Hierarchical species distribution models

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    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

    Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

  6. A case of parotid tumor showing remarkable regression following hyperthermo-chemo-radiotherapy

    International Nuclear Information System (INIS)

    Fujimura, Takashi; Yonemura, Yutaka; Kamata, Toru

    1987-01-01

    A 72-year-old woman developed adenocarcinoma of the left parotid gland. Because of the excessive size of her tumor and the fact that she suffered from severe liver dysfunction, she was treated by hyperthermo-chemo-radiotherapy (HCR therapy). After ten sessions of radiofrequency hyperthermia with HEH 500 (13.56 MHz radiofrequency wave), 50-Gy irradiation from a linac and administration of 33.0 g of tegafur in suppository form, the tumor mass showed remarkable regression decreasing in size by as much as 84 % on computed tomography. Histologically, the tumor which was resected under local anesthesia, showed almost total necrosis. The multidisciplinary HCR therapy was well tolerated and effective as a therapy for cancer in this case. (author)

  7. How hierarchical is language use?

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    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  8. TYPE Ia SUPERNOVA COLORS AND EJECTA VELOCITIES: HIERARCHICAL BAYESIAN REGRESSION WITH NON-GAUSSIAN DISTRIBUTIONS

    International Nuclear Information System (INIS)

    Mandel, Kaisey S.; Kirshner, Robert P.; Foley, Ryan J.

    2014-01-01

    We investigate the statistical dependence of the peak intrinsic colors of Type Ia supernovae (SNe Ia) on their expansion velocities at maximum light, measured from the Si II λ6355 spectral feature. We construct a new hierarchical Bayesian regression model, accounting for the random effects of intrinsic scatter, measurement error, and reddening by host galaxy dust, and implement a Gibbs sampler and deviance information criteria to estimate the correlation. The method is applied to the apparent colors from BVRI light curves and Si II velocity data for 79 nearby SNe Ia. The apparent color distributions of high-velocity (HV) and normal velocity (NV) supernovae exhibit significant discrepancies for B – V and B – R, but not other colors. Hence, they are likely due to intrinsic color differences originating in the B band, rather than dust reddening. The mean intrinsic B – V and B – R color differences between HV and NV groups are 0.06 ± 0.02 and 0.09 ± 0.02 mag, respectively. A linear model finds significant slopes of –0.021 ± 0.006 and –0.030 ± 0.009 mag (10 3 km s –1 ) –1 for intrinsic B – V and B – R colors versus velocity, respectively. Because the ejecta velocity distribution is skewed toward high velocities, these effects imply non-Gaussian intrinsic color distributions with skewness up to +0.3. Accounting for the intrinsic-color-velocity correlation results in corrections to A V extinction estimates as large as –0.12 mag for HV SNe Ia and +0.06 mag for NV events. Velocity measurements from SN Ia spectra have the potential to diminish systematic errors from the confounding of intrinsic colors and dust reddening affecting supernova distances

  9. Hierarchical Rhetorical Sentence Categorization for Scientific Papers

    Science.gov (United States)

    Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.

    2018-03-01

    Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.

  10. Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

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    Zahra Sharafi

    2017-01-01

    Full Text Available Background. The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods. The ordinal logistic regression (OLR and hierarchical ordinal logistic regression (HOLR were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™ 4.0 collected from 576 healthy school children were analyzed. Results. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

  11. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  12. Learning with hierarchical-deep models.

    Science.gov (United States)

    Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

    2013-08-01

    We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

  13. Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

    Science.gov (United States)

    Luo, Wen; Azen, Razia

    2013-01-01

    Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

  14. Conceptual hierarchical modeling to describe wetland plant community organization

    Science.gov (United States)

    Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.

    2010-01-01

    Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

  15. Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

    Science.gov (United States)

    Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

    2017-12-01

    Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream

  16. The Hierarchical Perspective

    Directory of Open Access Journals (Sweden)

    Daniel Sofron

    2015-05-01

    Full Text Available This paper is focused on the hierarchical perspective, one of the methods for representing space that was used before the discovery of the Renaissance linear perspective. The hierarchical perspective has a more or less pronounced scientific character and its study offers us a clear image of the way the representatives of the cultures that developed it used to perceive the sensitive reality. This type of perspective is an original method of representing three-dimensional space on a flat surface, which characterises the art of Ancient Egypt and much of the art of the Middle Ages, being identified in the Eastern European Byzantine art, as well as in the Western European Pre-Romanesque and Romanesque art. At the same time, the hierarchical perspective is also present in naive painting and infantile drawing. Reminiscences of this method can be recognised also in the works of some precursors of the Italian Renaissance. The hierarchical perspective can be viewed as a subjective ranking criterion, according to which the elements are visually represented by taking into account their relevance within the image while perception is ignored. This paper aims to show how the main objective of the artists of those times was not to faithfully represent the objective reality, but rather to emphasize the essence of the world and its perennial aspects. This may represent a possible explanation for the refusal of perspective in the Egyptian, Romanesque and Byzantine painting, characterised by a marked two-dimensionality.

  17. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    Science.gov (United States)

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

  18. Concurrent and convergent validity of the mobility- and multidimensional-hierarchical disability categorization models with physical performance in community older adults.

    Science.gov (United States)

    Hu, Ming-Hsia; Yeh, Chih-Jun; Chen, Tou-Rong; Wang, Ching-Yi

    2014-01-01

    A valid, time-efficient and easy-to-use instrument is important for busy clinical settings, large scale surveys, or community screening use. The purpose of this study was to validate the mobility hierarchical disability categorization model (an abbreviated model) by investigating its concurrent validity with the multidimensional hierarchical disability categorization model (a comprehensive model) and triangulating both models with physical performance measures in older adults. 604 community-dwelling older adults of at least 60 years in age volunteered to participate. Self-reported function on mobility, instrumental activities of daily living (IADL) and activities of daily living (ADL) domains were recorded and then the disability status determined based on both the multidimensional hierarchical categorization model and the mobility hierarchical categorization model. The physical performance measures, consisting of grip strength and usual and fastest gait speeds (UGS, FGS), were collected on the same day. Both categorization models showed high correlation (γs = 0.92, p categorization models. The results of multiple regression analysis indicated that both models individually explain similar amount of variance on all physical performances, with adjustments for age, sex, and number of comorbidities. Our results found that the mobility hierarchical disability categorization model is a valid and time efficient tool for large survey or screening use.

  19. The importance of trait emotional intelligence and feelings in the prediction of perceived and biological stress in adolescents: hierarchical regressions and fsQCA models.

    Science.gov (United States)

    Villanueva, Lidón; Montoya-Castilla, Inmaculada; Prado-Gascó, Vicente

    2017-07-01

    The purpose of this study is to analyze the combined effects of trait emotional intelligence (EI) and feelings on healthy adolescents' stress. Identifying the extent to which adolescent stress varies with trait emotional differences and the feelings of adolescents is of considerable interest in the development of intervention programs for fostering youth well-being. To attain this goal, self-reported questionnaires (perceived stress, trait EI, and positive/negative feelings) and biological measures of stress (hair cortisol concentrations, HCC) were collected from 170 adolescents (12-14 years old). Two different methodologies were conducted, which included hierarchical regression models and a fuzzy-set qualitative comparative analysis (fsQCA). The results support trait EI as a protective factor against stress in healthy adolescents and suggest that feelings reinforce this relation. However, the debate continues regarding the possibility of optimal levels of trait EI for effective and adaptive emotional management, particularly in the emotional attention and clarity dimensions and for female adolescents.

  20. Processing of hierarchical syntactic structure in music.

    Science.gov (United States)

    Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian

    2013-09-17

    Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

  1. Band structures of two dimensional solid/air hierarchical phononic crystals

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Y.L.; Tian, X.G. [State Key Laboratory for Mechanical Structure Strength and Vibration, Xi' an Jiaotong University, Xi' an 710049 (China); Chen, C.Q., E-mail: chencq@tsinghua.edu.cn [Department of Engineering Mechanics, AML and CNMM, Tsinghua University, Beijing 100084 (China)

    2012-06-15

    The hierarchical phononic crystals to be considered show a two-order 'hierarchical' feature, which consists of square array arranged macroscopic periodic unit cells with each unit cell itself including four sub-units. Propagation of acoustic wave in such two dimensional solid/air phononic crystals is investigated by the finite element method (FEM) with the Bloch theory. Their band structure, wave filtering property, and the physical mechanism responsible for the broadened band gap are explored. The corresponding ordinary phononic crystal without hierarchical feature is used for comparison. Obtained results show that the solid/air hierarchical phononic crystals possess tunable outstanding band gap features, which are favorable for applications such as sound insulation and vibration attenuation.

  2. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    Science.gov (United States)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

  3. Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

    Science.gov (United States)

    Ker, H. W.

    2014-01-01

    Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

  4. Hierarchically organized layout for visualization of biochemical pathways.

    Science.gov (United States)

    Tsay, Jyh-Jong; Wu, Bo-Liang; Jeng, Yu-Sen

    2010-01-01

    Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

  5. Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

    2009-04-15

    Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

  6. Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

    International Nuclear Information System (INIS)

    Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

    2009-01-01

    Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

  7. Facile synthesis and photocatalytic activity of zinc oxide hierarchical microcrystals

    KAUST Repository

    Xu, Xinjiang

    2013-04-04

    ZnO microcrystals with hierarchical structure have been synthesized by a simple solvothermal approach. The microcrystals were studied by means of X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. Research on the formation mechanism of the hierarchical microstructure shows that the coordination solvent and precursor concentration have considerable influence on the size and morphology of the microstructures. A possible formation mechanism of the hierarchical structure was suggested. Furthermore, the catalytic activity of the ZnO microcrystals was studied by treating low concentration Rhodamine B (RhB) solution under UV light, and research results show the hierarchical microstructures of ZnO display high catalytic activity in photocatalysis, the catalysis process follows first-order reaction kinetics, and the apparent rate constant k = 0.03195 min-1.

  8. Hierarchical Traces for Reduced NSM Memory Requirements

    Science.gov (United States)

    Dahl, Torbjørn S.

    This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

  9. Principal Covariates Clusterwise Regression (PCCR) : Accounting for multicollinearity and population heterogeneity in hierarchically organized data.

    NARCIS (Netherlands)

    Wilderjans, Tom F.; Van de Gaer, E.; Kiers, H.A.L.; Van Mechelen, Iven; Ceulemans, Eva

    In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three

  10. A hierarchical bayesian model to quantify uncertainty of stream water temperature forecasts.

    Directory of Open Access Journals (Sweden)

    Guillaume Bal

    Full Text Available Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i an emotive simulated example, ii application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife.

  11. Road Network Selection Based on Road Hierarchical Structure Control

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2015-04-01

    Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

  12. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

  14. Determinants of falls in community-dwelling elderly: hierarchical analysis.

    Science.gov (United States)

    Brito, Thais Alves; Coqueiro, Raildo da Silva; Fernandes, Marcos Henrique; de Jesus, Cleber Souza

    2014-01-01

    To analyze the fall-related factors in community-dwelling elderly. Epidemiologic cross-sectional population-based household study with hierarchical interrelationships among the potential risk factors. The sample was made up of noninstitutionalized individuals over age 60, who were resident of a city in Brazil's Northeast Region. The dependent variable was fall occurrence in the last 12 months; independent variables were sociodemographic, behavioral, health, and functional status factors. Multivariate hierarchical Poisson regression analysis was used based on a proposed theoretic model. Three hundred and sixteen (89.0%) elderly participated of the survey, average age 74.2 years; the majority was female, with limited literacy and had low-medium family income. The fall prevalence was of 25.8%; occurrence was related to depression symptoms (PR = 1.55) and balance limitation (PR = 1.56). The high fall prevalence among elderly necessitates the identification of fall-related factors for action planning prevention programs with this group. © 2014 Wiley Periodicals, Inc.

  15. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  16. Band structures of two dimensional solid/air hierarchical phononic crystals

    International Nuclear Information System (INIS)

    Xu, Y.L.; Tian, X.G.; Chen, C.Q.

    2012-01-01

    The hierarchical phononic crystals to be considered show a two-order “hierarchical” feature, which consists of square array arranged macroscopic periodic unit cells with each unit cell itself including four sub-units. Propagation of acoustic wave in such two dimensional solid/air phononic crystals is investigated by the finite element method (FEM) with the Bloch theory. Their band structure, wave filtering property, and the physical mechanism responsible for the broadened band gap are explored. The corresponding ordinary phononic crystal without hierarchical feature is used for comparison. Obtained results show that the solid/air hierarchical phononic crystals possess tunable outstanding band gap features, which are favorable for applications such as sound insulation and vibration attenuation.

  17. Three Ways to Link Merge with Hierarchical Concept-Combination

    Directory of Open Access Journals (Sweden)

    Chris Thornton

    2016-11-01

    Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

  18. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2012-01-01

    Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  19. Hierarchical effects on target detection and conflict monitoring

    Science.gov (United States)

    Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

    2016-01-01

    Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

  20. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

  1. Mental and physical health correlates among family caregivers of patients with newly-diagnosed incurable cancer: a hierarchical linear regression analysis.

    Science.gov (United States)

    Shaffer, Kelly M; Jacobs, Jamie M; Nipp, Ryan D; Carr, Alaina; Jackson, Vicki A; Park, Elyse R; Pirl, William F; El-Jawahri, Areej; Gallagher, Emily R; Greer, Joseph A; Temel, Jennifer S

    2017-03-01

    Caregiver, relational, and patient factors have been associated with the health of family members and friends providing care to patients with early-stage cancer. Little research has examined whether findings extend to family caregivers of patients with incurable cancer, who experience unique and substantial caregiving burdens. We examined correlates of mental and physical health among caregivers of patients with newly-diagnosed incurable lung or non-colorectal gastrointestinal cancer. At baseline for a trial of early palliative care, caregivers of participating patients (N = 275) reported their mental and physical health (Medical Outcome Survey-Short Form-36); patients reported their quality of life (Functional Assessment of Cancer Therapy-General). Analyses used hierarchical linear regression with two-tailed significance tests. Caregivers' mental health was worse than the U.S. national population (M = 44.31, p caregiver, relational, and patient factors simultaneously revealed that younger (B = 0.31, p = .001), spousal caregivers (B = -8.70, p = .003), who cared for patients reporting low emotional well-being (B = 0.51, p = .01) reported worse mental health; older (B = -0.17, p = .01) caregivers with low educational attainment (B = 4.36, p family caregivers of patients with incurable cancer, caregiver demographics, relational factors, and patient-specific factors were all related to caregiver mental health, while caregiver demographics were primarily associated with caregiver physical health. These findings help identify characteristics of family caregivers at highest risk of poor mental and physical health who may benefit from greater supportive care.

  2. Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

    International Nuclear Information System (INIS)

    Enoki, Motohiro; Ishiyama, Tomoaki; Kobayashi, Masakazu A. R.; Nagashima, Masahiro

    2014-01-01

    Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

  3. Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

    Energy Technology Data Exchange (ETDEWEB)

    Enoki, Motohiro [Faculty of Business Administration, Tokyo Keizai University, Kokubunji, Tokyo 185-8502 (Japan); Ishiyama, Tomoaki [Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Kobayashi, Masakazu A. R. [Research Center for Space and Cosmic Evolution, Ehime University, Matsuyama, Ehime 790-8577 (Japan); Nagashima, Masahiro, E-mail: enokimt@tku.ac.jp [Faculty of Education, Nagasaki University, Nagasaki, Nagasaki 852-8521 (Japan)

    2014-10-10

    Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

  4. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  5. Nanocrystalline Hierarchical ZSM-5: An Efficient Catalyst for the Alkylation of Phenol with Cyclohexene.

    Science.gov (United States)

    Radhika, N P; Selvin, Rosilda; Kakkar, Rita; Roselin, L Selva

    2018-08-01

    In this paper, authors report the synthesis of nanocrystalline hierarchical zeolite ZSM-5 and its application as a heterogeneous catalyst in the alkylation of phenol with cyclohexene. The catalyst was synthesized by vacuum-concentration coupled hydrothermal technique in the presence of two templates. This synthetic route could successfully introduce pores of higher hierarchy in the zeolite ZSM-5 structure. Hierarchical ZSM-5 could catalyse effectively the industrially important reaction of cyclohexene with phenol. We ascribe the high efficiency of the catalyst to its conducive structural features such as nanoscale size, high surface area, presence of hierarchy of pores and existence of Lewis sites along with Brønsted acid sites. The effect of various reaction parameters like duration, catalyst amount, reactant mole ratio and temperature were assessed. Under optimum reaction conditions, the catalyst showed up to 65% selectivity towards the major product, cyclohexyl phenyl ether. There was no discernible decline in percent conversion or selectivity even when the catalyst was re-used for up to four runs. Kinetic studies were done through regression analysis and a mechanistic route based on LHHW model was suggested.

  6. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  7. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  8. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    Science.gov (United States)

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

  9. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  10. Regularized multivariate regression models with skew-t error distributions

    KAUST Repository

    Chen, Lianfu

    2014-06-01

    We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding L1-penalties on the entries of the two matrices. Taking advantage of the hierarchical representation of skew-t distributions, and using the expectation conditional maximization (ECM) algorithm, we reduce the problem to penalized normal likelihood and develop a procedure to minimize the ensuing objective function. Using a simulation study the performance of the method is assessed, and the methodology is illustrated using a real data set with a 24-dimensional response vector. © 2014 Elsevier B.V.

  11. A local adaptive algorithm for emerging scale-free hierarchical networks

    International Nuclear Information System (INIS)

    Gomez Portillo, I J; Gleiser, P M

    2010-01-01

    In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

  12. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, Michael [Iowa State Univ., Ames, IA (United States)

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  13. Hierarchical prisoner’s dilemma in hierarchical game for resource competition

    Science.gov (United States)

    Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

    2017-07-01

    Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

  14. Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

    Science.gov (United States)

    Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

    2006-01-01

    Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

  15. Social Influence on Information Technology Adoption and Sustained Use in Healthcare: A Hierarchical Bayesian Learning Method Analysis

    Science.gov (United States)

    Hao, Haijing

    2013-01-01

    Information technology adoption and diffusion is currently a significant challenge in the healthcare delivery setting. This thesis includes three papers that explore social influence on information technology adoption and sustained use in the healthcare delivery environment using conventional regression models and novel hierarchical Bayesian…

  16. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  17. Deep hierarchical attention network for video description

    Science.gov (United States)

    Li, Shuohao; Tang, Min; Zhang, Jun

    2018-03-01

    Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

  18. Fabrication of Superhydrophobic Surface with Controlled Wetting Property by Hierarchical Particles.

    Science.gov (United States)

    Xu, Jianxiong; Liu, Weiwei; Du, Jingjing; Tang, Zengmin; Xu, Lijian; Li, Na

    2015-04-01

    Hierarchical particles were prepared by synthetically joining appropriately functionalized polystyrene spheres of poly[styrene-co-(3-(4-vinylphenyl)pentane-2,4-dione)] (PS-co-PVPD) nanoparticles and poly(styrene-co-chloromethylstyrene) (PS-co-PCMS) microparticles. The coupling reaction of nucleophilic substitution of pendent β-diketone groups with benzyl chloride was used to form the hierarchical particles. Since the polymeric nanoparticles and microparticles were synthesized by dispersion polymerization and emulsion polymerization, respectively, both the core microparticles and the surface nanoparticles can be different size and chemical composition. By means of changing the size of the PS-co-PVPD surface nanoparticles, a series of hierarchical particles with different scale ratio of the micro/nano surface structure were successfully prepared. Moreover, by employing the PS-co-PVPD microparticles and PS-co-PCMS nanoparticles as building blocks, hierarchical particles with surface nanoaprticles of different composition were made. These as-prepared hierarchical particles were subsequently assembled on glass substrates to form particulate films. Contact angle measurement shows that superhydrophobic surfaces can be obtained and the contact angle of water on the hierarchically structured surface can be adjusted by the scale ratio of the micro/nano surface structure and surface chemical component of hierarchical particles.

  19. Modular networks with hierarchical organization

    Indian Academy of Sciences (India)

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary ...

  20. On a Robust MaxEnt Process Regression Model with Sample-Selection

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2018-04-01

    Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

  1. How to show that unicorn milk is a chronobiotic: the regression-to-the-mean statistical artifact.

    Science.gov (United States)

    Atkinson, G; Waterhouse, J; Reilly, T; Edwards, B

    2001-11-01

    Few chronobiologists may be aware of the regression-to-the-mean (RTM) statistical artifact, even though it may have far-reaching influences on chronobiological data. With the aid of simulated measurements of the circadian rhythm phase of body temperature and a completely bogus stimulus (unicorn milk), we explain what RTM is and provide examples relevant to chronobiology. We show how RTM may lead to erroneous conclusions regarding individual differences in phase responses to rhythm disturbances and how it may appear as though unicorn milk has phase-shifting effects and can successfully treat some circadian rhythm disorders. Guidelines are provided to ensure RTM effects are minimized in chronobiological investigations.

  2. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

    Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

  3. Hierarchical sets: analyzing pangenome structure through scalable set visualizations

    Science.gov (United States)

    2017-01-01

    Abstract Motivation: The increase in available microbial genome sequences has resulted in an increase in the size of the pangenomes being analyzed. Current pangenome visualizations are not intended for the pangenome sizes possible today and new approaches are necessary in order to convert the increase in available information to increase in knowledge. As the pangenome data structure is essentially a collection of sets we explore the potential for scalable set visualization as a tool for pangenome analysis. Results: We present a new hierarchical clustering algorithm based on set arithmetics that optimizes the intersection sizes along the branches. The intersection and union sizes along the hierarchy are visualized using a composite dendrogram and icicle plot, which, in pangenome context, shows the evolution of pangenome and core size along the evolutionary hierarchy. Outlying elements, i.e. elements whose presence pattern do not correspond with the hierarchy, can be visualized using hierarchical edge bundles. When applied to pangenome data this plot shows putative horizontal gene transfers between the genomes and can highlight relationships between genomes that is not represented by the hierarchy. We illustrate the utility of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. Availability and Implementation: The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https://cran.r-project.org/web/packages/hierarchicalSets) Contact: thomasp85@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28130242

  4. Hierarchical architecture of active knits

    International Nuclear Information System (INIS)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-01-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm. (paper)

  5. Nested and Hierarchical Archimax copulas

    KAUST Repository

    Hofert, Marius

    2017-07-03

    The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

  6. Nested and Hierarchical Archimax copulas

    KAUST Repository

    Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

    2017-01-01

    The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

  7. Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

    Science.gov (United States)

    Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

    2009-01-01

    The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

  8. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  9. Hierarchical CuO hollow microspheres: Controlled synthesis for enhanced lithium storage performance

    International Nuclear Information System (INIS)

    Guan Xiangfeng; Li Liping; Li Guangshe; Fu Zhengwei; Zheng Jing; Yan Tingjiang

    2011-01-01

    Graphical abstract: Hierarchical CuO microspheres with hollow interiors were formed through self-wrapping of a single layer of radically oriented CuO nanorods, and these microspheres showed excellent cycle performance and enhanced lithium storage capacity. Display Omitted Research highlights: → Hierarchical CuO hollow microspheres were prepared by a hydrothermal method. → The CuO hollow microspheres were assembled from radically oriented nanorods. → The growth mechanism was proposed to proceed via self-assembly and Ostwald's ripening. → The microspheres showed good cycle performance and enhanced lithium storage capacity. → Hierarchical microstructures with hollow interiors promote electrochemical property. - Abstract: In this work, hierarchical CuO hollow microspheres were hydrothermally prepared without use of any surfactants or templates. By controlling the formation reaction conditions and monitoring the relevant reaction processes using time-dependent experiments, it is demonstrated that hierarchical CuO microspheres with hollow interiors were formed through self-wrapping of a single layer of radically oriented CuO nanorods, and that hierarchical spheres could be tuned to show different morphologies and microstructures. As a consequence, the formation mechanism was proposed to proceed via a combined process of self-assembly and Ostwald's ripening. Further, these hollow microspheres were initiated as the anode material in lithium ion batteries, which showed excellent cycle performance and enhanced lithium storage capacity, most likely because of the synergetic effect of small diffusion lengths in building blocks of nanorods and proper void space that buffers the volume expansion. The strategy reported in this work is reproducible, which may help to significantly improve the electrochemical performance of transition metal oxide-based anode materials via designing the hollow structures necessary for developing lithium ion batteries and the relevant

  10. Collaborative regression-based anatomical landmark detection

    International Nuclear Information System (INIS)

    Gao, Yaozong; Shen, Dinggang

    2015-01-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head and neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods. (paper)

  11. Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

    2010-11-15

    There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

  12. Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

    OpenAIRE

    Yi Huang; Francesca Dominici; Michelle Bell

    2004-01-01

    In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP ...

  13. Organization of excitable dynamics in hierarchical biological networks.

    Directory of Open Access Journals (Sweden)

    Mark Müller-Linow

    Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

  14. Multiple dynamical time-scales in networks with hierarchically

    Indian Academy of Sciences (India)

    Modular networks; hierarchical organization; synchronization. ... we show that such a topological structure gives rise to characteristic time-scale separation ... This suggests a possible functional role of such mesoscopic organization principle in ...

  15. Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

    2012-01-01

    The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

  16. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  17. Multiperiod Hierarchical Location Problem of Transit Hub in Urban Agglomeration Area

    Directory of Open Access Journals (Sweden)

    Ting-ting Li

    2017-01-01

    Full Text Available With the rapid urbanization in developing countries, urban agglomeration area (UAA forms. Also, transportation demand in UAA grows rapidly and presents hierarchical feature. Therefore, it is imperative to develop models for transit hubs to guide the development of UAA and better meet the time-varying and hierarchical transportation demand. In this paper, the multiperiod hierarchical location problem of transit hub in urban agglomeration area (THUAA is studied. A hierarchical service network of THUAA with a multiflow, nested, and noncoherent structure is described. Then a multiperiod hierarchical mathematical programming model is proposed, aiming at minimizing the total demand weighted travel time. Moreover, an improved adaptive clonal selection algorithm is presented to solve the model. Both the model and algorithm are verified by the application to a real-life problem of Beijing-Tianjin-Hebei Region in China. The results of different scenarios in the case show that urban population migration has a great impact on the THUAA location scheme. Sustained and appropriate urban population migration helps to reduce travel time for urban residents.

  18. Hierarchical adaptive experimental design for Gaussian process emulators

    International Nuclear Information System (INIS)

    Busby, Daniel

    2009-01-01

    Large computer simulators have usually complex and nonlinear input output functions. This complicated input output relation can be analyzed by global sensitivity analysis; however, this usually requires massive Monte Carlo simulations. To effectively reduce the number of simulations, statistical techniques such as Gaussian process emulators can be adopted. The accuracy and reliability of these emulators strongly depend on the experimental design where suitable evaluation points are selected. In this paper a new sequential design strategy called hierarchical adaptive design is proposed to obtain an accurate emulator using the least possible number of simulations. The hierarchical design proposed in this paper is tested on various standard analytic functions and on a challenging reservoir forecasting application. Comparisons with standard one-stage designs such as maximin latin hypercube designs show that the hierarchical adaptive design produces a more accurate emulator with the same number of computer experiments. Moreover a stopping criterion is proposed that enables to perform the number of simulations necessary to obtain required approximation accuracy.

  19. A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting

    OpenAIRE

    Zhaoxuan Li; SM Mahbobur Rahman; Rolando Vega; Bing Dong

    2016-01-01

    We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statisti...

  20. Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

    Science.gov (United States)

    Nitta, Tohru

    2017-10-01

    We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

  1. Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

    Directory of Open Access Journals (Sweden)

    Bin Ahmad Fawzan Mohammed Ridha

    2018-01-01

    Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

  2. Parameter-Invariant Hierarchical Exclusive Alphabet Design for 2-WRC with HDF Strategy

    Directory of Open Access Journals (Sweden)

    T. Uřičář

    2010-01-01

    Full Text Available Hierarchical eXclusive Code (HXC for the Hierarchical Decode and Forward (HDF strategy in the Wireless 2-Way Relay Channel (2-WRC has the achievable rate region extended beyond the classical MAC region. Although direct HXC design is in general highly complex, a layered approach to HXC design is a feasible solution. While the outer layer code of the layered HXC can be any state-of-the-art capacity approaching code, the inner layer must be designed in such a way that the exclusive property of hierarchical symbols (received at the relay will be provided. The simplest case of the inner HXC layer is a simple signal space channel symbol memoryless mapper called Hierarchical eXclusive Alphabet (HXA. The proper design of HXA is important, especially in the case of parametric channels, where channel parametrization (e.g. phase rotation can violate the exclusive property of hierarchical symbols (as seen by the relay, resulting in significant capacity degradation. In this paper we introduce an example of a geometrical approach to Parameter-Invariant HXA design, and we show that the corresponding hierarchical MAC capacity region extends beyond the classical MAC region, irrespective of the channel pametrization.

  3. Adaptive hierarchical multi-agent organizations

    NARCIS (Netherlands)

    Ghijsen, M.; Jansweijer, W.N.H.; Wielinga, B.J.; Babuška, R.; Groen, F.C.A.

    2010-01-01

    In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the

  4. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  5. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures.

    Science.gov (United States)

    Schargott, M

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  6. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    Energy Technology Data Exchange (ETDEWEB)

    Schargott, M [Institute of Mechanics, Technische Universitaet Berlin, Strd 17 Juni 135, 10623 Berlin (Germany)], E-mail: martin.schargott@tu-berlin.de

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  7. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    International Nuclear Information System (INIS)

    Schargott, M

    2009-01-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface

  8. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  9. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  10. Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

    Science.gov (United States)

    Fu, QiMing

    2016-01-01

    To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

  11. Ways of looking ahead: hierarchical planning in language production.

    Science.gov (United States)

    Lee, Eun-Kyung; Brown-Schmidt, Sarah; Watson, Duane G

    2013-12-01

    It is generally assumed that language production proceeds incrementally, with chunks of linguistic structure planned ahead of speech. Extensive research has examined the scope of language production and suggests that the size of planned chunks varies across contexts (Ferreira & Swets, 2002; Wagner & Jescheniak, 2010). By contrast, relatively little is known about the structure of advance planning, specifically whether planning proceeds incrementally according to the surface structure of the utterance, or whether speakers plan according to the hierarchical relationships between utterance elements. In two experiments, we examine the structure and scope of lexical planning in language production using a picture description task. Analyses of speech onset times and word durations show that speakers engage in hierarchical planning such that structurally dependent lexical items are planned together and that hierarchical planning occurs for both direct and indirect dependencies. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Detecting the overlapping and hierarchical community structure in complex networks

    International Nuclear Information System (INIS)

    Lancichinetti, Andrea; Fortunato, Santo; Kertesz, Janos

    2009-01-01

    Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.

  13. Dynamics and thermodynamics in hierarchically organized systems applications in physics, biology and economics

    CERN Document Server

    Auger, P

    2013-01-01

    One of the most fundamental and efficient ways of conceptualizing complex systems is to organize them hierarchically. A hierarchically organized system is represented by a network of interconnected subsystems, each of which has its own network of subsystems, and so on, until some elementary subsystems are reached that are not further decomposed. This original and important book proposes a general mathematical theory of a hierarchical system and shows how it can be applied to very different topics such as physics (Hamiltonian systems), biology (coupling the molecular and the cellular levels), e

  14. Using hierarchical Bayesian methods to examine the tools of decision-making

    OpenAIRE

    Michael D. Lee; Benjamin R. Newell

    2011-01-01

    Hierarchical Bayesian methods offer a principled and comprehensive way to relate psychological models to data. Here we use them to model the patterns of information search, stopping and deciding in a simulated binary comparison judgment task. The simulation involves 20 subjects making 100 forced choice comparisons about the relative magnitudes of two objects (which of two German cities has more inhabitants). Two worked-examples show how hierarchical models can be developed to account for and ...

  15. HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

    Directory of Open Access Journals (Sweden)

    V. T. Nguyen

    2016-05-01

    Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

  16. Effect of the sheet thickness of hierarchical SnO_2 on the gas sensing performance

    International Nuclear Information System (INIS)

    Zhang, Wenlong; Zeng, Wen; BinMiao; Wang, Zhongchang

    2015-01-01

    Graphical abstract: - Highlights: • A unique flower-like SnO_2 hierarchical architecture assembled with nanosheets were successfully synthesized. • The thickness of the unique hierarchical nanoflowers was precisely controlled. • The nanoflowers composed of thinner nanosheets show a significantly enhanced gas sensing properties. • A possible growth mechanism for the unique hierarchical SnO_2 nanoflower assembled with nanosheets of different thickness is proposed. - Abstract: A unique hierarchical SnO_2 nanoflower was successfully synthesized via a facile one-step hydrothermal method. The nanoflower was analyzed in detail using X ray diffraction, field-emission electron microscope and transmission electron microscope. It was found that the nanoflowers are all assembled from nanosheets. The nanosheet thickness could be precisely controlled by tuning the dosage of NaOH. Gas sensing tests demonstrated that the thickness of the sheet significantly affects the gas sensing performance. The improved gas sensing properties are attributed to the thinned petals as well as their pores and defects. These results show that the thickness and morphology of hierarchical nanostructures affect the functionality of gas sensors.

  17. Hierarchical scaffolds enhance osteogenic differentiation of human Wharton’s jelly derived stem cells

    International Nuclear Information System (INIS)

    Canha-Gouveia, Analuce; Rita Costa-Pinto, Ana; Martins, Albino M; Sousa, Rui A; Reis, Rui L; Neves, Nuno M; Silva, Nuno A; Salgado, António J; Sousa, Nuno; Faria, Susana

    2015-01-01

    Hierarchical structures, constituted by polymeric nano and microfibers, have been considered promising scaffolds for tissue engineering strategies, mainly because they mimic, in some way, the complexity and nanoscale detail observed in real organs. The chondrogenic potential of these scaffolds has been previously demonstrated, but their osteogenic potential is not yet corroborated. In order to assess if a hierarchical structure, with nanoscale details incorporated, is an improved scaffold for bone tissue regeneration, we evaluate cell adhesion, proliferation, and osteogenic differentiation of human Wharton’s jelly derived stem cells (hWJSCs), seeded into hierarchical fibrous scaffolds. Biological data corroborates that hierarchical fibrous scaffolds show an enhanced cell entrapment when compared to rapid prototyped scaffolds without nanofibers. Furthermore, upregulation of bone specific genes and calcium phosphate deposition confirms the successful osteogenic differentiation of hWJSCs on these scaffolds. These results support our hypothesis that a scaffold with hierarchical structure, in conjugation with hWJSCs, represents a possible feasible strategy for bone tissue engineering applications. (paper)

  18. First-born siblings show better second language skills than later born siblings

    Science.gov (United States)

    Keller, Karin; Troesch, Larissa M.; Grob, Alexander

    2015-01-01

    We examined the extent to which three sibling structure variables number of siblings, birth order, and presence of an older sibling at school age are linked to the second language skills of bilingual children. The research questions were tested using an ethnically heterogeneous sample of 1209 bilingual children with German as a second language. Controlling for children’s age, sex, nationality, number of children’s books at home, family language and parental German language skills, hierarchical regression analyses showed an inverse relationship between the number of siblings and second language skills: the more siblings a child had, the lower was his/her second language proficiency. This relationship was mediated by attendance in early education institutions. Moreover, first-born siblings showed better second language skills than later born siblings. The current study revealed that the resource dilution model, i.e., the decrease in resources for every additional sibling, holds for second language acquisition. Moreover, the results indicate that bilingual children from families with several children benefit from access to early education institutions. PMID:26089806

  19. First-born siblings show better second language skills than later born siblings

    Directory of Open Access Journals (Sweden)

    Karin eKeller

    2015-06-01

    Full Text Available We examined the extent to which three sibling structure variables number of siblings, birth order and presence of an older sibling at school age are linked to the second language skills of bilingual children. The research questions were tested using an ethnically heterogeneous sample of 1209 bilingual children with German as a second language. Controlling for children’s age, sex, nationality, number of children’s books at home, family language and parental German language skills, hierarchical regression analyses showed an inverse relationship between the number of siblings and second language skills: The more siblings a child had, the lower was his/her second language proficiency. This relationship was mediated by attendance in early education institutions. Moreover, first-born siblings showed better second language skills than later born siblings.The current study revealed that the resource dilution model, i.e., the decrease in resources for every additional sibling, holds for second language acquisition. Moreover, the results indicate that bilingual children from families with several children benefit from access to early education institutions.

  20. Estimating carbon and showing impacts of drought using satellite data in regression-tree models

    Science.gov (United States)

    Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.

    2018-01-01

    Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.

  1. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  2. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  3. Hierarchical drivers of reef-fish metacommunity structure.

    Science.gov (United States)

    MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

    2009-01-01

    Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at

  4. Prediction of road accidents: A Bayesian hierarchical approach

    DEFF Research Database (Denmark)

    Deublein, Markus; Schubert, Matthias; Adey, Bryan T.

    2013-01-01

    the expected number of accidents in which an injury has occurred and the expected number of light, severe and fatally injured road users. Additionally, the methodology is used for geo-referenced identification of road sections with increased occurrence probabilities of injury accident events on a road link......In this paper a novel methodology for the prediction of the occurrence of road accidents is presented. The methodology utilizes a combination of three statistical methods: (1) gamma-updating of the occurrence rates of injury accidents and injured road users, (2) hierarchical multivariate Poisson......-lognormal regression analysis taking into account correlations amongst multiple dependent model response variables and effects of discrete accident count data e.g. over-dispersion, and (3) Bayesian inference algorithms, which are applied by means of data mining techniques supported by Bayesian Probabilistic Networks...

  5. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Directory of Open Access Journals (Sweden)

    Zheng eRen

    2013-11-01

    Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  6. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong; Wu, Tao

    2017-01-01

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced

  7. Bayesian hierarchical models for smoothing in two-phase studies, with application to small area estimation.

    Science.gov (United States)

    Ross, Michelle; Wakefield, Jon

    2015-10-01

    Two-phase study designs are appealing since they allow for the oversampling of rare sub-populations which improves efficiency. In this paper we describe a Bayesian hierarchical model for the analysis of two-phase data. Such a model is particularly appealing in a spatial setting in which random effects are introduced to model between-area variability. In such a situation, one may be interested in estimating regression coefficients or, in the context of small area estimation, in reconstructing the population totals by strata. The efficiency gains of the two-phase sampling scheme are compared to standard approaches using 2011 birth data from the research triangle area of North Carolina. We show that the proposed method can overcome small sample difficulties and improve on existing techniques. We conclude that the two-phase design is an attractive approach for small area estimation.

  8. Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

    Science.gov (United States)

    Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

    2013-11-20

    Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

  9. Hierarchical screening for multiple mental disorders.

    Science.gov (United States)

    Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

    2013-10-01

    There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

  10. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

    Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

    2013-09-01

    Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong

    2017-08-03

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

  12. Poincaré Embeddings for Learning Hierarchical Representations

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Abstracts: Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, while complex symbolic datasets often exhibit a latent hierarchical structure, state-of-the-art methods typically do not account for this property. In this talk, I will discuss a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an n-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows us to learn parsimonious representations of symbolic data by simultaneously capturing hierarchy and similarity. We introduce an efficient algorithm to learn the embeddings based on Riemannian optimization and show experimentally that Poincaré embeddings outperform Euclidean embeddings significantly on data with latent hierarchies, both in terms of representation capacity and in terms of generalization ability.      &...

  13. Intermediate and advanced topics in multilevel logistic regression analysis.

    Science.gov (United States)

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  14. Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

    Science.gov (United States)

    Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

    Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

  15. Zeolitic materials with hierarchical porous structures.

    Science.gov (United States)

    Lopez-Orozco, Sofia; Inayat, Amer; Schwab, Andreas; Selvam, Thangaraj; Schwieger, Wilhelm

    2011-06-17

    During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

    International Nuclear Information System (INIS)

    Jafri, Y.Z.; Kamal, L.

    2007-01-01

    Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

  17. Bayesian semiparametric regression models to characterize molecular evolution

    Directory of Open Access Journals (Sweden)

    Datta Saheli

    2012-10-01

    Full Text Available Abstract Background Statistical models and methods that associate changes in the physicochemical properties of amino acids with natural selection at the molecular level typically do not take into account the correlations between such properties. We propose a Bayesian hierarchical regression model with a generalization of the Dirichlet process prior on the distribution of the regression coefficients that describes the relationship between the changes in amino acid distances and natural selection in protein-coding DNA sequence alignments. Results The Bayesian semiparametric approach is illustrated with simulated data and the abalone lysin sperm data. Our method identifies groups of properties which, for this particular dataset, have a similar effect on evolution. The model also provides nonparametric site-specific estimates for the strength of conservation of these properties. Conclusions The model described here is distinguished by its ability to handle a large number of amino acid properties simultaneously, while taking into account that such data can be correlated. The multi-level clustering ability of the model allows for appealing interpretations of the results in terms of properties that are roughly equivalent from the standpoint of molecular evolution.

  18. Hierarchical Nanoceramics for Industrial Process Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

    2011-07-15

    This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

  19. The Case for a Hierarchical Cosmology

    Science.gov (United States)

    Vaucouleurs, G. de

    1970-01-01

    The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)

  20. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  1. Hierarchical graphs for rule-based modeling of biochemical systems

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

    Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

  2. Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

    Science.gov (United States)

    Li, Yasong; Gates, Byron D; Menon, Carlo

    2015-08-05

    The gecko relies on van der Waals forces to cling onto surfaces with a variety of topography and composition. The hierarchical fibrillar structures on their climbing feet, ranging from mesoscale to nanoscale, are hypothesized to be key elements for the animal to conquer both smooth and rough surfaces. An epoxy-based artificial hierarchical fibrillar adhesive was prepared to study the influence of the hierarchical structures on the properties of a dry adhesive. The presented experiments highlight the advantages of a hierarchical structure despite a reduction of overall density and aspect ratio of nanofibrils. In contrast to an adhesive containing only nanometer-size fibrils, the hierarchical fibrillar adhesives exhibited a higher adhesion force and better compliancy when tested on an identical substrate.

  3. A nontransferring dry adhesive with hierarchical polymer nanohairs.

    Science.gov (United States)

    Jeong, Hoon Eui; Lee, Jin-Kwan; Kim, Hong Nam; Moon, Sang Heup; Suh, Kahp Y

    2009-04-07

    We present a simple yet robust method for fabricating angled, hierarchically patterned high-aspect-ratio polymer nanohairs to generate directionally sensitive dry adhesives. The slanted polymeric nanostructures were molded from an etched polySi substrate containing slanted nanoholes. An angled etching technique was developed to fabricate slanted nanoholes with flat tips by inserting an etch-stop layer of silicon dioxide. This unique etching method was equipped with a Faraday cage system to control the ion-incident angles in the conventional plasma etching system. The polymeric nanohairs were fabricated with tailored leaning angles, sizes, tip shapes, and hierarchical structures. As a result of controlled leaning angle and bulged flat top of the nanohairs, the replicated, slanted nanohairs showed excellent directional adhesion, exhibiting strong shear attachment (approximately 26 N/cm(2) in maximum) in the angled direction and easy detachment (approximately 2.2 N/cm(2)) in the opposite direction, with a hysteresis value of approximately 10. In addition to single scale nanohairs, monolithic, micro-nanoscale combined hierarchical hairs were also fabricated by using a 2-step UV-assisted molding technique. These hierarchical nanoscale patterns maintained their adhesive force even on a rough surface (roughness <20 microm) because of an increase in the contact area by the enhanced height of hierarchy, whereas simple nanohairs lost their adhesion strength. To demonstrate the potential applications of the adhesive patch, the dry adhesive was used to transport a large-area glass (47.5 x 37.5 cm(2), second-generation TFT-LCD glass), which could replace the current electrostatic transport/holding system with further optimization.

  4. A nontransferring dry adhesive with hierarchical polymer nanohairs

    KAUST Repository

    Jeong, H. E.

    2009-03-20

    We present a simple yet robust method for fabricating angled, hierarchically patterned high-aspect-ratio polymer nanohairs to generate directionally sensitive dry adhesives. The slanted polymeric nanostructures were molded from an etched polySi substrate containing slanted nanoholes. An angled etching technique was developed to fabricate slanted nanoholes with flat tips by inserting an etch-stop layer of silicon dioxide. This unique etching method was equipped with a Faraday cage system to control the ion-incident angles in the conventional plasma etching system. The polymeric nanohairs were fabricated with tailored leaning angles, sizes, tip shapes, and hierarchical structures. As a result of controlled leaning angle and bulged flat top of the nanohairs, the replicated, slanted nanohairs showed excellent directional adhesion, exhibiting strong shear attachment (approximately 26 N/cm(2) in maximum) in the angled direction and easy detachment (approximately 2.2 N/cm(2)) in the opposite direction, with a hysteresis value of approximately 10. In addition to single scale nanohairs, monolithic, micro-nanoscale combined hierarchical hairs were also fabricated by using a 2-step UV-assisted molding technique. These hierarchical nanoscale patterns maintained their adhesive force even on a rough surface (roughness <20 microm) because of an increase in the contact area by the enhanced height of hierarchy, whereas simple nanohairs lost their adhesion strength. To demonstrate the potential applications of the adhesive patch, the dry adhesive was used to transport a large-area glass (47.5 x 37.5 cm(2), second-generation TFT-LCD glass), which could replace the current electrostatic transport/holding system with further optimization.

  5. Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

    Science.gov (United States)

    Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

    2018-08-01

    The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

  6. A generalized linear factor model approach to the hierarchical framework for responses and response times.

    Science.gov (United States)

    Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

    2015-05-01

    We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.

  7. Hierarchical unilamellar vesicles of controlled compositional heterogeneity.

    Directory of Open Access Journals (Sweden)

    Maik Hadorn

    Full Text Available Eukaryotic life contains hierarchical vesicular architectures (i.e. organelles that are crucial for material production and trafficking, information storage and access, as well as energy production. In order to perform specific tasks, these compartments differ among each other in their membrane composition and their internal cargo and also differ from the cell membrane and the cytosol. Man-made structures that reproduce this nested architecture not only offer a deeper understanding of the functionalities and evolution of organelle-bearing eukaryotic life but also allow the engineering of novel biomimetic technologies. Here, we show the newly developed vesicle-in-water-in-oil emulsion transfer preparation technique to result in giant unilamellar vesicles internally compartmentalized by unilamellar vesicles of different membrane composition and internal cargo, i.e. hierarchical unilamellar vesicles of controlled compositional heterogeneity. The compartmentalized giant unilamellar vesicles were subsequently isolated by a separation step exploiting the heterogeneity of the membrane composition and the encapsulated cargo. Due to the controlled, efficient, and technically straightforward character of the new preparation technique, this study allows the hierarchical fabrication of compartmentalized giant unilamellar vesicles of controlled compositional heterogeneity and will ease the development of eukaryotic cell mimics that resemble their natural templates as well as the fabrication of novel multi-agent drug delivery systems for combination therapies and complex artificial microreactors.

  8. Hierarchical vs non-hierarchical audio indexation and classification for video genres

    Science.gov (United States)

    Dammak, Nouha; BenAyed, Yassine

    2018-04-01

    In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

  9. Fabrication and properties of dual-level hierarchical structures mimicking gecko foot hairs.

    Science.gov (United States)

    Zhang, Peng; Liu, Shiyuan; Lv, Hao

    2013-02-01

    In nature, geckos have extraordinary adhesive capabilities. The multi-scale hierarchical structure of the gecko foot hairs, especially the high-aspect-ratio structure of its micro-scale seta and nano-scale spatulae is the critical factor of the gecko's ability to adopt and stick to any different surface with powerful adhesion force. In this paper, we present a simple and effective approach to fabricate dual-level hierarchical structures mimicking gecko foot hairs. Polydimethyl-siloxane (PDMS) hierarchical arrays were fabricated by demolding from a double stack mold that was composed of an SU-8 mold by thick film photolithography and a silicon mold by inductively coupled plasma (ICP) etching. Top pillars of the fabricated structures have 3 micom diameter and 18 microm in height, while base pillars have 25 microm diameter and 40 microm in height. The water droplet contact angle tests indicate that the hierarchical structures increase the hydrophobic property significantly compared with the single-level arrays and the unstructured polymers, exhibiting superhydrophobicity (154.2 degrees) like the Tokay gecko's (160.9 degrees). The shear force tests show that the top pillars make attachment through side contact with a value of about 0.25 N/cm2, and moreover, the hierarchical structures are demonstrated to be more suitable for contacting with rough surfaces.

  10. A Bayesian hierarchical model for demand curve analysis.

    Science.gov (United States)

    Ho, Yen-Yi; Nhu Vo, Tien; Chu, Haitao; Luo, Xianghua; Le, Chap T

    2018-07-01

    Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine. The conventional approach popularly used to analyze the demand curve data is individual-specific non-linear least square regression. The non-linear least square approach sets out to minimize the residual sum of squares for each subject in the dataset; however, this one-subject-at-a-time approach does not allow for the estimation of between- and within-subject variability in a unified model framework. In this paper, we review the existing approaches to analyze the demand curve data, non-linear least square regression, and the mixed effects regression and propose a new Bayesian hierarchical model. We conduct simulation analyses to compare the performance of these three approaches and illustrate the proposed approaches in a case study of nicotine self-administration in rats. We present simulation results and discuss the benefits of using the proposed approaches.

  11. Intensity-based hierarchical elastic registration using approximating splines.

    Science.gov (United States)

    Serifovic-Trbalic, Amira; Demirovic, Damir; Cattin, Philippe C

    2014-01-01

    We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces. The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cramér-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model. The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method. The proposed hierarchical elastic image registration approach incorporates the GEBS

  12. Thermodynamic analysis on an anisotropically superhydrophobic surface with a hierarchical structure

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Jieliang [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China); Su, Zhengliang [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China); Department of Automotive Engineering, Tsinghua University, Beijing 100084 (China); Yan, Shaoze, E-mail: yansz@mail.tsinghua.edu.cn [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China)

    2015-12-01

    Graphical abstract: - Highlights: • We model the superhydrophobic surface with anisotropic and hierarchical structure. • Anisotropic wetting only shows in noncomposite state (not in composite state). • Transition from noncomposite to composite state on dual-scale structure is hard. • Droplets tend to roll in the particular direction. • Droplets tend to stably remain in one preferred thermodynamic state. - Abstract: Superhydrophobic surfaces, which refer to the surfaces with contact angle higher than 150° and hysteresis less than 10°, have been reported in various studies. However, studies on the superhydrophobicity of anisotropic, hierarchical surfaces are limited and the corresponding thermodynamic mechanisms could not be explained thoroughly. Here we propose a simplified surface model of anisotropic patterned surface with dual scale roughness. Based on the thermodynamic method, we calculate the equilibrium contact angle (ECA) and the contact angle hysteresis (CAH) on the given surface. We show here that the hierarchical structure has much better anisotropic wetting properties than the single-scale one, and the results shed light on the potential application in controllable micro-/nano-fluidic systems. Our studies can be potentially applied for the fabrication of anisotropically superhydrophobic surfaces.

  13. Thermodynamic analysis on an anisotropically superhydrophobic surface with a hierarchical structure

    International Nuclear Information System (INIS)

    Zhao, Jieliang; Su, Zhengliang; Yan, Shaoze

    2015-01-01

    Graphical abstract: - Highlights: • We model the superhydrophobic surface with anisotropic and hierarchical structure. • Anisotropic wetting only shows in noncomposite state (not in composite state). • Transition from noncomposite to composite state on dual-scale structure is hard. • Droplets tend to roll in the particular direction. • Droplets tend to stably remain in one preferred thermodynamic state. - Abstract: Superhydrophobic surfaces, which refer to the surfaces with contact angle higher than 150° and hysteresis less than 10°, have been reported in various studies. However, studies on the superhydrophobicity of anisotropic, hierarchical surfaces are limited and the corresponding thermodynamic mechanisms could not be explained thoroughly. Here we propose a simplified surface model of anisotropic patterned surface with dual scale roughness. Based on the thermodynamic method, we calculate the equilibrium contact angle (ECA) and the contact angle hysteresis (CAH) on the given surface. We show here that the hierarchical structure has much better anisotropic wetting properties than the single-scale one, and the results shed light on the potential application in controllable micro-/nano-fluidic systems. Our studies can be potentially applied for the fabrication of anisotropically superhydrophobic surfaces.

  14. A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China.

    Directory of Open Access Journals (Sweden)

    Xiongqing Zhang

    Full Text Available Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchical Bayesian method to estimate the self-thinning line. The results showed that the self-thinning line for Chinese fir (Cunninghamia lanceolata (Lamb.Hook. plantations was not sensitive to the initial planting density. The uncertainty of model predictions was mostly due to within-subject variability. The simulation precision of hierarchical Bayesian method was better than that of stochastic frontier function (SFF. Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables (site quality, soil type, aspect, etc. on self-thinning line, which gave us the posterior distribution of parameters of self-thinning line. The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.

  15. Facile synthesis and photocatalytic activity of zinc oxide hierarchical microcrystals

    KAUST Repository

    Xu, Xinjiang; Kuang, Fangcheng; Xu, Jiangping

    2013-01-01

    was suggested. Furthermore, the catalytic activity of the ZnO microcrystals was studied by treating low concentration Rhodamine B (RhB) solution under UV light, and research results show the hierarchical microstructures of ZnO display high catalytic activity

  16. Hierarchical analysis of acceptable use policies

    Directory of Open Access Journals (Sweden)

    P. A. Laughton

    2008-01-01

    Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

  17. A novel snowflake-like SnO2 hierarchical architecture with superior gas sensing properties

    Science.gov (United States)

    Li, Yanqiong

    2018-02-01

    Snowflake-like SnO2 hierarchical architecture has been synthesized via a facile hydrothermal method and followed by calcination. The SnO2 hierarchical structures are assembled with thin nanoflakes blocks, which look like snowflake shape. A possible mechanism for the formation of the SnO2 hierarchical structures is speculated. Moreover, gas sensing tests show that the sensor based on snowflake-like SnO2 architectures exhibited excellent gas sensing properties. The enhancement may be attributed to its unique structures, in which the porous feature on the snowflake surface could further increase the active surface area of the materials and provide facile pathways for the target gas.

  18. Virtual timers in hierarchical real-time systems

    NARCIS (Netherlands)

    Heuvel, van den M.M.H.P.; Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.; Zhu, D.

    2009-01-01

    Hierarchical scheduling frameworks (HSFs) provide means for composing complex real-time systems from welldefined subsystems. This paper describes an approach to provide hierarchically scheduled real-time applications with virtual event timers, motivated by the need for integrating priority

  19. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  20. Hierarchical organization versus self-organization

    OpenAIRE

    Busseniers, Evo

    2014-01-01

    In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

  1. The process and utility of classification and regression tree methodology in nursing research.

    Science.gov (United States)

    Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

    2014-06-01

    This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Discussion paper. English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984-2013. Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. © 2013 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

  2. COMPOSITE METHOD OF RELIABILITY RESEARCH FOR HIERARCHICAL MULTILAYER ROUTING SYSTEMS

    Directory of Open Access Journals (Sweden)

    R. B. Tregubov

    2016-09-01

    Full Text Available The paper deals with the idea of a research method for hierarchical multilayer routing systems. The method represents a composition of methods of graph theories, reliability, probabilities, etc. These methods are applied to the solution of different private analysis and optimization tasks and are systemically connected and coordinated with each other through uniform set-theoretic representation of the object of research. The hierarchical multilayer routing systems are considered as infrastructure facilities (gas and oil pipelines, automobile and railway networks, systems of power supply and communication with distribution of material resources, energy or information with the use of hierarchically nested functions of routing. For descriptive reasons theoretical constructions are considered on the example of task solution of probability determination for up state of specific infocommunication system. The author showed the possibility of constructive combination of graph representation of structure of the object of research and a logic probable analysis method of its reliability indices through uniform set-theoretic representation of its elements and processes proceeding in them.

  3. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Science.gov (United States)

    Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

    2017-01-01

    Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  4. Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Platycladi cacumen by Ultra-performance Liquid Chromatography Coupled with Hierarchical Cluster Analysis.

    Science.gov (United States)

    Shan, Mingqiu; Li, Sam Fong Yau; Yu, Sheng; Qian, Yan; Guo, Shuchen; Zhang, Li; Ding, Anwei

    2018-01-01

    Platycladi cacumen (dried twigs and leaves of Platycladus orientalis (L.) Franco) is a frequently utilized Chinese medicinal herb. To evaluate the quality of the phytomedcine, an ultra-performance liquid chromatographic method with diode array detection was established for chemical fingerprinting and quantitative analysis. In this study, 27 batches of P. cacumen from different regions were collected for analysis. A chemical fingerprint with 20 common peaks was obtained using Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A). Among these 20 components, seven flavonoids (myricitrin, isoquercitrin, quercitrin, afzelin, cupressuflavone, amentoflavone and hinokiflavone) were identified and determined simultaneously. In the method validation, the seven analytes showed good regressions (R ≥ 0.9995) within linear ranges and good recoveries from 96.4% to 103.3%. Furthermore, with the contents of these seven flavonoids, hierarchical clustering analysis was applied to distinguish the 27 batches into five groups. The chemometric results showed that these groups were almost consistent with geographical positions and climatic conditions of the production regions. Integrating fingerprint analysis, simultaneous determination and hierarchical clustering analysis, the established method is rapid, sensitive, accurate and readily applicable, and also provides a significant foundation for quality control of P. cacumen efficiently. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  5. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  6. Multiparty hierarchical quantum-information splitting

    International Nuclear Information System (INIS)

    Wang Xinwen; Zhang Dengyu; Tang Shiqing; Xie Lijun

    2011-01-01

    We propose a scheme for multiparty hierarchical quantum-information splitting (QIS) with a multipartite entangled state, where a boss distributes a secret quantum state to two grades of agents asymmetrically. The agents who belong to different grades have different authorities for recovering the boss's secret. Except for the boss's Bell-state measurement, no nonlocal operation is involved. The presented scheme is also shown to be secure against eavesdropping. Such a hierarchical QIS is expected to find useful applications in the field of modern multipartite quantum cryptography.

  7. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

  8. Hierarchical ZnO particles grafting by fluorocarbon polymer derivative: Preparation and superhydrophobic behavior

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Dahai; Jia, Mengqiu, E-mail: jiamq@mail.buct.edu.cn

    2015-07-15

    Graphical abstract: - Highlights: • The hierarchical particles were prepared by a simple, mild hydrothermal process. • The obtained “chestnut” ZnO particles show dual-scale morphology with high roughness. • FEVE derivative was creatively imported to graft onto hierarchical particles. • Superhydrophobic surfaces were obtained, on which the contact angles surpass 150°. • A special model was proposed to explain the wetting state in this work. - Abstract: Superhydrophobic surfaces on the basis of hierarchical ZnO particles grafted by fluoroethylene-vinylether (FEVE) polymer derivative were prepared using a facile, mild and low-cost method. X-ray diffraction (XRD) and scanning electron microscope (SEM) revealed that the resulting ZnO particles via hydrothermal process exhibit micro–nano dual-scale morphology with high purity under a suitable surfactant amount and alkali concentration. The grafting of FEVE derivative was confirmed by Fourier transform infrared spectroscopy (FTIR) and energy-dispersive X-ray spectrometer (EDS), suggesting that hierarchical surface of ZnO particles was an imported monomolecular layer of fluorocarbon polymer. The obtained surface fabricated by drop-casting shows considerably high contact angle and good resistance to water immersion. The wetting behavior in this work was furthermore analyzed by theoretical wetting model. This work demonstrates that the sufficient low-wettable surface and high roughness both take a vital role in the superhydrophobic behavior.

  9. Clinical, laboratory, and demographic determinants of hospitalization due to dengue in 7613 patients: A retrospective study based on hierarchical models.

    Science.gov (United States)

    da Silva, Natal Santos; Undurraga, Eduardo A; da Silva Ferreira, Elis Regina; Estofolete, Cássia Fernanda; Nogueira, Maurício Lacerda

    2018-01-01

    In Brazil, the incidence of hospitalization due to dengue, as an indicator of severity, has drastically increased since 1998. The objective of our study was to identify risk factors associated with subsequent hospitalization related to dengue. We analyzed 7613 dengue confirmed via serology (ELISA), non-structural protein 1, or polymerase chain reaction amplification. We used a hierarchical framework to generate a multivariate logistic regression based on a variety of risk variables. This was followed by multiple statistical analyses to assess hierarchical model accuracy, variance, goodness of fit, and whether or not this model reliably represented the population. The final model, which included age, sex, ethnicity, previous dengue infection, hemorrhagic manifestations, plasma leakage, and organ failure, showed that all measured parameters, with the exception of previous dengue, were statistically significant. The presence of organ failure was associated with the highest risk of subsequent dengue hospitalization (OR=5·75; CI=3·53-9·37). Therefore, plasma leakage and organ failure were the main indicators of hospitalization due to dengue, although other variables of minor importance should also be considered to refer dengue patients to hospital treatment, which may lead to a reduction in avoidable deaths as well as costs related to dengue. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. A Hierarchically Micro-Meso-Macroporous Zeolite CaA for Methanol Conversion to Dimethyl Ether

    Directory of Open Access Journals (Sweden)

    Yan Wang

    2016-11-01

    Full Text Available A hierarchical zeolite CaA with microporous, mesoporous and macroporous structure was hydrothermally synthesized by a ”Bond-Blocking” method using organo-functionalized mesoporous silica (MS as a silica source. The characterization by XRD, SEM/TEM and N2 adsorption/desorption techniques showed that the prepared material had well-crystalline zeolite Linde Type A (LTA topological structure, microspherical particle morphologies, and hierarchically intracrystalline micro-meso-macropores structure. With the Bond-Blocking principle, the external surface area and macro-mesoporosity of the hierarchical zeolite CaA can be adjusted by varying the organo-functionalized degree of the mesoporous silica surface. Similarly, the distribution of the micro-meso-macroporous structure in the zeolite CaA can be controlled purposely. Compared with the conventional microporous zeolite CaA, the hierarchical zeolite CaA as a catalyst in the conversion of methanol to dimethyl ether (DME, exhibited complete DME selectivity and stable catalytic activity with high methanol conversion. The catalytic performances of the hierarchical zeolite CaA results clearly from the micro-meso-macroporous structure, improving diffusion properties, favoring the access to the active surface and avoiding secondary reactions (no hydrocarbon products were detected after 3 h of reaction.

  11. Hierarchical structure observation and nanoindentation size effect characterization for a limnetic shell

    Science.gov (United States)

    Song, Jingru; Fan, Cuncai; Ma, Hansong; Wei, Yueguang

    2015-06-01

    In the present research, hierarchical structure observation and mechanical property characterization for a type of biomaterial are carried out. The investigated biomaterial is Hyriopsis cumingii, a typical limnetic shell, which consists of two different structural layers, a prismatic "pillar" structure and a nacreous "brick and mortar" structure. The prismatic layer looks like a "pillar forest" with variation-section pillars sized on the order of several tens of microns. The nacreous material looks like a "brick wall" with bricks sized on the order of several microns. Both pillars and bricks are composed of nanoparticles. The mechanical properties of the hierarchical biomaterial are measured by using the nanoindentation test. Hardness and modulus are measured for both the nacre layer and the prismatic layer, respectively. The nanoindentation size effects for the hierarchical structural materials are investigated experimentally. The results show that the prismatic nanostructured material has a higher stiffness and hardness than the nacre nanostructured material. In addition, the nanoindentation size effects for the hierarchical structural materials are described theoretically, by using the trans-scale mechanics theory considering both strain gradient effect and the surface/interface effect. The modeling results are consistent with experimental ones.

  12. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

    2014-01-01

    -parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

  13. Hierarchical tone mapping for high dynamic range image visualization

    Science.gov (United States)

    Qiu, Guoping; Duan, Jiang

    2005-07-01

    In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

  14. Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

    Science.gov (United States)

    Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.

    2011-01-01

    Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American

  15. The hierarchical nature of the spin alignment of dark matter haloes in filaments

    Science.gov (United States)

    Aragon-Calvo, M. A.; Yang, Lin Forrest

    2014-05-01

    Dark matter haloes in cosmological filaments and walls have (in average) their spin vector aligned with their host structure. While haloes in walls are aligned with the plane of the wall independently of their mass, haloes in filaments present a mass-dependent two-regime orientation. Here, we show that the transition mass determining the change in the alignment regime (from parallel to perpendicular) depends on the hierarchical level in which the halo is located, reflecting the hierarchical nature of the Cosmic Web. By explicitly exposing the hierarchical structure of the Cosmic Web, we are able to identify the contributions of different components of the filament network to the alignment signal. We propose a unifying picture of angular momentum acquisition that is based on the results presented here and previous results found by other authors. In order to do a hierarchical characterization of the Cosmic Web, we introduce a new implementation of the multiscale morphology filter, the MMF-2, that significantly improves the identification of structures and explicitly describes their hierarchy. L36

  16. Fabrication and condensation characteristics of metallic superhydrophobic surface with hierarchical micro-nano structures

    Science.gov (United States)

    Chu, Fuqiang; Wu, Xiaomin

    2016-05-01

    Metallic superhydrophobic surfaces have various applications in aerospace, refrigeration and other engineering fields due to their excellent water repellent characteristics. This study considers a simple but widely applicable fabrication method using a two simultaneous chemical reactions method to prepare the acid-salt mixed solutions to process the metal surfaces with surface deposition and surface etching to construct hierarchical micro-nano structures on the surface and then modify the surface with low surface-energy materials. Al-based and Cu-based superhydrophobic surfaces were fabricated using this method. The Al-based superhydrophobic surface had a water contact angle of 164° with hierarchical micro-nano structures similar to the lotus leaves. The Cu-based surface had a water contact angle of 157° with moss-like hierarchical micro-nano structures. Droplet condensation experiments were also performed on these two superhydrophobic surfaces to investigate their condensation characteristics. The results show that the Al-based superhydrophobic surface has lower droplet density, higher droplet jumping probability, slower droplet growth rate and lower surface coverage due to the more structured hierarchical structures.

  17. Colloidal quantum dot solar cells exploiting hierarchical structuring

    KAUST Repository

    Labelle, André J.

    2015-02-11

    Extremely thin-absorber solar cells offer low materials utilization and simplified manufacture but require improved means to enhance photon absorption in the active layer. Here, we report enhanced-absorption colloidal quantum dot (CQD) solar cells that feature transfer-stamped solution-processed pyramid-shaped electrodes employed in a hierarchically structured device. The pyramids increase, by up to a factor of 2, the external quantum efficiency of the device at absorption-limited wavelengths near the absorber band edge. We show that absorption enhancement can be optimized with increased pyramid angle with an appreciable net improvement in power conversion efficiency, that is, with the gain in current associated with improved absorption and extraction overcoming the smaller fractional decrease in open-circuit voltage associated with increased junction area. We show that the hierarchical combination of micron-scale structured electrodes with nanoscale films provides for an optimized enhancement at absorption-limited wavelengths. We fabricate 54.7° pyramid-patterned electrodes, conformally apply the quantum dot films, and report pyramid CQD solar cells that exhibit a 24% improvement in overall short-circuit current density with champion devices providing a power conversion efficiency of 9.2%.

  18. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  19. Hierarchical control of electron-transfer

    DEFF Research Database (Denmark)

    Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis

    1997-01-01

    In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

  20. A hierarchical cluster analysis of normal-tension glaucoma using spectral-domain optical coherence tomography parameters.

    Science.gov (United States)

    Bae, Hyoung Won; Ji, Yongwoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

    2015-01-01

    Normal-tension glaucoma (NTG) is a heterogenous disease, and there is still controversy about subclassifications of this disorder. On the basis of spectral-domain optical coherence tomography (SD-OCT), we subdivided NTG with hierarchical cluster analysis using optic nerve head (ONH) parameters and retinal nerve fiber layer (RNFL) thicknesses. A total of 200 eyes of 200 NTG patients between March 2011 and June 2012 underwent SD-OCT scans to measure ONH parameters and RNFL thicknesses. We classified NTG into homogenous subgroups based on these variables using a hierarchical cluster analysis, and compared clusters to evaluate diverse NTG characteristics. Three clusters were found after hierarchical cluster analysis. Cluster 1 (62 eyes) had the thickest RNFL and widest rim area, and showed early glaucoma features. Cluster 2 (60 eyes) was characterized by the largest cup/disc ratio and cup volume, and showed advanced glaucomatous damage. Cluster 3 (78 eyes) had small disc areas in SD-OCT and were comprised of patients with significantly younger age, longer axial length, and greater myopia than the other 2 groups. A hierarchical cluster analysis of SD-OCT scans divided NTG patients into 3 groups based upon ONH parameters and RNFL thicknesses. It is anticipated that the small disc area group comprised of younger and more myopic patients may show unique features unlike the other 2 groups.

  1. Stress generation and hierarchical fracturing in reactive systems

    Science.gov (United States)

    Jamtveit, B.; Iyer, K.; Royne, A.; Malthe-Sorenssen, A.; Mathiesen, J.; Feder, J.

    2007-12-01

    Hierarchical fracture patterns are the result of a slowly driven fracturing process that successively divides the rocks into smaller domains. In quasi-2D systems, such fracture patterns are characterized by four sided domains, and T-junctions where new fractures stop at right angles to pre-existing fractures. We describe fracturing of mm to dm thick enstatite layers in a dunite matrix from the Leka ophiolite complex in Norway. The fracturing process is driven by expansion of the dunite matrix during serpentinization. The cumulative distributions of fracture lengths show a scaling behavior that lies between a log - normal and power law (fractal) distribution. This is consistent with a simple fragmentation model in which domains are divided according to a 'top hat' distribution of new fracture positions within unfractured domains. Reaction-assisted hierarchical fracturing is also likely to be responsible for other (3-D) structures commonly observed in serpentinized ultramafic rocks, including the mesh-textures observed in individual olivine grains, and the high abundance of rectangular domains at a wide range of scales. Spectacular examples of 3-D hierarchical fracture patterns also form during the weathering of basaltic intrusions (dolerites). Incipient chemical weathering of dolerites in the Karoo Basin in South Africa occurs around water- filled fractures, originally produced by thermal contraction or by externally imposed stresses. This chemical weathering causes local expansion of the rock matrix and generates elastic stresses. On a mm to cm scale, these stresses lead to mechanical layer-by-layer spalling, producing the characteristic spheroidal weathering patterns. However, our field observations and computer simulations demonstrate that in confined environments, the spalling process alone is unable to relieve the elastic stresses. In such cases, chemical weathering drives a much larger scale hierarchical fracturing process in which fresh dolerite undergoes a

  2. A reward optimization method based on action subrewards in hierarchical reinforcement learning.

    Science.gov (United States)

    Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

    2014-01-01

    Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

  3. Topology of the correlation networks among major currencies using hierarchical structure methods

    Science.gov (United States)

    Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

    2011-02-01

    We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

  4. Biomedical application of hierarchically built structures based on metal oxides

    Science.gov (United States)

    Korovin, M. S.; Fomenko, A. N.

    2017-12-01

    Nowadays, the use of hierarchically built structures in biology and medicine arouses much interest. The aim of this work is to review and summarize the available literature data about hierarchically organized structures in biomedical application. Nanoparticles can serve as an example of such structures. Medicine holds a special place among various application methods of similar systems. Special attention is paid to inorganic nanoparticles based on different metal oxides and hydroxides, such as iron, zinc, copper, and aluminum. Our investigations show that low-dimensional nanostructures based on aluminum oxides and hydroxides have an inhibitory effect on tumor cells and possess an antimicrobial activity. At the same time, it is obvious that the large-scale use of nanoparticles by humans needs to thoroughly study their properties. Special attention should be paid to the study of nanoparticle interaction with living biological objects. The numerous data show that there is no clear understanding of interaction mechanisms between nanoparticles and various cell types.

  5. Hierarchical subtask discovery with non-negative matrix factorization

    CSIR Research Space (South Africa)

    Earle, AC

    2018-04-01

    Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

  6. Hierarchical subtask discovery with non-negative matrix factorization

    CSIR Research Space (South Africa)

    Earle, AC

    2017-08-01

    Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

  7. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

    Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

    2017-01-01

    Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

  8. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  9. Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

    Science.gov (United States)

    Quist, M.C.; Rahel, F.J.; Hubert, W.A.

    2005-01-01

    Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

  10. Hierarchical organization of brain functional networks during visual tasks.

    Science.gov (United States)

    Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

    2011-09-01

    The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

  11. Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

    DEFF Research Database (Denmark)

    He, W.; Min, D.D.; Zhang, X.D.

    2014-01-01

    Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...... and products of catalytic reactions can freely diffuse through open mesopores (2–40 nm). The formation mechanism of hierarchically structured porous bioactive glasses, the immobilization mechanism of enzyme and the catalysis mechanism of immobilized enzyme are then discussed. The novel nanostructure...

  12. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  13. Superhydrophobic SERS substrates based on silicon hierarchical nanostructures

    Science.gov (United States)

    Chen, Xuexian; Wen, Jinxiu; Zhou, Jianhua; Zheng, Zebo; An, Di; Wang, Hao; Xie, Weiguang; Zhan, Runze; Xu, Ningsheng; Chen, Jun; She, Juncong; Chen, Huanjun; Deng, Shaozhi

    2018-02-01

    Silicon nanostructures have been cultivated as promising surface enhanced Raman scattering (SERS) substrates in terms of their low-loss optical resonance modes, facile functionalization, and compatibility with today’s state-of-the-art CMOS techniques. However, unlike their plasmonic counterparts, the electromagnetic field enhancements induced by silicon nanostructures are relatively small, which restrict their SERS sensing limit to around 10-7 M. To tackle this problem, we propose here a strategy for improving the SERS performance of silicon nanostructures by constructing silicon hierarchical nanostructures with a superhydrophobic surface. The hierarchical nanostructures are binary structures consisted of silicon nanowires (NWs) grown on micropyramids (MPs). After being modified with perfluorooctyltriethoxysilane (PFOT), the nanostructure surface shows a stable superhydrophobicity with a high contact angle of ˜160°. The substrate can allow for concentrating diluted analyte solutions into a specific area during the evaporation of the liquid droplet, whereby the analytes are aggregated into a small volume and can be easily detected by the silicon nanostructure SERS substrate. The analyte molecules (methylene blue: MB) enriched from an aqueous solution lower than 10-8 M can be readily detected. Such a detection limit is ˜100-fold lower than the conventional SERS substrates made of silicon nanostructures. Additionally, the detection limit can be further improved by functionalizing gold nanoparticles onto silicon hierarchical nanostructures, whereby the superhydrophobic characteristics and plasmonic field enhancements can be combined synergistically to give a detection limit down to ˜10-11 M. A gold nanoparticle-functionalized superhydrophobic substrate was employed to detect the spiked melamine in liquid milk. The results showed that the detection limit can be as low as 10-5 M, highlighting the potential of the proposed superhydrophobic SERS substrate in

  14. Hierarchical modeling and its numerical implementation for layered thin elastic structures

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

    2017-05-15

    Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

  15. GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

    Science.gov (United States)

    Miki, Yohei; Umemura, Masayuki

    2017-04-01

    The tree method is a widely implemented algorithm for collisionless N-body simulations in astrophysics well suited for GPU(s). Adopting hierarchical time stepping can accelerate N-body simulations; however, it is infrequently implemented and its potential remains untested in GPU implementations. We have developed a Gravitational Oct-Tree code accelerated by HIerarchical time step Controlling named GOTHIC, which adopts both the tree method and the hierarchical time step. The code adopts some adaptive optimizations by monitoring the execution time of each function on-the-fly and minimizes the time-to-solution by balancing the measured time of multiple functions. Results of performance measurements with realistic particle distribution performed on NVIDIA Tesla M2090, K20X, and GeForce GTX TITAN X, which are representative GPUs of the Fermi, Kepler, and Maxwell generation of GPUs, show that the hierarchical time step achieves a speedup by a factor of around 3-5 times compared to the shared time step. The measured elapsed time per step of GOTHIC is 0.30 s or 0.44 s on GTX TITAN X when the particle distribution represents the Andromeda galaxy or the NFW sphere, respectively, with 224 = 16,777,216 particles. The averaged performance of the code corresponds to 10-30% of the theoretical single precision peak performance of the GPU.

  16. The Realized Hierarchical Archimedean Copula in Risk Modelling

    Directory of Open Access Journals (Sweden)

    Ostap Okhrin

    2017-06-01

    Full Text Available This paper introduces the concept of the realized hierarchical Archimedean copula (rHAC. The proposed approach inherits the ability of the copula to capture the dependencies among financial time series, and combines it with additional information contained in high-frequency data. The considered model does not suffer from the curse of dimensionality, and is able to accurately predict high-dimensional distributions. This flexibility is obtained by using a hierarchical structure in the copula. The time variability of the model is provided by daily forecasts of the realized correlation matrix, which is used to estimate the structure and the parameters of the rHAC. Extensive simulation studies show the validity of the estimator based on this realized correlation matrix, and its performance, in comparison to the benchmark models. The application of the estimator to one-day-ahead Value at Risk (VaR prediction using high-frequency data exhibits good forecasting properties for a multivariate portfolio.

  17. Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

    Science.gov (United States)

    Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

    2017-10-12

    The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

  18. Logistic regression applied to natural hazards: rare event logistic regression with replications

    OpenAIRE

    Guns, M.; Vanacker, Veerle

    2012-01-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

  19. Priority-Based Hierarchical Operational Management for Multiagent-Based Microgrids

    Directory of Open Access Journals (Sweden)

    Takumi Kato

    2014-03-01

    Full Text Available Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters.

  20. Hierarchical capitalism in Latin America: Comparative analysis with other economies

    Directory of Open Access Journals (Sweden)

    Edgar J. Saucedo A.

    2015-12-01

    Full Text Available Purpose – The purpose of this paper is to compare the three largest economies in Latin America (Brazil, Mexico and Argentina with other economies that have another type of capitalism, in that way we can extract some effects of the hierarchical capitalism in Latin America Design/methodology/approach – The data were taken from World Economic Outlook (IMF, The Global Innovation Index (INSEADand the Democracy Index (The Economist. The selected countries are: Argentina, Brazil, Mexico, South Korea, Spain and Croatia. We establish a comparison among countries in the following dimensions: economic growth, innovation and democracy. Findings – The comparison shows that Argentina, Brazil and Mexico have lower level of economic growth, innovation performance and democracy level than South Korea, Spain and Croatia. The variety of capitalism in Latin America (hierarchical has lower performance than others kinds of capitalism in other regions of the world. Research limitations/implications – We have compared Latin American countries with countries from other regions of the world. However, a comparison may include more countries and results could vary. Originality/value – The results tend to support the idea that hierarchical capitalism has poor results in comparison with other varieties of capitalism.

  1. Ultra-low Thermal Conductivity in Si/Ge Hierarchical Superlattice Nanowire.

    Science.gov (United States)

    Mu, Xin; Wang, Lili; Yang, Xueming; Zhang, Pu; To, Albert C; Luo, Tengfei

    2015-11-16

    Due to interfacial phonon scattering and nanoscale size effect, silicon/germanium (Si/Ge) superlattice nanowire (SNW) can have very low thermal conductivity, which is very attractive for thermoelectrics. In this paper, we demonstrate using molecular dynamics simulations that the already low thermal conductivity of Si/Ge SNW can be further reduced by introducing hierarchical structure to form Si/Ge hierarchical superlattice nanowire (H-SNW). The structural hierarchy introduces defects to disrupt the periodicity of regular SNW and scatters coherent phonons, which are the key contributors to thermal transport in regular SNW. Our simulation results show that periodically arranged defects in Si/Ge H-SNW lead to a ~38% reduction of the already low thermal conductivity of regular Si/Ge SNW. By randomizing the arrangement of defects and imposing additional surface complexities to enhance phonon scattering, further reduction in thermal conductivity can be achieved. Compared to pure Si nanowire, the thermal conductivity reduction of Si/Ge H-SNW can be as large as ~95%. It is concluded that the hierarchical structuring is an effective way of reducing thermal conductivity significantly in SNW, which can be a promising path for improving the efficiency of Si/Ge-based SNW thermoelectrics.

  2. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Directory of Open Access Journals (Sweden)

    Zhao Liu

    Full Text Available Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  3. Structural and photovoltaic characteristics of hierarchical ZnO nanostructures electrodes

    Energy Technology Data Exchange (ETDEWEB)

    Saleem, Muhammad, E-mail: saleem.malikape@gmail.com [Department of Physics, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044 (China); Fang, L. [Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044 (China); Shaukat, Saleem F.; Ahmad, M. Ashfaq [Department of Physics, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Raza, Rizwan, E-mail: razahussaini786@gmail.com [Department of Physics, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Akhtar, Majid Niaz; Jamil, Ayesha; Aslam, Samia [Department of Physics, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Abbas, Ghazanfar [Department of Physics, COMSATS Institute of Information Technology, Islamabad 44000 (Pakistan)

    2015-04-15

    Highlights: • Hierarchically ZnO nanostructures electrodes were grown using hot plate magnetic stirring at different growth reaction temperature. • We have investigated the effect of working temperature of 160°, 170°, 180°, and 190° on the growth mechanism of nanospheres and on the power conversion efficiency of DSSCs. • ZnO nanospheres with perfect aggregation show superior power conversion efficiency of 1.24% which is about 83% higher than nanoparticles DSSC. • An obvious vogue is that the overall power conversion efficiency decreases as the degree of the spherical aggregation is gradually destroyed. - Abstract: Structural and photovoltaic characteristics of hierarchical ZnO nanostructures solar cell have been studied in relation to growth reaction temperature. It is found that the hierarchical ZnO nanostructures network to act not only as large surface area substrates but also as a transport medium for electrons injected from the dye molecules. The incident photon-to-current conversion efficiency is decreased by increasing the growth reaction temperature of ZnO electrodes. The best conversion efficiency of a 0.25 cm{sup 2} cell is measured to be 1.24% under 100 mW cm{sup −2} irradiation.

  4. Structural and photovoltaic characteristics of hierarchical ZnO nanostructures electrodes

    International Nuclear Information System (INIS)

    Saleem, Muhammad; Fang, L.; Shaukat, Saleem F.; Ahmad, M. Ashfaq; Raza, Rizwan; Akhtar, Majid Niaz; Jamil, Ayesha; Aslam, Samia; Abbas, Ghazanfar

    2015-01-01

    Highlights: • Hierarchically ZnO nanostructures electrodes were grown using hot plate magnetic stirring at different growth reaction temperature. • We have investigated the effect of working temperature of 160°, 170°, 180°, and 190° on the growth mechanism of nanospheres and on the power conversion efficiency of DSSCs. • ZnO nanospheres with perfect aggregation show superior power conversion efficiency of 1.24% which is about 83% higher than nanoparticles DSSC. • An obvious vogue is that the overall power conversion efficiency decreases as the degree of the spherical aggregation is gradually destroyed. - Abstract: Structural and photovoltaic characteristics of hierarchical ZnO nanostructures solar cell have been studied in relation to growth reaction temperature. It is found that the hierarchical ZnO nanostructures network to act not only as large surface area substrates but also as a transport medium for electrons injected from the dye molecules. The incident photon-to-current conversion efficiency is decreased by increasing the growth reaction temperature of ZnO electrodes. The best conversion efficiency of a 0.25 cm 2 cell is measured to be 1.24% under 100 mW cm −2 irradiation

  5. Hierarchical surfaces for enhanced self-cleaning applications

    Science.gov (United States)

    Fernández, Ariadna; Francone, Achille; Thamdrup, Lasse H.; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus; Sotomayor Torres, Clivia M.; Kehagias, Nikolaos

    2017-04-01

    In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets.

  6. CTAB-Assisted Hydrothermal Synthesis of WO3 Hierarchical Porous Structures and Investigation of Their Sensing Properties

    Directory of Open Access Journals (Sweden)

    Dan Meng

    2015-01-01

    Full Text Available WO3 hierarchical porous structures were successfully synthesized via cetyltrimethylammonium bromide- (CTAB- assisted hydrothermal method. The structure and morphology were investigated using scanning electron microscope, X-ray diffractometer, transmission electron microscopy, X-ray photoelectron spectra, Brunauer-Emmett-Teller nitrogen adsorption-desorption, and thermogravimetry and differential thermal analysis. The result demonstrated that WO3 hierarchical porous structures with an orthorhombic structure were constructed by a number of nanoparticles about 50–100 nm in diameters. The H2 gas sensing measurements showed that well-defined WO3 hierarchical porous structures with a large specific surface area exhibited the higher sensitivity compared with products without CTAB at all operating temperatures. Moreover, the reversible and fast response to H2 gas and good selectivity were obtained. The results indicated that the WO3 hierarchical porous structures are promising materials for gas sensors.

  7. Synthesis of belt-like BiOBr hierarchical nanostructure with high photocatalytic performance

    Energy Technology Data Exchange (ETDEWEB)

    Li, Haiping [National Engineering Technology Research Center for Colloidal Materials, Shandong University, Jinan 250100 (China); Liu, Jingyi; Hu, Tingxia [Environment Research Institute, Shandong University, Jinan 250100 (China); Du, Na; Song, Shue [Key Laboratory of Colloid and Interface Chemistry (Ministry of Education), Shandong University, Jinan 250100 (China); Hou, Wanguo, E-mail: wghou@sdu.edu.cn [Key Laboratory of Colloid and Interface Chemistry (Ministry of Education), Shandong University, Jinan 250100 (China)

    2016-05-15

    Highlights: • BiOBr hierarchical nanobelts (NBs) were solvothermally prepared. • NBs show higher specific surface area and photoabsorption than BiOBr nanosheets. • NBs exhibit higher photoactivity than the nanosheets. - Abstract: One-dimensional (1D) bismuth oxyhalide (BiOX) hierarchical nanostructures are always difficult to prepare. Herein, we report, for the first time, a simple synthesis of BiOBr nanobelts (NBs) via a facile solvothermal route, using bismuth subsalicylate as the template and bismuth source. The BiOBr nanobelts are composed of irregular single crystal nanoparticles with highly exposed (0 1 0) facets. Compared with the BiOBr nanosheets (NSs) with dominant exposed (0 0 1) facets, they exhibit higher photocatalytic activity toward degradation of Rhodamine B and Methylene Blue under visible light irradiation. The higher photocatalytic performance of BiOBr NBs arises from their larger specific surface area and higher photoabsorption capability. This study provides a simple route for synthesis of belt-like Bi-based hierarchical nanostructures.

  8. Action detection by double hierarchical multi-structure space-time statistical matching model

    Science.gov (United States)

    Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

    2018-03-01

    Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

  9. Catalytically active and hierarchically porous SAPO-11 zeolite synthesized in the presence of polyhexamethylene biguanidine

    KAUST Repository

    Liu, Yan

    2014-03-01

    Hierarchically porous SAPO-11 zeolite (H-SAPO-11) is rationally synthesized from a starting silicoaluminophosphate gel in the presence of polyhexamethylene biguanidine as a mesoscale template. The sample is well characterized by XRD, N2 sorption, SEM, TEM, NMR, XPS, NH3-TPD, and TG techniques. The results show that the sample obtained has good crystallinity, hierarchical porosity (mesopores at ca. 10nm and macropores at ca. 50-200nm), high BET surface area (226m2/g), large pore volume (0.25cm3/g), and abundant medium and strong acidic sites (0.36mmol/g). After loading Pt (0.5wt.%) on H-SAPO-11 by using wet impregnation method, catalytic hydroisomerization tests of n-dodecane show that the hierarchical Pt/SAPO-11 zeolite exhibits high conversion of n-dodecane and enhanced selectivity for branched products as well as reduced selectivity for cracking products, compared with conventional Pt/SAPO-11 zeolite. This phenomenon is reasonably attributed to the presence of hierarchical porosity, which is favorable for access of reactants on catalytically active sites. The improvement in catalytic performance in long-chain paraffin hydroisomerization over Pt/SAPO-11-based catalyst is of great importance for its industrial applications in the future. © 2013 Elsevier Inc.

  10. Hierarchical Micro-Nano Coatings by Painting

    Science.gov (United States)

    Kirveslahti, Anna; Korhonen, Tuulia; Suvanto, Mika; Pakkanen, Tapani A.

    2016-03-01

    In this paper, the wettability properties of coatings with hierarchical surface structures and low surface energy were studied. Hierarchically structured coatings were produced by using hydrophobic fumed silica nanoparticles and polytetrafluoroethylene (PTFE) microparticles as additives in polyester (PES) and polyvinyldifluoride (PVDF). These particles created hierarchical micro-nano structures on the paint surfaces and lowered or supported the already low surface energy of the paint. Two standard application techniques for paint application were employed and the presented coatings are suitable for mass production and use in large surface areas. By regulating the particle concentrations, it was possible to modify wettability properties gradually. Highly hydrophobic surfaces were achieved with the highest contact angle of 165∘. Dynamic contact angle measurements were carried out for a set of selected samples and low hysteresis was obtained. Produced coatings possessed long lasting durability in the air and in underwater conditions.

  11. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  12. Hierarchical virtual screening approaches in small molecule drug discovery.

    Science.gov (United States)

    Kumar, Ashutosh; Zhang, Kam Y J

    2015-01-01

    Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. A hierarchical instrumental decision theory of nicotine dependence.

    Science.gov (United States)

    Hogarth, Lee; Troisi, Joseph R

    2015-01-01

    It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.

  14. A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube

    Science.gov (United States)

    Zou, Shuzhi; Zhao, Li; Hu, Kongfa

    The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.

  15. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  16. Oral diseases associated with condition-specific oral health-related quality of life and school performance of Thai primary school children: A hierarchical approach.

    Science.gov (United States)

    Kaewkamnerdpong, Issarapong; Krisdapong, Sudaduang

    2018-06-01

    To assess the hierarchical associations between children's school performance and condition-specific (CS) oral health-related quality of life (OHRQoL), school absence, oral status, sociodemographic and economic status (SDES) and social capital; and to investigate the associations between CS OHRQoL and related oral status, adjusting for SDES and social capital. Data on 925 sixth grade children in Sakaeo province, Thailand, were collected through oral examinations for dental caries and oral hygiene, social capital questionnaires, OHRQoL interviews using the Child-Oral Impacts on Daily Performances index, parental self-administered questionnaires and school documents. A hierarchical conceptual framework was developed, and independent variables were hierarchically entered into multiple logistic models for CS OHRQoL and linear regression models for school performance. After adjusting for SDES and social capital, children with high DMFT or DT scores were significantly threefold more likely to have CS impacts attributed to dental caries. However, poor oral hygiene was not significantly associated with CS impacts attributed to gingival disease. High DMFT scores were significantly associated with lower school performance, whereas high Simplified Oral Hygiene Index scores were not. The final model showed that CS impacts attributed to dental caries and school absence accounted for the association between DMFT score and school performance. Dental caries was associated with CS impacts on OHRQoL, and exerted its effect on school performance through the CS impacts and school absence. There was no association between oral hygiene and CS impacts on OHRQoL or school performance. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

    Science.gov (United States)

    Tsai, F. T. C.; Elshall, A. S.

    2014-12-01

    Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

  18. A simple approach to power and sample size calculations in logistic regression and Cox regression models.

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

    For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

  19. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-01-01

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  20. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  1. Improved SIRAP analysis for synchronization in hierarchical scheduled real-time systems

    NARCIS (Netherlands)

    Behnam, M.; Bril, R.J.; Nolte, T.

    2009-01-01

    We present our ongoing work on synchronization in hierarchical scheduled real-time systems, where tasks are scheduled using fixed-priority pre-emptive scheduling. In this paper, we show that the original local schedulability analysis of the synchronization protocol SIRAP [4] is very pessimistic when

  2. Hierarchical surfaces for enhanced self-cleaning applications

    International Nuclear Information System (INIS)

    Fernández, Ariadna; Francone, Achille; Sotomayor Torres, Clivia M; Kehagias, Nikolaos; Thamdrup, Lasse H; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus

    2017-01-01

    In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets. (paper)

  3. Hierarchical processing in the prefrontal cortex in a variety of cognitive domains

    Directory of Open Access Journals (Sweden)

    Hyeon-Ae eJeon

    2014-11-01

    Full Text Available This review scrutinizes several findings on human hierarchical processing within the prefrontal cortex (PFC in diverse cognitive domains. Converging evidence from previous studies has shown that the PFC, specifically Brodmann area (BA 44, may function as the essential region for hierarchical processing across the domains. In language fMRI studies, BA 44 was significantly activated for the hierarchical processing of center-embedded sentences and this pattern of activations was also observed in artificial grammar. The same pattern was observed in the visuo-spatial domain where BA44 was actively involved in the processing of hierarchy for the visual symbol. Musical syntax, which is the rule-based arrangement of musical sets, has also been construed as hierarchical processing as in the language domain such that the activation in BA44 was observed in a chord sequence paradigm. P600 ERP was also engendered during the processing of musical hierarchy. Along with a longstanding idea that a human’s number faculty is developed as a by-product of language faculty, BA44 was closely involved in hierarchical processing in mental arithmetic. This review extended its discussion of hierarchical processing to hierarchical behavior, that is, human action which has been referred to as being hierarchically composed. Several lesion and TMS studies supported the involvement of BA44 for hierarchical processing in the action domain. Lastly, the hierarchical organization of cognitive controls was discussed within the PFC, forming a cascade of top-down hierarchical processes operating along a posterior-to-anterior axis of the lateral PFC including BA44 within the network. It is proposed that PFC is actively involved in different forms of hierarchical processing and specifically BA44 may play an integral role in the process. Taking levels of proficiency and subcortical areas into consideration may provide further insight into the functional role of BA44 for hierarchical

  4. Mechanochemistry-assisted synthesis of hierarchical porous carbons applied as supercapacitors

    Science.gov (United States)

    Leistenschneider, Desirée; Jäckel, Nicolas; Hippauf, Felix; Presser, Volker

    2017-01-01

    A solvent-free synthesis of hierarchical porous carbons is conducted by a facile and fast mechanochemical reaction in a ball mill. By means of a mechanochemical ball-milling approach, we obtained titanium(IV) citrate-based polymers, which have been processed via high temperature chlorine treatment to hierarchical porous carbons with a high specific surface area of up to 1814 m2 g−1 and well-defined pore structures. The carbons are applied as electrode materials in electric double-layer capacitors showing high specific capacitances with 98 F g−1 in organic and 138 F g−1 in an ionic liquid electrolyte as well as good rate capabilities, maintaining 87% of the initial capacitance with 1 M TEA-BF4 in acetonitrile (ACN) and 81% at 10 A g−1 in EMIM-BF4. PMID:28781699

  5. Hierarchical Ag mesostructures for single particle SERS substrate

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Minwei, E-mail: xuminwei@xjtu.edu.cn; Zhang, Yin

    2017-01-30

    Highlights: • Hierarchical Ag mesostructures with the size of 250, 360 and 500 nm are synthesized via a seed-mediated approach. • The Ag mesostructures present the tailorable size and highly roughened surfaces. • The average enhancement factors for individual Ag mesostructures were estimated to be as high as 10{sup 6}. - Abstract: Hierarchical Ag mesostructures with highly rough surface morphology have been synthesized at room temperature through a simple seed-mediated approach. Electron microscopy characterizations indicate that the obtained Ag mesostructures exhibit a textured surface morphology with the flower-like architecture. Moreover, the particle size can be tailored easily in the range of 250–500 nm. For the growth process of the hierarchical Ag mesostructures, it is believed that the self-assembly mechanism is more reasonable rather than the epitaxial overgrowth of Ag seed. The oriented attachment of nanoparticles is revealed during the formation of Ag mesostructures. Single particle surface enhanced Raman spectra (sp-SERS) of crystal violet adsorbed on the hierarchical Ag mesostructures were measured. Results reveal that the hierarchical Ag mesostructures can be highly sensitive sp-SERS substrates with good reproducibility. The average enhancement factors for individual Ag mesostructures are estimated to be about 10{sup 6}.

  6. Preparation of hierarchical porous Zn-salt particles and their superhydrophobic performance

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Dahai; Jia, Mengqiu, E-mail: jiamq@mail.buct.edu.cn

    2015-12-30

    Graphical abstract: - Highlights: • Hierarchical particles with high roughness were prepared by modified hydrothermal route. • The high roughness is provided by extremely low thickness of sheet crystals. • FEVE polymer derivative was used for surface treatment of hierarchical surface. • The novel particles via surface treatment were firstly used as superhydrophobic materials. • The product properties were compared with multi-scale ZnO particles via conventional route. - Abstract: Superhydrophobic surfaces arranged by hierarchical porous particles were prepared using modified hydrothermal routes under the effect of sodium citrate. Two particle samples were generated in the medium of hexamethylenetetramine (P1) and urea (P2), respectively. X-ray diffraction, scanning electron microscope, and transmission electron microscope were adopted for the investigation, and results revealed that the P1 and P2 particles are porous microspheres with crosslinked extremely thin (10–30 nm) sheet crystals composed of Zn{sub 5}(OH){sub 8}Ac{sub 2}·2H{sub 2}O and Zn{sub 5}(CO{sub 3}){sub 2}(OH){sub 6}, respectively. The prepared particles were treated with a fluoroethylene vinyl ether derivative and studied using Fourier transform infrared spectroscopy and energy-dispersive X-ray spectrometer. Results showed that the hierarchical surfaces of these particles were combined with low-wettable fluorocarbon layers. Moreover, the fabricated surface composed of the prepared hierarchical particles displayed considerably high contact angles, indicating great superhydrophobicity for the products. The wetting behavior of the particles was analyzed with a theoretical wetting model in comparison with that of chestnut-like ZnO products obtained through a conventional hydrothermal route. Correspondingly, this study provided evidence that high roughness surface plays a great role in superhydrophobic behavior.

  7. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  8. Hierarchically nested river landform sequences

    Science.gov (United States)

    Pasternack, G. B.; Weber, M. D.; Brown, R. A.; Baig, D.

    2017-12-01

    River corridors exhibit landforms nested within landforms repeatedly down spatial scales. In this study we developed, tested, and implemented a new way to create river classifications by mapping domains of fluvial processes with respect to the hierarchical organization of topographic complexity that drives fluvial dynamism. We tested this approach on flow convergence routing, a morphodynamic mechanism with different states depending on the structure of nondimensional topographic variability. Five nondimensional landform types with unique functionality (nozzle, wide bar, normal channel, constricted pool, and oversized) represent this process at any flow. When this typology is nested at base flow, bankfull, and floodprone scales it creates a system with up to 125 functional types. This shows how a single mechanism produces complex dynamism via nesting. Given the classification, we answered nine specific scientific questions to investigate the abundance, sequencing, and hierarchical nesting of these new landform types using a 35-km gravel/cobble river segment of the Yuba River in California. The nested structure of flow convergence routing landforms found in this study revealed that bankfull landforms are nested within specific floodprone valley landform types, and these types control bankfull morphodynamics during moderate to large floods. As a result, this study calls into question the prevailing theory that the bankfull channel of a gravel/cobble river is controlled by in-channel, bankfull, and/or small flood flows. Such flows are too small to initiate widespread sediment transport in a gravel/cobble river with topographic complexity.

  9. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  10. Hierarchical porous nitrogen-doped partial graphitized carbon monoliths for supercapacitor

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Yifeng; Du, Juan; Liu, Lei; Wang, Guoxu; Zhang, Hongliang; Chen, Aibing, E-mail: chen-ab@163.com [Hebei University of Science and Technology, College of Chemical and Pharmaceutical Engineering (China)

    2017-03-15

    Porous carbon monoliths have attracted great interest in many fields due to their easy availability, large specific surface area, desirable electronic conductivity, and tunable pore structure. In this work, hierarchical porous nitrogen-doped partial graphitized carbon monoliths (N–MC–Fe) with ordered mesoporous have been successfully synthesized by using resorcinol-formaldehyde as precursors, iron salts as catalyst, and mixed triblock copolymers as templates via a one-step hydrothermal method. In the reactant system, hexamethylenetetramine (HMT) is used as nitrogen source and one of the carbon precursors under hydrothermal conditions instead of using toxic formaldehyde. The N–MC–Fe show hierarchically porous structures, with interconnected macroporous and ordered hexagonally arranged mesoporous. Nitrogen element is in situ doped into carbon through decomposition of HMT. Iron catalyst is helpful to improve the graphitization degree and pore volume of N–MC–Fe. The synthesis strategy is user-friendly, cost-effective, and can be easily scaled up for production. As supercapacitors, the N–MC–Fe show good capacity with high specific capacitance and good electrochemical stability.

  11. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  12. Packaging Glass with a Hierarchically Nanostructured Surface: A Universal Method to Achieve Self-Cleaning Omnidirectional Solar Cells

    KAUST Repository

    Lin, Chin An

    2015-12-01

    Fused-silica packaging glass fabricated with a hierarchical structure by integrating small (ultrathin nanorods) and large (honeycomb nanowalls) structures was demonstrated with exceptional light-harvesting solar performance, which is attributed to the subwavelength feature of the nanorods and an efficient scattering ability of the honeycomb nanowalls. Si solar cells covered with the hierarchically structured packaging glass exhibit enhanced conversion efficiency by 5.2% at normal incidence, and the enhancement went up to 46% at the incident angle of 60°. The hierarchical structured packaging glass shows excellent self-cleaning characteristics: 98.8% of the efficiency is maintained after 6 weeks of outdoor exposure, indicating that the nanostructured surface effectively repels polluting dust/particles. The presented self-cleaning omnidirectional light-harvesting design using the hierarchical structured packaging glass is a potential universal scheme for practical solar applications.

  13. Electrodeposition of hierarchical ZnO nanorod arrays on flexible stainless steel mesh for dye-sensitized solar cell

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Hui; Zhai, Xiangyang; Liu, Wenwu; Zhang, Mei; Guo, Min, E-mail: guomin@ustb.edu.cn

    2015-07-01

    Hierarchical ZnO nanorod arrays (ZNRAs) were synthesized on flexible stainless steel mesh (SSM) in large scale by a two-step facile electrodeposition method. The structure and morphology of the as-prepared samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM). The growth mechanism of the ZnO hierarchical nanostructures was also discussed. Moreover, the effect of ZnO morphology on the photovoltaic performance of the flexible DSSCs based on SSM supported ZnO nanostructures was investigated in detail. It is shown that the flexible DSSCs exhibited a relatively higher power conversion efficiency of 1.11% compared with that based on primary ZNRAs. - Highlights: • Hierarchical ZnO nanorod arrays (ZNRAs) were prepared by electrodeposition method. • Flexible stainless steel mesh (SSM) supported with hierarchical ZNRAs was first used for DSSCs. • The effect of ZnO morphology on the photovoltaic performance of flexible DSSCs was investigated. • The DSSC based on 3-Hierarchical ZNRAs/ZNPs showed a relatively efficiency of 1.11%.

  14. Nitrogen-doped hierarchical porous carbon materials prepared from meta-aminophenol formaldehyde resin for supercapacitor with high rate performance

    International Nuclear Information System (INIS)

    Zhou, Jin; Zhang, Zhongshen; Xing, Wei; Yu, Jing; Han, Guoxing; Si, Weijiang; Zhuo, Shuping

    2015-01-01

    Graphical abstract: N-doped hierarchical porous carbons with high rate capacitive performance are prepared by a combination method of nano-SiO 2 template/KOH activation. - Highlights: • A mass produced nano-SiO 2 is used to prepared hierarchical porous carbon. • N-doped hierarchical porous carbon materials are easily prepared. • The NHPCs materials exhibit a very high capacitance of up to 260.5 F g −1 . • The NHPC-800 sample shows very high rate capability. • Hierarchical porosity and N-doping synergistically enhances the whole capacitance. - Abstract: In this work, nitrogen-doped hierarchical porous carbon materials (NHPCs) are prepared by a two-step method combined of a hard template process and KOH-activation treatment. Low cost and large-scale commercial nano-SiO 2 are used as a hard template. The hierarchical porosity, structure and nitrogen-doped surface chemical properties are proved by a varies of means, such as scanning electron microscopy, transition electron microscopy, N 2 sorption, Raman spectroscopy, X-ray diffraction and X-ray photoelectron spectroscopy. When the prepared NHPCs materials are used as the electrode materials for supercapacitors in KOH electrolyte, they exhibit very high specific capacitance, good power capability and excellent cyclic stability. NHPC-800 carbon shows a high capacitance of 114.0 F g −1 at the current density of 40 A g −1 , responding to a high energy and power densities of 4.0 Wh kg −1 and 10 000 W kg −1 , and a very short drain time of 1.4 s. The excellent capacitive performance may be due to the synergistic effect of the hierarchical porosity, high effective surface area and heteroatom doping, resulting in both electrochemical double layer and Faradaic capacitance contributions

  15. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  16. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

    Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

  17. A hierarchical anatomical classification schema for prediction of phenotypic side effects.

    Science.gov (United States)

    Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh

    2018-01-01

    Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.

  18. Hierarchical composites: Analysis of damage evolution based on fiber bundle model

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon

    2011-01-01

    A computational model of multiscale composites is developed on the basis of the fiber bundle model with the hierarchical load sharing rule, and employed to study the effect of the microstructures of hierarchical composites on their damage resistance. Two types of hierarchical materials were consi...

  19. Hierarchical cellular designs for load-bearing biocomposite beams and plates

    International Nuclear Information System (INIS)

    Burgueno, Rigoberto; Quagliata, Mario J.; Mohanty, Amar K.; Mehta, Geeta; Drzal, Lawrence T.; Misra, Manjusri

    2005-01-01

    Scrutiny into the composition of natural, or biological materials convincingly reveals that high material and structural efficiency can be attained, even with moderate-quality constituents, by hierarchical topologies, i.e., successively organized material levels or layers. The present study demonstrates that biologically inspired hierarchical designs can help improve the moderate properties of natural fiber polymer composites or biocomposites and allow them to compete with conventional materials for load-bearing applications. An overview of the mechanics concepts that allow hierarchical designs to achieve higher performance is presented, followed by observation and results from flexural tests on periodic and hierarchical cellular beams and plates made from industrial hemp fibers and unsaturated polyester resin biocomposites. The experimental data is shown to agree well with performance indices predicted by mechanics models. A procedure for the multi-scale integrated material/structural analysis of hierarchical cellular biocomposite components is presented and its advantages and limitations are discussed

  20. Visual question answering using hierarchical dynamic memory networks

    Science.gov (United States)

    Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

    2018-04-01

    Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

  1. Mechanochemistry-assisted synthesis of hierarchical porous carbons applied as supercapacitors

    Directory of Open Access Journals (Sweden)

    Desirée Leistenschneider

    2017-07-01

    Full Text Available A solvent-free synthesis of hierarchical porous carbons is conducted by a facile and fast mechanochemical reaction in a ball mill. By means of a mechanochemical ball-milling approach, we obtained titanium(IV citrate-based polymers, which have been processed via high temperature chlorine treatment to hierarchical porous carbons with a high specific surface area of up to 1814 m2 g−1 and well-defined pore structures. The carbons are applied as electrode materials in electric double-layer capacitors showing high specific capacitances with 98 F g−1 in organic and 138 F g−1 in an ionic liquid electrolyte as well as good rate capabilities, maintaining 87% of the initial capacitance with 1 M TEA-BF4 in acetonitrile (ACN and 81% at 10 A g−1 in EMIM-BF4.

  2. Discursive Hierarchical Patterning in Law and Management Cases

    Science.gov (United States)

    Lung, Jane

    2008-01-01

    This paper investigates the differences in the discursive patterning of cases in Law and Management. It examines a corpus of 271 Law and Management cases and discusses the kind of information that these two disciplines call for and how discourses are constructed in discursive hierarchical patterns. A discursive hierarchical pattern is a model…

  3. Hierarchically porous MgCo2O4 nanochain networks: template-free synthesis and catalytic application

    Science.gov (United States)

    Guan, Xiangfeng; Yu, Yunlong; Li, Xiaoyan; Chen, Dagui; Luo, Peihui; Zhang, Yu; Guo, Shanxin

    2018-01-01

    In this work, hierarchically porous MgCo2O4 nanochain networks were successfully synthesized by a novel template-free method realized via a facile solvothermal synthesis followed by a heat treatment. The morphologies of MgCo2O4 precursor could be adjusted from nanosheets to nanobelts and finally to interwoven nanowires, depending on the volume ratio of diethylene glycol to deionized water in the solution. After calcination, the interwoven precursor nanowires were transformed to hierarchical MgCo2O4 nanochain networks with marco-/meso-porosity, which are composed of 10-20 nm nanoparticles connected one by one. Moreover, the relative formation mechanism of the MgCo2O4 nanochain networks was discussed. More importantly, when evaluated as catalytic additive for AP thermal decomposition, the MgCo2O4 nanochain networks show excellent accelerating effect. It is benefited from the unique hierarchically porous network structure and multicomponent effect, which effectively accelerates ammonia oxidation and {{{{ClO}}}4}- species dissociation. This approach opens the way to design other hierarchically porous multicomponent metal oxides.

  4. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

    Science.gov (United States)

    Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I

    2002-05-01

    Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.

  5. Hierarchical optimal control of large-scale nonlinear chemical processes.

    Science.gov (United States)

    Ramezani, Mohammad Hossein; Sadati, Nasser

    2009-01-01

    In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.

  6. Habits as action sequences: hierarchical action control and changes in outcome value.

    Science.gov (United States)

    Dezfouli, Amir; Lingawi, Nura W; Balleine, Bernard W

    2014-11-05

    Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  7. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    Dunson, David B

    2009-04-01

    In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

  8. Hierarchical silica particles by dynamic multicomponent assembly

    DEFF Research Database (Denmark)

    Wu, Z. W.; Hu, Q. Y.; Pang, J. B.

    2005-01-01

    Abstract: Aerosol-assisted assembly of mesoporous silica particles with hierarchically controllable pore structure has been prepared using cetyltrimethylammonium bromide (CTAB) and poly(propylene oxide) (PPO, H[OCH(CH3)CH2],OH) as co-templates. Addition of the hydrophobic PPO significantly...... influences the delicate hydrophilic-hydrophobic balance in the well-studied CTAB-silicate co-assembling system, resulting in various mesostructures (such as hexagonal, lamellar, and hierarchical structure). The co-assembly of CTAB, silicate clusters, and a low-molecular-weight PPO (average M-n 425) results...... in a uniform lamellar structure, while the use of a high-molecular-weight PPO (average M-n 2000), which is more hydrophobic, leads to the formation of hierarchical pore structure that contains meso-meso or meso-macro pore structure. The role of PPO additives on the mesostructure evolution in the CTAB...

  9. Photoelectrochemical properties of hierarchical ZnO micro-nanostructure sensitized with Sb2S3 nanoparticles

    Directory of Open Access Journals (Sweden)

    Zhimin GUO

    2016-02-01

    Full Text Available By using electrochemical deposition method, and assisted with additions of PEG-400 and EDA, well-aligned ZnO nanorods and hierarchical ZnO micro-nanostructure are fabricated directly on indium doped tin oxide coated conducting glass (ITO substrate. The shell-core Sb2S3/ZnO nanorod structure and the shell-core hierarchical Sb2S3/ZnO micro-nanostructure are prepared by chemical bath deposition method. SEM, XRD, UV-Vis and photocurrent test are used to characterize the morphology, nanostructures and their photoelectrochemical properties. The studies show that the photocurrent on the array membranes with shell-core hierarchical Sb2S3/ZnO micro-nanostructure is apparently higher than that with shell-core Sb2S3/ZnO nanorods array.

  10. Synthesis and properties of ZnFe2O4 replica with biological hierarchical structure

    International Nuclear Information System (INIS)

    Liu, Hongyan; Guo, Yiping; Zhang, Yangyang; Wu, Fen; Liu, Yun; Zhang, Di

    2013-01-01

    Highlights: • ZFO replica with hierarchical structure was synthesized from butterfly wings. • Biotemplate has a significant impact on the properties of ZFO material. • Our method opens up new avenues for the synthesis of spinel ferrites. -- Abstract: ZnFe 2 O 4 replica with biological hierarchical structure was synthesized from Papilio paris by a sol–gel method followed by calcination. The crystallographic structure and morphology of the obtained samples were characterized by X-ray diffraction, field-emission scanning electron microscope, and transmittance electron microscope. The results showed that the hierarchical structures were retained in the ZFO replica of spinel structure. The magnetic behavior of such novel products was measured by a vibrating sample magnetometer. A superparamagnetism-like behavior was observed due to nanostructuration size effects. In addition, the ZFO replica with “quasi-honeycomb-like structure” showed a much higher specific capacitance of 279.4 F g −1 at 10 mV s −1 in comparison with ZFO powder of 137.3 F g −1 , attributing to the significantly increased surface area. These results demonstrated that ZFO replica is a promising candidate for novel magnetic devices and supercapacitors

  11. Growth, characterization and electrochemical properties of hierarchical CuO nanostructures for supercapacitor applications

    Energy Technology Data Exchange (ETDEWEB)

    Krishnamoorthy, Karthikeyan [Nanomaterials and System Laboratory, Department of Mechanical Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of); Kim, Sang-Jae, E-mail: kimsangj@jejunu.ac.kr [Nanomaterials and System Laboratory, Department of Mechanical Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of); Department of Mechatronics Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of)

    2013-09-01

    Graphical abstract: - Highlights: • Hierarchical CuO nanostructures were grown on Cu foil. • Monoclinic phase of CuO was grown. • XPS analysis revealed the presence of Cu(2p{sub 3/2}) and Cu(2p{sub 1/2}) on the surfaces. • Specific capacitance of 94 F/g was achieved for the CuO using cyclic voltammetry. • Impedance spectra show their pseudo capacitor applications. - Abstract: In this paper, we have investigated the electrochemical properties of hierarchical CuO nanostructures for pseudo-supercapacitor device applications. Moreover, the CuO nanostructures were formed on Cu substrate by in situ crystallization process. The as-grown CuO nanostructures were characterized using X-ray diffraction (XRD), Fourier transform-infra red spectroscopy (FT-IR), X-ray photoelectron spectroscopy and field emission-scanning electron microscope (FE-SEM) analysis. The XRD and FT-IR analysis confirm the formation of monoclinic CuO nanostructures. FE-SEM analysis shows the formation of leave like hierarchical structures of CuO with high uniformity and controlled density. The electrochemical analysis such as cyclic voltammetry and electrochemical impedance spectroscopy studies confirms the pseudo-capacitive behavior of the CuO nanostructures. Our experimental results suggest that CuO nanostructures will create promising applications of CuO toward pseudo-supercapacitors.

  12. Growth, characterization and electrochemical properties of hierarchical CuO nanostructures for supercapacitor applications

    International Nuclear Information System (INIS)

    Krishnamoorthy, Karthikeyan; Kim, Sang-Jae

    2013-01-01

    Graphical abstract: - Highlights: • Hierarchical CuO nanostructures were grown on Cu foil. • Monoclinic phase of CuO was grown. • XPS analysis revealed the presence of Cu(2p 3/2 ) and Cu(2p 1/2 ) on the surfaces. • Specific capacitance of 94 F/g was achieved for the CuO using cyclic voltammetry. • Impedance spectra show their pseudo capacitor applications. - Abstract: In this paper, we have investigated the electrochemical properties of hierarchical CuO nanostructures for pseudo-supercapacitor device applications. Moreover, the CuO nanostructures were formed on Cu substrate by in situ crystallization process. The as-grown CuO nanostructures were characterized using X-ray diffraction (XRD), Fourier transform-infra red spectroscopy (FT-IR), X-ray photoelectron spectroscopy and field emission-scanning electron microscope (FE-SEM) analysis. The XRD and FT-IR analysis confirm the formation of monoclinic CuO nanostructures. FE-SEM analysis shows the formation of leave like hierarchical structures of CuO with high uniformity and controlled density. The electrochemical analysis such as cyclic voltammetry and electrochemical impedance spectroscopy studies confirms the pseudo-capacitive behavior of the CuO nanostructures. Our experimental results suggest that CuO nanostructures will create promising applications of CuO toward pseudo-supercapacitors

  13. Hierarchical Linked Views

    Energy Technology Data Exchange (ETDEWEB)

    Erbacher, Robert; Frincke, Deb

    2007-07-02

    Coordinated views have proven critical to the development of effective visualization environments. This results from the fact that a single view or representation of the data cannot show all of the intricacies of a given data set. Additionally, users will often need to correlate more data parameters than can effectively be integrated into a single visual display. Typically, development of multiple-linked views results in an adhoc configuration of views and associated interactions. The hierarchical model we are proposing is geared towards more effective organization of such environments and the views they encompass. At the same time, this model can effectively integrate much of the prior work on interactive and visual frameworks. Additionally, we expand the concept of views to incorporate perceptual views. This is related to the fact that visual displays can have information encoded at various levels of focus. Thus, a global view of the display provides overall trends of the data while focusing in on individual elements provides detailed specifics. By integrating interaction and perception into a single model, we show how one impacts the other. Typically, interaction and perception are considered separately, however, when interaction is being considered at a fundamental level and allowed to direct/modify the visualization directly we must consider them simultaneously and how they impact one another.

  14. In-situ preparation of Fe2O3 hierarchical arrays on stainless steel substrate for high efficient catalysis

    International Nuclear Information System (INIS)

    Yang, Zeheng; Wang, Kun; Shao, Zongming; Tian, Yuan; Chen, Gongde; Wang, Kai; Chen, Zhangxian; Dou, Yan; Zhang, Weixin

    2017-01-01

    Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe 2 O 3 hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N 2 atmosphere. As a Fenton-like catalyst, Fe 2 O 3 hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . The Fe 2 O 3 catalyst with unique hierarchical structures and efficient transport channels, effectively activates H 2 O 2 to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe 2 O 3 hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H 2 O 2 . - Highlights: • Fe 2 O 3 hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F − ions play an important role in the formation of the Fe 2 O 3 hierarchical arrays. • Fe 2 O 3 hierarchical arrays show high catalytic activity to methylene blue degradation.

  15. Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

    2012-01-01

    Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

  16. Hierarchical classification with a competitive evolutionary neural tree.

    Science.gov (United States)

    Adams, R G.; Butchart, K; Davey, N

    1999-04-01

    A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT offers over other hierarchical competitive networks is its ability to self determine the number, and structure, of the competitive nodes in the network, without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated heuristics. The results of network simulations are presented over a range of data sets, including Anderson's IRIS data set. The CENT network demonstrates its ability to produce a representative hierarchical structure to classify a broad range of data sets.

  17. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  18. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  19. Multimode multidrop serial coalescence effects during condensation on hierarchical superhydrophobic surfaces.

    Science.gov (United States)

    Rykaczewski, Konrad; Paxson, Adam T; Anand, Sushant; Chen, Xuemei; Wang, Zuankai; Varanasi, Kripa K

    2013-01-22

    The prospect of enhancing the condensation rate by decreasing the maximum drop departure diameter significantly below the capillary length through spontaneous drop motion has generated significant interest in condensation on superhydrophobic surfaces (SHS). The mobile coalescence leading to spontaneous drop motion was initially reported to occur only on hierarchical SHS, consisting of both nanoscale and microscale topological features. However, subsequent studies have shown that mobile coalescence also occurs on solely nanostructured SHS. Thus, recent focus has been on understanding the condensation process on nanostructured surfaces rather than on hierarchical SHS. In this work, we investigate the impact of microscale topography of hierarchical SHS on the droplet coalescence dynamics and wetting states during the condensation process. We show that isolated mobile and immobile coalescence between two drops, almost exclusively focused on in previous studies, are rare. We identify several new droplet shedding modes, which are aided by tangential propulsion of mobile drops. These droplet shedding modes comprise of multiple droplets merging during serial coalescence events, which culminate in formation of a drop that either departs or remains anchored to the surface. We directly relate postmerging drop adhesion to formation of drops in nanoscale as well as microscale Wenzel and Cassie-Baxter wetting states. We identify the optimal microscale feature spacing of the hierarchical SHS, which promotes departure of the highest number of microdroplets. This optimal surface architecture consists of microscale features spaced close enough to enable transition of larger droplets into micro-Cassie state yet, at the same time, provides sufficient spacing in-between the features for occurrence of mobile coalescence.

  20. Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems

    DEFF Research Database (Denmark)

    Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung

    2015-01-01

    The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...

  1. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  2. Non-Hierarchical Clustering as a method to analyse an open-ended ...

    African Journals Online (AJOL)

    We show that the use of non-hierarchical analysis allows us to interpret the reasoning of students solving different mathematical problems using Algebra, and to separate them into different groups, that can be recognised and characterised by common traits in their answers, without any prior knowledge on the part of the ...

  3. Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

    KAUST Repository

    Halim Boukaram, Wajih

    2017-09-14

    We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

  4. Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

    KAUST Repository

    Halim Boukaram, Wajih; Turkiyyah, George; Ltaief, Hatem; Keyes, David E.

    2017-01-01

    We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

  5. Hierarchical clustering using correlation metric and spatial continuity constraint

    Science.gov (United States)

    Stork, Christopher L.; Brewer, Luke N.

    2012-10-02

    Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

  6. Micro-nano hierarchically structured nylon 6,6 surfaces with unique wettability.

    Science.gov (United States)

    Zhang, Liang; Zhang, Xiaoyan; Dai, Zhen; Wu, Junjie; Zhao, Ning; Xu, Jian

    2010-05-01

    A micro-nano hierarchically structured nylon 6,6 surface was easily fabricated by phase separation. Nylon 6,6 plate was swelled by formic acid and then immersed in a coagulate bath to precipitate. Micro particles with nano protrusions were generated and linked together covering over the surface. After dried up, the as-formed surface showed superhydrophilic ability. Inspired by lotus only employing 2-tier structure and ordinary plant wax to maintain superhydrophobicity, paraffin wax, a low surface energy material, was used to modify the hierarchically structured nylon 6,6 surface. The resultant surface had water contact angle (CA) of 155.2+/-1.3 degrees and a low sliding angle. The whole process was carried on under ambient condition and only need a few minutes. Copyright 2010 Elsevier Inc. All rights reserved.

  7. Static and dynamic friction of hierarchical surfaces.

    Science.gov (United States)

    Costagliola, Gianluca; Bosia, Federico; Pugno, Nicola M

    2016-12-01

    Hierarchical structures are very common in nature, but only recently have they been systematically studied in materials science, in order to understand the specific effects they can have on the mechanical properties of various systems. Structural hierarchy provides a way to tune and optimize macroscopic mechanical properties starting from simple base constituents and new materials are nowadays designed exploiting this possibility. This can be true also in the field of tribology. In this paper we study the effect of hierarchical patterned surfaces on the static and dynamic friction coefficients of an elastic material. Our results are obtained by means of numerical simulations using a one-dimensional spring-block model, which has previously been used to investigate various aspects of friction. Despite the simplicity of the model, we highlight some possible mechanisms that explain how hierarchical structures can significantly modify the friction coefficients of a material, providing a means to achieve tunability.

  8. Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

    Science.gov (United States)

    Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

    2017-11-01

    In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

  9. Efficiently dense hierarchical graphene based aerogel electrode for supercapacitors

    Science.gov (United States)

    Wang, Xin; Lu, Chengxing; Peng, Huifen; Zhang, Xin; Wang, Zhenkun; Wang, Gongkai

    2016-08-01

    Boosting gravimetric and volumetric capacitances simultaneously at a high rate is still a discrepancy in development of graphene based supercapacitors. We report the preparation of dense hierarchical graphene/activated carbon composite aerogels via a reduction induced self-assembly process coupled with a drying post treatment. The compact and porous structures of composite aerogels could be maintained. The drying post treatment has significant effects on increasing the packing density of aerogels. The introduced activated carbons play the key roles of spacers and bridges, mitigating the restacking of adjacent graphene nanosheets and connecting lateral and vertical graphene nanosheets, respectively. The optimized aerogel with a packing density of 0.67 g cm-3 could deliver maximum gravimetric and volumetric capacitances of 128.2 F g-1 and 85.9 F cm-3, respectively, at a current density of 1 A g-1 in aqueous electrolyte, showing no apparent degradation to the specific capacitance at a current density of 10 A g-1 after 20000 cycles. The corresponding gravimetric and volumetric capacitances of 116.6 F g-1 and 78.1 cm-3 with an acceptable cyclic stability are also achieved in ionic liquid electrolyte. The results show a feasible strategy of designing dense hierarchical graphene based aerogels for supercapacitors.

  10. Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

    Directory of Open Access Journals (Sweden)

    Jun Ren

    2014-01-01

    Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

  11. Photocatalytic properties of hierarchical ZnO flowers synthesized by a sucrose-assisted hydrothermal method

    Energy Technology Data Exchange (ETDEWEB)

    Lv Wei [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China); Wei Bo [Center for Condensed Matter Science and Technology, Department of Physics, Harbin Institute of Technology, Harbin 150080 (China); Xu Lingling, E-mail: xulingling_hit@163.com [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China) and Center for Condensed Matter Science and Technology, Department of Physics, Harbin Institute of Technology, Harbin 150080 (China); Zhao Yan, E-mail: zhaoyan516@126.com [Department of Physics, Northeast Forestry University, Harbin 150040 (China); Gao Hong; Liu Jia [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China)

    2012-10-15

    Highlights: Black-Right-Pointing-Pointer Hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. Black-Right-Pointing-Pointer The sucrose added ZnO flowers showed improved activity mainly due to the improved crystallinity. Black-Right-Pointing-Pointer The effect of sucrose content was studied and optimized. - Abstract: In this work, hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. The thermogravimetric analysis/differential thermal analysis (TGA-DTA) and Fourier transform infrared spectra (FTIR) showed that sucrose acted as a complexing agent in the synthesis process and assisted combustion during annealing. Photocatalytic activity was evaluated using the degradation of organic dye methyl orange. The sucrose added ZnO flowers showed improved activity, which was mainly attributed to the better crystallinity as confirmed by X-ray photoelectron spectroscopy (XPS) analysis. The effect of sucrose amount on photocatalytic activity was also studied.

  12. Hierarchical nanostructures assembled from ultrathin Bi2WO6 nanoflakes and their visible-light induced photocatalytic property

    International Nuclear Information System (INIS)

    Wang, Xiong; Tian, Peng; Lin, Ying; Li, Li

    2015-01-01

    Graphical abstract: Hierarchical Bi 2 WO 6 nanostructures assembled from nanoflakes were successfully synthesized by a facile hydrothermal method. The excellent photocatalytic activity and recycling performance might be mainly ascribed to the unique hierarchical nanostructures and are expected to offer the nanostructures promising applications in the field of wastewater treatment. - Highlights: • Hierarchical Bi 2 WO 6 nanostructures assembled from nanoflakes were successfully synthesized by a facile hydrothermal method. • Visible-light-induced photocatalytic efficiency of the obtained nanoarchitectures was enhanced about 6 times. • A possible mechanism was proposed. - Abstract: With the aid of ethylene glycol and sodium dodecylbenzene sulfonate, the hierarchical Bi 2 WO 6 nanoarchitectures assembled from nanoflakes could be attained by a facile solvothermal method. The synthetic strategy is versatile and environmentally friendly and a plausible growth-assembly process was proposed for the formation of the hierarchical nanostructures. The visible-light-irradiated photocatalytic activity was estimated by the degradation of rhodamine B. Compared with the sample prepared by a solid-state reaction, the visible-light-induced photocatalytic efficiency of the nanostructures was enhanced about 6 times. The photocatalysis tests show that the nanostructures exhibit excellent photocatalytic activity and recycling performance, which were mainly ascribed to the unique hierarchical nanostructures and are expected to offer promising applications in the field of wastewater treatment

  13. Thin randomly aligned hierarchical carbon nanotube arrays as ultrablack metamaterials

    Science.gov (United States)

    De Nicola, Francesco; Hines, Peter; De Crescenzi, Maurizio; Motta, Nunzio

    2017-07-01

    Ultrablack metamaterials are artificial materials able to harvest all the incident light regardless of wavelength, angle, or polarization. Here, we show the ultrablack properties of randomly aligned hierarchical carbon nanotube arrays with thicknesses below 200 nm. The thin coatings are realized by solution processing and dry-transfer deposition on different substrates. The hierarchical surface morphology of the coatings is biomimetic and provides a large effective area that improves the film optical absorption. Also, such a morphology is responsible for the moth-eye effect, which leads to the omnidirectional and polarization-independent suppression of optical reflection. The films exhibit an emissivity up to 99.36% typical of an ideal black body, resulting in the thinnest ultrablack metamaterial ever reported. Such a material may be exploited for thermal, optical, and optoelectronic devices such as heat sinks, optical shields, solar cells, light and thermal sensors, and light-emitting diodes.

  14. Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

    DEFF Research Database (Denmark)

    Pedersen, Thomas Lin

    2017-01-01

    of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https...

  15. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Clinical time series prediction: towards a hierarchical dynamical system framework

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  17. A non-chemically selective top-down approach towards the preparation of hierarchical TS-1 zeolites with improved oxidative desulfurization catalytic performance.

    Science.gov (United States)

    Du, Shuting; Chen, Xiaoxin; Sun, Qiming; Wang, Ning; Jia, Mingjun; Valtchev, Valentin; Yu, Jihong

    2016-02-28

    Hierarchical TS-1 zeolites with secondary macropores have been successfully prepared by using two different fluoride-containing chemical etching post-treated routes. Hierarchical TS-1 zeolites exhibited a chemical composition similar to that of the parent material and showed remarkably enhanced catalytic activity in oxidative desulfurization reaction.

  18. Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

    Science.gov (United States)

    Li, Yanming; Nan, Bin; Zhu, Ji

    2015-06-01

    We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.

  19. HD 181068: A Red Giant in a Triply Eclipsing Compact Hierarchical Triple System

    DEFF Research Database (Denmark)

    Derekas, A.; Kiss, Lazlo L.; Borkovits, T.

    2011-01-01

    by ground-based spectroscopy and interferometry, which show it to be a hierarchical triple with two types of mutual eclipses. The primary is a red giant that is in a 45-day orbit with a pair of red dwarfs in a close 0.9-day orbit. The red giant shows evidence for tidally induced oscillations that are driven...

  20. Hierarchical porous TiO{sub 2} thin films by soft and dual templating

    Energy Technology Data Exchange (ETDEWEB)

    Henrist, Catherine, E-mail: catherine.henrist@ulg.ac.be [University of Liege, Department of Chemistry, GREENMAT-LCIS, B6 Sart Tilman, Liege 4000 (Belgium); University of Liege, Center for Applied Technology in Microscopy (CATmu), B6 Sart Tilman, Liege 4000 (Belgium); Dewalque, Jennifer [University of Liege, Department of Chemistry, GREENMAT-LCIS, B6 Sart Tilman, Liege 4000 (Belgium); Cloots, Rudi [University of Liege, Department of Chemistry, GREENMAT-LCIS, B6 Sart Tilman, Liege 4000 (Belgium); University of Liege, Center for Applied Technology in Microscopy (CATmu), B6 Sart Tilman, Liege 4000 (Belgium); Vertruyen, Bénédicte; Jonlet, Jonathan; Colson, Pierre [University of Liege, Department of Chemistry, GREENMAT-LCIS, B6 Sart Tilman, Liege 4000 (Belgium)

    2013-07-31

    Hierarchical porous structures, with different pore sizes, including pores larger than 10 nm, constitute an important field of research for many applications such as selective molecule detection, catalysis, dye-sensitized solar cells, nanobiotechnology and nanomedecine. However, increasing the pore size logically results in the decrease of specific surface. There is a need to quantify and predict the resulting porosity and specific surface. We have prepared hierarchical porous TiO{sub 2} thin films either by surfactant templating (soft) or dual surfactant/nanospheres templating (soft/hard). They all show narrow, bimodal distribution of pores. Soft templating route uses a modified sol–gel procedure by adding a swelling agent (polypropylene glycol) to a precursor solution containing Ti alkoxide and block-copolymer surfactant. This scheme leads to very thin films showing high specific surface and bimodal porosity with diameters of 10 nm and 54 nm. Dual templating route combines a precursor solution made of Ti alkoxide and block-copolymer surfactant with polystyrene (PS) nanospheres (diam. 250 nm) in a one-pot simple process. This gives thicker films with a bimodal distribution of pores (8 nm and 165-200 nm). The introduction of PS nanospheres in the surfactant–Ti system does not interfere with the soft templating process and results in a macroporosity with a pore diameter 20–30% smaller than the original beads diameter. The dye loading of hierarchical films is compared to pure surfactant-templated TiO{sub 2} films and shows a relative decrease of 29% for soft templating and 43% for dual templating. The microstructure of bimodal porous films is characterized by several techniques such as transmission and scanning electron microscopy, X-ray diffraction, profilometry and ellipsometry. Finally, a geometrical model is proposed and validated for each system, based on the agreement between calculated specific surfaces and experimental dye loading with N719 dye

  1. Hierarchical decision making for flood risk reduction

    DEFF Research Database (Denmark)

    Custer, Rocco; Nishijima, Kazuyoshi

    2013-01-01

    . In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...

  2. Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Dieqing [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China); Wen, Meicheng; Jiang, Bo; Li, Guisheng [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Yu, Jimmy C., E-mail: jimyu@cuhk.edu.hk [Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China)

    2012-04-15

    Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: Black-Right-Pointing-Pointer Ionothermal synthesis of BiOBr microspheres with hierarchical structure. Black-Right-Pointing-Pointer Efficient mass transfer and excellent light-harvesting ability. Black-Right-Pointing-Pointer Suitable for removing heavy metals and treatment of organic dyes. Black-Right-Pointing-Pointer Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

  3. Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

    International Nuclear Information System (INIS)

    Zhang, Dieqing; Wen, Meicheng; Jiang, Bo; Li, Guisheng; Yu, Jimmy C.

    2012-01-01

    Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: ► Ionothermal synthesis of BiOBr microspheres with hierarchical structure. ► Efficient mass transfer and excellent light-harvesting ability. ► Suitable for removing heavy metals and treatment of organic dyes. ► Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

  4. BiOCl nanowire with hierarchical structure and its Raman features

    International Nuclear Information System (INIS)

    Tian Ye; Guo Chuanfei; Guo Yanjun; Wang Qi; Liu Qian

    2012-01-01

    BiOCl is a promising V-VI-VII-compound semiconductor with excellent optical and electrical properties, and has great potential applications in photo-catalysis, photoelectric, etc. We successfully synthesize BiOCl nanowire with a hierarchical structure by combining wet etch (top-down) with liquid phase crystal growth (bottom-up) process, opening a novel method to construct ordered bismuth-based nanostructures. The morphology and lattice structures of Bi nanowires, β-Bi 2 O 3 nanowires and BiOCl nanowires with the hierarchical structure are investigated by scanning electron microscope (SEM) and transition electron microscope (TEM). The formation mechanism of such ordered BiOCl hierarchical structure is considered to mainly originate from the highly preferred growth, which is governed by the lattice match between (1 1 0) facet of BiOCl and (2 2 0) or (0 0 2) facet of β-Bi 2 O 3 . A schematic model is also illustrated to depict the formation process of the ordered BiOCl hierarchical structure. In addition, Raman properties of the BiOCl nanowire with the hierarchical structure are investigated deeply.

  5. Hierarchical Velocity Control Based on Differential Flatness for a DC/DC Buck Converter-DC Motor System

    Directory of Open Access Journals (Sweden)

    R. Silva-Ortigoza

    2014-01-01

    Full Text Available This paper presents a hierarchical controller that carries out the angular velocity trajectory tracking task for a DC motor driven by a DC/DC Buck converter. The high level control is related to the DC motor and the low level control is dedicated to the DC/DC Buck converter; both controls are designed via differential flatness. The high level control provides a desired voltage profile for the DC motor to achieve the tracking of a desired angular velocity trajectory. Then, a low level control is designed to ensure that the output voltage of the DC/DC Buck converter tracks the voltage profile imposed by the high level control. In order to experimentally verify the hierarchical controller performance, a DS1104 electronic board from dSPACE and Matlab-Simulink are used. The switched implementation of the hierarchical average controller is accomplished by means of pulse width modulation. Experimental results of the hierarchical controller for the velocity trajectory tracking task show good performance and robustness against the uncertainties associated with different system parameters.

  6. Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

    Science.gov (United States)

    Hou, Fujun

    2016-01-01

    This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

  7. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

    Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.

  8. On Utmost Multiplicity of Hierarchical Stellar Systems

    Directory of Open Access Journals (Sweden)

    Gebrehiwot Y. M.

    2016-12-01

    Full Text Available According to theoretical considerations, multiplicity of hierarchical stellar systems can reach, depending on masses and orbital parameters, several hundred, while observational data confirm the existence of at most septuple (seven-component systems. In this study, we cross-match the stellar systems of very high multiplicity (six and more components in modern catalogues of visual double and multiple stars to find among them the candidates to hierarchical systems. After cross-matching the catalogues of closer binaries (eclipsing, spectroscopic, etc., some of their components were found to be binary/multiple themselves, what increases the system's degree of multiplicity. Optical pairs, known from literature or filtered by the authors, were flagged and excluded from the statistics. We compiled a list of hierarchical systems with potentially very high multiplicity that contains ten objects. Their multiplicity does not exceed 12, and we discuss a number of ways to explain the lack of extremely high multiplicity systems.

  9. Hierarchical capillary adhesion of microcantilevers or hairs

    International Nuclear Information System (INIS)

    Liu Jianlin; Feng Xiqiao; Xia Re; Zhao Hongping

    2007-01-01

    As a result of capillary forces, animal hairs, carbon nanotubes or nanowires of a periodically or randomly distributed array often assemble into hierarchical structures. In this paper, the energy method is adopted to analyse the capillary adhesion of microsized hairs, which are modelled as clamped microcantilevers wetted by liquids. The critical conditions for capillary adhesion of two hairs, three hairs or two bundles of hairs are derived in terms of Young's contact angle, elastic modulus and geometric sizes of the beams. Then, the hierarchical capillary adhesion of hairs is addressed. It is found that for multiple hairs or microcantilevers, the system tends to take a hierarchical structure as a result of the minimization of the total potential energy of the system. The level number of structural hierarchy increases with the increase in the number of hairs if they are sufficiently long. Additionally, we performed experiments to verify our theoretical solutions for the adhesion of microbeams

  10. Validity of the t-plot method to assess microporosity in hierarchical micro/mesoporous materials.

    Science.gov (United States)

    Galarneau, Anne; Villemot, François; Rodriguez, Jeremy; Fajula, François; Coasne, Benoit

    2014-11-11

    The t-plot method is a well-known technique which allows determining the micro- and/or mesoporous volumes and the specific surface area of a sample by comparison with a reference adsorption isotherm of a nonporous material having the same surface chemistry. In this paper, the validity of the t-plot method is discussed in the case of hierarchical porous materials exhibiting both micro- and mesoporosities. Different hierarchical zeolites with MCM-41 type ordered mesoporosity are prepared using pseudomorphic transformation. For comparison, we also consider simple mechanical mixtures of microporous and mesoporous materials. We first show an intrinsic failure of the t-plot method; this method does not describe the fact that, for a given surface chemistry and pressure, the thickness of the film adsorbed in micropores or small mesopores (plot method to estimate the micro- and mesoporous volumes of hierarchical samples is then discussed, and an abacus is given to correct the underestimated microporous volume by the t-plot method.

  11. Development of ultralight, super-elastic, hierarchical metallic meta-structures with i3DP technology

    Science.gov (United States)

    Zhang, Dongxing; Xiao, Junfeng; Moorlag, Carolyn; Guo, Qiuquan; Yang, Jun

    2017-11-01

    Lightweight and mechanically robust materials show promising applications in thermal insulation, energy absorption, and battery catalyst supports. This study demonstrates an effective method for creation of ultralight metallic structures based on initiator-integrated 3D printing technology (i3DP), which provides a possible platform to design the materials with the best geometric parameters and desired mechanical performance. In this study, ultralight Ni foams with 3D interconnected hollow tubes were fabricated, consisting of hierarchical features spanning three scale orders ranging from submicron to centimeter. The resultant materials can achieve an ultralight density of as low as 5.1 mg cm-3 and nearly recover after significant compression up to 50%. Due to a high compression ratio, the hierarchical structure exhibits superior properties in terms of energy absorption and mechanical efficiency. The relationship of structural parameters and mechanical response was established. The ability of achieving ultralight density printing approach provides metallic structures with substantial benefits from the hierarchical design and fabrication flexibility to ultralight applications.

  12. Statistical shear lag model - unraveling the size effect in hierarchical composites.

    Science.gov (United States)

    Wei, Xiaoding; Filleter, Tobin; Espinosa, Horacio D

    2015-05-01

    Numerous experimental and computational studies have established that the hierarchical structures encountered in natural materials, such as the brick-and-mortar structure observed in sea shells, are essential for achieving defect tolerance. Due to this hierarchy, the mechanical properties of natural materials have a different size dependence compared to that of typical engineered materials. This study aimed to explore size effects on the strength of bio-inspired staggered hierarchical composites and to define the influence of the geometry of constituents in their outstanding defect tolerance capability. A statistical shear lag model is derived by extending the classical shear lag model to account for the statistics of the constituents' strength. A general solution emerges from rigorous mathematical derivations, unifying the various empirical formulations for the fundamental link length used in previous statistical models. The model shows that the staggered arrangement of constituents grants composites a unique size effect on mechanical strength in contrast to homogenous continuous materials. The model is applied to hierarchical yarns consisting of double-walled carbon nanotube bundles to assess its predictive capabilities for novel synthetic materials. Interestingly, the model predicts that yarn gauge length does not significantly influence the yarn strength, in close agreement with experimental observations. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  13. A Hierarchical Dispatch Structure for Distribution Network Pricing

    OpenAIRE

    Yuan, Zhao; Hesamzadeh, Mohammad Reza

    2015-01-01

    This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...

  14. The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

    Science.gov (United States)

    Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

    2018-04-01

    Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

  15. Hierarchical mesosilicalite nanoformulation integrated with cisplatin exhibits target-specific efficient anticancer activity

    Science.gov (United States)

    Jermy, B. Rabindran; Acharya, Sadananda; Ravinayagam, Vijaya; Alghamdi, Hajer Saleh; Akhtar, Sultan; Basuwaidan, Rehab S.

    2018-04-01

    Hierarchically structured zeolitic ZSM-5 and meso MCM-41 interlinked domain had an impeccable use as catalysis in many applications. The aim of the study was to develop a new drug delivery nanoformulation, specifically, cisplatin/mesosilicalite using top-down approach for cancer therapy. Hierarchical mesosilicalite with variable porosity was synthesized using alkaline molar solution (0.2 and 0.7 M NaOH) and was loaded with cisplatin through equilibrium adsorption technique. Physico-chemical properties of the nanoformulation (IAUM-56—Imam Abdulrahman Bin Faisal University Mesosilicalite-56) were characterized using X-ray diffraction, surface area analysis (BET), Fourier transformed infrared spectroscopy (FT-IR), diffuse reflectance UV-Vis spectroscopy, and transmission electron microscopy. Drug release study and anticancer activity were assayed on HeLa and MCF7 cancer cells using MTT assay. X-ray diffraction pattern showed interrelated meso- and microphases, while BET analysis revealed considerable mesoporosity formation with a remodulation of isotherm hysteresis indicating the presence of hierarchical pores. FT-IR showed the presence of nanozeolitic subunits into mesostructure with a band at about 550 cm-1. IAUM-56 demonstrated high cytotoxic activity against HeLa cancer cells with an LC50 of 0.02 mg/ml, MCF7 cancer cells with an LC50 of 0.05 mg/ml, and less toxic to normal fibroblast cells with an LC50 of approximately ten times higher at 0.5 mg/ml. Overall, IAUM-56 showed a high rate of sustained release of cisplatin imparting target specific cytotoxic effect against tumor cells with at least tenfold lower toxicity on normal fibroblast cells. Our nanoformulation has the potential use in cancer therapy as a targeted drug delivery system.

  16. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  17. Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

    Science.gov (United States)

    Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

    2016-08-18

    This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

  18. Silver Films with Hierarchical Chirality.

    Science.gov (United States)

    Ma, Liguo; Cao, Yuanyuan; Duan, Yingying; Han, Lu; Che, Shunai

    2017-07-17

    Physical fabrication of chiral metallic films usually results in singular or large-sized chirality, restricting the optical asymmetric responses to long electromagnetic wavelengths. The chiral molecule-induced formation of silver films prepared chemically on a copper substrate through a redox reaction is presented. Three levels of chirality were identified: primary twisted nanoflakes with atomic crystal lattices, secondary helical stacking of these nanoflakes to form nanoplates, and tertiary micrometer-sized circinates consisting of chiral arranged nanoplates. The chiral Ag films exhibited multiple plasmonic absorption- and scattering-based optical activities at UV/Vis wavelengths based on their hierarchical chirality. The Ag films showed chiral selectivity for amino acids in catalytic electrochemical reactions, which originated from their primary atomic crystal lattices. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. One-pot pseudomorphic crystallization of mesoporous porous silica to hierarchical porous zeolites

    Energy Technology Data Exchange (ETDEWEB)

    Xing, Jun-Ling; Jiang, Shu-Hua; Pang, Jun-Ling; Yuan, En-Hui; Ma, Xiao-Jing [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China); Lam, Koon-Fung [Department of Chemical Engineering, University College London, Torrington Place, London (United Kingdom); Xue, Qing-Song, E-mail: qsxue@chem.ecnu.edu.cn [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China); Zhang, Kun, E-mail: kzhang@chem.ecnu.edu.cn [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China)

    2015-09-15

    Hierarchically porous silica with mesopore and zeolitic micropore was synthesized via pseudomorphic crystallization under high-temperature hydrothermal treatment in the presence of cetyltrimethylammonium tosylate and tetrapropylammonium ions. A combined characterization using small-angle X-ray diffraction (XRD), nitrogen adsorption, high-resolution transmission electron microscopy (TEM), thermogravimetric analysis (TG), and elemental analysis showed that dual templates, CTA{sup +} and TPA{sup +} molecules, can work in a cooperative manner to synthesize mesoporous zeolite in a one-pot system by precisely tuning the reaction conditions, such as reaction time and temperature, and type and amount of heterometal atoms. It is found that the presence of Ti precursor is critical to the successful synthesis of such nanostructure. It not only retards the nucleation and growth of crystalline MFI domains, but also acts as nano-binder or nano-glue to favor the assembly of zeolite nanoblocks. - Graphical abstract: Display Omitted - Highlights: • A facile method to synthesize mesoporous zeolites with hierarchical porosity was presented. • It gives a new insight into keeping the balance between mesoscopic and molecular ordering in hierarchical porous materials. • A new understanding on the solid–solid transformation mechanism for the synthesis of titanosilicate zeolites was proposed.

  20. Hydrothermal synthesis of hierarchical WO3 nanostructures for dye-sensitized solar cells

    International Nuclear Information System (INIS)

    Rashad, M.M.; Shalan, A.E.

    2014-01-01

    Hierarchical architectures consisting of one-dimensional (1D) nanostructures are of great interest for potential use in energy and environmental applications in recent years. In this work, hierarchical tungsten oxide (WO 3 ) has been synthesized via a facile hydrothermal route from ammonium metatungstate hydrate and implemented as photoelectrode for dye-sensitized solar cells. The urchin-like WO 3 micro-patterns are constructed by self-organized nanoscale length 1D building blocks, which are single crystalline in nature, grown along (001) direction and confirm an orthorhombic crystal phase. The obtained powders were investigated by XRD, SEM, TEM and UV-Vis Spectroscopy. The photovoltaic performance of dye-sensitized solar cells based on WO 3 photoanodes was investigated. With increasing the calcination temperature of the prepared nanopowders, the light-electricity conversion efficiency (η) was increased. The results were attributed to increase the crystallinity of the particles and ease of electron movement. The DSSC based on hierarchical WO 3 showed a short-circuit current, an open-circuit voltage, a fill factor, and a conversion efficiency of 4.241 mA/cm 2 , 0.656 V, 66.74, and 1.85 %, respectively. (orig.)

  1. Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

    Science.gov (United States)

    Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

    2018-05-07

    A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

  2. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  3. Hierarchical Planning Methodology for a Supply Chain Management

    Directory of Open Access Journals (Sweden)

    Virna ORTIZ-ARAYA

    2012-01-01

    Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.

  4. MOF-5 decorated hierarchical ZnO nanorod arrays and its photoluminescence

    Science.gov (United States)

    Zhang, Yinmin; Lan, Ding; Wang, Yuren; Cao, He; Jiang, Heng

    2011-04-01

    The strategy to manipulate nanoscale materials into well-organized hierarchical architectures is very important to both material synthesis and nanodevice applications. Here, nanoscale MOF-5 crystallites were successfully fabricated onto ordered hierarchical ZnO arrays based on aqueous chemical synthesis and molecule self-assembly technology guided room temperature diffusion method, which has the advantages of energy saving and simple operation. The structures and morphologies of the samples were performed by X-ray powder diffraction and field emission scanning electronic microscopy. The MOF-5 crystallites have good quality and bind well to the hexagonal-patterned ZnO arrays. The photoluminescence spectrum shows that the emission of hybrid MOF-5-ZnO films displays a blue shift in green emission and intensity reduction in UV emission. This ordered hybrid semiconductor material is expected to exploit the great potentiality in sensors, micro/nanodevices, and screen displays.

  5. Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

    Science.gov (United States)

    Stankov, L

    1979-07-01

    The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

  6. Self-assembly of NiO/graphene with three-dimension hierarchical structure as high performance electrode material for supercapacitors

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Bing; Zhuang, Hua; Fang, Tao; Jiao, Zheng; Liu, Ruizhe; Ling, Xuetao [School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444 (China); Lu, Bo [Instrumental Analysis and Research Center, Shanghai University, Shanghai 200444 (China); Jiang, Yong, E-mail: jiangyong@shu.edu.cn [School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444 (China)

    2014-06-01

    Highlights: • 3D hierarchical NiO/graphene is prepared by a refluxing method with aqua-based solvent. • Time-dependent experiments are carried out to investigate formation mechanism. • Hierarchical sphere is formed through self-assembly of NiO grown on disc-shaped CTAB micelles. • It delivers a capacitance of 555 F g{sup −1} at 1 A g{sup −1} with 90.8% retention after 2000 cycles. - Abstract: This article reports a facile preparation of NiO/graphene composite by the combination of a controlled refluxing method with water based solvent in the presence of cetyltrimethylammonium bromide and subsequent annealing. X-ray diffraction and scanning electron microscopy reveal that the graphene nanosheets are uniformly wrapped by hierarchical porous NiO spheres with three-dimension hierarchical structure in the product. The composite shows highly improved electrochemical performance as electrode material for supercapacitor. The three-dimension hierarchical structure NiO/graphene composite delivers a first discharge capacitance of 555 F g{sup −1} and remains a reversible capacitance up to 504 F g{sup −1} after 2000 cycles at a current of 1 A g{sup −1} in three-electrode system. Contrarily, the pure NiO shows only a first discharge capacitance of 166 F g{sup −1} and remains only a reversible capacitance of 107 F g{sup −1} after 2000 cycles. The NiO/graphene composite also exhibits ameliorative rate capacitance of 402.9 F g{sup −1} at the current density of 5 A g{sup −1}. The enhanced electrochemical performances are ascribed to the higher surface area, the stable three-dimension hierarchical structure and the synergistic effects between the conductive graphene and porous NiO spheres.

  7. A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

    Science.gov (United States)

    Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

    In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

  8. Broca’s area processes the hierarchical organization of observed action

    Directory of Open Access Journals (Sweden)

    Masumi eWakita

    2014-01-01

    Full Text Available Broca’s area has been suggested as the area responsible for the domain-general hierarchical processing of language and music. Although meaningful action shares a common hierarchical structure with language and music, the role of Broca’s area in this domain remains controversial. To address the involvement of Broca’s area in the processing action hierarchy, the activation of Broca’s area was measured using near-infrared spectroscopy. Measurements were taken while participants watched silent movies that featured hand movements playing familiar and unfamiliar melodies. The unfamiliar melodies were reversed versions of the familiar melodies. Additionally, to investigate the effect of a motor experience on the activation of Broca’s area, the participants were divided into well-trained and less-trained groups. The results showed that Broca’s area in the well-trained participants demonstrated a significantly larger activation in response to the hand motion when an unfamiliar melody was played than when a familiar melody was played. However, Broca’s area in the less-trained participants did not show a contrast between conditions despite identical abilities of the two participant groups to identify the melodies by watching key pressing actions. These results are consistent with previous findings that Broca’s area exhibits increased activation in response to grammatically violated sentences and musically deviated chord progressions as well as the finding that this region does not represent the processing of grammatical structure in less-proficient foreign language speakers. Thus, the current study suggests that Broca’s area represents action hierarchy and that sufficiently long motor training is necessary for it to become sensitive to motor syntax. Therefore, the notion that hierarchical processing in Broca’s area is a common function shared between language and music may help to explain the role of Broca’s area in action perception.

  9. Ultrafast Hierarchical OTDM/WDM Network

    Directory of Open Access Journals (Sweden)

    Hideyuki Sotobayashi

    2003-12-01

    Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

  10. Hierarchically porous Ni monolith@branch-structured NiCo2O4 for high energy density supercapacitors

    Directory of Open Access Journals (Sweden)

    Mengjie Xu

    2016-06-01

    Full Text Available A variety of NiCo2O4 nanostrucutures ranging from nanowire to nanoplate and branched structures were successfully prepared via a simple hydrothermal process. The experimental results show that NiCo2O4 with branched structures possesses the best overall electrochemical performance. The improvement of energy density was explored in terms of hierarchically three-dimensional (3D metal substrates and a high specific area capacitance, and area energy density is obtained with hierarchically porous Ni monolith synthesized through a controlled combustion procedure.

  11. Hierarchical core-shell structure of ZnO nanorod@NiO/MoO₂ composite nanosheet arrays for high-performance supercapacitors.

    Science.gov (United States)

    Hou, Sucheng; Zhang, Guanhua; Zeng, Wei; Zhu, Jian; Gong, Feilong; Li, Feng; Duan, Huigao

    2014-08-27

    A hierarchical core-shell structure of ZnO nanorod@NiO/MoO2 composite nanosheet arrays on nickel foam substrate for high-performance supercapacitors was constructed by a two-step solution-based method involving two hydrothermal processes followed by a calcination treatment. Compared to one composed of pure NiO/MoO2 composite nanosheets, the hierarchical core-shell structure electrode displays better pseudocapacitive behaviors in 2 M KOH, including high areal specific capacitance values of 1.18 F cm(-2) at 5 mA cm(-2) and 0.6 F cm(-2) at 30 mA cm(-2) as well as relatively good rate capability at high current densities. Furthermore, it also shows remarkable cycle stability, remaining at 91.7% of the initial value even after 4000 cycles at a current density of 10 mA cm(-2). The enhanced pseudocapacitive behaviors are mainly due to the unique hierarchical core-shell structure and the synergistic effect of combining ZnO nanorod arrays and NiO/MoO2 composite nanosheets. This novel hierarchical core-shell structure shows promise for use in next-generation supercapacitors.

  12. Hierarchical structure of the otolith of adult wild carp

    International Nuclear Information System (INIS)

    Li Zhuo; Gao Yonghua; Feng Qingling

    2009-01-01

    The otolith of adult wild carp contains a pair of asterisci, a pair of lappilli and a pair of sagittae. Current research works are mainly restricted to the field of the daily ring structure. The purpose of this work is to explore the structural characteristics of carp's otolith in terms of hierarchy from nanometer to millimeter scale by transmission election microscope (TEM) and scanning electron microscope (SEM). Based on the observation, carp's lapillus is composed of ordered aragonite crystals. Seven hierarchical levels of the microstructure were proposed and described with the scheme representing a complete organization in detail. SEM studies show not only the clear daily growth increment, but also the morphology within the single daily increment. The domain structure of crystal orientation in otolith was observed for the first time. Furthermore, TEM investigation displays that the lapillus is composed of aragonite crystals with nanometer scale. Four hierarchical levels of the microstructure of the sagitta are also proposed. The asteriscus which is composed of nanometer scale vaterite crystals is considered to have a uniform structure.

  13. Hierarchical structure of the otolith of adult wild carp

    Energy Technology Data Exchange (ETDEWEB)

    Li Zhuo; Gao Yonghua [State key laboratory of new ceramics and fine processing, Department of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Feng Qingling, E-mail: biomater@mail.tsinghua.edu.cn [State key laboratory of new ceramics and fine processing, Department of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China)

    2009-04-30

    The otolith of adult wild carp contains a pair of asterisci, a pair of lappilli and a pair of sagittae. Current research works are mainly restricted to the field of the daily ring structure. The purpose of this work is to explore the structural characteristics of carp's otolith in terms of hierarchy from nanometer to millimeter scale by transmission election microscope (TEM) and scanning electron microscope (SEM). Based on the observation, carp's lapillus is composed of ordered aragonite crystals. Seven hierarchical levels of the microstructure were proposed and described with the scheme representing a complete organization in detail. SEM studies show not only the clear daily growth increment, but also the morphology within the single daily increment. The domain structure of crystal orientation in otolith was observed for the first time. Furthermore, TEM investigation displays that the lapillus is composed of aragonite crystals with nanometer scale. Four hierarchical levels of the microstructure of the sagitta are also proposed. The asteriscus which is composed of nanometer scale vaterite crystals is considered to have a uniform structure.

  14. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  15. SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

    Directory of Open Access Journals (Sweden)

    KwangHee Choi

    2014-10-01

    Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.

  16. Enhanced supercapacitor performance using hierarchical TiO2 nanorod/Co(OH)2 nanowall array electrodes

    International Nuclear Information System (INIS)

    Ramadoss, Ananthakumar; Kim, Sang Jae

    2014-01-01

    Graphical abstract: - Highlights: • TiO 2 /Co(OH) 2 hierarchical nanostructure was prepared by a combination of hydrothermal and cathodic electrodeposition method. • Hierarchical nanostructure electrode exhibited a maximum capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . • Combination of Co(OH) 2 nanowall with TiO 2 NR into a single system enhanced the electrochemical behavior of supercapacitor electrode. - Abstract: We report novel hierarchical TiO 2 nanorod (NR)/porous Co(OH) 2 nanowall array electrodes for high-performance supercapacitors fabricated using a two-step process that involves hydrothermal and electrodeposition techniques. Field-emission scanning electron microscope images reveal a bilayer structure consisting of TiO 2 NR arrays with porous Co(OH) 2 nanowalls. Compared with the bare TiO 2 NRs, the hierarchical TiO 2 NRs/Co(OH) 2 electrodes showed improved pseudocapacitive performance in a 2-M KOH electrolyte solution, exhibiting an areal specific capacitance of 274.3 mF cm −2 at a scan rate of 5 mV s −1 . The electrodes exhibited good stability, retaining 82.5% of the initial capacitance after 4000 cycles. The good pseudocapacitive performance of the hierarchical nanostructures is mainly due to the porous structure, which provides fast ion and electron transfer, a large surface area, short ion diffusion paths, and a favourable volume change during the cycling process

  17. Facile fabrication of superhydrophobic surfaces with hierarchical structures.

    Science.gov (United States)

    Lee, Eunyoung; Lee, Kun-Hong

    2018-03-06

    Hierarchical structures were fabricated on the surfaces of SUS304 plates using a one-step process of direct microwave irradiation under a carbon dioxide atmosphere. The surface nanostructures were composed of chrome-doped hematite single crystals. Superhydrophobic surfaces with a water contact angle up to 169° were obtained by chemical modification of the hierarchical structures. The samples maintained superhydrophobicity under NaCl solution up to 2 weeks.

  18. Fluorocarbon Adsorption in Hierarchical Porous Frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Motkuri, Radha K.; Annapureddy, Harsha V.; Vijayakumar, M.; Schaef, Herbert T.; Martin, P F.; McGrail, B. Peter; Dang, Liem X.; Krishna, Rajamani; Thallapally, Praveen K.

    2014-07-09

    The adsorption behavior of a series of fluorocarbon derivatives was examined on a set of microporous metal organic framework (MOF) sorbents and another set of hierarchical mesoporous MOFs. The microporous M-DOBDC (M = Ni, Co) showed a saturation uptake capacity for R12 of over 4 mmol/g at a very low relative saturation pressure (P/Po) of 0.02. In contrast, the mesoporous MOF MIL-101 showed an exceptionally high uptake capacity reaching over 14 mmol/g at P/Po of 0.4. Adsorption affinity in terms of mass loading and isosteric heats of adsorption were found to generally correlate with the polarizability of the refrigerant with R12 > R22 > R13 > R14 > methane. These results suggest the possibility of exploiting MOFs for separation of azeotropic mixtures of fluorocarbons and use in eco-friendly fluorocarbon-based adsorption cooling and refrigeration applications.

  19. Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

    Science.gov (United States)

    Klauer, Karl Christoph

    2010-01-01

    Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

  20. Hierarchically nanostructured hydroxyapatite: hydrothermal synthesis, morphology control, growth mechanism, and biological activity

    Directory of Open Access Journals (Sweden)

    Ma MG

    2012-04-01

    Full Text Available Ming-Guo MaInstitute of Biomass Chemistry and Technology, College of Materials Science and Technology, Beijing Forestry University, Beijing, People's Republic of ChinaAbstract: Hierarchically nanosized hydroxyapatite (HA with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours.Objective: The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks.Methods: A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide assay.Results: HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did

  1. MR-AFS: a global hierarchical file-system

    International Nuclear Information System (INIS)

    Reuter, H.

    2000-01-01

    The next generation of fusion experiments will use object-oriented technology creating the need for world wide sharing of an underlying hierarchical file-system. The Andrew file system (AFS) is a well known and widely spread global distributed file-system. Multiple-resident-AFS (MR-AFS) combines the features of AFS with hierarchical storage management systems. Files in MR-AFS therefore may be migrated on secondary storage, such as roboted tape libraries. MR-AFS is in use at IPP for the current experiments and data originating from super-computer applications. Experiences and scalability issues are discussed

  2. Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

    Science.gov (United States)

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

  3. Synthesis of hierarchical mesoporous lithium nickel cobalt manganese oxide spheres with high rate capability for lithium-ion batteries

    Science.gov (United States)

    Tong, Wei; Huang, Yudai; Cai, Yanjun; Guo, Yong; Wang, Xingchao; Jia, Dianzeng; Sun, Zhipeng; Pang, Weikong; Guo, Zaiping; Zong, Jun

    2018-01-01

    Hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres have been synthesized by urea-assisted solvothermal method with adding Triton X-100. The structure and morphology of the as-prepared materials were analyzed by X-ray diffraction and electron microscope. The results show that the as-prepared samples can be indexed as hexagonal layered structure with hierarchical architecture, and the possible formation mechanism is speculated. When evaluated as cathode material, the hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres show good electrochemical properties with high initial discharge capacity of 129.9 mAh g-1, and remain the discharge capacity of 95.5 mAh g-1 after 160 cycles at 10C. The excellent electrochemical performance of the as-prepared sample can be attributed to its stable hierarchical mesoporous framework in conjunction with large specific surface, low cation mixing and small particle size. They not only provide a large number of reaction sites for surface or interface reaction, but also shorten the diffusion length of Li+ ions. Meanwhile, the mesoporous spheres composed of nanoparticles can contribute to high rate ability and buffer volume changes during charge/discharge process.

  4. The construction of hierarchical structure on Ti substrate with superior osteogenic activity and intrinsic antibacterial capability

    Science.gov (United States)

    Huang, Ying; Zha, Guangyu; Luo, Qiaojie; Zhang, Jianxiang; Zhang, Feng; Li, Xiaohui; Zhao, Shifang; Zhu, Weipu; Li, Xiaodong

    2014-01-01

    The deficient osseointegration and implant-associated infections are pivotal issues for the long-term clinical success of endosteal Ti implants, while development of functional surfaces that can simultaneously overcome these problems remains highly challenging. This study aimed to fabricate sophisticated Ti implant surface with both osteogenic inducing activity and inherent antibacterial ability simply via tailoring surface topographical features. Micro/submciro/nano-scale structure was constructed on Ti by three cumulative subtractive methods, including sequentially conducted sandblasting as well as primary and secondary acid etching treatment. Topographical features of this hierarchical structure can be well tuned by the time of the secondary acid treatment. Ti substrate with mere micro/submicro-scale structure (MS0-Ti) served as a control to examine the influence of hierarchical structures on surface properties and biological activities. Surface analysis indicated that all hierarchically structured surfaces possessed exactly the same surface chemistry as that of MS0-Ti, and all of them showed super-amphiphilicity, high surface free energy, and high protein adsorption capability. Biological evaluations revealed surprisingly antibacterial ability and excellent osteogenic activity for samples with optimized hierarchical structure (MS30-Ti) when compared with MS0-Ti. Consequently, for the first time, a hierarchically structured Ti surface with topography-induced inherent antibacterial capability and excellent osteogenic activity was constructed. PMID:25146099

  5. Transmutations across hierarchical levels

    International Nuclear Information System (INIS)

    O'Neill, R.V.

    1977-01-01

    The development of large-scale ecological models depends implicitly on a concept known as hierarchy theory which views biological systems in a series of hierarchical levels (i.e., organism, population, trophic level, ecosystem). The theory states that an explanation of a biological phenomenon is provided when it is shown to be the consequence of the activities of the system's components, which are themselves systems in the next lower level of the hierarchy. Thus, the behavior of a population is explained by the behavior of the organisms in the population. The initial step in any modeling project is, therefore, to identify the system components and the interactions between them. A series of examples of transmutations in aquatic and terrestrial ecosystems are presented to show how and why changes occur. The types of changes are summarized and possible implications of transmutation for hierarchy theory, for the modeler, and for the ecological theoretician are discussed

  6. Hierarchical wave functions revisited

    International Nuclear Information System (INIS)

    Li Dingping.

    1997-11-01

    We study the hierarchical wave functions on a sphere and on a torus. We simplify some wave functions on a sphere or a torus using the analytic properties of wave functions. The open question, the construction of the wave function for quasi electron excitation on a torus, is also solved in this paper. (author)

  7. Regression of uveal malignant melanomas following cobalt-60 plaque. Correlates between acoustic spectrum analysis and tumor regression

    International Nuclear Information System (INIS)

    Coleman, D.J.; Lizzi, F.L.; Silverman, R.H.; Ellsworth, R.M.; Haik, B.G.; Abramson, D.H.; Smith, M.E.; Rondeau, M.J.

    1985-01-01

    Parameters derived from computer analysis of digital radio-frequency (rf) ultrasound scan data of untreated uveal malignant melanomas were examined for correlations with tumor regression following cobalt-60 plaque. Parameters included tumor height, normalized power spectrum and acoustic tissue type (ATT). Acoustic tissue type was based upon discriminant analysis of tumor power spectra, with spectra of tumors of known pathology serving as a model. Results showed ATT to be correlated with tumor regression during the first 18 months following treatment. Tumors with ATT associated with spindle cell malignant melanoma showed over twice the percentage reduction in height as those with ATT associated with mixed/epithelioid melanomas. Pre-treatment height was only weakly correlated with regression. Additionally, significant spectral changes were observed following treatment. Ultrasonic spectrum analysis thus provides a noninvasive tool for classification, prediction and monitoring of tumor response to cobalt-60 plaque

  8. Hierarchically nanostructured hydroxyapatite: hydrothermal synthesis, morphology control, growth mechanism, and biological activity

    Science.gov (United States)

    Ma, Ming-Guo

    2012-01-01

    Hierarchically nanosized hydroxyapatite (HA) with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours. Objective The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA) with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks. Methods A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Results HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did not decrease with the increasing concentration of hierarchically nanostructured HA added. Conclusion A novel, simple and reliable hydrothermal route had been developed for the synthesis of

  9. A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting

    Directory of Open Access Journals (Sweden)

    Zhaoxuan Li

    2016-01-01

    Full Text Available We evaluate and compare two common methods, artificial neural networks (ANN and support vector regression (SVR, for predicting energy productions from a solar photovoltaic (PV system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statistics such as mean bias error (MBE, mean absolute error (MAE, root mean square error (RMSE, relative MBE (rMBE, mean percentage error (MPE and relative RMSE (rRMSE. This work provides findings on how forecasts from individual inverters will improve the total solar power generation forecast of the PV system.

  10. Hierarchical partial order ranking

    International Nuclear Information System (INIS)

    Carlsen, Lars

    2008-01-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

  11. Hierarchical control of a nuclear reactor using uncertain dynamics techniques

    International Nuclear Information System (INIS)

    Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.; Perez, R.B.

    1988-01-01

    Recent advances in the nonlinear optimal control area are opening new possibilities towards its implementation in process control. Algorithms for multivariate control, hierarchical decomposition, parameter tracking, model uncertainties actuator saturation effects and physical limits to state variables can be implemented on the basis of a consistent mathematical formulation. In this paper, good agreement is shown between a centralized and a hierarchical implementation of a controller for a hypothetical nuclear power plant subject to multiple demands. The performance of the hierarchical distributed system in the presence of localized subsystem failures is analyzed. 4 refs., 13 figs

  12. Analytical and numerical studies of creation probabilities of hierarchical trees

    Directory of Open Access Journals (Sweden)

    S.S. Borysov

    2011-03-01

    Full Text Available We consider the creation conditions of diverse hierarchical trees both analytically and numerically. A connection between the probabilities to create hierarchical levels and the probability to associate these levels into a united structure is studied. We argue that a consistent probabilistic picture requires the use of deformed algebra. Our consideration is based on the study of the main types of hierarchical trees, among which both regular and degenerate ones are studied analytically, while the creation probabilities of Fibonacci, scale-free and arbitrary trees are determined numerically.

  13. Effects of different petal thickness on gas sensing properties of flower-like WO3·H2O hierarchical architectures

    International Nuclear Information System (INIS)

    Zeng, Wen; Zhang, He; Wang, Zhongchang

    2015-01-01

    Graphical abstract: In this work, we prepare four different petal thicknesses of hierarchical WO 3 ·H 2 O architectures via a simple hydrothermal process, and systematically report their formation mechanisms and gas-sensing properties. - Highlights: • Flower-like WO 3 ·H 2 O architectures with different petal thickness were reported. • The WO 3 ·H 2 O sheet-flower sensor shows a significantly enhanced gas response. • A possible growth mechanism for the flower-like architectures is proposed. - Abstract: Hierarchical architectures consisting of two-dimensional (2D) nanostructures are of great interest for potential use in recent year. Here, we report the successful synthesis of four hierarchical tungsten oxide flower-like architectures via a simple yet facile hydrothermal method. The as-prepared WO 3 ·H 2 O hierarchical architectures are in fact assembled with numerous nanosheets or nanoplates. Through a comprehensive characterization of microstructures and morphologies of the as-prepared products, we find that petal thickness is a key factor for affecting gas-sensing performances. We further propose a possible growth mechanism for the four flower-like architectures. Moreover, gas-sensing measurements showed that the well-defined sheet-flower WO 3 ·H 2 O hierarchical architectures exhibited the excellent gas-sensing properties to ethanol owing to their largest amount of thin petal structures and pores

  14. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    OpenAIRE

    Chih-Yu Wen; Ying-Chih Chen

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show t...

  15. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  16. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

  17. Superhydrophobic polytetrafluoroethylene thin films with hierarchical roughness deposited using a single step vapor phase technique

    International Nuclear Information System (INIS)

    Gupta, Sushant; Arjunan, Arul Chakkaravarthi; Deshpande, Sameer; Seal, Sudipta; Singh, Deepika; Singh, Rajiv K.

    2009-01-01

    Superhydrophobic polytetrafluoroethylene films with hierarchical surface roughness were deposited using pulse electron deposition technique. We were able to modulate roughness of the deposited films by controlling the beam energy and hence the electron penetration depth. The films deposited at higher beam energy showed contact angle as high as 166 o . The scanning electron and atomic force microscope studies revealed clustered growth and two level sub-micron asperities on films deposited at higher energies. Such dual-scale hierarchical roughness and heterogeneities at the water-surface interface was attributed to the observed contact angle and thus its superhydrophobic nature.

  18. Superhydrophobic polytetrafluoroethylene thin films with hierarchical roughness deposited using a single step vapor phase technique

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Sushant, E-mail: sushant3@ufl.ed [Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32611 (United States); Arjunan, Arul Chakkaravarthi [Sinmat Incorporated, 2153 SE Hawthorne Road, 129, Gainesville, Florida 32641 (United States); Deshpande, Sameer; Seal, Sudipta [Advanced Material Processing and Analysis Center, University of Central Florida, Orlando, Florida 32816 (United States); Singh, Deepika [Sinmat Incorporated, 2153 SE Hawthorne Road, 129, Gainesville, Florida 32641 (United States); Singh, Rajiv K. [Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32611 (United States)

    2009-06-30

    Superhydrophobic polytetrafluoroethylene films with hierarchical surface roughness were deposited using pulse electron deposition technique. We were able to modulate roughness of the deposited films by controlling the beam energy and hence the electron penetration depth. The films deposited at higher beam energy showed contact angle as high as 166{sup o}. The scanning electron and atomic force microscope studies revealed clustered growth and two level sub-micron asperities on films deposited at higher energies. Such dual-scale hierarchical roughness and heterogeneities at the water-surface interface was attributed to the observed contact angle and thus its superhydrophobic nature.

  19. Biomimetic "Cactus Spine" with Hierarchical Groove Structure for Efficient Fog Collection.

    Science.gov (United States)

    Bai, Fan; Wu, Juntao; Gong, Guangming; Guo, Lin

    2015-07-01

    A biomimetic "cactus spine" with hierarchical groove structure is designed and fabricated using simple electrospinning. This novel artificial cactus spine possesses excellent fog collection and water transportation ability. A model cactus equipped with artificial spines also shows a great water storage capacity. The results can be helpful in the development of water collectors and may make a contribution to the world water crisis.

  20. Preparing electrochemical active hierarchically porous carbons for detecting nitrite in drinkable water

    KAUST Repository

    Ding, Baojun

    2016-01-13

    A class of hierarchically porous carbons were prepared by a facile dual-templating approach. The obtained samples were characterized by scanning electron microscopy, X-ray diffraction, Raman spectroscopy, Brunaner-Emmett-Teller measurement and electrochemical work station, respectively. The porous carbons could possess large specific surface area, interconnected pore structures, high conductivity and graphitizing degree. The resulting materials were used to prepare integrated modified electrodes. Based on the experimental results, the as-prepared hierarchically porous graphite (HPG) modified electrode showed the best electroactive performances toward the detection of nitrite with a detection limit of 8.1 × 10-3 mM. This HPG electrode was also repeatable and stable for 6 weeks. Moreover, this electrode was used for the determination of nitrite in drinkable water, and had acceptable recoveries. © The Royal Society of Chemistry 2016.

  1. Hierarchically structured materials for lithium batteries

    International Nuclear Information System (INIS)

    Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

    2013-01-01

    The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg −1 ), new energy storage systems, such as lithium–oxygen (Li–O 2 ) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li–O 2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime. (paper)

  2. Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

    Science.gov (United States)

    Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

    2007-09-01

    Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

  3. Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

    Science.gov (United States)

    Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

    2012-11-01

    This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

  4. The role of supramolecular chemistry in stimuli responsive and hierarchically structured functional organic materials

    NARCIS (Netherlands)

    Schenning, A.P.H.J.; Bastiaansen, C.W.M.; Broer, D.J.; Debije, M.G.

    2014-01-01

    ABSTRACT: In this review, we show the important role of supramolecular chemistry in the fabrication of stimuli responsive and hierarchically structured liquid crystalline polymer networks. Supramolecular interactions can be used to create three dimensional order or as molecular triggers in materials

  5. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  6. Show me the money: incorporating financial motives into the gambling motives questionnaire.

    Science.gov (United States)

    Dechant, Kristianne

    2014-12-01

    Although research has only recently begun to measure what motivates all levels of gambling involvement, motives could offer a theoretically interesting and practical way to subtype gamblers in research and for responsible gambling initiatives. The Gambling Motives Questionnaire (GMQ) is one measure that weaves together much of the gambling motives literature, but it has been criticized for neglecting financial reasons for gambling. This study uses a series of factor analyses to explore the effect of adding nine financial motives to the GMQ in a heterogeneous sample of 1,014 adult past-year gamblers. After trimming trivial financial motives, the penultimate factor analysis of the 15 GMQ items and four financial motives led to a four-factor solution, with factors tapping enhancement, social, coping and financial motives, as predicted. A final factor analysis performed on a modified GMQ-F (i.e., 16 items, including a financial subscale) revealed the same four factors, and hierarchical regression showed that the financial motives improve the GMQ-F's prediction of gambling frequency. This study provides evidence that omitting financial motives is a clear gap in the GMQ, yet suggests that the GMQ is a promising tool that can be conceptually and empirically strengthened with the simple addition of financial items.

  7. Facile synthesis of TiO2 hierarchical microspheres assembled by ultrathin nanosheets for dye-sensitized solar cells

    International Nuclear Information System (INIS)

    Xu, Fang; Zhang, Xuyan; Wu, Yao; Wu, Dapeng; Gao, Zhiyong; Jiang, Kai

    2013-01-01

    Highlights: •TiO 2 hierarchical spheres were prepared via one-pot solvothermal route. •TiO 2 hierarchical spheres based DSSCs shows a conversion efficiency of 5.56%. •The performance of DSSC is dependence of the thickness of photoanode. -- Abstract: TiO 2 hierarchical microspheres assembled by ultrathin nanosheets were prepared via solvothermal route for dye-sensitized solar cells (DSSCs). The performance of cells was investigated by diffuse and reflectance spectra, photocurrent–voltage measurement, incident-photon-to-current conversion efficiency and electrochemical impedance spectra. Photoanodes with different thickness of TiO 2 hierarchical spheres were studied, which proves that the photoanode with thickness of 15.9 μm exhibits higher performance (short-circuit current density of 12.36 mA cm −2 , open-circuit voltage of 0.73 mV, fill factor of 61.95, and conversion efficiency of 5.56%) than that of P25-based DSSC due to the excellent particle interconnections, low electron recombination and high specific surface area (78 m 2 g −1 )

  8. Hierarchically structured lithium titanate for ultrafast charging in long-life high capacity batteries

    Science.gov (United States)

    Odziomek, Mateusz; Chaput, Frédéric; Rutkowska, Anna; Świerczek, Konrad; Olszewska, Danuta; Sitarz, Maciej; Lerouge, Frédéric; Parola, Stephane

    2017-05-01

    High-performance Li-ion batteries require materials with well-designed and controlled structures on nanometre and micrometre scales. Electrochemical properties can be enhanced by reducing crystallite size and by manipulating structure and morphology. Here we show a method for preparing hierarchically structured Li4Ti5O12 yielding nano- and microstructure well-suited for use in lithium-ion batteries. Scalable glycothermal synthesis yields well-crystallized primary 4-8 nm nanoparticles, assembled into porous secondary particles. X-ray photoelectron spectroscopy reveals presence of Ti+4 only; combined with chemical analysis showing lithium deficiency, this suggests oxygen non-stoichiometry. Electron microscopy confirms hierarchical morphology of the obtained material. Extended cycling tests in half cells demonstrates capacity of 170 mAh g-1 and no sign of capacity fading after 1,000 cycles at 50C rate (charging completed in 72 s). The particular combination of nanostructure, microstructure and non-stoichiometry for the prepared lithium titanate is believed to underlie the observed electrochemical performance of material.

  9. Hierarchical structure of moral stages assessed by a sorting task

    NARCIS (Netherlands)

    Boom, J.; Brugman, D.; Van der Heijden, P.G.M.

    2001-01-01

    Following criticism of Kohlberg’s theory of moral judgment, an empirical re-examination of hierarchical stage structure was desirable. Utilizing Piaget’s concept of reflective abstraction as a basis, the hierarchical stage structure was investigated using a new method. Study participants (553 Dutch

  10. Structural Group-based Auditing of Missing Hierarchical Relationships in UMLS

    Science.gov (United States)

    Chen, Yan; Gu, Huanying(Helen); Perl, Yehoshua; Geller, James

    2009-01-01

    The Metathesaurus of the UMLS was created by integrating various source terminologies. The inter-concept relationships were either integrated into the UMLS from the source terminologies or specially generated. Due to the extensive size and inherent complexity of the Metathesaurus, the accidental omission of some hierarchical relationships was inevitable. We present a recursive procedure which allows a human expert, with the support of an algorithm, to locate missing hierarchical relationships. The procedure starts with a group of concepts with exactly the same (correct) semantic type assignments. It then partitions the concepts, based on child-of hierarchical relationships, into smaller, singly rooted, hierarchically connected subgroups. The auditor only needs to focus on the subgroups with very few concepts and their concepts with semantic type reassignments. The procedure was evaluated by comparing it with a comprehensive manual audit and it exhibits a perfect error recall. PMID:18824248

  11. Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

    Science.gov (United States)

    Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

    2014-12-01

    Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

  12. Regression away from the mean: Theory and examples.

    Science.gov (United States)

    Schwarz, Wolf; Reike, Dennis

    2018-02-01

    Using a standard repeated measures model with arbitrary true score distribution and normal error variables, we present some fundamental closed-form results which explicitly indicate the conditions under which regression effects towards (RTM) and away from the mean are expected. Specifically, we show that for skewed and bimodal distributions many or even most cases will show a regression effect that is in expectation away from the mean, or that is not just towards but actually beyond the mean. We illustrate our results in quantitative detail with typical examples from experimental and biometric applications, which exhibit a clear regression away from the mean ('egression from the mean') signature. We aim not to repeal cautionary advice against potential RTM effects, but to present a balanced view of regression effects, based on a clear identification of the conditions governing the form that regression effects take in repeated measures designs. © 2017 The British Psychological Society.

  13. [Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

    Science.gov (United States)

    Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

    2011-11-01

    To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

  14. Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

    Science.gov (United States)

    Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

    2017-06-27

    Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

  15. Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

    Directory of Open Access Journals (Sweden)

    Kritski Afrânio

    2006-02-01

    Full Text Available Abstract Background Smear negative pulmonary tuberculosis (SNPT accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

  16. [From clinical judgment to linear regression model.

    Science.gov (United States)

    Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

    2013-01-01

    When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

  17. Hierarchical periodic micro/nano-structures on nitinol and their influence on oriented endothelialization and anti-thrombosis

    International Nuclear Information System (INIS)

    Nozaki, Kosuke; Shinonaga, Togo; Ebe, Noriko; Horiuchi, Naohiro; Nakamura, Miho; Tsutsumi, Yusuke; Hanawa, Takao; Tsukamoto, Masahiro; Yamashita, Kimihiro; Nagai, Akiko

    2015-01-01

    The applications of hierarchical micro/nano-structures, which possess properties of two-scale roughness, have been studied in various fields. In this study, hierarchical periodic micro/nano-structures were fabricated on nitinol, an equiatomic Ni–Ti alloy, using a femtosecond laser for the surface modification of intravascular stents. By controlling the laser fluence, two types of surfaces were developed: periodic nano- and micro/nano-structures. Evaluation of water contact angles indicated that the nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. Endothelial cells aligned along the nano-structures on both surfaces, whereas platelets failed to adhere to the micro/nano-surface. Decorrelation between the responses of the two cell types and the results of water contact angle analysis were a result of the pinning effect. This is the first study to show the applicability of hierarchical periodic micro/nano-structures for surface modification of nitinol. - Highlights: • Hierarchical micro/nano-structures were created on nitinol using a femtosecond laser. • The nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. • Endothelial cells aligned along the nano-structures • Platelets failed to adhere to the micro/nano-surface

  18. Hierarchical periodic micro/nano-structures on nitinol and their influence on oriented endothelialization and anti-thrombosis

    Energy Technology Data Exchange (ETDEWEB)

    Nozaki, Kosuke [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Shinonaga, Togo [Joining and Welding Research Institute, Osaka University, 11-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Ebe, Noriko; Horiuchi, Naohiro; Nakamura, Miho; Tsutsumi, Yusuke; Hanawa, Takao [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Tsukamoto, Masahiro [Joining and Welding Research Institute, Osaka University, 11-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Yamashita, Kimihiro [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Nagai, Akiko, E-mail: nag-bcr@tmd.ac.jp [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan)

    2015-12-01

    The applications of hierarchical micro/nano-structures, which possess properties of two-scale roughness, have been studied in various fields. In this study, hierarchical periodic micro/nano-structures were fabricated on nitinol, an equiatomic Ni–Ti alloy, using a femtosecond laser for the surface modification of intravascular stents. By controlling the laser fluence, two types of surfaces were developed: periodic nano- and micro/nano-structures. Evaluation of water contact angles indicated that the nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. Endothelial cells aligned along the nano-structures on both surfaces, whereas platelets failed to adhere to the micro/nano-surface. Decorrelation between the responses of the two cell types and the results of water contact angle analysis were a result of the pinning effect. This is the first study to show the applicability of hierarchical periodic micro/nano-structures for surface modification of nitinol. - Highlights: • Hierarchical micro/nano-structures were created on nitinol using a femtosecond laser. • The nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. • Endothelial cells aligned along the nano-structures • Platelets failed to adhere to the micro/nano-surface.

  19. Parental Vaccine Acceptance: A Logistic Regression Model Using Previsit Decisions.

    Science.gov (United States)

    Lee, Sara; Riley-Behringer, Maureen; Rose, Jeanmarie C; Meropol, Sharon B; Lazebnik, Rina

    2017-07-01

    This study explores how parents' intentions regarding vaccination prior to their children's visit were associated with actual vaccine acceptance. A convenience sample of parents accompanying 6-week-old to 17-year-old children completed a written survey at 2 pediatric practices. Using hierarchical logistic regression, for hospital-based participants (n = 216), vaccine refusal history ( P < .01) and vaccine decision made before the visit ( P < .05) explained 87% of vaccine refusals. In community-based participants (n = 100), vaccine refusal history ( P < .01) explained 81% of refusals. Over 1 in 5 parents changed their minds about vaccination during the visit. Thirty parents who were previous vaccine refusers accepted current vaccines, and 37 who had intended not to vaccinate choose vaccination. Twenty-nine parents without a refusal history declined vaccines, and 32 who did not intend to refuse before the visit declined vaccination. Future research should identify key factors to nudge parent decision making in favor of vaccination.

  20. Sparsey^TM: Spatiotemporal Event Recognition via Deep Hierarchical Sparse Distributed Codes

    Directory of Open Access Journals (Sweden)

    Gerard J Rinkus

    2014-12-01

    Full Text Available The visual cortex’s hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes in each representational field (which we equate with the cortical macrocolumn, mac, at each level. In localism, each represented feature/concept/event (hereinafter item is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac’s units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model’s core algorithm, which does both storage and retrieval (inference, makes a single pass over all macs on each time step, the overall model’s storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge (Big Data problems. A 2010 paper described a non-hierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level, describing novel model principles like progressive critical periods, dynamic modulation of principal cells’ activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of

  1. Hierarchical video summarization based on context clustering

    Science.gov (United States)

    Tseng, Belle L.; Smith, John R.

    2003-11-01

    A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

  2. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

  3. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

    Energy Technology Data Exchange (ETDEWEB)

    Nash, Stephen G.

    2013-11-11

    The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

  5. Hierarchical pulmonary target nanoparticles via inhaled administration for anticancer drug delivery.

    Science.gov (United States)

    Chen, Rui; Xu, Liu; Fan, Qin; Li, Man; Wang, Jingjing; Wu, Li; Li, Weidong; Duan, Jinao; Chen, Zhipeng

    2017-11-01

    Inhalation administration, compared with intravenous administration, significantly enhances chemotherapeutic drug exposure to the lung tissue and may increase the therapeutic effect for pulmonary anticancer. However, further identification of cancer cells after lung deposition of inhaled drugs is necessary to avoid side effects on normal lung tissue and to maximize drug efficacy. Moreover, as the action site of the major drug was intracellular organelles, drug target to the specific organelle is the final key for accurate drug delivery. Here, we designed a novel multifunctional nanoparticles (MNPs) for pulmonary antitumor and the material was well-designed for hierarchical target involved lung tissue target, cancer cell target, and mitochondrial target. The biodistribution in vivo determined by UHPLC-MS/MS method was employed to verify the drug concentration overwhelmingly increasing in lung tissue through inhaled administration compared with intravenous administration. Cellular uptake assay using A549 cells proved the efficient receptor-mediated cell endocytosis. Confocal laser scanning microscopy observation showed the location of MNPs in cells was mitochondria. All results confirmed the intelligent material can progressively play hierarchical target functions, which could induce more cell apoptosis related to mitochondrial damage. It provides a smart and efficient nanocarrier platform for hierarchical targeting of pulmonary anticancer drug. So far, this kind of material for pulmonary mitochondrial-target has not been seen in other reports.

  6. Hierarchical cultural values predict success and mortality in high-stakes teams

    Science.gov (United States)

    Anicich, Eric M.; Swaab, Roderick I.; Galinsky, Adam D.

    2015-01-01

    Functional accounts of hierarchy propose that hierarchy increases group coordination and reduces conflict. In contrast, dysfunctional accounts claim that hierarchy impairs performance by preventing low-ranking team members from voicing their potentially valuable perspectives and insights. The current research presents evidence for both the functional and dysfunctional accounts of hierarchy within the same dataset. Specifically, we offer empirical evidence that hierarchical cultural values affect the outcomes of teams in high-stakes environments through group processes. Experimental data from a sample of expert mountain climbers from 27 countries confirmed that climbers expect that a hierarchical culture leads to improved team coordination among climbing teams, but impaired psychological safety and information sharing compared with an egalitarian culture. An archival analysis of 30,625 Himalayan mountain climbers from 56 countries on 5,104 expeditions found that hierarchy both elevated and killed in the Himalayas: Expeditions from more hierarchical countries had more climbers reach the summit, but also more climbers die along the way. Importantly, we established the role of group processes by showing that these effects occurred only for group, but not solo, expeditions. These findings were robust to controlling for environmental factors, risk preferences, expedition-level characteristics, country-level characteristics, and other cultural values. Overall, this research demonstrates that endorsing cultural values related to hierarchy can simultaneously improve and undermine group performance. PMID:25605883

  7. Synthesis and properties of ZnFe{sub 2}O{sub 4} replica with biological hierarchical structure

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hongyan; Guo, Yiping, E-mail: ypguo@sjtu.edu.cn; Zhang, Yangyang; Wu, Fen; Liu, Yun; Zhang, Di, E-mail: zhangdi@sjtu.edu.cn

    2013-09-20

    Highlights: • ZFO replica with hierarchical structure was synthesized from butterfly wings. • Biotemplate has a significant impact on the properties of ZFO material. • Our method opens up new avenues for the synthesis of spinel ferrites. -- Abstract: ZnFe{sub 2}O{sub 4} replica with biological hierarchical structure was synthesized from Papilio paris by a sol–gel method followed by calcination. The crystallographic structure and morphology of the obtained samples were characterized by X-ray diffraction, field-emission scanning electron microscope, and transmittance electron microscope. The results showed that the hierarchical structures were retained in the ZFO replica of spinel structure. The magnetic behavior of such novel products was measured by a vibrating sample magnetometer. A superparamagnetism-like behavior was observed due to nanostructuration size effects. In addition, the ZFO replica with “quasi-honeycomb-like structure” showed a much higher specific capacitance of 279.4 F g{sup −1} at 10 mV s{sup −1} in comparison with ZFO powder of 137.3 F g{sup −1}, attributing to the significantly increased surface area. These results demonstrated that ZFO replica is a promising candidate for novel magnetic devices and supercapacitors.

  8. Hierarchical Control for Multiple DC-Microgrids Clusters

    DEFF Research Database (Denmark)

    Shafiee, Qobad; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2014-01-01

    DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed in this p......DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed...

  9. Hierarchical MAS based control strategy for microgrid

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Z.; Li, T.; Huang, M.; Shi, J.; Yang, J.; Yu, J. [School of Information Science and Engineering, Yunnan University, Kunming 650091 (China); Xiao, Z. [School of Electrical and Electronic Engineering, Nanyang Technological University, Western Catchment Area, 639798 (Singapore); Wu, W. [Communication Branch of Yunnan Power Grid Corporation, Kunming, Yunnan 650217 (China)

    2010-09-15

    Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness. (authors)

  10. Fluorocarbon adsorption in hierarchical porous frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Motkuri, RK; Annapureddy, HVR; Vijaykumar, M; Schaef, HT; Martin, PF; McGrail, BP; Dang, LX; Krishna, R; Thallapally, PK

    2014-07-09

    Metal-organic frameworks comprise an important class of solid-state materials and have potential for many emerging applications such as energy storage, separation, catalysis and bio-medical. Here we report the adsorption behaviour of a series of fluorocarbon derivatives on a set of microporous and hierarchical mesoporous frameworks. The microporous frameworks show a saturation uptake capacity for dichlorodifluoromethane of >4 mmol g(-1) at a very low relative saturation pressure (P/P-o) of 0.02. In contrast, the mesoporous framework shows an exceptionally high uptake capacity reaching >14 mmol g(-1) at P/P-o of 0.4. Adsorption affinity in terms of mass loading and isosteric heats of adsorption is found to generally correlate with the polarizability and boiling point of the refrigerant, with dichlorodifluoromethane >chlorodifluoromethane >chlorotrifluoromethane >tetrafluoromethane >methane. These results suggest the possibility of exploiting these sorbents for separation of azeotropic mixtures of fluorocarbons and use in eco-friendly fluorocarbon-based adsorption cooling.

  11. Hierarchical Trust Management of COI in Heterogeneous Mobile Networks

    Science.gov (United States)

    2017-08-01

    Report: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks The views, opinions and/or findings contained in this report are those of...Institute & State University Title: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks Report Term: 0-Other Email: irchen@vt.edu...Reconfigurability, Survivability and Intrusion Tolerance for Community of Interest (COI) Applications – Our proposed COI trust management protocol will

  12. Metastable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network

    International Nuclear Information System (INIS)

    Agliari, Elena; Barra, Adriano; Guerra, Francesco; Galluzzi, Andrea; Tantari, Daniele; Tavani, Flavia

    2015-01-01

    In this paper, we introduce and investigate the statistical mechanics of hierarchical neural networks. First, we approach these systems à la Mattis, by thinking of the Dyson model as a single-pattern hierarchical neural network. We also discuss the stability of different retrievable states as predicted by the related self-consistencies obtained both from a mean-field bound and from a bound that bypasses the mean-field limitation. The latter is worked out by properly reabsorbing the magnetization fluctuations related to higher levels of the hierarchy into effective fields for the lower levels. Remarkably, mixing Amit's ansatz technique for selecting candidate-retrievable states with the interpolation procedure for solving for the free energy of these states, we prove that, due to gauge symmetry, the Dyson model accomplishes both serial and parallel processing. We extend this scenario to multiple stored patterns by implementing the Hebb prescription for learning within the couplings. This results in Hopfield-like networks constrained on a hierarchical topology, for which, by restricting to the low-storage regime where the number of patterns grows at its most logarithmical with the amount of neurons, we prove the existence of the thermodynamic limit for the free energy, and we give an explicit expression of its mean-field bound and of its related improved bound. We studied the resulting self-consistencies for the Mattis magnetizations, which act as order parameters, are studied and the stability of solutions is analyzed to get a picture of the overall retrieval capabilities of the system according to both mean-field and non-mean-field scenarios. Our main finding is that embedding the Hebbian rule on a hierarchical topology allows the network to accomplish both serial and parallel processing. By tuning the level of fast noise affecting it or triggering the decay of the interactions with the distance among neurons, the system may switch from sequential retrieval to

  13. Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

    Science.gov (United States)

    Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

    2014-04-29

    To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

  14. Translating Management Practices in Hierarchical Organizations

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe Agger

    structures affect translators’ approaches taken towards management ideas. This paper reports the findings from a longitudinal case study of the translation of Leadership Pipeline in a Danish fire department and how the translators’ approach changed over time from a modifying to a reproducing mode. The study......This study examines how translators in a hierarchical context approach the translation of management practices. Although current translation theory and research emphasize the importance of contextual factors in translation processes, little research has investigated how strongly hierarchical...... finds that translation does not necessarily imply transformation of the management idea, pointing instead to aspects of exact imitation and copying of an ”original” idea. It also highlights how translation is likely to involve multiple and successive translation modes and, furthermore, that strongly...

  15. Scalable 2D Hierarchical Porous Carbon Nanosheets for Flexible Supercapacitors with Ultrahigh Energy Density.

    Science.gov (United States)

    Yao, Lei; Wu, Qin; Zhang, Peixin; Zhang, Junmin; Wang, Dongrui; Li, Yongliang; Ren, Xiangzhong; Mi, Hongwei; Deng, Libo; Zheng, Zijian

    2018-03-01

    2D carbon nanomaterials such as graphene and its derivatives, have gained tremendous research interests in energy storage because of their high capacitance and chemical stability. However, scalable synthesis of ultrathin carbon nanosheets with well-defined pore architectures remains a great challenge. Herein, the first synthesis of 2D hierarchical porous carbon nanosheets (2D-HPCs) with rich nitrogen dopants is reported, which is prepared with high scalability through a rapid polymerization of a nitrogen-containing thermoset and a subsequent one-step pyrolysis and activation into 2D porous nanosheets. 2D-HPCs, which are typically 1.5 nm thick and 1-3 µm wide, show a high surface area (2406 m 2 g -1 ) and with hierarchical micro-, meso-, and macropores. This 2D and hierarchical porous structure leads to robust flexibility and good energy-storage capability, being 139 Wh kg -1 for a symmetric supercapacitor. Flexible supercapacitor devices fabricated by these 2D-HPCs also present an ultrahigh volumetric energy density of 8.4 mWh cm -3 at a power density of 24.9 mW cm -3 , which is retained at 80% even when the power density is increased by 20-fold. The devices show very high electrochemical life (96% retention after 10000 charge/discharge cycles) and excellent mechanical flexibility. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Hydrothermal synthesis of hierarchical WO{sub 3} nanostructures for dye-sensitized solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Rashad, M.M. [Central Metallurgical Research and Development Institute (CMRDI), Helwan, P.O. Box 87, Cairo (Egypt); Shalan, A.E. [Central Metallurgical Research and Development Institute (CMRDI), Helwan, P.O. Box 87, Cairo (Egypt); Friedrich-Alexander-University of Erlangen-Nuremberg, Institute of Materials for Electronics and Energy Technology (i-MEET), Erlangen (Germany)

    2014-08-15

    Hierarchical architectures consisting of one-dimensional (1D) nanostructures are of great interest for potential use in energy and environmental applications in recent years. In this work, hierarchical tungsten oxide (WO{sub 3}) has been synthesized via a facile hydrothermal route from ammonium metatungstate hydrate and implemented as photoelectrode for dye-sensitized solar cells. The urchin-like WO{sub 3} micro-patterns are constructed by self-organized nanoscale length 1D building blocks, which are single crystalline in nature, grown along (001) direction and confirm an orthorhombic crystal phase. The obtained powders were investigated by XRD, SEM, TEM and UV-Vis Spectroscopy. The photovoltaic performance of dye-sensitized solar cells based on WO{sub 3} photoanodes was investigated. With increasing the calcination temperature of the prepared nanopowders, the light-electricity conversion efficiency (η) was increased. The results were attributed to increase the crystallinity of the particles and ease of electron movement. The DSSC based on hierarchical WO{sub 3} showed a short-circuit current, an open-circuit voltage, a fill factor, and a conversion efficiency of 4.241 mA/cm{sup 2}, 0.656 V, 66.74, and 1.85 %, respectively. (orig.)

  17. Carbon fiber reinforced hierarchical orthogrid stiffened cylinder: Fabrication and testing

    Science.gov (United States)

    Wu, Hao; Lai, Changlian; Sun, Fangfang; Li, Ming; Ji, Bin; Wei, Weiyi; Liu, Debo; Zhang, Xi; Fan, Hualin

    2018-04-01

    To get strong, stiff and light cylindrical shell, carbon fiber reinforced hierarchical orthogrid stiffened cylinders are designed and fabricated. The cylinder is stiffened by two-scale orthogrid. The primary orthogrid has thick and high ribs and contains several sub-orthogrid cells whose rib is much thinner and lower. The primary orthogrid stiffens the bending rigidity of the cylinder to resist the global instability while the sub-orthogrid stiffens the bending rigidity of the skin enclosed by the primary orthogrid to resist local buckling. The cylinder is fabricated by filament winding method based on a silicone rubber mandrel with hierarchical grooves. Axial compression tests are performed to reveal the failure modes. With hierarchical stiffeners, the cylinder fails at skin fracture and has high specific strength. The cylinder will fail at end crushing if the end of the cylinder is not thickened. Global instability and local buckling are well restricted by the hierarchical stiffeners.

  18. In-situ preparation of Fe{sub 2}O{sub 3} hierarchical arrays on stainless steel substrate for high efficient catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Zeheng, E-mail: zehengyang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Wang, Kun; Shao, Zongming; Tian, Yuan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Chen, Gongde [Department of Chemical and Environmental Engineering, University of California at Riverside, Riverside, CA 92521 (United States); Wang, Kai; Chen, Zhangxian; Dou, Yan [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China); Zhang, Weixin, E-mail: wxzhang@hfut.edu.cn [School of Chemistry and Chemical Engineering, Anhui Key Laboratory of Controllable Chemical Reaction & Material Chemical Engineering, Hefei University of Technology, Hefei, Anhui 230009 (China)

    2017-02-15

    Hierarchical array catalysts with micro/nano structures on substrates not only possess high reactivity from large surface area and suitable interface, but intensify mass transfer through shortening the diffusion paths of both reactants and products for high catalytic efficiency. Herein, we first demonstrate fabrication of Fe{sub 2}O{sub 3} hierarchical arrays grown on stainless-steel substrates via in-situ hydrothermal chemical oxidation followed by heat treatment in N{sub 2} atmosphere. As a Fenton-like catalyst, Fe{sub 2}O{sub 3} hierarchical arrays exhibit excellent catalytic activity and life cycle performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. The Fe{sub 2}O{sub 3} catalyst with unique hierarchical structures and efficient transport channels, effectively activates H{sub 2}O{sub 2} to generate large quantity of • OH radicals and highly promotes reaction kinetics between MB and • OH radicals. Immobilization of hierarchical array catalysts on stainless-steel can prevent particles agglomeration, facilitate the recovery and reuse of the catalysts, which is expected promising applications in wastewater remediation. - Graphical abstract: The in-situ synthesis of Fe{sub 2}O{sub 3} hierarchical arrays on stainless-steel substrates was reported for the first time, which exhibit excellent catalytic activity performance for methylene blue (MB) dye degradation in aqueous solution in the presence of H{sub 2}O{sub 2}. - Highlights: • Fe{sub 2}O{sub 3} hierarchical arrays was prepared by in-situ hydrothermal chemical oxidation. • F{sup −} ions play an important role in the formation of the Fe{sub 2}O{sub 3} hierarchical arrays. • Fe{sub 2}O{sub 3} hierarchical arrays show high catalytic activity to methylene blue degradation.

  19. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  20. Hierarchical Bayesian sparse image reconstruction with application to MRFM.

    Science.gov (United States)

    Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves

    2009-09-01

    This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.

  1. HiPS - Hierarchical Progressive Survey Version 1.0

    Science.gov (United States)

    Fernique, Pierre; Allen, Mark; Boch, Thomas; Donaldson, Tom; Durand, Daniel; Ebisawa, Ken; Michel, Laurent; Salgado, Jesus; Stoehr, Felix; Fernique, Pierre

    2017-05-01

    This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.

  2. Construction of 3D Arrays of Cylindrically Hierarchical Structures with ZnO Nanorods Hydrothermally Synthesized on Optical Fiber Cores

    Directory of Open Access Journals (Sweden)

    Weixuan Jing

    2014-01-01

    Full Text Available With ZnO nanorods hydrothermally synthesized on manually assembled arrays of optical fiber cores, 3D arrays of ZnO nanorod-based cylindrically hierarchical structures with nominal pitch 250 μm or 375 μm were constructed. Based on micrographs of scanning electron microscopy and image processing operators of MATLAB software, the 3D arrays of cylindrically hierarchical structures were quantitatively characterized. The values of the actual diameters, the actual pitches, and the parallelism errors suggest that the process capability of the manual assembling is sufficient and the quality of the 3D arrays of cylindrically hierarchical structures is acceptable. The values of the characteristic parameters such as roughness, skewness, kurtosis, correlation length, and power spectrum density show that the surface morphologies of the cylindrically hierarchical structures not only were affected significantly by Zn2+ concentration of the growth solution but also were anisotropic due to different curvature radii of the optical fiber core at side and front view.

  3. Glycine assisted synthesis of flower-like TiO2 hierarchical spheres and its application in photocatalysis

    International Nuclear Information System (INIS)

    Tao, Yu-gui; Xu, Yan-qiu; Pan, Jun; Gu, Hao; Qin, Chang-yun; Zhou, Peng

    2012-01-01

    Graphical abstract: Flower-like anatase TiO 2 hierarchical spheres assembled by nanosheets were synthesized by glycine assistant via a simple hydrothermal approach and after-annealing process. The obtained TiO 2 sample showed good photocatalytic activity of decomposition of methyl orange under sunlight. Highlights: ► Flower-like TiO 2 hierarchical spheres were synthesized by glycine assistant. ► Reaction time, temperature, solution pH and glycine dosage were studied. ► The formation of the flower-like TiO 2 spheres is an Ostwald ripening process. ► Flower-like TiO 2 showed high photocatalytic activity under sunlight. - Abstract: Flower-like anatase TiO 2 hierarchical spheres assembled by nanosheets were synthesized by glycine assistant via a simple hydrothermal approach and after-annealing process. These flower-like spheres are about 2 μm in diameter with sheet thickness about 20 nm. Results showed reaction time, temperature, solution pH and glycine dosage all played an important role in control of shape and size of the as-synthesized TiO 2 nanocrystals. The photocatalytic activity of this nano-TiO 2 was evaluated by the photocatalytic oxidation decomposition of methyl orange under sunlight illumination in the presence of hydrogen peroxide (H 2 O 2 ). The photocatalytic activity of the obtained TiO 2 was higher than that of commercial TiO 2 .

  4. Easy synthesis of hierarchical carbon spheres with superior capacitive performance in supercapacitors.

    Science.gov (United States)

    Huang, Xinhua; Kim, Seok; Heo, Min Seon; Kim, Ji Eun; Suh, Hongsuk; Kim, Il

    2013-10-01

    An easy template-free approach to the fabrication of pure carbon microspheres has been achieved via direct pyrolysis of as-prepared polyaromatic hydrocarbons including polynaphthalene and polypyrene. The polyaromatics were synthesized from aromatic hydrocarbons (AHCs) using anhydrous zinc chloride as the Friedel-Crafts catalyst and chloromethyl methyl ether as a cross-linker. The experimental results show that the methylene bridges between phenyl rings generate a hierarchical porous polyaromatic precursor to form three-dimensionally (3D) interconnected micro-, meso-, and macroporous networks during carbonization. These hierarchical porous carbon aggregates of spherical carbon spheres exhibit faster ion transport/diffusion behavior and increased surface area usage in electric double-layer capacitors. Furthermore, micropores are present in the 3D interconnected network inside the cross-linked AHC-based carbon microspheres, thus imparting an exceptionally large, electrochemically accessible surface area for charge accumulation.

  5. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  6. Road network safety evaluation using Bayesian hierarchical joint model.

    Science.gov (United States)

    Wang, Jie; Huang, Helai

    2016-05-01

    Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Hierarchical Microaggressions in Higher Education

    Science.gov (United States)

    Young, Kathryn; Anderson, Myron; Stewart, Saran

    2015-01-01

    Although there has been substantial research examining the effects of microaggressions in the public sphere, there has been little research that examines microaggressions in the workplace. This study explores the types of microaggressions that affect employees at universities. We coin the term "hierarchical microaggression" to represent…

  8. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  9. Hierarchical nanoflowers assembled with Au nanoparticles decorated ZnO nanosheets toward enhanced photocatalytic properties

    DEFF Research Database (Denmark)

    Yu, Cuiyan; Yu, Yanlong; Xu, Tao

    2017-01-01

    Hierarchical nanoflowers assembled with Au nanoparticles (NPs) decorated ZnO nanosheets (Au-ZnO nanosheet flowers, AZNSFs) were successful synthesized. The AZNSFs showed more efficient activity to photodegradation of RhB than that of pure ZnO nanosheet flowers and commercial ZnO nanopowders. The ...

  10. Stability of glassy hierarchical networks

    Science.gov (United States)

    Zamani, M.; Camargo-Forero, L.; Vicsek, T.

    2018-02-01

    The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

  11. Hierarchical Semantic Model of Geovideo

    Directory of Open Access Journals (Sweden)

    XIE Xiao

    2015-05-01

    Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

  12. A Hierarchical Security Architecture for Cyber-Physical Systems

    Energy Technology Data Exchange (ETDEWEB)

    Quanyan Zhu; Tamer Basar

    2011-08-01

    Security of control systems is becoming a pivotal concern in critical national infrastructures such as the power grid and nuclear plants. In this paper, we adopt a hierarchical viewpoint to these security issues, addressing security concerns at each level and emphasizing a holistic cross-layer philosophy for developing security solutions. We propose a bottom-up framework that establishes a model from the physical and control levels to the supervisory level, incorporating concerns from network and communication levels. We show that the game-theoretical approach can yield cross-layer security strategy solutions to the cyber-physical systems.

  13. Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

    Science.gov (United States)

    Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

    2018-01-01

    In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

  14. TiO2 nanowire-templated hierarchical nanowire network as water-repelling coating

    Science.gov (United States)

    Hang, Tian; Chen, Hui-Jiuan; Xiao, Shuai; Yang, Chengduan; Chen, Meiwan; Tao, Jun; Shieh, Han-ping; Yang, Bo-ru; Liu, Chuan; Xie, Xi

    2017-12-01

    Extraordinary water-repelling properties of superhydrophobic surfaces make them novel candidates for a great variety of potential applications. A general approach to achieve superhydrophobicity requires low-energy coating on the surface and roughness on nano- and micrometre scale. However, typical construction of superhydrophobic surfaces with micro-nano structure through top-down fabrication is restricted by sophisticated fabrication techniques and limited choices of substrate materials. Micro-nanoscale topographies templated by conventional microparticles through surface coating may produce large variations in roughness and uncontrollable defects, resulting in poorly controlled surface morphology and wettability. In this work, micro-nanoscale hierarchical nanowire network was fabricated to construct self-cleaning coating using one-dimensional TiO2 nanowires as microscale templates. Hierarchical structure with homogeneous morphology was achieved by branching ZnO nanowires on the TiO2 nanowire backbones through hydrothermal reaction. The hierarchical nanowire network displayed homogeneous micro/nano-topography, in contrast to hierarchical structure templated by traditional microparticles. This hierarchical nanowire network film exhibited high repellency to both water and cell culture medium after functionalization with fluorinated organic molecules. The hierarchical structure templated by TiO2 nanowire coating significantly increased the surface superhydrophobicity compared to vertical ZnO nanowires with nanotopography alone. Our results demonstrated a promising strategy of using nanowires as microscale templates for the rational design of hierarchical coatings with desired superhydrophobicity that can also be applied to various substrate materials.

  15. Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

    Directory of Open Access Journals (Sweden)

    Yoshinobu Hagiwara

    2018-03-01

    Full Text Available In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA. Object recognition results using convolutional neural network (CNN, hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL, and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

  16. On hierarchical solutions to the BBGKY hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.

    1988-01-01

    It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

  17. Statistical dynamics of ultradiffusion in hierarchical systems

    International Nuclear Information System (INIS)

    Gardner, S.

    1987-01-01

    In many types of disordered systems which exhibit frustration and competition, an ultrametric topology is found to exist in the space of allowable states. This ultrametric topology of states is associated with a hierarchical relaxation process called ultradiffusion. Ultradiffusion occurs in hierarchical non-linear (HNL) dynamical systems when constraints cause large scale, slow modes of motion to be subordinated to small scale, fast modes. Examples of ultradiffusion are found throughout condensed matter physics and critical phenomena (e.g. the states of spin glasses), in biophysics (e.g. the states of Hopfield networks) and in many other fields including layered computing based upon nonlinear dynamics. The statistical dynamics of ultradiffusion can be treated as a random walk on an ultrametric space. For reversible bifurcating ultrametric spaces the evolution equation governing the probability of a particle being found at site i at time t has a highly degenerate transition matrix. This transition matrix has a fractal geometry similar to the replica form proposed for spin glasses. The authors invert this fractal matrix using a recursive quad-tree (QT) method. Possible applications of hierarchical systems to communications and symbolic computing are discussed briefly

  18. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  19. Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

    Science.gov (United States)

    Peng, Jiankun; He, Hongwen; Guo, Hongqiang

    2015-01-01

    This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved. PMID:26236772

  20. Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle.

    Science.gov (United States)

    Peng, Jiankun; He, Hongwen; Liu, Wei; Guo, Hongqiang

    2015-01-01

    This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

  1. Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Jiankun Peng

    2015-01-01

    Full Text Available This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

  2. Hierarchically Structured Electrospun Fibers

    Science.gov (United States)

    2013-01-07

    in the natural lotus and silver ragwort leaves. Figure 4. Examples of electrospun bio-mimics of natural hierarchical structures. (A) Lotus leaf...B) pillared poly(methyl methacrylate) (PMMA) electrospun fiber mimic; (C) silver ragwort leaf; (D) electrospun fiber mimic made from nylon 6 and...domains containing the protein in the surrounding EVA fibers [115]. A wide variety of core-shell fibers have been generated, including PCL/ gelatin

  3. Hierarchical Graphene-Encapsulated Hollow SnO2@SnS2 Nanostructures with Enhanced Lithium Storage Capability.

    Science.gov (United States)

    Xu, Wangwang; Xie, Zhiqiang; Cui, Xiaodan; Zhao, Kangning; Zhang, Lei; Dietrich, Grant; Dooley, Kerry M; Wang, Ying

    2015-10-14

    Complex hierarchical structures have received tremendous attention due to their superior properties over their constitute components. In this study, hierarchical graphene-encapsulated hollow SnO2@SnS2 nanostructures are successfully prepared by in situ sulfuration on the backbones of hollow SnO2 spheres via a simple hydrothermal method followed by a solvothermal surface modification. The as-prepared hierarchical SnO2@SnS2@rGO nanocomposite can be used as anode material in lithium ion batteries, exhibiting excellent cyclability with a capacity of 583 mAh/g after 100 electrochemical cycles at a specific current of 200 mA/g. This material shows a very low capacity fading of only 0.273% per cycle from the second to the 100th cycle, lower than the capacity degradation of bare SnO2 hollow spheres (0.830%) and single SnS2 nanosheets (0.393%). Even after being cycled at a range of specific currents varied from 100 mA/g to 2000 mA/g, hierarchical SnO2@SnS2@rGO nanocomposites maintain a reversible capacity of 664 mAh/g, which is much higher than single SnS2 nanosheets (374 mAh/g) and bare SnO2 hollow spheres (177 mAh/g). Such significantly improved electrochemical performance can be attributed to the unique hierarchical hollow structure, which not only effectively alleviates the stress resulting from the lithiation/delithiation process and maintaining structural stability during cycling but also reduces aggregation and facilitates ion transport. This work thus demonstrates the great potential of hierarchical SnO2@SnS2@rGO nanocomposites for applications as a high-performance anode material in next-generation lithium ion battery technology.

  4. Anticollusion Attack Noninteractive Security Hierarchical Key Agreement Scheme in WHMS

    Directory of Open Access Journals (Sweden)

    Kefei Mao

    2016-01-01

    Full Text Available Wireless Health Monitoring Systems (WHMS have potential to change the way of health care and bring numbers of benefits to patients, physicians, hospitals, and society. However, there are crucial barriers not only to transmit the biometric information but also to protect the privacy and security of the patients’ information. The key agreement between two entities is an essential cryptography operation to clear the barriers. In particular, the noninteractive hierarchical key agreement scheme becomes an attractive direction in WHMS because each sensor node or gateway has limited resources and power. Recently, a noninteractive hierarchical key agreement scheme has been proposed by Kim for WHMS. However, we show that Kim’s cryptographic scheme is vulnerable to the collusion attack if the physicians can be corrupted. Obviously, it is a more practical security condition. Therefore, we proposed an improved key agreement scheme against the attack. Security proof, security analysis, and experimental results demonstrate that our proposed scheme gains enhanced security and more efficiency than Kim’s previous scheme while inheriting its qualities of one-round communication and security properties.

  5. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  6. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  7. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

  8. An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

    OpenAIRE

    Yunqing Rao; Dezhong Qi; Jinling Li

    2013-01-01

    For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better ...

  9. Hierarchy concepts: classification and preparation strategies for zeolite containing materials with hierarchical porosity.

    Science.gov (United States)

    Schwieger, Wilhelm; Machoke, Albert Gonche; Weissenberger, Tobias; Inayat, Amer; Selvam, Thangaraj; Klumpp, Michael; Inayat, Alexandra

    2016-06-13

    'Hierarchy' is a property which can be attributed to a manifold of different immaterial systems, such as ideas, items and organisations or material ones like biological systems within living organisms or artificial, man-made constructions. The property 'hierarchy' is mainly characterised by a certain ordering of individual elements relative to each other, often in combination with a certain degree of branching. Especially mass-flow related systems in the natural environment feature special hierarchically branched patterns. This review is a survey into the world of hierarchical systems with special focus on hierarchically porous zeolite materials. A classification of hierarchical porosity is proposed based on the flow distribution pattern within the respective pore systems. In addition, this review might serve as a toolbox providing several synthetic and post-synthetic strategies to prepare zeolitic or zeolite containing material with tailored hierarchical porosity. Very often, such strategies with their underlying principles were developed for improving the performance of the final materials in different technical applications like adsorptive or catalytic processes. In the present review, besides on the hierarchically porous all-zeolite material, special focus is laid on the preparation of zeolitic composite materials with hierarchical porosity capable to face the demands of industrial application.

  10. Algorithm of parallel: hierarchical transformation and its implementation on FPGA

    Science.gov (United States)

    Timchenko, Leonid I.; Petrovskiy, Mykola S.; Kokryatskay, Natalia I.; Barylo, Alexander S.; Dembitska, Sofia V.; Stepanikuk, Dmytro S.; Suleimenov, Batyrbek; Zyska, Tomasz; Uvaysova, Svetlana; Shedreyeva, Indira

    2017-08-01

    In this paper considers the algorithm of laser beam spots image classification in atmospheric-optical transmission systems. It discusses the need for images filtering using adaptive methods, using, for example, parallel-hierarchical networks. The article also highlights the need to create high-speed memory devices for such networks. Implementation and simulation results of the developed method based on the PLD are demonstrated, which shows that the presented method gives 15-20% better prediction results than similar methods.

  11. Optimization of photoelectrochemical water splitting performance on hierarchical TiO 2 nanotube arrays

    KAUST Repository

    Zhang, Z.

    2012-02-10

    In this paper, we show that by varying the voltages during two-step anodization the morphology of the hierarchical top-layer/bottom-tube TiO 2 (TiO 2 NTs) can be finely tuned between nanoring/nanotube, nanopore/nanotube, and nanohole-nanocave/nanotube morphologies. This allows us to optimize the photoelectrochemical (PEC) water splitting performance on the hierarchical TiO 2 NTs. The optimized photocurrent density and photoconversion efficiency in this study, occurring on the nanopore/nanotube TiO 2 NTs, were 1.59 mA cm -2 at 1.23 V vs. RHE and 0.84% respectively, which are the highest values ever reported on pristine TiO 2 materials under illumination of AM 1.5G. Our findings contribute to further improvement of the energy conversion efficiency of TiO 2-based devices.

  12. Optimization of photoelectrochemical water splitting performance on hierarchical TiO 2 nanotube arrays

    KAUST Repository

    Zhang, Z.; Wang, Peng

    2012-01-01

    In this paper, we show that by varying the voltages during two-step anodization the morphology of the hierarchical top-layer/bottom-tube TiO 2 (TiO 2 NTs) can be finely tuned between nanoring/nanotube, nanopore/nanotube, and nanohole-nanocave/nanotube morphologies. This allows us to optimize the photoelectrochemical (PEC) water splitting performance on the hierarchical TiO 2 NTs. The optimized photocurrent density and photoconversion efficiency in this study, occurring on the nanopore/nanotube TiO 2 NTs, were 1.59 mA cm -2 at 1.23 V vs. RHE and 0.84% respectively, which are the highest values ever reported on pristine TiO 2 materials under illumination of AM 1.5G. Our findings contribute to further improvement of the energy conversion efficiency of TiO 2-based devices.

  13. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  14. An ordered array of hierarchical spheres for surface-enhanced Raman scattering detection of traces of pesticide

    Science.gov (United States)

    Hu, Xiaoye; Zheng, Peng; Meng, Guowen; Huang, Qing; Zhu, Chuhong; Han, Fangming; Huang, Zhulin; Li, Zhongbo; Wang, Zhaoming; Wu, Nianqiang

    2016-09-01

    An ordered array of hierarchically-structured core-nanosphere@space-layer@shell-nanoparticles has been fabricated for surface-enhanced Raman scattering (SERS) detection. To fabricate this hierarchically-structured chip, a long-range ordered array of Au/Ag-nanospheres is first patterned in the nano-bowls on the planar surface of ordered nanoporous anodic titanium oxide template. A ultra-thin alumina middle space-layer is then conformally coated on the Au/Ag-nanospheres, and Ag-nanoparticles are finally deposited on the surface of the alumina space-layer to form an ordered array of Au/Ag-nanosphere@Al2O3-layer@Ag-nanoparticles. Finite-difference time-domain simulation shows that SERS hot spots are created between the neighboring Ag-nanoparticles. The ordered array of hierarchical nanostructures is used as the SERS-substrate for a trial detection of methyl parathion (a pesticide) in water and a limit of detection of 1 nM is reached, indicating its promising potential in rapid monitoring of organic pollutants in aquatic environment.

  15. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

  16. Molecular simulation of adsorption and transport in hierarchical porous materials.

    Science.gov (United States)

    Coasne, Benoit; Galarneau, Anne; Gerardin, Corine; Fajula, François; Villemot, François

    2013-06-25

    Adsorption and transport in hierarchical porous solids with micro- (~1 nm) and mesoporosities (>2 nm) are investigated by molecular simulation. Two models of hierarchical solids are considered: microporous materials in which mesopores are carved out (model A) and mesoporous materials in which microporous nanoparticles are inserted (model B). Adsorption isotherms for model A can be described as a linear combination of the adsorption isotherms for pure mesoporous and microporous solids. In contrast, adsorption in model B departs from adsorption in pure microporous and mesoporous solids; the inserted microporous particles act as defects, which help nucleate the liquid phase within the mesopore and shift capillary condensation toward lower pressures. As far as transport under a pressure gradient is concerned, the flux in hierarchical materials consisting of microporous solids in which mesopores are carved out obeys the Navier-Stokes equation so that Darcy's law is verified within the mesopore. Moreover, the flow in such materials is larger than in a single mesopore, due to the transfer between micropores and mesopores. This nonzero velocity at the mesopore surface implies that transport in such hierarchical materials involves slippage at the mesopore surface, although the adsorbate has a strong affinity for the surface. In contrast to model A, flux in model B is smaller than in a single mesopore, as the nanoparticles act as constrictions that hinder transport. By a subtle effect arising from fast transport in the mesopores, the presence of mesopores increases the number of molecules in the microporosity in hierarchical materials and, hence, decreases the flow in the micropores (due to mass conservation). As a result, we do not observe faster diffusion in the micropores of hierarchical materials upon flow but slower diffusion, which increases the contact time between the adsorbate and the surface of the microporosity.

  17. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau; Fu, Hui-Chun

    2017-01-01

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures

  18. Preparation and Lithium-Storage Performance of a Novel Hierarchical Porous Carbon from Sucrose Using Mg-Al Layered Double Hydroxides as Template

    International Nuclear Information System (INIS)

    Shi, Liluo; Chen, Yaxin; Song, Huaihe; Li, Ang; Chen, Xiaohong; Zhou, Jisheng; Ma, Zhaokun

    2017-01-01

    Highlights: • A new hierarchical porous carbon containing slit-shaped mesopores and 3D carbon nanosheets were prepared using Mg-Al layered double hydroxides as template. • The hierarchical porous carbon electrode showed a high capacity and excellent cycle stability when used in lithium-ion battery. • The excellent performance is ascribed to its hierarchical porous structure, especially the mesoporous struture. - Abstract: Novel hierarchical porous carbons (NHPCs) containing 3D carbon nanosheets and slit-mesopores are prepared in this work, using MgAl-layered double hydroxides as template and sucrose as carbon source, and their electrochemical performances as anodes of lithium-ion batteries are also investigated. Owing to the existence of abundant carbon nanosheets and slit-mesopores, the NHPCs electrode exhibits the specific reversible capacity of 1151.9 mA h/g at the current density of 50 mA/g, which is significantly higher than other hierarchical porous carbons reported in previous literatures. The contributions of carbon nanosheets and mesopores to the electrochemical performance are further clarified by nitrogen adsorption-desorption test, electrochemical impedance spectroscopy, cyclic voltammograms and galvanostatic charge/discharge test. This work not only provides an easy and effective method to prepare hierarchical porous carbon materials, but also is beneficial for the design of high-performance anode materials for lithium ion batteries.

  19. Inheritance rules for Hierarchical Metadata Based on ISO 19115

    Science.gov (United States)

    Zabala, A.; Masó, J.; Pons, X.

    2012-04-01

    registry is complete for each metadata hierarchical level, but at the implementation level most of the metadata elements are not stored at both levels but only at more generic one. This communication defines a metadata system that covers 4 levels, describes which metadata has to support series-layer inheritance and in which way, and how hierarchical levels are defined and stored. Metadata elements are classified according to the type of inheritance between products, series, tiles and the datasets. It explains the metadata elements classification and exemplifies it using core metadata elements. The communication also presents a metadata viewer and edition tool that uses the described model to propagate metadata elements and to show to the user a complete set of metadata for each level in a transparent way. This tool is integrated in the MiraMon GIS software.

  20. Selective hierarchical patterning of silicon nanostructures via soft nanostencil lithography.

    Science.gov (United States)

    Du, Ke; Ding, Junjun; Wathuthanthri, Ishan; Choi, Chang-Hwan

    2017-11-17

    It is challenging to hierarchically pattern high-aspect-ratio nanostructures on microstructures using conventional lithographic techniques, where photoresist (PR) film is not able to uniformly cover on the microstructures as the aspect ratio increases. Such non-uniformity causes poor definition of nanopatterns over the microstructures. Nanostencil lithography can provide an alternative means to hierarchically construct nanostructures on microstructures via direct deposition or plasma etching through a free-standing nanoporous membrane. In this work, we demonstrate the multiscale hierarchical fabrication of high-aspect-ratio nanostructures on microstructures of silicon using a free-standing nanostencil, which is a nanoporous membrane consisting of metal (Cr), PR, and anti-reflective coating. The nanostencil membrane is used as a deposition mask to define Cr nanodot patterns on the predefined silicon microstructures. Then, deep reactive ion etching is used to hierarchically create nanostructures on the microstructures using the Cr nanodots as an etch mask. With simple modification of the main fabrication processes, high-aspect-ratio nanopillars are selectively defined only on top of the microstructures, on bottom, or on both top and bottom.

  1. Hierarchically porous LaFeO3 perovskite prepared from the pomelo peel bio-template for catalytic oxidation of NO

    Science.gov (United States)

    Zhao, Shaojun; Wang, Li; Wang, Ying; Li, Xing

    2018-05-01

    In this paper, pomelo peel was used as biological template to obtain hierarchically porous LaFeO3 perovskite for the catalytic oxidation of NO to NO2. In addition, X-ray diffraction (XRD), scanning electron microscopy (SEM), N2 adsorption-desorption analyses, X-ray photoelectron spectra (XPS), NO temperature-programmed desorption (NO-TPD), oxygen temperature-programmed desorption (O2-TPD) and hydrogen temperature-programmed reduction (H2-TPR) were used to investigate the micro-structure and the redox properties of the hierarchically porous LaFeO3 perovskite prepared from pomelo peel biological template and the LaFeO3 perovskite without the biological template. The results indicated that the hierarchically porous LaFeO3 perovskite successfully replicated the porous structure of pomelo peel with high specific surface area. Compared to the LaFeO3 perovskite prepared without the pomelo peel template, the hierarchically porous LaFeO3 perovskite showed better catalytic oxidization of NO to NO2 under the same conditions. The maximum NO conversions for LaFeO3 prepared with and without template were 90% at 305 °C and 76% at 313 °C, respectively. This is mainly attributed to the higher ratio of Fe4+/Fe3+, the hierarchically porous structure with more adsorbed oxygen species and higher surface area for the hierarchically porous LaFeO3 perovskite compared with the sample prepared without the pomelo peel template.

  2. Lattice-Symmetry-Driven Epitaxy of Hierarchical GaN Nanotripods

    KAUST Repository

    Wang, Ping

    2017-01-18

    Lattice-symmetry-driven epitaxy of hierarchical GaN nanotripods is demonstrated. The nanotripods emerge on the top of hexagonal GaN nanowires, which are selectively grown on pillar-patterned GaN templates using molecular beam epitaxy. High-resolution transmission electron microscopy confirms that two kinds of lattice-symmetry, wurtzite (wz) and zinc-blende (zb), coexist in the GaN nanotripods. Periodical transformation between wz and zb drives the epitaxy of the hierarchical nanotripods with N-polarity. The zb-GaN is formed by the poor diffusion of adatoms, and it can be suppressed by improving the ability of the Ga adatoms to migrate as the growth temperature increased. This controllable epitaxy of hierarchical GaN nanotripods allows quantum dots to be located at the phase junctions of the nanotripods and nanowires, suggesting a new recipe for multichannel quantum devices.

  3. A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

    Science.gov (United States)

    Meaney, Christopher; Moineddin, Rahim

    2014-01-24

    In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

  4. Biomimetic fabrication of a three-level hierarchical calcium phosphate/collagen/hydroxyapatite scaffold for bone tissue engineering

    International Nuclear Information System (INIS)

    Zhou, Changchun; Ye, Xingjiang; Fan, Yujiang; Tan, Yanfei; Qing, Fangzu; Zhang, Xingdong; Ma, Liang

    2014-01-01

    A three-level hierarchical calcium phosphate/collagen/hydroxyapatite (CaP/Col/HAp) scaffold for bone tissue engineering was developed using biomimetic synthesis. Porous CaP ceramics were first prepared as substrate materials to mimic the porous bone structure. A second-level Col network was then composited into porous CaP ceramics by vacuum infusion. Finally, a third-level HAp layer was achieved by biomimetic mineralization. The three-level hierarchical biomimetic scaffold was characterized using scanning electron microscopy, energy-dispersive x-ray spectra, x-ray diffraction and Fourier transform infrared spectroscopy, and the mechanical properties of the scaffold were evaluated using dynamic mechanical analysis. The results show that this scaffold exhibits a similar structure and composition to natural bone tissues. Furthermore, this three-level hierarchical biomimetic scaffold showed enhanced mechanical strength compared with pure porous CaP scaffolds. The biocompatibility and osteoinductivity of the biomimetic scaffolds were evaluated using in vitro and in vivo tests. Cell culture results indicated the good biocompatibility of this biomimetic scaffold. Faster and increased bone formation was observed in these scaffolds following a six-month implantation in the dorsal muscles of rabbits, indicating that this biomimetic scaffold exhibits better osteoinductivity than common CaP scaffolds. (papers)

  5. Hierarchical Targeting Strategy for Enhanced Tumor Tissue Accumulation/Retention and Cellular Internalization.

    Science.gov (United States)

    Wang, Sheng; Huang, Peng; Chen, Xiaoyuan

    2016-09-01

    Targeted delivery of therapeutic agents is an important way to improve the therapeutic index and reduce side effects. To design nanoparticles for targeted delivery, both enhanced tumor tissue accumulation/retention and enhanced cellular internalization should be considered simultaneously. So far, there have been very few nanoparticles with immutable structures that can achieve this goal efficiently. Hierarchical targeting, a novel targeting strategy based on stimuli responsiveness, shows good potential to enhance both tumor tissue accumulation/retention and cellular internalization. Here, the recent design and development of hierarchical targeting nanoplatforms, based on changeable particle sizes, switchable surface charges and activatable surface ligands, will be introduced. In general, the targeting moieties in these nanoplatforms are not activated during blood circulation for efficient tumor tissue accumulation, but re-activated by certain internal or external stimuli in the tumor microenvironment for enhanced cellular internalization. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Hierarchical Fiber Structures Made by Electrospinning Polymers

    Science.gov (United States)

    Reneker, Darrell H.

    2009-03-01

    A filter for water purification that is very thin, with small interstices and high surface area per unit mass, can be made with nanofibers. The mechanical strength of a very thin sheet of nanofibers is not great enough to withstand the pressure drop of the fluid flowing through. If the sheet of nanofibers is made thicker, the strength will increase, but the flow will be reduced to an impractical level. An optimized filter can be made with nanometer scale structures supported on micron scale structures, which are in turn supported on millimeter scale structures. This leads to a durable hierarchical structure to optimize the filtration efficiency with a minimum amount of material. Buckling coils,ootnotetextTao Han, Darrell H Reneker, Alexander L. Yarin, Polymer, Volume 48, issue 20 (September 21, 2007), p. 6064-6076. electrical bending coilsootnotetextDarrell H. Reneker and Alexander L. Yarin, Polymer, Volume 49, Issue 10 (2008) Pages 2387-2425, DOI:10.1016/j.polymer.2008.02.002. Feature Article. and pendulum coilsootnotetextT. Han, D.H. Reneker, A.L. Yarin, Polymer, Volume 49, (2008) Pages 2160-2169, doi:10.1016/jpolymer.2008.01.0487878. spanning dimensions from a few microns to a few centimeters can be collected from a single jet by controlling the position and motion of a collector. Attractive routes to the design and construction of hierarchical structures for filtration are based on nanofibers supported on small coils that are in turn supported on larger coils, which are supported on even larger overlapping coils. ``Such top-down'' hierarchical structures are easy to make by electrospinning. In one example, a thin hierarchical structure was made, with a high surface area and small interstices, having an open area of over 50%, with the thinnest fibers supported at least every 15 microns.

  7. Hierarchical control of vehicular fuel cell / battery hybrid powertrain

    OpenAIRE

    Xu, Liangfei; Ouyang, Minggao; Li, Jianqiu; Hua, Jianfeng

    2010-01-01

    In a proton exchange membrane (PEM) fuel cell/battery hybrid vehicle, a fuel cell system fulfills the stationary power demand, and a traction battery provides the accelerating power and recycles braking energy. The entire system is coordinated by a distributed control system, incorporating three key strategies: 1) vehicle control, 2) fuel cell control and 3) battery management. They make up a hierarchical control system. This paper introduces a hierarchical control strategy for a fuel cell / ...

  8. Electroactive nanoparticle directed assembly of functionalized graphene nanosheets into hierarchical structures with hybrid compositions for flexible supercapacitors

    Science.gov (United States)

    Choi, Bong Gill; Huh, Yun Suk; Hong, Won Hi; Erickson, David; Park, Ho Seok

    2013-04-01

    Hierarchical structures of hybrid materials with the controlled compositions have been shown to offer a breakthrough for energy storage and conversion. Here, we report the integrative assembly of chemically modified graphene (CMG) building blocks into hierarchical complex structures with the hybrid composition for high performance flexible pseudocapacitors. The formation mechanism of hierarchical CMG/Nafion/RuO2 (CMGNR) microspheres, which is triggered by the cooperative interplay during the in situ synthesis of RuO2 nanoparticles (NPs), was extensively investigated. In particular, the hierarchical CMGNR microspheres consisting of the aggregates of CMG/Nafion (CMGN) nanosheets and RuO2 NPs provided large surface area and facile ion accessibility to storage sites, while the interconnected nanosheets offered continuous electron pathways and mechanical integrity. The synergistic effect of CMGNR hybrids on the supercapacitor (SC) performance was derived from the hybrid composition of pseudocapacitive RuO2 NPs with the conductive CMGNs as well as from structural features. Consequently, the CMGNR-SCs showed a specific capacitance as high as 160 F g-1, three-fold higher than that of conventional graphene SCs, and a capacitance retention of >95% of the maximum value even after severe bending and 1000 charge-discharge tests due to the structural and compositional features.Hierarchical structures of hybrid materials with the controlled compositions have been shown to offer a breakthrough for energy storage and conversion. Here, we report the integrative assembly of chemically modified graphene (CMG) building blocks into hierarchical complex structures with the hybrid composition for high performance flexible pseudocapacitors. The formation mechanism of hierarchical CMG/Nafion/RuO2 (CMGNR) microspheres, which is triggered by the cooperative interplay during the in situ synthesis of RuO2 nanoparticles (NPs), was extensively investigated. In particular, the hierarchical CMGNR

  9. Application of hierarchical matrices for partial inverse

    KAUST Repository

    Litvinenko, Alexander

    2013-11-26

    In this work we combine hierarchical matrix techniques (Hackbusch, 1999) and domain decomposition methods to obtain fast and efficient algorithms for the solution of multiscale problems. This combination results in the hierarchical domain decomposition (HDD) method, which can be applied for solution multi-scale problems. Multiscale problems are problems that require the use of different length scales. Using only the finest scale is very expensive, if not impossible, in computational time and memory. Domain decomposition methods decompose the complete problem into smaller systems of equations corresponding to boundary value problems in subdomains. Then fast solvers can be applied to each subdomain. Subproblems in subdomains are independent, much smaller and require less computational resources as the initial problem.

  10. Hierarchical control system of advanced robot manipulator

    International Nuclear Information System (INIS)

    Oomichi, Takeo; Okino, Akihisa; Nishihara, Masatoshi; Sakamoto, Taizou; Matsuda, Koichi; Ohnishi, Ken

    1990-01-01

    We introduce a double arm with 4-finger's manipulator system which process the large volume of information at high speed. This is under research/development many type of works in the harsh condition. Namely, hierarchization of instruction unit in which motion control system as real time processing unit, and task planning unit as non-real time processing unit, interface with operation through the task planning unit has been made. Also, high speed processing of large volume information has been realized by decentralizing the motion control unit by function, hierarchizing the high speed processing unit, and developing high speed transmission, IC which does not depend on computer OS to avoid the delay in transmission. (author)

  11. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  12. Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

    Science.gov (United States)

    Liu, Quan; Liu, Aiming; Meng, Wei; Ai, Qingsong; Xie, Sheng Q

    2017-01-01

    Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient's active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant's assessment. The robot reduces its assistance output when participants contribute more and vice versa , thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

  13. Masking effects of speech and music: does the masker's hierarchical structure matter?

    Science.gov (United States)

    Shi, Lu-Feng; Law, Yvonne

    2010-04-01

    Speech and music are time-varying signals organized by parallel hierarchical rules. Through a series of four experiments, this study compared the masking effects of single-talker speech and instrumental music on speech perception while manipulating the complexity of hierarchical and temporal structures of the maskers. Listeners' word recognition was found to be similar between hierarchically intact and disrupted speech or classical music maskers (Experiment 1). When sentences served as the signal, significantly greater masking effects were observed with disrupted than intact speech or classical music maskers (Experiment 2), although not with jazz or serial music maskers, which differed from the classical music masker in their hierarchical structures (Experiment 3). Removing the classical music masker's temporal dynamics or partially restoring it affected listeners' sentence recognition; yet, differences in performance between intact and disrupted maskers remained robust (Experiment 4). Hence, the effect of structural expectancy was largely present across maskers when comparing them before and after their hierarchical structure was purposefully disrupted. This effect seemed to lend support to the auditory stream segregation theory.

  14. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    2004-01-01

    dependencies between the number of nodes and the distances in the structures. The perfect square mesh is introduced for hierarchies, and it is shown that applying ordered hierarchies in this way results in logarithmic dependencies between the number of nodes and the distances, resulting in better scaling...... structures. For example, in a mesh of 391876 nodes the average distance is reduced from 417.33 to 17.32 by adding hierarchical lines. This is gained by increasing the number of lines by 4.20% compared to the non-hierarchical structure. A similar hierarchical extension of the torus structure also results...

  15. Wetting and Dewetting Transitions on Submerged Superhydrophobic Surfaces with Hierarchical Structures.

    Science.gov (United States)

    Wu, Huaping; Yang, Zhe; Cao, Binbin; Zhang, Zheng; Zhu, Kai; Wu, Bingbing; Jiang, Shaofei; Chai, Guozhong

    2017-01-10

    The wetting transition on submersed superhydrophobic surfaces with hierarchical structures and the influence of trapped air on superhydrophobic stability are predicted based on the thermodynamics and mechanical analyses. The dewetting transition on the hierarchically structured surfaces is investigated, and two necessary thermodynamic conditions and a mechanical balance condition for dewetting transition are proposed. The corresponding thermodynamic phase diagram of reversible transition and the critical reversed pressure well explain the experimental results reported previously. Our theory provides a useful guideline for precise controlling of breaking down and recovering of superhydrophobicity by designing superhydrophobic surfaces with hierarchical structures under water.

  16. Two Paradoxes in Linear Regression Analysis

    Science.gov (United States)

    FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

    2016-01-01

    Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

  17. Variable and subset selection in PLS regression

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2001-01-01

    The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...

  18. The influence of visual and phonological features on the hemispheric processing of hierarchical Navon letters.

    Science.gov (United States)

    Aiello, Marilena; Merola, Sheila; Lasaponara, Stefano; Pinto, Mario; Tomaiuolo, Francesco; Doricchi, Fabrizio

    2018-01-31

    The possibility of allocating attentional resources to the "global" shape or to the "local" details of pictorial stimuli helps visual processing. Investigations with hierarchical Navon letters, that are large "global" letters made up of small "local" ones, consistently demonstrate a right hemisphere advantage for global processing and a left hemisphere advantage for local processing. Here we investigated how the visual and phonological features of the global and local components of Navon letters influence these hemispheric advantages. In a first study in healthy participants, we contrasted the hemispheric processing of hierarchical letters with global and local items competing for response selection, to the processing of hierarchical letters in which a letter, a false-letter conveying no phonological information or a geometrical shape presented at the unattended level did not compete for response selection. In a second study, we investigated the hemispheric processing of hierarchical stimuli in which global and local letters were both visually and phonologically congruent (e.g. large uppercase G made of smaller uppercase G), visually incongruent and phonologically congruent (e.g. large uppercase G made of small lowercase g) or visually incongruent and phonologically incongruent (e.g. large uppercase G made of small lowercase or uppercase M). In a third study, we administered the same tasks to a right brain damaged patient with a lesion involving pre-striate areas engaged by global processing. The results of the first two experiments showed that the global abilities of the left hemisphere are limited because of its strong susceptibility to interference from local letters even when these are irrelevant to the task. Phonological features played a crucial role in this interference because the interference was entirely maintained also when letters at the global and local level were presented in different uppercase vs. lowercase formats. In contrast, when local features

  19. Hierarchical DSE for multi-ASIP platforms

    DEFF Research Database (Denmark)

    Micconi, Laura; Corvino, Rosilde; Gangadharan, Deepak

    2013-01-01

    This work proposes a hierarchical Design Space Exploration (DSE) for the design of multi-processor platforms targeted to specific applications with strict timing and area constraints. In particular, it considers platforms integrating multiple Application Specific Instruction Set Processors (ASIPs...

  20. Hierarchical quark mass matrices

    International Nuclear Information System (INIS)

    Rasin, A.

    1998-02-01

    I define a set of conditions that the most general hierarchical Yukawa mass matrices have to satisfy so that the leading rotations in the diagonalization matrix are a pair of (2,3) and (1,2) rotations. In addition to Fritzsch structures, examples of such hierarchical structures include also matrices with (1,3) elements of the same order or even much larger than the (1,2) elements. Such matrices can be obtained in the framework of a flavor theory. To leading order, the values of the angle in the (2,3) plane (s 23 ) and the angle in the (1,2) plane (s 12 ) do not depend on the order in which they are taken when diagonalizing. We find that any of the Cabbibo-Kobayashi-Maskawa matrix parametrizations that consist of at least one (1,2) and one (2,3) rotation may be suitable. In the particular case when the s 13 diagonalization angles are sufficiently small compared to the product s 12 s 23 , two special CKM parametrizations emerge: the R 12 R 23 R 12 parametrization follows with s 23 taken before the s 12 rotation, and vice versa for the R 23 R 12 R 23 parametrization. (author)

  1. Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach

    Science.gov (United States)

    Mohebbi, Mohammadreza; Wolfe, Rory; Forbes, Andrew

    2014-01-01

    This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference. PMID:24413702

  2. Catalytic Fast Pyrolysis of Kraft Lignin over Hierarchical HZSM-5 and Hβ Zeolites

    Directory of Open Access Journals (Sweden)

    Yadong Bi

    2018-02-01

    Full Text Available The hierarchical HZSM-5 and Hβ zeolites were prepared by alkaline post-treatment methods adopting Na2CO3, TMAOH/NaOH mixture, and NaOH as desilication sources, respectively. More mesopores are produced over two kinds of zeolites, while the micropores portion is well preserved. The mesopores formed in hierarchical Hβ zeolites were directly related to the basicity of the alkaline solution, indicating that Hβ zeolite is more sensitive to the alkaline post-treatment. The hierarchical HZSM-5 and Hβ zeolites are more active than the parent one for catalytic fast pyrolysis (CFP of Kraft lignin. Hierarchical zeolites retained the function of acid catalysis, while additionally creating larger mesopores to ensure the entry of bulkier reactant molecules. The increase of the condensable volatiles yield can be attributed to the improvement of the mass transfer performance, which correlates well with the change of mesoporous surface area. In particular, the condensable volatiles yield for the optimized hierarchical Hβ reached approximately two times that of the parent Hβ zeolites. In contrast to the parent HZSM-5, the optimized hierarchical HZSM-5 zeolite significantly reduced the selectivity of oxygenates from 27.2% to 3.3%.

  3. Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

    Directory of Open Access Journals (Sweden)

    Qiutong Jin

    2016-06-01

    Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

  4. Microscale and nanoscale hierarchical structured mesh films with superhydrophobic and superoleophilic properties induced by long-chain fatty acids

    International Nuclear Information System (INIS)

    Wang Shutao; Song Yanlin; Jiang Lei

    2007-01-01

    Inspired by the lotus effect, we fabricate new microscale and nanoscale hierarchical structured copper mesh films by a simple electrochemical deposition. After modification of the long-chain fatty acid monolayer, these films show superhydrophobic and superoleophilic properties, which could be used for the effective separation of oil and water. The length of the fatty acid chain strongly influences the surface wettability of as-prepared films. It is confirmed that the cooperative effect of the hierarchical structure of the copper film and the nature of the long-chain fatty acid contribute to this unique surface wettability

  5. Hierarchical machining materials and their performance

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Levashov, Evgeny

    2016-01-01

    as nanoparticles in the binder, or polycrystalline, aggregate-like reinforcements, also at several scale levels). Such materials can ensure better productivity, efficiency, and lower costs of drilling, cutting, grinding, and other technological processes. This article reviews the main groups of hierarchical...

  6. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau

    2017-08-03

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures extending from the HNWs.

  7. Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

    Czech Academy of Sciences Publication Activity Database

    Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

    2009-01-01

    Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

  8. Loops in hierarchical channel networks

    Science.gov (United States)

    Katifori, Eleni; Magnasco, Marcelo

    2012-02-01

    Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

  9. Hierarchical modeling of molecular energies using a deep neural network

    Science.gov (United States)

    Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

    2018-06-01

    We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

  10. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

    Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

    2015-01-01

    The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

  11. Hierarchical structure of stock price fluctuations in financial markets

    International Nuclear Information System (INIS)

    Gao, Ya-Chun; Cai, Shi-Min; Wang, Bing-Hong

    2012-01-01

    The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they share. In this paper, the She–Leveque (SL) hierarchy, proposed to explain the anomalous scaling exponents deviating from Kolmogorov monofractal scaling of the velocity fluctuation in fluid turbulence, is applied to study and quantify the hierarchical structure of stock price fluctuations in financial markets. We therefore observed certain interesting results: (i) the hierarchical structure related to multifractal scaling generally presents in all the stock price fluctuations we investigated. (ii) The quantitatively statistical parameters that describe SL hierarchy are different between developed financial markets and emerging ones, distinctively. (iii) For the high-frequency stock price fluctuation, the hierarchical structure varies with different time periods. All these results provide a novel analogy in turbulence and financial market dynamics and an insight to deeply understand multifractality in financial markets. (paper)

  12. Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

    International Nuclear Information System (INIS)

    Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

    2003-01-01

    Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

  13. Development of hierarchically porous cobalt oxide for enhanced photo-oxidation of indoor pollutants

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, J. P., E-mail: chengjp@zju.edu.cn [Zhejiang University, State Key Laboratory of Silicon Materials, Department of Materials Science and Engineering (China); Shereef, Anas; Gray, Kimberly A., E-mail: k-gray@northwestern.edu [Northwestern University, Center for Catalysis and Surface Science (United States); Wu, Jinsong [Northwestern University, Department of Materials Science and Engineering (United States)

    2015-03-15

    Porous cobalt oxide was successfully prepared by precipitation of cobalt hydroxide followed by low temperature thermal decomposition. The morphologies of the resultant oxides remained as the corresponding hydroxides, although the morphology of cobalt hydroxides was greatly influenced by the precursor salts. The cobalt oxides with average crystal size less than 20 nm were characterized by X-ray diffraction, scanning electron microscope, BET surface area, and XPS analysis. The photocatalytic activities of the various cobalt oxides morphologies were investigated by comparing the photo-degradation of acetaldehyde under simulated solar illumination. Relative to their low order structures and reference titania samples, the hierarchical nanostructures of cobalt oxide showed excellent abilities to rapidly degrade acetaldehyde, a model air pollutant. This was attributed to the unique nature of these hierarchical cobalt oxide nanoassemblies, which contained many catalytically active reaction sites and open pores.

  14. Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

    Science.gov (United States)

    Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

    2013-03-27

    Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

  15. Assembly of CdS Quantum Dots onto Hierarchical TiO2 Structure for Quantum Dots Sensitized Solar Cell Applications

    Directory of Open Access Journals (Sweden)

    Syed Mansoor Ali

    2015-05-01

    Full Text Available Quantum dot (QD sensitized solar cells based on Hierarchical TiO2 structure (HTS consisting of spherical nano-urchins on transparent conductive fluorine doped tin oxide glass substrate is fabricated. The hierarchical TiO2 structure consisting of spherical nano-urchins on transparent conductive fluorine doped tin oxide glass substrate synthesized by hydrothermal route. The CdS quantum dots were grown by the successive ionic layer adsorption and reaction deposition method. The quantum dot sensitized solar cell based on the hierarchical TiO2 structure shows a current density JSC = 1.44 mA, VOC = 0.46 V, FF = 0.42 and η = 0.27%. The QD provide a high surface area and nano-urchins offer a highway for fast charge collection and multiple scattering centers within the photoelectrode.

  16. An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

    Directory of Open Access Journals (Sweden)

    Yunqing Rao

    2013-01-01

    Full Text Available For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

  17. An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

    Science.gov (United States)

    Rao, Yunqing; Qi, Dezhong; Li, Jinling

    2013-01-01

    For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony--hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

  18. Urban pattern: Layout design by hierarchical domain splitting

    KAUST Repository

    Yang, Yongliang; Wang, Jun; Vouga, Etienne; Wonka, Peter

    2013-01-01

    We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

  19. Urban pattern: Layout design by hierarchical domain splitting

    KAUST Repository

    Yang, Yongliang

    2013-11-06

    We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

  20. Interpreting Bivariate Regression Coefficients: Going beyond the Average

    Science.gov (United States)

    Halcoussis, Dennis; Phillips, G. Michael

    2010-01-01

    Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

  1. Hierarchical eco-restoration: A systematical approach to removal of COD and dissolved nutrients from an intensive agricultural area

    Energy Technology Data Exchange (ETDEWEB)

    Wu Yonghong, E-mail: yhwu@issas.ac.c [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 Beijing East Road, Nanjing 210008 (China); Graduate Schools, Chinese Academy of Sciences, Beijing 100049 (China); Hu Zhengyi [Graduate Schools, Chinese Academy of Sciences, Beijing 100049 (China); Yang Linzhang, E-mail: lzyang@issas.ac.c [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 Beijing East Road, Nanjing 210008 (China)

    2010-10-15

    A systematical approach based on hierarchical eco-restoration system for the simultaneous removal of COD and dissolved nutrients was proposed and applied in a complex residential-cropland area in Kunming, China from August 2006 to August 2008, where the self-purifying capacity of the agricultural ecosystem had been lost. The system includes four main parts: (1) fertilizer management and agricultural structure optimization, (2) nutrients reuse, (3) wastewater treatment, and (4) catchment restoration. The results showed that the average removal efficiencies were 90% for COD, 93% for ammonia, 94% for nitrate and 71% for total dissolved phosphorus (TDP) when the hierarchical eco-restoration agricultural system was in a relatively steady-state condition. The emergence of 14 species of macrophytes and 4 species of zoobenthos indicated that the growth conditions for the plankton were improved. The results demonstrated that this promising and environmentally benign hierarchical eco-restoration system could decrease the output of nutrients and reduce downstream eutrophication risk. - A systematical approach based on hierarchical eco-restoration system has proven highly effective for simultaneously removing COD and dissolved nutrients, decreasing the output of nutrients, and reducing the eutrophic risk of downstream surface waters.

  2. Hierarchical eco-restoration: A systematical approach to removal of COD and dissolved nutrients from an intensive agricultural area

    International Nuclear Information System (INIS)

    Wu Yonghong; Hu Zhengyi; Yang Linzhang

    2010-01-01

    A systematical approach based on hierarchical eco-restoration system for the simultaneous removal of COD and dissolved nutrients was proposed and applied in a complex residential-cropland area in Kunming, China from August 2006 to August 2008, where the self-purifying capacity of the agricultural ecosystem had been lost. The system includes four main parts: (1) fertilizer management and agricultural structure optimization, (2) nutrients reuse, (3) wastewater treatment, and (4) catchment restoration. The results showed that the average removal efficiencies were 90% for COD, 93% for ammonia, 94% for nitrate and 71% for total dissolved phosphorus (TDP) when the hierarchical eco-restoration agricultural system was in a relatively steady-state condition. The emergence of 14 species of macrophytes and 4 species of zoobenthos indicated that the growth conditions for the plankton were improved. The results demonstrated that this promising and environmentally benign hierarchical eco-restoration system could decrease the output of nutrients and reduce downstream eutrophication risk. - A systematical approach based on hierarchical eco-restoration system has proven highly effective for simultaneously removing COD and dissolved nutrients, decreasing the output of nutrients, and reducing the eutrophic risk of downstream surface waters.

  3. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  4. Comparing hierarchical models via the marginalized deviance information criterion.

    Science.gov (United States)

    Quintero, Adrian; Lesaffre, Emmanuel

    2018-07-20

    Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent variables, there are several versions of this statistic: the conditional DIC (cDIC) that incorporates the latent variables in the focus of the analysis and the marginalized DIC (mDIC) that integrates them out. Regardless of the asymptotic and coherency difficulties of cDIC, this alternative is usually used in Markov chain Monte Carlo (MCMC) methods for hierarchical models because of practical convenience. The mDIC criterion is more appropriate in most cases but requires integration of the likelihood, which is computationally demanding and not implemented in Bayesian software. Therefore, we consider a method to compute mDIC by generating replicate samples of the latent variables that need to be integrated out. This alternative can be easily conducted from the MCMC output of Bayesian packages and is widely applicable to hierarchical models in general. Additionally, we propose some approximations in order to reduce the computational complexity for large-sample situations. The method is illustrated with simulated data sets and 2 medical studies, evidencing that cDIC may be misleading whilst mDIC appears pertinent. Copyright © 2018 John Wiley & Sons, Ltd.

  5. Moisture condensation behavior of hierarchically carbon nanotube-grafted carbon nanofibers.

    Science.gov (United States)

    Park, Kyu-Min; Lee, Byoung-Sun; Youk, Ji Ho; Lee, Jinyong; Yu, Woong-Reol

    2013-11-13

    Hierarchical micro/nanosurfaces with nanoscale roughness on microscale uneven substrates have been the subject of much recent research interest because of phenomena such as superhydrophobicity. However, an understanding of the effect of the difference in the scale of the hierarchical entities, i.e., nanoscale roughness on microscale uneven substrates as opposed to nanoscale roughness on (a larger) nanoscale uneven surface, is still lacking. In this study, we investigated the effect of the difference in scale between the nano- and microscale features. We fabricated carbon nanotube-grafted carbon nanofibers (CNFs) by dispersing a catalyst precursor in poly (acrylonitrile) (PAN) solution, electrospinning the PAN/catalyst precursor solution, carbonization of electrospun PAN nanofibers, and direct growth of carbon nanotubes (CNTs) on the CNFs. We investigated the relationships between the catalyst concentrations, the size of catalyst nanoparticles on CNFs, and the sizes of CNFs and CNTs. Interestingly, the hydrophobic behavior of micro/nano and nano/nano hierarchical surfaces with water droplets was similar; however a significant difference in the water condensation behavior was observed. Water condensed into smaller droplets on the nano/nano hierarchical surface, causing it to dry much faster.

  6. Nanotrumpets and circularly polarized luminescent nanotwists hierarchically self-assembled from an achiral C3-symmetric ester.

    Science.gov (United States)

    Sang, Yutao; Duan, Pengfei; Liu, Minghua

    2018-04-17

    An achiral C3-symmetric molecule was found to self-assemble into various hierarchical nanostructures such as nanotwists, nanotrumpets and nanobelts, in which the twisted fibers showed supramolecular chirality as well as circularly polarized luminescence although the compound is achiral.

  7. Hierarchically structured self-supported latex films for flexible and semi-transparent electronics

    International Nuclear Information System (INIS)

    Määttänen, Anni; Ihalainen, Petri; Törngren, Björn; Rosqvist, Emil; Pesonen, Markus; Peltonen, Jouko

    2016-01-01

    Graphical abstract: - Highlights: • Transparent self-supported latex films were fabricated by a peel-off process. • Various template substrates were used for creating e.g. hierarchically structured latex films. • Ultra-thin and semi-transparent conductive gold electrodes were evaporated on the latex films.Electrochemical experiments were carried out to verify the applicability of the electrodes. - Abstract: Different length scale alterations in topography, surface texture, and symmetry are known to evoke diverse cell behavior, including adhesion, orientation, motility, cytoskeletal condensation, and modulation of intracellular signaling pathways. In this work, self-supported latex films with well-defined isotropic/anisotropic surface features and hierarchical morphologies were fabricated by a peel-off process from different template surfaces. In addition, the latex films were used as substrates for evaporated ultrathin gold films with nominal thicknesses of 10 and 20 nm. Optical properties and topography of the samples were characterized using UV–vis spectroscopy and Atomic Force Microscopy (AFM) measurements, respectively. The latex films showed high-level transmittance of visible light, enabling the fabrication of semi-transparent gold electrodes. Electrochemical impedance spectroscopy (EIS) measurements were carried out for a number of days to investigate the long-term stability of the electrodes. The effect of 1-octadecanethiol (ODT) and HS(CH_2)_1_1OH (MuOH) thiolation and protein (human serum albumin, HSA) adsorption on the impedance and capacitance was studied. In addition, cyclic voltammetry (CV) measurements were carried out to determine active medicinal components, i.e., caffeic acid with interesting biological activities and poorly water-soluble anti-inflammatory drug, piroxicam. The results show that the fabrication procedure presented in this study enables the formation of platforms with hierarchical morphologies for multimodal (optical and

  8. Hierarchically structured self-supported latex films for flexible and semi-transparent electronics

    Energy Technology Data Exchange (ETDEWEB)

    Määttänen, Anni, E-mail: anni.maattanen@abo.fi [Laboratory of Physical Chemistry, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland); Ihalainen, Petri, E-mail: petri.ihalainen@abo.fi [Laboratory of Physical Chemistry, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland); Törngren, Björn, E-mail: bjorn.torngren@abo.fi [Laboratory of Physical Chemistry, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland); Rosqvist, Emil, E-mail: emil.rosqvist@abo.fi [Laboratory of Physical Chemistry, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland); Pesonen, Markus, E-mail: markus.pesonen@abo.fi [Physics, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland); Peltonen, Jouko, E-mail: jouko.peltonen@abo.fi [Laboratory of Physical Chemistry, Faculty of Science and Engineering, Center for Functional Materials, Åbo Akademi University, Porthaninkatu 3, 20500, Turku (Finland)

    2016-02-28

    Graphical abstract: - Highlights: • Transparent self-supported latex films were fabricated by a peel-off process. • Various template substrates were used for creating e.g. hierarchically structured latex films. • Ultra-thin and semi-transparent conductive gold electrodes were evaporated on the latex films.Electrochemical experiments were carried out to verify the applicability of the electrodes. - Abstract: Different length scale alterations in topography, surface texture, and symmetry are known to evoke diverse cell behavior, including adhesion, orientation, motility, cytoskeletal condensation, and modulation of intracellular signaling pathways. In this work, self-supported latex films with well-defined isotropic/anisotropic surface features and hierarchical morphologies were fabricated by a peel-off process from different template surfaces. In addition, the latex films were used as substrates for evaporated ultrathin gold films with nominal thicknesses of 10 and 20 nm. Optical properties and topography of the samples were characterized using UV–vis spectroscopy and Atomic Force Microscopy (AFM) measurements, respectively. The latex films showed high-level transmittance of visible light, enabling the fabrication of semi-transparent gold electrodes. Electrochemical impedance spectroscopy (EIS) measurements were carried out for a number of days to investigate the long-term stability of the electrodes. The effect of 1-octadecanethiol (ODT) and HS(CH{sub 2}){sub 11}OH (MuOH) thiolation and protein (human serum albumin, HSA) adsorption on the impedance and capacitance was studied. In addition, cyclic voltammetry (CV) measurements were carried out to determine active medicinal components, i.e., caffeic acid with interesting biological activities and poorly water-soluble anti-inflammatory drug, piroxicam. The results show that the fabrication procedure presented in this study enables the formation of platforms with hierarchical morphologies for multimodal

  9. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  10. LSTM-Based Hierarchical Denoising Network for Android Malware Detection

    Directory of Open Access Journals (Sweden)

    Jinpei Yan

    2018-01-01

    Full Text Available Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN, a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequences are too long for LSTM to train due to the gradient vanishing problem. Hence, HDN uses a hierarchical structure, whose first-level LSTM parallelly computes on opcode subsequences (we called them method blocks to learn the dense representations; then the second-level LSTM can learn and detect malware through method block sequences. Considering that malicious behavior only appears in partial sequence segments, HDN uses method block denoise module (MBDM for data denoising by adaptive gradient scaling strategy based on loss cache. We evaluate and compare HDN with the latest mainstream researches on three datasets. The results show that HDN outperforms these Android malware detection methods,and it is able to capture longer sequence features and has better detection efficiency than N-gram-based malware detection which is similar to our method.

  11. A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

    Directory of Open Access Journals (Sweden)

    Shaoning Li

    2017-01-01

    Full Text Available In the fields of geographic information systems (GIS and remote sensing (RS, the clustering algorithm has been widely used for image segmentation, pattern recognition, and cartographic generalization. Although clustering analysis plays a key role in geospatial modelling, traditional clustering methods are limited due to computational complexity, noise resistant ability and robustness. Furthermore, traditional methods are more focused on the adjacent spatial context, which makes it hard for the clustering methods to be applied to multi-density discrete objects. In this paper, a new method, cell-dividing hierarchical clustering (CDHC, is proposed based on convex hull retraction. The main steps are as follows. First, a convex hull structure is constructed to describe the global spatial context of geospatial objects. Then, the retracting structure of each borderline is established in sequence by setting the initial parameter. The objects are split into two clusters (i.e., “sub-clusters” if the retracting structure intersects with the borderlines. Finally, clusters are repeatedly split and the initial parameter is updated until the terminate condition is satisfied. The experimental results show that CDHC separates the multi-density objects from noise sufficiently and also reduces complexity compared to the traditional agglomerative hierarchical clustering algorithm.

  12. Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

    Energy Technology Data Exchange (ETDEWEB)

    Xiong, Xiaopeng, E-mail: xpxiong@xmu.edu.cn; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju [Xiamen University, Department of Materials Science and Engineering, College of Materials (China)

    2013-08-15

    We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30-70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials.

  13. Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

    Science.gov (United States)

    Xiong, Xiaopeng; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju

    2013-08-01

    We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30-70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials.

  14. Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

    International Nuclear Information System (INIS)

    Xiong, Xiaopeng; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju

    2013-01-01

    We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30–70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials

  15. Free-standing and porous hierarchical nanoarchitectures constructed with cobalt cobaltite nanowalls for supercapacitors with high specific capacitances

    Science.gov (United States)

    Xiao, Yuanhua; Zhang, Aiqin; Liu, Shaojun; Zhao, Jihong; Fang, Shaoming; Jia, Dianzeng; Li, Feng

    2012-12-01

    Free-standing and porous hierarchical nanoarchitectures constructed with cobalt cobaltite (Co3O4) nanowalls have been successfully synthesized in large scale by calcining three dimensional (3D) hierarchical nanostructures consisting of single crystalline cobalt carbonate hydroxide hydrate - Co(CO3)0.5(OH)·0.11H2O nanowalls prepared with a solvothermal method. The step-by-step decomposition of the precursor can generate porous Co3O4 nanowalls with BET surface area of 88.34 m2 g-1. The as-prepared Co3O4 nanoarchitectures show superior specific capacitance to the most Co3O4 supercapacitor electrode materials to date. After continuously cycled for 1000 times of charge-discharge at 4 A g-1, the supercapacitors can retain ca 92.3% of their original specific capacitances. The excellent performances of the devices can be attributed to the porous and hierarchical 3D nanostructure of the materials.

  16. The Revised Hierarchical Model: A critical review and assessment

    OpenAIRE

    Kroll, Judith F.; van Hell, Janet G.; Tokowicz, Natasha; Green, David W.

    2010-01-01

    Brysbaert and Duyck (2009) suggest that it is time to abandon the Revised Hierarchical Model (Kroll and Stewart, 1994) in favor of connectionist models such as BIA+ (Dijkstra and Van Heuven, 2002) that more accurately account for the recent evidence on nonselective access in bilingual word recognition. In this brief response, we first review the history of the Revised Hierarchical Model (RHM), consider the set of issues that it was proposed to address, and then evaluate the evidence that supp...

  17. Communication Reducing Algorithms for Distributed Hierarchical N-Body Problems with Boundary Distributions

    KAUST Repository

    AbdulJabbar, Mustafa Abdulmajeed

    2017-05-11

    Reduction of communication and efficient partitioning are key issues for achieving scalability in hierarchical N-Body algorithms like Fast Multipole Method (FMM). In the present work, we propose three independent strategies to improve partitioning and reduce communication. First, we show that the conventional wisdom of using space-filling curve partitioning may not work well for boundary integral problems, which constitute a significant portion of FMM’s application user base. We propose an alternative method that modifies orthogonal recursive bisection to relieve the cell-partition misalignment that has kept it from scaling previously. Secondly, we optimize the granularity of communication to find the optimal balance between a bulk-synchronous collective communication of the local essential tree and an RDMA per task per cell. Finally, we take the dynamic sparse data exchange proposed by Hoefler et al. [1] and extend it to a hierarchical sparse data exchange, which is demonstrated at scale to be faster than the MPI library’s MPI_Alltoallv that is commonly used.

  18. Enhanced in vitro biocompatibility of ultrafine-grained titanium with hierarchical porous surface

    International Nuclear Information System (INIS)

    Zheng, C.Y.; Nie, F.L.; Zheng, Y.F.; Cheng, Y.; Wei, S.C.; Valiev, R.Z.

    2011-01-01

    Bulk ultrafine-grained Ti (UFG Ti) was successfully fabricated by equal-channel angular pressing (ECAP) technique in the present study, and to further improve its surface biocompatibility, surface modification techniques including sandblasting, acid etching and alkali treatment were employed to produce a hierarchical porous surface. The effect of the above surface treatments on the surface roughness, wettability, electrochemical corrosion behavior, apatite forming ability and cellular behavior of UFG Ti were systematically investigated with the coarse-grained Ti as control. Results show that UFG-Ti with surface modification had no pitting corrosion and presented low corrosion rate in simulated body fluids (SBF). The hierarchical porous surface yielded by surface modification enhanced the ability of UFG Ti to form a complete apatite layer when soaked in SBF and promoted osteoblast-like cells attachment and proliferation in vitro, which promises to have a significant impact on increasing bone-bonding ability and reducing healing time when implanted due to faster tissue integration.

  19. Hierarchical structure in the distribution of galaxies

    International Nuclear Information System (INIS)

    Schulman, L.S.; Seiden, P.E.; Technion - Israel Institute of Technology, Haifa; IBM Thomas J. Watson Research Center, Yorktown Heights, NY)

    1986-01-01

    The distribution of galaxies has a hierarchical structure with power-law correlations. This is usually thought to arise from gravity alone acting on an originally uniform distributioon. If, however, the original process of galaxy formation occurs through the stimulated birth of one galaxy due to a nearby recently formed galaxy, and if this process occurs near its percolation threshold, then a hierarchical structure with power-law correlations arises at the time of galaxy formation. If subsequent gravitational evolution within an expanding cosmology is such as to retain power-law correlations, the initial r exp -1 dropoff can steepen to the observed r exp -1.8. The distribution of galaxies obtained by this process produces clustering and voids, as observed. 23 references

  20. Subject-Verb Agreement in Children and Adults: Serial or Hierarchical Processing?

    Science.gov (United States)

    Negro, Isabelle; Chanquoy, Lucile; Fayol, Michel; Louis-Sidney, Maryse

    2005-01-01

    Two processes, serial and hierarchical, are generally opposed to account for grammatical encoding in language production. In a developmental perspective, the question addressed here is whether the subject-verb agreement during writing is computed serially, once the words are linearly ordered in the sentence, or hierarchically, as soon as the…

  1. HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

    Science.gov (United States)

    Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

    2013-01-01

    The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

  2. Self-cleaning poly(dimethylsiloxane) film with functional micro/nano hierarchical structures.

    Science.gov (United States)

    Zhang, Xiao-Sheng; Zhu, Fu-Yun; Han, Meng-Di; Sun, Xu-Ming; Peng, Xu-Hua; Zhang, Hai-Xia

    2013-08-27

    This paper reports a novel single-step wafer-level fabrication of superhydrophobic micro/nano dual-scale (MNDS) poly(dimethylsiloxane) (PDMS) films. The MNDS PDMS films were replicated directly from an ultralow-surface-energy silicon substrate at high temperature without any surfactant coating, achieving high precision. An improved deep reactive ion etching (DRIE) process with enhanced passivation steps was proposed to easily realize the ultralow-surface-energy MNDS silicon substrate and also utilized as a post-treatment process to strengthen the hydrophobicity of the MNDS PDMS film. The chemical modification of this enhanced passivation step to the surface energy has been studied by density functional theory, which is also the first investigation of C4F8 plasma treatment at molecular level by using first-principle calculations. From the results of a systematic study on the effect of key process parameters (i.e., baking temperature and time) on PDMS replication, insight into the interaction of hierarchical multiscale structures of polymeric materials during the micro/nano integrated fabrication process is experimentally obtained for the first time. Finite element simulation has been employed to illustrate this new phenomenon. Additionally, hierarchical PDMS pyramid arrays and V-shaped grooves have been developed and are intended for applications as functional structures for a light-absorption coating layer and directional transport of liquid droplets, respectively. This stable, self-cleaning PDMS film with functional micro/nano hierarchical structures, which is fabricated through a wafer-level single-step fabrication process using a reusable silicon mold, shows attractive potential for future applications in micro/nanodevices, especially in micro/nanofluidics.

  3. Effects of different hierarchical hybrid micro/nanostructure surfaces on implant osseointegration.

    Science.gov (United States)

    Cheng, Bingkun; Niu, Qiang; Cui, Yajun; Jiang, Wei; Zhao, Yunzhuan; Kong, Liang

    2017-06-01

    Hierarchical hybrid micro/nanostructure implant surfaces are considered to better mimic the hierarchical structure of bone and the nanostructures substantively influence osseointegration through managing cell behaviors. To enhance implant osseointegration for further clinical application, we evaluated the material properties and osseointegration effects of hierarchical surfaces with different nano-morphologies, using a rat model. Two representative surface fabrication methods, hydrofluoric (HF) acid etching combined with anodization (HF + AN) or magnetron sputtering (HF + MS), were selected. Sample material properties were evaluated by scanning electron microscopy, atomic force microscopy, X-ray diffraction, X-ray photoemission spectroscopy, and epoxy resin docking tensile test. Implants with different surfaces were inserted into the distal femurs of rats. After 12 weeks, osseointegration was examined by microcomputed tomography (micro-CT), histological, and biomechanical tests. Tensile testing demonstrated high bonding strength at coating/implant in the HF + MS group. Micro-CT revealed increased bone volume/total volume and significantly reduced trabecular separation in HF + MS versus other groups. Histological analysis showed significantly higher HF + MS bone-to-implant contact (74.78 ± 4.40%) versus HF + AN (65.11 ± 5.10%) and machined samples (56.03 ± 3.23%). The maximal HF + MS pull-out force increased by 33.7% versus HF + AN. These results indicated that HF + MS surfaces exhibited superior material property in terms of bonding strength and favorable implant osseointegration compared to other groups. © 2017 Wiley Periodicals, Inc.

  4. HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python

    Directory of Open Access Journals (Sweden)

    Thomas V Wiecki

    2013-08-01

    Full Text Available The diffusion model is a commonly used tool to infer latent psychological processes underlying decision making, and to link them to neural mechanisms based on reaction times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of reaction time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model, which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject / condition than non-hierarchical method, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g. fMRI influence decision making parameters. This paper will first describe the theoretical background of drift-diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the chi-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs

  5. The well-designed hierarchical structure of Musa basjoo for supercapacitors

    Science.gov (United States)

    Zheng, Kaiwen; Fan, Xiaorong; Mao, Yingzhu; Lin, Jingkai; Dai, Wenxuan; Zhang, Junying; Cheng, Jue

    2016-01-01

    Application of biological structure is one of the hottest topics in the field of science and technology. The unimaginable and excellent architectures of living beings supporting their vital activities have attracted the interests of worldwide researchers. An intriguing example is Musa basjoo which belongs to the herb, while appears like a tree. The profound mystery of structure and potential application of Musa basjoo have not been probed. Here we show the finding of the hierarchical structure of Musa basjoo and the outstanding electrochemical performance of the super-capacitors fabricated through the simple carbonization of Musa basjoo followed by KOH activation. Musa basjoo has three layers of structure: nanometer-level, micrometer-level and millimeter-level. The nanometer-level structure constructs the micrometer-level structure, while the micrometer-level structure constructs the millimeter-level structure. Based on this hierarchical structure, Musa basjoo reduces the unnecessary weight and therefore supports its huge body. The super-capacitors derived from Musa basjoo display a high specific capacitance and a good cycling stability. This enlightening work opens a window for the applications of the natural structure and we hope that more and more people could pay attention to the bio-inspired materials. PMID:26842714

  6. Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

    Science.gov (United States)

    Wilson, Alex; Blunsom, Phil; Ker, Andrew D.

    2014-02-01

    This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.

  7. Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

    Science.gov (United States)

    Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

    2015-12-01

    Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. The well-designed hierarchical structure of Musa basjoo for supercapacitors

    Science.gov (United States)

    Zheng, Kaiwen; Fan, Xiaorong; Mao, Yingzhu; Lin, Jingkai; Dai, Wenxuan; Zhang, Junying; Cheng, Jue

    2016-02-01

    Application of biological structure is one of the hottest topics in the field of science and technology. The unimaginable and excellent architectures of living beings supporting their vital activities have attracted the interests of worldwide researchers. An intriguing example is Musa basjoo which belongs to the herb, while appears like a tree. The profound mystery of structure and potential application of Musa basjoo have not been probed. Here we show the finding of the hierarchical structure of Musa basjoo and the outstanding electrochemical performance of the super-capacitors fabricated through the simple carbonization of Musa basjoo followed by KOH activation. Musa basjoo has three layers of structure: nanometer-level, micrometer-level and millimeter-level. The nanometer-level structure constructs the micrometer-level structure, while the micrometer-level structure constructs the millimeter-level structure. Based on this hierarchical structure, Musa basjoo reduces the unnecessary weight and therefore supports its huge body. The super-capacitors derived from Musa basjoo display a high specific capacitance and a good cycling stability. This enlightening work opens a window for the applications of the natural structure and we hope that more and more people could pay attention to the bio-inspired materials.

  9. A hierarchical approach to reducing communication in parallel graph algorithms

    KAUST Repository

    Harshvardhan,

    2015-01-01

    Large-scale graph computing has become critical due to the ever-increasing size of data. However, distributed graph computations are limited in their scalability and performance due to the heavy communication inherent in such computations. This is exacerbated in scale-free networks, such as social and web graphs, which contain hub vertices that have large degrees and therefore send a large number of messages over the network. Furthermore, many graph algorithms and computations send the same data to each of the neighbors of a vertex. Our proposed approach recognizes this, and reduces communication performed by the algorithm without change to user-code, through a hierarchical machine model imposed upon the input graph. The hierarchical model takes advantage of locale information of the neighboring vertices to reduce communication, both in message volume and total number of bytes sent. It is also able to better exploit the machine hierarchy to further reduce the communication costs, by aggregating traffic between different levels of the machine hierarchy. Results of an implementation in the STAPL GL shows improved scalability and performance over the traditional level-synchronous approach, with 2.5 × - 8× improvement for a variety of graph algorithms at 12, 000+ cores.

  10. A hierarchical spatiotemporal analog forecasting model for count data.

    Science.gov (United States)

    McDermott, Patrick L; Wikle, Christopher K; Millspaugh, Joshua

    2018-01-01

    Analog forecasting is a mechanism-free nonlinear method that forecasts a system forward in time by examining how past states deemed similar to the current state moved forward. Previous applications of analog forecasting has been successful at producing robust forecasts for a variety of ecological and physical processes, but it has typically been presented in an empirical or heuristic procedure, rather than as a formal statistical model. The methodology presented here extends the model-based analog method of McDermott and Wikle (Environmetrics, 27, 2016, 70) by placing analog forecasting within a fully hierarchical statistical framework that can accommodate count observations. Using a Bayesian approach, the hierarchical analog model is able to quantify rigorously the uncertainty associated with forecasts. Forecasting waterfowl settling patterns in the northwestern United States and Canada is conducted by applying the hierarchical analog model to a breeding population survey dataset. Sea surface temperature (SST) in the Pacific Ocean is used to help identify potential analogs for the waterfowl settling patterns.

  11. Large-scale model of flow in heterogeneous and hierarchical porous media

    Science.gov (United States)

    Chabanon, Morgan; Valdés-Parada, Francisco J.; Ochoa-Tapia, J. Alberto; Goyeau, Benoît

    2017-11-01

    Heterogeneous porous structures are very often encountered in natural environments, bioremediation processes among many others. Reliable models for momentum transport are crucial whenever mass transport or convective heat occurs in these systems. In this work, we derive a large-scale average model for incompressible single-phase flow in heterogeneous and hierarchical soil porous media composed of two distinct porous regions embedding a solid impermeable structure. The model, based on the local mechanical equilibrium assumption between the porous regions, results in a unique momentum transport equation where the global effective permeability naturally depends on the permeabilities at the intermediate mesoscopic scales and therefore includes the complex hierarchical structure of the soil. The associated closure problem is numerically solved for various configurations and properties of the heterogeneous medium. The results clearly show that the effective permeability increases with the volume fraction of the most permeable porous region. It is also shown that the effective permeability is sensitive to the dimensionality spatial arrangement of the porous regions and in particular depends on the contact between the impermeable solid and the two porous regions.

  12. Hierarchical remote data possession checking method based on massive cloud files

    Directory of Open Access Journals (Sweden)

    Ma Haifeng

    2017-06-01

    Full Text Available Cloud storage service enables users to migrate their data and applications to the cloud, which saves the local data maintenance and brings great convenience to the users. But in cloud storage, the storage servers may not be fully trustworthy. How to verify the integrity of cloud data with lower overhead for users has become an increasingly concerned problem. Many remote data integrity protection methods have been proposed, but these methods authenticated cloud files one by one when verifying multiple files. Therefore, the computation and communication overhead are still high. Aiming at this problem, a hierarchical remote data possession checking (hierarchical-remote data possession checking (H-RDPC method is proposed, which can provide efficient and secure remote data integrity protection and can support dynamic data operations. This paper gives the algorithm descriptions, security, and false negative rate analysis of H-RDPC. The security analysis and experimental performance evaluation results show that the proposed H-RDPC is efficient and reliable in verifying massive cloud files, and it has 32–81% improvement in performance compared with RDPC.

  13. Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Feng Juan

    2013-10-01

    Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

  14. New insight in magnetic saturation behavior of nickel hierarchical structures

    Science.gov (United States)

    Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng

    2017-09-01

    It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.

  15. The effect of hierarchical micro/nanosurface titanium implant on osseointegration in ovariectomized sheep.

    Science.gov (United States)

    Xiao, J; Zhou, H; Zhao, L; Sun, Y; Guan, S; Liu, B; Kong, L

    2011-06-01

    Hydrofluoric etching and anodized hierarchical micro/nanotextured surface titanium implant was placed in mandibles of ovariectomized sheep for 12 weeks, and it showed improved osseointegration by resonance frequency analysis (RFA), microcomputed tomography (micro-CT) evaluation, histomorphometry, and biomechanical test. This study aimed to investigate the effects of micro/nanotextured titanium implant on osseointegration in ovariectomized (OVX) sheep. The hierarchical micro/nanotextured surface of titanium implant was fabricated by acid in 0.5% (w/v) hydrofluoric (HF) and anodized in HF acid electrolytes with a DC power of 20 V, and the machined surface implants with no treatment served as control group. The implants were placed in mandibles of OVX sheep, respectively. Twelve weeks after implantation, RFA, microcomputed tomography, histomorphometry, and biomechanical tests were applied to detect the osseointegration of the two groups. The implant stability quotient (ISQ) values, the maximum pull-out forces, and the bone-implant contact (BIC) were 65.5 ± 6.3, 490.6 ± 72.7 N, and 58.31 ± 5.79% in the micro/nanogroup and 58.3 ± 8.9, 394.5 ± 54.5 N, and 46.85 ± 5.04% in the control group, respectively. There was no significant difference between the two groups in ISQ values (p > 0.05), but in the micro/nanogroup, the maximal pull-out force and the BIC were increased significantly (p Micro-CT analysis showed that the bone volume ratio and the trabecular number increased significantly (p micro/nanogroup. Implant modification by HF acid etching and anodization to form a hierarchical micro/nanotextured surface could improve titanium implant osseointegration in OVX sheep 12 weeks after implantation.

  16. Obstacle Avoidance of a Mobile Robot with Hierarchical Structure

    Energy Technology Data Exchange (ETDEWEB)

    Park, Chan Gyu [Yeungnam College of Science and Technolgy, Taegu (Korea)

    2001-06-01

    This paper proposed a new hierarchical fuzzy-neural network algorithm for navigation of a mobile robot within unknown dynamic environment. Proposed navigation algorithm used the learning ability of the neural network and the feasibility of control highly nonlinear system of fuzzy theory. The proposed navigation algorithm used fuzzy algorithm for goal approach and fuzzy-network for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment. (author). 11 refs., 14 figs., 2 tabs.

  17. Enhanced lithium storage performances of hierarchical hollow MoS₂ nanoparticles assembled from nanosheets.

    Science.gov (United States)

    Wang, Meng; Li, Guangda; Xu, Huayun; Qian, Yitai; Yang, Jian

    2013-02-01

    MoS(2), because of its layered structure and high theoretical capacity, has been regarded as a potential candidate for electrode materials in lithium secondary batteries. But it suffers from the poor cycling stability and low rate capability. Here, hierarchical hollow nanoparticles of MoS(2) nanosheets with an increased interlayer distance are synthesized by a simple solvothermal reaction at a low temperature. The formation of hierarchical hollow nanoparticles is based on the intermediate, K(2)NaMoO(3)F(3), as a self-sacrificed template. These hollow nanoparticles exhibit a reversible capacity of 902 mA h g(-1) at 100 mA g(-1) after 80 cycles, much higher than the solid counterpart. At a current density of 1000 mA g(-1), the reversible capacity of the hierarchical hollow nanoparticles could be still maintained at 780 mAh g(-1). The enhanced lithium storage performances of the hierarchical hollow nanoparticles in reversible capacities, cycling stability and rate performances can be attributed to their hierarchical surface, hollow structure feature and increased layer distance of S-Mo-S. Hierarchical hollow nanoparticles as an ensemble of these features, could be applied to other electrode materials for the superior electrochemical performance.

  18. Runtime Concepts of Hierarchical Software Components

    Czech Academy of Sciences Publication Activity Database

    Bureš, Tomáš; Hnětynka, P.; Plášil, František

    2007-01-01

    Roč. 8, special (2007), s. 454-463 ISSN 1525-9293 R&D Projects: GA AV ČR 1ET400300504 Institutional research plan: CEZ:AV0Z10300504 Keywords : component-based development * hierarchical components * connectors * controlers * runtime environment Subject RIV: JC - Computer Hardware ; Software

  19. Hierarchical production planning for consumer goods

    NARCIS (Netherlands)

    Kok, de A.G.

    1990-01-01

    Abstract In this paper the mathematical logic behind a hierarchical planning procedure is discussed. The planning procedure is used to derive production volumes of consumer products. The essence of the planning procedure is that first a commitment is made concerning the production volume for a

  20. Spatial-area selective retrieval of multiple object-place associations in a hierarchical cognitive map formed by theta phase coding.

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    2009-06-01

    The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.