Sample records for 2-level hierarchical linear

1. Reasons for Hierarchical Linear Modeling: A Reminder.

ERIC Educational Resources Information Center

Wang, Jianjun

1999-01-01

Uses examples of hierarchical linear modeling (HLM) at local and national levels to illustrate proper applications of HLM and dummy variable regression. Raises cautions about the circumstances under which hierarchical data do not need HLM. (SLD)

2. Managing Clustered Data Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

2012-01-01

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

3. Hierarchical Linear Modeling in Salary-Equity Studies.

ERIC Educational Resources Information Center

Loeb, Jane W.

2003-01-01

Provides information on how hierarchical linear modeling can be used as an alternative to multiple regression analysis for conducting salary-equity studies. Salary data are used to compare and contrast the two approaches. (EV)

4. Hierarchical Multiobjective Linear Programming Problems with Fuzzy Domination Structures

Yano, Hitoshi

2010-10-01

In this paper, we focus on hierarchical multiobjective linear programming problems with fuzzy domination structures where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. After introducing decision powers and the solution concept based on the α-level set for the fuzzy convex cone Λ which reflects a fuzzy domination structure, we propose a fuzzy approach to obtain a satisfactory solution which reflects not only the hierarchical relationships between multiple decision makers but also their own preferences for their membership functions. In the proposed method, instead of Pareto optimal concept, a generalized Λ˜α-extreme point concept is introduced. In order to obtain a satisfactory solution from among a generalized Λ˜α-extreme point set, an interactive algorithm based on linear programming is proposed, and an interactive processes are demonstrated by means of an illustrative numerical example.

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

ERIC Educational Resources Information Center

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…

6. Building Algebra Testlets: A Comparison of Hierarchical and Linear Structures.

ERIC Educational Resources Information Center

Wainer, Howard; And Others

1991-01-01

Hierarchical (adaptive) and linear methods of testlet construction were compared. The performance of 2,080 ninth and tenth graders on a 4-item testlet was used to predict performance on the entire test. The adaptive test was slightly superior as a predictor, but the cost of obtaining that superiority was considerable. (SLD)

7. Johnson-Neyman Type Technique in Hierarchical Linear Model.

ERIC Educational Resources Information Center

Miyazaki, Yasuo

One of the innovative approaches in the use of hierarchical linear models (HLM) is to use HLM for Slopes as Outcomes models. This implies that the researcher considers that the regression slopes vary from cluster to cluster randomly as well as systematically with certain covariates at the cluster level. Among the covariates, group indicator…

8. Johnson-Neyman Type Technique in Hierarchical Linear Models

ERIC Educational Resources Information Center

Miyazaki, Yasuo; Maier, Kimberly S.

2005-01-01

In hierarchical linear models we often find that group indicator variables at the cluster level are significant predictors for the regression slopes. When this is the case, the average relationship between the outcome and a key independent variable are different from group to group. In these settings, a question such as "what range of the…

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

ERIC Educational Resources Information Center

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…

10. Predictability of extremes in non-linear hierarchically organized systems

Kossobokov, V. G.; Soloviev, A.

2011-12-01

Understanding the complexity of non-linear dynamics of hierarchically organized systems progresses to new approaches in assessing hazard and risk of the extreme catastrophic events. In particular, a series of interrelated step-by-step studies of seismic process along with its non-stationary though self-organized behaviors, has led already to reproducible intermediate-term middle-range earthquake forecast/prediction technique that has passed control in forward real-time applications during the last two decades. The observed seismic dynamics prior to and after many mega, great, major, and strong earthquakes demonstrate common features of predictability and diverse behavior in course durable phase transitions in complex hierarchical non-linear system of blocks-and-faults of the Earth lithosphere. The confirmed fractal nature of earthquakes and their distribution in space and time implies that many traditional estimations of seismic hazard (from term-less to short-term ones) are usually based on erroneous assumptions of easy tractable analytical models, which leads to widespread practice of their deceptive application. The consequences of underestimation of seismic hazard propagate non-linearly into inflicted underestimation of risk and, eventually, into unexpected societal losses due to earthquakes and associated phenomena (i.e., collapse of buildings, landslides, tsunamis, liquefaction, etc.). The studies aimed at forecast/prediction of extreme events (interpreted as critical transitions) in geophysical and socio-economical systems include: (i) large earthquakes in geophysical systems of the lithosphere blocks-and-faults, (ii) starts and ends of economic recessions, (iii) episodes of a sharp increase in the unemployment rate, (iv) surge of the homicides in socio-economic systems. These studies are based on a heuristic search of phenomena preceding critical transitions and application of methodologies of pattern recognition of infrequent events. Any study of rare

11. On the unnecessary ubiquity of hierarchical linear modeling.

PubMed

McNeish, Daniel; Stapleton, Laura M; Silverman, Rebecca D

2017-03-01

In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular methods for modeling clustered data. HLM and its discrete outcome extensions, however, are certainly not the only methods available to model clustered data. Although other methods exist and are widely implemented in other disciplines, it seems that psychologists have yet to consider these methods in substantive studies. This article compares and contrasts HLM with alternative methods including generalized estimating equations and cluster-robust standard errors. These alternative methods do not model random effects and thus make a smaller number of assumptions and are interpreted identically to single-level methods with the benefit that estimates are adjusted to reflect clustering of observations. Situations where these alternative methods may be advantageous are discussed including research questions where random effects are and are not required, when random effects can change the interpretation of regression coefficients, challenges of modeling with random effects with discrete outcomes, and examples of published psychology articles that use HLM that may have benefitted from using alternative methods. Illustrative examples are provided and discussed to demonstrate the advantages of the alternative methods and also when HLM would be the preferred method. (PsycINFO Database Record

12. Centering, Scale Indeterminacy, and Differential Item Functioning Detection in Hierarchical Generalized Linear and Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Cheong, Yuk Fai; Kamata, Akihito

2013-01-01

In this article, we discuss and illustrate two centering and anchoring options available in differential item functioning (DIF) detection studies based on the hierarchical generalized linear and generalized linear mixed modeling frameworks. We compared and contrasted the assumptions of the two options, and examined the properties of their DIF…

13. Hierarchical linear modeling of longitudinal pedigree data for genetic association analysis.

PubMed

Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads; Jensen, Andreas Kryger; Christiansen, Lene; Christensen, Kaare; Zhao, Jing Hua; Kruse, Torben A

2014-01-01

Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed-effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects on the mean level of a phenotype, they are not sufficiently straightforward to handle the kinship correlation on the time-dependent trajectories of a phenotype. We introduce a 2-level hierarchical linear model to separately assess the genetic associations with the mean level and the rate of change of a phenotype, integrating kinship correlation in the analysis. We apply our method to the Genetic Analysis Workshop 18 genome-wide association studies data on chromosome 3 to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees. Our method identifies genetic variants associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful for genetic association studies in related samples using longitudinal design.

14. Hierarchical linear model: thinking outside the traditional repeated-measures analysis-of-variance box.

PubMed

Lininger, Monica; Spybrook, Jessaca; Cheatham, Christopher C

2015-04-01

Longitudinal designs are common in the field of athletic training. For example, in the Journal of Athletic Training from 2005 through 2010, authors of 52 of the 218 original research articles used longitudinal designs. In 50 of the 52 studies, a repeated-measures analysis of variance was used to analyze the data. A possible alternative to this approach is the hierarchical linear model, which has been readily accepted in other medical fields. In this short report, we demonstrate the use of the hierarchical linear model for analyzing data from a longitudinal study in athletic training. We discuss the relevant hypotheses, model assumptions, analysis procedures, and output from the HLM 7.0 software. We also examine the advantages and disadvantages of using the hierarchical linear model with repeated measures and repeated-measures analysis of variance for longitudinal data.

15. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

ERIC Educational Resources Information Center

Fung, Karen; ElAtia, Samira

2015-01-01

Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

16. Augmenting Visual Analysis in Single-Case Research with Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Davis, Dawn H.; Gagne, Phill; Fredrick, Laura D.; Alberto, Paul A.; Waugh, Rebecca E.; Haardorfer, Regine

2013-01-01

The purpose of this article is to demonstrate how hierarchical linear modeling (HLM) can be used to enhance visual analysis of single-case research (SCR) designs. First, the authors demonstrated the use of growth modeling via HLM to augment visual analysis of a sophisticated single-case study. Data were used from a delayed multiple baseline…

17. Analyzing Measurement Models of Latent Variables through Multilevel Confirmatory Factor Analysis and Hierarchical Linear Modeling Approaches.

ERIC Educational Resources Information Center

Li, Fuzhong; Duncan, Terry E.; Harmer, Peter; Acock, Alan; Stoolmiller, Mike

1998-01-01

Discusses the utility of multilevel confirmatory factor analysis and hierarchical linear modeling methods in testing measurement models in which the underlying attribute may vary as a function of levels of observation. A real dataset is used to illustrate the two approaches and their comparability. (SLD)

18. A Hierarchical Linear Model with Factor Analysis Structure at Level 2

ERIC Educational Resources Information Center

Miyazaki, Yasuo; Frank, Kenneth A.

2006-01-01

In this article the authors develop a model that employs a factor analysis structure at Level 2 of a two-level hierarchical linear model (HLM). The model (HLM2F) imposes a structure on a deficient rank Level 2 covariance matrix [tau], and facilitates estimation of a relatively large [tau] matrix. Maximum likelihood estimators are derived via the…

19. Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

ERIC Educational Resources Information Center

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

2012-01-01

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

20. What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

1. Examining Factors Affecting Science Achievement of Hong Kong in PISA 2006 Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Lam, Terence Yuk Ping; Lau, Kwok Chi

2014-01-01

This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science…

2. Meta-Analysis in Higher Education: An Illustrative Example Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Denson, Nida; Seltzer, Michael H.

2011-01-01

The purpose of this article is to provide higher education researchers with an illustrative example of meta-analysis utilizing hierarchical linear modeling (HLM). This article demonstrates the step-by-step process of meta-analysis using a recently-published study examining the effects of curricular and co-curricular diversity activities on racial…

3. Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2013-01-01

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

4. A Closer Look at Charter Schools Using Hierarchical Linear Modeling. NCES 2006-460

ERIC Educational Resources Information Center

Braun, Henry; Jenkins, Frank; Grigg, Wendy

2006-01-01

Charter schools are a relatively new, but fast-growing, phenomenon in American public education. As such, they merit the attention of all parties interested in the education of the nation's youth. The present report comprises two separate analyses. The first is a "combined analysis" in which hierarchical linear models (HLMs) were…

5. Missing Data Treatments at the Second Level of Hierarchical Linear Models

ERIC Educational Resources Information Center

St. Clair, Suzanne W.

2011-01-01

The current study evaluated the performance of traditional versus modern MDTs in the estimation of fixed-effects and variance components for data missing at the second level of an hierarchical linear model (HLM) model across 24 different study conditions. Variables manipulated in the analysis included, (a) number of Level-2 variables with missing…

6. A Hierarchical Linear Model for Estimating Gender-Based Earnings Differentials.

ERIC Educational Resources Information Center

Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

1998-01-01

Estimates of gender earnings inequality in data from 116,431 Jewish workers were compared using a hierarchical linear model (HLM) and ordinary least squares model. The HLM allows estimation of the extent to which earnings inequality depends on occupational characteristics. (SK)

7. Efficient analysis of Q-level nested hierarchical general linear models given ignorable missing data.

PubMed

Shin, Yongyun; Raudenbush, Stephen W

2013-09-28

This article extends single-level missing data methods to efficient estimation of a Q-level nested hierarchical general linear model given ignorable missing data with a general missing pattern at any of the Q levels. The key idea is to reexpress a desired hierarchical model as the joint distribution of all variables including the outcome that are subject to missingness, conditional on all of the covariates that are completely observed and to estimate the joint model under normal theory. The unconstrained joint model, however, identifies extraneous parameters that are not of interest in subsequent analysis of the hierarchical model and that rapidly multiply as the number of levels, the number of variables subject to missingness, and the number of random coefficients grow. Therefore, the joint model may be extremely high dimensional and difficult to estimate well unless constraints are imposed to avoid the proliferation of extraneous covariance components at each level. Furthermore, the over-identified hierarchical model may produce considerably biased inferences. The challenge is to represent the constraints within the framework of the Q-level model in a way that is uniform without regard to Q; in a way that facilitates efficient computation for any number of Q levels; and also in a way that produces unbiased and efficient analysis of the hierarchical model. Our approach yields Q-step recursive estimation and imputation procedures whose qth-step computation involves only level-q data given higher-level computation components. We illustrate the approach with a study of the growth in body mass index analyzing a national sample of elementary school children.

8. Nonexpansiveness of a linearized augmented Lagrangian operator for hierarchical convex optimization

2017-04-01

Hierarchical convex optimization concerns two-stage optimization problems: the first stage problem is a convex optimization; the second stage problem is the minimization of a convex function over the solution set of the first stage problem. For the hierarchical convex optimization, the hybrid steepest descent method (HSDM) can be applied, where the solution set of the first stage problem must be expressed as the fixed point set of a certain nonexpansive operator. In this paper, we propose a nonexpansive operator that yields a computationally efficient update when it is plugged into the HSDM. The proposed operator is inspired by the update of the linearized augmented Lagrangian method. It is applicable to characterize the solution set of recent sophisticated convex optimization problems found in the context of inverse problems, where the sum of multiple proximable convex functions involving linear operators must be minimized to incorporate preferable properties into the minimizers. For such a problem formulation, there has not yet been reported any nonexpansive operator that yields an update free from the inversions of linear operators in cases where it is utilized in the HSDM. Unlike previously known nonexpansive operators, the proposed operator yields an inversion-free update in such cases. As an application of the proposed operator plugged into the HSDM, we also present, in the context of the so-called superiorization, an algorithmic solution to a convex optimization problem over the generalized convex feasible set where the intersection of the hard constraints is not necessarily simple.

9. A Monte Carlo Power Analysis of Traditional Repeated Measures and Hierarchical Multivariate Linear Models in Longitudinal Data Analysis.

PubMed

Fang, Hua; Brooks, Gordon P; Rizzo, Maria L; Espy, Kimberly A; Barcikowski, Robert S

2008-01-01

The power properties of traditional repeated measures and hierarchical linear models have not been clearly determined in the balanced design for longitudinal studies in the current literature. A Monte Carlo power analysis of traditional repeated measures and hierarchical multivariate linear models are presented under three variance-covariance structures. Results suggest that traditional repeated measures have higher power than hierarchical linear models for main effects, but lower power for interaction effects. Significant power differences are also exhibited when power is compared across different covariance structures. Results also supplement more comprehensive empirical indexes for estimating model precision via bootstrap estimates and the approximate power for both main effects and interaction tests under standard model assumptions.

10. Personality change over 40 years of adulthood: hierarchical linear modeling analyses of two longitudinal samples.

PubMed

Helson, Ravenna; Jones, Constance; Kwan, Virginia S Y

2002-09-01

Normative personality change over 40 years was shown in 2 longitudinal cohorts with hierarchical linear modeling of California Psychological Inventory data obtained at multiple times between ages 21-75. Although themes of change and the paucity of differences attributable to gender and cohort largely supported findings of multiethnic cross-sectional samples, the authors also found much quadratic change and much individual variability. The form of quadratic change supported predictions about the influence of period of life and social climate as factors in change over the adult years: Scores on Dominance and Independence peaked in the middle age of both cohorts, and scores on Responsibility were lowest during peak years of the culture of individualism. The idea that personality change is most pronounced before age 30 and then reaches a plateau received no support.

11. Using hierarchical linear growth models to evaluate protective mechanisms that mediate science achievement

von Secker, Clare Elaine

The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.

12. Fitting host-parasitoid models with CV2 > 1 using hierarchical generalized linear models.

PubMed Central

Perry, J N; Noh, M S; Lee, Y; Alston, R D; Norowi, H M; Powell, W; Rennolls, K

2000-01-01

The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density-dependent heterogeneity (HDD) to be distinguished from between-patch, host density-independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well-known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent. PMID:11416907

13. Hierarchical Linear Modeling (HLM): An Introduction to Key Concepts within Cross-Sectional and Growth Modeling Frameworks. Technical Report #1308

ERIC Educational Resources Information Center

Anderson, Daniel

2012-01-01

This manuscript provides an overview of hierarchical linear modeling (HLM), as part of a series of papers covering topics relevant to consumers of educational research. HLM is tremendously flexible, allowing researchers to specify relations across multiple "levels" of the educational system (e.g., students, classrooms, schools, etc.).…

14. Exploring the Effects of Congruence and Holland's Personality Codes on Job Satisfaction: An Application of Hierarchical Linear Modeling Techniques

ERIC Educational Resources Information Center

Ishitani, Terry T.

2010-01-01

This study applied hierarchical linear modeling to investigate the effect of congruence on intrinsic and extrinsic aspects of job satisfaction. Particular focus was given to differences in job satisfaction by gender and by Holland's first-letter codes. The study sample included nationally represented 1462 female and 1280 male college graduates who…

15. Motivation, Classroom Environment, and Learning in Introductory Geology: A Hierarchical Linear Model

Gilbert, L. A.; Hilpert, J. C.; Van Der Hoeven Kraft, K.; Budd, D.; Jones, M. H.; Matheney, R.; Mcconnell, D. A.; Perkins, D.; Stempien, J. A.; Wirth, K. R.

2013-12-01

Prior research has indicated that highly motivated students perform better and that learning increases in innovative, reformed classrooms, but untangling the student effects from the instructor effects is essential to understanding how to best support student learning. Using a hierarchical linear model, we examine these effects separately and jointly. We use data from nearly 2,000 undergraduate students surveyed by the NSF-funded GARNET (Geoscience Affective Research NETwork) project in 65 different introductory geology classes at research universities, public masters-granting universities, liberal arts colleges and community colleges across the US. Student level effects were measured as increases in expectancy and self-regulation using the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991). Instructor level effects were measured using the Reformed Teaching Observation Protocol, (RTOP; Sawada et al., 2000), with higher RTOP scores indicating a more reformed, student-centered classroom environment. Learning was measured by learning gains on a Geology Concept Inventory (GCI; Libarkin and Anderson, 2005) and normalized final course grade. The hierarchical linear model yielded significant results at several levels. At the student level, increases in expectancy and self-regulation are significantly and positively related to higher grades regardless of instructor; the higher the increase, the higher the grade. At the instructor level, RTOP scores are positively related to normalized average GCI learning gains. The higher the RTOP score, the higher the average class GCI learning gains. Across both levels, average class GCI learning gains are significantly and positively related to student grades; the higher the GCI learning gain, the higher the grade. Further, the RTOP scores are significantly and negatively related to the relationship between expectancy and course grade. The lower the RTOP score, the higher the correlation between change in

16. Working memory contributions to relative clause attachment processing: a hierarchical linear modeling analysis.

PubMed

Traxler, Matthew J

2007-07-01

An eye-movement-monitoring experiment tested readers' responses to sentences containing relative clauses that could be attached to one or both of two preceding nouns. Previous experiments with such sentences have indicated that globally ambiguous relative clauses are processed more quickly than are determinately attached relative clauses. Central to the present research, a recent study (Swets, Desmet, Hambrick, & Ferreira, 2007) showed that offline preferences for such sentences differ as a function of working memory capacity. Specifically, both English and Dutch participants' preference for the second of two nouns as the host for the relative clause increased as their working memory capacity increased. In the present study, readers' working memory capacity was measured, and eye movements were monitored. Hierarchical linear modeling was used to determine whether working memory capacity moderated readers' online processing performance. The modeling indicated that determinately attached sentences were harder to process than globally ambiguous sentences, that working memory did not affect processing of the relative clause itself, but that working memory did moderate how easy it was to integrate the relative clause with the preceding sentence context. Specifically, in contrast with the offline results from Swets and colleagues' study, readers with higher working memory capacity were more likely to prefer the first noun over the second noun as the host for the relative clause.

17. Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis.

PubMed

Bona, M T; Andrés, J M

2007-06-15

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.

18. Examining Factors Affecting Science Achievement of Hong Kong in PISA 2006 Using Hierarchical Linear Modeling

Lam, Terence Yuk Ping; Lau, Kwok Chi

2014-10-01

This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science Study; therefore, an exploration of the factors that affect science performances of Hong Kong students can give a lens to examine how science education can be improved in Hong Kong and other countries. The analyses reveal that student backgrounds as male, at higher grade levels, and born in mainland (when in the same grade) are associated with better science performance. Among the attitudinal factors, enjoyment of science and self-efficacy in science play important roles in scientific achievements. Most of the parental factors, on the other hand, are not having significant impacts on achievement after student attitudes are taken into account, with only parents' value of science having a small effect. School student intake is found to be a strong predictor of school average achievement, as well as a major mediator of the effects of school enrollment size and school socio-economic status. The findings differ from recently reported results, which suggested that school enrollment size was associated with achievement. This study also points out the problems of the use of science instruction time as a school-level variable to explain science achievement in Hong Kong.

19. Determinants of hospital closure in South Korea: use of a hierarchical generalized linear model.

PubMed

Noh, Maengseok; Lee, Youngjo; Yun, Sung-Cheol; Lee, Sang-Il; Lee, Moo-Song; Khang, Young-Ho

2006-11-01

Understanding causes of hospital closure is important if hospitals are to survive and continue to fulfill their missions as the center for health care in their neighborhoods. Knowing which hospitals are most susceptible to closure can be of great use for hospital administrators and others interested in hospital performance. Although prior studies have identified a range of factors associated with increased risk of hospital closure, most are US-based and do not directly relate to health care systems in other countries. We examined determinants of hospital closure in a nationally representative sample: 805 hospitals established in South Korea before 1996 were examined-hospitals established in 1996 or after were excluded. Major organizational changes (survival vs. closure) were followed for all South Korean hospitals from 1996 through 2002. With the use of a hierarchical generalized linear model, a frailty model was used to control correlation among repeated measurements for risk factors for hospital closure. Results showed that ownership and hospital size were significantly associated with hospital closure. Urban hospitals were less likely to close than rural hospitals. However, the urban location of a hospital was not associated with hospital closure after adjustment for the proportion of elderly. Two measures for hospital competition (competitive beds and 1-Hirshman--Herfindalh index) were positively associated with risk of hospital closure before and after adjustment for confounders. In addition, annual 10% change in competitive beds was significantly predictive of hospital closure. In conclusion, yearly trends in hospital competition as well as the level of hospital competition each year affected hospital survival. Future studies need to examine the contribution of internal factors such as management strategies and financial status to hospital closure in South Korea.

20. Comparing Four Different Statistical Packages for Hierarchical Linear Regression: GENMOD, HLM, ML2, and VARCL.

ERIC Educational Resources Information Center

Kreft, Ita G. G.; And Others

An overview is given of the available statistical theory and software for analyzing hierarchically nested data. Programs are evaluated, and general techniques are proposed to analyze data from several domains. This research is part of a larger project to evaluate elementary education in the Netherlands. The models discussed are the random…

1. A Monte Carlo Study of Fit Indices in Hierarchical Linear Models

ERIC Educational Resources Information Center

McMurray, Kelly

2010-01-01

In educational research, students often exist in a multilevel social setting that can be identified by students within classrooms, classrooms nested in schools, schools nested in school districts, school districts nested in school counties, and school counties nested in states. These are considered hierarchical, nested, or multilevel because…

2. Treatment of Missing Data at the Second Level of Hierarchical Linear Models.

ERIC Educational Resources Information Center

Gibson, Nicole Morgan; Olejnik, Stephen

2003-01-01

Studied the problem of missing data at the second level of a two-level hierarchal data structure using data generated to simulate the 1982 High School and Beyond data set with five different missing data treatments: listwise deletion, overall mean substitution, group mean substitution, the EM algorithm, and multiple imputation. (SLD)

3. Evaluating the Impacts of ICT Use: A Multi-Level Analysis with Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Song, Hae-Deok; Kang, Taehoon

2012-01-01

The purpose of this study is to evaluate the impacts of ICT use on achievements by considering not only ICT use, but also the process and background variables that influence ICT use at both the student- and school-level. This study was conducted using data from the 2010 Survey of Seoul Education Longitudinal Research. A Hierarchical Linear…

4. booc.io: An Education System with Hierarchical Concept Maps and Dynamic Non-linear Learning Plans.

PubMed

Schwab, Michail; Strobelt, Hendrik; Tompkin, James; Fredericks, Colin; Huff, Connor; Higgins, Dana; Strezhnev, Anton; Komisarchik, Mayya; King, Gary; Pfister, Hanspeter

2017-01-01

Information hierarchies are difficult to express when real-world space or time constraints force traversing the hierarchy in linear presentations, such as in educational books and classroom courses. We present booc.io, which allows linear and non-linear presentation and navigation of educational concepts and material. To support a breadth of material for each concept, booc.io is Web based, which allows adding material such as lecture slides, book chapters, videos, and LTIs. A visual interface assists the creation of the needed hierarchical structures. The goals of our system were formed in expert interviews, and we explain how our design meets these goals. We adapt a real-world course into booc.io, and perform introductory qualitative evaluation with students.

5. Pedagogical Representations to Teach Linear Relations in Chinese and U.S. Classrooms: Parallel or Hierarchical?

ERIC Educational Resources Information Center

Huang, Rongjin; Cai, Jinfa

2011-01-01

This study investigates Chinese and U.S. teachers' construction and use of pedagogical representations surrounding implementation of mathematical tasks. It does this by analyzing video-taped lessons from the Learner's Perspective Study, involving 15 Chinese and 10 U.S. consecutive lessons on the topic of linear equations/linear relations. We…

6. Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models.

PubMed

Felleki, M; Lee, D; Lee, Y; Gilmour, A R; Rönnegård, L

2012-12-01

The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being -0·52 for IRWLS and -0·62 in Sorensen & Waagepetersen (2003).

7. Hierarchical Linear Modeling Analyses of NEO-PI-R Scales In the Baltimore Longitudinal Study of Aging

PubMed Central

Terracciano, Antonio; McCrae, Robert R.; Brant, Larry J.; Costa, Paul T.

2009-01-01

We examined age trends in the five factors and 30 facets assessed by the Revised NEO Personality Inventory in Baltimore Longitudinal Study of Aging data (N = 1,944; 5,027 assessments) collected between 1989 and 2004. Consistent with cross-sectional results, Hierarchical Linear Modeling analyses showed gradual personality changes in adulthood: a decline up to age 80 in Neuroticism, stability and then decline in Extraversion, decline in Openness, increase in Agreeableness, and increase up to age 70 in Conscientiousness. Some facets showed different curves from the factor they define. Birth cohort effects were modest, and there were no consistent Gender × Age interactions. Significant non-normative changes were found for all five factors; they were not explained by attrition but might be due to genetic factors, disease, or life experience. PMID:16248708

8. The effect of maternal psychopathology on parent-child agreement of child anxiety symptoms: A hierarchical linear modeling approach.

PubMed

Affrunti, Nicholas W; Woodruff-Borden, Janet

2015-05-01

The current study examined the effects of maternal anxiety, worry, depression, child age and gender on mother and child reports of child anxiety using hierarchical linear modeling. Participants were 73 mother-child dyads with children between the ages of 7 and 10 years. Reports of child anxiety symptoms, including symptoms of specific disorders (e.g., social phobia) were obtained using concordant versions of the Screen for Anxiety and Related Emotional Disorders (SCARED). Children reported significantly higher levels of anxiety symptoms relative to their mothers. Maternal worry and depression predicted for significantly lower levels of maternal-reported child anxiety and increasing discrepant reports. Maternal anxiety predicted for higher levels of maternal-reported child anxiety and decreasing discrepant reports. Maternal depression was associated with increased child-reported child anxiety symptoms. No significant effect of child age or gender was observed. Findings may inform inconsistencies in previous studies on reporter discrepancies. Implications and future directions are discussed.

9. Remarks on Hierarchic Control for a Linearized Micropolar Fluids System in Moving Domains

SciTech Connect

Jesus, Isaías Pereira de

2015-12-15

We study a Stackelberg strategy subject to the evolutionary linearized micropolar fluids equations in domains with moving boundaries, considering a Nash multi-objective equilibrium (non necessarily cooperative) for the “follower players” (as is called in the economy field) and an optimal problem for the leader player with approximate controllability objective. We will obtain the following main results: the existence and uniqueness of Nash equilibrium and its characterization, the approximate controllability of the linearized micropolar system with respect to the leader control and the existence and uniqueness of the Stackelberg–Nash problem, where the optimality system for the leader is given.

10. Use of Hierarchical Linear Modeling and Curriculum-Based Measurement for Assessing Academic Growth and Instructional Factors for Students with Learning Difficulties

ERIC Educational Resources Information Center

Shin, Jongho; Espin, Christine A.; Deno, Stanley L.; McConnell, Scott

2004-01-01

The main purpose of this paper is to demonstrate how to apply the Hierarchical Linear Modeling (HLM) technique to multi-wave Curriculum-Based Measurement (CBM) measures in modeling academic growth and assessing its relations to student-and instruction-related variables. HLM has advantages over other statistical methods (e.g., repeated measures…

11. The Asian clam Corbicula fluminea as a biomonitor of trace element contamination: Accounting for different sources of variation using an hierarchical linear model

USGS Publications Warehouse

Shoults-Wilson, W. A.; Peterson, J.T.; Unrine, J.M.; Rickard, J.; Black, M.C.

2009-01-01

In the present study, specimens of the invasive clam, Corbicula fluminea, were collected above and below possible sources of potentially toxic trace elements (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the Altamaha River system (Georgia, USA). Bioaccumulation of these elements was quantified, along with environmental (water and sediment) concentrations. Hierarchical linear models were used to account for variability in tissue concentrations related to environmental (site water chemistry and sediment characteristics) and individual (growth metrics) variables while identifying the strongest relations between these variables and trace element accumulation. The present study found significantly elevated concentrations of Cd, Cu, and Hg downstream of the outfall of kaolin-processing facilities, Zn downstream of a tire cording facility, and Cr downstream of both a nuclear power plant and a paper pulp mill. Models of the present study indicated that variation in trace element accumulation was linked to distance upstream from the estuary, dissolved oxygen, percentage of silt and clay in the sediment, elemental concentrations in sediment, shell length, and bivalve condition index. By explicitly modeling environmental variability, the Hierarchical linear modeling procedure allowed the identification of sites showing increased accumulation of trace elements that may have been caused by human activity. Hierarchical linear modeling is a useful tool for accounting for environmental and individual sources of variation in bioaccumulation studies. ?? 2009 SETAC.

12. A Bayesian Hierarchical Non-Linear Regression Model in Receiver Operating Characteristic Analysis of Clustered Continuous Diagnostic Data

PubMed Central

Zou, Kelly H.; O’Malley, A. James

2005-01-01

Receiver operating characteristic (ROC) analysis is a useful evaluative method of diagnostic accuracy. A Bayesian hierarchical nonlinear regression model for ROC analysis was developed. A validation analysis of diagnostic accuracy was conducted using prospective multi-center clinical trial prostate cancer biopsy data collected from three participating centers. The gold standard was based on radical prostatectomy to determine local and advanced disease. To evaluate the diagnostic performance of PSA level at fixed levels of Gleason score, a normality transformation was applied to the outcome data. A hierarchical regression analysis incorporating the effects of cluster (clinical center) and cancer risk (low, intermediate, and high) was performed, and the area under the ROC curve (AUC) was estimated. PMID:16161801

13. Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra

Hine, N. D. M.; Haynes, P. D.; Mostofi, A. A.; Payne, M. C.

2010-09-01

We present calculations of formation energies of defects in an ionic solid (Al2O3) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

14. Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

PubMed

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

15. Hierarchical transformation of Hamiltonians with linear and quadratic couplings for nonadiabatic quantum dynamics: application to the ππ∗∕nπ∗ internal conversion in thymine.

PubMed

Picconi, David; Lami, Alessandro; Santoro, Fabrizio

2012-06-28

We face with the general problem of defining a reduced number of effective collective coordinates to describe accurately the short-time nonadiabatic dynamics of large semirigid systems, amenable to a description in terms of coupled harmonic potential energy surfaces. We present a numeric iterative protocol to define a hierarchical representation of the Hamiltonian taking into account both linear and quadratic intra- and inter-state couplings (QVC, quadratic vibronic coupling model), thus generalizing the method introduced recently in the literature [E. Gindensperger, H. Köppel, and L. S. Cederbaum, J. Chem. Phys. 126, 034106 (2007)] for the linear vibronic coupling (LVC) model. This improvement allows to take into account the effect of harmonic frequency changes and Duschinsky mixings among the different electronic states, providing a route to upgrade the models for nonadiabatic harmonic systems to those nowadays routinely used for the simulation of vibronic spectra of adiabatic systems (negligible nonadiabatic couplings). We apply our method to the study of ππ∗ → nπ∗ internal conversion in thymine, analysing the differences in LVC and QVC predictions both for the absorption spectrum and the dynamics of electronic populations.

16. A multilevel excess hazard model to estimate net survival on hierarchical data allowing for non-linear and non-proportional effects of covariates.

PubMed

Charvat, Hadrien; Remontet, Laurent; Bossard, Nadine; Roche, Laurent; Dejardin, Olivier; Rachet, Bernard; Launoy, Guy; Belot, Aurélien

2016-08-15

The excess hazard regression model is an approach developed for the analysis of cancer registry data to estimate net survival, that is, the survival of cancer patients that would be observed if cancer was the only cause of death. Cancer registry data typically possess a hierarchical structure: individuals from the same geographical unit share common characteristics such as proximity to a large hospital that may influence access to and quality of health care, so that their survival times might be correlated. As a consequence, correct statistical inference regarding the estimation of net survival and the effect of covariates should take this hierarchical structure into account. It becomes particularly important as many studies in cancer epidemiology aim at studying the effect on the excess mortality hazard of variables, such as deprivation indexes, often available only at the ecological level rather than at the individual level. We developed here an approach to fit a flexible excess hazard model including a random effect to describe the unobserved heterogeneity existing between different clusters of individuals, and with the possibility to estimate non-linear and time-dependent effects of covariates. We demonstrated the overall good performance of the proposed approach in a simulation study that assessed the impact on parameter estimates of the number of clusters, their size and their level of unbalance. We then used this multilevel model to describe the effect of a deprivation index defined at the geographical level on the excess mortality hazard of patients diagnosed with cancer of the oral cavity. Copyright © 2016 John Wiley & Sons, Ltd.

SciTech Connect

Carter, M.

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.

18. Understanding uncertainties in non-linear population trajectories: a Bayesian semi-parametric hierarchical approach to large-scale surveys of coral cover.

PubMed

Vercelloni, Julie; Caley, M Julian; Kayal, Mohsen; Low-Choy, Samantha; Mengersen, Kerrie

2014-01-01

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.

19. Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

PubMed Central

Vercelloni, Julie; Caley, M. Julian; Kayal, Mohsen; Low-Choy, Samantha; Mengersen, Kerrie

2014-01-01

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making. PMID:25364915

20. Measuring School Effectiveness Using Hierarchical Linear Models.

ERIC Educational Resources Information Center

Mandeville, Garrett K.; Heidari, Khosrow

Two major groups of researchers focus on identifying schools that have been unusually effective in terms of their students' achievement: (1) "effective schools" researchers; and (2) those charged with the responsibility of identifying schools for special recognition. However, all legitimate attemps to operationalize school effectiveness…

1. Hierarchical Multiagent Reinforcement Learning

DTIC Science & Technology

2004-01-25

In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

2. Bayesian Hierarchical Classes Analysis

ERIC Educational Resources Information Center

Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn

2008-01-01

Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…

3. Ultrametric Hierarchical Clustering Algorithms.

ERIC Educational Resources Information Center

Milligan, Glenn W.

1979-01-01

Johnson has shown that the single linkage and complete linkage hierarchical clustering algorithms induce a metric on the data known as the ultrametric. Johnson's proof is extended to four other common clustering algorithms. Two additional methods also produce hierarchical structures which can violate the ultrametric inequality. (Author/CTM)

4. Hierarchical Auxetic Mechanical Metamaterials

Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

2015-02-01

Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

5. Hierarchical Approximate Bayesian Computation

PubMed Central

Turner, Brandon M.; Van Zandt, Trisha

2013-01-01

Approximate Bayesian computation (ABC) is a powerful technique for estimating the posterior distribution of a model’s parameters. It is especially important when the model to be fit has no explicit likelihood function, which happens for computational (or simulation-based) models such as those that are popular in cognitive neuroscience and other areas in psychology. However, ABC is usually applied only to models with few parameters. Extending ABC to hierarchical models has been difficult because high-dimensional hierarchical models add computational complexity that conventional ABC cannot accommodate. In this paper we summarize some current approaches for performing hierarchical ABC and introduce a new algorithm called Gibbs ABC. This new algorithm incorporates well-known Bayesian techniques to improve the accuracy and efficiency of the ABC approach for estimation of hierarchical models. We then use the Gibbs ABC algorithm to estimate the parameters of two models of signal detection, one with and one without a tractable likelihood function. PMID:24297436

6. Perception and Hierarchical Dynamics

PubMed Central

Kiebel, Stefan J.; Daunizeau, Jean; Friston, Karl J.

2009-01-01

In this paper, we suggest that perception could be modeled by assuming that sensory input is generated by a hierarchy of attractors in a dynamic system. We describe a mathematical model which exploits the temporal structure of rapid sensory dynamics to track the slower trajectories of their underlying causes. This model establishes a proof of concept that slowly changing neuronal states can encode the trajectories of faster sensory signals. We link this hierarchical account to recent developments in the perception of human action; in particular artificial speech recognition. We argue that these hierarchical models of dynamical systems are a plausible starting point to develop robust recognition schemes, because they capture critical temporal dependencies induced by deep hierarchical structure. We conclude by suggesting that a fruitful computational neuroscience approach may emerge from modeling perception as non-autonomous recognition dynamics enslaved by autonomous hierarchical dynamics in the sensorium. PMID:19649171

7. Hierarchical Auxetic Mechanical Metamaterials

PubMed Central

Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

2015-01-01

Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts. PMID:25670400

8. Hierarchical auxetic mechanical metamaterials.

PubMed

Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

2015-02-11

Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

SciTech Connect

Raju, G.V.S.; Jun Zhou

1993-07-01

A methodology for designing adaptive hierarchical fuzzy controllers is presented. In order to evaluate this concept, several suitable performance indices were developed and converted to linguistic fuzzy variables. Based on those variables, a supervisory fuzzy rule set was constructed and used to change the parameters of a hierarchical fuzzy controller to accommodate the variations of system parameters. The proposed algorithm was used in feedwater flow control to a steam generator. Simulation studies are presented that illustrate the effectiveness of the approach

10. Quantum transport through hierarchical structures.

PubMed

Boettcher, S; Varghese, C; Novotny, M A

2011-04-01

The transport of quantum electrons through hierarchical lattices is of interest because such lattices have some properties of both regular lattices and random systems. We calculate the electron transmission as a function of energy in the tight-binding approximation for two related Hanoi networks. HN3 is a Hanoi network with every site having three bonds. HN5 has additional bonds added to HN3 to make the average number of bonds per site equal to five. We present a renormalization group approach to solve the matrix equation involved in this quantum transport calculation. We observe band gaps in HN3, while no such band gaps are observed in linear networks or in HN5. We provide a detailed scaling analysis near the edges of these band gaps.

11. Hierarchical Porous Structures

SciTech Connect

Grote, Christopher John

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. Microparticles with hierarchical porosity

DOEpatents

Petsev, Dimiter N; Atanassov, Plamen; Pylypenko, Svitlana; Carroll, Nick; Olson, Tim

2012-12-18

The present disclosure provides oxide microparticles with engineered hierarchical porosity and methods of manufacturing the same. Also described are structures that are formed by templating, impregnating, and/or precipitating the oxide microparticles and method for forming the same. Suitable applications include catalysts, electrocatalysts, electrocatalysts support materials, capacitors, drug delivery systems, sensors and chromatography.

13. Hierarchical manifold learning.

PubMed

Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

2012-01-01

We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

14. Hierarchical Pattern Classifier

NASA Technical Reports Server (NTRS)

Yates, Gigi L.; Eberlein, Susan J.

1992-01-01

Hierarchical pattern classifier reduces number of comparisons between input and memory vectors without reducing detail of final classification by dividing classification process into coarse-to-fine hierarchy that comprises first "grouping" step and second classification step. Three-layer neural network reduces computation further by reducing number of vector dimensions in processing. Concept applicable to pattern-classification problems with need to reduce amount of computation necessary to classify, identify, or match patterns to desired degree of resolution.

15. HDS: Hierarchical Data System

Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

2015-02-01

The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

16. A hierarchical model for estimating change in American Woodcock populations

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.; Kendall, W.L.; Kelley, J.R.; Niven, D.K.

2008-01-01

The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model?based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = -0.9%/yr, 95% credible interval: -1.2, -0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.

17. Hierarchical Safety Cases

NASA Technical Reports Server (NTRS)

Denney, Ewen W.; Whiteside, Iain J.

2012-01-01

We introduce hierarchical safety cases (or hicases) as a technique to overcome some of the difficulties that arise creating and maintaining industrial-size safety cases. Our approach extends the existing Goal Structuring Notation with abstraction structures, which allow the safety case to be viewed at different levels of detail. We motivate hicases and give a mathematical account of them as well as an intuition, relating them to other related concepts. We give a second definition which corresponds closely to our implementation of hicases in the AdvoCATE Assurance Case Editor and prove the correspondence between the two. Finally, we suggest areas of future enhancement, both theoretically and practically.

18. Efficient scalable algorithms for hierarchically semiseparable matrices

SciTech Connect

Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de

2011-09-14

Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.

19. Hierarchical Bayesian model updating for structural identification

Behmanesh, Iman; Moaveni, Babak; Lombaert, Geert; Papadimitriou, Costas

2015-12-01

A new probabilistic finite element (FE) model updating technique based on Hierarchical Bayesian modeling is proposed for identification of civil structural systems under changing ambient/environmental conditions. The performance of the proposed technique is investigated for (1) uncertainty quantification of model updating parameters, and (2) probabilistic damage identification of the structural systems. Accurate estimation of the uncertainty in modeling parameters such as mass or stiffness is a challenging task. Several Bayesian model updating frameworks have been proposed in the literature that can successfully provide the "parameter estimation uncertainty" of model parameters with the assumption that there is no underlying inherent variability in the updating parameters. However, this assumption may not be valid for civil structures where structural mass and stiffness have inherent variability due to different sources of uncertainty such as changing ambient temperature, temperature gradient, wind speed, and traffic loads. Hierarchical Bayesian model updating is capable of predicting the overall uncertainty/variability of updating parameters by assuming time-variability of the underlying linear system. A general solution based on Gibbs Sampler is proposed to estimate the joint probability distributions of the updating parameters. The performance of the proposed Hierarchical approach is evaluated numerically for uncertainty quantification and damage identification of a 3-story shear building model. Effects of modeling errors and incomplete modal data are considered in the numerical study.

20. Improving Measurement Precision of Hierarchical Latent Traits Using Adaptive Testing

ERIC Educational Resources Information Center

Wang, Chun

2014-01-01

Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order factors directly govern the actual item responses.…

1. How hierarchical is language use?

PubMed

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

2012-11-22

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.

2. How hierarchical is language use?

PubMed Central

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

3. Hierarchical partial order ranking.

PubMed

Carlsen, Lars

2008-09-01

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 prioritization of polluted sites is given.

4. Associative Hierarchical Random Fields.

PubMed

Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

2014-06-01

This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

5. Onboard hierarchical network

Tunesi, Luca; Armbruster, Philippe

2004-02-01

6. Relevance of the Hierarchical Linear Model to TIMSS Data Analyses.

ERIC Educational Resources Information Center

Wang, Jianjun

Multilevel international data have been released from the Third International Mathematics and Science Study (TIMSS), providing an opportunity to apply multilevel modeling techniques in educational research. In this paper, TIMSS factors are classified in fixed and random categories according to the project design. Classifying fixed and random…

7. Item Response Theory Using Hierarchical Generalized Linear Models

ERIC Educational Resources Information Center

Ravand, Hamdollah

2015-01-01

Multilevel models (MLMs) are flexible in that they can be employed to obtain item and person parameters, test for differential item functioning (DIF) and capture both local item and person dependence. Papers on the MLM analysis of item response data have focused mostly on theoretical issues where applications have been add-ons to simulation…

8. Using Hierarchical Linear Modeling for Proformative Evaluation: A Case Example

ERIC Educational Resources Information Center

Coryn, Chris L. S.

2007-01-01

Proformative evaluation--first introduced in Scriven's (2006) "The great enigma: An evaluation design puzzle"--"is motivated, like formative evaluation, by the intention to improve something that is still developing, but unlike formative, the improvement is only possible by taking action, hence proactive instead of reactive, hence both, hence…

9. Direct hierarchical assembly of nanoparticles

DOEpatents

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.

10. Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey

USGS Publications Warehouse

Sauer, John R.; Zimmerman, Guthrie S.; Klimstra, Jon D.; Link, William A.

2014-01-01

We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic

USGS Publications Warehouse

Royle, Andy

2016-01-01

In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

12. Genetic segregation analyses of serum IgG2 levels.

PubMed Central

Marazita, M. L.; Lu, H.; Cooper, M. E.; Quinn, S. M.; Zhang, J.; Burmeister, J. A.; Califano, J. V.; Pandey, J. P.; Schenkein, H. A.; Tew, J. G.

1996-01-01

Summary : The aim of this study was to determine whether there was evidence for a genetic component in the immune response as measured by IgG2 levels. The study was motivated by our studies of early-onset periodontitis (EOP), a group of disorders characterized by rapid destruction of the supporting tissues of the teeth in otherwise healthy individuals. EOP has two subforms, localized juvenile periodontitis (LJP) and a generalized form (G-EOP). IgG2 levels are elevated in LJP but not G-EOP individuals; and African-American IgG2 levels are higher than Caucasian levels regardless of EOP status. IgG2 levels were determined in 123 EOP families and in 508 unrelated non-EOP control individuals. Segregation analysis under the regressive model approach of Bonney was used to analyze IgG2 levels for evidence of major locus segregation. After adjusting for LJP status, race, sex, and age, the best fitting model was an autosomal codominant major locus model (accounting for approximately 62% of the variance in IgG2), plus residual parent/offspring and spousal correlations. Smoking and GM23 are also known to affect IgG2 levels. If additional adjustments are made for smoking and GM23, the best-fitting model is still a codominant major locus but with no significant residual correlations. PMID:8651265

13. Linear Text vs. Non-Linear Hypertext in Handheld Computers: Effects on Declarative and Structural Knowledge, and Learner Motivation

ERIC Educational Resources Information Center

Son, Chanhee; Park, Sanghoon; Kim, Minjeong

2011-01-01

This study compared linear text-based and non-linear hypertext-based instruction in a handheld computer regarding effects on two different levels of knowledge (declarative and structural knowledge) and learner motivation. Forty four participants were randomly assigned to one of three experimental conditions: linear text, hierarchical hypertext,…

14. Linear Accelerators

Sidorin, Anatoly

2010-01-01

In linear accelerators the particles are accelerated by either electrostatic fields or oscillating Radio Frequency (RF) fields. Accordingly the linear accelerators are divided in three large groups: electrostatic, induction and RF accelerators. Overview of the different types of accelerators is given. Stability of longitudinal and transverse motion in the RF linear accelerators is briefly discussed. The methods of beam focusing in linacs are described.

15. Hierarchical Microaggressions in Higher Education

ERIC Educational Resources Information Center

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…

16. Sensory Hierarchical Organization and Reading.

ERIC Educational Resources Information Center

Skapof, Jerome

The purpose of this study was to judge the viability of an operational approach aimed at assessing response styles in reading using the hypothesis of sensory hierarchical organization. A sample of 103 middle-class children from a New York City public school, between the ages of five and seven, took part in a three phase experiment. Phase one…

17. Image Information Mining Utilizing Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai

2002-01-01

The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

18. Extended Generalized Linear Latent and Mixed Model

ERIC Educational Resources Information Center

Segawa, Eisuke; Emery, Sherry; Curry, Susan J.

2008-01-01

The generalized linear latent and mixed modeling (GLLAMM framework) includes many models such as hierarchical and structural equation models. However, GLLAMM cannot currently accommodate some models because it does not allow some parameters to be random. GLLAMM is extended to overcome the limitation by adding a submodel that specifies a…

19. Parallel hierarchical method in networks

Malinochka, Olha; Tymchenko, Leonid

2007-09-01

This method of parallel-hierarchical Q-transformation offers new approach to the creation of computing medium - of parallel -hierarchical (PH) networks, being investigated in the form of model of neurolike scheme of data processing [1-5]. The approach has a number of advantages as compared with other methods of formation of neurolike media (for example, already known methods of formation of artificial neural networks). The main advantage of the approach is the usage of multilevel parallel interaction dynamics of information signals at different hierarchy levels of computer networks, that enables to use such known natural features of computations organization as: topographic nature of mapping, simultaneity (parallelism) of signals operation, inlaid cortex, structure, rough hierarchy of the cortex, spatially correlated in time mechanism of perception and training [5].

20. Hierarchical Theme and Topic Modeling.

PubMed

Chien, Jen-Tzung

2016-03-01

Considering the hierarchical data groupings in text corpus, e.g., words, sentences, and documents, we conduct the structural learning and infer the latent themes and topics for sentences and words from a collection of documents, respectively. The relation between themes and topics under different data groupings is explored through an unsupervised procedure without limiting the number of clusters. A tree stick-breaking process is presented to draw theme proportions for different sentences. We build a hierarchical theme and topic model, which flexibly represents the heterogeneous documents using Bayesian nonparametrics. Thematic sentences and topical words are extracted. In the experiments, the proposed method is evaluated to be effective to build semantic tree structure for sentences and the corresponding words. The superiority of using tree model for selection of expressive sentences for document summarization is illustrated.

1. Hierarchical structure of biological systems

PubMed Central

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

2. Multicast Routing of Hierarchical Data

NASA Technical Reports Server (NTRS)

Shacham, Nachum

1992-01-01

The issue of multicast of broadband, real-time data in a heterogeneous environment, in which the data recipients differ in their reception abilities, is considered. Traditional multicast schemes, which are designed to deliver all the source data to all recipients, offer limited performance in such an environment, since they must either force the source to overcompress its signal or restrict the destination population to those who can receive the full signal. We present an approach for resolving this issue by combining hierarchical source coding techniques, which allow recipients to trade off reception bandwidth for signal quality, and sophisticated routing algorithms that deliver to each destination the maximum possible signal quality. The field of hierarchical coding is briefly surveyed and new multicast routing algorithms are presented. The algorithms are compared in terms of network utilization efficiency, lengths of paths, and the required mechanisms for forwarding packets on the resulting paths.

3. Hierarchical Molecular Modelling with Ellipsoids

SciTech Connect

Max, N

2004-03-29

Protein and DNA structures are represented at varying levels of details using ellipsoidal RGBA textured splats. The splat texture at each level is generated by rendering its children in a hierarchical model, from a distribution of viewing directions, and averaging the result. For rendering, the ellipsoids to be used are chosen adaptively, depending on the distance to the viewpoint. This technique is applied to visualize DNA coiling around nucleosomes in chromosomes.

4. Plasma matrix metalloproteinase 2 levels and breast cancer risk.

PubMed

Aroner, Sarah A; Rosner, Bernard A; Tamimi, Rulla M; Tworoger, Shelley S; Baur, Nadja; Joos, Thomas O; Hankinson, Susan E

2015-06-01

Matrix metalloproteinase 2 (MMP2) is an enzyme with important functions in breast cancer invasion and metastasis. However, it is unclear whether circulating MMP2 levels may predict breast cancer risk. We conducted a prospective nested case-control analysis in the Nurses' Health Study among 1136 cases who were diagnosed with invasive breast cancer between 1992 and 2004 and 1136 matched controls. All participants provided blood samples in 1989-1990, and a subset (170 cases, 170 controls) contributed an additional sample in 2000-2002. Pre-diagnostic plasma MMP2 levels were measured via immunoassay, and conditional logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs), adjusted for breast cancer risk factors. No association was observed between plasma MMP2 levels and risk of total invasive breast cancer (top vs. bottom quartile, OR=1.0; 95% CI: 0.7, 1.2; p-trend=0.89). Findings did not vary significantly by time since blood draw, body mass index, postmenopausal hormone use, or menopausal status at either blood draw or breast cancer diagnosis. MMP2 was associated with a greater risk of nodal metastases at diagnosis (top vs. bottom quartile, OR=1.5; 95% CI: 1.0, 2.2; p-heterogeneity, any vs. no lymph nodes=0.002), but no significant associations were observed with other tumor characteristics or with recurrent or fatal cancers. Plasma MMP2 levels do not appear to be predictive of total invasive breast cancer risk, although associations with aggressive disease warrant further study.

5. Treatment Protocols as Hierarchical Structures

PubMed Central

Ben-Bassat, Moshe; Carlson, Richard W.; Puri, Vinod K.; Weil, Max Harry

1978-01-01

We view a treatment protocol as a hierarchical structure of therapeutic modules. The lowest level of this structure consists of individual therapeutic actions. Combinations of individual actions define higher level modules, which we call routines. Routines are designed to manage limited clinical problems, such as the routine for fluid loading to correct hypovolemia. Combinations of routines and additional actions, together with comments, questions, or precautions organized in a branching logic, in turn, define the treatment protocol for a given disorder. Adoption of this modular approach may facilitate the formulation of treatment protocols, since the physician is not required to prepare complex flowcharts. This hierarchical approach also allows protocols to be updated and modified in a flexible manner. By use of such a standard format, individual components may be fitted together to create protocols for multiple disorders. The technique is suited for computer implementation. We believe that this hierarchical approach may facilitate standarization of patient care as well as aid in clinical teaching. A protocol for acute pancreatitis is used to illustrate this technique.

6. Personality Traits: Hierarchically Organized Systems.

PubMed

Fajkowska, Małgorzata

2017-03-13

Personality science has always been and is still ready for new theorizing on traits. Accordingly, this paper presents the recently proposed Traits as Hierarchical Systems (THS) model, where personality traits are not only the emergent properties of the three-level hierarchy of the personality system, but are also hierarchical per se. As hierarchical systems, they are organized into three levels: mechanisms and processes, structures, and behavioral markers. In this approach trait denotes the underlying, recurrent mechanisms that pattern its structure and account for the stability/variability of individual characteristics. Here, traits might be described as processes with a slow rate of change that can be substituted for structure. The main function of personality traits, within the personality system, is stimulation processing. Three dominant functions of stimulation processing in traits are proposed: reactive, regulative, and self-regulative. Some important questions regarding the concept of trait remain, e.g. concerning trait stability, determinacy, measurement, their relation to overt behaviors, personality type or state, differentiation between temperament traits and other-than-temperament personality traits. All of these topics are discussed in this paper, as well as the compatible and distinctive features of this approach in relation to selected, modern trait theories. This article is protected by copyright. All rights reserved.

7. Constraining PCO2 Levels in the Early-Middle Paleogene

Shellito, L. J.; Sloan, L. C.; Huber, M.

2001-12-01

Inconsistencies among paleo-pCO2 estimates have added considerable difficulty to the reconstruction of past climates. This study uses the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) with a slab ocean and Eocene geography in an attempt to constrain atmospheric pCO2 levels during the early-middle Paleogene (50-60 Ma), a time period which proxy records suggest was the warmest of the Cenozoic. We test the sensitivity of the modeled climate to three levels of CO2: 500, 1000, and 2000 ppm. Our results strongly suggest that a high CO2 level (1000-2000 ppm) was more likely for the late Paleocene and early Eocene than a low CO2 level (500 ppm). With increasing CO2, the greatest warming occurs at wintertime polar and high latitude continental regions. Wintertime northern hemispheric polar temperatures are ~20 degrees C warmer in the 2000 ppm case than in the 500 ppm case, while tropical temperatures are only 3-4 degrees C warmer in the 2000 ppm case. The 2000 ppm scenario is the only case to produce mean annual and cold month mean temperatures at mid-latitudes and high latitude coastal regions that would be tolerable for early Eocene flora.

8. LINEAR ACCELERATOR

DOEpatents

Christofilos, N.C.; Polk, I.J.

1959-02-17

Improvements in linear particle accelerators are described. A drift tube system for a linear ion accelerator reduces gap capacity between adjacent drift tube ends. This is accomplished by reducing the ratio of the diameter of the drift tube to the diameter of the resonant cavity. Concentration of magnetic field intensity at the longitudinal midpoint of the external sunface of each drift tube is reduced by increasing the external drift tube diameter at the longitudinal center region.

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

PubMed Central

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

10. Hierarchical flexural strength of enamel: transition from brittle to damage-tolerant behaviour.

PubMed

Bechtle, Sabine; Özcoban, Hüseyin; Lilleodden, Erica T; Huber, Norbert; Schreyer, Andreas; Swain, Michael V; Schneider, Gerold A

2012-06-07

Hard, biological materials are generally hierarchically structured from the nano- to the macro-scale in a somewhat self-similar manner consisting of mineral units surrounded by a soft protein shell. Considerable efforts are underway to mimic such materials because of their structurally optimized mechanical functionality of being hard and stiff as well as damage-tolerant. However, it is unclear how different hierarchical levels interact to achieve this performance. In this study, we consider dental enamel as a representative, biological hierarchical structure and determine its flexural strength and elastic modulus at three levels of hierarchy using focused ion beam (FIB) prepared cantilevers of micrometre size. The results are compared and analysed using a theoretical model proposed by Jäger and Fratzl and developed by Gao and co-workers. Both properties decrease with increasing hierarchical dimension along with a switch in mechanical behaviour from linear-elastic to elastic-inelastic. We found Gao's model matched the results very well.

11. Higher minor hemoglobin A2 levels in multiple sclerosis patients correlate with lesser disease severity

PubMed Central

Ozcan, Muhammed Emin; Ince, Bahri; Karadeli, Hasan Huseyin; Gedikbasi, Asuman; Asil, Talip; Altinoz, Meric A

2016-01-01

Objective To define whether minor adult hemoglobin A2 (HbA2, α2δ2) exerts any protective activity in multiple sclerosis (MS). Methods HbA2 levels were measured in 146 MS patients with high performance liquid chromatography and association with MS Severity Scores (MSSS) were determined. HbA2 associations with blood count parameters were also studied using blood counts evaluated on the same day of high performance liquid chromatography sampling. Routine biochemical parameters were also determined to rule out elusively influential factors, such as anemia and thyroid disorders. Results HbA2 levels negatively correlated with MSSS (Spearman correlation, R: −0.186, P=0.025). Exclusion of confounding factors with a generalized linear model revealed an even stronger negative correlation between HbA2 and MSSS (P<0.001). HbA2 positively correlated with red blood cells (RBCs) (R=0.350, P<0.001) and in turn, RBCs negatively correlated with MSSS (R=−0.180, P=0.031). Average HbA2 levels were highest among patients treated with interferon β1a. Conclusion RBC fragility is increased in MS, and recent data suggest that circulating free Hb contributes to neural injury in MS. HbA2 and its oxidative denaturation product hemichrome A2 enhance RBC membrane stability to a greater extent than do major HbA or hemichrome A. Reductions in ischemic cerebrovascular vascular events are reported in β-thalassemia carriers and HbA2 levels are considerably higher in this population. Episodic declines of cerebral blood flow were shown in bipolar disorder, and we have recently shown a protective role of HbA2 against postpartum episodes in females with bipolar disorder. HbA2’s erythroprotective functions may reduce free Hb and long-term neural injury in MS. PMID:27578976

12. Some physical applications of random hierarchical matrices

SciTech Connect

Avetisov, V. A.; Bikulov, A. Kh.; Vasilyev, O. A.; Nechaev, S. K.; Chertovich, A. V.

2009-09-15

The investigation of spectral properties of random block-hierarchical matrices as applied to dynamic and structural characteristics of complex hierarchical systems with disorder is proposed for the first time. Peculiarities of dynamics on random ultrametric energy landscapes are discussed and the statistical properties of scale-free and polyscale (depending on the topological characteristics under investigation) random hierarchical networks (graphs) obtained by multiple mapping are considered.

13. Hierarchical flux-based thermal-structural finite element analysis method

NASA Technical Reports Server (NTRS)

Polesky, Sandra P.

1992-01-01

A hierarchical flux-based finite element method is developed for both a one and two dimensional thermal structural analyses. Derivation of the finite element equations is presented. The resulting finite element matrices associated with the flux based formulation are evaluated in a closed form. The hierarchical finite elements include additional degrees of freedom in the approximation of the element variable distributions by the use of nodeless variables. The nodeless variables offer increased solution accuracy without the need for defining actual nodes and rediscretizing the finite element model. Thermal and structural responses are obtained from a conventional linear finite element method and exact solutions. Results show that the hierarchical flux-based method can provide improved thermal and structural solution accuracy with fewer elements when compared to results for the conventional linear element method.

14. Relating indoor NO 2 levels to infant personal exposures

Harlos, David P.; Marbury, Marian; Samet, Jonathan; Spengler, John D.

We report here the results of a field survey of personal nitrogen dioxide exposure (PNO 2) of infants and simultaneous indoor NO 2 levels from various points throughout the infants' homes. Personal nitrogen dioxide levels can be predicted by average room NO 2 concentrations when appropriately weighted by infant presence in the room. Bedroom NO 2 concentration alone presents an alternative predictor which is more suitable for use in large scale surveys. Because of the typical infant's peculiar time-location patterns, they receive most of their NO 2 exposures in bedrooms (65 %)and living rooms (32 %), while the kitchen (5 %) and outdoor environments (> 2%)contribute only a small fraction of daily exposure. Average NO 2 exposure during cooking periods can be predicted using passive samplers placed directly over stoves and hours of stove use time.

15. Drawing the future: Stomatal response to CO(2) levels.

PubMed

Serna, Laura

2008-04-01

Gas exchange between the plant and the atmosphere is regulated by controlling both the stomatal density and the aperture of the stomatal pore. Environmental factors such as light, the level of atmospheric CO(2) and hormones regulate stomatal development and/or function. Because atmospheric CO(2) levels have been rising since the Industrial Revolution, and it is predicted that they will continue doing so in the future, an understanding of the CO(2) signalling mechanisms in the stomatal responses will help to know how plants were in the past and will allow predicting how they will respond to climate change in the near future. This article covers the recent knowledge of the CO(2) signalling mechanisms that regulate both stomatal function and development.

16. Hierarchical organization of a reference system in newborn spontaneous movements.

PubMed

Assmann, Birte; Romano, M Carmen; Thiel, Marco; Niemitz, Carsten

2007-12-01

In this paper, we studied spontaneous newborn movements regarding the coordination of the four limbs, arms and legs, from a dynamic perspective. We used the method of recurrence plots to analyse the kinematic data from audiovisual recordings of neonates. We identified temporal and spatial synchronization of the four limbs that resulted in high recurrence patterns of biomechanical reference configurations. Furthermore, we identified transitions between linear and nonlinear epochs in the movement behavior of newborns on different time scales by means of recurrence quantification analysis. Results are discussed in the context of the concept of a structural hierarchy, in which different time scales correspond to hierarchical levels of organization.

17. Hierarchical and multiple hand action representation using temporal postural synergies.

PubMed

Tessitore, G; Sinigaglia, C; Prevete, R

2013-03-01

The notion of synergy enables one to provide simplified descriptions of hand actions. It has been used in a number of different meanings ranging from kinematic and dynamic synergies to postural and temporal postural synergies. However, relatively little is known about how representing an action by synergies might take into account the possibility to have a hierarchical and multiple action representation. This is a key aspect for action representation as it has been characterized by action theorists and cognitive neuroscientists. Thus, the aim of the present paper is to investigate whether and to what extent a hierarchical and multiple action representation can be obtained by a synergy approach. To this purpose, we took advantage of representing hand action as a linear combination of temporal postural synergies (TPSs), but on the assumption that TPSs have a tree-structured organization. In a tree-structured organization, a hand action representation can involve a TPS only if the ancestors of the synergy in the tree are themselves involved in the action representation. The results showed that this organization is enough to force a multiple representation of hand actions in terms of synergies which are hierarchically organized.

PubMed

Zhao, Tiesong; Wang, Zhou; Chen, Chang Wen

2016-04-20

The state-of-the-art High Efficiency Video Coding (HEVC) standard adopts a hierarchical coding structure to improve its coding efficiency. This allows for the Quantization Parameter Cascading (QPC) scheme that assigns Quantization Parameters (Qps) to different hierarchical layers in order to further improve the Rate-Distortion (RD) performance. However, only static QPC schemes have been suggested in HEVC test model (HM), which are unable to fully explore the potentials of QPC. In this paper, we propose an adaptive QPC scheme for HEVC hierarchical structure to code natural video sequences characterized by diversified textures, motions and encoder configurations. We formulate the adaptive QPC scheme as a non-linear programming problem and solve it in a scientifically sound way with a manageable low computational overhead. The proposed model addresses a generic Qp assignment problem of video coding. Therefore, it also applies to Group-Of-Picture (GOP)- level, frame-level and Coding Unit (CU)-level Qp assignments. Comprehensive experiments have demonstrated the proposed QPC scheme is able to adapt quickly to different video contents and coding configurations while achieving noticeable RD performance enhancement over all static and adaptive QPC schemes under comparison as well as HEVC default frame-level rate control. We have also made valuable observations on the distributions of adaptive QPC sets in videos of different types of contents, which provide useful insights on how to further improve static QPC schemes.

PubMed

Zhao, Tiesong; Wang, Zhou; Chen, Chang Wen

2016-07-01

The state-of-the-art High Efficiency Video Coding (HEVC) standard adopts a hierarchical coding structure to improve its coding efficiency. This allows for the quantization parameter cascading (QPC) scheme that assigns quantization parameters (Qps) to different hierarchical layers in order to further improve the rate-distortion (RD) performance. However, only static QPC schemes have been suggested in HEVC test model, which are unable to fully explore the potentials of QPC. In this paper, we propose an adaptive QPC scheme for an HEVC hierarchical structure to code natural video sequences characterized by diversified textures, motions, and encoder configurations. We formulate the adaptive QPC scheme as a non-linear programming problem and solve it in a scientifically sound way with a manageable low computational overhead. The proposed model addresses a generic Qp assignment problem of video coding. Therefore, it also applies to group-of-picture-level, frame-level and coding unit-level Qp assignments. Comprehensive experiments have demonstrated that the proposed QPC scheme is able to adapt quickly to different video contents and coding configurations while achieving noticeable RD performance enhancement over all static and adaptive QPC schemes under comparison as well as HEVC default frame-level rate control. We have also made valuable observations on the distributions of adaptive QPC sets in the videos of different types of contents, which provide useful insights on how to further improve static QPC schemes.

20. Precise hierarchical self-assembly of multicompartment micelles.

PubMed

Gröschel, André H; Schacher, Felix H; Schmalz, Holger; Borisov, Oleg V; Zhulina, Ekaterina B; Walther, Andreas; Müller, Axel H E

2012-02-28

Hierarchical self-assembly offers elegant and energy-efficient bottom-up strategies for the structuring of complex materials. For block copolymers, the last decade witnessed great progress in diversifying the structural complexity of solution-based assemblies into multicompartment micelles. However, a general understanding of what governs multicompartment micelle morphologies and polydispersity, and how to manipulate their hierarchical superstructures using straightforward concepts and readily accessible polymers remains unreached. Here we demonstrate how to create homogeneous multicompartment micelles with unprecedented structural control via the intermediate pre-assembly of subunits. This directed self-assembly leads to a step-wise reduction of the degree of conformational freedom and dynamics and avoids undesirable kinetic obstacles during the structure build-up. It yields a general concept for homogeneous populations of well-defined multicompartment micelles with precisely tunable patchiness, while using simple linear ABC triblock terpolymers. We further demonstrate control over the hierarchical step-growth polymerization of multicompartment micelles into micron-scale segmented supracolloidal polymers as an example of programmable mesoscale colloidal hierarchies via well-defined patchy nanoobjects.

1. The Case for a Hierarchical Cosmology

ERIC Educational Resources Information Center

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)

2. Discursive Hierarchical Patterning in Economics Cases

ERIC Educational Resources Information Center

Lung, Jane

2011-01-01

This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

3. Genetic Network Inference Using Hierarchical Structure

PubMed Central

Kimura, Shuhei; Tokuhisa, Masato; Okada-Hatakeyama, Mariko

2016-01-01

Many methods for inferring genetic networks have been proposed, but the regulations they infer often include false-positives. Several researchers have attempted to reduce these erroneous regulations by proposing the use of a priori knowledge about the properties of genetic networks such as their sparseness, scale-free structure, and so on. This study focuses on another piece of a priori knowledge, namely, that biochemical networks exhibit hierarchical structures. Based on this idea, we propose an inference approach that uses the hierarchical structure in a target genetic network. To obtain a reasonable hierarchical structure, the first step of the proposed approach is to infer multiple genetic networks from the observed gene expression data. We take this step using an existing method that combines a genetic network inference method with a bootstrap method. The next step is to extract a hierarchical structure from the inferred networks that is consistent with most of the networks. Third, we use the hierarchical structure obtained to assign confidence values to all candidate regulations. Numerical experiments are also performed to demonstrate the effectiveness of using the hierarchical structure in the genetic network inference. The improvement accomplished by the use of the hierarchical structure is small. However, the hierarchical structure could be used to improve the performances of many existing inference methods. PMID:26941653

4. Sagittal spinopelvic parameters in 2-level lumbar degenerative spondylolisthesis

PubMed Central

Wang, Tao; Wang, Hui; Liu, Huan; Ma, Lei; Liu, Feng-Yu; Ding, Wen-Yuan

2016-01-01

Abstract The purpose of our study is to evaluate sagittal parameters in 2-level lumbar degenerative spondylolisthesis (DS) (TLDS). A total of 15 patients with TLDS, 40 patients with single-level DS (SLDS), and 30 normal volunteers as control were included in our study. All subjects performed on full spine X-ray. Two categorized data were analyzed: patient characteristics—age, sex, body mass index, radiographic parameters-pelvic incidence (PI), pelvic tilt (PT), lumbar lordosis (LL), sacral slope (SS), PI–LL, Cobb between the fifth thoracic vertebral and 12th thoracic vertebral (T5–T12), sagittal vertical axis (SVA) Cobb angle of spondylolisthesis level (CSL), ratio of PT to SS (PT/SS), CSL/LL, variation trend of SS over PI, and LL over PI. The PI (73.1° vs 52.9°), SS (50.8° vs 32.2°), LL (53.1° vs 46.9°), SVA (66.1 vs 22.0 mm), PI–LL (20.0° vs 6.0°), and CSL (23.6° vs 20.0°) in TLDS were significantly larger than these in SLDS. The PI (73.1° vs 40.6°), PT (22.3° vs 17.1°), SS (50.8° vs 23.5°), LL (53.1° vs 32.5°), PI–LL (20.0° vs 8.1°), and SVA (66.1 vs 17.0 mm) in TLDS were significantly larger than those in the normal group (NG). The PI (52.9° vs 40.6°), PT (21.0° vs 17.1°), SS (32.2° vs 23.5°), LL (46.9° vs 32.5°), and SVA (22.0 vs 17.0 mm) in SLDS were significantly higher than those in NG. However, PT/SS (44.0%), LL over PI (y = 0.39x + 24.25), SS over PI (y = 10.79 + 0.55x) were lower in TLDS than these in SLDS (63.8%, y = 0.41x + 25, y = 0.65x − 2.09, respectively), and the similar tend between SLDS and NG (74.0%, y = 0.49x + 13.09, y = 0.67x − 3.9, respectively). Our results showed that 2-level lumbar DS, which was caused by multiple-factors, has a severe sagittal imbalance, but single-level has not any. When we plan for surgical selection for 2-level lumbar DS, global sagittal balance must be considered. PMID:27977581

5. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

2013-11-01

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 nanostructured materials for sustainable environmental applications

PubMed Central

Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

2013-01-01

This review 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 toward water remediation, biosensing, 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. PMID:24790946

7. A neural signature of hierarchical reinforcement learning.

PubMed

Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

2011-07-28

Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

8. A novel method for a multi-level hierarchical composite with brick-and-mortar structure

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-07-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

9. Hierarchical analysis of molecular spectra

SciTech Connect

Davis, M.J.

1996-03-01

A novel representation of molecular spectra in terms of hierarchical trees has proven to be an important aid for the study of many significant problems in gas-phase chemical dynamics. Trees are generated from molecular spectra by monitoring the changes that occur in a spectrum as resolution is changed in a continuous manner. A tree defines a genealogy among all lines of a spectrum. This allows for a detailed understanding of the assignment of features of a spectrum that may be difficult to obtain any other way as well as an understanding of intramolecular energy transfer time scales, mechanisms, and pathways. The methodology has been applied to several problems: transition state spectroscopy, intramolecular energy transfer in highly excited molecules, high-resolution overtone spectroscopy, and the nature of the classical-quantum correspondence when there is classical chaos (``quantum chaos``).

10. Galaxy formation through hierarchical clustering

NASA Technical Reports Server (NTRS)

White, Simon D. M.; Frenk, Carlos S.

1991-01-01

Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

11. Adaptive Sampling in Hierarchical Simulation

SciTech Connect

Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R

2007-07-09

We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.

12. Core Recursive Hierarchical Image Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James

2011-01-01

The Recursive Hierarchical Image Segmentation (RHSEG) software has been repackaged to provide a version of the RHSEG software that is not subject to patent restrictions and that can be released to the general public through NASA GSFC's Open Source release process. Like the Core HSEG Software Package, this Core RHSEG Software Package also includes a visualization program called HSEGViewer along with a utility program HSEGReader. It also includes an additional utility program called HSEGExtract. The unique feature of the Core RHSEG package is that it is a repackaging of the RHSEG technology designed to specifically avoid the inclusion of the certain software technology. Unlike the Core HSEG package, it includes the recursive portions of the technology, but does not include processing window artifact elimination technology.

13. Hierarchical modeling for image classification

NASA Technical Reports Server (NTRS)

Likens, W.; Maw, K.

1982-01-01

As part of the California Integrated Remote Sensing System's (CIRSS) San Bernardino County Project, the use of data layers from a geographic information system (GIS) as an integral part of the Landsat image classification process was investigated. Through a hierarchical modeling technique, elevation, aspect, land use, vegetation, and growth management data from the project's data base were used to guide class labeling decisions in a 1976 Landsat MSS land cover classification. A similar model, incorporating 1976-1979 Landsat spectral change data in addition to other data base elements, was used in the classification of a 1979 Landsat image. The resultant Landsat products were integrated as additional layers into the data base for use in growth management, fire hazard, and hydrological modeling.

14. Cluster assembly of hierarchical nanostructures

SciTech Connect

Siegel, R.W.

1992-02-01

In the past few years, atom clusters with diameters in the range of 2--20 nm of a variety of materials, including both metals and ceramics, have been synthesized by evaporation and condensation in high-purity gases and subsequently consolidated in situ under ultrahigh vacuum conditions to create nanophase materials. These new utlrafine-grained materials have properties that are often significantly different and considerably improved relative to those of their coarser-grained counterparts owing to both their small grain-size scale and the large percentage of their atoms in grain boundary environments. Since their properties can be engineered during the synthesis and processing steps, cluster-assembled materials appear to have significant potential for the introduction of a hierarchy of both structure and properties. Some of the recent research on nanophase materials related to properties and scale are reviewed and some of the possibilities for synthesizing hierarchical nanostructures via cluster assembly are considered.

15. Hierarchical modeling of protein interactions.

PubMed

Kurcinski, Mateusz; Kolinski, Andrzej

2007-07-01

A novel approach to hierarchical peptide-protein and protein-protein docking is described and evaluated. Modeling procedure starts from a reduced space representation of proteins and peptides. Polypeptide chains are represented by strings of alpha-carbon beads restricted to a fine-mesh cubic lattice. Side chains are represented by up to two centers of interactions, corresponding to beta-carbons and the centers of mass of the remaining portions of the side groups, respectively. Additional pseudoatoms are located in the centers of the virtual bonds connecting consecutive alpha carbons. These pseudoatoms support a model of main-chain hydrogen bonds. Docking starts from a collection of random configurations of modeled molecules. Interacting molecules are flexible; however, higher accuracy models are obtained when the conformational freedom of one (the larger one) of the assembling molecules is limited by a set of weak distance restraints extracted from the experimental (or theoretically predicted) structures. Sampling is done by means of Replica Exchange Monte Carlo method. Afterwards, the set of obtained structures is subject to a hierarchical clustering. Then, the centroids of the resulting clusters are used as scaffolds for the reconstruction of the atomic details. Finally, the all-atom models are energy minimized and scored using classical tools of molecular mechanics. The method is tested on a set of macromolecular assemblies consisting of proteins and peptides. It is demonstrated that the proposed approach to the flexible docking could be successfully applied to prediction of protein-peptide and protein-protein interactions. The obtained models are almost always qualitatively correct, although usually of relatively low (or moderate) resolution. In spite of this limitation, the proposed method opens new possibilities of computational studies of macromolecular recognition and mechanisms of assembly of macromolecular complexes.

16. LINEAR ACCELERATOR

DOEpatents

Colgate, S.A.

1958-05-27

An improvement is presented in linear accelerators for charged particles with respect to the stable focusing of the particle beam. The improvement consists of providing a radial electric field transverse to the accelerating electric fields and angularly introducing the beam of particles in the field. The results of the foregoing is to achieve a beam which spirals about the axis of the acceleration path. The combination of the electric fields and angular motion of the particles cooperate to provide a stable and focused particle beam.

17. Reliability analysis of interconnection networks using hierarchical composition

SciTech Connect

Blake, J.T. ); Trivedi, K.S. )

1989-04-01

Based on the nature of the upper- and lower-bound block diagram models of Multistage Interconnection Networks (MINs), the authors generalize and consider a series system consisting of independent subsystems. In order to model the reliability of such a system with on-line repair and imperfect coverage, the usual approach is to construct and solve a large, overall Markov model. Instead, they propose a 2-level hierarchical model in which each subsystem is modeled as a Markov chain and the system reliability is then modeled as a series system of independent Markov components. They extend this technique to compute the instantaneous availability of the system with imperfect coverage and on-line repair. Thus, they extend the size of problems for which reliability/availability analysis, incorporating imperfect coverage and on-line repair, can be computed without resorting to a large, 1-level Markov model.

18. Linear Clouds

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Context image for PIA03667 Linear Clouds

These clouds are located near the edge of the south polar region. The cloud tops are the puffy white features in the bottom half of the image.

Image information: VIS instrument. Latitude -80.1N, Longitude 52.1E. 17 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

19. Vaspin and lipocalin-2 levels in severe obsructive sleep apnea

PubMed Central

Zorlu, Mehmet; Akkoyunlu, Muhammed Emin; Kilic, Elif; Karatoprak, Cumali; Cakirca, Mustafa; Yavuz, Erdinc; Ardic, Cuneyt; Camli, Ahmet Adil; Cikrikcioglu, Mehmetali; Kart, Levent

2014-01-01

Background Vaspin and lipocalin-2 are less-known recent members of adipocytokine family. There are ongoing studies investigating the role of vaspin ve lipocalin-2 in metabolic syndrome (MS). Obstructive sleep apnea syndrome (OSAS) is independently associated with an increased prevalence of MS. We aimed to measure the levels of vaspin and lipocalin-2 which are secreted from adipocytes in patients with severe OSAS and examine the relationship between these two adipocytokines and OSAS. Methods The study consisted of two groups: severe OSAS patients with an apnea-hypopnea index (AHI) of >30/h (OSAS group, 34 subjects) and age-matched healthy volunteers with a AHI <5/h (control group, 25 subjects) Serum levels of vaspin and lipocalin-2 in these two groups were compared. Results Serum levels of vaspin were significantly lower in OSAS group; patients with severe OSAS compared with control group; healthy volunteers (OSAS group: 0.69±0.5 vs. control group: 1.24±1.13; P=0.034). The difference between the two groups in terms of serum levels of lipocalin-2 has not reached statistical significance (OSAS group: 61.6±18.2 vs. control group: 68.5±20.1; P=0.17). Conclusions We found that serum vaspin levels were significantly lower in patients with severe OSAS compared with healthy controls. Lipocalin-2 levels were similar. The decrease in serum vaspin levels in severe OSAS patients may be important in diagnosis and follow-up of these patients. PMID:24976995

20. Lower-Critical Spin-Glass Dimension from 23 Sequenced Hierarchical Models

Demirtas, Mehmet; Tuncer, Asli; Berker, A. Nihat

The lower-critical dimension for the existence of the Ising spin-glass phase is calculated, numerically exactly, as dL = 2 . 520 for a sequence of hierarchical lattices, from an essentially exact (correlation coefficent R2 = 0 . 999999) near-linear fit to 23 different diminishing fractional dimensions. To obtain this result, the phase transition temperature between the disordered and spin-glass phases, the corresponding critical exponent yT, and the runaway exponent yR of the spin-glass phase are calculated for consecutive hierarchical lattices as dimension is lowered.

1. Lower-critical spin-glass dimension from 23 sequenced hierarchical models.

PubMed

Demirtaş, Mehmet; Tuncer, Aslı; Berker, A Nihat

2015-08-01

The lower-critical dimension for the existence of the Ising spin-glass phase is calculated, numerically exactly, as dL=2.520 for a family of hierarchical lattices, from an essentially exact (correlation coefficent R2=0.999999) near-linear fit to 23 different diminishing fractional dimensions. To obtain this result, the phase transition temperature between the disordered and spin-glass phases, the corresponding critical exponent yT, and the runaway exponent yR of the spin-glass phase are calculated for consecutive hierarchical lattices as dimension is lowered.

2. Lower-critical spin-glass dimension from 23 sequenced hierarchical models

Demirtaş, Mehmet; Tuncer, Aslı; Berker, A. Nihat

2015-08-01

The lower-critical dimension for the existence of the Ising spin-glass phase is calculated, numerically exactly, as dL=2.520 for a family of hierarchical lattices, from an essentially exact (correlation coefficent R2=0.999 999 ) near-linear fit to 23 different diminishing fractional dimensions. To obtain this result, the phase transition temperature between the disordered and spin-glass phases, the corresponding critical exponent yT, and the runaway exponent yR of the spin-glass phase are calculated for consecutive hierarchical lattices as dimension is lowered.

3. Estimation of inter-modular connectivity from the local field potentials in a hierarchical modular network

Cui, Xue-Mei; Kim, Won Sup; Hwang, Dong-Uk; Han, Seung Kee

2015-05-01

We propose a method of estimating inter-modular connectivity in a hierarchical modular network. The method is based on an analysis of inverse phase synchronization applied to the local field potentials on a hierarchical modular network of phase oscillators. For a strong-coupling strength, the inverse phase synchronization index of the local field potentials for two modules depends linearly on the corresponding inter-modular connectivity defined as the number of links connecting the modules. The method might enable us to estimate the inter-modular connectivity in various complex systems from the inverse phase synchronization index of the mesoscopic modular activities.

4. Unpacking the Complexity of Linear Equations from a Cognitive Load Theory Perspective

ERIC Educational Resources Information Center

Ngu, Bing Hiong; Phan, Huy P.

2016-01-01

The degree of element interactivity determines the complexity and therefore the intrinsic cognitive load of linear equations. The unpacking of linear equations at the level of operational and relational lines allows the classification of linear equations in a hierarchical level of complexity. Mapping similar operational and relational lines across…

5. A Bayesian hierarchical model for categorical data with nonignorable nonresponse.

PubMed

Green, Paul E; Park, Taesung

2003-12-01

Log-linear models have been shown to be useful for smoothing contingency tables when categorical outcomes are subject to nonignorable nonresponse. A log-linear model can be fit to an augmented data table that includes an indicator variable designating whether subjects are respondents or nonrespondents. Maximum likelihood estimates calculated from the augmented data table are known to suffer from instability due to boundary solutions. Park and Brown (1994, Journal of the American Statistical Association 89, 44-52) and Park (1998, Biometrics 54, 1579-1590) developed empirical Bayes models that tend to smooth estimates away from the boundary. In those approaches, estimates for nonrespondents were calculated using an EM algorithm by maximizing a posterior distribution. As an extension of their earlier work, we develop a Bayesian hierarchical model that incorporates a log-linear model in the prior specification. In addition, due to uncertainty in the variable selection process associated with just one log-linear model, we simultaneously consider a finite number of models using a stochastic search variable selection (SSVS) procedure due to George and McCulloch (1997, Statistica Sinica 7, 339-373). The integration of the SSVS procedure into a Markov chain Monte Carlo (MCMC) sampler is straightforward, and leads to estimates of cell frequencies for the nonrespondents that are averages resulting from several log-linear models. The methods are demonstrated with a data example involving serum creatinine levels of patients who survived renal transplants. A simulation study is conducted to investigate properties of the model.

6. NASA thesaurus. Volume 1: Hierarchical Listing

NASA Technical Reports Server (NTRS)

1988-01-01

There are over 17,000 postable terms and nearly 4,000 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary and Volume 3 - Definitions.

7. NASA thesaurus. Volume 1: Hierarchical listing

NASA Technical Reports Server (NTRS)

1985-01-01

There are 16,835 postable terms and 3,765 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary.

8. NASA Thesaurus. Volume 1: Hierarchical listing

NASA Technical Reports Server (NTRS)

1982-01-01

There are 16,713 postable terms and 3,716 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary.

9. Hierarchical analysis of rainfall variability across Nigeria

Nnaji, Chidozie Charles; Mama, Cordelia Nnennaya; Ukpabi, Okechukwu

2016-01-01

Rainfall in Nigeria is subjected to wide variability both in time and space. This variability has assumed a more pronounced dimension as a result of climate change. In this paper, cluster analyses were used to study rainfall variability in Nigeria. Rainfall data in 20 locations spread across the geopolitical and ecological zones of Nigeria were subjected to hierarchical cluster analysis and analysis of time series and coefficient of variation for over periods spanning 30 years. Maps of spatial variations of mean annual rainfall and mean rainfall coefficient of variation were produced using ARCGIS 10.1. Furthermore, a better understanding of temporal variation of rainfall was sought by an investigation into the time series of rainfall coefficients of variation. It was found that the southern parts of the country were given to more severe rainfall variability/fluctuations than the northern parts. The north central parts exhibited more similarity to the southern parts than the other northern locations. The relationship between average annual rainfall and the coefficient of rainfall variation was found to follow a power law with R 2 value approximately 0.7. With respect to variability of annual rainfall, three zones emerged as follows: a linear relationship ( R 2 = 0.90) exists between coefficient of variation and average annual rainfall for the rainforest zone of the southsouth; a power law ( R 2 = 0.86) exists between coefficient of variation and average annual rainfall for all rainforest and derived guinea savannah zones of the southeastern and southwestern states; and a logarithmic relationship ( R 2 = 0.54) exists between coefficient of variation and average annual rainfall for all northern states regardless of ecological zone. Generally, in-year rainfall variability increases from the northwest to the southwest; while between-year (yearly) rainfall variability increases from the north central to the southeast. This study further confirms that rainfall variability

10. A hierarchical artificial retina architecture

Parker, Alice C.; Azar, Adi N.

2009-05-01

Connectivity in the human retina is complex. Over one hundred million photoreceptors transduce light into electrical signals. These electrical signals are sent to the ganglion cells through amacrine and bipolar cells. Lateral connections involving horizontal and amacrine cells span throughout the outer plexiform layer and inner plexiform layer respectively. Horizontal cells are important for photoreceptor regulation by depolarizing them after an illumination occurs. Horizontal cells themselves form an electrical network that communicates by gap junctions, and these cells exhibit plasticity (change in behavior and structure) with respect to glycine receptors. The bipolar and amacrine cells transfer electrical signals from photoreceptors to the ganglion cells. Furthermore, amacrine cells are responsible for further processing the retinal image. Finally, the ganglion cells receive electrical signals from the bipolar and amacrine cells and will spike at a faster rate if there is a change in the overall intensity for a group of photoreceptors, sending a signal to the brain. Dramatic progress is being made with respect to retinal prostheses, raising hope for an entire synthetic retina in the future. We propose a bio-inspired 3D hierarchical pyramidal architecture for a synthetic retina that mimics the overall structure of the human retina. We chose to use a 3D architecture to facilitate connectivity among retinal cells, maintaining a hierarchical structure similar to that of the biological retina. The first layer of the architecture contains electronic circuits that model photoreceptors and horizontal cells. The second layer contains amacrine and bipolar electronic cells, and the third layer contains ganglion cells. Layer I has the highest number of cells, and layer III has the lowest number of cells, resulting in a pyramidal architecture. In our proposed architecture we intend to use photodetectors to transduce light into electrical signals. We propose to employ

11. Hierarchical drivers of reef-fish metacommunity structure.

PubMed

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

12. Hierarchically nanostructured barium sulfate fibers.

PubMed

Romero-Ibarra, Issis C; Rodríguez-Gattorno, Geonel; García-Sánchez, Mario F; Sánchez-Solís, Antonio; Manero, Octavio

2010-05-18

BaSO(4) nanostructures with controlled morphologies were successfully produced via one-step process through precipitation of BaSO(4) in aqueous and organic media. The synthesis is carried out by mixing solutions of BaCl(2) and Na(2)SO(4) in presence of EDTA (disodium ethylenediaminetetraacetic acid) at room temperature. The influence of the reaction conditions such as initial reactants concentration, pH, EDTA/[Ba(2+)] ratio and aging on the BaSO(4) nanoparticles organization is studied. Using EDTA in aqueous media, spherical secondary particles of 500 nm diameter are obtained, which are formed by 4 nm size primary particles. With dimethyl sulfoxide and small amounts of water (5%) and EDTA, the aging process allows the production of long homogeneous fibers, related to hierarchical organization of BaSO(4) nanoparticles. Direct observation of self-assembling of primary particles by HRTEM allows proposing a mechanism for fiber formation, which is based on multipolar attractions that lead to a brick-by-brick organization along a preferential orientation. Results evidence the role of EDTA as controlling agent of the morphology and primary and secondary mean particle size.

13. Object recognition with hierarchical discriminant saliency networks

PubMed Central

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

14. Altered Carbon Isotope Discrimination of C3 Plants Under Very High pCO2 Levels

Panetta, R. J.; Schubert, B.; Jahren, H.

2009-12-01

Various modeling and proxy-based reconstructions of atmospheric pCO2 levels for the last 120 Ma have estimated RCO2 as high as 12x for the Early Cretaceous, generally decreasing into the Cenozoic, and decreasing further into the Quaternary. Multiple ecological studies to assess the effect of elevated CO2 on plant biomass and δ13C value have been spurred on by recent increases in greenhouse gases, however these studies typically grow plants under only slightly elevated CO2 levels (i.e., the twenty foremost studies published since 1990 involved 550 to 750 ppm pCO2, which equals RCO2 = 1.4 to 1.9x). In order to recreate the highest pCO2 environments of the last 120 Ma, we grew radish (Raphanus sativus L.) in growth chambers that maintained controlled environmental conditions and pCO2 levels ranging from ~5 to 11x that of today’s atmosphere (1791 to 4200 ppm); upon harvest we measured total biomass and stable carbon isotope ratio (δ13Cplant) in both above and below ground plant tissue. Unlike the 1:1 relationship between stable isotopes of atmospheric CO2 (δ13Catm) and δ13Cplant observed at lower pCO2 levels (i.e., RCO2 = 1x to 3x; Jahren et al., 2008), the δ13Cplant of biomass grown at more elevated RCO2 was dependent upon δ13Catm according to the linear relationship: δ13Cplant = 1.9(δ13Cplant) - 12.2 ‰ (r2 = 0.71). Concomitantly, we see a highly significant (p < 0.001) positive correlation between net carbon isotope discrimination in plant tissue and pCO2 level, with a change in the average Δδ13Cplant-atm in R. sativus L. from -27.0 to -28.0 ‰ at RCO2 = 5x to 11x, respectively. We will discuss possible mechanisms for changing isotope discrimination at very high pCO2 levels that may not be operative at lower concentrations. For example, we noted a striking reduction in the variability of biomass between plants grown at the same (very high) level of pCO2. This variability (calculated as the standard deviation of the log-transformed biomass data after

15. Hierarchically UVO patterned elastomeric and thermoplastic structures

Chen, Ying; Kulkarni, Manish; Marshall, Allan; Karim, Alamgir

2014-03-01

We demonstrate a simple yet versatile method to fabricate tunable hierarchical micro-nanostructures on flexible Poly(dimethylsiloxane) (PDMS) elastomer and thermoplastic polymer surface by a two-step process. Nanoscale patterned PDMS was obtained by imprinting compact disc (CD)/digital video disc (DVD) patterns. The second micro pattern was superposed by selective densification of PDMS by exposing to ultraviolet-ozone radiation (UVO) through micro-patterned TEM grid as a mask. The nanoscale patterns are preserved through UVO exposure step leading to formation of deep hierarchical patterns, so that for a 19 um square mesh, the micro pattern has a depth of 600nm with 6h PDMS UVO exposure time. This simple method can be promoted to fabricate hierarchical structures of thermoplastic materials (such as polystyrene), from which the mechanism of capillary imprinting and thermal stability of hierarchical patterns are investigated. This study is potentially important to various applications ranging from biomimetic scaffolds to solar cell.

16. Zeolitic materials with hierarchical porous structures.

PubMed

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.

17. The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods.

PubMed

Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

2007-01-01

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

18. Microfluidic Droplet-Facilitated Hierarchical Assembly for Dual Cargo Loading and Synergistic Delivery

PubMed Central

2016-01-01

Bottom-up hierarchical assembly has emerged as an elaborate and energy-efficient strategy for the fabrication of smart materials. Herein, we present a hierarchical assembly process, whereby linear amphiphilic block copolymers are self-assembled into micelles, which in turn are accommodated at the interface of microfluidic droplets via cucurbit[8]uril-mediated host–guest chemistry to form supramolecular microcapsules. The monodisperse microcapsules can be used for simultaneous carriage of both organic (Nile Red) and aqueous-soluble (fluorescein isothiocyanate-dextran) cargo. Furthermore, the well-defined compartmentalized structure benefits from the dynamic nature of the supramolecular interaction and offers synergistic delivery of cargos with triggered release or through photocontrolled porosity. This demonstration of premeditated hierarchical assembly, where interactions from the molecular to microscale are designed, illustrates the power of this route toward accessing the next generation of functional materials and encapsulation strategies. PMID:26982167

19. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido

2015-12-01

The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.

20. Hierarchical Models of the Nearshore Complex System

DTIC Science & Technology

2004-01-01

unclassified unclassified /,andard Form 7 7Qien. -pii Prescrbed by ANS Sid 239-18 zgB -10z Hierarchical Models of the Nearshore Complex System: Final...TITLE AND SUBTITLE S. FUNDING NUMBERS Hierarchical Models of the Nearshore Complex System N00014-02-1-0358 6. AUTHOR(S) Brad Werner 7. PERFORMING...8217 ........... The long-term goal of this reasearch was to develop and test predictive models for nearshore processes. This grant was terminaton funding for the

1. Hierarchical Nanoceramics for Industrial Process Sensors

SciTech Connect

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.

2. A Biologically Inspired Hierarchical Goal Directed Navigation Model

PubMed Central

Erdem, Uğur M.; Hasselmo, Michael E.

2014-01-01

We propose an extended version of our previous goal directed navigation model based on forward planning of trajectories in a network of head direction cells, persistent spiking cells, grid cells, and place cells. In our original work the animat incrementally creates a place cell map by random exploration of a novel environment. After the exploration phase, the animat decides on its next movement direction towards a goal by probing linear look-ahead trajectories in several candidate directions while stationary and picking the one activating place cells representing the goal location. In this work we present several improvements over our previous model. We improve the range of linear look-ahead probes significantly by imposing a hierarchical structure on the place cell map consistent with the experimental findings of differences in the firing field size and spacing of grid cells recorded at different positions along the dorsal to ventral axis of entorhinal cortex. The new model represents the environment at different scales by populations of simulated hippocampal place cells with changing firing field sizes. Among other advantages this model allows simultaneous constant duration linear look-ahead probes at different scales while significantly extending each probe range. The extension of the linear look-ahead probe range while keeping its duration constant also limits the degrading effects of noise accumulation in the network. We show the extended model’s performance using an animat in a large open field environment. PMID:23891644

3. A biologically inspired hierarchical goal directed navigation model.

PubMed

Erdem, Uğur M; Hasselmo, Michael E

2014-02-01

We propose an extended version of our previous goal directed navigation model based on forward planning of trajectories in a network of head direction cells, persistent spiking cells, grid cells, and place cells. In our original work the animat incrementally creates a place cell map by random exploration of a novel environment. After the exploration phase, the animat decides on its next movement direction towards a goal by probing linear look-ahead trajectories in several candidate directions while stationary and picking the one activating place cells representing the goal location. In this work we present several improvements over our previous model. We improve the range of linear look-ahead probes significantly by imposing a hierarchical structure on the place cell map consistent with the experimental findings of differences in the firing field size and spacing of grid cells recorded at different positions along the dorsal to ventral axis of entorhinal cortex. The new model represents the environment at different scales by populations of simulated hippocampal place cells with different firing field sizes. Among other advantages this model allows simultaneous constant duration linear look-ahead probes at different scales while significantly extending each probe range. The extension of the linear look-ahead probe range while keeping its duration constant also limits the degrading effects of noise accumulation in the network. We show the extended model's performance using an animat in a large open field environment.

4. On Hierarchical Threshold Access Structures

DTIC Science & Technology

2010-11-01

section claims this property with a probability merely close to 1 depending on the field size and some constants. Linear SSS’s ( LSSS ) are widely...distributed to all participants in U. Now giving share si to participant  (i), we can identify an LSSS with its underlying MSP. It is known, due to [6...by an authorized set with probability 1. An observation on the difficulty of establishing an ideal and efficient LSSS for the realization of [4] is

5. Application Scenarios for Nonstandard Log-Linear Models

ERIC Educational Resources Information Center

Mair, Patrick; von Eye, Alexander

2007-01-01

In this article, the authors have 2 aims. First, hierarchical, nonhierarchical, and nonstandard log-linear models are defined. Second, application scenarios are presented for nonhierarchical and nonstandard models, with illustrations of where these scenarios can occur. Parameters can be interpreted in regard to their formal meaning and in regard…

6. Quantifying and reducing uncertainties in estimated soil CO2 fluxes with hierarchical data-model integration

Ogle, Kiona; Ryan, Edmund; Dijkstra, Feike A.; Pendall, Elise

2016-12-01

Nonsteady state chambers are often employed to measure soil CO2 fluxes. CO2 concentrations (C) in the headspace are sampled at different times (t), and fluxes (f) are calculated from regressions of C versus t based on a limited number of observations. Variability in the data can lead to poor fits and unreliable f estimates; groups with too few observations or poor fits are often discarded, resulting in "missing" f values. We solve these problems by fitting linear (steady state) and nonlinear (nonsteady state, diffusion based) models of C versus t, within a hierarchical Bayesian framework. Data are from the Prairie Heating and CO2 Enrichment study that manipulated atmospheric CO2, temperature, soil moisture, and vegetation. CO2 was collected from static chambers biweekly during five growing seasons, resulting in >12,000 samples and >3100 groups and associated fluxes. We compare f estimates based on nonhierarchical and hierarchical Bayesian (B versus HB) versions of the linear and diffusion-based (L versus D) models, resulting in four different models (BL, BD, HBL, and HBD). Three models fit the data exceptionally well (R2 ≥ 0.98), but the BD model was inferior (R2 = 0.87). The nonhierarchical models (BL and BD) produced highly uncertain f estimates (wide 95% credible intervals), whereas the hierarchical models (HBL and HBD) produced very precise estimates. Of the hierarchical versions, the linear model (HBL) underestimated f by 33% relative to the nonsteady state model (HBD). The hierarchical models offer improvements upon traditional nonhierarchical approaches to estimating f, and we provide example code for the models.

7. A hierarchical state space approach to affective dynamics

PubMed Central

Lodewyckx, Tom; Tuerlinckx, Francis; Kuppens, Peter; Allen, Nicholas; Sheeber, Lisa

2010-01-01

Linear dynamical system theory is a broad theoretical framework that has been applied in various research areas such as engineering, econometrics and recently in psychology. It quantifies the relations between observed inputs and outputs that are connected through a set of latent state variables. State space models are used to investigate the dynamical properties of these latent quantities. These models are especially of interest in the study of emotion dynamics, with the system representing the evolving emotion components of an individual. However, for simultaneous modeling of individual and population differences, a hierarchical extension of the basic state space model is necessary. Therefore, we introduce a Bayesian hierarchical model with random effects for the system parameters. Further, we apply our model to data that were collected using the Oregon adolescent interaction task: 66 normal and 67 depressed adolescents engaged in a conflict interaction with their parents and second-to-second physiological and behavioral measures were obtained. System parameters in normal and depressed adolescents were compared, which led to interesting discussions in the light of findings in recent literature on the links between cardiovascular processes, emotion dynamics and depression. We illustrate that our approach is flexible and general: The model can be applied to any time series for multiple systems (where a system can represent any entity) and moreover, one is free to focus on whatever component of the versatile model. PMID:21516216

8. Statistical label fusion with hierarchical performance models

Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.

2014-03-01

Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally - fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy.

9. Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

10. Analysis hierarchical model for discrete event systems

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.

11. Hierarchal Genetic Stratigraphy: A Framework for Paleoceanography

Busch, R. M.; West, R. R.

1987-04-01

A detailed, genetic stratigraphic framework for paleoceanographic studies can be derived by describing, correlating, interpreting, and predicting stratigraphic sequences relative to a hierarchy of their constituent time-stratigraphic transgressive-regressive units ("T-R units"). T-R unit hierarchies are defined and correlated using lithostratigraphic and paleoecologic data, but correlations can be enhanced or "checked" (tested to confirm or deny) with objective biostratigraphic, magnetostratigraphic, or chemostratigraphic data. Such chronostratigraphies can then be bracketed by radiometric ages, so that average periodicities for T-R units can be calculated and a hierarchal geochronology derived. T-R units are inferred to be the net depositional result of eustatic cycles of sea level change and can be differentiated from autocyclic deepening-shallowing units because the latter are noncorrelative intrabasinally. Boundaries between T-R units are conformable or unconformable "genetic surfaces" of two types: transgressive surfaces and "climate change surfaces". The latter are useful for correlating minor transgressive phases through nonmarine intervals, thereby deriving information linking paleoclimatic and paleoceanographic processes. Permo-Carboniferous sequences can be analyzed relative to a hierarchy of six scales of genetic T-R units having periodicities of 225-300 m.y. (first order), 20-90 m.y. (second order), 7-13 m.y. (third-order), 0.6-3.6 m.y. (fourth order), 300-500 × 10³ years (fifth order), and 50-130 × 10³ years or less (sixth-order). Paleogeographic maps for the time of maximum transgression ("transgressive apex") of successive fifth-order T-R units (5-25 m thick) in the Glenshaw Formation (Upper Pennsylvanian, Northern Appalachian Basin) delineate delta lobes, embayments, islands, and linear seaways. Relative extent of marine inundation on the fifth-order maps was used to delineate fourth-order T-R units, and the fourth-order T-R units constitute the

12. Towards a sustainable manufacture of hierarchical zeolites.

PubMed

Verboekend, Danny; Pérez-Ramírez, Javier

2014-03-01

Hierarchical zeolites have been established as a superior type of aluminosilicate catalysts compared to their conventional (purely microporous) counterparts. An impressive array of bottom-up and top-down approaches has been developed during the last decade to design and subsequently exploit these exciting materials catalytically. However, the sustainability of the developed synthetic methods has rarely been addressed. This paper highlights important criteria to ensure the ecological and economic viability of the manufacture of hierarchical zeolites. Moreover, by using base leaching as a promising case study, we verify a variety of approaches to increase reactor productivity, recycle waste streams, prevent the combustion of organic compounds, and minimize separation efforts. By reducing their synthetic footprint, hierarchical zeolites are positioned as an integral part of sustainable chemistry.

13. Hierarchical Micro-Nano Coatings by Painting

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.

14. Static and dynamic friction of hierarchical surfaces

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.

15. Intelligent controllers as hierarchical stochastic automata.

PubMed

Lima, P U; Saridis, G N

1999-01-01

This paper introduces a design methodology for intelligent controllers, based on a hierarchical linguistic model of command translation by tasks-primitive tasks-primitive actions, and on a two-stage hierarchical learning stochastic automaton that models the translation interfaces of a three-level hierarchical intelligent controller. The methodology relies on the designer's a priori knowledge on how to implement by primitive actions the different primitive tasks which define the intelligent controller. A cost function applicable to any primitive task is introduced and used to learn on-line the optimal choices from the corresponding predesigned sets of primitive actions. The same concept applies to the optimal tasks for each command, whose choice is based on conflict sets of stochastic grammar productions. Optional designs can be compared using this performance measure. A particular design evolves towards the command translation (by tasks-primitive tasks-primitive actions) that minimizes the cost function.

16. Static and dynamic friction of hierarchical surfaces.

PubMed

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.

17. A hierarchical cellular logic for pyramid computers

SciTech Connect

Tanimoto, S.L.

1984-11-01

Hierarchical structure occurs in biological vision systems and there is good reason to incorporate it into a model of computation for processing binary images. A mathematical formalism is presented which can describe a wide variety of operations useful in image processing and graphics. The formalism allows for two kinds of simple transformations on the values (called pyramids) of a set of cells called a hierarchical domain: the first are binary operations on boolean values, and the second are neighborhood-matching operations. The implied model of computation is more structured than previously discussed pyramidal models, and is more readily realized in parallel hardware, while it remains sufficiently rich to provide efficient solutions to a wide variety of problems. The model has a simplicity which is due to the restricted nature of the operations and the implied synchronization across the hierarchical domain. A corresponding algebraic simplicity in the logic makes possible the concise representation of many cellular-data operations.

18. [Comparative hierarchic structure of the genetic language].

PubMed

Ratner, V A

1993-05-01

The genetical texts and genetic language are built according to hierarchic principle and contain no less than 6 levels of coding sequences, separated by marks of punctuation, separation and indication: codons, cistrons, scriptons, replicons, linkage groups, genomes. Each level has all the attributes of the language. This hierarchic system expresses some general properties and regularities. The rules of genetic language being determined, the variability of genetical texts is generated by block-modular combinatorics on each level. Between levels there are some intermediate sublevels and module types capable of being combined. The genetic language is compared with two different independent linguistic systems: human natural languages and artificial programming languages. Genetic language is a natural one by its origin, but it is a typical technical language of the functioning genetic regulatory system--by its predestination. All three linguistic systems under comparison have evident similarity of the organization principles and hierarchical structures. This argues for similarity of their principles of appearance and evolution.

19. Anisotropic wettability on imprinted hierarchical structures.

PubMed

Zhang, Fengxiang; Low, Hong Yee

2007-07-03

A series of two-level hierarchical structures on polystyrene (PS) and poly(methyl methacrylate) (PMMA) were fabricated using sequential nanoimprinting lithography (NIL). The hierarchical structures consist of micrometer and sub-micrometer scale grating imprinted with varying orientations. Through water contact angle measurements, these surface hierarchical structures showed a wide range of anisotropic wettabilities on PMMA and PS, with PMMA having an anisotropic wettability from 6 degrees to 54 degrees and PS having an anisotropic wettability from 8 degrees to 32 degrees. At the same time, the water contact angle of PMMA and PS can be tuned to nearly 120 degrees without modifying the surface chemistry. A tunable anisotropic wettability is beneficial for applications where controlling the direction of liquid flow is important, such as in microfluidic devices.

20. Hierarchical Control and Trajectory Planning

NASA Technical Reports Server (NTRS)

Martin, Clyde F.; Horn, P. W.

1994-01-01

Most of the time on this project was spent on the trajectory planning problem. The construction is equivalent to the classical spline construction in the case that the system matrix is nilpotent. If the dimension of the system is n then the spline of degree 2n-1 is constructed. This gives a new approach to the construction of splines that is more efficient than the usual construction and at the same time allows the construction of a much larger class of splines. All known classes of splines are reconstructed using the approach of linear control theory. As a numerical analysis tool control theory gives a very good tool for constructing splines. However, for the purposes of trajectory planning it is quite another story. Enclosed in this document are four reports done under this grant.

1. Hierarchical Analysis of the Omega Ontology

SciTech Connect

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.

2. A hierarchical clustering algorithm for MIMD architecture.

PubMed

Du, Zhihua; Lin, Feng

2004-12-01

Hierarchical clustering is the most often used method for grouping similar patterns of gene expression data. A fundamental problem with existing implementations of this clustering method is the inability to handle large data sets within a reasonable time and memory resources. We propose a parallelized algorithm of hierarchical clustering to solve this problem. Our implementation on a multiple instruction multiple data (MIMD) architecture shows considerable reduction in computational time and inter-node communication overhead, especially for large data sets. We use the standard message passing library, message passing interface (MPI) for any MIMD systems.

3. Hierarchical social networks and information flow

López, Luis; F. F. Mendes, Jose; Sanjuán, Miguel A. F.

2002-12-01

Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders, because the global influence each actor has within the network is completely determined by the hierarchical level occupied.

4. Formation mechanism of silver nanoparticle 1D microstructures and their hierarchical assembly into 3D superstructures

Suber, Lorenza; Plunkett, William. R.

2010-01-01

Flower-like silver nanoparticle superstructures are prepared by the reaction of silver nitrate and ascorbic acid in an acidic aqueous solution of a polynaphthalene system. The three-dimensional flower-like structure has a purely hierarchic arrangement, wherein each petal is composed of bundles of silver particle chains, each enclosed in a polymer sheath. The ordering arises from strong adsorption of silver ions onto the polymer and by the interplay of the redox properties of nitric and ascorbic acid. As a result, linear silver cyanide, formed on the polymer, probably due to intrinsic electric dipole fields, organizes the silver particle chains in dumbbell-like structures, resembling buds and flower-like structures. By dilution and heating of the mother liquors, it is also possible to obtain single petals, i.e. micrometer sized bundles of linearly aggregated silver nanoparticle chains, each enclosed in a polymer sheath. The comprehension of the hierarchic assembly of silver nanoparticles, paves the way to a facile general method to prepare polymer-metal nanoparticle chains and flower-like superstructures. The results of this study improve both the understanding of the formation mechanism of hierarchic structures at mild temperatures and our ability to tailor them to sizes and shapes appropriate for technological purposes.Flower-like silver nanoparticle superstructures are prepared by the reaction of silver nitrate and ascorbic acid in an acidic aqueous solution of a polynaphthalene system. The three-dimensional flower-like structure has a purely hierarchic arrangement, wherein each petal is composed of bundles of silver particle chains, each enclosed in a polymer sheath. The ordering arises from strong adsorption of silver ions onto the polymer and by the interplay of the redox properties of nitric and ascorbic acid. As a result, linear silver cyanide, formed on the polymer, probably due to intrinsic electric dipole fields, organizes the silver particle chains in

5. Three-dimensional macroporous carbon/hierarchical Co3O4 nanoclusters for nonenzymatic electrochemical glucose sensor

Wang, Li; Zhang, Yayun; Xie, Yingzhen; Yu, Jie; Yang, Han; Miao, Longfei; Song, Yonghai

2017-04-01

A novel supporting material named as three-dimensional kenaf stem-derived carbon (3D-KSCs) was used to load hierarchical Co3O4 nanoclusters for electrochemical sensing glucose. The 3D-KSCs/hierarchical Co3O4 nanoclusters were constructed by two steps. Los of acicular precursor nanoclusters firstly grew on the channels of 3D-KSCs densely by hydrothermal method and then the as-prepared 3D-KSCs/hierarchical Co3O4 nanoclusters was obtained by thermal pyrolysis of the 3D-KSCs/precursors nanocomposites at 400 °C. The 3D macroporous configuration of 3D-KSCs resulted in lots of hierarchical Co3O4 nanoclusters arrayed on the surface of 3D-KSCs owing to its large enough specific surface area, which effectively avoided their aggregations and improved the stability of nanocomposites. The obtained 3D-KSCs/hierarchical Co3O4 nanoclusters showed a large number of needle-shaped and layered Co3O4 nanoclusters uniformly grew on the macropore's walls of 3D-KSC. Due to its unique nanostructures, the 3D-KSCs/hierarchical Co3O4 nanoclusters integrated electrode showed superior performance for nonenzymatic electrochemical glucose sensing, showing wide linear range (0.088-7.0 mM) and low detection limit of 26 μM. It might be a new strategy to prepare nanostructures on 3D-KSC for future applications.

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

ERIC Educational Resources Information Center

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…

7. Hierarchical Models in the Brain

PubMed Central

Friston, Karl

2008-01-01

This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain. PMID:18989391

8. Rehabilitation Goals: Their Hierarchical and Multifaceted Nature.

ERIC Educational Resources Information Center

Livneh, Hanoch

1988-01-01

Rehabilitation goals are analyzed from a hierarchical, multifaceted perspective, illustrating reduction of the ultimate goal of life adjustment to smaller goals. Addressed are: the contexts within which rehabilitation takes place, the activity levels defining human performance, and the functional levels achieved. A matrix of 12 sets of goals is…

9. Cognitive Diagnostic Analysis Using Hierarchically Structured Skills

ERIC Educational Resources Information Center

Su, Yu-Lan

2013-01-01

This dissertation proposes two modified cognitive diagnostic models (CDMs), the deterministic, inputs, noisy, "and" gate with hierarchy (DINA-H) model and the deterministic, inputs, noisy, "or" gate with hierarchy (DINO-H) model. Both models incorporate the hierarchical structures of the cognitive skills in the model estimation…

10. Types of Online Hierarchical Repository Structures

ERIC Educational Resources Information Center

Hershkovitz, Arnon; Azran, Ronit; Hardof-Jaffe, Sharon; Nachmias, Rafi

2011-01-01

This study presents an empirical investigation of online hierarchical repositories of items presented to university students in Web-supported course websites, using Web mining methods. To this end, data from 1747 courses were collected, and the use of online repositories of content items in these courses was examined. At a later stage, courses…

11. Transforming Hierarchical Relationships in Student Conduct Administration

ERIC Educational Resources Information Center

Jacobson, Kelly A.

2013-01-01

Conflict transformation theory provided a philosophical lens for this critical cultural, constructivist study, wherein four student conduct administrators who engage in leveling hierarchical relationships with students in conduct processes shared ways they make meaning of their professional practice. Through informal, unstructured interviews, a…

12. The Lyman Alpha Forest in hierarchical cosmologies

SciTech Connect

Anninos, P; Bryan, G L; Machacek, M; Moiksin, A; Norman, M L; Zhang, Y

1999-07-02

The comparison of quasar absorption spectra with numerically simulated spectra from hierarchical cosmological models of structure formation promises to be a valuable tool to discriminate among these models. We present simulation results for the column density, Doppler b parameter, and optical depth probability distributions for five popular cosmological models.

13. A Hierarchical Grouping of Great Educators

ERIC Educational Resources Information Center

Barker, Donald G.

1977-01-01

Great educators of history were categorized on the basis of their: aims of education, fundamental ideas, and educational theories. They were classed by Ward's method of hierarchical analysis into six groupings: Socrates, Ausonius, Jerome, Abelard; Quintilian, Origen, Melanchthon, Ascham, Loyola; Alciun, Comenius; Vittorino, Basedow, Pestalozzi,…

14. Parallel Temporal Dynamics in Hierarchical Cognitive Control

PubMed Central

Ranti, Carolyn; Chatham, Christopher H.; Badre, David

2015-01-01

Cognitive control allows us to follow abstract rules in order to choose appropriate responses given our desired outcomes. Cognitive control is often conceptualized as a hierarchical decision process, wherein decisions made at higher, more abstract levels of control asymmetrically influence lower-level decisions. These influences could evolve sequentially across multiple levels of a hierarchical decision, consistent with much prior evidence for central bottlenecks and seriality in decision-making processes. However, here, we show that multiple levels of hierarchical cognitive control are processed primarily in parallel. Human participants selected responses to stimuli using a complex, multiply contingent (third order) rule structure. A response deadline procedure allowed assessment of the accuracy and timing of decisions made at each level of the hierarchy. In contrast to a serial decision process, error rates across levels of the decision mostly declined simultaneously and at identical rates, with only a slight tendency to complete the highest level decision first. Simulations with a biologically plausible neural network model demonstrate how such parallel processing could emerge from a previously developed hierarchically nested frontostriatal architecture. Our results support a parallel processing model of cognitive control, in which uncertainty on multiple levels of a decision is reduced simultaneously. PMID:26051820

15. Metal oxide nanostructures with hierarchical morphology

SciTech Connect

Ren, Zhifeng; Lao, Jing Yu; Banerjee, Debasish

2007-11-13

The present invention relates generally to metal oxide materials with varied symmetrical nanostructure morphologies. In particular, the present invention provides metal oxide materials comprising one or more metallic oxides with three-dimensionally ordered nanostructural morphologies, including hierarchical morphologies. The present invention also provides methods for producing such metal oxide materials.

16. Arbitrary Order Hierarchical Bases for Computational Electromagnetics

SciTech Connect

Rieben, R N; White, D; Rodrigue, G

2002-12-20

We present a clear and general method for constructing hierarchical vector bases of arbitrary polynomial degree for use in the finite element solution of Maxwell's equations. Hierarchical bases enable p-refinement methods, where elements in a mesh can have different degrees of approximation, to be easily implemented. This can prove to be quite useful as sections of a computational domain can be selectively refined in order to achieve a greater error tolerance without the cost of refining the entire domain. While there are hierarchical formulations of vector finite elements in publication (e.g. [1]), they are defined for tetrahedral elements only, and are not generalized for arbitrary polynomial degree. Recently, Hiptmair, motivated by the theory of exterior algebra and differential forms presented a unified mathematical framework for the construction of conforming finite element spaces [2]. In [2], both 1-form (also called H(curl)) and 2-form (also called H(div)) conforming finite element spaces and the definition of their degrees of freedom are presented. These degrees of freedom are weighted integrals where the weighting function determines the character of the bases, i.e. interpolatory, hierarchical, etc.

17. The Hierarchical Structure of Formal Operational Tasks.

ERIC Educational Resources Information Center

Bart, William M.; Mertens, Donna M.

1979-01-01

The hierarchical structure of the formal operational period of Piaget's theory of cognitive development was explored through the application of ordering theoretical methods to a set of data that systematically utilized the various formal operational schemes. Results suggested a common structure underlying task performance. (Author/BH)

18. A Hierarchical Process-Dissociation Model

ERIC Educational Resources Information Center

Rouder, Jeffrey N.; Lu, Jun; Morey, Richard D.; Sun, Dongchu; Speckman, Paul L.

2008-01-01

In fitting the process-dissociation model (L. L. Jacoby, 1991) to observed data, researchers aggregate outcomes across participant, items, or both. T. Curran and D. L. Hintzman (1995) demonstrated how biases from aggregation may lead to artifactual support for the model. The authors develop a hierarchical process-dissociation model that does not…

19. Hierarchical Context Modeling for Video Event Recognition.

PubMed

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.

20. Bone hierarchical structure in three dimensions.

PubMed

Reznikov, Natalie; Shahar, Ron; Weiner, Steve

2014-09-01

Bone is a complex hierarchically structured family of materials that includes a network of cells and their interconnected cell processes. New insights into the 3-D structure of various bone materials (mainly rat and human lamellar bone and minipig fibrolamellar bone) were obtained using a focused ion beam electron microscope and the serial surface view method. These studies revealed the presence of two different materials, the major material being the well-known ordered arrays of mineralized collagen fibrils and associated macromolecules, and the minor component being a relatively disordered material composed of individual collagen fibrils with no preferred orientation, with crystals inside and possibly between fibrils, and extensive ground mass. Significantly, the canaliculi and their cell processes are confined within the disordered material. Here we present a new hierarchical scheme for several bone tissue types that incorporates these two materials. The new scheme updates the hierarchical scheme presented by Weiner and Wagner (1998). We discuss the structures at different hierarchical levels with the aim of obtaining further insights into structure-function-related questions, as well as defining some remaining unanswered questions.

1. Hierarchical Bayesian Models of Subtask Learning

ERIC Educational Resources Information Center

Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

2. Generic hierarchical engine for mask data preparation

Kalus, Christian K.; Roessl, Wolfgang; Schnitker, Uwe; Simecek, Michal

2002-07-01

Electronic layouts are usually flattened on their path from the hierarchical source downstream to the wafer. Mask data preparation has certainly been identified as a severe bottleneck since long. Data volumes are not only doubling every year along the ITRS roadmap. With the advent of optical proximity correction and phase-shifting masks data volumes are escalating up to non-manageable heights. Hierarchical treatment is one of the most powerful means to keep memory and CPU consumption in reasonable ranges. Only recently, however, has this technique acquired more public attention. Mask data preparation is the most critical area calling for a sound infrastructure to reduce the handling problem. Gaining more and more attention though, are other applications such as large area simulation and manufacturing rule checking (MRC). They all would profit from a generic engine capable to efficiently treat hierarchical data. In this paper we will present a generic engine for hierarchical treatment which solves the major problem, steady transitions along cell borders. Several alternatives exist how to walk through the hierarchy tree. They have, to date, not been thoroughly investigated. One is a bottom-up attempt to treat cells starting with the most elementary cells. The other one is a top-down approach which lends itself to creating a new hierarchy tree. In addition, since the variety, degree of hierarchy and quality of layouts extends over a wide range a generic engine has to take intelligent decisions when exploding the hierarchy tree. Several applications will be shown, in particular how far the limits can be pushed with the current hierarchical engine.

3. Hierarchical organisation in perception of orientation.

PubMed

Spinelli, D; Antonucci, G; Daini, R; Martelli, M L; Zoccolotti, P

1999-01-01

According to Rock [1990, in The Legacy of Solomon Asch (Hillsdale, NJ: Lawrence Erlbaum Associates)], hierarchical organisation of perception describes cases in which the orientation of an object is affected by the immediately surrounding elements in the visual field. Various experiments were performed to study the hierarchical organisation of orientation perception. In most of them the rod-and-frame-illusion (RFI: change of the apparent vertical measured on a central rod surrounded by a tilted frame) was measured in the presence/absence of a second inner frame. The first three experiments showed that, when the inner frame is vertical, the direction and size of the illusion are consistent with expectancies based on the hierarchical organisation hypothesis. An analysis of published and unpublished data collected on a large number of subjects showed that orientational hierarchical effects are independent from the absolute size of the RFI. In experiments 4 to 7 we examined the perceptual conditions of the inner stimulus (enclosure, orientation, and presence of luminance borders) critical for obtaining a hierarchical organisation effect. Although an inner vertical square was effective in reducing the illusion (experiment 3), an inner circle enclosing the rod was ineffective (experiment 4). This indicates that definite orientation is necessary to modulate the illusion. However, orientational information provided by a vertical or horizontal rectangle presented near the rod, but not enclosing it, did not modulate the RFI (experiment 5). This suggests that the presence of a figure with oriented contours enclosing the rod is critical. In experiments 6 and 7 we studied whether the presence of luminance borders is important or whether the inner upright square might be effective also if made of subjective contours. When the subjective contour figure was salient and the observers perceived it clearly, its effectiveness in modulating the RFI was comparable to that observed with

4. Nanotribological and wetting performance of hierarchical patterns.

PubMed

Grewal, H S; Piao, Shuxue; Cho, Il-Joo; Jhang, Kyung-Young; Yoon, Eui-Sung

2016-01-21

Surface modification is a promising method to solve the tribological problems in microsystems. To modify the surface, we fabricated hierarchical patterns with different pitches of nano-scale features and different surface chemistries. Micro- and nano-patterns with similar geometrical configurations were also fabricated for comparison. The nano-tribological behavior of the patterns was investigated using an atomic force microscope at different relative humidity levels (5% to 80%) and applied normal loads (40 nN to 120 nN) under a constant sliding velocity. The results showed significant enhancement in the de-wetting and tribological performance of the hierarchical patterns compared with those of flat and micro- and nano-patterned surfaces. The PTFE-coated hierarchical patterns showed similar dynamic contact angles (advancing and receding) to those of the real lotus leaf. The influence of relative humidity on adhesion and friction behavior was found to be significant for all the tested surfaces. The tribological performance was improved as the pitch of the nano-scale geometry of the hierarchical pattern increased, even though the wetting property was not influenced significantly. A model was proposed based on the role of intermolecular force to explain the effect of the pitch of the hierarchical patterns on the adhesion and friction behavior. According to the model based on the molecular force, the contact between a ball and the patterned surface was a multi-asperity contact, contrary to the single-asperity contact predicted by the Johnson-Kendall-Roberts (JKR) and Maugis-Dugdale (MD) models. The strong intermolecular forces, which are activated in the confined spaces between the adjacent nano-pillars and the ball, contributed to the contact area and hence the adhesion and friction forces.

5. A Study of Hierarchical Classification in Concrete and Formal Thought.

ERIC Educational Resources Information Center

Lowell, Walter E.

This researcher investigated the relationship of hierarchical classification processes in subjects categorized as to developmental level as defined by Piaget's theory, and explored the validity of the hierarchical model and test used in the study. A hierarchical classification test and a battery of four Piaget-type tasks were administered…

6. Incorporating Usability Criteria into the Development of Animated Hierarchical Maps

ERIC Educational Resources Information Center

Shih, Yu-Cheng; Huang, Pei-Ren; Chen, Sherry Y.

2013-01-01

Nowadays, Web-based learning systems have become popular because they can provide multiple tools, among which hierarchical maps are widely used to support teaching and learning. However, traditional hierarchical maps may let learners easily get lost within large information space. This study proposes an animated hierarchical map to address this…

7. Inference and Hierarchical Modeling in the Social Sciences.

ERIC Educational Resources Information Center

Draper, David

1995-01-01

The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)

8. Application of a hierarchical structure stochastic learning automation

NASA Technical Reports Server (NTRS)

Neville, R. G.; Chrystall, M. S.; Mars, P.

1979-01-01

A hierarchical structure automaton was developed using a two state stochastic learning automato (SLA) in a time shared model. Application of the hierarchical SLA to systems with multidimensional, multimodal performance criteria is described. Results of experiments performed with the hierarchical SLA using a performance index with a superimposed noise component of ? or - delta distributed uniformly over the surface are discussed.

9. Nonlinear inversion for wave fields monitoring data in hierarchic heterogeneous media

Hachay, Olga; Khachay, Andrey; Khachay, Oleg

2016-04-01

Geological medium is an open system which is influenced by outer and inner factors that can lead it to a unstable state. That non stability is as a rule occurred locally and these zones are named as dynamically active elements, which are indicators of potential catastrophic sources. These objects differ from the embedded geological medium by their structural forms, which often are of hierarchical type. The process of their activisation can be searched, using wave fields monitoring. For that purpose it is needed to develop new algorithms of modeling wave fields propagation through the local objects with hierarchical structure. Also it is needed to develop new theory of interpretation the distribution of wave fields for defining the contours of these local hierarchical objects. It had been constructed an algorithm for 3D modeling electromagnetic field for arbitrary type of source of excitation in N-layered medium with a hierarchic conductive intrusion, located in the layer number J. It had been constructed algorithms for 2D modeling of sound diffraction and linear polarized transversal seismic wave on an intrusion of hierarchic structure, located in the layer number J of N-layered elastic medium. We used the method of integral and integral-differential equations for a space frequency presentation of wave fields distribution. It is developed an algorithm for constructing the equation of theoretical inverse problem for 2-D electromagnetic field of E and H polarization and linear polarized longitudinal elastic wave by excitation of the N-layered conductive or elastic medium with hierarchic conductive or elastic inclusion located in the ν -th layer. From the theory it is obviously that for such complicated medium each wave field contains its own information about the inner structure of the hierarchical inclusion. Therefore it is needed to interpret the monitoring data for each wave field apart, and not mixes the data base. These results will be the base for constructing

10. A Hierarchical Control Architecture for a PEBB-Based ILC Marx Modulator

SciTech Connect

Macken, K.; Burkhart, C.; Larsen, R.; Nguyen, M.N.; Olsen, J.; /SLAC

2011-12-15

The idea of building power conversion systems around Power Electronic Building Blocks (PEBBs) was initiated by the U.S. Office of Naval Research in the mid 1990s. A PEBB-based design approach is advantageous in terms of power density, modularity, reliability, and serviceability. It is obvious that this approach has much appeal for pulsed power conversion including the International Linear Collider (ILC) klystron modulator application. A hierarchical control architecture has the inherent capability to support the integration of PEBBs. This has already been successfully demonstrated in a number of industrial applications in the recent past. This paper outlines the underlying concepts of a hierarchical control architecture for a PEBB-based Marx-topology ILC klystron modulator. The control in PEBB-based power conversion systems can be functionally partitioned into (three) hierarchical layers; system layer, application layer, and PEBB layer. This has been adopted here. Based on such a hierarchical partition, the interfaces are clearly identified and defined and, consequently, are easily characterised. A conceptual design of the hardware manager, executing low-level hardware oriented tasks, is detailed. In addition, the idea of prognostics is briefly discussed.

11. Hierarchical flexural strength of enamel: transition from brittle to damage-tolerant behaviour

PubMed Central

Bechtle, Sabine; Özcoban, Hüseyin; Lilleodden, Erica T.; Huber, Norbert; Schreyer, Andreas; Swain, Michael V.; Schneider, Gerold A.

2012-01-01

Hard, biological materials are generally hierarchically structured from the nano- to the macro-scale in a somewhat self-similar manner consisting of mineral units surrounded by a soft protein shell. Considerable efforts are underway to mimic such materials because of their structurally optimized mechanical functionality of being hard and stiff as well as damage-tolerant. However, it is unclear how different hierarchical levels interact to achieve this performance. In this study, we consider dental enamel as a representative, biological hierarchical structure and determine its flexural strength and elastic modulus at three levels of hierarchy using focused ion beam (FIB) prepared cantilevers of micrometre size. The results are compared and analysed using a theoretical model proposed by Jäger and Fratzl and developed by Gao and co-workers. Both properties decrease with increasing hierarchical dimension along with a switch in mechanical behaviour from linear-elastic to elastic-inelastic. We found Gao's model matched the results very well. PMID:22031729

12. Hierarchical multi-dimensional limiting strategy for correction procedure via reconstruction

Park, Jin Seok; Kim, Chongam

2016-03-01

Hierarchical multi-dimensional limiting process (MLP) is improved and extended for flux reconstruction or correction procedure via reconstruction (FR/CPR) on unstructured grids. MLP was originally developed in finite volume method (FVM) and it provides an accurate, robust and efficient oscillation-control mechanism in multiple dimensions for linear reconstruction. This limiting philosophy can be hierarchically extended into higher-order Pn approximation or reconstruction. The resulting algorithm is referred to as the hierarchical MLP and facilitates detailed capture of flow structures while maintaining formal order-of-accuracy in a smooth region and providing accurate non-oscillatory solutions across a discontinuous region. This algorithm was developed within modal DG framework, but it can also be formulated into a nodal framework, most notably the FR/CPR framework. Troubled-cells are detected by applying the MLP concept, and the final accuracy is determined by a projection procedure and the hierarchical MLP limiting step. Extensive numerical analyses and computations, ranging from two-dimensional to three-dimensional fluid systems, have demonstrated that the proposed limiting approach yields outstanding performances in capturing compressible inviscid and viscous flow features.

13. Failure of Tube Models to Predict the Linear Rheology of Star/Linear Blends

Hall, Ryan; Desai, Priyanka; Kang, Beomgoo; Katzarova, Maria; Huang, Qifan; Lee, Sanghoon; Chang, Taihyun; Venerus, David; Mays, Jimmy; Schieber, Jay; Larson, Ronald

We compare predictions of two of the most advanced versions of the tube model, namely the Hierarchical model by Wang et al. (J. Rheol. 54:223, 2010) and the BOB (branch-on-branch) model by Das et al. (J. Rheol. 50:207-234, 2006), against linear viscoelastic data on blends of monodisperse star and monodisperse linear polybutadiene polymers. The star was carefully synthesized/characterized by temperature gradient interaction chromatography, and rheological data in the high frequency region were obtained through time-temperature superposition. We found massive failures of both the Hierarchical and BOB models to predict the terminal relaxation behavior of the star/linear blends, despite their success in predicting the rheology of the pure star and pure linear. This failure occurred regardless of the choices made concerning constraint release, such as assuming arm retraction in fat or skinny tubes, or allowing for disentanglement relaxation to cut off the constraint release Rouse process at long times. The failures call into question whether constraint release can be described as a combination of constraint release Rouse processes and dynamic tube dilation within a canonical tube model of entanglement interactions.

14. Soluble ST2 Levels and Left Ventricular Structure and Function in Patients With Metabolic Syndrome

PubMed Central

Celic, Vera; Majstorovic, Anka; Pencic-Popovic, Biljana; Sljivic, Aleksandra; Lopez-Andres, Natalia; Roy, Ignacio; Escribano, Elena; Beunza, Maite; Melero, Amaia; Floridi, Federico; Magrini, Laura; Marino, Rossella; Salerno, Gerardo; Cardelli, Patrizia

2016-01-01

Background A biomarker that is of great interest in relation to adverse cardiovascular events is soluble ST2 (sST2), a member of the interleukin family. Considering that metabolic syndrome (MetS) is accompanied by a proinflammatory state, we aimed to assess the relationship between sST2 and left ventricular (LV) structure and function in patients with MetS. Methods A multicentric, cross-sectional study was conducted on180 MetS subjects with normal LV ejection fraction as determined by echocardiography. LV hypertrophy (LVH) was defined as an LV mass index greater than the gender-specific upper limit of normal as determined by echocardiography. LV diastolic dysfunction (DD) was assessed by pulse-wave and tissue Doppler imaging. sST2 was measured by using a quantitative monoclonal ELISA assay. Results LV mass index (β=0.337, P<0.001, linear regression) was independently associated with sST2 concentrations. Increased sST2 was associated with an increased likelihood of LVH [Exp (B)=2.20, P=0.048, logistic regression] and increased systolic blood pressure [Exp (B)=1.02, P=0.05, logistic regression]. Comparing mean sST2 concentrations (adjusted for age, body mass index, gender) between different LV remodeling patterns, we found the greatest sST2 level in the group with concentric hypertrophy. There were no differences in sST2 concentration between groups with and without LV DD. Conclusions Increased sST2 concentration in patients with MetS was associated with a greater likelihood of exhibiting LVH. Our results suggest that inflammation could be one of the principal triggering mechanisms for LV remodeling in MetS. PMID:27578507

15. On the geostatistical characterization of hierarchical media

Neuman, Shlomo P.; Riva, Monica; Guadagnini, Alberto

2008-02-01

The subsurface consists of porous and fractured materials exhibiting a hierarchical geologic structure, which gives rise to systematic and random spatial and directional variations in hydraulic and transport properties on a multiplicity of scales. Traditional geostatistical moment analysis allows one to infer the spatial covariance structure of such hierarchical, multiscale geologic materials on the basis of numerous measurements on a given support scale across a domain or "window" of a given length scale. The resultant sample variogram often appears to fit a stationary variogram model with constant variance (sill) and integral (spatial correlation) scale. In fact, some authors, who recognize that hierarchical sedimentary architecture and associated log hydraulic conductivity fields tend to be nonstationary, nevertheless associate them with stationary "exponential-like" transition probabilities and variograms, respectively, the latter being a consequence of the former. We propose that (1) the apparent ability of stationary spatial statistics to characterize the covariance structure of nonstationary hierarchical media is an artifact stemming from the finite size of the windows within which geologic and hydrologic variables are ubiquitously sampled, and (2) the artifact is eliminated upon characterizing the covariance structure of such media with the aid of truncated power variograms, which represent stationary random fields obtained upon sampling a nonstationary fractal over finite windows. To support our opinion, we note that truncated power variograms arise formally when a hierarchical medium is sampled jointly across all geologic categories and scales within a window; cite direct evidence that geostatistical parameters (variance and integral scale) inferred on the basis of traditional variograms vary systematically with support and window scales; demonstrate the ability of truncated power models to capture these variations in terms of a few scaling parameters

16. Hierarchical 3-dimensional nickel-iron nanosheet arrays on carbon fiber paper as a novel electrode for non-enzymatic glucose sensing.

PubMed

Kannan, Palanisamy; Maiyalagan, Thandavarayan; Marsili, Enrico; Ghosh, Srabanti; Niedziolka-Jönsson, Joanna; Jönsson-Niedziolka, Martin

2016-01-14

Three-dimensional nickel-iron (3-D/Ni-Fe) nanostructures are exciting candidates for various applications because they produce more reaction-active sites than 1-D and 2-D nanostructured materials and exhibit attractive optical, electrical and catalytic properties. In this work, freestanding 3-D/Ni-Fe interconnected hierarchical nanosheets, hierarchical nanospheres, and porous nanospheres are directly grown on a flexible carbon fiber paper (CFP) substrate by a single-step hydrothermal process. Among the nanostructures, 3-D/Ni-Fe interconnected hierarchical nanosheets show excellent electrochemical properties because of its high conductivity, large specific active surface area, and mesopores on its walls (vide infra). The 3-D/Ni-Fe hierarchical nanosheet array modified CFP substrate is further explored as a novel electrode for electrochemical non-enzymatic glucose sensor application. The 3-D/Ni-Fe hierarchical nanosheet arrays exhibit significant catalytic activity towards the electrochemical oxidation of glucose, as compared to the 3-D/Ni-Fe hierarchical nanospheres, and porous nanospheres. The 3-D/Ni-Fe hierarchical nanosheet arrays can access a large amount of glucose molecules on their surface (mesopore walls) for an efficient electrocatalytic oxidation process. Moreover, 3-D/Ni-Fe hierarchical nanosheet arrays showed higher sensitivity (7.90 μA μM(-1) cm(-2)) with wide linear glucose concentration ranging from 0.05 μM to 0.2 mM, and the low detection limit (LOD) of 0.031 μM (S/N = 3) is achieved by the amperometry method. Further, the 3-D/Ni-Fe hierarchical nanosheet array modified CFP electrode can be demonstrated to have excellent selectivity towards the detection of glucose in the presence of 500-fold excess of major important interferents. All these results indicate that 3-D/Ni-Fe hierarchical nanosheet arrays are promising candidates for non-enzymatic glucose sensing.

17. Biomimetic silicification of demineralized hierarchical collagenous tissues

PubMed Central

Ryou, Heonjune; Diogenes, Anibal; Yiu, Cynthia K.Y.; Mazzoni, Annalisa; Chen, Ji-hua; Arola, Dwayne D.; Hargreaves, Kenneth M.; Pashley, David H.; Tay, Franklin R.

2013-01-01

Unlike man-made composite materials, natural biominerals containing composites usually demonstrate different levels of sophisticated hierarchical structures which are responsible for their mechanical properties and other metabolic functions. However, the complex spatial organizations of the organic-inorganic phases are far beyond what they be achieved by contemporary engineering techniques. Here, we demonstrate that carbonated apatite present in collagen matrices derived from fish scale and bovine bone may be replaced by amorphous silica, using an approach that simulates what is utilized by phylogenetically ancient glass sponges. The structural hierarchy of these collagen-based biomaterials is replicated by the infiltration and condensation of fluidic polymer-stabilized silicic acid precursors within the intrafibrillar milieu of type I collagen fibrils. This facile biomimetic silicification strategy may be used for fabricating silica-based, three-dimensional functional materials with specific morphological and hierarchical requirements. PMID:23586938

18. Design of Hierarchical Structures for Synchronized Deformations

PubMed Central

Seifi, Hamed; Javan, Anooshe Rezaee; Ghaedizadeh, Arash; Shen, Jianhu; Xu, Shanqing; Xie, Yi Min

2017-01-01

In this paper we propose a general method for creating a new type of hierarchical structures at any level in both 2D and 3D. A simple rule based on a rotate-and-mirror procedure is introduced to achieve multi-level hierarchies. These new hierarchical structures have remarkably few degrees of freedom compared to existing designs by other methods. More importantly, these structures exhibit synchronized motions during opening or closure, resulting in uniform and easily-controllable deformations. Furthermore, a simple analytical formula is found which can be used to avoid collision of units of the structure during the closing process. The novel design concept is verified by mathematical analyses, computational simulations and physical experiments. PMID:28117427

19. Hierarchical model of vulnerabilities for emotional disorders.

PubMed

Norton, Peter J; Mehta, Paras D

2007-01-01

Clark and Watson's (1991) tripartite model of anxiety and depression has had a dramatic impact on our understanding of the dispositional variables underlying emotional disorders. More recently, calls have been made to examine not simply the influence of negative affectivity (NA) but also mediating factors that might better explain how NA influences anxious and depressive syndromes (e.g. Taylor, 1998; Watson, 2005). Extending preliminary projects, this study evaluated two hierarchical models of NA, mediating factors of anxiety sensitivity and intolerance of uncertainty, and specific emotional manifestations. Data provided a very good fit to a model elaborated from preliminary studies, lending further support to hierarchical models of emotional vulnerabilities. Implications for classification and diagnosis are discussed.

20. Contour detection and hierarchical image segmentation.

PubMed

Arbeláez, Pablo; Maire, Michael; Fowlkes, Charless; Malik, Jitendra

2011-05-01

This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

1. Multiple sequence alignment with hierarchical clustering.

PubMed Central

Corpet, F

1988-01-01

An algorithm is presented for the multiple alignment of sequences, either proteins or nucleic acids, that is both accurate and easy to use on microcomputers. The approach is based on the conventional dynamic-programming method of pairwise alignment. Initially, a hierarchical clustering of the sequences is performed using the matrix of the pairwise alignment scores. The closest sequences are aligned creating groups of aligned sequences. Then close groups are aligned until all sequences are aligned in one group. The pairwise alignments included in the multiple alignment form a new matrix that is used to produce a hierarchical clustering. If it is different from the first one, iteration of the process can be performed. The method is illustrated by an example: a global alignment of 39 sequences of cytochrome c. PMID:2849754

2. An Hierarchical approach to Big Data

Allen, Mark G.; Fernique, Pierre

2015-08-01

The increasing volumes of astronomical data require practical methods for data access, visualisation and analysis. Hierarchical methods based on sky tessellation techniques enable a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. The Hierarchical Progressive Survey (HiPS) scheme based on the HEALPix is able to describe images, catalogues and 3-dimensional data cubes and is a practical solution for managing large volumes of heterogeneous data. We present the development of HiPS, and its implementation for ~200 diverse data sets at the CDS and other data centres. We highlight the ease of implementation and the use of HiPS with Aladin Lite and other applications.

3. Hierarchical clustering in minimum spanning trees.

PubMed

Yu, Meichen; Hillebrand, Arjan; Tewarie, Prejaas; Meier, Jil; van Dijk, Bob; Van Mieghem, Piet; Stam, Cornelis Jan

2015-02-01

The identification of clusters or communities in complex networks is a reappearing problem. The minimum spanning tree (MST), the tree connecting all nodes with minimum total weight, is regarded as an important transport backbone of the original weighted graph. We hypothesize that the clustering of the MST reveals insight in the hierarchical structure of weighted graphs. However, existing theories and algorithms have difficulties to define and identify clusters in trees. Here, we first define clustering in trees and then propose a tree agglomerative hierarchical clustering (TAHC) method for the detection of clusters in MSTs. We then demonstrate that the TAHC method can detect clusters in artificial trees, and also in MSTs of weighted social networks, for which the clusters are in agreement with the previously reported clusters of the original weighted networks. Our results therefore not only indicate that clusters can be found in MSTs, but also that the MSTs contain information about the underlying clusters of the original weighted network.

4. Design of Hierarchical Structures for Synchronized Deformations

Seifi, Hamed; Javan, Anooshe Rezaee; Ghaedizadeh, Arash; Shen, Jianhu; Xu, Shanqing; Xie, Yi Min

2017-01-01

In this paper we propose a general method for creating a new type of hierarchical structures at any level in both 2D and 3D. A simple rule based on a rotate-and-mirror procedure is introduced to achieve multi-level hierarchies. These new hierarchical structures have remarkably few degrees of freedom compared to existing designs by other methods. More importantly, these structures exhibit synchronized motions during opening or closure, resulting in uniform and easily-controllable deformations. Furthermore, a simple analytical formula is found which can be used to avoid collision of units of the structure during the closing process. The novel design concept is verified by mathematical analyses, computational simulations and physical experiments.

5. Noise enhances information transfer in hierarchical networks.

PubMed

Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

6. Noise enhances information transfer in hierarchical networks

PubMed Central

Czaplicka, Agnieszka; Holyst, Janusz A.; Sloot, Peter M. A.

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor. PMID:23390574

7. Object tracking with hierarchical multiview learning

Yang, Jun; Zhang, Shunli; Zhang, Li

2016-09-01

Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

8. Hierarchical networks, power laws, and neuronal avalanches.

PubMed

Friedman, Eric J; Landsberg, Adam S

2013-03-01

We show that in networks with a hierarchical architecture, critical dynamical behaviors can emerge even when the underlying dynamical processes are not critical. This finding provides explicit insight into current studies of the brain's neuronal network showing power-law avalanches in neural recordings, and provides a theoretical justification of recent numerical findings. Our analysis shows how the hierarchical organization of a network can itself lead to power-law distributions of avalanche sizes and durations, scaling laws between anomalous exponents, and universal functions-even in the absence of self-organized criticality or critical points. This hierarchy-induced phenomenon is independent of, though can potentially operate in conjunction with, standard dynamical mechanisms for generating power laws.

9. Hierarchical clustering in minimum spanning trees

Yu, Meichen; Hillebrand, Arjan; Tewarie, Prejaas; Meier, Jil; van Dijk, Bob; Van Mieghem, Piet; Stam, Cornelis Jan

2015-02-01

The identification of clusters or communities in complex networks is a reappearing problem. The minimum spanning tree (MST), the tree connecting all nodes with minimum total weight, is regarded as an important transport backbone of the original weighted graph. We hypothesize that the clustering of the MST reveals insight in the hierarchical structure of weighted graphs. However, existing theories and algorithms have difficulties to define and identify clusters in trees. Here, we first define clustering in trees and then propose a tree agglomerative hierarchical clustering (TAHC) method for the detection of clusters in MSTs. We then demonstrate that the TAHC method can detect clusters in artificial trees, and also in MSTs of weighted social networks, for which the clusters are in agreement with the previously reported clusters of the original weighted networks. Our results therefore not only indicate that clusters can be found in MSTs, but also that the MSTs contain information about the underlying clusters of the original weighted network.

10. Hierarchical Robot Control In A Multisensor Environment

Bhanu, Bir; Thune, Nils; Lee, Jih Kun; Thune, Mari

1987-03-01

Automatic recognition, inspection, manipulation and assembly of objects will be a common denominator in most of tomorrow's highly automated factories. These tasks will be handled by intelligent computer controlled robots with multisensor capabilities which contribute to desired flexibility and adaptability. The control of a robot in such a multisensor environment becomes of crucial importance as the complexity of the problem grows exponentially with the number of sensors, tasks, commands and objects. In this paper we present an approach which uses CAD (Computer-Aided Design) based geometric and functional models of objects together with action oriented neuroschemas to recognize and manipulate objects by a robot in a multisensor environment. The hierarchical robot control system is being implemented on a BBN Butterfly multi processor. Index terms: CAD, Hierarchical Control, Hypothesis Generation and Verification, Parallel Processing, Schemas

11. Hierarchical abstract semantic model for image classification

Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

2015-09-01

Semantic gap limits the performance of bag-of-visual-words. To deal with this problem, a hierarchical abstract semantics method that builds abstract semantic layers, generates semantic visual vocabularies, measures semantic gap, and constructs classifiers using the Adaboost strategy is proposed. First, abstract semantic layers are proposed to narrow the semantic gap between visual features and their interpretation. Then semantic visual words are extracted as features to train semantic classifiers. One popular form of measurement is used to quantify the semantic gap. The Adaboost training strategy is used to combine weak classifiers into strong ones to further improve performance. For a testing image, the category is estimated layer-by-layer. Corresponding abstract hierarchical structures for popular datasets, including Caltech-101 and MSRC, are proposed for evaluation. The experimental results show that the proposed method is capable of narrowing semantic gaps effectively and performs better than other categorization methods.

12. Hierarchical structure of the logical Internet graph

Ge, Zihui; Figueiredo, Daniel R.; Jaiswal, Sharad; Gao, Lixin

2001-07-01

The study of the Internet topology has recently received much attention from the research community. In particular, the observation that the network graph has interesting properties, such as power laws, that might be explored in a myriad of ways. Most of the work in characterizing the Internet graph is based on the physical network graph, i.e., the connectivity graph. In this paper we investigate how logical relationships between nodes of the AS graph can be used to gain insight to its structure. We characterize the logical graph using various metrics and identify the presence of power laws in the number of customers that a provider has. Using these logical relationships we define a structural model of the AS graph. The model highlights the hierarchical nature of logical relationships and the preferential connection to larger providers. We also investigate the consistency of this model over time and observe interesting properties of the hierarchical structure.

13. Hierarchical porous polymer scaffolds from block copolymers.

PubMed

Sai, Hiroaki; Tan, Kwan Wee; Hur, Kahyun; Asenath-Smith, Emily; Hovden, Robert; Jiang, Yi; Riccio, Mark; Muller, David A; Elser, Veit; Estroff, Lara A; Gruner, Sol M; Wiesner, Ulrich

2013-08-02

Hierarchical porous polymer materials are of increasing importance because of their potential application in catalysis, separation technology, or bioengineering. Examples for their synthesis exist, but there is a need for a facile yet versatile conceptual approach to such hierarchical scaffolds and quantitative characterization of their nonperiodic pore systems. Here, we introduce a synthesis method combining well-established concepts of macroscale spinodal decomposition and nanoscale block copolymer self-assembly with porosity formation on both length scales via rinsing with protic solvents. We used scanning electron microscopy, small-angle x-ray scattering, transmission electron tomography, and nanoscale x-ray computed tomography for quantitative pore-structure characterization. The method was demonstrated for AB- and ABC-type block copolymers, and resulting materials were used as scaffolds for calcite crystal growth.

14. Neural decoding with hierarchical generative models.

PubMed

van Gerven, Marcel A J; de Lange, Floris P; Heskes, Tom

2010-12-01

Recent research has shown that reconstruction of perceived images based on hemodynamic response as measured with functional magnetic resonance imaging (fMRI) is starting to become feasible. In this letter, we explore reconstruction based on a learned hierarchy of features by employing a hierarchical generative model that consists of conditional restricted Boltzmann machines. In an unsupervised phase, we learn a hierarchy of features from data, and in a supervised phase, we learn how brain activity predicts the states of those features. Reconstruction is achieved by sampling from the model, conditioned on brain activity. We show that by using the hierarchical generative model, we can obtain good-quality reconstructions of visual images of handwritten digits presented during an fMRI scanning session.

15. Hierarchical optimization for neutron scattering problems

DOE PAGES

Bao, Feng; Archibald, Rick; Bansal, Dipanshu; ...

2016-03-14

In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

16. Hierarchical Bayesian Approach to Locating Seismic Events

SciTech Connect

Johannesson, G; Myers, S C; Hanley, W G

2005-11-09

We propose a hierarchical Bayesian model for conducting inference on the location of multiple seismic events (earthquakes) given data on the arrival of various seismic phases to sensor locations. The model explicitly accounts for the uncertainty associated with a theoretical seismic-wave travel-time model used along with the uncertainty of the arrival data. Posterior inferences is carried out using Markov chain Monte Carlo (MCMC).

17. Megavariate analysis of hierarchical QSAR data

Eriksson, Lennart; Johansson, Erik; Lindgren, Fredrik; Sjöström, Michael; Wold, Svante

2002-10-01

Multivariate PCA- and PLS-models involving many variables are often difficult to interpret, because plots and lists of loadings, coefficients, VIPs, etc, rapidly become messy and hard to overview. There may then be a strong temptation to eliminate variables to obtain a smaller data set. Such a reduction of variables, however, often removes information and makes the modelling efforts less reliable. Model interpretation may be misleading and predictive power may deteriorate. A better alternative is usually to partition the variables into blocks of logically related variables and apply hierarchical data analysis. Such blocked data may be analyzed by PCA and PLS. This modelling forms the base-level of the hierarchical modelling set-up. On the base-level in-depth information is extracted for the different blocks. The score vectors formed on the base-level, here called `super variables', may be linked together in new matrices on the top-level. On the top-level superficial relationships between the X- and the Y-data are investigated. In this paper the basic principles of hierarchical modelling by means of PCA and PLS are reviewed. One objective of the paper is to disseminate this concept to a broader QSAR audience. The hierarchical methods are used to analyze a set of 10 haloalkanes for which K = 30 chemical descriptors and M = 255 biological responses have been gathered. Due to the complexity of the biological data, they are sub-divided in four blocks. All the modelling steps on the base-level and the top-level are reported and the final QSAR model is interpreted thoroughly.

18. Hierarchical video summarization based on context clustering

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.

19. Angelic Hierarchical Planning: Optimal and Online Algorithms

DTIC Science & Technology

2008-12-06

describe an alternative “satisficing” algorithm, AHSS . 4.1 Abstract Lookahead Trees Our ALT data structures support our search algorithms by efficiently...Angelic Hierarchical Satisficing Search ( AHSS ), which at- tempts to find a plan that reaches the goal with at most some pre-specified cost α. AHSS can be...much more efficient than AHA*, since it can commit to a plan without first proving its optimality. At each step, AHSS (see Algorithm 3) begins by

20. Hierarchical optimization for neutron scattering problems

SciTech Connect

Bao, Feng; Archibald, Rick; Bansal, Dipanshu; Delaire, Olivier

2016-06-15

We present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

1. Modular, Hierarchical Learning By Artificial Neural Networks

NASA Technical Reports Server (NTRS)

1996-01-01

Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

2. Hierarchical structure of Turkey's foreign trade

Kantar, Ersin; Deviren, Bayram; Keskin, Mustafa

2011-10-01

We examine the hierarchical structures of Turkey's foreign trade by using real prices of their commodity export and import move together over time. We obtain the topological properties among the countries based on Turkey's foreign trade during the 1996-2010 period by using the concept of hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)). These periods are divided into two subperiods, such as 1996-2002 and 2003-2010, in order to test various time-window and observe the temporal evolution. We perform the bootstrap techniques to investigate a value of the statistical reliability to the links of the MSTs and HTs. We also use a clustering linkage procedure in order to observe the cluster structure much better. From the structural topologies of these trees, we identify different clusters of countries according to their geographical location and economic ties. Our results show that the DE (Germany), UK (United Kingdom), FR (France), IT (Italy) and RU (Russia) are more important within the network, due to a tighter connection with other countries. We have also found that these countries play a significant role for Turkey's foreign trade and have important implications for the design of portfolio and investment strategies.

3. Resilient 3D hierarchical architected metamaterials.

PubMed

Meza, Lucas R; Zelhofer, Alex J; Clarke, Nigel; Mateos, Arturo J; Kochmann, Dennis M; Greer, Julia R

2015-09-15

Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic-polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥ 50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property.

4. Exploring hierarchical visualization designs using phylogenetic trees

Li, Shaomeng; Crouser, R. Jordan; Griffin, Garth; Gramazio, Connor; Schulz, Hans-Jörg; Childs, Hank; Chang, Remco

2015-01-01

Ongoing research on information visualization has produced an ever-increasing number of visualization designs. Despite this activity, limited progress has been made in categorizing this large number of information visualizations. This makes understanding their common design features challenging, and obscures the yet unexplored areas of novel designs. With this work, we provide categorization from an evolutionary perspective, leveraging a computational model to represent evolutionary processes, the phylogenetic tree. The result - a phylogenetic tree of a design corpus of hierarchical visualizations - enables better understanding of the various design features of hierarchical information visualizations, and further illuminates the space in which the visualizations lie, through support for interactive clustering and novel design suggestions. We demonstrate these benefits with our software system, where a corpus of two-dimensional hierarchical visualization designs is constructed into a phylogenetic tree. This software system supports visual interactive clustering and suggesting for novel designs; the latter capacity is also demonstrated via collaboration with an artist who sketched new designs using our system.

5. Cluster assembly in hierarchically collapsing molecular clouds

2015-08-01

I will discuss the mechanism of cluster formation in hierarchically collapsing molecular clouds. Recent evidence, both observational and numerical, suggests that molecular clouds (MCs) may be undergoing global, hierarchical gravitational collapse. The "hierarchical" regime consists of small-scale collapses within larger-scale ones. The former occur in a more scattered fashion and at slightly earlier times, and are themselves falling into the larger potential well of the still-ongoing large-scale collapse. Instead, the large-scale collapse culminates a few Myr later, in a highly focused region, of higher density, mass, and velocity dispersion. The stars formed in the early, small-scale collapses share the infall velocity of their parent clumps towards the larger potential trough, while those formed later, in the aforementioned trough, form from gas that has already dissipated some of its kinetic energy, and thus have a lower velocity dispersion. This leads to a radial age gradient in the stellar population, in agreement with recent observations.

6. A Hierarchical Approach to Buckling Load Calculations

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.; Nemeth, Michael P.

1999-01-01

The advantages of using a hierarchical analysis approach to calculate the buckling load of an axially compressed composite cylindrical shell is demonstrated using an example taken from a recent experimental program. The Delft Interactive Shell DEsign COde (DISDECO) shell design code is used for this hierarchical analysis approach to provide an accurate prediction of the critical buckling load of the actual shell structure. DISDECO includes the influence of the boundary conditions, initial geometric imperfections, the effects of stiffener and load eccentricities, and the effects of prebuckling deformations caused by edge constraints in the analysis. It is shown that the use of DISDECO makes it relatively simple to proceed step by step from simple to more complex models and solution procedures. As a final step in the hierarchical analysis approach, the critical buckling load and the estimated imperfection sensitivity of the shell are verified by conducting an analysis of a large finite element model with one of the current generation two-dimensional shell analysis codes with advanced capabilities needed to represent both geometric and material nonlinearities.

7. Hierarchically Structured Materials for Lithium Batteries

SciTech Connect

Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Jiguang

2013-09-25

Lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles (EV), including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electrical vehicles. With the increasing demand on devices of high energy densities (>500 Wh/kg) , new energy storage systems, such as lithium-oxygen (Li-O2) batteries and other emerging systems beyond the conventional LIB also attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performances of these energy storage systems depend not only on the composition of the materials, but also on the structure of electrode materials used in the batteries. Although the desired performances characteristics of batteries often have conflict requirements on the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflict requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li-O2 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, prolongs the electrode stability and battery lifetime.

8. Anisotropic and Hierarchical Porosity in Multifunctional Ceramics

Lichtner, Aaron Zev

The performance of multifunctional porous ceramics is often hindered by the seemingly contradictory effects of porosity on both mechanical and non-structural properties and yet a sufficient body of knowledge linking microstructure to these properties does not exist. Using a combination of tailored anisotropic and hierarchical materials, these disparate effects may be reconciled. In this project, a systematic investigation of the processing, characterization and properties of anisotropic and isotropic hierarchically porous ceramics was conducted. The system chosen was a composite ceramic intended as the cathode for a solid oxide fuel cell (SOFC). Comprehensive processing investigations led to the development of approaches to make hierarchical, anisotropic porous microstructures using directional freeze-casting of well dispersed slurries. The effect of all the important processing parameters was investigated. This resulted in an ability to tailor and control the important microstructural features including the scale of the microstructure, the macropore size and total porosity. Comparable isotropic porous ceramics were also processed using fugitive pore formers. A suite of characterization techniques including x-ray tomography and 3-D sectional scanning electron micrographs (FIB-SEM) was used to characterize and quantify the green and partially sintered microstructures. The effect of sintering temperature on the microstructure was quantified and discrete element simulations (DEM) were used to explain the experimental observations. Finally, the comprehensive mechanical properties, at room temperature, were investigated, experimentally and using DEM, for the different microstructures.

9. Resilient 3D hierarchical architected metamaterials

PubMed Central

Meza, Lucas R.; Zelhofer, Alex J.; Clarke, Nigel; Mateos, Arturo J.; Kochmann, Dennis M.; Greer, Julia R.

2015-01-01

Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic–polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property. PMID:26330605

10. Hierarchical image classification in the bioscience literature.

PubMed

Kim, Daehyun; Yu, Hong

2009-11-14

Our previous work has shown that images appearing in bioscience articles can be classified into five types: Gel-Image, Image-of-Thing, Graph, Model, and Mix. For this paper, we explored and analyzed features strongly associated with each image type and developed a hierarchical image classification approach for classifying an image into one of the five types. First, we applied texture features to separate images into two groups: 1) a texture group comprising Gel Image, Image-of-Thing, and Mix, and 2) a non-texture group comprising Graph and Model. We then applied entropy, skewness, and uniformity for the first group, and edge difference, uniformity, and smoothness for the second group to classify images into specific types. Our results show that hierarchical image classification accurately divided images into the two groups during the initial classification and that the overall accuracy of the image classification was higher than that of our previous approach. In particular, the recall of hierarchical image classification was greatly improved due to the high accuracy of the initial classification.

11. Metal hierarchical patterning by direct nanoimprint lithography

PubMed Central

Radha, Boya; Lim, Su Hui; Saifullah, Mohammad S. M.; Kulkarni, Giridhar U.

2013-01-01

Three-dimensional hierarchical patterning of metals is of paramount importance in diverse fields involving photonics, controlling surface wettability and wearable electronics. Conventionally, this type of structuring is tedious and usually involves layer-by-layer lithographic patterning. Here, we describe a simple process of direct nanoimprint lithography using palladium benzylthiolate, a versatile metal-organic ink, which not only leads to the formation of hierarchical patterns but also is amenable to layer-by-layer stacking of the metal over large areas. The key to achieving such multi-faceted patterning is hysteretic melting of ink, enabling its shaping. It undergoes transformation to metallic palladium under gentle thermal conditions without affecting the integrity of the hierarchical patterns on micro- as well as nanoscale. A metallic rice leaf structure showing anisotropic wetting behavior and woodpile-like structures were thus fabricated. Furthermore, this method is extendable for transferring imprinted structures to a flexible substrate to make them robust enough to sustain numerous bending cycles. PMID:23446801

12. Hierarchical models of animal abundance and occurrence

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.

2006-01-01

Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

13. Hierarchically structured materials for lithium batteries

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

2013-10-01

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-O2) 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-O2 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.

14. Advanced Non-Linear Control Algorithms Applied to Design Highly Maneuverable Autonomous Underwater Vehicles (AUVs)

DTIC Science & Technology

2007-08-01

Advanced non- linear control algorithms applied to design highly maneuverable Autonomous Underwater Vehicles (AUVs) Vladimir Djapic, Jay A. Farrell...hierarchical such that an ”inner loop” non- linear controller (outputs the appropriate thrust values) is the same for all mission scenarios while a...library of ”outer-loop” non- linear controllers are available to implement specific maneuvering scenarios. On top of the outer-loop is the mission planner

15. A Hierarchical Bayesian Model to Quantify Uncertainty of Stream Water Temperature Forecasts

PubMed Central

Bal, Guillaume; Rivot, Etienne; Baglinière, Jean-Luc; White, Jonathan; Prévost, Etienne

2014-01-01

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. PMID:25541732

16. NLMEM: a new SAS/IML macro for hierarchical nonlinear models.

PubMed

Galecki, A T

1998-03-01

Analysis of longitudinal data is one of the most challenging tasks in statistical modeling. In the analysis, it is often necessary to take into account nonlinear response to a set of parameters of interest and correlation between measurements taken from the same individual. In addition, between- and within-subject variation has to be handled properly. An example of addressing these issues is the hierarchical nonlinear model, where parameter estimation can be performed using linearization method. In this paper a new NLMEM SAS/IML macro for hierarchical nonlinear models is proposed. The program uses a portion of the code developed earlier in NLINMIX. NLMEM retains all the benefits of NLINMIX while allowing the systematic part of the model structure to be specified using IML syntax. Consequently, NLMEM allows estimation of models which are not tractable using NLINMIX. In particular, it allows us to address advanced population pharmacokinetics and pharmacodynamics models specified by ordinary differential equations.

17. Hierarchical Bayes Ensemble Kalman Filter for geophysical data assimilation

Tsyrulnikov, Michael; Rakitko, Alexander

2016-04-01

In the Ensemble Kalman Filter (EnKF), the forecast error covariance matrix B is estimated from a sample (ensemble), which inevitably implies a degree of uncertainty. This uncertainty is especially large in high dimensions, where the affordable ensemble size is orders of magnitude less than the dimensionality of the system. Common remedies include ad-hoc devices like variance inflation and covariance localization. The goal of this study is to optimize the account for the inherent uncertainty of the B matrix in EnKF. Following the idea by Myrseth and Omre (2010), we explicitly admit that the B matrix is unknown and random and estimate it along with the state (x) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components P and Q of the B matrix into the extended control vector (x,P,Q). Similarly, we break the traditional forecast ensemble into the predictability-error related ensemble and model-error related ensemble. The reason for the separation of model errors from predictability errors is the fundamental difference between the two sources of error. Model error are external (i.e. do not depend on the filter's performance) whereas predictability errors are internal to a filter (i.e. are determined by the filter's behavior). At the analysis step, we specify Inverse Wishart based priors for the random matrices P and Q and conditionally Gaussian prior for the state x. Then, we update the prior distribution of (x,P,Q) using both observation and ensemble data, so that ensemble members are used as generalized observations and ordinary observations are allowed to influence the covariances. We show that for linear dynamics and linear observation operators, conditional Gaussianity of the state is preserved in the course of filtering. At the forecast

18. Hierarchical Naive Bayes for genetic association studies

PubMed Central

2012-01-01

Background Genome Wide Association Studies represent powerful approaches that aim at disentangling the genetic and molecular mechanisms underlying complex traits. The usual "one-SNP-at-the-time" testing strategy cannot capture the multi-factorial nature of this kind of disorders. We propose a Hierarchical Naïve Bayes classification model for taking into account associations in SNPs data characterized by Linkage Disequilibrium. Validation shows that our model reaches classification performances superior to those obtained by the standard Naïve Bayes classifier for simulated and real datasets. Methods In the Hierarchical Naïve Bayes implemented, the SNPs mapping to the same region of Linkage Disequilibrium are considered as "details" or "replicates" of the locus, each contributing to the overall effect of the region on the phenotype. A latent variable for each block, which models the "population" of correlated SNPs, can be then used to summarize the available information. The classification is thus performed relying on the latent variables conditional probability distributions and on the SNPs data available. Results The developed methodology has been tested on simulated datasets, each composed by 300 cases, 300 controls and a variable number of SNPs. Our approach has been also applied to two real datasets on the genetic bases of Type 1 Diabetes and Type 2 Diabetes generated by the Wellcome Trust Case Control Consortium. Conclusions The approach proposed in this paper, called Hierarchical Naïve Bayes, allows dealing with classification of examples for which genetic information of structurally correlated SNPs are available. It improves the Naïve Bayes performances by properly handling the within-loci variability. PMID:23095471

19. Extensions to Real-time Hierarchical Mine Detection Algorithm

DTIC Science & Technology

2002-09-01

Extensions to Real-Time Hierarchical Mine Detection Algorithm System Number: Patron Number: Requester: Notes: DSIS Use only: Deliver to: DK...Recherche et developpement pour Ia defense Canada Extensions to Real-Time Hierarchical Mine Detection Algorithm Final Report Sinh Duong and Mabo R. Ito...EXTENSIONS TO REAL-TIME HIERARCHICAL MINE DETECTION ALGORITHM FINAL REPORT by Smh Duong and Mabo R Ito The Univer~ity of Bntl~h Columbia Vancouver

20. Structural analysis of hierarchically organized zeolites

PubMed Central

Mitchell, Sharon; Pinar, Ana B.; Kenvin, Jeffrey; Crivelli, Paolo; Kärger, Jörg; Pérez-Ramírez, Javier

2015-01-01

Advances in materials synthesis bring about many opportunities for technological applications, but are often accompanied by unprecedented complexity. This is clearly illustrated by the case of hierarchically organized zeolite catalysts, a class of crystalline microporous solids that has been revolutionized by the engineering of multilevel pore architectures, which combine unique chemical functionality with efficient molecular transport. Three key attributes, the crystal, the pore and the active site structure, can be expected to dominate the design process. This review examines the adequacy of the palette of techniques applied to characterize these distinguishing features and their catalytic impact. PMID:26482337

1. Constructing storyboards based on hierarchical clustering analysis

Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

2005-07-01

There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

2. Hierarchical multisensor analysis for robotic exploration

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi; Majani, Eric

1991-01-01

Robotic vehicles for lunar and Mars exploration will carry an array of complex instruments requiring real-time data interpretation and fusion. The system described here uses hierarchical multiresolution analysis of visible and multispectral images to extract information on mineral composition, texture and object shape. This information is used to characterize the site geology and choose interesting samples for acquisition. Neural networks are employed for many data analysis steps. A decision tree progressively integrates information from multiple instruments and performs goal-driven decision making. The system is designed to incorporate more instruments and data types as they become available.

3. Hierarchical multisensor analysis for robotic exploration

Eberlein, Susan; Yates, Gigi; Majani, Eric

1991-03-01

Robotic vehicles for lunar and Mars exploration will carry an array of complex instruments requiring real-time data interpretation and fusion. The system described here uses hierarchical multiresolution analysis of visible and multispectral images to extract information on mineral composition, texture and object shape. This information is used to characterize the site geology and choose interesting samples for acquisition. Neural networks are employed for many data analysis steps. A decision tree progressively integrates information from multiple instruments and performs goal-driven decision making. The system is designed to incorporate more instruments and data types as they become available.

4. Hierarchical structure description of spatiotemporal chaos.

PubMed

Liu, Jian; She, Zhen-Su; Guo, Hongyu; Li, Liang; Ouyang, Qi

2004-09-01

We develop a hierarchical structure (HS) analysis for quantitative description of statistical states of spatially extended systems. Examples discussed here include an experimental reaction-diffusion system with Belousov-Zhabotinsky kinetics, the two-dimensional complex Ginzburg-Landau equation, and the modified FitzHugh-Nagumon equation, which all show complex dynamics of spirals and defects. We demonstrate that the spatial-temporal fluctuation fields in the above-mentioned systems all display the HS similarity property originally proposed for the study of fully developed turbulence [Phys. Rev. Lett. 72, 336 (1994)

5. Hierarchical nucleus segmentation in digital pathology images

Gao, Yi; Ratner, Vadim; Zhu, Liangjia; Diprima, Tammy; Kurc, Tahsin; Tannenbaum, Allen; Saltz, Joel

2016-03-01

Extracting nuclei is one of the most actively studied topic in the digital pathology researches. Most of the studies directly search the nuclei (or seeds for the nuclei) from the finest resolution available. While the richest information has been utilized by such approaches, it is sometimes difficult to address the heterogeneity of nuclei in different tissues. In this work, we propose a hierarchical approach which starts from the lower resolution level and adaptively adjusts the parameters while progressing into finer and finer resolution. The algorithm is tested on brain and lung cancers images from The Cancer Genome Atlas data set.

6. Hierarchical nucleus segmentation in digital pathology images

PubMed Central

Gao, Yi; Ratner, Vadim; Zhu, Liangjia; Diprima, Tammy; Kurc, Tahsin; Tannenbaum, Allen; Saltz, Joel

2016-01-01

Extracting nuclei is one of the most actively studied topic in the digital pathology researches. Most of the studies directly search the nuclei (or seeds for the nuclei) from the finest resolution available. While the richest information has been utilized by such approaches, it is sometimes difficult to address the heterogeneity of nuclei in different tissues. In this work, we propose a hierarchical approach which starts from the lower resolution level and adaptively adjusts the parameters while progressing into finer and finer resolution. The algorithm is tested on brain and lung cancers images from The Cancer Genome Atlas data set. PMID:27375315

7. Additive Manufacturing of Hierarchical Porous Structures

SciTech Connect

Grote, Christopher John

2016-08-30

Additive manufacturing has become a tool of choice for the development of customizable components. Developments in this technology have led to a powerful array of printers that t serve a variety of needs. However, resin development plays a crucial role in leading the technology forward. This paper addresses the development and application of printing hierarchical porous structures. Beginning with the development of a porous scaffold, which can be functionalized with a variety of materials, and concluding with customized resins for metal, ceramic, and carbon structures.

8. Modified Recursive Hierarchical Segmentation of Data

NASA Technical Reports Server (NTRS)

Tilton, James C.

2006-01-01

An algorithm and a computer program that implements the algorithm that performs recursive hierarchical segmentation (RHSEG) of data have been developed. While the current implementation is for two-dimensional data having spatial characteristics (e.g., image, spectral, or spectral-image data), the generalized algorithm also applies to three-dimensional or higher dimensional data and also to data with no spatial characteristics. The algorithm and software are modified versions of a prior RHSEG algorithm and software, the outputs of which often contain processing-window artifacts including, for example, spurious segmentation-image regions along the boundaries of processing-window edges.

9. Technique for fast and efficient hierarchical clustering

DOEpatents

Stork, Christopher

2013-10-08

A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

10. Fractal image perception provides novel insights into hierarchical cognition.

PubMed

Martins, M J; Fischmeister, F P; Puig-Waldmüller, E; Oh, J; Geissler, A; Robinson, S; Fitch, W T; Beisteiner, R

2014-08-01

Hierarchical structures play a central role in many aspects of human cognition, prominently including both language and music. In this study we addressed hierarchy in the visual domain, using a novel paradigm based on fractal images. Fractals are self-similar patterns generated by repeating the same simple rule at multiple hierarchical levels. Our hypothesis was that the brain uses different resources for processing hierarchies depending on whether it applies a "fractal" or a "non-fractal" cognitive strategy. We analyzed the neural circuits activated by these complex hierarchical patterns in an event-related fMRI study of 40 healthy subjects. Brain activation was compared across three different tasks: a similarity task, and two hierarchical tasks in which subjects were asked to recognize the repetition of a rule operating transformations either within an existing hierarchical level, or generating new hierarchical levels. Similar hierarchical images were generated by both rules and target images were identical. We found that when processing visual hierarchies, engagement in both hierarchical tasks activated the visual dorsal stream (occipito-parietal cortex, intraparietal sulcus and dorsolateral prefrontal cortex). In addition, the level-generating task specifically activated circuits related to the integration of spatial and categorical information, and with the integration of items in contexts (posterior cingulate cortex, retrosplenial cortex, and medial, ventral and anterior regions of temporal cortex). These findings provide interesting new clues about the cognitive mechanisms involved in the generation of new hierarchical levels as required for fractals.

11. Linear integrated circuits

Young, T.

This book is intended to be used as a textbook in a one-semester course at a variety of levels. Because of self-study features incorporated, it may also be used by practicing electronic engineers as a formal and thorough introduction to the subject. The distinction between linear and digital integrated circuits is discussed, taking into account digital and linear signal characteristics, linear and digital integrated circuit characteristics, the definitions for linear and digital circuits, applications of digital and linear integrated circuits, aspects of fabrication, packaging, and classification and numbering. Operational amplifiers are considered along with linear integrated circuit (LIC) power requirements and power supplies, voltage and current regulators, linear amplifiers, linear integrated circuit oscillators, wave-shaping circuits, active filters, DA and AD converters, demodulators, comparators, instrument amplifiers, current difference amplifiers, analog circuits and devices, and aspects of troubleshooting.

12. A linear programming manual

NASA Technical Reports Server (NTRS)

Tuey, R. C.

1972-01-01

Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.

13. Linear Accelerator (LINAC)

MedlinePlus

... equipment? How is safety ensured? What is this equipment used for? A linear accelerator (LINAC) is the ... Therapy (SBRT) . top of page How does the equipment work? The linear accelerator uses microwave technology (similar ...

14. IR Linearity Monitor

Hilbert, Bryan

2012-10-01

These observations will be used to monitor the signal non-linearity of the IR channel, as well as to update the IR channel non-linearity calibration reference file. The non-linearity behavior of each pixel in the detector will be investigated through the use of full frame and subarray flat fields, while the photometric behavior of point sources will be studied using observations of 47 Tuc. This is a continuation of the Cycle 19 non-linearity monitor, program 12696.

15. IR linearity monitor

Hilbert, Bryan

2013-10-01

These observations will be used to monitor the signal non-linearity of the IR channel, as well as to update the IR channel non-linearity calibration reference file. The non-linearity behavior of each pixel in the detector will be investigated through the use of full frame and subarray flat fields, while the photometric behavior of point sources will be studied using observations of 47 Tuc. This is a continuation of the Cycle 20 non-linearity monitor, program 13079.

16. Modeling place field activity with hierarchical slow feature analysis

PubMed Central

Schönfeld, Fabian; Wiskott, Laurenz

2015-01-01

What are the computational laws of hippocampal activity? In this paper we argue for the slowness principle as a fundamental processing paradigm behind hippocampal place cell firing. We present six different studies from the experimental literature, performed with real-life rats, that we replicated in computer simulations. Each of the chosen studies allows rodents to develop stable place fields and then examines a distinct property of the established spatial encoding: adaptation to cue relocation and removal; directional dependent firing in the linear track and open field; and morphing and scaling the environment itself. Simulations are based on a hierarchical Slow Feature Analysis (SFA) network topped by a principal component analysis (ICA) output layer. The slowness principle is shown to account for the main findings of the presented experimental studies. The SFA network generates its responses using raw visual input only, which adds to its biological plausibility but requires experiments performed in light conditions. Future iterations of the model will thus have to incorporate additional information, such as path integration and grid cell activity, in order to be able to also replicate studies that take place during darkness. PMID:26052279

17. Iris Image Classification Based on Hierarchical Visual Codebook.

PubMed

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

18. Effective parameters determining the information flow in hierarchical biological systems.

PubMed

Blöchl, Florian; Wittmann, Dominik M; Theis, Fabian J

2011-04-01

Signaling networks are abundant in higher organisms. They play pivotal roles, e.g., during embryonic development or within the immune system. In this contribution, we study the combined effect of the various kinetic parameters on the dynamics of signal transduction. To this end, we consider hierarchical complex systems as prototypes of signaling networks. For given topology, the output of these networks is determined by an interplay of the single parameters. For different kinetics, we describe this by algebraic expressions, the so-called effective parameters.When modeling switch-like interactions by Heaviside step functions, we obtain these effective parameters recursively from the interaction graph. They can be visualized as directed trees, which allows us to easily determine the global effect of single kinetic parameters on the system's behavior. We provide evidence that these results generalize to sigmoidal Hill kinetics.In the case of linear activation functions, we again show that the algebraic expressions can be immediately inferred from the topology of the interaction network. This allows us to transform time-consuming analytic solutions of differential equations into a simple graph-theoretic problem. In this context, we also discuss the impact of our work on parameter estimation problems. An issue is that even the fitting of identifiable effective parameters often turns out to be numerically ill-conditioned. We demonstrate that this fitting problem can be reformulated as the problem of fitting exponential sums, for which robust algorithms exist.

19. Linear-Algebra Programs

NASA Technical Reports Server (NTRS)

Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.

1982-01-01

The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.

20. A neural network with modular hierarchical learning

NASA Technical Reports Server (NTRS)

Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

1994-01-01

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

1. A Hierarchical Bayes Ensemble Kalman Filter

Tsyrulnikov, Michael; Rakitko, Alexander

2017-01-01

A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the model-error and predictability-error covariance matrices. The latter are treated as random matrices and updated in a hierarchical Bayes scheme along with the state. The (hyper)prior distribution of the covariance matrices is assumed to be inverse Wishart. The new Hierarchical Bayes Ensemble Filter (HBEF) assimilates ensemble members as generalized observations and allows ordinary observations to influence the covariances. The actual probability distribution of the ensemble members is allowed to be different from the true one. An approximation that leads to a practicable analysis algorithm is proposed. The new filter is studied in numerical experiments with a doubly stochastic one-variable model of "truth". The model permits the assessment of the variance of the truth and the true filtering error variance at each time instance. The HBEF is shown to outperform the EnKF and the HEnKF by Myrseth and Omre (2010) in a wide range of filtering regimes in terms of performance of its primary and secondary filters.

2. HIERARCHICAL STAR FORMATION IN NEARBY LEGUS GALAXIES

SciTech Connect

Elmegreen, Debra Meloy; Elmegreen, Bruce G.; Adamo, Angela; Gouliermis, Dimitrios A.; Aloisi, Alessandra; Bright, Stacey N.; Cignoni, Michele; Lee, Janice; Sabbi, Elena; Andrews, Jennifer; Calzetti, Daniela; Annibali, Francesca; Evans, Aaron S.; Johnson, Kelsey; Gallagher III, John S.; Grebel, Eva K.; Hunter, Deidre A.; Kim, Hwihyun; Smith, Linda J.; Thilker, David; and others

2014-05-20

Hierarchical structure in ultraviolet images of 12 late-type LEGUS galaxies is studied by determining the numbers and fluxes of nested regions as a function of size from ∼1 to ∼200 pc, and the number as a function of flux. Two starburst dwarfs, NGC 1705 and NGC 5253, have steeper number-size and flux-size distributions than the others, indicating high fractions of the projected areas filled with star formation. Nine subregions in seven galaxies have similarly steep number-size slopes, even when the whole galaxies have shallower slopes. The results suggest that hierarchically structured star-forming regions several hundred parsecs or larger represent common unit structures. Small galaxies dominated by only a few of these units tend to be starbursts. The self-similarity of young stellar structures down to parsec scales suggests that star clusters form in the densest parts of a turbulent medium that also forms loose stellar groupings on larger scales. The presence of super star clusters in two of our starburst dwarfs would follow from the observed structure if cloud and stellar subregions more readily coalesce when self-gravity in the unit cell contributes more to the total gravitational potential.

3. Hierarchically structured activated carbon for ultracapacitors

PubMed Central

Kim, Mok-Hwa; Kim, Kwang-Bum; Park, Sun-Min; Roh, Kwang Chul

2016-01-01

To resolve the pore-associated bottleneck problem observed in the electrode materials used for ultracapacitors, which inhibits the transport of the electrolyte ions, we designed hierarchically structured activated carbon (HAC) by synthesizing a mesoporous silica template/carbon composite and chemically activating it to simultaneously remove the silica template and increase the pore volume. The resulting HAC had a well-designed, unique porous structure, which allowed for large interfaces for efficient electric double-layer formation. Given the unique characteristics of the HAC, we believe that the developed synthesis strategy provides important insights into the design and fabrication of hierarchical carbon nanostructures. The HAC, which had a specific surface area of 1,957 m2 g−1, exhibited an extremely high specific capacitance of 157 F g−1 (95 F cc−1), as well as a high rate capability. This indicated that it had superior energy storage capability and was thus suitable for use in advanced ultracapacitors. PMID:26878820

4. A hierarchical neuronal network for planning behavior.

PubMed

Dehaene, S; Changeux, J P

1997-11-25

Planning a goal-directed sequence of behavior is a higher function of the human brain that relies on the integrity of prefrontal cortical areas. In the Tower of London test, a puzzle in which beads sliding on pegs must be moved to match a designated goal configuration, patients with lesioned prefrontal cortex show deficits in planning a goal-directed sequence of moves. We propose a neuronal network model of sequence planning that passes this test and, when lesioned, fails in a way that mimics prefrontal patients' behavior. Our model comprises a descending planning system with hierarchically organized plan, operation, and gesture levels, and an ascending evaluative system that analyzes the problem and computes internal reward signals that index the correct/erroneous status of the plan. Multiple parallel pathways connecting the evaluative and planning systems amend the plan and adapt it to the current problem. The model illustrates how specialized hierarchically organized neuronal assemblies may collectively emulate central executive or supervisory functions of the human brain.

5. A self-defining hierarchical data system

NASA Technical Reports Server (NTRS)

Bailey, J.

1992-01-01

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

6. Retrieving information from a hierarchical plan.

PubMed

Schneider, Darryl W; Logan, Gordon D

2007-11-01

Plans give structure to behavior by specifying whether and when different tasks must be performed. However, the structure of behavior need not mirror the structure of the plan. To investigate this idea, the authors studied how plan information is retrieved in the context of a novel sequence-position cuing procedure, wherein subjects memorize two task sequences, then perform trials on which they are randomly cued to perform a task at one of the serial positions in a sequence. Several empirical effects were consistent with retrieval from a hierarchically structured representation (but not a non-hierarchical representation), including large sequence-repetition benefits, position-repetition benefits only for sequence repetitions, and a lack of robust task-repetition benefits. The data were successfully modeled by assuming that retrieval was time-consuming, susceptible to priming, cue-dependent, structurally constrained, and token-specific. In tandem, the empirical data and modeling work provide deeper insight into the representation of and access to information in memory that comprises a plan for guiding behavior.

7. Hierarchical feature selection for erythema severity estimation

Wang, Li; Shi, Chenbo; Shu, Chang

2014-10-01

At present PASI system of scoring is used for evaluating erythema severity, which can help doctors to diagnose psoriasis [1-3]. The system relies on the subjective judge of doctors, where the accuracy and stability cannot be guaranteed [4]. This paper proposes a stable and precise algorithm for erythema severity estimation. Our contributions are twofold. On one hand, in order to extract the multi-scale redness of erythema, we design the hierarchical feature. Different from traditional methods, we not only utilize the color statistical features, but also divide the detect window into small window and extract hierarchical features. Further, a feature re-ranking step is introduced, which can guarantee that extracted features are irrelevant to each other. On the other hand, an adaptive boosting classifier is applied for further feature selection. During the step of training, the classifier will seek out the most valuable feature for evaluating erythema severity, due to its strong learning ability. Experimental results demonstrate the high precision and robustness of our algorithm. The accuracy is 80.1% on the dataset which comprise 116 patients' images with various kinds of erythema. Now our system has been applied for erythema medical efficacy evaluation in Union Hosp, China.

8. A Hierarchical Bayesian Model for Crowd Emotions

PubMed Central

Urizar, Oscar J.; Baig, Mirza S.; Barakova, Emilia I.; Regazzoni, Carlo S.; Marcenaro, Lucio; Rauterberg, Matthias

2016-01-01

Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the behavior of individuals and of the crowd as a single entity, and explore the relation between behavior and emotions to infer emotional states. Information about the motion patterns of individuals are described using a self-organizing map, and a hierarchical Bayesian network builds probabilistic models to identify behaviors and infer the emotional state of individuals and the crowd. This model is trained and tested using data produced from simulated scenarios that resemble real-life environments. The conducted experiments tested the efficiency of our method to learn, detect and associate behaviors with emotional states yielding accuracy levels of 74% for individuals and 81% for the crowd, similar in performance with existing methods for pedestrian behavior detection but with novel concepts regarding the analysis of crowds. PMID:27458366

9. A hierarchical exact accelerated stochastic simulation algorithm

Orendorff, David; Mjolsness, Eric

2012-12-01

A new algorithm, "HiER-leap" (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled "blocks" and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms.

10. Improvement in Recursive Hierarchical Segmentation of Data

NASA Technical Reports Server (NTRS)

Tilton, James C.

2006-01-01

A further modification has been made in the algorithm and implementing software reported in Modified Recursive Hierarchical Segmentation of Data (GSC- 14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The output of a prior version of the software contained artifacts, including spurious segmentation-image regions bounded by processing-window edges. The modification for suppressing the artifacts, mentioned in the cited article, was addition of a subroutine that analyzes data in the vicinities of seams to find pairs of regions that tend to lie adjacent to each other on opposite sides of the seams. Within each such pair, pixels in one region that are more similar to pixels in the other region are reassigned to the other region. The present modification provides for a parameter ranging from 0 to 1 for controlling the relative priority of merges between spatially adjacent and spatially non-adjacent regions. At 1, spatially-adjacent-/spatially- non-adjacent-region merges have equal priority. At 0, only spatially-adjacent-region merges (no spectral clustering) are allowed. Between 0 and 1, spatially-adjacent- region merges have priority over spatially- non-adjacent ones.

11. Learning deep hierarchical visual feature coding.

PubMed

Goh, Hanlin; Thome, Nicolas; Cord, Matthieu; Lim, Joo-Hwee

2014-12-01

In this paper, we propose a hybrid architecture that combines the image modeling strengths of the bag of words framework with the representational power and adaptability of learning deep architectures. Local gradient-based descriptors, such as SIFT, are encoded via a hierarchical coding scheme composed of spatial aggregating restricted Boltzmann machines (RBM). For each coding layer, we regularize the RBM by encouraging representations to fit both sparse and selective distributions. Supervised fine-tuning is used to enhance the quality of the visual representation for the categorization task. We performed a thorough experimental evaluation using three image categorization data sets. The hierarchical coding scheme achieved competitive categorization accuracies of 79.7% and 86.4% on the Caltech-101 and 15-Scenes data sets, respectively. The visual representations learned are compact and the model's inference is fast, as compared with sparse coding methods. The low-level representations of descriptors that were learned using this method result in generic features that we empirically found to be transferrable between different image data sets. Further analysis reveal the significance of supervised fine-tuning when the architecture has two layers of representations as opposed to a single layer.

12. Hierarchical RFI Mitigation System at the Mauritius Radio Telescope

Udaya Shankar, N.; Pandey, V. N.

2006-08-01

In this paper, we present salient features of the hierarchical RFI mitigation system developed and implemented for offline processing of the visibilities recorded at MRT. Its aim is to achieve effective, reliable and non-toxic automatic RFI mitigation with minimal human intervention. RFI poses a serious problem at MRT due to its low frequency of operation, wide primary beam  (EWxNS~2°x56°) and large amount of data collected for a low frequency survey. Even though several signal processing methods are used to handle RFI, in practice there is no universal foolproof technique. The developed system uses a conjunction of a variety of techniques involving linear and non-linear methods in the visibility as well as in the image domain. These include Thresholding, Fourier filtering, Hampel filtering, Model fitting, Visual inspection, multi-parameter decision based algorithm which uses cumulative interference statistics, and the fact that the sky signal is correlated in each day's images but interference is most likely not. More than 99.7% of the interference is detected automatically, the remaining is detected by semi-automatic methods. The images obtained after applying the RFI mitigation system are free from any perceivable interference and demonstrate its effectiveness. The principles and techniques used in the RFI mitigation system are of general nature. We believe that such an approach based on a conjunction of techniques exploiting their natural strengths and judiciously applying them at various stages of data processing is an important step in the future direction of research to accomplish the ultimate goal of achieving completely automatic data flagging. Use of an RFI database is valuable to investigate the nature of interference at an observatory site and develop appropriate techniques based on its statistics for its mitigation. The 20,000 hours of astronomical observations for the MRT survey have been used for such an analysis. The interesting aspects of

13. Hierarchical and linear sequence processing: an electrophysiological exploration of two different grammar types.

PubMed

Bahlmann, Jörg; Gunter, Thomas C; Friederici, Angela D

2006-11-01

The present study investigated the processing of two types of artificial grammars by means of event-related brain potentials. Two categories of meaningless CV syllables were applied in each grammar type. The two grammars differed with regard to the type of the underlying rule. The finite-state grammar (FSG) followed the rule (AB)n, thereby generating local transitions between As and Bs (e.g., n=2, ABAB). The phrase structure grammar (PSG) followed the rule AnBn, thereby generating center-embedded structures in which the first A and the last B embed the middle elements (e.g., n=2, [A[AB]B]). Two sequence lengths (n=2, n=4) were used. Violations of the structures were introduced at different positions of the syllable sequences. Early violations were situated at the beginning of a sequence, and late violations were placed at the end of a sequence. A posteriorly distributed early negativity elicited by violations was present only in FSG. This effect was interpreted as the possible reflection of a violated local expectancy. Moreover, both grammar-type violations elicited a late positivity. This positivity varied as a function of the violation position in PSG, but not in FSG. These findings suggest that the late positivity could reflect difficulty of integration in PSG sequences.

14. Hierarchical Linear Modeling Meta-Analysis of Single-Subject Design Research

ERIC Educational Resources Information Center

Gage, Nicholas A.; Lewis, Timothy J.

2014-01-01

The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD's utility centers on three issues: sample size, effect size, and serial dependence. One potential…

15. Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qui

2009-01-01

Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

16. Automating Multiple Software Packages in Simulation Research for Structural Equation Modeling and Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Gagne, Phill; Furlow, Carolyn F.

2009-01-01

Simulation researchers are sometimes faced with the need to use multiple statistical software packages in the process of conducting their research, potentially having to go between software packages manually. This can be a tedious and time-consuming process that generally motivates researchers to use fewer replications in their simulations than…

17. Sample Size in Differential Item Functioning: An Application of Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Acar, Tulin

2011-01-01

The purpose of this study is to examine the number of DIF items detected by HGLM at different sample sizes. Eight different sized data files have been composed. The population of the study is 798307 students who had taken the 2006 OKS Examination. 10727 students of 798307 are chosen by random sampling method as the sample of the study. Turkish,…

18. Does High School Facility Quality Affect Student Achievement? A Two-Level Hierarchical Linear Model

ERIC Educational Resources Information Center

Bowers, Alex J.; Urick, Angela

2011-01-01

The purpose of this study is to isolate the independent effects of high school facility quality on student achievement using a large, nationally representative U.S. database of student achievement and school facility quality. Prior research on linking school facility quality to student achievement has been mixed. Studies that relate overall…

19. Comparing Private Schools and Public Schools Using Hierarchical Linear Modeling. NCES 2006-461

ERIC Educational Resources Information Center

Braun, Henry; Jenkins, Frank; Grigg, Wendy

2006-01-01

The goal of the study was to examine differences in mean National Assessment of Educational Progress (NAEP) reading and mathematics scores between public and private schools when selected characteristics of students and/or schools were taken into account. Among the student characteristics considered were gender, race/ethnicity, disability status,…

20. Nonresident Undergraduates' Performance in English Writing Classes-- Hierarchical Linear Modeling Analysis

ERIC Educational Resources Information Center

Vaughn, Allison A.; Bergman, Matthew; Fass-Holmes, Barry

2015-01-01

Do undergraduates whose native language is not English have writing deficiencies leading to academic struggles? The present study showed that the answer to this question was "no" at an American West Coast public university. This university's nonresident undergraduates on average earned B- to B+ in their colleges' English…

1. Aspirin response: Differences in serum thromboxane B2 levels between clinical studies.

PubMed

Brun, Charlotte; Daali, Youssef; Combescure, Christophe; Zufferey, Anne; Michelson, Alan D; Fontana, Pierre; Reny, Jean-Luc; Frelinger, Andrew L

2016-01-01

Serum thromboxane B2 (TxB2) is a specific marker of platelet inhibition by aspirin. Yet, TxB2 levels differ by up to 10-fold between some aspirin-treated patient cohorts. This study aimed to identify factors responsible for differences in serum TxB2 between cohorts in the ADRIE study (n = 657) and the BOSTON study (n = 678) of aspirin-treated cardiovascular patients originally tested with different ELISA assays. TxB2 levels were assessed in representative subgroups of the two cohorts (34 samples in BOSTON and 39 in ADRIE) by both ELISAs, as well as liquid chromatography and tandem mass spectroscopy (MS). A multivariate analysis was performed on the whole cohort database to identify determinants of the difference of TxB2 levels between cohorts. There was no systematic bias between the original ELISA TxB2 values and the MS values and the median difference was small, 0.12 ng/ml, thus not explaining the difference between median TxB2 levels in the two study populations (7 and 0.6 ng/ml in the ADRIE and BOSTON studies, respectively). In the combined dataset of the ADRIE and BOSTON cohorts (n = 1342), body mass index, age, gender, aspirin dose, time from aspirin intake to blood draw, NSAID intake, platelet count and C-reactive protein were significantly associated with TxB2 levels. After adjustment for patient characteristics, the difference between cohorts did not decrease. Unexplained differences in serum TxB2 levels in different populations of aspirin-treated cardiovascular patients suggest that further studies are needed to confirm the role of serum TxB2 level as a prognostic factor or rather as a marker of therapeutic observance.

2. Flowering responses of insect-pollinated plants to elevated CO{sub 2} levels

SciTech Connect

Cushman, J.H.; Koch, G.W.; Chiariello, N.R. ||

1995-06-01

Elevated atmospheric CO{sub 2} concentrations have been predicted or shown to substantially influence plants, communities and ecosystems in a variety of ways. Here, we examined the effects of elevated CO{sub 2} levels on the timing and magnitude of flowering for two insect-pollinated annual plant species in a serpentine grassland. We focused on Lasthenia californica and Linanthus parviflorus and addressed three questions: (1) Do elevated CO{sub 2} levels influence flowering phenologies and is this species specific? (2) Do elevated CO{sub 2} levels affect flower production and is this due to altered numbers of individuals, flowers per plant, or both? and (3) Are effects on flowering due to elevated CO{sub 2} levels per se or changes in environmental conditions associated with methods used to manipulate CO{sub 2} levels? To address these questions, we used the ecosystem experiment at Stanford University`s Jasper Ridge Biological Preserve (San Mateo Co., CA). This system consists of 20 open-topped chambers - half receiving ambient CO{sub 2} (360 ppm) and half receiving elevated CO{sub 2} (720 ppm) - and 10 untreated plots serving as chamber controls. Results from the 1994 season demonstrated that there were species-specific responses to elevated CO{sub 2} levels and the field chambers. For Lasthenia californica, elevated CO{sub 2} per se did not affect relative abundance, inflorescence production, or phenology, but chambers did significantly increase inflorescence production and extend the duration of flowering. For Linanthus parviflorus, elevated CO{sub 2} levels significantly increased relative abundance and flower production, and extended the flowering period slightly, while the chambers significantly decreased flower production early in the season and increased it later in the season.

3. Hierarchical Graphene coating for highly sensitive solid phase microextraction of organochlorine pesticides.

PubMed

Wang, Fuxin; Liu, Shuqin; Yang, Hao; Zheng, Juan; Qiu, Junlang; Xu, Jianqiao; Tong, Yexiang; Zhu, Fang; Ouyang, Gangfeng

2016-11-01

Graphene, a novel class of carbon nanostructures, has received great attention as sorbents due to its fascinating structures, ultrahigh specific surface area, and good extraction ability. In this paper, a new type of hierarchical graphene was synthesized through employing a mild and environment-friendly method. Such 3D interconnected graphene own a high specific surface area up to 524m(2)g(-1), which is about 2.5 fold larger than the graphene, since the synthetic material has interlayer pores between nanosheets and in-plane pores. Then a superior solid-phase microextraction fiber was fabricated by sequentially coating the stainless steel fiber with silicone sealant film and hierarchical graphene powder. Since the novel hierarchical graphene possessed large surface area and good adsorption property, the as-prepared fiber exhibited good extraction properties of the organochlorine pesticides (OCPs). As for the analytical performance, the as-prepared fiber achieved low detection limits (0.08-0.80ngL(-1)) and wide linearity (10-30,000ngL(-1)) under the optimal conditions. The repeatability (n=5) for single fiber were between 5.1% and 11%, while the reproducibility (n=3) of fiber-to-fiber were range from 6.2% to14%. Moreover, the fiber was successfully applied to the analysis of OCPs in the Pearl River water.

4. Status of soluble ST2 levels in serum of HTLV-1 infected individuals.

PubMed

2015-06-01

ST2 is a member of IL-1 receptor family expressed on Th2 cells and regulates Th2 responces. The gene of ST2 encodes soluble ST2 (sST2) and the transmembrane ST2 (ST2L) isoforms through alternative mRNA splicing. The discovery of IL33/ ST2 signaling pathway, has drawn a great scientific attention to this system. sST2 has been shown to be an indacating factor in various infl ammatory conditions. This study aims to evaluate serum sST2 levels in HTLV-1 infected patients. This study included 49 HTLV-1 seropositive cases of which 14 were sympthomatic. Controls consisted of 30 healthy volunteers. sST2 level was measured using a quantitative ELISA assay and the results of the study groups were compared. Corroborating the previous reports, sST2 was lower in females (P = 0.003). The sST2 levels was slightly increased in HTLV-1 patients, though such increase was not statistically significant (P = 0.91), in addition sST2 level did not correlate significantly to the disease duration (P = 0.78). Despite some other chronic viral infection, HTLV-1 seems not to induce high serum sST2. However owing to relatively high normal variation of sST2 levels and rather small sample size, we stongly recommend further reseach with preferably larger sample size to evalute sST2 in HTLV-1 infected patients.

5. Dihydrotestosterone alters cyclooxygenase-2 levels in human coronary artery smooth muscle cells

PubMed Central

Osterlund, Kristen L.; Handa, Robert J.

2010-01-01

Both protective and nonprotective effects of androgens on the cardiovascular system have been reported. Our previous studies show that the potent androgen receptor (AR) agonist dihydrotestosterone (DHT) increases levels of the vascular inflammatory mediator cyclooxygenase (COX)-2 in rodent cerebral arteries independent of an inflammatory stimulus. Little is known about the effects of androgens on inflammation in human vascular tissues. Therefore, we tested the hypothesis that DHT alters COX-2 levels in the absence and presence of induced inflammation in primary human coronary artery smooth muscle cells (HCASMC). Furthermore, we tested the ancillary hypothesis that DHT's effects on COX-2 levels are AR-dependent. Cells were treated with DHT (10 nM) or vehicle for 6 h in the presence or absence of LPS or IL-1β. Similar to previous observations in rodent arteries, in HCASMC, DHT alone increased COX-2 levels compared with vehicle. This effect of DHT was attenuated in the presence of the AR antagonist bicalutamide. Conversely, in the presence of LPS or IL-1β, increases in COX-2 were attenuated by cotreatment with DHT. Bicalutamide did not affect this response, suggesting that DHT-induced decreases in COX-2 levels occur independent of AR stimulation. Thus we conclude that DHT differentially influences COX-2 levels under physiological and pathophysiological conditions in HCASMC. This effect of DHT on COX-2 involves AR-dependent and- independent mechanisms, depending on the physiological state of the cell. PMID:20103743

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

USGS Publications Warehouse

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

2010-01-01

-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

7. Response of tomato to defoliation and elevated CO[sub 2]level

SciTech Connect

Freidus, D. )

1993-06-01

Increased resources are expected to result in increased plant productivity and to increase a plant's ability to replace tissue lost to defoliation. This hypothesis was tested by growing tomato plants (Lycopersicon esculentum) in a phytotron greenhouse at ambient (355 ppm) and elevated (710 ppm) levels of CO[sub 2]. The experiment was fully factorial for CO[sub 2] level and two manual defoliation treatments, the first during vegetative growth and the second during fruiting. Elevated CO[sub 2] level did not alter total biomass, but did alter allocation: total fruit biomass and fruit number decreased. This is contrary to the expected result. Only the first defoliation treatment lowered total vegetative and reproductive biomass produced. There was no interaction between response to defoliation and response to elevated CO[sub 2] level. Thus, both the main effect of elevated CO[sub 2] and the interaction of defoliation and elevated CO[sub 2] were inconsistent with my hypothesis.

8. Umami changes intracellular Ca2+ levels using intracellular and extracellular sources in mouse taste receptor cells.

PubMed

Narukawa, Masataka; Mori, Tomohiko; Hayashi, Yukako

2006-11-01

Recently, candidates for umami receptors have been identified in taste cells, but the precise transduction mechanisms of the downstream receptor remain unknown. To investigate how intracellular Ca(2+) increases in the umami transduction pathway, we measured changes in intracellular Ca(2+) levels in response to umami stimuli monosodium glutamate (MSG), IMP, and MSG + IMP in mouse taste receptor cells (TRCs) by Ca(2+) imaging. Even when extracellular Ca(2+) was absent, 1/3 of umami-responsive TRCs exhibited increased intracellular Ca(2+) levels. When intracellular Ca(2+) was depleted, half of the TRCs retained their response to umami. These results suggest that umami-responsive TRCs increase their intracellular Ca(2+) levels through two pathways: by releasing Ca(2+) from intracellular stores and by an influx of Ca(2+) from extracellular sources. We conclude that the Ca(2+) influx from extracellular source might play an important role in the synergistic effect between MSG and IMP.

9. Higher-Order Item Response Models for Hierarchical Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming

2013-01-01

Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

10. Imitation of Hierarchical Action Structure by Young Children

ERIC Educational Resources Information Center

Whiten, Andrew; Flynn, Emma; Brown, Katy; Lee, Tanya

2006-01-01

To provide the first systematic test of whether young children will spontaneously perceive and imitate hierarchical structure in complex actions, a task was devised in which a set of 16 elements can be modelled through either of two different, hierarchically organized strategies. Three-year-old children showed a strong and significant tendency to…

11. Discursive Hierarchical Patterning in Law and Management Cases

ERIC Educational Resources Information Center

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…

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

PubMed

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.

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

ERIC Educational Resources Information Center

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…

14. English Pyramids: Using Hierarchical Diagrams for Communication Activities.

ERIC Educational Resources Information Center

Johnson, Tia; Sheetz-Brunetti, Judy

The pyramid, or hierarchical diagram, is used in teaching writing English as a second language (ESL) as a visual representation of the way English speakers and writers organize ideas, for comparison with discourse organization in other cultures. A common problem of ESL students is an inability to organize ideas hierarchically. One class activity…

15. Using Hierarchical Folders and Tags for File Management

ERIC Educational Resources Information Center

Ma, Shanshan

2010-01-01

Hierarchical folders have been widely used for managing digital files. A well constructed hierarchical structure can keep files organized. A parent folder can have several subfolders and one subfolder can only reside in one parent folder. Files are stored in folders or subfolders. Files can be found by traversing a given path, going through…

16. Signaling Hierarchical and Sequential Organization in Expository Text

ERIC Educational Resources Information Center

Lorch, Robert; Lemarie, Julie; Grant, Russell

2011-01-01

Four experiments tested a hypothesized function of signaling devices, namely, to communicate information about text organization. Experiments 1 and 2 compared headings that communicated the hierarchical organization of text topics with headings that did not communicate the hierarchical organization. Signaling organization led to more complete and…

17. Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences

ERIC Educational Resources Information Center

Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

2015-01-01

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

18. Hierarchical clustering using correlation metric and spatial continuity constraint

DOEpatents

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.

19. POLLUTION PREVENTION IN THE EARLY STAGES OF HIERARCHICAL PROCESS DESIGN

EPA Science Inventory

Hierarchical methods are often used in the conceptual stages of process design to synthesize and evaluate process alternatives. In this work, the methods of hierarchical process design will be focused on environmental aspects. In particular, the design methods will be coupled to ...

20. Acoustic performance of reiterated hierarchical honeycomb structures

Nainar, Naveen

Sandwich panels constructed from honeycomb structures have been found to reduce sound transmission and improve vibration isolation. In this work, reiterated hierarchical honeycomb structures have been modeled for the core in sandwich panels and studied for sound transmission properties using finite element analysis. Several honeycomb unit cell geometries are considered, including, regular hexagonal, auxetic with properties of negative Poisson's ratio, and different reiterated hierarchical structures. Previous studies have shown that auxetic honeycomb structures exhibit improved sound transmission loss compared to regular honeycomb sandwich panels. Two different orientations of the honeycomb unit cell geometry have been studied, namely, the zigzag and armchair configurations, which are, rotated 90 degrees. Both regular and auxetic honeycombs have been used in both these configurations. The finite element model of the panels are used to extract natural frequencies and mode shapes and to perform steady state frequency response dynamic analysis up to 1000 Hz. The transmitted sound pressure levels on the surface of each structure is extracted and compared to study the influence of the reiterated hierarchy on sound transmission characteristics. The influence of corner reinforcement constructed by subtracting interior high-level hierarchical structure except at the vertices of the underlying lower-level honeycomb unit cell was also studied. Furthermore, a study was conducted to quantify the effect of changing the ratio of cell-wall thickness between various levels of hierarchy. Special focus on the limiting case of level-1 hierarchy with zero level-0 thickness is also studied. In all cases, the total mass was kept constant in order to isolate only stiffness and mass distribution effects. The results show that introduction of reiterated hierarchy in level-1 structures reduced the sound transmission of honeycomb sandwich panels compared to parent level-0 geometry. Results

1. Hierarchical Strategy for Rapid Analysis Environment

NASA Technical Reports Server (NTRS)

Whitcomb, John

2003-01-01

A new philosophy is developed wherein the hierarchical definition of data is made use of in creating a better environment to conduct analyses of practical problems. This system can be adapted to conduct virtually any type of analysis, since this philosophy is not bound to any specific kind of analysis. It provides a framework to manage different models and its results and more importantly, the interaction between the different models. Thus, it is ideal for many types of finite element analyses like globalAoca1 analysis and those that involve multiple scales and fields. The system developed during the course of this work is just a demonstrator of the basic concepts. A complete implementation of this strategy could potentially make a major impact on the way analyses are conducted. It could considerably reduce the time frame required to conduct the analysis of real-life problems by efficient management of the data involved and reducing the human effort involved. It also helps in better decision making because of more ways to interpret the results. The strategy has been currently implemented for structural analysis, but with more work it could be extended to other fields of science when the finite element method is used to solve the differential equations numerically. This report details the work that has been done during the course of this project and its achievements and results. The following section discusses the meaning of the word hierarchical and the different references to the term in the literature. It talks about the development of the finite element method, its different versions and how hierarchy has been used to improve the methodology. The next section describes the hierarchical philosophy in detail and explains the different concepts and terms associated with it. It goes on to describe the implementation and the features of the demonstrator. A couple of problems are analyzed using the demonstrator program to show the working of the system. The two

2. Distributed functions of detection and discrimination of vibrotactile stimuli in the hierarchical human somatosensory system.

PubMed

Kim, Junsuk; Müller, Klaus-Robert; Chung, Yoon Gi; Chung, Soon-Cheol; Park, Jang-Yeon; Bülthoff, Heinrich H; Kim, Sung-Phil

2014-01-01

According to the hierarchical view of human somatosensory network, somatic sensory information is relayed from the thalamus to primary somatosensory cortex (S1), and then distributed to adjacent cortical regions to perform further perceptual and cognitive functions. Although a number of neuroimaging studies have examined neuronal activity correlated with tactile stimuli, comparatively less attention has been devoted toward understanding how vibrotactile stimulus information is processed in the hierarchical somatosensory cortical network. To explore the hierarchical perspective of tactile information processing, we studied two cases: (a) discrimination between the locations of finger stimulation; and (b) detection of stimulation against no stimulation on individual fingers, using both standard general linear model (GLM) and searchlight multi-voxel pattern analysis (MVPA) techniques. These two cases were studied on the same data set resulting from a passive vibrotactile stimulation experiment. Our results showed that vibrotactile stimulus locations on fingers could be discriminated from measurements of human functional magnetic resonance imaging (fMRI). In particular, it was in case (a) we observed activity in contralateral posterior parietal cortex (PPC) and supramarginal gyrus (SMG) but not in S1, while in case; (b) we found significant cortical activations in S1 but not in PPC and SMG. These discrepant observations suggest the functional specialization with regard to vibrotactile stimulus locations, especially, the hierarchical information processing in the human somatosensory cortical areas. Our findings moreover support the general understanding that S1 is the main sensory receptive area for the sense of touch, and adjacent cortical regions (i.e., PPC and SMG) are in charge of a higher level of processing and may thus contribute most for the successful classification between stimulated finger locations.

3. A hierarchical preconditioner for the electric field integral equation on unstructured meshes based on primal and dual Haar bases

Adrian, S. B.; Andriulli, F. P.; Eibert, T. F.

2017-02-01

A new hierarchical basis preconditioner for the electric field integral equation (EFIE) operator is introduced. In contrast to existing hierarchical basis preconditioners, it works on arbitrary meshes and preconditions both the vector and the scalar potential within the EFIE operator. This is obtained by taking into account that the vector and the scalar potential discretized with loop-star basis functions are related to the hypersingular and the single layer operator (i.e., the well known integral operators from acoustics). For the single layer operator discretized with piecewise constant functions, a hierarchical preconditioner can easily be constructed. Thus the strategy we propose in this work for preconditioning the EFIE is the transformation of the scalar and the vector potential into operators equivalent to the single layer operator and to its inverse. More specifically, when the scalar potential is discretized with star functions as source and testing functions, the resulting matrix is a single layer operator discretized with piecewise constant functions and multiplied left and right with two additional graph Laplacian matrices. By inverting these graph Laplacian matrices, the discretized single layer operator is obtained, which can be preconditioned with the hierarchical basis. Dually, when the vector potential is discretized with loop functions, the resulting matrix can be interpreted as a hypersingular operator discretized with piecewise linear functions. By leveraging on a scalar Calderón identity, we can interpret this operator as spectrally equivalent to the inverse single layer operator. Then we use a linear-in-complexity, closed-form inverse of the dual hierarchical basis to precondition the hypersingular operator. The numerical results show the effectiveness of the proposed preconditioner and the practical impact of theoretical developments in real case scenarios.

4. Evidence for the Postconquest Demographic Collapse of the Americas in Historical CO2 Levels

Mannstein, H.; Faust, F. X.

2008-12-01

In this talk we promote the hypothesis that the massive demographic collapse of the native populations of the Americas triggered by the European colonization brought about the abandonment of large expanses of agricultural fields soon recovered by forests, which in due turn fixed atmospheric CO2 in significant quantities. This hypothesis is supported by measurements of atmospheric CO2 levels in ice cores from Law Dome, Antarctica. Changing the focus from paleoclimate to global population dynamics and using the same causal chain, the measured drop in historic atmospheric CO2 levels can also be looked upon as further, strong evidence for the postconquest demographic collapse of the Americas.

PubMed

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.

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

PubMed

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.

7. Hierarchical loop detection for mobile outdoor robots

Lang, Dagmar; Winkens, Christian; Häselich, Marcel; Paulus, Dietrich

2012-01-01

Loop closing is a fundamental part of 3D simultaneous localization and mapping (SLAM) that can greatly enhance the quality of long-term mapping. It is essential for the creation of globally consistent maps. Conceptually, loop closing is divided into detection and optimization. Recent approaches depend on a single sensor to recognize previously visited places in the loop detection stage. In this study, we combine data of multiple sensors such as GPS, vision, and laser range data to enhance detection results in repetitively changing environments that are not sufficiently explained by a single sensor. We present a fast and robust hierarchical loop detection algorithm for outdoor robots to achieve a reliable environment representation even if one or more sensors fail.

8. Hierarchical distributed stabilization of power networks

Ishizaki, Takayuki; Sadamoto, Tomonori; Imura, Jun-ichi

2014-10-01

Large fluctuation of electric power due to high penetration of renewable energy sources such as photovoltaic and wind power generation increases the risk to make the whole power network system unstable. The conventional frequency control called load frequency control is based on PID (proportional-integral-derivative) control or more advanced centralized and decentralized/distributed control. If we could more effectively use information on the state of the other neighbor generators, we can expect to make the whole system more robust against the large frequency fluctuation. This paper proposes a fundamental framework towards the design of hierarchical distributed stabilizing controllers for a network of power generators and loads. This novel type of distributed controller, composed of a global controller and a set of local controllers, takes into account the effect of the interaction among the generators and loads to improve robustness for the variation of locally stabilizing controllers.

9. Hierarchical tapered bar elements undergoing axial deformation

NASA Technical Reports Server (NTRS)

Ganesan, N.; Thampi, S. K.

1992-01-01

A method is described to model the dynamics of tapered axial bars of various cross sections based on the well-known Craig/Bampton component mode synthesis technique. This element is formed in terms of the static constraint modes and interface restrained normal modes. This is in contrast with the finite elements as implemented in NASTRAN where the interface restrained normal modes are neglected. These normal modes are in terms of Bessel functions. Restoration of a few of these modes leads to higher accuracy with fewer generalized coordinates. The proposed models are hierarchical so that all lower order element matrices are embedded in higher order element matrices. The advantages of this formulation compared to standard NASTRAN truss element formulation are demonstrated through simple numerical examples.

10. Hierarchical approaches to VLSI circuit layout

SciTech Connect

1987-01-01

This thesis studies two hierarchical approaches to the circuit-layout problem: the top-down approach and the bottom-up approach. The first part is devoted to the traditional top-down approach, and particularly, to an important subproblem thereof called the Channel Routing Problem (CRP). The complexity of CRP in three different layout modes - the reserved mode, the knock-knee mode, and the restricted-overlap mode - is studied. Besides the conventional square grid, two new grids - the alternate grid and the 45/sup 0/ grid - are considered, and their respective versatility is assessed. In the second part, a novel bottom-up technique for solving the layout problem is proposed. The strategy is to recursively interconnect a set of modules, in conformity with the design rules. The basic step consists of merging a pair of strongly-connected modules. This technique is elaborated on and the fundamental problems of this approach are discussed.

11. Fluorocarbon Adsorption in Hierarchical Porous Frameworks

SciTech Connect

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.

12. Hierarchical manifold learning for regional image analysis.

PubMed

Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Joseph V; Rueckert, Daniel

2014-02-01

We present a novel method of hierarchical manifold learning which aims to automatically discover regional properties of image datasets. While traditional manifold learning methods have become widely used for dimensionality reduction in medical imaging, they suffer from only being able to consider whole images as single data points. We extend conventional techniques by additionally examining local variations, in order to produce spatially-varying manifold embeddings that characterize a given dataset. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate the utility of our method in two very different settings: 1) to learn the regional correlations in motion within a sequence of time-resolved MR images of the thoracic cavity; 2) to find discriminative regions of 3-D brain MR images associated with neurodegenerative disease.

13. A Hierarchical Approach to Fracture Mechanics

NASA Technical Reports Server (NTRS)

Saether, Erik; Taasan, Shlomo

2004-01-01

Recent research conducted under NASA LaRC's Creativity and Innovation Program has led to the development of an initial approach for a hierarchical fracture mechanics. This methodology unites failure mechanisms occurring at different length scales and provides a framework for a physics-based theory of fracture. At the nanoscale, parametric molecular dynamic simulations are used to compute the energy associated with atomic level failure mechanisms. This information is used in a mesoscale percolation model of defect coalescence to obtain statistics of fracture paths and energies through Monte Carlo simulations. The mathematical structure of predicted crack paths is described using concepts of fractal geometry. The non-integer fractal dimension relates geometric and energy measures between meso- and macroscales. For illustration, a fractal-based continuum strain energy release rate is derived for inter- and transgranular fracture in polycrystalline metals.

14. Navigating large hierarchical space using invisible links

Hao, Ming C.; Hsu, Meichun; Dayal, Umeshwar; Krug, Adrian

2000-02-01

To date, many web visualization applications have shown the usefulness of a hyperbolic tree. However, we have discovered that strict hierarchical tree structures are too limited. For many practical applications, we need to generalize a hyperbolic tree to a hyperbolic space. This approach results in massive cross-links in a highly connected graph that clutter the display. To resolve this problem, an invisible link technique is introduced. In this paper. we describe the navigation in a large hyperbolic space using invisible links in some detail. We have applied this invisible link method to three data mining visualization applications: e-business web navigation for URL visits, customer call center for question-answer service, and web site index creation.

15. Image Segmentation Using Hierarchical Merge Tree.

PubMed

Liu, Ting; Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-07-18

This paper investigates one of the most fundamental computer vision problems: image segmentation. We propose a supervised hierarchical approach to object-independent image segmentation. Starting with over-segmenting superpixels, we use a tree structure to represent the hierarchy of region merging, by which we reduce the problem of segmenting image regions to finding a set of label assignment to tree nodes. We formulate the tree structure as a constrained conditional model to associate region merging with likelihoods predicted using an ensemble boundary classifier. Final segmentations can then be inferred by finding globally optimal solutions to the model efficiently. We also present an iterative training and testing algorithm that generates various tree structures and combines them to emphasize accurate boundaries by segmentation accumulation. Experiment results and comparisons with other recent methods on six public data sets demonstrate that our approach achieves state-of-the-art region accuracy and is competitive in image segmentation without semantic priors.

16. Evolution of groups with a hierarchical structure

Ohnishi, Teruaki

2012-12-01

The universal occurrence of a hierarchical structure and its dynamic behavior in various types of group, living or abstract, are discussed. Here the word “group” refers not only to tangible aggregation but also to invisible aggregation of social psychological and of geopolitical meaning. The evolution of these groups is simulated using a model of agents distributed on the lattices of cellular grids. It is assumed that agents, fearing isolation, interact asymmetrically with each other with regard to exchange of “power”. As an indicator of hierarchy, the Gini coefficient is introduced. Example calculations are made for the aggregation, fusion and fission of animal groups, and for the appearance of a powerful empire and the rise and fall of supremacy. It is shown that such abstract objects evolve with time in accordance with the universal rules of groups common to birds and fish.

17. Efficient promotion strategies in hierarchical organizations

Pluchino, Alessandro; Rapisarda, Andrea; Garofalo, Cesare

2011-10-01

The Peter principle has recently been investigated by means of an agent-based simulation, and its validity has been numerically corroborated. It has been confirmed that, within certain conditions, it can really influence in a negative way the efficiency of a pyramidal organization adopting meritocratic promotions. It was also found that, in order to bypass these effects, alternative promotion strategies should be adopted, as for example a random selection choice. In this paper, within the same line of research, we study promotion strategies in a more realistic hierarchical and modular organization, and we show the robustness of our previous results, extending their validity to a more general context. We also discuss why the adoption of these strategies could be useful for real organizations.

18. Crack Propagation in Bamboo's Hierarchical Cellular Structure

PubMed Central

Habibi, Meisam K.; Lu, Yang

2014-01-01

Bamboo, as a natural hierarchical cellular material, exhibits remarkable mechanical properties including excellent flexibility and fracture toughness. As far as bamboo as a functionally graded bio-composite is concerned, the interactions of different constituents (bamboo fibers; parenchyma cells; and vessels.) alongside their corresponding interfacial areas with a developed crack should be of high significance. Here, by using multi-scale mechanical characterizations coupled with advanced environmental electron microscopy (ESEM), we unambiguously show that fibers' interfacial areas along with parenchyma cells' boundaries were preferred routes for crack growth in both radial and longitudinal directions. Irrespective of the honeycomb structure of fibers along with cellular configuration of parenchyma ground, the hollow vessels within bamboo culm affected the crack propagation too, by crack deflection or crack-tip energy dissipation. It is expected that the tortuous crack propagation mode exhibited in the present study could be applicable to other cellular natural materials as well. PMID:24998298

19. Crack propagation in bamboo's hierarchical cellular structure.

PubMed

Habibi, Meisam K; Lu, Yang

2014-07-07

Bamboo, as a natural hierarchical cellular material, exhibits remarkable mechanical properties including excellent flexibility and fracture toughness. As far as bamboo as a functionally graded bio-composite is concerned, the interactions of different constituents (bamboo fibers; parenchyma cells; and vessels.) alongside their corresponding interfacial areas with a developed crack should be of high significance. Here, by using multi-scale mechanical characterizations coupled with advanced environmental electron microscopy (ESEM), we unambiguously show that fibers' interfacial areas along with parenchyma cells' boundaries were preferred routes for crack growth in both radial and longitudinal directions. Irrespective of the honeycomb structure of fibers along with cellular configuration of parenchyma ground, the hollow vessels within bamboo culm affected the crack propagation too, by crack deflection or crack-tip energy dissipation. It is expected that the tortuous crack propagation mode exhibited in the present study could be applicable to other cellular natural materials as well.

20. A new intelligent hierarchical fault diagnosis system

SciTech Connect

Huang, Y.C.; Huang, C.L.; Yang, H.T.

1997-02-01

As a part of a substation-level decision support system, a new intelligent Hierarchical Fault Diagnosis System for on-line fault diagnosis is presented in this paper. The proposed diagnosis system divides the fault diagnosis process into two phases. Using time-stamped information of relays and breakers, phase 1 identifies the possible fault sections through the Group Method of Data Handling (GMDH) networks, and phase 2 recognizes the types and detailed situations of the faults identified in phase 1 by using a fast bit-operation logical inference mechanism. The diagnosis system has been practically verified by testing on a typical Taiwan power secondary transmission system. Test results show that rapid and accurate diagnosis can be obtained with flexibility and portability for fault diagnosis purpose of diverse substations.

1. Hierarchical Design and Verification for VLSI

NASA Technical Reports Server (NTRS)

Shostak, R. E.; Elliott, W. D.; Levitt, K. N.

1983-01-01

The specification and verification work is described in detail, and some of the problems and issues to be resolved in their application to Very Large Scale Integration VLSI systems are examined. The hierarchical design methodologies enable a system architect or design team to decompose a complex design into a formal hierarchy of levels of abstraction. The first step inprogram verification is tree formation. The next step after tree formation is the generation from the trees of the verification conditions themselves. The approach taken here is similar in spirit to the corresponding step in program verification but requires modeling of the semantics of circuit elements rather than program statements. The last step is that of proving the verification conditions using a mechanical theorem-prover.

2. Influence of expansion on hierarchical structure.

PubMed

Miller, Bruce N; Rouet, J L

2002-05-01

We study a one-dimensional model of gravitational instability in an Einstein-de Sitter universe. Scaling in both space and time results in an autonomous set of coupled Poisson-Vlasov equations for both the field and phase space density, and the N-body problem. Using dynamical simulation, we find direct evidence of hierarchical clustering. A multifractal analysis reveals a bifractal geometry similar to that observed in the distribution of galaxies. To demonstrate the role of scaling, we compare the system to other one-dimensional models recently employed to study structure formation. Finally we show that the model yields an estimate of the time of galaxy formation of the correct order.

3. Hierarchical motion organization in random dot configurations

NASA Technical Reports Server (NTRS)

Bertamini, M.; Proffitt, D. R.; Kaiser, M. K. (Principal Investigator)

2000-01-01

Motion organization has 2 aspects: the extraction of a (moving) frame of reference and the hierarchical organization of moving elements within the reference frame. Using a discrimination of relative motions task, the authors found large differences between different types of motion (translation, divergence, and rotation) in the degree to which each can serve as a moving frame of reference. Translation and divergence are superior to rotation. There are, however, situations in which rotation can serve as a reference frame. This is due to the presence of a second factor, structural invariants (SIs). SIs are spatial relationships persisting among the elements within a configuration such as a collinearity among points or one point coinciding with the center of rotation for another (invariant radius). The combined effect of these 2 factors--motion type and SIs-influences perceptual motion organization.

4. Hierarchical image segmentation for learning object priors

SciTech Connect

Prasad, Lakshman; Yang, Xingwei; Latecki, Longin J; Li, Nan

2010-11-10

The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

5. Deep Learning with Hierarchical Convolutional Factor Analysis

PubMed Central

Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

2013-01-01

Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

6. Epidemic Control in a Hierarchical Social Network

Grabowski, Andrzej; Kosiński, Robert A.

The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIR model with incubation time is used. In our model the localization of individuals in different social groups, the effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The influence of different control methods on the spreading process is investigated as a function of different initial conditions. The cost-effectiveness of mass preventive random vaccinations, target vaccinations and sick leaves are compared. A critical range of vaccinations, sufficient for suppressing of an epidemic is calculated. The results of numerical calculations are similar to the solutions of the master equation for the spreading process.

7. Epidemic spreading in a hierarchical social network

Grabowski, A.; Kosiński, R. A.

2004-09-01

A model of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The structure of interpersonal connections is based on a scale-free network. Spatial localization of individuals belonging to different social groups, and the mobility of a contemporary community, as well as the effectiveness of different interpersonal interactions, are taken into account. Typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, are discussed. The influence of preventive vaccinations on the spreading process is investigated. The critical value of preventively vaccinated individuals that is sufficient for the suppression of an epidemic is calculated. Our results are compared with solutions of the master equation for the spreading process and good agreement of the character of this process is found.

8. Hierarchical task analysis: developments, applications, and extensions.

PubMed

Stanton, Neville A

2006-01-01

Hierarchical task analysis (HTA) is a core ergonomics approach with a pedigree of over 30 years continuous use. At its heart, HTA is based upon a theory of performance and has only three governing principles. Originally developed as a means of determining training requirements, there was no way the initial pioneers of HTA could have foreseen the extent of its success. HTA has endured as a way of representing a system sub-goal hierarchy for extended analysis. It has been used for a range of applications, including interface design and evaluation, allocation of function, job aid design, error prediction, and workload assessment. Ergonomists are still developing new ways of using HTA which has assured the continued use of the approach for the foreseeable future.

9. Hierarchical structures in fully developed turbulence

Liu, Li

Analysis of the probability density functions (PDFs) of the velocity increment dvl and of their deformation is used to reveal the statistical structure of the intermittent energy cascade dynamics of turbulence. By analyzing a series of turbulent data sets including that of an experiment of fully developed low temperature helium turbulent gas flow (Belin, Tabeling, & Willaime, Physica D 93, 52, 1996), of a three-dimensional isotropic Navier-Stokes simulation with a resolution of 2563 (Cao, Chen, & She, Phys. Rev. Lett. 76, 3711, 1996) and of a GOY shell model simulation (Leveque & She, Phys. Rev. E 55, 1997) of a very big sample size (up to 5 billions), the validity of the Hierarchical Structure model (She & Leveque, Phys. Rev. Lett. 72, 366, 1994) for the inertial-range is firmly demonstrated. Furthermore, it is shown that parameters in the Hierarchical Structure model can be reliably measured and used to characterize the cascade process. The physical interpretations of the parameters then allow to describe differential changes in different turbulent systems so as to address non-universal features of turbulent systems. It is proposed that the above study provides a framework for the study of non-homogeneous turbulence. A convergence study of moments and scaling exponents is also carried out with detailed analysis of effects of finite statistical sample size. A quantity Pmin is introduced to characterize the resolution of a PDF, and hence the sample size. The fact that any reported scaling exponent depends on the PDF resolution suggests that the validation (or rejection) of a model of turbulence needs to carry out a resolution dependence analysis on its scaling prediction.

10. Hierarchical imaging of the human knee

Schulz, Georg; Götz, Christian; Deyhle, Hans; Müller-Gerbl, Magdalena; Zanette, Irene; Zdora, Marie-Christine; Khimchenko, Anna; Thalmann, Peter; Rack, Alexander; Müller, Bert

2016-10-01

Among the clinically relevant imaging techniques, computed tomography (CT) reaches the best spatial resolution. Sub-millimeter voxel sizes are regularly obtained. For investigations on true micrometer level lab-based μCT has become gold standard. The aim of the present study is the hierarchical investigation of a human knee post mortem using hard X-ray μCT. After the visualization of the entire knee using a clinical CT with a spatial resolution on the sub-millimeter range, a hierarchical imaging study was performed using a laboratory μCT system nanotom m. Due to the size of the whole knee the pixel length could not be reduced below 65 μm. These first two data sets were directly compared after a rigid registration using a cross-correlation algorithm. The μCT data set allowed an investigation of the trabecular structures of the bones. The further reduction of the pixel length down to 25 μm could be achieved by removing the skin and soft tissues and measuring the tibia and the femur separately. True micrometer resolution could be achieved after extracting cylinders of several millimeters diameters from the two bones. The high resolution scans revealed the mineralized cartilage zone including the tide mark line as well as individual calcified chondrocytes. The visualization of soft tissues including cartilage, was arranged by X-ray grating interferometry (XGI) at ESRF and Diamond Light Source. Whereas the high-energy measurements at ESRF allowed the simultaneous visualization of soft and hard tissues, the low-energy results from Diamond Light Source made individual chondrocytes within the cartilage visual.

11. Secular Evolution of Hierarchical Triple Star Systems

Ford, Eric B.; Kozinsky, Boris; Rasio, Frederic A.

2000-05-01

We derive octupole-level secular perturbation equations for hierarchical triple systems, using classical Hamiltonian perturbation techniques. Our equations describe the secular evolution of the orbital eccentricities and inclinations over timescales that are long compared to the orbital periods. By extending previous work done to leading (quadrupole) order to octupole level (i.e., including terms of order α3, where α≡a1/a2<1 is the ratio of semimajor axes), we obtain expressions that are applicable to a much wider range of parameters. In particular, our results can be applied to high-inclination as well as coplanar systems, and our expressions are valid for almost all mass ratios for which the system is in a stable hierarchical configuration. In contrast, the standard quadrupole-level theory of Kozai gives a vanishing result in the limit of zero relative inclination. The classical planetary perturbation theory, while valid to all orders in α, applies only to orbits of low-mass objects orbiting a common central mass, with low eccentricities and low relative inclinations. For triple systems containing a close inner binary, we also discuss the possible interaction between the classical Newtonian perturbations and the general relativistic precession of the inner orbit. In some cases we show that this interaction can lead to resonances and a significant increase in the maximum amplitude of eccentricity perturbations. We establish the validity of our analytic expressions by providing detailed comparisons with the results of direct numerical integrations of the three-body problem obtained for a large number of representative cases. In addition, we show that our expressions reduce correctly to previously published analytic results obtained in various limiting regimes. We also discuss applications of the theory in the context of several observed triple systems of current interest, including the millisecond pulsar PSR B1620-26 in M4, the giant planet in 16 Cygni, and

12. Linear collider: a preview

SciTech Connect

Wiedemann, H.

1981-11-01

Since no linear colliders have been built yet it is difficult to know at what energy the linear cost scaling of linear colliders drops below the quadratic scaling of storage rings. There is, however, no doubt that a linear collider facility for a center of mass energy above say 500 GeV is significantly cheaper than an equivalent storage ring. In order to make the linear collider principle feasible at very high energies a number of problems have to be solved. There are two kinds of problems: one which is related to the feasibility of the principle and the other kind of problems is associated with minimizing the cost of constructing and operating such a facility. This lecture series describes the problems and possible solutions. Since the real test of a principle requires the construction of a prototype I will in the last chapter describe the SLC project at the Stanford Linear Accelerator Center.

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

SciTech Connect

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

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.

14. Constituent Structure and Linear Order in Language Production: Evidence from Subject-Verb Agreement

ERIC Educational Resources Information Center

Haskell, Todd R.; MacDonald, Maryellen C.

2005-01-01

A number of studies have shown that structural factors play a much larger role than the linear order of words during the production of grammatical agreement. These findings have been used as evidence for a stage in the production process at which hierarchical relations between constituents have been established (a necessary precursor to…

15. Linear regulator design for stochastic systems by a multiple time scales method

NASA Technical Reports Server (NTRS)

Teneketzis, D.; Sandell, N. R., Jr.

1976-01-01

A hierarchically-structured, suboptimal controller for a linear stochastic system composed of fast and slow subsystems is considered. The controller is optimal in the limit as the separation of time scales of the subsystems becomes infinite. The methodology is illustrated by design of a controller to suppress the phugoid and short period modes of the longitudinal dynamics of the F-8 aircraft.

16. Linear mass actuator

NASA Technical Reports Server (NTRS)

Holloway, Sidney E., III (Inventor); Crossley, Edward A., Jr. (Inventor); Jones, Irby W. (Inventor); Miller, James B. (Inventor); Davis, C. Calvin (Inventor); Behun, Vaughn D. (Inventor); Goodrich, Lewis R., Sr. (Inventor)

1992-01-01

A linear mass actuator includes an upper housing and a lower housing connectable to each other and having a central passageway passing axially through a mass that is linearly movable in the central passageway. Rollers mounted in the upper and lower housings in frictional engagement with the mass translate the mass linearly in the central passageway and drive motors operatively coupled to the roller means, for rotating the rollers and driving the mass axially in the central passageway.

17. Fault tolerant linear actuator

DOEpatents

Tesar, Delbert

2004-09-14

In varying embodiments, the fault tolerant linear actuator of the present invention is a new and improved linear actuator with fault tolerance and positional control that may incorporate velocity summing, force summing, or a combination of the two. In one embodiment, the invention offers a velocity summing arrangement with a differential gear between two prime movers driving a cage, which then drives a linear spindle screw transmission. Other embodiments feature two prime movers driving separate linear spindle screw transmissions, one internal and one external, in a totally concentric and compact integrated module.

18. Linear phase compressive filter

DOEpatents

McEwan, Thomas E.

1995-01-01

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line.

19. Linear phase compressive filter

DOEpatents

McEwan, T.E.

1995-06-06

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line. 2 figs.

20. Recombineering linear BACs.

PubMed

Chen, Qingwen; Narayanan, Kumaran

2015-01-01

Recombineering is a powerful genetic engineering technique based on homologous recombination that can be used to accurately modify DNA independent of its sequence or size. One novel application of recombineering is the assembly of linear BACs in E. coli that can replicate autonomously as linear plasmids. A circular BAC is inserted with a short telomeric sequence from phage N15, which is subsequently cut and rejoined by the phage protelomerase enzyme to generate a linear BAC with terminal hairpin telomeres. Telomere-capped linear BACs are protected against exonuclease attack both in vitro and in vivo in E. coli cells and can replicate stably. Here we describe step-by-step protocols to linearize any BAC clone by recombineering, including inserting and screening for presence of the N15 telomeric sequence, linearizing BACs in vivo in E. coli, extracting linear BACs, and verifying the presence of hairpin telomere structures. Linear BACs may be useful for functional expression of genomic loci in cells, maintenance of linear viral genomes in their natural conformation, and for constructing innovative artificial chromosome structures for applications in mammalian and plant cells.

1. PCOS women show significantly higher homocysteine level, independent to glucose and E2 level

PubMed Central

Eskandari, Zahra; Sadrkhanlou, Rajab-Ali; Nejati, Vahid; Tizro, Gholamreza

2016-01-01

Background: It is reasonable to think that some biochemical characteristics of follicular fluid (FF) surrounding the oocyte may play a critical role in determining the quality of oocyte and the subsequent potential needed to achieve fertilization and embryo development. Objective: This study was carried out to evaluate the levels of FF homocysteine (Hcy) in IVF candidate polycystic ovary syndrome (PCOS) women and any relationships with FF glucose and estradiol (E2) levels. Materials and Methods: In this case control study which was performed in Dr. Tizro Day Care and IVF Center 70 infertile patients were enrolled in two groups: comprising 35 PCOS and 35 non PCOS women. Long protocol was performed for all patients. FF Hcy, glucose and E2 levels were analyzed at the time of oocyte retrieval. Results: It was observed that FF Hcy level was significantly higher in PCOS patients compared with non PCOSs (p<0.01). Observations demonstrated that in PCOS group, the Hcy level increased independent to E2, glucose levels, BMI and age, while the PCOS group showed significantly higher BMI compared with non-PCOS group (p=0.03). However, no significant differences were revealed between groups for FF glucose and E2 levels. Conclusion: Present data showed that although FF glucose and E2 levels were constant in PCOS and non PCOS patients, but the FF Hcy levels in PCOS were significantly increased (p=0.01). PMID:27679823

2. Analysis of skin patch test results and metalloproteinase-2 levels in a patient with contact dermatitis

PubMed Central

Czajkowski, Rafał; Kowaliszyn, Bogna; Żbikowska-Gotz, Magdalena; Bartuzi, Zbigniew

2015-01-01

Introduction The complex course of skin reactions that contact eczema involves is due in part to abnormalities of the extracellular matrix function. Proteins that degrade extracellular matrix components include metalloproteinases (MMP), which are divided into subcategories depending on the chemical structure and substrate specificity. Aim To analyse patch test results in contact dermatitis patients and to assess MMP-2 levels during skin lesion exacerbation and remission. Material and methods Fifty patients suffering from contact eczema were qualified to the study and 20 healthy volunteers as a control group. The study group patients had epidermal skin tests performed with the “European Standard” set. To assess the MMP-2 level in serum, venous blood was drawn, twice from study group patients – during contact dermatitis exacerbation and remission periods – and once from control group patients. Assessment of MMP-2 in serum was done with ELISA immunoassay. To verify the proposed hypotheses, parametric and nonparametric significance tests were used. Results Hands were the most frequent location of contact dermatitis. Nickel (II) sulphate was the most frequent sensitizing substance. Mean MMP-2 levels were statistically higher in the study group both in contact dermatitis exacerbation and remission periods than in the control group. There was no statistically significant difference between MMP-2 levels and skin patch test results. Conclusions Nickel is one of the most allergenic contact allergens in patients with contact dermatitis. Metalloproteinase-2 is a good marker of contact dermatitis in various stages of the disease. PMID:26161054

3. Towards Stability Analysis of Jump Linear Systems with State-Dependent and Stochastic Switching

NASA Technical Reports Server (NTRS)

Tejada, Arturo; Gonzalez, Oscar R.; Gray, W. Steven

2004-01-01

This paper analyzes the stability of hierarchical jump linear systems where the supervisor is driven by a Markovian stochastic process and by the values of the supervised jump linear system s states. The stability framework for this class of systems is developed over infinite and finite time horizons. The framework is then used to derive sufficient stability conditions for a specific class of hybrid jump linear systems with performance supervision. New sufficient stochastic stability conditions for discrete-time jump linear systems are also presented.

4. The Relationship Between CO2 Levels and CO2 Related Symptoms Reported on the ISS

NASA Technical Reports Server (NTRS)

VanBaalen, M.; Law, J.; Foy, M.; Wear, M. L.; Mason, S.; Mendez, C.; Meyers, V.

2014-01-01

5. Synthesis of hierarchical iron hydrogen phosphate crystal as a robust peroxidase mimic for stable H₂O₂ detection.

PubMed

Zhang, Tongbao; Lu, Yangcheng; Luo, Guangsheng

2014-08-27

To develop a green, cost-efficient and robust peroxidase mimic, micro/nano hierarchical morphology (for ease of separation and reuse), relative chemically stable composition (for ease of storage) and stable crystal structure (for long-term stability) are highly desired. Herein, using phosphoric acid as a chelating ligand to control the release of iron ions, hierarchical iron(III) hydrogen phosphate hydrate crystals are successfully prepared by nanosheets formation and following self-assembling in a facile low-temperature hydrothermal process. They are first found to have peroxidase-like activity and showed higher affinity for H2O2 and lower affinity for 3,3',5,5'-tetramethylbenzidine compared with horseradish peroxidase. The affinity feature is used for quantitative detection of H2O2 and shows a wide linear detection range from 57.4 to 525.8 μM (R(2) = 0.994) with a low detection limit of 1 μM. Benefited from chemical stability of hierarchical iron(III) salt crystals, they own good reproducibility (relative standard deviation = 1.95% for 10 independent measurements), long-term stability (no activity loss after 10 cycles), and ease of recovery (by simple centrifugation). Because the method is easily accessible, iron hydrogen phosphate hierarchical crystals have great potential for practical use of H2O2 sensing and detection under harsh conditions.

6. CuO nanoparticles incorporated in hierarchical MFI zeolite as highly active electrocatalyst for non-enzymatic glucose sensing.

PubMed

Dong, Junping; Tian, Taolei; Ren, Linxiao; Zhang, Yuan; Xu, Jiaqiang; Cheng, Xiaowei

2015-01-01

A hierarchical MFI zeolite, with typical micro/meso bimodal pore structures, was prepared by desilication method. CuO nanoparticles (NPs) were incorporated into the hierarchical MFI zeolite by impregnation method. CuO/hierarchical zeolite composites were characterized by X-ray diffraction, transmission electron microscopy and nitrogen sorption. It is shown that the CuO nanoparticles are mostly dispersed in the mesopores with remaining of the crystallinity and morphology of the host zeolite. CuO nanoparticles located in hierarchical zeolite exhibit the excellent electrocatalytic performances to oxidation of glucose in alkaline media. The electrocatalytic activity enhances with increasing the loading content of CuO from 5% to 15%. The composites were fabricated for nonenzyme glucose sensing. Under the optimal conditions, the sensor shows a wide linear range from 5×10(-7) to 1.84×10(-2) M with a low detection limit of 3.7×10(-7) M. The sensor also exhibits good repeatability, long-term stability as well as high selectivity against interfering species.

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

PubMed Central

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 ℓ2-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

8. SLAC Linear Collider

SciTech Connect

Richter, B.

1985-12-01

A report is given on the goals and progress of the SLAC Linear Collider. The status of the machine and the detectors are discussed and an overview is given of the physics which can be done at this new facility. Some ideas on how (and why) large linear colliders of the future should be built are given.

9. Linear Equations: Equivalence = Success

ERIC Educational Resources Information Center

Baratta, Wendy

2011-01-01

The ability to solve linear equations sets students up for success in many areas of mathematics and other disciplines requiring formula manipulations. There are many reasons why solving linear equations is a challenging skill for students to master. One major barrier for students is the inability to interpret the equals sign as anything other than…

10. Linear drug eruption.

PubMed

Alfonso, R; Belinchon, I

2001-01-01

Linear eruptions are sometimes associated with systemic diseases and they may also be induced by various drugs. Paradoxically, such acquired inflammatory skin diseases tend to follow the system of Blaschko's lines. We describe a case of unilateral linear drug eruption caused by ibuprofen, which later became bilateral and generalized.

11. Linearization of Robot Manipulators

NASA Technical Reports Server (NTRS)

Kreutz, Kenneth

1987-01-01

Four nonlinear control schemes equivalent. Report discusses theory of nonlinear feedback control of robot manipulator, emphasis on control schemes making manipulator input and output behave like decoupled linear system. Approach, called "exact external linearization," contributes efforts to control end-effector trajectories, positions, and orientations.

12. Catalytic test reactions for the evaluation of hierarchical zeolites.

PubMed

Hartmann, Martin; Machoke, Albert Gonche; Schwieger, Wilhelm

2016-06-13

Hierarchical zeolites have received increasing attention in the last decade due to their outstanding catalytic performance. Several types of hierarchical zeolites can be prepared by a large number of different techniques. Hierarchical zeolites combine the intrinsic catalytic properties of conventional zeolites and the facilitated access and transport in the additional meso- or macropore system. In this tutorial review, we discuss several test reactions that have been explored to show the benefit of the hierarchical pore system with respect to their suitability to prove the positive effects of hierarchical porous zeolites. It is important to note that positive effects on activity, stability and less frequently selectivity observed for hierarchically structured catalysts not necessarily are only a consequence of the additional meso- or macropores but also the number, strength and location of active sites as well as defects and impurities. With regard to these aspects, the test reaction has to be chosen carefully and potential changes in the chemistry of the catalyst have to be considered as well. In addition to the determination of conversion, yield and selectivity, we will show that the calculation of the activation energy and the determination of the Thiele modulus and the effectiveness factor are good indicators of the presence or absence of diffusion limitations in hierarchical zeolites compared to their parent materials.

13. Linear models: permutation methods

USGS Publications Warehouse

Cade, B.S.; Everitt, B.S.; Howell, D.C.

2005-01-01

Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...

14. Linear force device

NASA Technical Reports Server (NTRS)

Clancy, John P.

1988-01-01

The object of the invention is to provide a mechanical force actuator which is lightweight and manipulatable and utilizes linear motion for push or pull forces while maintaining a constant overall length. The mechanical force producing mechanism comprises a linear actuator mechanism and a linear motion shaft mounted parallel to one another. The linear motion shaft is connected to a stationary or fixed housing and to a movable housing where the movable housing is mechanically actuated through actuator mechanism by either manual means or motor means. The housings are adapted to releasably receive a variety of jaw or pulling elements adapted for clamping or prying action. The stationary housing is adapted to be pivotally mounted to permit an angular position of the housing to allow the tool to adapt to skewed interfaces. The actuator mechanisms is operated by a gear train to obtain linear motion of the actuator mechanism.

15. Hierarchical assemblies of Si3N4 nanostructures

Yao, Xiaohong; Huo, Huidan

2014-08-01

In the present work, for the first time, we report the growth of hierarchical assemblies of Si3N4 nanostructures via catalyst-assisted pyrolysis of a polymeric precursor on the Si substrates. The synthesized products were characterized by using field emission scanning electron microscopy, X-ray diffraction, and transmission electron microscopy. It is found that the size of the catalytic droplet plays a critical role on the formation of hierarchical assemblies of Si3N4 nanostructures rather than common single nanowire. A mechanism based on the Vapor-Liquid-Solid (VLS) process was proposed for the assembly of hierarchical Si3N4 nanostructures.

16. Adaptive mobility management scheme in hierarchical mobile IPv6

Fang, Bo; Song, Junde

2004-04-01

Hierarchical mobile IPv6 makes the mobility management localized. Registration with HA is only needed while MN moving between MAP domains. This paper proposed an adaptive mobility management scheme based on the hierarchical mobile IPv6. The scheme focuses on the MN operation as well as MAP operation during the handoff. Adaptive MAP selection algorithm can be used to select a suitable MAP to register with once MN moves into a new subnet while MAP can thus adaptively changing his management domain. Furthermore, MAP can also adaptively changes its level in the hierarchical referring on the service load or other related information. Detailed handoff algorithm is also discussed in this paper.

17. Maximizing the Divergence from a Hierarchical Model of Quantum States

Weis, Stephan; Knauf, Andreas; Ay, Nihat; Zhao, Ming-Jing

2015-03-01

We study many-party correlations quantified in terms of the Umegaki relative entropy (divergence) from a Gibbs family known as a hierarchical model. We derive these quantities from the maximum-entropy principle which was used earlier to define the closely related irreducible correlation. We point out the differences between quantum states and probability vectors which exist in hierarchical models, in the divergence from a hierarchical model and in local maximizers of this divergence. The differences are, respectively, missing factorization, discontinuity and reduction of uncertainty. We discuss global maximizers of the mutual information of separable qubit states.

18. On stable Pareto laws in a hierarchical model of economy

Chebotarev, A. M.

2007-01-01

This study considers a model of the income distribution of agents whose pairwise interaction is asymmetric and price-invariant. Asymmetric transactions are typical for chain-trading groups who arrange their business such that commodities move from senior to junior partners and money moves in the opposite direction. The price-invariance of transactions means that the probability of a pairwise interaction is a function of the ratio of incomes, which is independent of the price scale or absolute income level. These two features characterize the hierarchical model. The income distribution in this class of models is a well-defined double-Pareto function, which possesses Pareto tails for the upper and lower incomes. For gross and net upper incomes, the model predicts definite values of the Pareto exponents, agross and anet, which are stable with respect to quantitative variation of the pair-interaction. The Pareto exponents are also stable with respect to the choice of a demand function within two classes of status-dependent behavior of agents: linear demand ( agross=1, anet=2) and unlimited slowly varying demand ( agross=anet=1). For the sigmoidal demand that describes limited returns, agross=anet=1+α, with some α>0 satisfying a transcendental equation. The low-income distribution may be singular or vanishing in the neighborhood of the minimal income; in any case, it is L1-integrable and its Pareto exponent is given explicitly. The theory used in the present study is based on a simple balance equation and new results from multiplicative Markov chains and exponential moments of random geometric progressions.

19. A hierarchical perspective of plant diversity

USGS Publications Warehouse

Sarr, Daniel; Hibbs, D.E.; Huston, M.

2005-01-01

Predictive models of plant diversity have typically focused on either a landscapea??s capacity for richness (equilibrium models), or on the processes that regulate competitive exclusion, and thus allow species to coexist (nonequilibrium models). Here, we review the concepts and purposes of a hierarchical, multiscale model of the controls of plant diversity that incorporates the equilibrium model of climatic favorability at macroscales, nonequilibrium models of competition at microscales, and a mixed model emphasizing environmental heterogeneity at mesoscales. We evaluate the conceptual model using published data from three spatially nested datasets: (1) a macroscale analysis of ecoregions in the continental and western U.S.; (2) a mesoscale study in California; and (3) a microscale study in the Siskiyou Mountains of Oregon and California. At the macroscale (areas from 3889 km2 to 638,300 km2), climate (actual evaporation) was a strong predictor of tree diversity (R2 = 0.80), as predicted by the conceptual model, but area was a better predictor for vascular plant diversity overall (R2 = 0.38), which suggests different types of plants differ in their sensitivity to climatic controls. At mesoscales (areas from 1111 km2 to 15,833 km2 ), climate was still an important predictor of richness (R2 = 0.52), but, as expected, topographic heterogeneity explained an important share of the variance (R2 = 0.19), showed positive correlations with diversity of trees, shrubs, and annual and perennial herbs, and was the primary predictor of shrub and annual plant species richness. At microscales (0.1 ha plots), spatial patterns of diversity showed a clear unimodal pattern along a climatea??driven productivity gradient and a negative relationship with soil fertility. The strong decline in understory and total diversity at the most productive sites suggests that competitive controls, as predicted, can override climatic controls at this scale. We conclude that this hierarchical

20. Hierarchical Inorganic Assemblies for Artificial Photosynthesis.

PubMed

Kim, Wooyul; Edri, Eran; Frei, Heinz

2016-09-20

Artificial photosynthesis is an attractive approach for renewable fuel generation because it offers the prospect of a technology suitable for deployment on highly abundant, non-arable land. Recent leaps forward in the development of efficient and durable light absorbers and catalysts for oxygen evolution and the growing attention to catalysts for carbon dioxide activation brings into focus the tasks of hierarchically integrating the components into assemblies for closing of the photosynthetic cycle. A particular challenge is the efficient coupling of the multi-electron processes of CO2 reduction and H2O oxidation. Among the most important requirements for a complete integrated system are catalytic rates that match the solar flux, efficient charge transport between the various components, and scalability of the photosynthetic assembly on the unprecedented scale of terawatts in order to have impact on fuel consumption. To address these challenges, we have developed a heterogeneous inorganic materials approach with molecularly precise control of light absorption and charge transport pathways. Oxo-bridged heterobinuclear units with metal-to-metal charge-transfer transitions absorbing deep in the visible act as single photon, single charge transfer pumps for driving multi-electron catalysts. A photodeposition method has been introduced for the spatially directed assembly of nanoparticle catalysts for selective coupling to the donor or acceptor metal of the light absorber. For CO2 reduction, a Cu oxide cluster is coupled to the Zr center of a ZrOCo light absorber, while coupling of an Ir nanoparticle catalyst for water oxidation to the Co donor affords closing of the photosynthetic cycle of CO2 conversion by H2O to CO and O2. Optical, vibrational, and X-ray spectroscopy provide detailed structural knowledge of the polynuclear assemblies. Time resolved visible and rapid-scan FT-IR studies reveal charge transfer mechanisms and transient surface intermediates under

1. HIERARCHICAL FRAGMENTATION OF THE ORION MOLECULAR FILAMENTS

SciTech Connect

Takahashi, Satoko; Ho, Paul T. P.; Su, Yu-Nung; Teixeira, Paula S.; Zapata, Luis A.

2013-01-20

We present a high angular resolution map of the 850 {mu}m continuum emission of the Orion Molecular Cloud-3 (OMC 3) obtained with the Submillimeter Array (SMA); the map is a mosaic of 85 pointings covering an approximate area of 6.'5 Multiplication-Sign 2.'0 (0.88 Multiplication-Sign 0.27 pc). We detect 12 spatially resolved continuum sources, each with an H{sub 2} mass between 0.3-5.7 M {sub Sun} and a projected source size between 1400-8200 AU. All the detected sources are on the filamentary main ridge (n{sub H{sub 2}}{>=}10{sup 6} cm{sup -3}), and analysis based on the Jeans theorem suggests that they are most likely gravitationally unstable. Comparison of multi-wavelength data sets indicates that of the continuum sources, 6/12 (50%) are associated with molecular outflows, 8/12 (67%) are associated with infrared sources, and 3/12 (25%) are associated with ionized jets. The evolutionary status of these sources ranges from prestellar cores to protostar phase, confirming that OMC-3 is an active region with ongoing embedded star formation. We detect quasi-periodical separations between the OMC-3 sources of Almost-Equal-To 17''/0.035 pc. This spatial distribution is part of a large hierarchical structure that also includes fragmentation scales of giant molecular cloud ( Almost-Equal-To 35 pc), large-scale clumps ( Almost-Equal-To 1.3 pc), and small-scale clumps ( Almost-Equal-To 0.3 pc), suggesting that hierarchical fragmentation operates within the Orion A molecular cloud. The fragmentation spacings are roughly consistent with the thermal fragmentation length in large-scale clumps, while for small-scale cores it is smaller than the local fragmentation length. These smaller spacings observed with the SMA can be explained by either a helical magnetic field, cloud rotation, or/and global filament collapse. Finally, possible evidence for sequential fragmentation is suggested in the northern part of the OMC-3 filament.

2. Linear ubiquitination in immunity.

PubMed

Shimizu, Yutaka; Taraborrelli, Lucia; Walczak, Henning

2015-07-01

Linear ubiquitination is a post-translational protein modification recently discovered to be crucial for innate and adaptive immune signaling. The function of linear ubiquitin chains is regulated at multiple levels: generation, recognition, and removal. These chains are generated by the linear ubiquitin chain assembly complex (LUBAC), the only known ubiquitin E3 capable of forming the linear ubiquitin linkage de novo. LUBAC is not only relevant for activation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases (MAPKs) in various signaling pathways, but importantly, it also regulates cell death downstream of immune receptors capable of inducing this response. Recognition of the linear ubiquitin linkage is specifically mediated by certain ubiquitin receptors, which is crucial for translation into the intended signaling outputs. LUBAC deficiency results in attenuated gene activation and increased cell death, causing pathologic conditions in both, mice, and humans. Removal of ubiquitin chains is mediated by deubiquitinases (DUBs). Two of them, OTULIN and CYLD, are constitutively associated with LUBAC. Here, we review the current knowledge on linear ubiquitination in immune signaling pathways and the biochemical mechanisms as to how linear polyubiquitin exerts its functions distinctly from those of other ubiquitin linkage types.

3. Cafeteria diet increases prostaglandin E2 levels in rat prostate, kidney and testis.

PubMed

Brunetti, L; Leone, S; Chiavaroli, A; Orlando, G; Recinella, L; Ferrante, C; Di Nisio, C; Verratti, V; Vacca, M

2010-01-01

Nutrient composition, particularly the omega-6/omega-3 polyunsaturated fatty acids ratio, may differently affect inflammatory mediators production in tissues, which could be causally related to increased cancer incidence in obesity. We evaluated prostaglandin E(2) levels in male Wistar rat prostate, kidney and testicle tissues after 15 days of either a high fat, cafeteria-style diet (5.50 Kcal/g, 30 percent calories from fat, omega-6/omega-3 ratio 2.33) or a standard laboratory chow diet (3.35 Kcal/g, 3 percent calories from fat, omega-6/omega-3 ratio 0.56). In the cafeteria diet compared to standard laboratory diet rats, we found both an increase in weight gain and increased prostaglandin E(2) (PGE(2)) levels in prostate, kidney and testicle tissues. The increased levels of PGE(2) induced by the cafeteria diet could drive an inflammatory process leading to increased incidence of prostate, kidney and testicular cancer in overweight patients.

4. Lamb shift in the hydrogen atom: Lifetime of the 2p{1/2}level

SciTech Connect

Karshenboim, S.G.

1995-05-01

Corrections of order {alpha}(Z{alpha}){sup 2} to the width of the 2p{1/2} level in the hydrogen atom are considered in the logarithmic approximation. The ratio of this width to the splitting of n=2 states can be measured to high accuracy. With the aid of the experimental data available for this ratio, the new value for the Lamb splitting is found to be 1057.8576(21) MHz. 17 refs.

5. Serum annexin A2 levels in acute brucellosis and brucellar spondylodiscitis.

PubMed

Aktug Demir, N; Kolgelier, S; Sumer, S; Inkaya, A C; Ozcimen, S; Demir, L S; Ural, O; Arpaci, A

2014-10-01

Brucellosis is a chronic granulomatous infection and may present with various clinical manifestations. Brucellar spondylodiscitis symptoms are initially subtle and nonspecific. Annexin A2 (ANXA2) is involved in various biological functions, including osteoclast formation, bone resorption, and cell growth regulation. In this study, we aimed to determine the clinical significance of serum ANXA2 levels in acute brucellosis and brucellar spondylodiscitis. This prospective study included 96 acute brucellosis patients and 51 healthy controls. Acute brucellosis was diagnosed by a 1/160 or higher titer in a standard tube agglutination (STA) test or a four-fold increase in titers between two STA tests performed two weeks apart in the presence of clinical symptoms within the last eight weeks and/or growth of Brucella spp. in appropriately prepared culture media. ANXA2 levels were determined with an enzyme-linked immunosorbent assay (ELISA). Forty (41.7 %) of 96 acute brucellosis patients were male and 56 (58.3 %) were female. Serum ANXA2 levels were elevated in patients compared to healthy controls (p = 0.001). Eighteen of 96 (18.7 %) acute brucellosis patients had brucellar spondylodiscitis. The serum ANXA2 levels of patients with brucellar spondylodiscitis were higher than those of patients with acute disease without brucellar spondylodiscitis (p = 0.001). ANXA2, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) values were elevated in the brucellar spondylodiscitis group compared to patients without brucellar spondylodiscitis. Serum ANXA2 measurement together with ESR and CRP is thought to be indicative in the diagnosis of brucellar spondylodiscitis, a common complication of brucellosis.

6. Rising CO2 Levels Will Intensify Phytoplankton Blooms in Eutrophic and Hypertrophic Lakes

PubMed Central

Verspagen, Jolanda M. H.; Van de Waal, Dedmer B.; Finke, Jan F.; Visser, Petra M.; Van Donk, Ellen; Huisman, Jef

2014-01-01

Harmful algal blooms threaten the water quality of many eutrophic and hypertrophic lakes and cause severe ecological and economic damage worldwide. Dense blooms often deplete the dissolved CO2 concentration and raise pH. Yet, quantitative prediction of the feedbacks between phytoplankton growth, CO2 drawdown and the inorganic carbon chemistry of aquatic ecosystems has received surprisingly little attention. Here, we develop a mathematical model to predict dynamic changes in dissolved inorganic carbon (DIC), pH and alkalinity during phytoplankton bloom development. We tested the model in chemostat experiments with the freshwater cyanobacterium Microcystis aeruginosa at different CO2 levels. The experiments showed that dense blooms sequestered large amounts of atmospheric CO2, not only by their own biomass production but also by inducing a high pH and alkalinity that enhanced the capacity for DIC storage in the system. We used the model to explore how phytoplankton blooms of eutrophic waters will respond to rising CO2 levels. The model predicts that (1) dense phytoplankton blooms in low- and moderately alkaline waters can deplete the dissolved CO2 concentration to limiting levels and raise the pH over a relatively wide range of atmospheric CO2 conditions, (2) rising atmospheric CO2 levels will enhance phytoplankton blooms in low- and moderately alkaline waters with high nutrient loads, and (3) above some threshold, rising atmospheric CO2 will alleviate phytoplankton blooms from carbon limitation, resulting in less intense CO2 depletion and a lesser increase in pH. Sensitivity analysis indicated that the model predictions were qualitatively robust. Quantitatively, the predictions were sensitive to variation in lake depth, DIC input and CO2 gas transfer across the air-water interface, but relatively robust to variation in the carbon uptake mechanisms of phytoplankton. In total, these findings warn that rising CO2 levels may result in a marked intensification of

7. Optimal Linear Control.

DTIC Science & Technology

1979-12-01

OPTIMAL LINEAR CONTROL C.A. HARVEY M.G. SAFO NOV G. STEIN J.C. DOYLE HONEYWELL SYSTEMS & RESEARCH CENTER j 2600 RIDGWAY PARKWAY j [ MINNEAPOLIS...RECIPIENT’S CAT ALC-’ W.IMIJUff’? * J~’ CR2 15-238-4F TP P EI)ŕll * (~ Optimal Linear Control ~iOGRPR UBA m a M.G Lnar o Con_ _ _ _ _ _ R PORT__ _ _ I RE...Characterizations of optimal linear controls have been derived, from which guides for selecting the structure of the control system and the weights in

8. Linear magnetic bearing

NASA Technical Reports Server (NTRS)

Studer, P. A. (Inventor)

1983-01-01

A linear magnetic bearing system having electromagnetic vernier flux paths in shunt relation with permanent magnets, so that the vernier flux does not traverse the permanent magnet, is described. Novelty is believed to reside in providing a linear magnetic bearing having electromagnetic flux paths that bypass high reluctance permanent magnets. Particular novelty is believed to reside in providing a linear magnetic bearing with a pair of axially spaced elements having electromagnets for establishing vernier x and y axis control. The magnetic bearing system has possible use in connection with a long life reciprocating cryogenic refrigerator that may be used on the space shuttle.

9. A 2-Level Condensate with Tunable and Sharp Susceptibility Against the Magnetic Field

Li, Z. B.; Yao, D. X.; He, Y. Z.; Bao, C. G.

2016-01-01

A 2-level condensate of spin-1 Na atoms under a magnetic field B with its spin modes decoupled from its spatial modes is studied. This system can emerge at very low temperature by putting an atom with its spin down into a fully polarized condensate with all N-1 spins up, similar to embedding an impurity into a well-organized system. The most distinguished feature of this 2-level system is that it is inert to B in general, but extremely sensitive to B in a specific domain D-o-S around B_0 at which the energy gap between the two levels arrives at a minimum. Population oscillations are found and the underlying regularity is clarified and described by simple formulae. Therefore, the inherent dynamic parameters of the condensate can be known via the measurement of the population. The experimental condition that such a system can exist has been evaluated. Furthermore, there is a characteristic constant γ =0.278466 common to various 2-level systems. This constant provides a common upper bound γ kBT for the internal energy U of all these systems.

10. High sensitivity to chronically elevated CO2 levels in a eurybathic marine sipunculid.

PubMed

Langenbuch, M; Pörtner, H O

2004-10-18

CO2 levels are expected to rise (a) in surface waters of the oceans as atmospheric accumulation continues or (b) in the deep sea, once industrial CO2 dumping is implemented. These scenarios suggest that CO2 will become a general stress factor in aquatic environments. The mechanisms of sensitivity to CO2 as well as adaptation capacity of marine animals are insufficiently understood. Here, we present data obtained in Sipunculus nudus, a sediment-dwelling marine worm that is able to undergo drastic metabolic depression to survive regular exposure to elevated CO2 levels within its natural habitat. We investigated animal survival and the proximate biochemical body composition during long-term CO2 exposure. Results indicate an unexpected and pronounced sensitivity characterized by the delayed onset of enhanced mortality at CO2 levels within the natural range of concentrations. Therefore, the present study contrasts the previously assumed high-CO2 tolerance of animals adapted to temporary hypercapnia. As a consequence, we expect future loss of species and, thereby, detrimental effects on marine benthic ecosystems with as yet poorly defined critical thresholds of long-term tolerance to CO2.

11. Maintenance of CO2 level in a BLSS by controlling solid waste treatment unit

Dong, Yingying; Li, Leyuan; Liu, Hong; Fu, Yuming; Xie, Beizhen; Hu, Dawei; Liu, Dianlei; Dong, Chen; Liu, Guanghui

A bioregenerative life support system (BLSS) is an artificial closed ecosystem for providing basic human life support for long-duration, far-distance space explorations such as lunar bases. In such a system, the circulation of gases is one of the main factor for realizing a higher closure degree. O2 produced by higher plants goes to humans, as well as microorganisms for the treatment of inedible plant biomass and human wastes; CO2 produced by the crew and microorganisms is provided for plant growth. During this process, an excessively high CO2 level will depress plant growth and may be harmful to human health; and if the CO2 level is too low, plant growth will also be affected. Thus, keeping the balance between CO2 and O2 levels is a crucial problem. In this study, a high-efficiency, controllable solid waste treatment unit is constructed, which adopts microbial fermentation of the mixture of inedible biomass and human wastes. CO2 production during the fermentation process is controlled by adjusting fermentation temperature, aeration rate, moisture, etc., so as to meet the CO2 requirement of plants

12. Dynamic hierarchical algorithm for accelerated microfossil identification

Wong, Cindy M.; Joseph, Dileepan

2015-02-01

Marine microfossils provide a useful record of the Earth's resources and prehistory via biostratigraphy. To study Hydrocarbon reservoirs and prehistoric climate, geoscientists visually identify the species of microfossils found in core samples. Because microfossil identification is labour intensive, automation has been investigated since the 1980s. With the initial rule-based systems, users still had to examine each specimen under a microscope. While artificial neural network systems showed more promise for reducing expert labour, they also did not displace manual identification for a variety of reasons, which we aim to overcome. In our human-based computation approach, the most difficult step, namely taxon identification is outsourced via a frontend website to human volunteers. A backend algorithm, called dynamic hierarchical identification, uses unsupervised, supervised, and dynamic learning to accelerate microfossil identification. Unsupervised learning clusters specimens so that volunteers need not identify every specimen during supervised learning. Dynamic learning means interim computation outputs prioritize subsequent human inputs. Using a dataset of microfossils identified by an expert, we evaluated correct and incorrect genus and species rates versus simulated time, where each specimen identification defines a moment. The proposed algorithm accelerated microfossil identification effectively, especially compared to benchmark results obtained using a k-nearest neighbour method.

13. Hierarchical structure and biomineralization in cricket teeth

Xing, Xue-Qing; Gong, Yu; Cai, Quan; Mo, Guang; Du, Rong; Chen, Zhong-Jun; Wu, Zhong-Hua

2013-02-01

The cricket is a truculent insect with stiff and sharp teeth as a fighting weapon. The structure and possible biomineralization of cricket teeth are always interesting. Synchrotron radiation X-ray fluorescence, X-ray diffraction, and small angle X-ray scattering techniques were used to probe the element distribution, possible crystalline structures and size distribution of scatterers in cricket teeth. A scanning electron microscope was used to observe the nanoscaled structure. The results demonstrate that Zn is the main heavy element in cricket teeth. The surface of a cricket tooth has a crystalline compound like ZnFe2(AsO4)2(OH)2(H2O)4. The interior of the tooth has a crystalline compound like ZnCl2, which is from the biomineralization. The ZnCl2-like biomineral forms nanoscaled microfibrils and their axial direction points towards the top of the tooth cusp. The microfibrils aggregate randomly into intermediate filaments, forming a hierarchical structure. A sketch map of the cricket tooth cusp is proposed and a detailed discussion is given in this paper.

14. Modeling abundance using hierarchical distance sampling

USGS Publications Warehouse

Royle, Andy; Kery, Marc

2016-01-01

In this chapter, we provide an introduction to classical distance sampling ideas for point and line transect data, and for continuous and binned distance data. We introduce the conditional and the full likelihood, and we discuss Bayesian analysis of these models in BUGS using the idea of data augmentation, which we discussed in Chapter 7. We then extend the basic ideas to the problem of hierarchical distance sampling (HDS), where we have multiple point or transect sample units in space (or possibly in time). The benefit of HDS in practice is that it allows us to directly model spatial variation in population size among these sample units. This is a preeminent concern of most field studies that use distance sampling methods, but it is not a problem that has received much attention in the literature. We show how to analyze HDS models in both the unmarked package and in the BUGS language for point and line transects, and for continuous and binned distance data. We provide a case study of HDS applied to a survey of the island scrub-jay on Santa Cruz Island, California.

15. Multichannel hierarchical image classification using multivariate copulas

Voisin, Aurélie; Krylov, Vladimir A.; Moser, Gabriele; Serpico, Sebastiano B.; Zerubia, Josiane

2012-03-01

This paper focuses on the classification of multichannel images. The proposed supervised Bayesian classification method applied to histological (medical) optical images and to remote sensing (optical and synthetic aperture radar) imagery consists of two steps. The first step introduces the joint statistical modeling of the coregistered input images. For each class and each input channel, the class-conditional marginal probability density functions are estimated by finite mixtures of well-chosen parametric families. For optical imagery, the normal distribution is a well-known model. For radar imagery, we have selected generalized gamma, log-normal, Nakagami and Weibull distributions. Next, the multivariate d-dimensional Clayton copula, where d can be interpreted as the number of input channels, is applied to estimate multivariate joint class-conditional statistics. As a second step, we plug the estimated joint probability density functions into a hierarchical Markovian model based on a quadtree structure. Multiscale features are extracted by discrete wavelet transforms, or by using input multiresolution data. To obtain the classification map, we integrate an exact estimator of the marginal posterior mode.

16. Formal Foundations for Hierarchical Safety Cases

NASA Technical Reports Server (NTRS)

Denney, Ewen; Pai, Ganesh; Whiteside, Iain

2015-01-01

Safety cases are increasingly being required in many safety-critical domains to assure, using structured argumentation and evidence, that a system is acceptably safe. However, comprehensive system-wide safety arguments present appreciable challenges to develop, understand, evaluate, and manage, partly due to the volume of information that they aggregate, such as the results of hazard analysis, requirements analysis, testing, formal verification, and other engineering activities. Previously, we have proposed hierarchical safety cases, hicases, to aid the comprehension of safety case argument structures. In this paper, we build on a formal notion of safety case to formalise the use of hierarchy as a structuring technique, and show that hicases satisfy several desirable properties. Our aim is to provide a formal, theoretical foundation for safety cases. In particular, we believe that tools for high assurance systems should be granted similar assurance to the systems to which they are applied. To this end, we formally specify and prove the correctness of key operations for constructing and managing hicases, which gives the specification for implementing hicases in AdvoCATE, our toolset for safety case automation. We motivate and explain the theory with the help of a simple running example, extracted from a real safety case and developed using AdvoCATE.

17. Hierarchical detection of rectangles in images

Hasan, Mohamed; Abdellatif, Mohamed; Babaguchi, Noborou

2016-07-01

This paper proposes a new technique for rectangle detection in images based on hierarchical feature complexity. The algorithm follows a bottom-up/top-down approach: in the bottom-up phase, contour curves are extracted and its edges are fit to straight lines. Long contours may grow away from the object boundary and they may not complete a loop due to missing edges. The proposed algorithm introduces a solution to such problems in the top-down phase through two simple rules. First, contours are split into segments at the point where non-convexity occurs since this is the point where long contours depart from the object boundary. Second, the split segments are classified into six classes according to their probability of being a rectangle depending on the numbers of the segment sides and right angles they enclose. These classes are then completed into rectangles by searching for suitable lines that may have been missed during the bottom-up phase. The method is verified through experiments on a set of images covering several applications. The results are compared to state of the art methods and benchmarked to groundtruth.

18. Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.

19. Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, Mevin B.; Wikle, Christopher K.; Dorazio, Robert M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.

20. HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

SciTech Connect

Schneider, Michael D.; Dawson, William A.; Hogg, David W.; Marshall, Philip J.; Bard, Deborah J.; Meyers, Joshua; Lang, Dustin

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

1. Fluorocarbon adsorption in hierarchical porous frameworks

SciTech Connect

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.

2. Dynamics of influence on hierarchical structures

Fotouhi, Babak; Rabbat, Michael G.

2013-08-01

Dichotomous spin dynamics on a pyramidal hierarchical structure (the Bethe lattice) are studied. The system embodies a number of classes, where a class comprises nodes that are equidistant from the root (head node). Weighted links exist between nodes from the same and different classes. The spin (hereafter state) of the head node is fixed. We solve for the dynamics of the system for different boundary conditions. We find necessary conditions so that the classes eventually repudiate or acquiesce in the state imposed by the head node. The results indicate that to reach unanimity across the hierarchy, it suffices that the bottommost class adopts the same state as the head node. Then the rest of the hierarchy will inevitably comply. This also sheds light on the importance of mass media as a means of synchronization between the topmost and bottommost classes. Surprisingly, in the case of discord between the head node and the bottommost classes, the average state over all nodes inclines towards that of the bottommost class regardless of the link weights and intraclass configurations. Hence the role of the bottommost class is signified.

3. Expectation and attention in hierarchical auditory prediction.

PubMed

Chennu, Srivas; Noreika, Valdas; Gueorguiev, David; Blenkmann, Alejandro; Kochen, Silvia; Ibáñez, Agustín; Owen, Adrian M; Bekinschtein, Tristan A

2013-07-03

Hierarchical predictive coding suggests that attention in humans emerges from increased precision in probabilistic inference, whereas expectation biases attention in favor of contextually anticipated stimuli. We test these notions within auditory perception by independently manipulating top-down expectation and attentional precision alongside bottom-up stimulus predictability. Our findings support an integrative interpretation of commonly observed electrophysiological signatures of neurodynamics, namely mismatch negativity (MMN), P300, and contingent negative variation (CNV), as manifestations along successive levels of predictive complexity. Early first-level processing indexed by the MMN was sensitive to stimulus predictability: here, attentional precision enhanced early responses, but explicit top-down expectation diminished it. This pattern was in contrast to later, second-level processing indexed by the P300: although sensitive to the degree of predictability, responses at this level were contingent on attentional engagement and in fact sharpened by top-down expectation. At the highest level, the drift of the CNV was a fine-grained marker of top-down expectation itself. Source reconstruction of high-density EEG, supported by intracranial recordings, implicated temporal and frontal regions differentially active at early and late levels. The cortical generators of the CNV suggested that it might be involved in facilitating the consolidation of context-salient stimuli into conscious perception. These results provide convergent empirical support to promising recent accounts of attention and expectation in predictive coding.

4. Automatic Construction of Hierarchical Road Networks

Yang, Weiping

2016-06-01

This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.

5. The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

6. Automatic layout of structured hierarchical reports.

PubMed

Bakke, Eirik; Karger, David R; Miller, Robert C

2013-12-01

Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets.

7. Hierarchical nonlinear dynamics of human attention.

PubMed

Rabinovich, Mikhail I; Tristan, Irma; Varona, Pablo

2015-08-01

Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions.

8. Hierarchical characterization procedures for dimensional metrology

MacKinnon, David; Beraldin, Jean-Angelo; Cournoyer, Luc; Carrier, Benjamin

2011-03-01

We present a series of dimensional metrology procedures for evaluating the geometrical performance of a 3D imaging system that have either been designed or modified from existing procedures to ensure, where possible, statistical traceability of each characteristic value from the certified reference surface to the certifying laboratory. Because there are currently no internationally-accepted standards for characterizing 3D imaging systems, these procedures have been designed to avoid using characteristic values provided by the vendors of 3D imaging systems. For this paper, we focus only on characteristics related to geometric surface properties, dividing them into surface form precision and surface fit trueness. These characteristics have been selected to be familiar to operators of 3D imaging systems that use Geometrical Dimensioning and Tolerancing (GD&T). The procedures for generating characteristic values would form the basis of either a volumetric or application-specific analysis of the characteristic profile of a 3D imaging system. We use a hierarchical approach in which each procedure builds on either certified reference values or previously-generated characteristic values. Starting from one of three classes of surface forms, we demonstrate how procedures for quantifying for flatness, roundness, angularity, diameter error, angle error, sphere-spacing error, and unidirectional and bidirectional plane-spacing error are built upon each other. We demonstrate how these procedures can be used as part of a process for characterizing the geometrical performance of a 3D imaging system.

9. Dynamics of influence on hierarchical structures.

PubMed

Fotouhi, Babak; Rabbat, Michael G

2013-08-01

Dichotomous spin dynamics on a pyramidal hierarchical structure (the Bethe lattice) are studied. The system embodies a number of classes, where a class comprises nodes that are equidistant from the root (head node). Weighted links exist between nodes from the same and different classes. The spin (hereafter state) of the head node is fixed. We solve for the dynamics of the system for different boundary conditions. We find necessary conditions so that the classes eventually repudiate or acquiesce in the state imposed by the head node. The results indicate that to reach unanimity across the hierarchy, it suffices that the bottommost class adopts the same state as the head node. Then the rest of the hierarchy will inevitably comply. This also sheds light on the importance of mass media as a means of synchronization between the topmost and bottommost classes. Surprisingly, in the case of discord between the head node and the bottommost classes, the average state over all nodes inclines towards that of the bottommost class regardless of the link weights and intraclass configurations. Hence the role of the bottommost class is signified.

10. Hierarchical Bayesian models of subtask learning.

PubMed

Anglim, Jeromy; Wynton, Sarah K A

2015-07-01

11. Hierarchical group dynamics in pigeon flocks.

PubMed

Nagy, Máté; Akos, Zsuzsa; Biro, Dora; Vicsek, Tamás

2010-04-08

Animals that travel together in groups display a variety of fascinating motion patterns thought to be the result of delicate local interactions among group members. Although the most informative way of investigating and interpreting collective movement phenomena would be afforded by the collection of high-resolution spatiotemporal data from moving individuals, such data are scarce and are virtually non-existent for long-distance group motion within a natural setting because of the associated technological difficulties. Here we present results of experiments in which track logs of homing pigeons flying in flocks of up to 10 individuals have been obtained by high-resolution lightweight GPS devices and analysed using a variety of correlation functions inspired by approaches common in statistical physics. We find a well-defined hierarchy among flock members from data concerning leading roles in pairwise interactions, defined on the basis of characteristic delay times between birds' directional choices. The average spatial position of a pigeon within the flock strongly correlates with its place in the hierarchy, and birds respond more quickly to conspecifics perceived primarily through the left eye-both results revealing differential roles for birds that assume different positions with respect to flock-mates. From an evolutionary perspective, our results suggest that hierarchical organization of group flight may be more efficient than an egalitarian one, at least for those flock sizes that permit regular pairwise interactions among group members, during which leader-follower relationships are consistently manifested.

12. Fluorocarbon adsorption in hierarchical porous frameworks

Motkuri, Radha Kishan; Annapureddy, Harsha V. R.; Vijaykumar, M.; Schaef, H. Todd; Martin, Paul F.; McGrail, B. Peter; Dang, Liem X.; Krishna, Rajamani; Thallapally, Praveen K.

2014-07-01

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/Po) of 0.02. In contrast, the mesoporous framework shows an exceptionally high uptake capacity reaching >14 mmol g-1 at P/Po 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.

13. Hierarchical Bayesian inference in the visual cortex

Lee, Tai Sing; Mumford, David

2003-07-01

Traditional views of visual processing suggest that early visual neurons in areas V1 and V2 are static spatiotemporal filters that extract local features from a visual scene. The extracted information is then channeled through a feedforward chain of modules in successively higher visual areas for further analysis. Recent electrophysiological recordings from early visual neurons in awake behaving monkeys reveal that there are many levels of complexity in the information processing of the early visual cortex, as seen in the long-latency responses of its neurons. These new findings suggest that activity in the early visual cortex is tightly coupled and highly interactive with the rest of the visual system. They lead us to propose a new theoretical setting based on the mathematical framework of hierarchical Bayesian inference for reasoning about the visual system. In this framework, the recurrent feedforward/feedback loops in the cortex serve to integrate top-down contextual priors and bottom-up observations so as to implement concurrent probabilistic inference along the visual hierarchy. We suggest that the algorithms of particle filtering and Bayesian-belief propagation might model these interactive cortical computations. We review some recent neurophysiological evidences that support the plausibility of these ideas. 2003 Optical Society of America

14. Hierarchical programming for data storage and visualization

USGS Publications Warehouse

Donovan, J.M.; Smith, P.E.; ,

2001-01-01

Graphics software is an essential tool for interpreting, analyzing, and presenting data from multidimensional hydrodynamic models used in estuarine and coastal ocean studies. The post-processing of time-varying three-dimensional model output presents unique requirements for data visualization because of the large volume of data that can be generated and the multitude of time scales that must be examined. Such data can relate to estuarine or coastal ocean environments and come from numerical models or field instruments. One useful software tool for the display, editing, visualization, and printing of graphical data is the Gr application, written by the first author for use in U.S. Geological Survey San Francisco Bay Program. The Gr application has been made available to the public via the Internet since the year 2000. The Gr application is written in the Java (Sun Microsystems, Nov. 29, 2001) programming language and uses the Extensible Markup Language standard for hierarchical data storage. Gr presents a hierarchy of objects to the user that can be edited using a common interface. Java's object-oriented capabilities allow Gr to treat data, graphics, and tools equally and to save them all to a single XML file.

15. Relativized hierarchical decomposition of Markov decision processes.

PubMed

Ravindran, B

2013-01-01

Reinforcement Learning (RL) is a popular paradigm for sequential decision making under uncertainty. A typical RL algorithm operates with only limited knowledge of the environment and with limited feedback on the quality of the decisions. To operate effectively in complex environments, learning agents require the ability to form useful abstractions, that is, the ability to selectively ignore irrelevant details. It is difficult to derive a single representation that is useful for a large problem setting. In this chapter, we describe a hierarchical RL framework that incorporates an algebraic framework for modeling task-specific abstraction. The basic notion that we will explore is that of a homomorphism of a Markov Decision Process (MDP). We mention various extensions of the basic MDP homomorphism framework in order to accommodate different commonly understood notions of abstraction, namely, aspects of selective attention. Parts of the work described in this chapter have been reported earlier in several papers (Narayanmurthy and Ravindran, 2007, 2008; Ravindran and Barto, 2002, 2003a,b; Ravindran et al., 2007).

16. Hierarchical organization of ferrocene-peptides.

PubMed

Beheshti, Samaneh; Martić, Sanela; Kraatz, Heinz-Bernhard

2012-07-16

Hierarchical self-assembly of disubstituted ferrocene (Fc)-peptide conjugates that possess Gly-Val-Phe and Gly-Val-Phe-Phe peptide substituents leads to the formation of nano- and micro-sized assemblies. Hydrogen-bonding and hydrophobic interactions provide directionality to the assembly patterns. The self-assembling behavior of these compounds was studied in solution by using (1)H NMR and circular dichroism (CD) spectroscopies. In the solid state, attenuated total reflectance (ATR) FTIR spectroscopy, single-crystal X-ray diffraction (XRD), powder X-ray diffraction (PXRD), and scanning electron microscopy (SEM) methods were used. Spontaneous self-assembly of Fc-peptides through intra- and intermolecular hydrogen-bonding interactions induces supramolecular assemblies, which further associate and give rise to fibers, large fibrous crystals, and twisted ropes. In the case of Fc[CO-Gly-Val-Phe-OMe](2) (1), molecules initially interact to form pleated sheets that undergo association into long fibers that form bundles and rectangular crystalline cuboids. Molecular offsets and defects, such as screw dislocations and solvent effects that occur during crystal growth, induce the formation of helical arrangements, ultimately leading to large twisted ropes. By contrast, the Fc-tetrapeptide conjugate Fc[CO-Gly-Val-Phe-Phe-OMe](2) (2) forms a network of nanofibers at the supramolecular level, presumably due to the additional hydrogen-bonding and hydrophobic interactions that stem from the additional Phe residues.

17. Hierarchical cosmic shear power spectrum inference

Alsing, Justin; Heavens, Alan; Jaffe, Andrew H.; Kiessling, Alina; Wandelt, Benjamin; Hoffmann, Till

2016-02-01

We develop a Bayesian hierarchical modelling approach for cosmic shear power spectrum inference, jointly sampling from the posterior distribution of the cosmic shear field and its (tomographic) power spectra. Inference of the shear power spectrum is a powerful intermediate product for a cosmic shear analysis, since it requires very few model assumptions and can be used to perform inference on a wide range of cosmological models a posteriori without loss of information. We show that joint posterior for the shear map and power spectrum can be sampled effectively by Gibbs sampling, iteratively drawing samples from the map and power spectrum, each conditional on the other. This approach neatly circumvents difficulties associated with complicated survey geometry and masks that plague frequentist power spectrum estimators, since the power spectrum inference provides prior information about the field in masked regions at every sampling step. We demonstrate this approach for inference of tomographic shear E-mode, B-mode and EB-cross power spectra from a simulated galaxy shear catalogue with a number of important features; galaxies distributed on the sky and in redshift with photometric redshift uncertainties, realistic random ellipticity noise for every galaxy and a complicated survey mask. The obtained posterior distributions for the tomographic power spectrum coefficients recover the underlying simulated power spectra for both E- and B-modes.

18. Cortical tracking of hierarchical linguistic structures in connected speech.

PubMed

Ding, Nai; Melloni, Lucia; Zhang, Hang; Tian, Xing; Poeppel, David

2016-01-01

The most critical attribute of human language is its unbounded combinatorial nature: smaller elements can be combined into larger structures on the basis of a grammatical system, resulting in a hierarchy of linguistic units, such as words, phrases and sentences. Mentally parsing and representing such structures, however, poses challenges for speech comprehension. In speech, hierarchical linguistic structures do not have boundaries that are clearly defined by acoustic cues and must therefore be internally and incrementally constructed during comprehension. We found that, during listening to connected speech, cortical activity of different timescales concurrently tracked the time course of abstract linguistic structures at different hierarchical levels, such as words, phrases and sentences. Notably, the neural tracking of hierarchical linguistic structures was dissociated from the encoding of acoustic cues and from the predictability of incoming words. Our results indicate that a hierarchy of neural processing timescales underlies grammar-based internal construction of hierarchical linguistic structure.

19. Cortical Tracking of Hierarchical Linguistic Structures in Connected Speech

PubMed Central

Ding, Nai; Melloni, Lucia; Zhang, Hang; Tian, Xing; Poeppel, David

2016-01-01

The most critical attribute of human language is its unbounded combinatorial nature: smaller elements can be combined into larger structures based on a grammatical system, resulting in a hierarchy of linguistic units, e.g., words, phrases, and sentences. Mentally parsing and representing such structures, however, poses challenges for speech comprehension. In speech, hierarchical linguistic structures do not have boundaries clearly defined by acoustic cues and must therefore be internally and incrementally constructed during comprehension. Here we demonstrate that during listening to connected speech, cortical activity of different time scales concurrently tracks the time course of abstract linguistic structures at different hierarchical levels, e.g. words, phrases, and sentences. Critically, the neural tracking of hierarchical linguistic structures is dissociated from the encoding of acoustic cues as well as from the predictability of incoming words. The results demonstrate that a hierarchy of neural processing timescales underlies grammar-based internal construction of hierarchical linguistic structure. PMID:26642090

20. A Hierarchical Clustering Methodology for the Estimation of Toxicity

EPA Science Inventory

A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

1. Estimation of Carcinogenicity using Hierarchical Clustering and Nearest Neighbor Methodologies

EPA Science Inventory

Previously a hierarchical clustering (HC) approach and a nearest neighbor (NN) approach were developed to model acute aquatic toxicity end points. These approaches were developed to correlate the toxicity for large, noncongeneric data sets. In this study these approaches applie...

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

USGS Publications Warehouse

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)

3. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

EPA Science Inventory

Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

4. Modeling the deformation behavior of nanocrystalline alloy with hierarchical microstructures

Liu, Hongxi; Zhou, Jianqiu; Zhao, Yonghao

2016-02-01

A mechanism-based plasticity model based on dislocation theory is developed to describe the mechanical behavior of the hierarchical nanocrystalline alloys. The stress-strain relationship is derived by invoking the impeding effect of the intra-granular solute clusters and the inter-granular nanostructures on the dislocation movements along the sliding path. We found that the interaction between dislocations and the hierarchical microstructures contributes to the strain hardening property and greatly influence the ductility of nanocrystalline metals. The analysis indicates that the proposed model can successfully describe the enhanced strength of the nanocrystalline hierarchical alloy. Moreover, the strain hardening rate is sensitive to the volume fraction of the hierarchical microstructures. The present model provides a new perspective to design the microstructures for optimizing the mechanical properties in nanostructural metals.

5. Hierarchical Ag mesostructures for single particle SERS substrate

Xu, Minwei; Zhang, Yin

2017-01-01

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 106.

6. Age differences in the perception of hierarchical structure in events.

PubMed

Kurby, Christopher A; Zacks, Jeffrey M

2011-01-01

Everyday activities break down into parts and subparts, and appreciating this hierarchical structure is an important component of understanding. In two experiments we found age differences in the ability to perceive hierarchical structure in continuous activity. In both experiments, younger and older adults segmented movies of everyday activities into large and small meaningful events. Older adults' segmentation deviated more from group norms than did younger adults' segmentation, and older adults' segmentation was less hierarchically organized than that of younger adults. Older adults performed less well than younger adults on event memory tasks. In some cases, measures of event segmentation discriminated between those older adults with better and worse memory. These results suggest that the hierarchical encoding of ongoing activity declines with age, and that such encoding may be important for memory.

7. Age Differences in the Perception of Hierarchical Structure in Events

PubMed Central

Kurby, Christopher A.; Zacks, Jeffrey M.

2011-01-01

Everyday activities break down into parts and subparts, and appreciating this hierarchical structure is an important component of understanding. In two experiments we found age differences in the ability to perceive hierarchical structure in continuous activity. In both experiments, younger and older adults segmented movies of everyday activities into large and small meaningful events. Older adults’ segmentation deviated more from group norms than did younger adults’ segmentation, and older adults’ segmentation was less hierarchically organized than that of younger adults. Older adults performed less well than younger adults on event memory tasks. In some cases, measures of event segmentation discriminated between those older adults with better and worse memory. These results suggest that the hierarchical encoding of ongoing activity declines with age, and that such encoding may be important for memory. PMID:21264613

8. Inertial Linear Actuators

NASA Technical Reports Server (NTRS)

Laughlin, Darren

1995-01-01

Inertial linear actuators developed to suppress residual accelerations of nominally stationary or steadily moving platforms. Function like long-stroke version of voice coil in conventional loudspeaker, with superimposed linear variable-differential transformer. Basic concept also applicable to suppression of vibrations of terrestrial platforms. For example, laboratory table equipped with such actuators plus suitable vibration sensors and control circuits made to vibrate much less in presence of seismic, vehicular, and other environmental vibrational disturbances.

9. Linear system theory

NASA Technical Reports Server (NTRS)

Callier, Frank M.; Desoer, Charles A.

1991-01-01

The aim of this book is to provide a systematic and rigorous access to the main topics of linear state-space system theory in both the continuous-time case and the discrete-time case; and the I/O description of linear systems. The main thrusts of the work are the analysis of system descriptions and derivations of their properties, LQ-optimal control, state feedback and state estimation, and MIMO unity-feedback systems.

10. Linear Resonance Cooler.

DTIC Science & Technology

1985-04-01

for a Stirling cycle cryocooler . 26 * .*o .. * COMPRESSOR MOTOR FORCE VERSUS ROTOR AXIAL POSITION COMPRESSOR P-V DIAGRAM *COMPRESSOR MOTOR COMPRESSOR...potential. However, the limited test program has demonstrated the application of linear motor drive technology to a Stirling cycle cryocooler design. L...Ace-ss Ion& For flTIC TAB - TABLE OF CONTENTS TITLE IPAGE - 2. DETAILED DESIGN OF LINEAR RESONANCE CRYOCOOLER ......... 3 2.2 Expander

11. Non-Linear Control Allocation Using Piecewise Linear Functions

DTIC Science & Technology

2003-08-01

A novel method is presented for the solution of the non- linear control allocation problem. Historically, control allocation has been performed by... linear control allocation problem to be cast as a piecewise linear program. The piecewise linear program is ultimately cast as a mixed-integer linear...piecewise linear control allocation method is shown to be markedly improved when compared to the performance of a more traditional control allocation approach that assumes linearity.

12. Stabilizing hierarchical compensation for locally controlled large flexible structures

NASA Technical Reports Server (NTRS)

Das, B.; Balas, M.

1989-01-01

A two-level hierarchical control strategy is proposed for large flexible space structures. The lower level consists of a set of local controllers. The higher level is a stabilizing compensator to account for any instabilities caused by controller-structure interaction with unmodeled dynamics. The advantage of this hierarchical strategy is that the lower level can be designed to meet the performance requirements, and the higher level can be designed independently to produce overall stability.

13. A Comparision of Heuristic Methods Used in Hierarchical Production Planning.

DTIC Science & Technology

1979-03-01

1965). ~~~. Golovin , J. J.; “Hierarchical Integration of Planning and Control”, M.I.T., Operations Research Center, Technical Report No. 116...Nostrand Reinhold , 1978. 9. flax, A. C. and J. J. Golovin ; “Computer Based Operations Management System (COMS)” , Studieä in Operations Management (A. C...flax , ed.), North Holland—American Elsevier, 1978. 10. flax, A. C. and J. J. Golovin ; “Hierarchical Production Planning Systems”, M.I.T

14. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

DTIC Science & Technology

2016-01-05

events (and subsequently, their likelihood of occurrence) based on historical evidence of the counts of previous event occurrences. The novel Bayesian...Aug-2014 22-May-2015 Approved for Public Release; Distribution Unlimited Final Report: Sparse Event Modeling with Hierarchical Bayesian Kernel Methods...Sparse Event Modeling with Hierarchical Bayesian Kernel Methods Report Title The research objective of this proposal was to develop a predictive Bayesian

15. Micromechanical design of hierarchical composites using global load sharing theory

Rajan, V. P.; Curtin, W. A.

2016-05-01

Hierarchical composites, embodied by natural materials ranging from bone to bamboo, may offer combinations of material properties inaccessible to conventional composites. Using global load sharing (GLS) theory, a well-established micromechanics model for composites, we develop accurate numerical and analytical predictions for the strength and toughness of hierarchical composites with arbitrary fiber geometries, fiber strengths, interface properties, and number of hierarchical levels, N. The model demonstrates that two key material properties at each hierarchical level-a characteristic strength and a characteristic fiber length-control the scalings of composite properties. One crucial finding is that short- and long-fiber composites behave radically differently. Long-fiber composites are significantly stronger than short-fiber composites, by a factor of 2N or more; they are also significantly tougher because their fiber breaks are bridged by smaller-scale fibers that dissipate additional energy. Indeed, an "infinite" fiber length appears to be optimal in hierarchical composites. However, at the highest level of the composite, long fibers localize on planes of pre-existing damage, and thus short fibers must be employed instead to achieve notch sensitivity and damage tolerance. We conclude by providing simple guidelines for microstructural design of hierarchical composites, including the selection of N, the fiber lengths, the ratio of length scales at successive hierarchical levels, the fiber volume fractions, and the desired properties of the smallest-scale reinforcement. Our model enables superior hierarchical composites to be designed in a rational way, without resorting either to numerical simulation or trial-and-error-based experimentation.

16. A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection

DTIC Science & Technology

2012-04-01

6] K. Ranney and M. Soumekh, “Signal subspace change detection in averaged multilook sar imagery,” Geoscience and Remote Sensing, IEEE Transactions on...A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection Gregory E. Newstadta, Edmund G. Zelniob, and Alfred O. Hero IIIa...Base, OH, 45433, USA ABSTRACT This paper proposes a hierarchical Bayesian model for multiple-pass, multiple antenna synthetic aperture radar ( SAR

17. The cost of linearization

Morel, Danielle; Levy, William B.

2006-03-01

Information processing in the brain is metabolically expensive and energy usage by the different components of the nervous system is not well understood. In a continuing effort to explore the costs and constraints of information processing at the single neuron level, dendritic processes are being studied. More specifically, the role of various ion channel conductances is explored in terms of integrating dendritic excitatory synaptic input. Biophysical simulations of dendritic behavior show that the complexity of voltage-dependent, non-linear dendritic conductances can produce simplicity in the form of linear synaptic integration. Over increasing levels of synaptic activity, it is shown that two types of voltage-dependent conductances produce linearization over a limited range. This range is determined by the parameters defining the ion channel and the 'passive' properties of the dendrite. A persistent sodium and a transient A-type potassium channel were considered at steady-state transmembrane potentials in the vicinity of and hyperpolarized to the threshold for action potential initiation. The persistent sodium is seen to amplify and linearize the synaptic input over a short range of low synaptic activity. In contrast, the A-type potassium channel has a broader linearization range but tends to operate at higher levels of synaptic bombardment. Given equivalent 'passive' dendritic properties, the persistent sodium is found to be less costly than the A-type potassium in linearizing synaptic input.

18. Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

19. Conversion of Ethanol to Hydrocarbons on Hierarchical HZSM-5 Zeolites

SciTech Connect

Ramasamy, Karthikeyan K.; Zhang, He; Sun, Junming; Wang, Yong

2014-02-22

This study reports synthesis, characterization, and catalytic activity of the nano-size hierarchical HZSM-5 zeolite with high mesoporosity produced via a solvent evaporation procedure. Further, this study compares hierarchical zeolites with conventional HZSM-5 zeolite with similar Si/Al ratios for the ethanol-to-hydrocarbon conversion process. The catalytic performance of the hierarchical and conventional zeolites was evaluated using a fixed-bed reactor at 360 °C, 300 psig, and a weight hourly space velocity of 7.9 h-1. For the low Si/Al ratio zeolite (~40), the catalytic life-time for the hierarchical HZSM-5 was approximately 2 times greater than the conventional HZSM-5 despite its coking amount deposited 1.6 times higher than conventional HZSM-5. For the high Si/Al ratio zeolite (~140), the catalytic life-time for the hierarchical zeolite was approximately 5 times greater than the conventional zeolite and the amount of coking deposited was 2.1 times higher. Correlation was observed between catalyst life time, porosity, and the crystal size of the zeolite. The nano-size hierarchical HZSM-5 zeolites containing mesoporosity demonstrated improved catalyst life-time compared to the conventional catalyst due to faster removal of products, shorter diffusion path length, and the migration of the coke deposits to the external surface from the pore structure.

20. Modular and hierarchical structure of social contact networks

Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2013-10-01

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

1. Hierarchical analysis of filtration. Progress report

SciTech Connect

Quintard, M.; Whitaker, S.

1993-07-01

The original proposal for this work suggested two lines Of analysis that could be used to develop an hierarchical analysis of filtration. The first of these was semi-empirical and required the use of an angle-dependent rate coefficient to model the effect of particle inertia, while the second made use of a particle velocity decomposition that separated the velocity into an inertial part and a diffusive part. We have concluded that the semiempirical approach cannot lead to an efficient treatment of the filtration problem, and in this study we have dirrcted most of our effort toward the development of the velocity decomposition approach. Problems arise with the velocity decomposition method because the panicle tracking equation is hyperbolic in nature, and there are regions in the flow field where it is difficult to calculate the deterministic particle velocity. These problems can be avoided with an asymptotic analysis, and we have used this approach to determine single fiber efficiencies for small Stokes numbers. These efficiencies illustrate a minimum as a function of the particle diameter; however, the range of validity (in terms of the Stokes number) of the asymptotic method is uncertain. If the range of validity of the asymptotic expansion is suitable for the solution of practical problems, the current work on homogeneous filters should be expanded to included a broader range of values of the key parameters and then extended to include the case of heterogeneous filters. If the range of validity of the asymptotic method is not suitable for the solution of practical problems, the particle tracking problem must be resolved or we must move on to the use of Brownian dynamics. This approach is outlined, where we have indicated how Brownian dynamics may be incorporated into the method of volume averaging.

2. Hierarchical Star Formation Across Galactic Disks

Gouliermis, Dimitrios

2016-09-01

Most stars form in clusters. This fact has emerged from the finding that "embedded clusters account for the 70 - 90% fraction of all stars formed in Giant Molecular Clouds (GMCs)." While this is the case at scales of few 10 parsecs, typical for GMCs, a look at star-forming galaxies in the Local Group (LG) shows significant populations of enormous loose complexes of early-type stars extending at scales from few 100 to few 1000 parsecs. The fact that these stellar complexes host extremely large numbers of loosely distributed massive blue stars implies either that stars form also in an unbound fashion or they are immediately dislocated from their original compact birthplaces or both. The Legacy Extra-Galactic UV Survey (LEGUS) has produced remarkable collections of resolved early-type stars in 50 star-forming LG galaxies, suited for testing ideas about recent star formation. I will present results from our ongoing project on star formation across LEGUS disk galaxies. We characterize the global clustering behavior of the massive young stars in order to understand the morphology of star formation over galactic scales. This morphology appears to be self-similar with fractal dimensions comparable to those of the molecular interstellar medium, apparently driven by large-scale turbulence. Our clustering analysis reveals compact stellar systems nested in larger looser concentrations, which themselves are the dense parts of unbound complexes and super-structures, giving evidence of hierarchical star formation up to galactic scales. We investigate the structural and star formation parameters demographics of the star-forming complexes revealed at various levels of compactness. I will discuss the outcome of our correlation and regression analyses on these parameters in an attempt to understand the link between galactic disk dynamics and morphological structure in spiral and ring galaxies of the local universe.

3. Hierarchical Representation Learning for Kinship Verification.

PubMed

Kohli, Naman; Vatsa, Mayank; Singh, Richa; Noore, Afzel; Majumdar, Angshul

2017-01-01

Kinship verification has a number of applications such as organizing large collections of images and recognizing resemblances among humans. In this paper, first, a human study is conducted to understand the capabilities of human mind and to identify the discriminatory areas of a face that facilitate kinship-cues. The visual stimuli presented to the participants determine their ability to recognize kin relationship using the whole face as well as specific facial regions. The effect of participant gender and age and kin-relation pair of the stimulus is analyzed using quantitative measures such as accuracy, discriminability index d' , and perceptual information entropy. Utilizing the information obtained from the human study, a hierarchical kinship verification via representation learning (KVRL) framework is utilized to learn the representation of different face regions in an unsupervised manner. We propose a novel approach for feature representation termed as filtered contractive deep belief networks (fcDBN). The proposed feature representation encodes relational information present in images using filters and contractive regularization penalty. A compact representation of facial images of kin is extracted as an output from the learned model and a multi-layer neural network is utilized to verify the kin accurately. A new WVU kinship database is created, which consists of multiple images per subject to facilitate kinship verification. The results show that the proposed deep learning framework (KVRL-fcDBN) yields the state-of-the-art kinship verification accuracy on the WVU kinship database and on four existing benchmark data sets. Furthermore, kinship information is used as a soft biometric modality to boost the performance of face verification via product of likelihood ratio and support vector machine based approaches. Using the proposed KVRL-fcDBN framework, an improvement of over 20% is observed in the performance of face verification.

4. Hierarchical Representation Learning for Kinship Verification.

PubMed

Kohli, Naman; Vatsa, Mayank; Singh, Richa; Noore, Afzel; Majumdar, Angshul

2016-09-14

Kinship verification has a number of applications such as organizing large collections of images and recognizing resemblances among humans. In this research, first, a human study is conducted to understand the capabilities of human mind and to identify the discriminatory areas of a face that facilitate kinship-cues. The visual stimuli presented to the participants determines their ability to recognize kin relationship using the whole face as well as specific facial regions. The effect of participant gender and age and kin-relation pair of the stimulus is analyzed using quantitative measures such as accuracy, discriminability index d1, and perceptual information entropy. Utilizing the information obtained from the human study, a hierarchical Kinship Verification via Representation Learning (KVRL) framework is utilized to learn the representation of different face regions in an unsupervised manner. We propose a novel approach for feature representation termed as filtered contractive deep belief networks (fcDBN). The proposed feature representation encodes relational information present in images using filters and contractive regularization penalty. A compact representation of facial images of kin is extracted as an output from the learned model and a multi-layer neural network is utilized to verify the kin accurately. A new WVU Kinship Database is created which consists of multiple images per subject to facilitate kinship verification. The results show that the proposed deep learning framework (KVRL-fcDBN) yields stateof- the-art kinship verification accuracy on the WVU Kinship database and on four existing benchmark datasets. Further, kinship information is used as a soft biometric modality to boost the performance of face verification via product of likelihood ratio and support vector machine based approaches. Using the proposed KVRL-fcDBN framework, an improvement of over 20% is observed in the performance of face verification.

5. Correlation Between Hierarchical Bayesian and Aerosol ...

EPA Pesticide Factsheets

Tools to estimate PM2.5 mass have expanded in recent years, and now include: 1) stationary monitor readings, 2) Community Multi-Scale Air Quality (CMAQ) model estimates, 3) Hierarchical Bayesian (HB) estimates from combined stationary monitor readings and CMAQ model output; and, 4) calibrated Aerosol Optical Depth (AOD) readings from two Moderate Resolution Imaging Spetroradiometer (MODIS) units on National Aeronautics and Space Administration’s (NASA) Terra and Aqua satellites. Case-crossover design and conditional logistic regression were used to determine concentration response (CR) functions for three different PM2.5 levels on asthma emergency department (ED) visits and acute myocardial infarction (MI) inpatient hospitalizations in ninety-nine, 12 km2 grids in Baltimore, MD (2005 data). HB analyses for asthma ED visits produced significant results at 3-day lags for the main effect (OR=1.002, 95% CI=1.000-1.005), and two effect modifiers for females (OR=1.003, 95% CI=1.000-1.006), and non-Caucasian/non-African American persons (OR=1.010, 95% CI=1.001-1.019). HB analyses for acute MI inpatient hospitalizations also consistently produced a significant outcome for persons of other race (OR=1.031, 95% CI=1.006-1.056). Correlation coefficients computed between stationary monitor and satellite AOD PM2.5 values were significant for both asthma (rxy=0.944) and acute MI (rxy=0.940). Both monitor and AOD PM2.5 values were higher in February and June through Aug

6. Hierarchical processing in spoken language comprehension.

PubMed

Davis, Matthew H; Johnsrude, Ingrid S

2003-04-15

Understanding spoken language requires a complex series of processing stages to translate speech sounds into meaning. In this study, we use functional magnetic resonance imaging to explore the brain regions that are involved in spoken language comprehension, fractionating this system into sound-based and more abstract higher-level processes. We distorted English sentences in three acoustically different ways, applying each distortion to varying degrees to produce a range of intelligibility (quantified as the number of words that could be reported) and collected whole-brain echo-planar imaging data from 12 listeners using sparse imaging. The blood oxygenation level-dependent signal correlated with intelligibility along the superior and middle temporal gyri in the left hemisphere and in a less-extensive homologous area on the right, the left inferior frontal gyrus (LIFG), and the left hippocampus. Regions surrounding auditory cortex, bilaterally, were sensitive to intelligibility but also showed a differential response to the three forms of distortion, consistent with sound-form-based processes. More distant intelligibility-sensitive regions within the superior and middle temporal gyri, hippocampus, and LIFG were insensitive to the acoustic form of sentences, suggesting more abstract nonacoustic processes. The hierarchical organization suggested by these results is consistent with cognitive models and auditory processing in nonhuman primates. Areas that were particularly active for distorted speech conditions and, thus, might be involved in compensating for distortion, were found exclusively in the left hemisphere and partially overlapped with areas sensitive to intelligibility, perhaps reflecting attentional modulation of auditory and linguistic processes.

7. Reflection of hierarchical medium structures of different scales in the space time data of wave fields distribution.

Hachay, Olga; Khachay, Andrey

2015-04-01

The last decades are characterized by active development of Earth's sciences. The modern research methods and technologies give the opportunity to obtain new data about the Earth's structure and processes, which occur in its interior. The conception development about the nonlinear geodynamics practically coincides with research of nonlinear processes in different parts of physics. In geology soliton and auto wave conceptions are developed, principles of synergetic and self organization become be used, in geodynamics the macro quantum behavior of large mass matter, which are in critical state, in geophysics the auto wave nature of geophysical fields is researched in a frame of a new structural model with hierarchical inclusions. It is very significant to define the time of reaction lagging, in spite of the influence on the massif can be assumed as elastic. The unique model which can explain that effect is a model of the massif with a hierarchic structure. We developed a mathematical algorithm using integral and integral-differential equations for 2-D model for two problems in a frequency domain: diffraction a sound wave and linear polarized transverse wave through a arbitrary hierarchy rank inclusion plunged in an N-layered medium. That algorithm differs from the fractal model approach by a freer selecting of heterogeneities position of each rank. And the second, the problem is solved in the dynamical approach. The higher the amount of the hierarchic ranks the more is the degree of nonlinearity of the massive response and the longer can be the time of massive reaction lag of the influence. For research of hierarchic medium we had developed an iterative algorithm for electromagnetic and seismic fields in the problem setting similar to analyze higher for layered-block models with homogeneous inclusions. We had developed an iterative algorithm of inverse problem solution for the same models, using the approach of three stage interpretation. For that we had developed a

8. Posterior propriety for hierarchical models with log-likelihoods that have norm bounds

SciTech Connect

Michalak, Sarah E.; Morris, Carl N.

2015-07-17

Statisticians often use improper priors to express ignorance or to provide good frequency properties, requiring that posterior propriety be verified. Our paper addresses generalized linear mixed models, GLMMs, when Level I parameters have Normal distributions, with many commonly-used hyperpriors. It provides easy-to-verify sufficient posterior propriety conditions based on dimensions, matrix ranks, and exponentiated norm bounds, ENBs, for the Level I likelihood. Since many familiar likelihoods have ENBs, which is often verifiable via log-concavity and MLE finiteness, our novel use of ENBs permits unification of posterior propriety results and posterior MGF/moment results for many useful Level I distributions, including those commonly used with multilevel generalized linear models, e.g., GLMMs and hierarchical generalized linear models, HGLMs. Furthermore, those who need to verify existence of posterior distributions or of posterior MGFs/moments for a multilevel generalized linear model given a proper or improper multivariate F prior as in Section 1 should find the required results in Sections 1 and 2 and Theorem 3 (GLMMs), Theorem 4 (HGLMs), or Theorem 5 (posterior MGFs/moments).

9. Posterior propriety for hierarchical models with log-likelihoods that have norm bounds

DOE PAGES

Michalak, Sarah E.; Morris, Carl N.

2015-07-17

Statisticians often use improper priors to express ignorance or to provide good frequency properties, requiring that posterior propriety be verified. Our paper addresses generalized linear mixed models, GLMMs, when Level I parameters have Normal distributions, with many commonly-used hyperpriors. It provides easy-to-verify sufficient posterior propriety conditions based on dimensions, matrix ranks, and exponentiated norm bounds, ENBs, for the Level I likelihood. Since many familiar likelihoods have ENBs, which is often verifiable via log-concavity and MLE finiteness, our novel use of ENBs permits unification of posterior propriety results and posterior MGF/moment results for many useful Level I distributions, including those commonlymore » used with multilevel generalized linear models, e.g., GLMMs and hierarchical generalized linear models, HGLMs. Furthermore, those who need to verify existence of posterior distributions or of posterior MGFs/moments for a multilevel generalized linear model given a proper or improper multivariate F prior as in Section 1 should find the required results in Sections 1 and 2 and Theorem 3 (GLMMs), Theorem 4 (HGLMs), or Theorem 5 (posterior MGFs/moments).« less

10. Exercise training reduces PGE2 levels and induces recovery from steatosis in tumor-bearing rats.

PubMed

Lira, F S; Yamashita, A; Carnevali, L C; Gonçalves, D C; Lima, W P; Rosa, J C; Caperuto, E C; Rosa, L F C; Seelaender, M

2010-12-01

The effects of endurance training on PGE (2) levels and upon the maximal activity of hepatic carnitine palmitoyltransferase (CPT) system were studied in rats bearing the Walker 256 carciosarcoma. Animals were randomly assigned to a sedentary control (SC), sedentary tumor-bearing (ST), exercised control (EC), and as an exercised tumor-bearing (ET) group. Trained rats ran on a treadmill (60% VO (2) max) for 60 min/day, 5 days/week, for 8 weeks. We examined the mRNA expression (RT-PCR) and maximal activity (radioassay) of the carnitine palmitoyltransferase system enzymes (CPT I and CPT II), as well as the gene expression of fatty-acid-binding protein (L-FABP) in the liver. PGE (2) content was measured in the serum, in tumor cells, and in the liver (ELISA). CPT I and CPT II maximal activity were decreased (p<0.01) in ST when compared with SC. In contrast, serum PGE (2) was increased (p<0.05) in cachectic animals as compared with SC. In the liver, PGE (2) content was also increased (p<0.05) when compared with SC. Endurance training restored maximal CPT I and CPT II activity in the tumor-bearing animals (p<0.0001). Exercise training induced PGE (2) levels to return to control values in the liver of tumor-bearing training rats (p<0.05) and decreased the eicosanoid content in the tumor (p<0.01). In conclusion, endurance training was capable of reestablishing liver carnitine palmitoyltransferase (CPT) system activity associated with decreased PGE (2) levels in cachectic tumor-bearing animals, preventing steatosis.

11. Clinical Presentation of Cervical Myelopathy at C1–2 Level

PubMed Central

Takebayashi, Tsuneo; Terashima, Yoshinori; Tsuda, Hajime; Yoshimoto, Mitsunori; Yamashita, Toshihiko

2016-01-01

Study Design Single-center retrospective study. Purpose To clarify the clinical features of cervical myelopathy at the C1–2 level. Overview of Literature Methods for distinguishing the affected level based on myelomere symptoms or dysfunction of the conducting pathway were established. However, no symptoms have been identified as being specific to the C1–2 level segment. Methods We evaluated 24 patients with cervical myelopathy due to spinal cord compression at the C1–2 level. Preoperative neurological assessment were investigated and compared with the rate and site of compression of the spinal cord using computed tomography-myelography. Results Impaired temperature and pain sensation were confirmed in 18 of the 24 patients with that localized to the upper arms (n=3), forearm (n=9), both (n=2), and whole body (n=4). Muscle weakness was observed in 18 patients, muscle weakness extended from the biceps brachii to the abductor digiti minimi in 10 patients, and in the whole body in 8 patients. Deep tendon reflexes were normal in 10 patients, whereas hyperactive deep tendon reflexes were noted in 14 patients. The rate of spinal cord compression was significantly higher in patients with perceptual dysfunction and muscle weakness compared with those with no dysfunction. However, no significant difference in the rate and site of compression was identified in those with dysfunction. Conclusions Perceptual dysfunction and muscle weakness localized to the upper limbs was observed in 58% and 42% of patients, respectively. Neurological abnormalities, such as perceptual dysfunction and muscle weakness, were visualized in patients with marked compression. PMID:27559458

12. The Voltage Activation of Cortical KCNQ Channels Depends on Global PIP2 Levels

PubMed Central

Kim, Kwang S.; Duignan, Kevin M.; Hawryluk, Joanna M.; Soh, Heun; Tzingounis, Anastasios V.

2016-01-01

The slow afterhyperpolarization (sAHP) is a calcium-activated potassium conductance with critical roles in multiple physiological processes. Pharmacological and genetic data suggest that KCNQ channels partly mediate the sAHP. However, these channels are not typically open within the observed voltage range of the sAHP. Recent work has shown that the sAHP is gated by increased PIP2 levels, which are generated downstream of calcium binding by neuronal calcium sensors such as hippocalcin. Here, we examined whether changes in PIP2 levels could shift the voltage-activation range of KCNQ channels. In HEK293T cells, expression of the PIP5 kinase PIPKIγ90, which increases global PIP2 levels, shifted the KCNQ voltage activation to within the operating range of the sAHP. Further, the sensitivity of this effect on KCNQ3 channels appeared to be higher than that on KCNQ2. Therefore, we predict that KCNQ3 plays an essential role in maintaining the sAHP under low PIP2 conditions. In support of this notion, we find that sAHP inhibition by muscarinic receptors that increase phosphoinositide turnover in neurons is enhanced in Kcnq3-knockout mice. Likewise, the presence of KCNQ3 is essential for maintaining the sAHP when hippocalcin is ablated, a condition that likely impairs PIP2 generation. Together, our results establish the relationship between PIP2 and the voltage dependence of cortical KCNQ channels (KCNQ2/3, KCNQ3/5, and KCNQ5), and suggest a possible mechanism for the involvement of KCNQ channels in the sAHP. PMID:26958886

13. Detection of endobronchial intubation by monitoring the CO2 level above the endotracheal cuff.

PubMed

Efrati, Shai; Deutsch, Israel; Weksler, Nathan; Gurman, Gabriel M

2015-02-01

Early detection of accidental endobronchial intubation (EBI) is still an unsolved problem in anesthesia and critical care daily practice. The aim of this study was to evaluate the ability of monitoring above cuff CO2 to detect EBI (the working hypothesis was that the origin of CO2 is from the unventilated, but still perfused, lung). Six goats were intubated under general anesthesia and the ETT positioning was verified by a flexible bronchoscope. The AnapnoGuard system, already successfully used to detect air leak around the ETT cuff, was used for continuous monitoring of above-the-cuff CO2 level. When the ETT distal tip was located in the trachea, with an average cuff pressure of 15 mmHg, absence of CO2 above the cuff was observed. The ETT was then deliberately advanced into one of the main bronchi under flexible bronchoscopic vision. In all six cases the immediate presence of CO2 above the cuff was identified. Further automatic inflation of the cuff, up to a level of 27 mmHg, did not affect the above-the-cuff measured CO2 level. Withdrawal of the ETT and repositioning of its distal tip in mid-trachea caused the disappearance of CO2 above the cuff in a maximum of 3 min, confirming the absence of air leak and the correct positioning of the ETT. Our results suggest that measurement of the above-the-cuff CO2 level could offer a reliable, on-line solution for early identification of accidental EBI. Further studies are planned to validate the efficacy of the method in a clinical setup.

14. Sentinel-2 Level 2A Prototype Processor: Architecture, Algorithms And First Results

Muller-Wilm, Uwe; Louis, Jerome; Richter, Rudolf; Gascon, Ferran; Niezette, Marc

2013-12-01

Sen2Core is a prototype processor for Sentinel-2 Level 2A product processing and formatting. The processor is developed for and with ESA and performs the tasks of Atmospheric Correction and Scene Classification of Level 1C input data. Level 2A outputs are: Bottom-Of- Atmosphere (BOA) corrected reflectance images, Aerosol Optical Thickness-, Water Vapour-, Scene Classification maps and Quality indicators, including cloud and snow probabilities. The Level 2A Product Formatting performed by the processor follows the specification of the Level 1C User Product.

15. Evidence that elevated CO2 levels can indirectly increase rhizosphere denitrifier activity

NASA Technical Reports Server (NTRS)

Smart, D. R.; Ritchie, K.; Stark, J. M.; Bugbee, B.

1997-01-01

We examined the influence of elevated CO2 concentration on denitrifier enzyme activity in wheat rhizoplanes by using controlled environments and solution culture techniques. Potential denitrification activity was from 3 to 24 times higher on roots that were grown under an elevated CO2 concentration of 1,000 micromoles of CO2 mol-1 than on roots grown under ambient levels of CO2. Nitrogen loss, as determined by a nitrogen mass balance, increased with elevated CO2 levels in the shoot environment and with a high NO3- concentration in the rooting zone. These results indicated that aerial CO2 concentration can play a role in rhizosphere denitrifier activity.

16. Monitoring yeast intracellular Ca2+ levels using an in vivo bioluminescence assay.

PubMed

Tisi, Renata; Martegani, Enzo; Brandão, Rogelio L

2015-02-02

This protocol describes the use of the jellyfish Aequorea victoria aequorin protein to measure Ca(2+) levels in living yeast cells. All yeast strains to be analyzed must express the A. victoria apoprotein of the aequorin calcium biosensor, to be reconstituted into fully active aequorin by association with its cofactor, coelenterazine, which cannot be synthesized by yeast itself. The simplest way to achieve reconstitution is to transform yeast cells with a vector driving apoaequorin expression, and then supply commercially available coelenterazine cofactor in the medium. Coelenterazine is a hydrophobic molecule and is able to permeate yeast cells.

17. Synthesis strategies in the search for hierarchical zeolites.

PubMed

Serrano, D P; Escola, J M; Pizarro, P

2013-05-07

Great interest has arisen in the past years in the development of hierarchical zeolites, having at least two levels of porosities. Hierarchical zeolites show an enhanced accessibility, leading to improved catalytic activity in reactions suffering from steric and/or diffusional limitations. Moreover, the secondary porosity offers an ideal space for the deposition of additional active phases and for functionalization with organic moieties. However, the secondary surface represents a discontinuity of the crystalline framework, with a low connectivity and a high concentration of silanols. Consequently, hierarchical zeolites exhibit a less "zeolitic behaviour" than conventional ones in terms of acidity, hydrophobic/hydrophilic character, confinement effects, shape-selectivity and hydrothermal stability. Nevertheless, this secondary surface is far from being amorphous, which provides hierarchical zeolites with a set of novel features. A wide variety of innovative strategies have been developed for generating a secondary porosity in zeolites. In the present review, the different synthetic routes leading to hierarchical zeolites have been classified into five categories: removal of framework atoms, surfactant-assisted procedures, hard-templating, zeolitization of preformed solids and organosilane-based methods. Significant advances have been achieved recently in several of these alternatives. These include desilication, due to its versatility, dual templating with polyquaternary ammonium surfactants and framework reorganization by treatment with surfactant-containing basic solutions. In the last two cases, the materials so prepared show both mesoscopic ordering and zeolitic lattice planes. Likewise, interesting results have been obtained with the incorporation of different types of organosilanes into the zeolite crystallization gels, taking advantage of their high affinity for silicate and aluminosilicate species. Crystallization of organofunctionalized species favours the

18. Superconducting linear actuator

NASA Technical Reports Server (NTRS)

Johnson, Bruce; Hockney, Richard

1993-01-01

Special actuators are needed to control the orientation of large structures in space-based precision pointing systems. Electromagnetic actuators that presently exist are too large in size and their bandwidth is too low. Hydraulic fluid actuation also presents problems for many space-based applications. Hydraulic oil can escape in space and contaminate the environment around the spacecraft. A research study was performed that selected an electrically-powered linear actuator that can be used to control the orientation of a large pointed structure. This research surveyed available products, analyzed the capabilities of conventional linear actuators, and designed a first-cut candidate superconducting linear actuator. The study first examined theoretical capabilities of electrical actuators and determined their problems with respect to the application and then determined if any presently available actuators or any modifications to available actuator designs would meet the required performance. The best actuator was then selected based on available design, modified design, or new design for this application. The last task was to proceed with a conceptual design. No commercially-available linear actuator or modification capable of meeting the specifications was found. A conventional moving-coil dc linear actuator would meet the specification, but the back-iron for this actuator would weigh approximately 12,000 lbs. A superconducting field coil, however, eliminates the need for back iron, resulting in an actuator weight of approximately 1000 lbs.

19. Community turnover of wood-inhabiting fungi across hierarchical spatial scales.

PubMed

Abrego, Nerea; García-Baquero, Gonzalo; Halme, Panu; Ovaskainen, Otso; Salcedo, Isabel

2014-01-01

For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual

20. Neural mechanisms underlying the computation of hierarchical tree structures in mathematics.

PubMed

Nakai, Tomoya; Sakai, Kuniyoshi L

2014-01-01

Whether mathematical and linguistic processes share the same neural mechanisms has been a matter of controversy. By examining various sentence structures, we recently demonstrated that activations in the left inferior frontal gyrus (L. IFG) and left supramarginal gyrus (L. SMG) were modulated by the Degree of Merger (DoM), a measure for the complexity of tree structures. In the present study, we hypothesize that the DoM is also critical in mathematical calculations, and clarify whether the DoM in the hierarchical tree structures modulates activations in these regions. We tested an arithmetic task that involved linear and quadratic sequences with recursive computation. Using functional magnetic resonance imaging, we found significant activation in the L. IFG, L. SMG, bilateral intraparietal sulcus (IPS), and precuneus selectively among the tested conditions. We also confirmed that activations in the L. IFG and L. SMG were free from memory-related factors, and that activations in the bilateral IPS and precuneus were independent from other possible factors. Moreover, by fitting parametric models of eight factors, we found that the model of DoM in the hierarchical tree structures was the best to explain the modulation of activations in these five regions. Using dynamic causal modeling, we showed that the model with a modulatory effect for the connection from the L. IPS to the L. IFG, and with driving inputs into the L. IFG, was highly probable. The intrinsic, i.e., task-independent, connection from the L. IFG to the L. IPS, as well as that from the L. IPS to the R. IPS, would provide a feedforward signal, together with negative feedback connections. We indicate that mathematics and language share the network of the L. IFG and L. IPS/SMG for the computation of hierarchical tree structures, and that mathematics recruits the additional network of the L. IPS and R. IPS.

1. Linear and Non-Linear Visual Feature Learning in Rat and Humans

PubMed Central

Bossens, Christophe; Op de Beeck, Hans P.

2016-01-01

The visual system processes visual input in a hierarchical manner in order to extract relevant features that can be used in tasks such as invariant object recognition. Although typically investigated in primates, recent work has shown that rats can be trained in a variety of visual object and shape recognition tasks. These studies did not pinpoint the complexity of the features used by these animals. Many tasks might be solved by using a combination of relatively simple features which tend to be correlated. Alternatively, rats might extract complex features or feature combinations which are nonlinear with respect to those simple features. In the present study, we address this question by starting from a small stimulus set for which one stimulus-response mapping involves a simple linear feature to solve the task while another mapping needs a well-defined nonlinear combination of simpler features related to shape symmetry. We verified computationally that the nonlinear task cannot be trivially solved by a simple V1-model. We show how rats are able to solve the linear feature task but are unable to acquire the nonlinear feature. In contrast, humans are able to use the nonlinear feature and are even faster in uncovering this solution as compared to the linear feature. The implications for the computational capabilities of the rat visual system are discussed. PMID:28066201

2. Linear encoding device

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

1993-01-01

A Linear Motion Encoding device for measuring the linear motion of a moving object is disclosed in which a light source is mounted on the moving object and a position sensitive detector such as an array photodetector is mounted on a nearby stationary object. The light source emits a light beam directed towards the array photodetector such that a light spot is created on the array. An analog-to-digital converter, connected to the array photodetector is used for reading the position of the spot on the array photodetector. A microprocessor and memory is connected to the analog-to-digital converter to hold and manipulate data provided by the analog-to-digital converter on the position of the spot and to compute the linear displacement of the moving object based upon the data from the analog-to-digital converter.

3. Photochemical consequences of enhanced CO2 levels in earth's early atmosphere

NASA Technical Reports Server (NTRS)

Kasting, J. F.

1985-01-01

Greatly enhanced atmospheric CO2 concentrations are the most likely mechanism for offsetting the effects of reduced solar luminosity early in the earth's history. CO2 levels of 80 to 600 times the present value could have maintained a mean surface temperature of 0 C to 15 C, given a 25 percent decrease in solar output. Such high CO2 levels are at least qualitatively consistent with the present understanding of the carbonate-silicate geochemical cycle. The presence of large amounts of CO2 has important implications for the composition of the earth's prebiotic atmosphere. The hydrogen budget of a high-CO2 primitive atmosphere would have been strongly influenced by rainout of H2O2 and H2CO. The reaction of H2O2 with dissolved ferrous iron in the early oceans could have been a major sink for atmospheric oxygen. The requirement that this loss of oxygen be balanced by a corresponding loss of hydrogen (by escape to space and rainout of H2CO) implies that the atmospheric H2 mixing ratio was greater than 2 x 10 to the -5th and the ground level O2 mixing ratio was below 10 to the -12th, even if other surface sources of H2 were small. These results are only weakly dependent on changes in solar UV flux, rainout rates, and vertical mixing rates in the primitive atmosphere.

4. Hierarchically porous materials: synthesis strategies and structure design.

PubMed

Yang, Xiao-Yu; Chen, Li-Hua; Li, Yu; Rooke, Joanna Claire; Sanchez, Clément; Su, Bao-Lian

2017-01-23

Owing to their immense potential in energy conversion and storage, catalysis, photocatalysis, adsorption, separation and life science applications, significant interest has been devoted to the design and synthesis of hierarchically porous materials. The hierarchy of materials on porosity, structural, morphological, and component levels is key for high performance in all kinds of applications. Synthesis and applications of hierarchically structured porous materials have become a rapidly evolving field of current interest. A large series of synthesis methods have been developed. This review addresses recent advances made in studies of this topic. After identifying the advantages and problems of natural hierarchically porous materials, synthetic hierarchically porous materials are presented. The synthesis strategies used to prepare hierarchically porous materials are first introduced and the features of synthesis and the resulting structures are presented using a series of examples. These involve templating methods (surfactant templating, nanocasting, macroporous polymer templating, colloidal crystal templating and bioinspired process, i.e. biotemplating), conventional techniques (supercritical fluids, emulsion, freeze-drying, breath figures, selective leaching, phase separation, zeolitization process, and replication) and basic methods (sol-gel controlling and post-treatment), as well as self-formation phenomenon of porous hierarchy. A series of detailed examples are given to show methods for the synthesis of hierarchically porous structures with various chemical compositions (dual porosities: micro-micropores, micro-mesopores, micro-macropores, meso-mesopores, meso-macropores, multiple porosities: micro-meso-macropores and meso-meso-macropores). We hope that this review will be helpful for those entering the field and also for those in the field who want quick access to helpful reference information about the synthesis of new hierarchically porous materials and

5. Decentralization, stabilization, and estimation of large-scale linear systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Vukcevic, M. B.

1976-01-01

In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

6. Preparation of aluminum-containing mesoporous silica with hierarchical macroporous architecture and its enhanced catalytic activities.

PubMed

Kamegawa, Takashi; Tanaka, Shota; Seto, Hiroki; Zhou, Dayang; Yamashita, Hiromi

2013-08-28

Aluminum-containing mesoporous silica with hierarchical macroporous architecture (Al-MMS) was successfully prepared using a solvent evaporation method through the combination of precursor solution for synthesis of Al-containing mesoporous silica (Al-MS) and poly(methyl methacrylate) (PMMA) colloidal crystals as a hard template. The porous structure and the state of aluminum were investigated using various characterization techniques. The construction of combined structure of Al-MMS, i.e., hierarchical macroporous architecture consisting of thin mesoporous silica frameworks, led to the formation of many mesopore entrances and the shortening of the mesoporous channels. In the tetrahydropyranylation of linear alcohols with dihydropyran (DHP), Al-MMS exhibited higher catalytic activities for the formation of corresponding tetrahydropyranyl ethers as compared to Al-MS. The advantageous structure of Al-MMS enables the efficient transport of reactants to the catalytically active sites, which realizes the significant enhancement of catalytic performances in the reaction of DHP with alcohols having longer alkyl chains.

7. Simultaneous analysis of plasma and CSF by NMR and hierarchical models fusion.

PubMed

Smolinska, Agnieszka; Posma, Joram M; Blanchet, Lionel; Ampt, Kirsten A M; Attali, Amos; Tuinstra, Tinka; Luider, Theo; Doskocz, Marek; Michiels, Paul J; Girard, Frederic C; Buydens, Lutgarde M C; Wijmenga, Sybren S

2012-05-01

Because cerebrospinal fluid (CSF) is the biofluid which interacts most closely with the central nervous system, it holds promise as a reporter of neurological disease, for example multiple sclerosis (MScl). To characterize the metabolomics profile of neuroinflammatory aspects of this disease we studied an animal model of MScl-experimental autoimmune/allergic encephalomyelitis (EAE). Because CSF also exchanges metabolites with blood via the blood-brain barrier, malfunctions occurring in the CNS may be reflected in the biochemical composition of blood plasma. The combination of blood plasma and CSF provides more complete information about the disease. Both biofluids can be studied by use of NMR spectroscopy. It is then necessary to perform combined analysis of the two different datasets. Mid-level data fusion was therefore applied to blood plasma and CSF datasets. First, relevant information was extracted from each biofluid dataset by use of linear support vector machine recursive feature elimination. The selected variables from each dataset were concatenated for joint analysis by partial least squares discriminant analysis (PLS-DA). The combined metabolomics information from plasma and CSF enables more efficient and reliable discrimination of the onset of EAE. Second, we introduced hierarchical models fusion, in which previously developed PLS-DA models are hierarchically combined. We show that this approach enables neuroinflamed rats (even on the day of onset) to be distinguished from either healthy or peripherally inflamed rats. Moreover, progression of EAE can be investigated because the model separates the onset and peak of the disease.

8. Controllable synthesis of branched hierarchical ZnO nanorod arrays for highly sensitive hydrazine detection

Hu, Jie; Zhao, Zhenting; Sun, Yongjiao; Wang, Ying; Li, Pengwei; Zhang, Wendong; Lian, Kun

2016-02-01

In this paper, three different kinds of ZnO nanostructures were successfully synthesized on Au/Glass (Au/G) substrate by electrochemical deposition method. The morphology and crystalline structures of the obtained samples were characterized using SEM, XRD and HRTEM. Electrochemical responses of the as-prepared ZnO based sensors to hydrazine in 0.1 M phosphate buffer solution (PBS, pH 7.4) were analyzed by cyclic voltammetry and single-potential amperometry. The results confirmed that the electrochemical performances of ZnO sensors are strongly dependent on the specific surface area. Especially, the branched hierarchical ZnO nanorod arrays shows the highest sensitivity of 5.35 μA μM-1 cm-2, a short response time of 3 s, a low detection limit of 0.08 μM with a linear hydrazine concentration response range from 0.8 μM to 101 μM, and it also exhibits excellent anti-interference, stability and reproducibility abilities, which provide great potential method of ZnO branched hierarchical structures in the development of high-performance electrochemical sensor.

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

USGS Publications Warehouse

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.

10. Microfibres and macroscopic films from the coordination-driven hierarchical self-assembly of cylindrical micelles

PubMed Central

Lunn, David J.; Gould, Oliver E. C.; Whittell, George R.; Armstrong, Daniel P.; Mineart, Kenneth P.; Winnik, Mitchell A.; Spontak, Richard J.; Pringle, Paul G.; Manners, Ian

2016-01-01

Anisotropic nanoparticles prepared from block copolymers are of growing importance as building blocks for the creation of synthetic hierarchical materials. However, the assembly of these structural units is generally limited to the use of amphiphilic interactions. Here we report a simple, reversible coordination-driven hierarchical self-assembly strategy for the preparation of micron-scale fibres and macroscopic films based on monodisperse cylindrical block copolymer micelles. Coordination of Pd(0) metal centres to phosphine ligands immobilized within the soluble coronas of block copolymer micelles is found to induce intermicelle crosslinking, affording stable linear fibres comprised of micelle subunits in a staggered arrangement. The mean length of the fibres can be varied by altering the micelle concentration, reaction stoichiometry or aspect ratio of the micelle building blocks. Furthermore, the fibres aggregate on drying to form robust, self-supporting macroscopic micelle-based thin films with useful mechanical properties that are analogous to crosslinked polymer networks, but on a longer length scale. PMID:27538877

11. Determination of trace amounts of mercury using hierarchically nanostructured europium oxide.

PubMed

Peng, Yanfen; Chen, Xiaojun; Gao, Zhiqiang

2010-10-15

This work reports a highly sensitive procedure for the determination of trace amounts of mercury, based on fluorescence quenching of thenoyltrifluoroacetone (TTA) capped hierarchically nanostructured europium oxide (cHN-Eu(2)O(3)). The HN-Eu(2)O(3) consisted of nanometer-thick Eu(2)O(3) sheets self-organized into nano- and micro-sized monoliths with a hierarchical architecture while retaining its desirable fluorescence properties. The fluorescence intensity of the cHN-Eu(2)O(3) was 1000 times higher than that of commercial Eu(2)O(3) nanoparticles (equivalent weight) when it was capped with TTA, suggesting that a synergetic effect, confining the longtime Eu(3+) excitation within the nanostructure and light-harvesting effect of the capping agent, is responsible for this fluorescence enhancement. Excellent interaction between the cHN-Eu(2)O(3) and solution species is expected owing to its large surface area, high surface-to-bulk ratio, and ultrahigh fluorescence intensity. As an example, aqueous suspensions of the cHN-Eu(2)O(3) were used as sensing agent for the determination of trace amounts of mercury. A linear relationship between the concentration of mercury and fluorescence quenching was observed from 10 ppb to 10 ppm with a correlation coefficient of 0.997 and a detection limit of 5.0 ppb. Mercury in various samples was analyzed using the cHN-Eu(2)O(3) suspension.

12. Cross-frequency power coupling between hierarchically organized face-selective areas.

PubMed

Furl, Nicholas; Coppola, Richard; Averbeck, Bruno B; Weinberger, Daniel R

2014-09-01

Neural oscillations are linked to perception and behavior and may reflect mechanisms for long-range communication between brain areas. We developed a causal model of oscillatory dynamics in the face perception network using magnetoencephalographic data from 51 normal volunteers. This model predicted induced responses to faces by estimating oscillatory power coupling between source locations corresponding to bilateral occipital and fusiform face areas (OFA and FFA) and the right superior temporal sulcus (STS). These sources showed increased alpha and theta and decreased beta power as well as selective responses to fearful facial expressions. We then used Bayesian model comparison to compare hypothetical models, which were motivated by previous connectivity data and a well-known theory of temporal lobe function. We confirmed this theory in detail by showing that the OFA bifurcated into 2 independent, hierarchical, feedforward pathways, with fearful expressions modulating power coupling only in the more dorsal (STS) pathway. The power coupling parameters showed a common pattern over connections. Low-frequency bands showed same-frequency power coupling, which, in the dorsal pathway, was modulated by fearful faces. Also, theta power showed a cross-frequency suppression of beta power. This combination of linear and nonlinear mechanisms could reflect computational mechanisms in hierarchical feedforward networks.

13. Linear motion valve

NASA Technical Reports Server (NTRS)

Chandler, J. A. (Inventor)

1985-01-01

The linear motion valve is described. The valve spool employs magnetically permeable rings, spaced apart axially, which engage a sealing assembly having magnetically permeable pole pieces in magnetic relationship with a magnet. The gap between the ring and the pole pieces is sealed with a ferrofluid. Depletion of the ferrofluid is minimized.

14. On Solving Linear Recurrences

ERIC Educational Resources Information Center

Dobbs, David E.

2013-01-01

A direct method is given for solving first-order linear recurrences with constant coefficients. The limiting value of that solution is studied as "n to infinity." This classroom note could serve as enrichment material for the typical introductory course on discrete mathematics that follows a calculus course.

15. Improved Electrohydraulic Linear Actuators

NASA Technical Reports Server (NTRS)

Hamtil, James

2004-01-01

A product line of improved electrohydraulic linear actuators has been developed. These actuators are designed especially for use in actuating valves in rocket-engine test facilities. They are also adaptable to many industrial uses, such as steam turbines, process control valves, dampers, motion control, etc. The advantageous features of the improved electrohydraulic linear actuators are best described with respect to shortcomings of prior electrohydraulic linear actuators that the improved ones are intended to supplant. The flow of hydraulic fluid to the two ports of the actuator cylinder is controlled by a servo valve that is controlled by a signal from a servo amplifier that, in turn, receives an analog position-command signal (a current having a value between 4 and 20 mA) from a supervisory control system of the facility. As the position command changes, the servo valve shifts, causing a greater flow of hydraulic fluid to one side of the cylinder and thereby causing the actuator piston to move to extend or retract a piston rod from the actuator body. A linear variable differential transformer (LVDT) directly linked to the piston provides a position-feedback signal, which is compared with the position-command signal in the servo amplifier. When the position-feedback and position-command signals match, the servo valve moves to its null position, in which it holds the actuator piston at a steady position.

16. Road network safety evaluation using Bayesian hierarchical joint model.

PubMed

Wang, Jie; Huang, Helai

2016-05-01

17. Planetary stability zones in hierarchical triple star systems

Verrier, P. E.; Evans, N. W.

2007-12-01

A symplectic integrator algorithm suitable for hierarchical triple systems is formulated and tested. The positions of the stars are followed in hierarchical Jacobi coordinates, whilst the planets are referenced purely to their primary. The algorithm is fast, accurate and easily generalized to incorporate collisions. There are five distinct cases - circumtriple orbits, circumbinary orbits and circumstellar orbits around each of the stars in the hierarchical triple - which require a different formulation of the symplectic integration algorithm. As an application, a survey of the stability zones for planets in hierarchical triples is presented, with the case of a single planet orbiting the inner binary considered in detail. Fits to the inner and the outer edges of the stability zone are computed. Considering the hierarchical triple as two decoupled binary systems, the earlier work of Holman and Wiegert on binaries is shown to be applicable to triples, except in the cases of high eccentricities and close or massive stars. Application to triple stars with good data in the multiple star catalogue suggests that more than 50 per cent are unable to support circumbinary planets, as the stable zone is non-existent or very narrow.

18. Aggregating Hierarchical Service Level Agreements in Business Value Networks

Ul Haq, Irfan; Huqqani, Altaf; Schikuta, Erich

Business scenarios such as Business Value Networks and Extended Enterprises pose new challenges for service choreographies across heterogeneous Virtual Organizations. In such scenarios, services compose together hierarchically in a producer-consumer manner to form service supply-chains of added value. Service Level Agreements (SLAs) are defined at various levels in this hierarchy to ensure the expected quality of service for different stakeholders. Automation of service composition directly implies the aggregation of their corresponding SLAs. But so far, the aggregation of SLAs has been treated only as a single layer process which is insufficient to complement the hierarchical aggregation of services. In this paper we elaborate on the requirement of a hierarchical aggregation of SLAs corresponding to service choreographies in Business Value Networks. During the hierarchical aggregation of SLAs, certain SLA information pertaining to different stakeholders is meant to be restricted and can be only partially revealed to a subset of their business partners. We introduce the concept of SLA-Views to protect such privacy concerns. We, then formalize the notion of SLA Choreography and define an aggregation model based on SLA-Views to enable the automation of hierarchical aggregation of Service Level Agreements. The aggregation model has been designed to comply with the WS-Agreement standard.

19. Free-Energy Bounds for Hierarchical Spin Models

Castellana, Michele; Barra, Adriano; Guerra, Francesco

2014-04-01

In this paper we study two non-mean-field (NMF) spin models built on a hierarchical lattice: the hierarchical Edward-Anderson model (HEA) of a spin glass, and Dyson's hierarchical model (DHM) of a ferromagnet. For the HEA, we prove the existence of the thermodynamic limit of the free energy and the replica-symmetry-breaking (RSB) free-energy bounds previously derived for the Sherrington-Kirkpatrick model of a spin glass. These RSB mean-field bounds are exact only if the order-parameter fluctuations (OPF) vanish: given that such fluctuations are not negligible in NMF models, we develop a novel strategy to tackle part of OPF in hierarchical models. The method is based on absorbing part of OPF of a block of spins into an effective Hamiltonian of the underlying spin blocks. We illustrate this method for DHM and show that, compared to the mean-field bound for the free energy, it provides a tighter NMF bound, with a critical temperature closer to the exact one. To extend this method to the HEA model, a suitable generalization of Griffith's correlation inequalities for Ising ferromagnets is needed: since correlation inequalities for spin glasses are still an open topic, we leave the extension of this method to hierarchical spin glasses as a future perspective.

20. Hierarchical bilateral filtering based disparity estimation for view synthesis

Shin, Hong-Chang; Lee, Gwangsoon; Cheong, Won-Sik; Hur, Namho

2016-06-01

In this paper, we introduce a high efficient and practical disparity estimation using hierarchical bilateral filtering for real-time view synthesis. The proposed method is based on hierarchical stereo matching with hardware-efficient bilateral filtering. Hardware-efficient bilateral filtering is different from the exact bilateral filter. The purpose of the method is to design an edge-preserving filter that can be efficiently parallelized on hardware. The proposed hierarchical bilateral filtering based disparity estimation is essentially a coarse-to-fine use of stereo matching with bilateral filtering. It works as follows: firstly, the hierarchical image pyramid are constructed; the multi-scale algorithm then starts by applying a local stereo matching to the downsampled images at the coarsest level of the hierarchy. After the local stereo matching, the estimated disparity map is refined with the bilateral filtering. And then the refined disparity map will be adaptively upsampled to the next finer level. The upsampled disparity map used as a prior of the corresponding local stereo matching at the next level, and filtered and so on. The method we propose is essentially a combination of hierarchical stereo matching and hardware-efficient bilateral filtering. As a result, visual comparison using real-world stereoscopic video clips shows that the method gives better results than one of state-of-art methods in terms of robustness and computation time.

1. 3D Printing of Hierarchical Silk Fibroin Structures.

PubMed

Sommer, Marianne R; Schaffner, Manuel; Carnelli, Davide; Studart, André R

2016-12-21

Like many other natural materials, silk is hierarchically structured from the amino acid level up to the cocoon or spider web macroscopic structures. Despite being used industrially in a number of applications, hierarchically structured silk fibroin objects with a similar degree of architectural control as in natural structures have not been produced yet due to limitations in fabrication processes. In a combined top-down and bottom-up approach, we exploit the freedom in macroscopic design offered by 3D printing and the template-guided assembly of ink building blocks at the meso- and nanolevel to fabricate hierarchical silk porous materials with unprecedented structural control. Pores with tunable sizes in the range 40-350 μm are generated by adding sacrificial organic microparticles as templates to a silk fibroin-based ink. Commercially available wax particles or monodisperse polycaprolactone made by microfluidics can be used as microparticle templates. Since closed pores are generated after template removal, an ultrasonication treatment can optionally be used to achieve open porosity. Such pore templating particles can be further modified with nanoparticles to create a hierarchical template that results in porous structures with a defined nanotopography on the pore walls. The hierarchically porous silk structures obtained with this processing technique can potentially be utilized in various application fields from structural materials to thermal insulation to tissue engineering scaffolds.

2. Auction-based resource allocation game under a hierarchical structure

Cui, Yingying; Zou, Suli; Ma, Zhongjing

2016-01-01

This paper studies a class of auction-based resource allocation games under a hierarchical structure, such that each supplier is assigned a certain amount of resource from a single provider and allocates it to its buyers with auction mechanisms. To implement the efficient allocations for the underlying hierarchical system, we first design an auction mechanism, for each local system composed of a supplier and its buyers, which inherits the advantages of the progressive second price mechanism. By employing a dynamic algorithm, each local system converges to its own efficient Nash equilibrium, at which the efficient resource allocation is achieved and the bidding prices of all the buyers in this local system are identical with each other. After the local systems reach their own equilibria respectively, the resources assigned to suppliers are readjusted via a dynamic hierarchical algorithm with respect to the bidding prices associated with the implemented equilibria of local systems. By applying the proposed hierarchical process, the formulated hierarchical system can converge to the efficient allocation under certain mild conditions. The developed results in this work are demonstrated with simulations.

3. Phase-space structures - II. Hierarchical Structure Finder

Maciejewski, M.; Colombi, S.; Springel, V.; Alard, C.; Bouchet, F. R.

2009-07-01

A new multidimensional Hierarchical Structure Finder (HSF) to study the phase-space structure of dark matter in N-body cosmological simulations is presented. The algorithm depends mainly on two parameters, which control the level of connectivity of the detected structures and their significance compared to Poisson noise. By working in six-dimensional phase space, where contrasts are much more pronounced than in three-dimensional (3D) position space, our HSF algorithm is capable of detecting subhaloes including their tidal tails, and can recognize other phase-space structures such as pure streams and candidate caustics. If an additional unbinding criterion is added, the algorithm can be used as a self-consistent halo and subhalo finder. As a test, we apply it to a large halo of the Millennium Simulation, where 19 per cent of the halo mass is found to belong to bound substructures, which is more than what is detected with conventional 3D substructure finders, and an additional 23-36 per cent of the total mass belongs to unbound HSF structures. The distribution of identified phase-space density peaks is clearly bimodal: high peaks are dominated by the bound structures and show a small spread in their height distribution; low peaks belong mostly to tidal streams, as expected. However, the projected (3D) density distribution of the structures shows that some of the streams can have comparable density to the bound structures in position space. In order to better understand what HSF provides, we examine the time evolution of structures, based on the merger tree history. Given the resolution limit of the Millennium Simulation, bound structures typically make only up to six orbits inside the main halo. The number of orbits scales approximately linearly with the redshift corresponding to the moment of merging of the structures with the halo. At fixed redshift, the larger the initial mass of the structure which enters the main halo, the faster it loses mass. The difference in

4. Terahertz photoluminescence from S.I.-GaAs by below gap excitation via EL2 level

SciTech Connect

Oyama, Yutaka Dezaki, Hikari; Shimizu, Yusaku; Maeda, Kensaku

2015-01-12

Terahertz emission by radiative transitions in semi-conductors via shallow impurity states is investigated. We report on the observation of terahertz photoluminescence from S.I.-GaAs by below gap excitation via EL2 level which is located at the center of band gap. In order to investigate the terahertz wave emission mechanisms, the emission spectra and temperature dependence of the emission intensity are evaluated. It is shown that intense terahertz emission from S.I.-GaAs over 120 K is observed due to the thermal recovery of photo-quenched EL2 meta-stable state, and that the emission peak frequency looks to be attributed to the shallow level energy in GaAs.

5. Terahertz photoluminescence from S.I.-GaAs by below gap excitation via EL2 level

Oyama, Yutaka; Dezaki, Hikari; Shimizu, Yusaku; Maeda, Kensaku

2015-01-01

Terahertz emission by radiative transitions in semi-conductors via shallow impurity states is investigated. We report on the observation of terahertz photoluminescence from S.I.-GaAs by below gap excitation via EL2 level which is located at the center of band gap. In order to investigate the terahertz wave emission mechanisms, the emission spectra and temperature dependence of the emission intensity are evaluated. It is shown that intense terahertz emission from S.I.-GaAs over 120 K is observed due to the thermal recovery of photo-quenched EL2 meta-stable state, and that the emission peak frequency looks to be attributed to the shallow level energy in GaAs.

6. Evolution of NO2 levels in Spain from 1996 to 2012

PubMed Central

Cuevas, Carlos A.; Notario, Alberto; Adame, José Antonio; Hilboll, Andreas; Richter, Andreas; Burrows, John P.; Saiz-Lopez, Alfonso

2014-01-01

We report on the evolution of tropospheric nitrogen dioxide (NO2) over Spain, focusing on the densely populated cities of Barcelona, Bilbao, Madrid, Sevilla and Valencia, during 17 years, from 1996 to 2012. This data series combines observations from in-situ air quality monitoring networks and the satellite-based instruments GOME and SCIAMACHY. The results in these five cities show a smooth decrease in the NO2 concentrations of ~2% per year in the period 1996–2008, due to the implementation of emissions control environmental legislation, and a more abrupt descend of ~7% per year from 2008 to 2012 as a consequence of the economic recession. In the whole Spanish territory the NO2 levels have decreased by ~22% from 1996 to 2012. Statistical analysis of several economic indicators is used to investigate the different factors driving the NO2 concentration trends over Spain during the last two decades. PMID:25074028

7. Sensing, physiological effects and molecular response to elevated CO2 levels in eukaryotes

PubMed Central

Sharabi, Kfir; Lecuona, Emilia; Helenius, Iiro Taneli; Beitel, Greg J; Sznajder, Jacob Iasha; Gruenbaum, Yosef

2009-01-01

Carbon dioxide (CO2) is an important gaseous molecule that maintains biosphere homeostasis and is an important cellular signalling molecule in all organisms. The transport of CO2 through membranes has fundamental roles in most basic aspects of life in both plants and animals. There is a growing interest in understanding how CO2 is transported into cells, how it is sensed by neurons and other cell types and in understanding the physiological and molecular consequences of elevated CO2 levels (hypercapnia) at the cell and organism levels. Human pulmonary diseases and model organisms such as fungi, C. elegans, Drosophila and mice have been proven to be important in understanding of the mechanisms of CO2 sensing and response. PMID:19863692

8. Plate tectonic controls on atmospheric CO2 levels since the Triassic

PubMed Central

Van Der Meer, Douwe G.; Zeebe, Richard E.; van Hinsbergen, Douwe J. J.; Sluijs, Appy; Spakman, Wim; Torsvik, Trond H.

2014-01-01

Climate trends on timescales of 10s to 100s of millions of years are controlled by changes in solar luminosity, continent distribution, and atmosphere composition. Plate tectonics affect geography, but also atmosphere composition through volcanic degassing of CO2 at subduction zones and midocean ridges. So far, such degassing estimates were based on reconstructions of ocean floor production for the last 150 My and indirectly, through sea level inversion before 150 My. Here we quantitatively estimate CO2 degassing by reconstructing lithosphere subduction evolution, using recent advances in combining global plate reconstructions and present-day structure of the mantle. First, we estimate that since the Triassic (250–200 My) until the present, the total paleosubduction-zone length reached up to ∼200% of the present-day value. Comparing our subduction-zone lengths with previously reconstructed ocean-crust production rates over the past 140 My suggests average global subduction rates have been constant, ∼6 cm/y: Higher ocean-crust production is associated with longer total subduction length. We compute a strontium isotope record based on subduction-zone length, which agrees well with geological records supporting the validity of our approach: The total subduction-zone length is proportional to the summed arc and ridge volcanic CO2 production and thereby to global volcanic degassing at plate boundaries. We therefore use our degassing curve as input for the GEOCARBSULF model to estimate atmospheric CO2 levels since the Triassic. Our calculated CO2 levels for the mid Mesozoic differ from previous modeling results and are more consistent with available proxy data. PMID:24616495

9. Increased trefoil factor 2 levels in patients with chronic kidney disease

PubMed Central

Lebherz-Eichinger, Diana; Tudor, Bianca; Ankersmit, Hendrik J.; Reiter, Thomas; Haas, Martin; Einwallner, Elisa; Roth-Walter, Franziska; Krenn, Claus G.; Roth, Georg A.

2017-01-01

In chronically damaged tissue, trefoil factor family (TFF) peptides ensure epithelial protection and restitution. In chronic kidney disease (CKD), TFF1 and TFF2 are reported to be upregulated. Especially in the early phase, CKD is associated with silently ongoing renal damage and inflammation. Moreover, many patients are diagnosed late during disease progression. We therefore sought to investigate the potential of TFF2 as biomarker for CKD. We followed 118 patients suffering from predialysis CKD and 23 healthy volunteers. TFF2 concentrations were measured using ELISA. Our results showed, that median TFF2 serum levels were significantly higher in patients with later CKD stages as compared to healthy controls (p < 0.001) or early stages (p < 0.001). In patients with mid CKD stages TFF2 serum levels were significantly higher than in healthy controls (p = 0.002). Patients with early or mid CKD stages had significantly higher TFF2 urine concentrations than later CKD stages (p < 0.001 and p = 0.009, respectively). Fractional TFF2 excretion differed significantly between early CKD stages and healthy controls (p = 0.01). ROC curve showed that TFF2 levels can predict different CKD stages (AUC > 0.75). In conclusion, urine and serum TFF2 levels of CKD patients show a different profile dependent on CKD stages. Whereas TFF2 urine levels continuously decreased with disease progression, TFF2 serum concentrations progressively increased from the early to later CKD stages, indicating changes in renal function and offering the potential to examine the course of CKD. PMID:28355260

10. Plate tectonic controls on atmospheric CO2 levels since the Triassic.

PubMed

Van Der Meer, Douwe G; Zeebe, Richard E; van Hinsbergen, Douwe J J; Sluijs, Appy; Spakman, Wim; Torsvik, Trond H

2014-03-25

Climate trends on timescales of 10s to 100s of millions of years are controlled by changes in solar luminosity, continent distribution, and atmosphere composition. Plate tectonics affect geography, but also atmosphere composition through volcanic degassing of CO2 at subduction zones and midocean ridges. So far, such degassing estimates were based on reconstructions of ocean floor production for the last 150 My and indirectly, through sea level inversion before 150 My. Here we quantitatively estimate CO2 degassing by reconstructing lithosphere subduction evolution, using recent advances in combining global plate reconstructions and present-day structure of the mantle. First, we estimate that since the Triassic (250-200 My) until the present, the total paleosubduction-zone length reached up to ∼200% of the present-day value. Comparing our subduction-zone lengths with previously reconstructed ocean-crust production rates over the past 140 My suggests average global subduction rates have been constant, ∼6 cm/y: Higher ocean-crust production is associated with longer total subduction length. We compute a strontium isotope record based on subduction-zone length, which agrees well with geological records supporting the validity of our approach: The total subduction-zone length is proportional to the summed arc and ridge volcanic CO2 production and thereby to global volcanic degassing at plate boundaries. We therefore use our degassing curve as input for the GEOCARBSULF model to estimate atmospheric CO2 levels since the Triassic. Our calculated CO2 levels for the mid Mesozoic differ from previous modeling results and are more consistent with available proxy data.

11. Effect of CO2 levels on nutrient content of lettuce and radish

NASA Technical Reports Server (NTRS)

McKeehen, J. D.; Smart, D. J.; Mackowiak, C. L.; Wheeler, R. M.; Nielsen, S. S.; Mitchell, C. A. (Principal Investigator)

1996-01-01

Atmospheric carbon-dioxide enrichment is known to affect the yield of lettuce and radish grown in controlled environments, but little is known about CO2 enrichment effects on the chemical composition of lettuce and radish. These crops are useful model systems for a Controlled Ecological Life-Support System (CELSS), largely because of their relatively short production cycles. Lettuce (Lactuca sativa L.) cultivar 'Waldmann's Green' and radish (Raphanus sativus L.) cultivar 'Giant White Globe' were grown both in the field and in controlled environments, where hydroponic nutrient solution, light, and temperature were regulated, and where CO2 levels were controlled at 400, 1000, 5000, or 10,000 ppm. Plants were harvested at maturity, dried, and analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate N, free sugars, starch, total dietary fiber, and minerals. Total N, protein N, nonprotein N (NPN), and nitrate N generally increased for radish roots and lettuce leaves when grown under growth chamber conditions compared to field conditions. The nitrate-N level of lettuce leaves, as a percentage of total NPN, decreased with increasing levels of CO2 enrichment. The ash content of radish roots and of radish and lettuce leaves decreased with increasing levels of CO2 enrichment. The levels of certain minerals differed between field- and chamber-grown materials, including changes in the calcium (Ca) and phosphorus (P) contents of radish and lettuce leaves, resulting in reduced Ca/P ratio for chamber-grown materials. The free-sugar contents were similar between the field and chamber-grown lettuce leaves, but total dietary fiber content was much higher in the field-grown plant material. The starch content of growth-chamber lettuce increased with CO2 level.

12. Microzooplankton grazing and phytoplankton growth in marine mesocosms with increased CO2 levels

Suffrian, K.; Simonelli, P.; Nejstgaard, J. C.; Putzeys, S.; Carotenuto, Y.; Antia, A. N.

2008-01-01

Microzooplankton grazing and algae growth responses to increasing pCO2 levels (350, 700 and 1050 μatm) were investigated in nitrate and phosphate fertilized mesocosms during the PeECE III experiment 2005. Grazing and growth rates were estimated by the dilution technique combined with taxon specific HPLC pigment analysis. Phytoplankton and microzooplankton composition were determined by light microscopy. Despite a range up to 3 times the present CO2 levels, there were no clear differences in any measured parameter between the different CO2 treatments. Thus, during the first 9 days of the experiment the algae community standing stock (SS), measured as chlorophyll a (Chl a), showed the highest instantaneous grow rates (0.02-0.99 d-1) and increased from ca 2-3 to 6-12 μg l-1, in all mesocosms. Afterwards the phytoplankton SS decreased in all mesocosms until the end of the experiment. The microzooplankton SS, that was mainly dinoflagellates and ciliates varied between 23 and 130 μg C l-1, peaking on day 13-15, apparently responding to the phytoplankton development. Instantaneous Chl a growth rates were generally higher than the grazing rates, indicating only a limited overall effect of microzooplankton grazing on the most dominant phytoplankton. Diatoms and prymnesiophytes were significantly grazed (14-43% of the SS d-1) only in the pre-bloom phase when they were in low numbers and in the post-bloom phase when they were already limited by low nutrients and/or virus lysis. The cyanobacteria populations appeared more effected by microzooplankton grazing, generally removing 20-65% of the SS d-1.

13. Effects of high CO2 levels on dynamic photosynthesis: carbon gain, mechanisms, and environmental interactions.

PubMed

Tomimatsu, Hajime; Tang, Yanhong

2016-05-01

Understanding the photosynthetic responses of terrestrial plants to environments with high levels of CO2 is essential to address the ecological effects of elevated atmospheric CO2. Most photosynthetic models used for global carbon issues are based on steady-state photosynthesis, whereby photosynthesis is measured under constant environmental conditions; however, terrestrial plant photosynthesis under natural conditions is highly dynamic, and photosynthetic rates change in response to rapid changes in environmental factors. To predict future contributions of photosynthesis to the global carbon cycle, it is necessary to understand the dynamic nature of photosynthesis in relation to high CO2 levels. In this review, we summarize the current body of knowledge on the photosynthetic response to changes in light intensity under experimentally elevated CO2 conditions. We found that short-term exposure to high CO2 enhances photosynthetic rate, reduces photosynthetic induction time, and reduces post-illumination CO2 burst, resulting in increased leaf carbon gain during dynamic photosynthesis. However, long-term exposure to high CO2 during plant growth has varying effects on dynamic photosynthesis. High levels of CO2 increase the carbon gain in photosynthetic induction in some species, but have no significant effects in other species. Some studies have shown that high CO2 levels reduce the biochemical limitation on RuBP regeneration and Rubisco activation during photosynthetic induction, whereas the effects of high levels of CO2 on stomatal conductance differ among species. Few studies have examined the influence of environmental factors on effects of high levels of CO2 on dynamic photosynthesis. We identified several knowledge gaps that should be addressed to aid future predictions of photosynthesis in high-CO2 environments.

14. Effect of CO_2 levels on nutrient content of lettuce and radish

McKeehen, J. D.; Smart, D. J.; Mackowiak, C. L.; Wheeler, R. M.; Nielsen, S. S.

Atmospheric carbon-dioxide enrichment is known to affect the yield of lettuce and radish grown in controlled environments, but little is known about CO_2 enrichment effects on the chemical composition of lettuce and radish. These crops are useful model systems for a Controlled Ecological Life-Support System (CELSS), largely because of their relatively short production cycles. Lettuce (Lactuca sativa L.) cultivar `Waldmann's Green' and radish (Raphanus sativus L.) cultivar `Giant White Globe' were grown both in the field and in controlled environments, where hydroponic nutrient solution, light, and temperature were regulated, and where CO_2 levels were controlled at 400, 1000, 5000, or 10,000 ppm. Plants were harvested at maturity, dried, and analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate N, free sugars, starch, total dietary fiber, and minerals. Total N, protein N, nonprotein N (NPN), and nitrate N generally increased for radish roots and lettuce leaves when grown under growth chamber conditions compared to field conditions. The nitrate-N level of lettuce leaves, as a percentage of total NPN, decreased with increasing levels of CO_2 enrichment. The ash content of radish roots and of radish and lettuce leaves decreased with increasing levels of CO_2 enrichment. The levels of certain minerals differed between field- and chamber-grown materials, including changes in the calcium (Ca) and phosphorus (P) contents of radish roots and lettuce leaves, resulting in reduced Ca/P ratio for chamber-grown materials. The free-sugar contents were similar between the field and chamber-grown lettuce leaves, but total dietary fiber content was much higher in the field-grown plant material. The starch content of growth-chamber lettuce increased with CO_2 level.

15. Effect of CO2 levels on nutrient content of lettuce and radish.

PubMed

McKeehen, J D; Smart, D J; Mackowiak, C L; Wheeler, R M; Nielsen, S S

1996-01-01

Atmospheric carbon-dioxide enrichment is known to affect the yield of lettuce and radish grown in controlled environments, but little is known about CO2 enrichment effects on the chemical composition of lettuce and radish. These crops are useful model systems for a Controlled Ecological Life-Support System (CELSS), largely because of their relatively short production cycles. Lettuce (Lactuca sativa L.) cultivar 'Waldmann's Green' and radish (Raphanus sativus L.) cultivar 'Giant White Globe' were grown both in the field and in controlled environments, where hydroponic nutrient solution, light, and temperature were regulated, and where CO2 levels were controlled at 400, 1000, 5000, or 10,000 ppm. Plants were harvested at maturity, dried, and analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate N, free sugars, starch, total dietary fiber, and minerals. Total N, protein N, nonprotein N (NPN), and nitrate N generally increased for radish roots and lettuce leaves when grown under growth chamber conditions compared to field conditions. The nitrate-N level of lettuce leaves, as a percentage of total NPN, decreased with increasing levels of CO2 enrichment. The ash content of radish roots and of radish and lettuce leaves decreased with increasing levels of CO2 enrichment. The levels of certain minerals differed between field- and chamber-grown materials, including changes in the calcium (Ca) and phosphorus (P) contents of radish and lettuce leaves, resulting in reduced Ca/P ratio for chamber-grown materials. The free-sugar contents were similar between the field and chamber-grown lettuce leaves, but total dietary fiber content was much higher in the field-grown plant material. The starch content of growth-chamber lettuce increased with CO2 level.

16. Toward Controlled Hierarchical Heterogeneities in Giant Molecules with Precisely Arranged Nano Building Blocks

PubMed Central

2016-01-01

Herein we introduce a unique synthetic methodology to prepare a library of giant molecules with multiple, precisely arranged nano building blocks, and illustrate the influence of minute structural differences on their self-assembly behaviors. The T8 polyhedral oligomeric silsesquioxane (POSS) nanoparticles are orthogonally functionalized and sequentially attached onto the end of a hydrophobic polymer chain in either linear or branched configuration. The heterogeneity of primary chemical structure in terms of composition, surface functionality, sequence, and topology can be precisely controlled and is reflected in the self-assembled supramolecular structures of these giant molecules in the condensed state. This strategy offers promising opportunities to manipulate the hierarchical heterogeneities of giant molecules via precise and modular assemblies of various nano building blocks. PMID:27163025

17. Multiclass feature learning for hyperspectral image classification: Sparse and hierarchical solutions

Tuia, Devis; Flamary, Rémi; Courty, Nicolas

2015-07-01

In this paper, we tackle the question of discovering an effective set of spatial filters to solve hyperspectral classification problems. Instead of fixing a priori the filters and their parameters using expert knowledge, we let the model find them within random draws in the (possibly infinite) space of possible filters. We define an active set feature learner that includes in the model only features that improve the classifier. To this end, we consider a fast and linear classifier, multiclass logistic classification, and show that with a good representation (the filters discovered), such a simple classifier can reach at least state of the art performances. We apply the proposed active set learner in four hyperspectral image classification problems, including agricultural and urban classification at different resolutions, as well as multimodal data. We also propose a hierarchical setting, which allows to generate more complex banks of features that can better describe the nonlinearities present in the data.

18. Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system

SciTech Connect

Shorikov, A. F.

2015-11-30

We consider a discrete–time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector nonlinear or linear discrete–time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminal approach process with incomplete information and give a general scheme for its solving.

19. A hierarchical visualization model of the global terrain based on QTM

Bai, Jian-jun; Yan, Chao-de; Zhao, Xue-sheng

2008-10-01

A global multi-resolution digital elevation model (DEM) and a feasible solution for its visualization and management remains a challenging vision. In this paper a multi-resolution DEM based on the ellipsoidal triangular meshes is made to approximate to the earth surface. It was built through quaternary triangular mesh (QTM) hierarchical tessellation of the ellipsoidal surface. In order to achieve fast access, we organize the global DEM data as a hierarchy of Diamonds and indexing them based on the linear quadtree. Furthermore, a LOD is built through recursive subdivision of each Diamond, and an approach of viewpoints-based data extraction based on the neighbor-Diamond searching from the global DEM data is implemented for visualization. All this is backed with an implementation of a prototype computer system.

20. Hierarchical Assembly of a Dual-responsive Macroscopic Insulated Molecular Wire Bundle in a Gradient System

PubMed Central

Sheng, Yujie; Chen, Qibin; Yao, Junyao; Wang, Ying; Liu, Honglai

2015-01-01

Here, we report the hierarchical self-assembly of a cationic gemini amphiphile, Azo 1, in a composition gradient solution generated using solvent evaporation. As the gradient solution is formed, Azo 1 forms nanorods in the lower region of the solution. Depending on solvent composition, these nanorods can further develop into nanofibres, which can then intertwine to form double helices and other types of nanohelices in the upper region of the solution. Finally, a macroscopic wire bundle is formed via the fusion of nanohelices; this ribbon-like bundle exhibits elasticity and linear ohmic resistance properties. More intriguingly, this bundle exhibits photoresponsive properties that affect its deformation and conductivity, as well as a rapid electroresponse that affects its conductivity, indicating that it is feasible to control the charge pathway. PMID:25588881