Emerging Hierarchical Aerogels: Self-Assembly of Metal and Semiconductor Nanocrystals.

PubMed

Cai, Bin; Sayevich, Vladimir; Gaponik, Nikolai; Eychmüller, Alexander

2018-06-19

Aerogels assembled from colloidal metal or semiconductor nanocrystals (NCs) feature large surface area, ultralow density, and high porosity, thus rendering them attractive in various applications, such as catalysis, sensors, energy storage, and electronic devices. Morphological and structural modification of the aerogel backbones while maintaining the aerogel properties enables a second stage of the aerogel research, which is defined as hierarchical aerogels. Different from the conventional aerogels with nanowire-like backbones, those hierarchical aerogels are generally comprised of at least two levels of architectures, i.e., an interconnected porous structure on the macroscale and a specially designed configuration at local backbones at the nanoscale. This combination "locks in" the inherent properties of the NCs, so that the beneficial genes obtained by nanoengineering are retained in the resulting monolithic hierarchical aerogels. Herein, groundbreaking advances in the design, synthesis, and physicochemical properties of the hierarchical aerogels are reviewed and organized in three sections: i) pure metallic hierarchical aerogels, ii) semiconductor hierarchical aerogels, and iii) metal/semiconductor hybrid hierarchical aerogels. This report aims to define and demonstrate the concept, potential, and challenges of the hierarchical aerogels, thereby providing a perspective on the further development of these materials. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Leadership styles across hierarchical levels in nursing departments.

PubMed

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

2000-01-01

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

Elaboration on the Culturally Informed Iranian Hierarchical Wisdom Model: Comparison with Sternberg's ACCEL Model

ERIC Educational Resources Information Center

Karami, Sareh; Ghahremani, Mehdi

2017-01-01

Using a grounded theory approach to the study of historical texts and an expert interview, we developed the Iranian hierarchical wisdom model (IHWM; Karami & Ghahremani, 2016). According to IHWM, there are three levels to wisdom: practical intelligence, wise, and sage. In this article, we discuss the model and elaborate on it. Next, we examine…

Hierarchical Learning of Tree Classifiers for Large-Scale Plant Species Identification.

PubMed

Fan, Jianping; Zhou, Ning; Peng, Jinye; Gao, Ling

2015-11-01

In this paper, a hierarchical multi-task structural learning algorithm is developed to support large-scale plant species identification, where a visual tree is constructed for organizing large numbers of plant species in a coarse-to-fine fashion and determining the inter-related learning tasks automatically. For a given parent node on the visual tree, it contains a set of sibling coarse-grained categories of plant species or sibling fine-grained plant species, and a multi-task structural learning algorithm is developed to train their inter-related classifiers jointly for enhancing their discrimination power. The inter-level relationship constraint, e.g., a plant image must first be assigned to a parent node (high-level non-leaf node) correctly if it can further be assigned to the most relevant child node (low-level non-leaf node or leaf node) on the visual tree, is formally defined and leveraged to learn more discriminative tree classifiers over the visual tree. Our experimental results have demonstrated the effectiveness of our hierarchical multi-task structural learning algorithm on training more discriminative tree classifiers for large-scale plant species identification.

Data graphing methods, articles of manufacture, and computing devices

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

Wong, Pak Chung; Mackey, Patrick S.; Cook, Kristin A.

Data graphing methods, articles of manufacture, and computing devices are described. In one aspect, a method includes accessing a data set, displaying a graphical representation including data of the data set which is arranged according to a first of different hierarchical levels, wherein the first hierarchical level represents the data at a first of a plurality of different resolutions which respectively correspond to respective ones of the hierarchical levels, selecting a portion of the graphical representation wherein the data of the portion is arranged according to the first hierarchical level at the first resolution, modifying the graphical representation by arrangingmore » the data of the portion according to a second of the hierarchal levels at a second of the resolutions, and after the modifying, displaying the graphical representation wherein the data of the portion is arranged according to the second hierarchal level at the second resolution.« less

The mathematical relationship between Zipf’s law and the hierarchical scaling law

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2012-06-01

The empirical studies of city-size distribution show that Zipf's law and the hierarchical scaling law are linked in many ways. The rank-size scaling and hierarchical scaling seem to be two different sides of the same coin, but their relationship has never been revealed by strict mathematical proof. In this paper, the Zipf's distribution of cities is abstracted as a q-sequence. Based on this sequence, a self-similar hierarchy consisting of many levels is defined and the numbers of cities in different levels form a geometric sequence. An exponential distribution of the average size of cities is derived from the hierarchy. Thus we have two exponential functions, from which follows a hierarchical scaling equation. The results can be statistically verified by simple mathematical experiments and observational data of cities. A theoretical foundation is then laid for the conversion from Zipf's law to the hierarchical scaling law, and the latter can show more information about city development than the former. Moreover, the self-similar hierarchy provides a new perspective for studying networks of cities as complex systems. A series of mathematical rules applied to cities such as the allometric growth law, the 2n principle and Pareto's law can be associated with one another by the hierarchical organization.

A Multi-Level Examination of College and Its Influence on Ecumenical Worldview Development

ERIC Educational Resources Information Center

Mayhew, Matthew J.

2012-01-01

This multi-level, longitudinal study investigated the ecumenical worldview development of 13,932 students enrolled in one of 126 institutions. Results indicated that the final hierarchical linear model, consisting of institution-and-student-level predictors as well as slopes explaining the relationships among some of these predictors, explained…

Modelling the mechanics of partially mineralized collagen fibrils, fibres and tissue

PubMed Central

Liu, Yanxin; Thomopoulos, Stavros; Chen, Changqing; Birman, Victor; Buehler, Markus J.; Genin, Guy M.

2014-01-01

Progressive stiffening of collagen tissue by bioapatite mineral is important physiologically, but the details of this stiffening are uncertain. Unresolved questions about the details of the accommodation of bioapatite within and upon collagen's hierarchical structure have posed a central hurdle, but recent microscopy data resolve several major questions. These data suggest how collagen accommodates bioapatite at the lowest relevant hierarchical level (collagen fibrils), and suggest several possibilities for the progressive accommodation of bioapatite at higher hierarchical length scales (fibres and tissue). We developed approximations for the stiffening of collagen across spatial hierarchies based upon these data, and connected models across hierarchies levels to estimate mineralization-dependent tissue-level mechanics. In the five possible sequences of mineralization studied, percolation of the bioapatite phase proved to be an important determinant of the degree of stiffening by bioapatite. The models were applied to study one important instance of partially mineralized tissue, which occurs at the attachment of tendon to bone. All sequences of mineralization considered reproduced experimental observations of a region of tissue between tendon and bone that is more compliant than either tendon or bone, but the size and nature of this region depended strongly upon the sequence of mineralization. These models and observations have implications for engineered tissue scaffolds at the attachment of tendon to bone, bone development and graded biomimetic attachment of dissimilar hierarchical materials in general. PMID:24352669

Effects of host social hierarchy on disease persistence.

PubMed

Davidson, Ross S; Marion, Glenn; Hutchings, Michael R

2008-08-07

The effects of social hierarchy on population dynamics and epidemiology are examined through a model which contains a number of fundamental features of hierarchical systems, but is simple enough to allow analytical insight. In order to allow for differences in birth rates, contact rates and movement rates among different sets of individuals the population is first divided into subgroups representing levels in the hierarchy. Movement, representing dominance challenges, is allowed between any two levels, giving a completely connected network. The model includes hierarchical effects by introducing a set of dominance parameters which affect birth rates in each social level and movement rates between social levels, dependent upon their rank. Although natural hierarchies vary greatly in form, the skewing of contact patterns, introduced here through non-uniform dominance parameters, has marked effects on the spread of disease. A simple homogeneous mixing differential equation model of a disease with SI dynamics in a population subject to simple birth and death process is presented and it is shown that the hierarchical model tends to this as certain parameter regions are approached. Outside of these parameter regions correlations within the system give rise to deviations from the simple theory. A Gaussian moment closure scheme is developed which extends the homogeneous model in order to take account of correlations arising from the hierarchical structure, and it is shown that the results are in reasonable agreement with simulations across a range of parameters. This approach helps to elucidate the origin of hierarchical effects and shows that it may be straightforward to relate the correlations in the model to measurable quantities which could be used to determine the importance of hierarchical corrections. Overall, hierarchical effects decrease the levels of disease present in a given population compared to a homogeneous unstructured model, but show higher levels of disease than structured models with no hierarchy. The separation between these three models is greatest when the rate of dominance challenges is low, reducing mixing, and when the disease prevalence is low. This suggests that these effects will often need to be considered in models being used to examine the impact of control strategies where the low disease prevalence behaviour of a model is critical.

Professionals’ views on interprofessional stroke team functioning

PubMed Central

Cramm, Jane M; Nieboer, Anna P

2011-01-01

Introduction The quality of integrated stroke care depends on smooth team functioning but professionals may not always work well together. Professionals’ perspectives on the factors that influence stroke team functioning remain largely unexamined. Understanding their experiences is critical to indentifying measures to improve team functioning. The aim of this study was to identify the factors that contributed to the success of interprofessional stroke teams as perceived by team members. Methods We distributed questionnaires to professionals within 34 integrated stroke care teams at various health care facilities in 9 Dutch regions. 558 respondents (response rate: 39%) completed the questionnaire. To account for the hierarchical structure of the study design we fitted a hierarchical random-effects model. The hierarchical structure comprised 558 stroke team members (level 1) nested in 34 teams (level 2). Results Analyses showed that personal development, social well-being, interprofessional education, communication, and role understanding significantly contributed to stroke team functioning. Team-level constructs affecting interprofessional stroke team functioning were communication and role understanding. No significant relationships were found with individual-level personal autonomy and team-level cohesion. Discussion and conclusion Our findings suggest that interventions to improve team members’ social well-being, communication, and role understanding will improve teams’ performance. To further advance interprofessional team functioning, healthcare organizations should pay attention to developing professionals’ interpersonal skills and interprofessional education. PMID:23390409

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

PubMed Central

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

2013-01-01

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. PMID:23900554

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

PubMed

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

2013-01-01

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.

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

NASA Astrophysics Data System (ADS)

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.

A Hierarchical Multiple-Level Approach to the Assessment of Interpersonal Relatedness and Self-Definition: Implications for Research, Clinical Practice, and DSM Planning.

PubMed

Luyten, Patrick; Blatt, Sidney J

2016-01-01

Extant research suggests there is considerable overlap between so-called 2-polarities models of personality development; that is, models that propose that personality development evolves through a dialectic synergistic interaction between 2 key developmental tasks across the life span-the development of self-definition on the one hand and of relatedness on the other. These models have attracted considerable research attention and play a central role in DSM planning. This article provides a researcher- and clinician-friendly guide to the assessment of these personality theories. We argue that current theoretical models focus on issues of relatedness and self-definition at different hierarchically organized levels of analysis; that is (a) at the level of broad personality features, (b) at the motivational level (i.e., the motivational processes underlying the development of these dimensions), and (c) at the level of underlying internal working models or cognitive affective schemas, and the specific interpersonal features and problems in which they are expressed. Implications for further research and DSM planning are outlined.

[Governance of PHC development in Rosario, Argentina].

PubMed

Báscolo, Ernesto; Yavich, Natalia

2010-01-01

Describing the development of PHC policy as promoted by Rosario Municipality (Argentina). A case-study was carried out during 2007 and 2008. Data was collected from secondary and primary sources (interviews, organisational census and observations). PHC development stages were identified by recognising the social norms which produced institutional change and transformation in municipal health services structure and health care and management models. The prevailing modes of governance in each stage were reconognised and characterised (clan, hierarchy and/or incentives). Four stages were identified between 1990 and 2008: 1990-1995/hierarchical mode: primary health care level organisation autonomied from hospitals. 1995-2000/ clan mode: developing of participatory managerial boards and community participation. 2000-2004/ clan mode: maturation of the "PHC movement" in competition with hospitals. 2004-2008/ clan-hierarchical mode: "movement's" crisis and constructions of norms tending towards enhancing an integrated network. Strengthening and empowering first-level health-care produced innovation favouring: the consolidation of a "PHC movement" having strong social commitment and improved services performance. The clan governance mode (regulating collective action via voluntary adhesion to shared values) was crucial for developing PHC between 1995 and 2004. Later on, the movement's fragmentation and the challenges of integrating the health system required developing hierarchical regulation mechanisms to complement the governance clan mode regulation.

Functional adaptation of crustacean exoskeletal elements through structural and compositional diversity: a combined experimental and theoretical study.

PubMed

Fabritius, Helge-Otto; Ziegler, Andreas; Friák, Martin; Nikolov, Svetoslav; Huber, Julia; Seidl, Bastian H M; Ruangchai, Sukhum; Alagboso, Francisca I; Karsten, Simone; Lu, Jin; Janus, Anna M; Petrov, Michal; Zhu, Li-Fang; Hemzalová, Pavlína; Hild, Sabine; Raabe, Dierk; Neugebauer, Jörg

2016-09-09

The crustacean cuticle is a composite material that covers the whole animal and forms the continuous exoskeleton. Nano-fibers composed of chitin and protein molecules form most of the organic matrix of the cuticle that, at the macroscale, is organized in up to eight hierarchical levels. At least two of them, the exo- and endocuticle, contain a mineral phase of mainly Mg-calcite, amorphous calcium carbonate and phosphate. The high number of hierarchical levels and the compositional diversity provide a high degree of freedom for varying the physical, in particular mechanical, properties of the material. This makes the cuticle a versatile material ideally suited to form a variety of skeletal elements that are adapted to different functions and the eco-physiological strains of individual species. This review presents our recent analytical, experimental and theoretical studies on the cuticle, summarising at which hierarchical levels structure and composition are modified to achieve the required physical properties. We describe our multi-scale hierarchical modeling approach based on the results from these studies, aiming at systematically predicting the structure-composition-property relations of cuticle composites from the molecular level to the macro-scale. This modeling approach provides a tool to facilitate the development of optimized biomimetic materials within a knowledge-based design approach.

Strong influence of variable treatment on the performance of numerically defined ecological regions.

PubMed

Snelder, Ton; Lehmann, Anthony; Lamouroux, Nicolas; Leathwick, John; Allenbach, Karin

2009-10-01

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale "sub-domains" defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.

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

PubMed

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

2018-05-10

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

Cable deformation simulation and a hierarchical framework for Nb3Sn Rutherford cables

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

Arbelaez, D.; Prestemon, S. O.; Ferracin, P.

2009-09-13

Knowledge of the three-dimensional strain state induced in the superconducting filaments due to loads on Rutherford cables is essential to analyze the performance of Nb{sub 3}Sn magnets. Due to the large range of length scales involved, we develop a hierarchical computational scheme that includes models at both the cable and strand levels. At the Rutherford cable level, where the strands are treated as a homogeneous medium, a three-dimensional computational model is developed to determine the deformed shape of the cable that can subsequently be used to determine the strain state under specified loading conditions, which may be of thermal, magnetic,more » and mechanical origins. The results can then be transferred to the model at the strand/macro-filament level for rod restack process (RRP) strands, where the geometric details of the strand are included. This hierarchical scheme can be used to estimate the three-dimensional strain state in the conductor as well as to determine the effective properties of the strands and cables from the properties of individual components. Examples of the modeling results obtained for the orthotropic mechanical properties of the Rutherford cables are presented.« less

Uncertainty in the Work-Place: Hierarchical Differences of Uncertainty Levels and Reduction Strategies.

ERIC Educational Resources Information Center

Petelle, John L.; And Others

A study examined the uncertainty levels and types reported by supervisors and employees at three hierarchical levels of an organization: first-line supervisors, full-time employees, and part-time employees. It investigated differences in uncertainty-reduction strategies employed by these three hierarchical groups. The 61 subjects who completed…

Hierarchical classification method and its application in shape representation

NASA Astrophysics Data System (ADS)

Ireton, M. A.; Oakley, John P.; Xydeas, Costas S.

1992-04-01

In this paper we describe a technique for performing shaped-based content retrieval of images from a large database. In order to be able to formulate such user-generated queries about visual objects, we have developed an hierarchical classification technique. This hierarchical classification technique enables similarity matching between objects, with the position in the hierarchy signifying the level of generality to be used in the query. The classification technique is unsupervised, robust, and general; it can be applied to any suitable parameter set. To establish the potential of this classifier for aiding visual querying, we have applied it to the classification of the 2-D outlines of leaves.

Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

NASA Astrophysics Data System (ADS)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

Continuum damage modeling and simulation of hierarchical dental enamel

NASA Astrophysics Data System (ADS)

Ma, Songyun; Scheider, Ingo; Bargmann, Swantje

2016-05-01

Dental enamel exhibits high fracture toughness and stiffness due to a complex hierarchical and graded microstructure, optimally organized from nano- to macro-scale. In this study, a 3D representative volume element (RVE) model is adopted to study the deformation and damage behavior of the fibrous microstructure. A continuum damage mechanics model coupled to hyperelasticity is developed for modeling the initiation and evolution of damage in the mineral fibers as well as protein matrix. Moreover, debonding of the interface between mineral fiber and protein is captured by employing a cohesive zone model. The dependence of the failure mechanism on the aspect ratio of the mineral fibers is investigated. In addition, the effect of the interface strength on the damage behavior is studied with respect to geometric features of enamel. Further, the effect of an initial flaw on the overall mechanical properties is analyzed to understand the superior damage tolerance of dental enamel. The simulation results are validated by comparison to experimental data from micro-cantilever beam testing at two hierarchical levels. The transition of the failure mechanism at different hierarchical levels is also well reproduced in the simulations.

An approach to separating the levels of hierarchical structure building in language and mathematics.

PubMed

Makuuchi, Michiru; Bahlmann, Jörg; Friederici, Angela D

2012-07-19

We aimed to dissociate two levels of hierarchical structure building in language and mathematics, namely 'first-level' (the build-up of hierarchical structure with externally given elements) and 'second-level' (the build-up of hierarchical structure with internally represented elements produced by first-level processes). Using functional magnetic resonance imaging, we investigated these processes in three domains: sentence comprehension, arithmetic calculation (using Reverse Polish notation, which gives two operands followed by an operator) and a working memory control task. All tasks required the build-up of hierarchical structures at the first- and second-level, resulting in a similar computational hierarchy across language and mathematics, as well as in a working memory control task. Using a novel method that estimates the difference in the integration cost for conditions of different trial durations, we found an anterior-to-posterior functional organization in the prefrontal cortex, according to the level of hierarchy. Common to all domains, the ventral premotor cortex (PMv) supports first-level hierarchy building, while the dorsal pars opercularis (POd) subserves second-level hierarchy building, with lower activation for language compared with the other two tasks. These results suggest that the POd and the PMv support domain-general mechanisms for hierarchical structure building, with the POd being uniquely efficient for language.

Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

PubMed Central

Badre, David

2012-01-01

Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490

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

ERIC Educational Resources Information Center

Choi, Kilchan

2011-01-01

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

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Hierarchical effects on target detection and conflict monitoring

PubMed Central

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

2016-01-01

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

Dissociable Frontal–Striatal and Frontal–Parietal Networks Involved in Updating Hierarchical Contexts in Working Memory

PubMed Central

Nee, Derek Evan; Brown, Joshua W.

2013-01-01

Recent theories propose that the prefrontal cortex (PFC) is organized in a hierarchical fashion with more abstract, higher level information represented in anterior regions and more concrete, lower level information represented in posterior regions. This hierarchical organization affords flexible adjustments of action plans based on the context. Computational models suggest that such hierarchical organization in the PFC is achieved through interactions with the basal ganglia (BG) wherein the BG gate relevant contexts into the PFC. Here, we tested this proposal using functional magnetic resonance imaging (fMRI). Participants were scanned while updating working memory (WM) with 2 levels of hierarchical contexts. Consistent with PFC abstraction proposals, higher level context updates involved anterior portions of the PFC (BA 46), whereas lower level context updates involved posterior portions of the PFC (BA 6). Computational models were only partially supported as the BG were sensitive to higher, but not lower level context updates. The posterior parietal cortex (PPC) showed the opposite pattern. Analyses examining changes in functional connectivity confirmed dissociable roles of the anterior PFC–BG during higher level context updates and posterior PFC–PPC during lower level context updates. These results suggest that hierarchical contexts are organized by distinct frontal–striatal and frontal–parietal networks. PMID:22798339

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

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

Sleep Disrupts High-Level Speech Parsing Despite Significant Basic Auditory Processing.

PubMed

Makov, Shiri; Sharon, Omer; Ding, Nai; Ben-Shachar, Michal; Nir, Yuval; Zion Golumbic, Elana

2017-08-09

The extent to which the sleeping brain processes sensory information remains unclear. This is particularly true for continuous and complex stimuli such as speech, in which information is organized into hierarchically embedded structures. Recently, novel metrics for assessing the neural representation of continuous speech have been developed using noninvasive brain recordings that have thus far only been tested during wakefulness. Here we investigated, for the first time, the sleeping brain's capacity to process continuous speech at different hierarchical levels using a newly developed Concurrent Hierarchical Tracking (CHT) approach that allows monitoring the neural representation and processing-depth of continuous speech online. Speech sequences were compiled with syllables, words, phrases, and sentences occurring at fixed time intervals such that different linguistic levels correspond to distinct frequencies. This enabled us to distinguish their neural signatures in brain activity. We compared the neural tracking of intelligible versus unintelligible (scrambled and foreign) speech across states of wakefulness and sleep using high-density EEG in humans. We found that neural tracking of stimulus acoustics was comparable across wakefulness and sleep and similar across all conditions regardless of speech intelligibility. In contrast, neural tracking of higher-order linguistic constructs (words, phrases, and sentences) was only observed for intelligible speech during wakefulness and could not be detected at all during nonrapid eye movement or rapid eye movement sleep. These results suggest that, whereas low-level auditory processing is relatively preserved during sleep, higher-level hierarchical linguistic parsing is severely disrupted, thereby revealing the capacity and limits of language processing during sleep. SIGNIFICANCE STATEMENT Despite the persistence of some sensory processing during sleep, it is unclear whether high-level cognitive processes such as speech parsing are also preserved. We used a novel approach for studying the depth of speech processing across wakefulness and sleep while tracking neuronal activity with EEG. We found that responses to the auditory sound stream remained intact; however, the sleeping brain did not show signs of hierarchical parsing of the continuous stream of syllables into words, phrases, and sentences. The results suggest that sleep imposes a functional barrier between basic sensory processing and high-level cognitive processing. This paradigm also holds promise for studying residual cognitive abilities in a wide array of unresponsive states. Copyright © 2017 the authors 0270-6474/17/377772-10$15.00/0.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

An object-oriented class library for medical software development.

PubMed

O'Kane, K C; McColligan, E E

1996-12-01

The objective of this research is the development of a Medical Object Library (MOL) consisting of reusable, inheritable, portable, extendable C++ classes that facilitate rapid development of medical software at reduced cost and increased functionality. The result of this research is a library of class objects that range in function from string and hierarchical file handling entities to high level, procedural agents that perform increasingly complex, integrated tasks. A system built upon these classes is compatible with any other system similarly constructed with respect to data definitions, semantics, data organization and storage. As new objects are built, they can be added to the class library for subsequent use. The MOL is a toolkit of software objects intended to support a common file access methodology, a unified medical record structure, consistent message processing, standard graphical display facilities and uniform data collection procedures. This work emphasizes the relationship that potentially exists between the structure of a hierarchical medical record and procedural language components by means of a hierarchical class library and tree structured file access facility. In doing so, it attempts to establish interest in and demonstrate the practicality of the hierarchical medical record model in the modern context of object oriented programming.

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

Bayesian X-ray computed tomography using a three-level hierarchical prior model

NASA Astrophysics Data System (ADS)

Wang, Li; Mohammad-Djafari, Ali; Gac, Nicolas

2017-06-01

In recent decades X-ray Computed Tomography (CT) image reconstruction has been largely developed in both medical and industrial domain. In this paper, we propose using the Bayesian inference approach with a new hierarchical prior model. In the proposed model, a generalised Student-t distribution is used to enforce the Haar transformation of images to be sparse. Comparisons with some state of the art methods are presented. It is shown that by using the proposed model, the sparsity of sparse representation of images is enforced, so that edges of images are preserved. Simulation results are also provided to demonstrate the effectiveness of the new hierarchical model for reconstruction with fewer projections.

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

NASA Technical Reports Server (NTRS)

Koch, Patrick N.

1997-01-01

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Array-based Hierarchical Mesh Generation in Parallel

DOE PAGES

Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; ...

2015-11-03

In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. Inmore » conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.« less

SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3

PubMed Central

Smith, Lucian P.; Hucka, Michael; Hoops, Stefan; Finney, Andrew; Ginkel, Martin; Myers, Chris J.; Moraru, Ion; Liebermeister, Wolfram

2017-01-01

Summary Constructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models. PMID:26528566

Familial and Religious Influences on Adolescent Alcohol Use: A Multi-Level Study of Students and School Communities

ERIC Educational Resources Information Center

Bjarnason, Thoroddur; Thorlindsson, Thorolfur; Sigfusdottir, Inga D.; Welch, Michael R.

2005-01-01

A multi-level Durkheimian theory of familial and religious influences on adolescent alcohol use is developed and tested with hierarchical linear modeling of data from Icelandic schools and students. On the individual level, traditional family structure, parental monitoring, parental support, religious participation, and perceptions of divine…

Delineation of climate regions in the Northeastern United States

Treesearch

Arthur T. DeGaetano

1996-01-01

Climate is a primary criterion for the development, description and validation of subregional levels of the National Hierarchical Framework of Ecological Units. However, climate information is not currently available in the form or level of detail required for integration with other biophysical factors at the section or subsection levels. In this study, historical...

Operationalizing Levels of Academic Mastery Based on Vygotsky's Theory: The Study of Mathematical Knowledge

ERIC Educational Resources Information Center

Nezhnov, Peter; Kardanova, Elena; Vasilyeva, Marina; Ludlow, Larry

2015-01-01

The present study tested the possibility of operationalizing levels of knowledge acquisition based on Vygotsky's theory of cognitive growth. An assessment tool (SAM-Math) was developed to capture a hypothesized hierarchical structure of mathematical knowledge consisting of procedural, conceptual, and functional levels. In Study 1, SAM-Math was…

A hierarchical modeling methodology for the definition and selection of requirements

NASA Astrophysics Data System (ADS)

Dufresne, Stephane

This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems. At the core of the methodology, the Analytic Network Process (ANP) is used to ensure the traceability between the qualitative and quantitative information present in the hierarchical model. The proposed methodology is implemented to the requirements definition of a hurricane tracker Unmanned Aerial Vehicle. Three research objectives are identified in this work; (1) improve the requirements mapping process by matching the stakeholder expectations with the concept of operations, systems and available resources; (2) reduce the epistemic uncertainty surrounding the requirements and requirements mapping; and (3) improve the requirements down-selection process by taking into account the level of importance of the criteria and the available resources. Several challenges are associated with the identification and definition of requirements. The complexity of the system implies that a large number of requirements are needed to define the systems. These requirements are defined early in the conceptual design, where the level of knowledge is relatively low and the level of uncertainty is large. The proposed methodology intends to increase the level of knowledge and reduce the level of uncertainty by guiding the design team through a structured process. To address these challenges, a new methodology is created to flow-down the requirements from the stakeholder expectations to the systems alternatives. A taxonomy of requirements is created to classify the information gathered during the problem definition. Subsequently, the operational and systems functions and measures of effectiveness are integrated to a hierarchical model to allow the traceability of the information. Monte Carlo methods are used to evaluate the variations of the hierarchical model elements and consequently reduce the epistemic uncertainty. The proposed methodology is applied to the design of a hurricane tracker Unmanned Aerial Vehicles to demonstrate the origin and impact of requirements on the concept of operations and systems alternatives. This research demonstrates that the hierarchical modeling methodology provides a traceable flow-down of the requirements from the problem definition to the systems alternatives phases of conceptual design.

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.

Integrating UniTree with the data migration API

NASA Technical Reports Server (NTRS)

Schrodel, David G.

1994-01-01

The Data Migration Application Programming Interface (DMAPI) has the potential to allow developers of open systems Hierarchical Storage Management (HSM) products to virtualize native file systems without the requirement to make changes to the underlying operating system. This paper describes advantages of virtualizing native file systems in hierarchical storage management systems, the DMAPI at a high level, what the goals are for the interface, and the integration of the Convex UniTree+HSM with DMAPI along with some of the benefits derived in the resulting product.

Three-level global resource allocation model for hiv control: A hierarchical decision system approach.

PubMed

Kassa, Semu Mitiku

2018-02-01

Funds from various global organizations, such as, The Global Fund, The World Bank, etc. are not directly distributed to the targeted risk groups. Especially in the so-called third-world-countries, the major part of the fund in HIV prevention programs comes from these global funding organizations. The allocations of these funds usually pass through several levels of decision making bodies that have their own specific parameters to control and specific objectives to achieve. However, these decisions are made mostly in a heuristic manner and this may lead to a non-optimal allocation of the scarce resources. In this paper, a hierarchical mathematical optimization model is proposed to solve such a problem. Combining existing epidemiological models with the kind of interventions being on practice, a 3-level hierarchical decision making model in optimally allocating such resources has been developed and analyzed. When the impact of antiretroviral therapy (ART) is included in the model, it has been shown that the objective function of the lower level decision making structure is a non-convex minimization problem in the allocation variables even if all the production functions for the intervention programs are assumed to be linear.

Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity

USGS Publications Warehouse

Kotliar, Natasha B.; Wiens, John A.

1990-01-01

We develop a hierarchical model of heterogeneity that provides a framework for classifying patch structure across a range of scales. Patches at lower levels in the hierarchy are more simplistic and correspond to the traditional view of patches. At levels approaching the upper bounds of the hierarchy the internal structure becomes more heterogeneous and boundaries more ambiguous. At each level in the hierarchy, patch structure will be influenced by both contrast among patches as well as the degree of aggregation of patches at lower levels in the hierarchy. We apply this model to foraging theory, but it has wider applications as in the study of habitat selection, population dynamics, and habitat fragmentation. It may also be useful in expanding the realm of landscape ecology beyond the current focus on anthropocentric scales.

Maximum Likelihood Analysis of a Two-Level Nonlinear Structural Equation Model with Fixed Covariates

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan

2005-01-01

In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

On Muthen's Maximum Likelihood for Two-Level Covariance Structure Models

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Hayashi, Kentaro

2005-01-01

Data in social and behavioral sciences are often hierarchically organized. Special statistical procedures that take into account the dependence of such observations have been developed. Among procedures for 2-level covariance structure analysis, Muthen's maximum likelihood (MUML) has the advantage of easier computation and faster convergence. When…

An Ecological Perspective on Deafness.

ERIC Educational Resources Information Center

Harvey, Michael A.; Dym, Barry

1988-01-01

The article offers an ecological view of deafness through identification of the hierarchically arranged, bio-psych-social levels which influence development and the sequences of interaction within and between levels. The organization of ecological fields is described by a cybernetic model from family therapy. A detailed case example is presented.…

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…

An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

ERIC Educational Resources Information Center

Atas, Dogu; Karadag, Özge

2017-01-01

In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

Hierarchical Control Using Networks Trained with Higher-Level Forward Models

PubMed Central

Wayne, Greg; Abbott, L.F.

2015-01-01

We propose and develop a hierarchical approach to network control of complex tasks. In this approach, a low-level controller directs the activity of a “plant,” the system that performs the task. However, the low-level controller may only be able to solve fairly simple problems involving the plant. To accomplish more complex tasks, we introduce a higher-level controller that controls the lower-level controller. We use this system to direct an articulated truck to a specified location through an environment filled with static or moving obstacles. The final system consists of networks that have memorized associations between the sensory data they receive and the commands they issue. These networks are trained on a set of optimal associations that are generated by minimizing cost functions. Cost function minimization requires predicting the consequences of sequences of commands, which is achieved by constructing forward models, including a model of the lower-level controller. The forward models and cost minimization are only used during training, allowing the trained networks to respond rapidly. In general, the hierarchical approach can be extended to larger numbers of levels, dividing complex tasks into more manageable sub-tasks. The optimization procedure and the construction of the forward models and controllers can be performed in similar ways at each level of the hierarchy, which allows the system to be modified to perform other tasks, or to be extended for more complex tasks without retraining lower-levels. PMID:25058706

Modelling habitat associations with fingernail clam (Family: Sphaeriidae) counts at multiple spatial scales using hierarchical count models

USGS Publications Warehouse

Gray, B.R.; Haro, R.J.; Rogala, J.T.; Sauer, J.S.

2005-01-01

1. Macroinvertebrate count data often exhibit nested or hierarchical structure. Examples include multiple measurements along each of a set of streams, and multiple synoptic measurements from each of a set of ponds. With data exhibiting hierarchical structure, outcomes at both sampling (e.g. Within stream) and aggregated (e.g. Stream) scales are often of interest. Unfortunately, methods for modelling hierarchical count data have received little attention in the ecological literature. 2. We demonstrate the use of hierarchical count models using fingernail clam (Family: Sphaeriidae) count data and habitat predictors derived from sampling and aggregated spatial scales. The sampling scale corresponded to that of a standard Ponar grab (0.052 m(2)) and the aggregated scale to impounded and backwater regions within 38-197 km reaches of the Upper Mississippi River. Impounded and backwater regions were resampled annually for 10 years. Consequently, measurements on clams were nested within years. Counts were treated as negative binomial random variates, and means from each resampling event as random departures from the impounded and backwater region grand means. 3. Clam models were improved by the addition of covariates that varied at both the sampling and regional scales. Substrate composition varied at the sampling scale and was associated with model improvements, and reductions (for a given mean) in variance at the sampling scale. Inorganic suspended solids (ISS) levels, measured in the summer preceding sampling, also yielded model improvements and were associated with reductions in variances at the regional rather than sampling scales. ISS levels were negatively associated with mean clam counts. 4. Hierarchical models allow hierarchically structured data to be modelled without ignoring information specific to levels of the hierarchy. In addition, information at each hierarchical level may be modelled as functions of covariates that themselves vary by and within levels. As a result, hierarchical models provide researchers and resource managers with a method for modelling hierarchical data that explicitly recognises both the sampling design and the information contained in the corresponding data.

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)

How children perceive fractals: Hierarchical self-similarity and cognitive development

PubMed Central

Martins, Maurício Dias; Laaha, Sabine; Freiberger, Eva Maria; Choi, Soonja; Fitch, W. Tecumseh

2014-01-01

The ability to understand and generate hierarchical structures is a crucial component of human cognition, available in language, music, mathematics and problem solving. Recursion is a particularly useful mechanism for generating complex hierarchies by means of self-embedding rules. In the visual domain, fractals are recursive structures in which simple transformation rules generate hierarchies of infinite depth. Research on how children acquire these rules can provide valuable insight into the cognitive requirements and learning constraints of recursion. Here, we used fractals to investigate the acquisition of recursion in the visual domain, and probed for correlations with grammar comprehension and general intelligence. We compared second (n = 26) and fourth graders (n = 26) in their ability to represent two types of rules for generating hierarchical structures: Recursive rules, on the one hand, which generate new hierarchical levels; and iterative rules, on the other hand, which merely insert items within hierarchies without generating new levels. We found that the majority of fourth graders, but not second graders, were able to represent both recursive and iterative rules. This difference was partially accounted by second graders’ impairment in detecting hierarchical mistakes, and correlated with between-grade differences in grammar comprehension tasks. Empirically, recursion and iteration also differed in at least one crucial aspect: While the ability to learn recursive rules seemed to depend on the previous acquisition of simple iterative representations, the opposite was not true, i.e., children were able to acquire iterative rules before they acquired recursive representations. These results suggest that the acquisition of recursion in vision follows learning constraints similar to the acquisition of recursion in language, and that both domains share cognitive resources involved in hierarchical processing. PMID:24955884

Conceptual Hierarchies in a Flat Attractor Network

PubMed Central

O’Connor, Christopher M.; Cree, George S.; McRae, Ken

2009-01-01

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory. PMID:19543434

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries.

PubMed

Boehler, Christian E H; Lord, Joanne

2016-01-01

Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%-19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. © The Author(s) 2015.

A neural model of hierarchical reinforcement learning.

PubMed

Rasmussen, Daniel; Voelker, Aaron; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain's general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model's behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions.

Fabrication and good ethanol sensing of biomorphic SnO2 with architecture hierarchy of butterfly wings.

PubMed

Song, Fang; Su, Huilan; Han, Jie; Zhang, Di; Chen, Zhixin

2009-12-09

Using super-hydrophobic butterfly wings as templates, we developed an aqueous sol-gel soakage process assisted by ethanol-wetting and followed by calcination to fabricate well-organized porous hierarchical SnO(2) with connective hollow interiors and thin mesoporous walls. The exquisite hierarchical architecture of SnO(2) is faithfully replicated from the lightweight skeleton of butterfly wings at the level from nano- to macro-scales. On the basis of the self-assembly of SnO(2) nanocrystallites with diameter around 7.0 nm, the interconnected tubes (lamellas), the fastigiated hollow tubers (pillars) and the double-layered substrates further construct the biomorphic hierarchical architecture. Benefiting from the small grain size and the unique hierarchical architecture, the biomorphic SnO(2) as an ethanol sensor exhibits high sensitivity (49.8 to 50 ppm ethanol), and fast response/recovery time (11/31 s to 50 ppm ethanol) even at relatively low working temperature (170 degrees C).

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

PubMed

Liu, Quan; Liu, Aiming; Meng, Wei; Ai, Qingsong; Xie, Sheng Q

2017-01-01

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient's active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant's assessment. The robot reduces its assistance output when participants contribute more and vice versa , thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

PubMed Central

Liu, Quan; Liu, Aiming; Meng, Wei; Ai, Qingsong; Xie, Sheng Q.

2017-01-01

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient’s active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant’s assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy. PMID:29255412

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

PubMed Central

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

2014-01-01

Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure. PMID:25267824

Settlement Networks in Polish Spatial Development Regional Plans

NASA Astrophysics Data System (ADS)

Sołtys, Jacek

2017-10-01

In 1999, ten years after the great political changes in Poland, 16 self-governed regions (in Polish: voivodeship) were created. According to Polish law, voivodeship spatial development plans, or regional plans in short, determine basic elements of the settlement network. No detailed regulations indicate the specific elements of the settlement network or what features of these elements should be determined. For this reason, centres as elements of the settlement network are variously named in different regions and take the form of various models. The purposes of the research described in this article are: (1) recognition and systematization of settlement network models determined in regional plans; and (2) assessment of the readability of determination in planning and its usefulness in the practice of regional policy. Six models of settlement networks in regional plans have been identified and classified into types and sub-types. Names of specific levels of centres indicate that they were classified according to two criteria: (1) level of services, which concerns only 5 voivodships; and (2) importance in development, which concerns the 11 other voivodships. The hierarchical model referring to the importance of development is less understandable than the one related to services. In the text of most plans, centres of services and centres of development are treated independently from their names. In some plans the functional types of towns and cities are indicated. In some voivodships, specifications in the plan text are too general and seem to be rather useless in the practice of regional policy. The author suggests that regional plans should determine two kinds of centres: hierarchical service centres and non-hierarchical centres of development. These centres should be further distinguished according to: (1) their role in the activation of surroundings; (2) their level of development and the necessity of action for their development; and (3) the types of actions indicated in the regional policy.

Auditing of SNOMED CT's Hierarchical Structure using the National Drug File - Reference Terminology.

PubMed

Zakharchenko, Aleksandr; Geller, James

2015-01-01

With the ongoing development in the field of Medical Informatics, the availability of cross-references and the consistency of coverage between terminologies become critical requirements for clinical decision support. In this paper, we examine the possibility of developing a framework that highlights and exposes hierarchical incompatibilities between different medical terminologies in order to facilitate the process of achieving a sufficient level of consistency between terminologies. For the purpose of this research, we are working with the Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT) and the National Drug File--Reference Terminology (NDF-RT)--a clinical terminology focused on drugs. For discovery of inconsistencies we built an automated tool.

Developing PFC representations using reinforcement learning

PubMed Central

Reynolds, Jeremy R.; O'Reilly, Randall C.

2009-01-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically (Fuster, 1990, Koechlin, Ody, & Kouneiher, 2003, & Miller, Galanter, & Pribram, 1960) However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data. PMID:19591977

High-Level Heteroatom Doped Two-Dimensional Carbon Architectures for Highly Efficient Lithium-Ion Storage.

PubMed

Wang, Zhijie; Wang, Yanyan; Wang, Wenhui; Yu, Xiaoliang; Lv, Wei; Xiang, Bin; He, Yan-Bing

2018-01-01

In this work, high-level heteroatom doped two-dimensional hierarchical carbon architectures (H-2D-HCA) are developed for highly efficient Li-ion storage applications. The achieved H-2D-HCA possesses a hierarchical 2D morphology consisting of tiny carbon nanosheets vertically grown on carbon nanoplates and containing a hierarchical porosity with multiscale pore size. More importantly, the H-2D-HCA shows abundant heteroatom functionality, with sulfur (S) doping of 0.9% and nitrogen (N) doping of as high as 15.5%, in which the electrochemically active N accounts for 84% of total N heteroatoms. In addition, the H-2D-HCA also has an expanded interlayer distance of 0.368 nm. When used as lithium-ion battery anodes, it shows excellent Li-ion storage performance. Even at a high current density of 5 A g -1 , it still delivers a high discharge capacity of 329 mA h g -1 after 1,000 cycles. First principle calculations verifies that such unique microstructure characteristics and high-level heteroatom doping nature can enhance Li adsorption stability, electronic conductivity and Li diffusion mobility of carbon nanomaterials. Therefore, the H-2D-HCA could be promising candidates for next-generation LIB anodes.

High-Level Heteroatom Doped Two-Dimensional Carbon Architectures for Highly Efficient Lithium-Ion Storage

NASA Astrophysics Data System (ADS)

Wang, Zhijie; Wang, Yanyan; Wang, Wenhui; Yu, Xiaoliang; Lv, Wei; Xiang, Bin; He, Yan-Bing

2018-04-01

In this work, high-level heteroatom doped two-dimensional hierarchical carbon architectures (H-2D-HCA) are developed for highly efficient Li-ion storage applications. The achieved H-2D-HCA possesses a hierarchical 2D morphology consisting of tiny carbon nanosheets vertically grown on carbon nanoplates and containing a hierarchical porosity with multiscale pore size. More importantly, the H-2D-HCA shows abundant heteroatom functionality, with sulfur (S) doping of 0.9 % and nitrogen (N) doping of as high as 15.5 %, in which the electrochemically active N accounts for 84 % of total N heteroatoms. In addition, the H-2D-HCA also has an expanded interlayer distance of 0.368 nm. When used as lithium-ion battery anodes, it shows excellent Li-ion storage performance. Even at a high current density of 5 A g-1, it still delivered a high discharge capacity of 329 mA h g-1 after 1000 cycles. First principle calculations verified that such unique microstructure characteristics and high-level heteroatom doping nature can enhance Li adsorption stability, electronic conductivity and Li diffusion mobility of carbon nanomaterials. Therefore, the H-2D-HCA could be promising candidates for next-generation LIB anodes.

Three-level multilevel growth models for nested change data: a guide for group treatment researchers.

PubMed

Tasca, Giorgio A; Illing, Vanessa; Joyce, Anthony S; Ogrodniczuk, John S

2009-07-01

Researchers have known for years about the negative impact on Type I error rates caused by dependencies in hierarchically nested and longitudinal data. Despite this, group treatment researchers do not consistently use methods such as multilevel models (MLMs) to assess dependence and appropriately analyse their nested data. The goals of this study are to review some of the study design issues with regard to hierarchically nested and longitudinal data, discuss MLMs for assessing and handling dependence in data, and present a guide for developing a three-level growth MLM that is appropriate for group treatment data, design, and research questions. The authors present an example from group treatment research to illustrate these issues and methods.

Spatio-temporal hierarchical modeling of rates and variability of Holocene sea-level changes in the western North Atlantic and the Caribbean

NASA Astrophysics Data System (ADS)

Ashe, E.; Kopp, R. E.; Khan, N.; Horton, B.; Engelhart, S. E.

2016-12-01

Sea level varies over of both space and time. Prior to the instrumental period, the sea-level record depends upon geological reconstructions that contain vertical and temporal uncertainty. Spatio-temporal statistical models enable the interpretation of RSL and rates of change as well as the reconstruction of the entire sea-level field from such noisy data. Hierarchical models explicitly distinguish between a process level, which characterizes the spatio-temporal field, and a data level, by which sparse proxy data and its noise is recorded. A hyperparameter level depicts prior expectations about the structure of variability in the spatio-temporal field. Spatio-temporal hierarchical models are amenable to several analysis approaches, with tradeoffs regarding computational efficiency and comprehensiveness of uncertainty characterization. A fully-Bayesian hierarchical model (BHM), which places prior probability distributions upon the hyperparameters, is more computationally intensive than an empirical hierarchical model (EHM), which uses point estimates of hyperparameters, derived from the data [1]. Here, we assess the sensitivity of posterior estimates of relative sea level (RSL) and rates to different statistical approaches by varying prior assumptions about the spatial and temporal structure of sea-level variability and applying multiple analytical approaches to Holocene sea-level proxies along the Atlantic coast of North American and the Caribbean [2]. References: 1. N Cressie, Wikle CK (2011) Statistics for spatio-temporal data (John Wiley & Sons). 2. Kahn N et al. (2016). Quaternary Science Reviews (in revision).

Synthesizing trait correlations and functional relationships across multiple scales: A Hierarchical Bayes approach

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Cowdery, E.; Dietze, M.

2016-12-01

Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.

Aligning interprofessional education collaborative sub-competencies to a progression of learning.

PubMed

Patel Gunaldo, Tina; Brisolara, Kari Fitzmorris; Davis, Alison H; Moore, Robert

2017-05-01

In the United States, the Interprofessional Education Collaborative (IPEC) developed four core competencies for interprofessional collaborative practice. Even though the IPEC competencies and respective sub-competencies were not created in a hierarchal manner, one might reflect upon a logical progression of learning as well as learners accruing skills allowing them to master one level of learning and building on the aggregate of skills before advancing to the next level. The Louisiana State University Health-New Orleans Center for Interprofessional Education and Collaborative Practice (CIPECP) determined the need to align the sub-competencies with the level of behavioural expectations in order to simplify the process of developing an interprofessional education experience targeted to specific learning levels. In order to determine the most effective alignment, CIPECP discussions revolved around current programmatic expectations across the institution. Faculty recognised the need to align sub-competencies with student learning objectives. Simultaneously, a progression of learning existing within each of the four IPEC domains was noted. Ultimately, the faculty and staff team agreed upon categorising the sub-competencies in a hierarchical manner for the four domains into either a "basic, intermediate, or advanced" level of competency.

Measuring Stages of Growth: A Psychometric Model of Hierarchical Development. Occasional Paper No. 19.

ERIC Educational Resources Information Center

Wilson, Mark

A psychometric model called Saltus, which represents the qualitative aspects of hierarchical development in a form applicable to additive measurement, was applied. Both Piaget's theory of cognitive development and Gagne's theory of learning hierarchies were used to establish the common features of hierarchical development: (1) gappiness--the…

Task switching in a hierarchical task structure: evidence for the fragility of the task repetition benefit.

PubMed

Lien, Mei-Ching; Ruthruff, Eric

2004-05-01

This study examined how task switching is affected by hierarchical task organization. Traditional task-switching studies, which use a constant temporal and spatial distance between each task element (defined as a stimulus requiring a response), promote a flat task structure. Using this approach, Experiment 1 revealed a large switch cost of 238 ms. In Experiments 2-5, adjacent task elements were grouped temporally and/or spatially (forming an ensemble) to create a hierarchical task organization. Results indicate that the effect of switching at the ensemble level dominated the effect of switching at the element level. Experiments 6 and 7, using an ensemble of 3 task elements, revealed that the element-level switch cost was virtually absent between ensembles but was large within an ensemble. The authors conclude that the element-level task repetition benefit is fragile and can be eliminated in a hierarchical task organization.

Task switching in a hierarchical task structure: evidence for the fragility of the task repetition benefit

NASA Technical Reports Server (NTRS)

Lien, Mei-Ching; Ruthruff, Eric

2004-01-01

This study examined how task switching is affected by hierarchical task organization. Traditional task-switching studies, which use a constant temporal and spatial distance between each task element (defined as a stimulus requiring a response), promote a flat task structure. Using this approach, Experiment 1 revealed a large switch cost of 238 ms. In Experiments 2-5, adjacent task elements were grouped temporally and/or spatially (forming an ensemble) to create a hierarchical task organization. Results indicate that the effect of switching at the ensemble level dominated the effect of switching at the element level. Experiments 6 and 7, using an ensemble of 3 task elements, revealed that the element-level switch cost was virtually absent between ensembles but was large within an ensemble. The authors conclude that the element-level task repetition benefit is fragile and can be eliminated in a hierarchical task organization.

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

The Role of Reinforcement Sensitivity in the Development of Childhood Personality

ERIC Educational Resources Information Center

Slobodskaya, Helena R.; Kuznetsova, Valeriya B.

2013-01-01

The study examined the contribution of reinforcement sensitivity to childhood personality at three levels of the hierarchical structure, mid-level traits, the Big Five and two higher-order factors, and the moderating role of sex and age in a sample of 3-18-year-olds. The canonical correlation analyses indicated that reinforcement sensitivity and…

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics

ERIC Educational Resources Information Center

Chen, Chi-hsin; Zhang, Yayun; Yu, Chen

2018-01-01

Objects in the world usually have names at different hierarchical levels (e.g., "beagle," "dog," "animal"). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use…

Multi-scale chromatin state annotation using a hierarchical hidden Markov model

NASA Astrophysics Data System (ADS)

Marco, Eugenio; Meuleman, Wouter; Huang, Jialiang; Glass, Kimberly; Pinello, Luca; Wang, Jianrong; Kellis, Manolis; Yuan, Guo-Cheng

2017-04-01

Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.

Measuring Teacher Effectiveness through Hierarchical Linear Models: Exploring Predictors of Student Achievement and Truancy

ERIC Educational Resources Information Center

Subedi, Bidya Raj; Reese, Nancy; Powell, Randy

2015-01-01

This study explored significant predictors of student's Grade Point Average (GPA) and truancy (days absent), and also determined teacher effectiveness based on proportion of variance explained at teacher level model. We employed a two-level hierarchical linear model (HLM) with student and teacher data at level-1 and level-2 models, respectively.…

Hierarchical cortical transcriptome disorganization in autism.

PubMed

Lombardo, Michael V; Courchesne, Eric; Lewis, Nathan E; Pramparo, Tiziano

2017-01-01

Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation.

Models and Methods of Aggregating Linguistic Information in Multi-criteria Hierarchical Quality Assessment Systems

NASA Astrophysics Data System (ADS)

Azarnova, T. V.; Titova, I. A.; Barkalov, S. A.

2018-03-01

The article presents an algorithm for obtaining an integral assessment of the quality of an organization from the perspective of customers, based on the method of aggregating linguistic information on a multilevel hierarchical system of quality assessment. The algorithm is of a constructive nature, it provides not only the possibility of obtaining an integral evaluation, but also the development of a quality improvement strategy based on the method of linguistic decomposition, which forms the minimum set of areas of work with clients whose quality change will allow obtaining the required level of integrated quality assessment.

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…

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

NASA Technical Reports Server (NTRS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.

2003-01-01

ANTS (Autonomous Nano-Technology Swarm), a large (1000 member) swarm of nano to picoclass (10 to 1 kg) totally autonomous spacecraft, are being developed as a NASA advanced mission concept. ANTS, based on a hierarchical insect social order, use an evolvable, self-similar, hierarchical neural system in which individual spacecraft represent the highest level nodes. ANTS uses swarm intelligence attained through collective, cooperative interactions of the nodes at all levels of the system. At the highest levels this can take the form of cooperative, collective behavior among the individual spacecraft in a very large constellation. The ANTS neural architecture is designed for totally autonomous operation of complex systems including spacecraft constellations. The ANTS (Autonomous Nano Technology Swarm) concept has a number of possible applications. A version of ANTS designed for surveying and determining the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

Principles Supporting the Perceptional Teaching of Physics: A ``Practical Teaching Philosophy''

NASA Astrophysics Data System (ADS)

Kurki-Suonio, Kaarle

2011-03-01

This article sketches a framework of ideas developed in the context of decades of physics teacher-education that was entitled the "perceptional approach". Individual learning and the scientific enterprise are interpreted as different manifestations of the same process aimed at understanding the natural and social worlds. The process is understood to possess the basic nature of perception, where empirical meanings are first born and then conceptualised. The accumulation of perceived gestalts in the "structure of the mind" leads to structural perception and the generation of conceptual hierarchies, which form a general principle for the expansion of our understanding. The process undergoes hierarchical development from early sensory perception to individual learning and finally to science. The process is discussed in terms of a three-process dynamic. Scientific and technological processes are driven by the interaction of the mind and nature. They are embedded in the social process due to the interaction of individual minds. These sub-processes are defined by their aims: The scientific process affects the mind and aims at understanding; the technological process affects nature and aims at human well-being; and the social process aims at mutual agreement and cooperation. In hierarchical development the interaction of nature and the mind gets structured into a "methodical cycle" by procedures involving conscious activities. Its intuitive nature is preserved due to subordination of the procedures to empirical meanings. In physics, two dimensions of hierarchical development are distinguished: Unification development gives rise to a generalisation hierarchy of concepts; Quantification development transfers the empirical meanings to quantities, laws and theories representing successive hierarchical levels of quantitative concepts. Consequences for physics teaching are discussed in principle, and in the light of examples and experiences from physics teacher education.

Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema.

PubMed

Lassere, Marissa N; Johnson, Kent R; Boers, Maarten; Tugwell, Peter; Brooks, Peter; Simon, Lee; Strand, Vibeke; Conaghan, Philip G; Ostergaard, Mikkel; Maksymowych, Walter P; Landewe, Robert; Bresnihan, Barry; Tak, Paul-Peter; Wakefield, Richard; Mease, Philip; Bingham, Clifton O; Hughes, Michael; Altman, Doug; Buyse, Marc; Galbraith, Sally; Wells, George

2007-03-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Our objective was to review the literature on biomarkers and surrogates to develop a hierarchical schema that systematically evaluates and ranks the surrogacy status of biomarkers and surrogates; and to obtain feedback from stakeholders. After a systematic search of Medline and Embase on biomarkers, surrogate (outcomes, endpoints, markers, indicators), intermediate endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation level of evidence schema that evaluates biomarkers along 4 domains: Target, Study Design, Statistical Strength, and Penalties. Scores derived from 3 domains the Target that the marker is being substituted for, the Design of the (best) evidence, and the Statistical strength are additive. Penalties are then applied if there is serious counterevidence. A total score (0 to 15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. It was proposed that the term "surrogate" be restricted to markers attaining Levels 1 or 2 only. Most stakeholders agreed that this operationalization of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery, development, and approval.

Self-cleaning poly(dimethylsiloxane) film with functional micro/nano hierarchical structures.

PubMed

Zhang, Xiao-Sheng; Zhu, Fu-Yun; Han, Meng-Di; Sun, Xu-Ming; Peng, Xu-Hua; Zhang, Hai-Xia

2013-08-27

This paper reports a novel single-step wafer-level fabrication of superhydrophobic micro/nano dual-scale (MNDS) poly(dimethylsiloxane) (PDMS) films. The MNDS PDMS films were replicated directly from an ultralow-surface-energy silicon substrate at high temperature without any surfactant coating, achieving high precision. An improved deep reactive ion etching (DRIE) process with enhanced passivation steps was proposed to easily realize the ultralow-surface-energy MNDS silicon substrate and also utilized as a post-treatment process to strengthen the hydrophobicity of the MNDS PDMS film. The chemical modification of this enhanced passivation step to the surface energy has been studied by density functional theory, which is also the first investigation of C4F8 plasma treatment at molecular level by using first-principle calculations. From the results of a systematic study on the effect of key process parameters (i.e., baking temperature and time) on PDMS replication, insight into the interaction of hierarchical multiscale structures of polymeric materials during the micro/nano integrated fabrication process is experimentally obtained for the first time. Finite element simulation has been employed to illustrate this new phenomenon. Additionally, hierarchical PDMS pyramid arrays and V-shaped grooves have been developed and are intended for applications as functional structures for a light-absorption coating layer and directional transport of liquid droplets, respectively. This stable, self-cleaning PDMS film with functional micro/nano hierarchical structures, which is fabricated through a wafer-level single-step fabrication process using a reusable silicon mold, shows attractive potential for future applications in micro/nanodevices, especially in micro/nanofluidics.

Teacher-Child Relationship Quality and Academic Achievement in Elementary School: Does Gender Matter?

ERIC Educational Resources Information Center

McCormick, Meghan P.; O'Connor, Erin E.

2015-01-01

Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (N = 1,364) and 2-level hierarchical linear models with site fixed effects, we examined between- and within-child associations between teacher-child relationship closeness and conflict and standardized measures of children's…

Quantifying allometric model uncertainty for plot-level live tree biomass stocks with a data-driven, hierarchical framework

Treesearch

Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall

2016-01-01

Accurate uncertainty assessments of plot-level live tree biomass stocks are an important precursor to estimating uncertainty in annual national greenhouse gas inventories (NGHGIs) developed from forest inventory data. However, current approaches employed within the United States’ NGHGI do not specifically incorporate methods to address error in tree-scale biomass...

A neural model of hierarchical reinforcement learning

PubMed Central

Rasmussen, Daniel; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain’s general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model’s behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions. PMID:28683111

Hierarchical Regional Disparities and Potential Sector Identification Using Modified Agglomerative Clustering

NASA Astrophysics Data System (ADS)

Munandar, T. A.; Azhari; Mushdholifah, A.; Arsyad, L.

2017-03-01

Disparities in regional development methods are commonly identified using the Klassen Typology and Location Quotient. Both methods typically use the data on the gross regional domestic product (GRDP) sectors of a particular region. The Klassen approach can identify regional disparities by classifying the GRDP sector data into four classes, namely Quadrants I, II, III, and IV. Each quadrant indicates a certain level of regional disparities based on the GRDP sector value of the said region. Meanwhile, the Location Quotient (LQ) is usually used to identify potential sectors in a particular region so as to determine which sectors are potential and which ones are not potential. LQ classifies each sector into three classes namely, the basic sector, the non-basic sector with a competitive advantage, and the non-basic sector which can only meet its own necessities. Both Klassen Typology and LQ are unable to visualize the relationship of achievements in the development clearly of each region and sector. This research aimed to develop a new approach to the identification of disparities in regional development in the form of hierarchical clustering. The method of Hierarchical Agglomerative Clustering (HAC) was employed as the basis of the hierarchical clustering model for identifying disparities in regional development. Modifications were made to HAC using the Klassen Typology and LQ. Then, HAC which had been modified using the Klassen Typology was called MHACK while HAC which had been modified using LQ was called MACLoQ. Both algorithms can be used to identify regional disparities (MHACK) and potential sectors (MACLoQ), respectively, in the form of hierarchical clusters. Based on the MHACK in 31 regencies in Central Java Province, it is identified that 3 regencies (Demak, Jepara, and Magelang City) fall into the category of developed and rapidly-growing regions, while the other 28 regencies fall into the category of developed but depressed regions. Results of the MACLoQ implementation suggest that there is only 1 regency which falls into the basic-sector category (Banyumas), while the other regencies fall into the non-basic non-competitive sector category.

High-Level Heteroatom Doped Two-Dimensional Carbon Architectures for Highly Efficient Lithium-Ion Storage

PubMed Central

Wang, Zhijie; Wang, Yanyan; Wang, Wenhui; Yu, Xiaoliang; Lv, Wei; Xiang, Bin; He, Yan-Bing

2018-01-01

In this work, high-level heteroatom doped two-dimensional hierarchical carbon architectures (H-2D-HCA) are developed for highly efficient Li-ion storage applications. The achieved H-2D-HCA possesses a hierarchical 2D morphology consisting of tiny carbon nanosheets vertically grown on carbon nanoplates and containing a hierarchical porosity with multiscale pore size. More importantly, the H-2D-HCA shows abundant heteroatom functionality, with sulfur (S) doping of 0.9% and nitrogen (N) doping of as high as 15.5%, in which the electrochemically active N accounts for 84% of total N heteroatoms. In addition, the H-2D-HCA also has an expanded interlayer distance of 0.368 nm. When used as lithium-ion battery anodes, it shows excellent Li-ion storage performance. Even at a high current density of 5 A g−1, it still delivers a high discharge capacity of 329 mA h g−1 after 1,000 cycles. First principle calculations verifies that such unique microstructure characteristics and high-level heteroatom doping nature can enhance Li adsorption stability, electronic conductivity and Li diffusion mobility of carbon nanomaterials. Therefore, the H-2D-HCA could be promising candidates for next-generation LIB anodes. PMID:29686985

The forest, the trees, and the leaves: Differences of processing across development.

PubMed

Krakowski, Claire-Sara; Poirel, Nicolas; Vidal, Julie; Roëll, Margot; Pineau, Arlette; Borst, Grégoire; Houdé, Olivier

2016-08-01

To act and think, children and adults are continually required to ignore irrelevant visual information to focus on task-relevant items. As real-world visual information is organized into structures, we designed a feature visual search task containing 3-level hierarchical stimuli (i.e., local shapes that constituted intermediate shapes that formed the global figure) that was presented to 112 participants aged 5, 6, 9, and 21 years old. This task allowed us to explore (a) which level is perceptively the most salient at each age (i.e., the fastest detected level) and (b) what kind of attentional processing occurs for each level across development (i.e., efficient processing: detection time does not increase with the number of stimuli on the display; less efficient processing: detection time increases linearly with the growing number of distractors). Results showed that the global level was the most salient at 5 years of age, whereas the global and intermediate levels were both salient for 9-year-olds and adults. Interestingly, at 6 years of age, the intermediate level was the most salient level. Second, all participants showed an efficient processing of both intermediate and global levels of hierarchical stimuli, and a less efficient processing of the local level, suggesting a local disadvantage rather than a global advantage in visual search. The cognitive cost for selecting the local target was higher for 5- and 6-year-old children compared to 9-year-old children and adults. These results are discussed with regards to the development of executive control. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Perception of hierarchical boundaries in music and its modulation by expertise.

PubMed

Zhang, Jingjing; Jiang, Cunmei; Zhou, Linshu; Yang, Yufang

2016-10-01

Hierarchical structure with units of different timescales is a key feature of music. For the perception of such structures, the detection of each boundary is crucial. Here, using electroencephalography (EEG), we explore the perception of hierarchical boundaries in music, and test whether musical expertise modifies such processing. Musicians and non-musicians were presented with musical excerpts containing boundaries at three hierarchical levels, including section, phrase and period boundaries. Non-boundary was chosen as a baseline condition. Recordings from musicians showed CPS (closure positive shift) was evoked at all the three boundaries, and their amplitude increased as the hierarchical level became higher, which suggest that musicians could represent music events at different timescales in a hierarchical way. For non-musicians, the CPS was only elicited at the period boundary and undistinguishable negativities were induced at all the three boundaries. The results indicate that a different and less clear way was used by non-musicians in boundary perception. Our findings reveal, for the first time, an ERP correlate of perceiving hierarchical boundaries in music, and show that the phrasing ability could be enhanced by musical expertise. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biomimetic cellular metals-using hierarchical structuring for energy absorption.

PubMed

Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

2016-07-19

Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form-structure-function relationship of the biological concept generators as well as the bio-inspired metal foams was achieved, on deeper hierarchical levels and overarching different levels.

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…

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Hierarchical Structure of Articular Bone-Cartilage Interface and Its Potential Application for Osteochondral Tissue Engineering

NASA Astrophysics Data System (ADS)

Bian, Weiguo; Qin, Lian; Li, Dichen; Wang, Jin; Jin, Zhongmin

2010-09-01

The artificial biodegradable osteochondral construct is one of mostly promising lifetime substitute in the joint replacement. And the complex hierarchical structure of natural joint is important in developing the osteochondral construct. However, the architecture features of the interface between cartilage and bone, in particular those at the micro-and nano-structural level, remain poorly understood. This paper investigates these structural data of the cartilage-bone interface by micro computerized tomography (μCT) and Scanning Electron Microscope (SEM). The result of μCT shows that important bone parameters and the density of articular cartilage are all related to the position in the hierarchical structure. The conjunctions of bone and cartilage were defined by SEM. All of the study results would be useful for the design of osteochondral construct further manufactured by nano-tech. A three-dimensional model with gradient porous structure is constructed in the environment of Pro/ENGINEERING software.

Nanomechanical strength mechanisms of hierarchical biological materials and tissues.

PubMed

Buehler, Markus J; Ackbarow, Theodor

2008-12-01

Biological protein materials (BPMs), intriguing hierarchical structures formed by assembly of chemical building blocks, are crucial for critical functions of life. The structural details of BPMs are fascinating: They represent a combination of universally found motifs such as alpha-helices or beta-sheets with highly adapted protein structures such as cytoskeletal networks or spider silk nanocomposites. BPMs combine properties like strength and robustness, self-healing ability, adaptability, changeability, evolvability and others into multi-functional materials at a level unmatched in synthetic materials. The ability to achieve these properties depends critically on the particular traits of these materials, first and foremost their hierarchical architecture and seamless integration of material and structure, from nano to macro. Here, we provide a brief review of this field and outline new research directions, along with a review of recent research results in the development of structure-property relationships of biological protein materials exemplified in a study of vimentin intermediate filaments.

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation.

PubMed

Chen, Cong; Zhang, Guohui; Liu, Xiaoyue Cathy; Ci, Yusheng; Huang, Helai; Ma, Jianming; Chen, Yanyan; Guan, Hongzhi

2016-12-01

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Working memory, perceptual priming, and the perception of hierarchical forms: opposite effects of priming and working memory without memory refreshing.

PubMed

Kim, Jeong-Im; Humphreys, Glyn W

2010-08-01

Previous research has shown that stimuli held in working memory (WM) can influence spatial attention. Using Navon stimuli, we explored whether and how items in WM affect the perception of visual targets at local and global levels in compound letters. Participants looked for a target letter presented at a local or global level while holding a regular block letter as a memory item. An effect of holding the target's identity in WM was found. When memory items and targets were the same, performance was better than in a neutral condition when the memory item did not appear in the hierarchical letter (a benefit from valid cuing). When the memory item matched the distractor in the hierarchical stimulus, performance was worse than in the neutral baseline (a cost on invalid trials). These effects were greatest when the WM cue matched the global level of the hierarchical stimulus, suggesting that WM biases attention to the global level of form. Interestingly, in a no-memory priming condition, target perception was faster in the invalid condition than in the neutral baseline, reversing the effect in the WM condition. A further control experiment ruled out the effects of WM being due to participants' refreshing their memory from the hierarchical stimulus display. The data show that information in WM biases the selection of hierarchical forms, whereas priming does not. Priming alters the perceptual processing of repeated stimuli without biasing attention.

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries

PubMed Central

Boehler, Christian E. H.; Lord, Joanne

2016-01-01

Background. Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. Objectives. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Methods. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. Results. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%−19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Conclusions. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. PMID:25878194

A bioscaffolding strategy for hierarchical zeolites with a nanotube-trimodal network.

PubMed

Li, Guannan; Huang, Haibo; Yu, Bowen; Wang, Yun; Tao, Jiawei; Wei, Yingxu; Li, Shougui; Liu, Zhongmin; Xu, Yan; Xu, Ruren

2016-02-01

Hierarchical zeolite monoliths with multimodal porosity are of paramount importance as they open up new horizons for advanced applications. So far, hierarchical zeolites based on nanotube scaffolds have never been reported. Inspired by the organization of biominerals, we have developed a novel precursor scaffolding-solid phase crystallization strategy for hierarchical zeolites with a unique nanotube scaffolding architecture and nanotube-trimodal network, where biomolecular self-assembly (BSA) provides a scaffolding blueprint. By vapor-treating Sil-1 seeded precursor scaffolds, zeolite MFI nanotube scaffolds are self-generated, during which evolution phenomena such as segmented voids and solid bridges are observed, in agreement with the Kirkendall effect in a solid-phase crystallization system. The nanotube walls are made of intergrown single crystals rendering good mechanical stability. The inner diameter of the nanotube is tunable between 30 and 90 nm by varying the thickness of the precursor layers. Macropores enclosed by cross-linked nanotubes can be modulated by the choice of BSA. Narrow mesopores are formed by intergrown nanocrystals. Hierarchical ZSM-5 monoliths with nanotube (90 nm), micropore (0.55 nm), mesopore (2 nm) and macropore (700 nm) exhibit superior catalytic performance in the methanol-to-hydrocarbon (MTH) conversion compared to conventional ZSM-5. BSA remains intact after crystallization, allowing a higher level of organization and functionalization of the zeolite nanotube scaffolds. The current work may afford a versatile strategy for hierarchical zeolite monoliths with nanotube scaffolding architectures and a nanotube-multimodal network leading to self-supporting and active zeolite catalysts, and for applications beyond.

Hierarchical Recursive Organization and the Free Energy Principle: From Biological Self-Organization to the Psychoanalytic Mind

PubMed Central

Connolly, Patrick; van Deventer, Vasi

2017-01-01

The present paper argues that a systems theory epistemology (and particularly the notion of hierarchical recursive organization) provides the critical theoretical context within which the significance of Friston's (2010a) Free Energy Principle (FEP) for both evolution and psychoanalysis is best understood. Within this perspective, the FEP occupies a particular level of the hierarchical organization of the organism, which is the level of biological self-organization. This form of biological self-organization is in turn understood as foundational and pervasive to the higher levels of organization of the human organism that are of interest to both neuroscience as well as psychoanalysis. Consequently, central psychoanalytic claims should be restated, in order to be located in their proper place within a hierarchical recursive organization of the (situated) organism. In light of the FEP the realization of the psychoanalytic mind by the brain should be seen in terms of the evolution of different levels of systematic organization where the concepts of psychoanalysis describe a level of hierarchical recursive organization superordinate to that of biological self-organization and the FEP. The implication of this formulation is that while “psychoanalytic” mental processes are fundamentally subject to the FEP, they nonetheless also add their own principles of process over and above that of the FEP. A model found in Grobbelaar (1989) offers a recursive bottom-up description of the self-organization of the psychoanalytic ego as dependent on the organization of language (and affect), which is itself founded upon the tendency toward autopoiesis (self-making) within the organism, which is in turn described as formally similar to the FEP. Meaningful consilience between Grobbelaar's model and the hierarchical recursive description available in Friston's (2010a) theory is described. The paper concludes that the valuable contribution of the FEP to psychoanalysis underscores the necessity of reengagement with the core concepts of psychoanalytic theory, and the usefulness that a systems theory epistemology—particularly hierarchical recursive description—can have for this goal. PMID:29038652

Hierarchical Recursive Organization and the Free Energy Principle: From Biological Self-Organization to the Psychoanalytic Mind.

PubMed

Connolly, Patrick; van Deventer, Vasi

2017-01-01

The present paper argues that a systems theory epistemology (and particularly the notion of hierarchical recursive organization) provides the critical theoretical context within which the significance of Friston's (2010a) Free Energy Principle (FEP) for both evolution and psychoanalysis is best understood. Within this perspective, the FEP occupies a particular level of the hierarchical organization of the organism, which is the level of biological self-organization. This form of biological self-organization is in turn understood as foundational and pervasive to the higher levels of organization of the human organism that are of interest to both neuroscience as well as psychoanalysis. Consequently, central psychoanalytic claims should be restated, in order to be located in their proper place within a hierarchical recursive organization of the (situated) organism. In light of the FEP the realization of the psychoanalytic mind by the brain should be seen in terms of the evolution of different levels of systematic organization where the concepts of psychoanalysis describe a level of hierarchical recursive organization superordinate to that of biological self-organization and the FEP. The implication of this formulation is that while "psychoanalytic" mental processes are fundamentally subject to the FEP, they nonetheless also add their own principles of process over and above that of the FEP. A model found in Grobbelaar (1989) offers a recursive bottom-up description of the self-organization of the psychoanalytic ego as dependent on the organization of language (and affect), which is itself founded upon the tendency toward autopoiesis (self-making) within the organism, which is in turn described as formally similar to the FEP. Meaningful consilience between Grobbelaar's model and the hierarchical recursive description available in Friston's (2010a) theory is described. The paper concludes that the valuable contribution of the FEP to psychoanalysis underscores the necessity of reengagement with the core concepts of psychoanalytic theory, and the usefulness that a systems theory epistemology-particularly hierarchical recursive description-can have for this goal.

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…

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

PubMed

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

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

Hierarchical and hybrid energy storage devices in data centers: Architecture, control and provisioning.

PubMed

Sun, Mengshu; Xue, Yuankun; Bogdan, Paul; Tang, Jian; Wang, Yanzhi; Lin, Xue

2018-01-01

Recently, a new approach has been introduced that leverages and over-provisions energy storage devices (ESDs) in data centers for performing power capping and facilitating capex/opex reductions, without performance overhead. To fully realize the potential benefits of the hierarchical ESD structure, we propose a comprehensive design, control, and provisioning framework including (i) designing power delivery architecture supporting hierarchical ESD structure and hybrid ESDs for some levels, as well as (ii) control and provisioning of the hierarchical ESD structure including run-time ESD charging/discharging control and design-time determination of ESD types, homogeneous/hybrid options, ESD provisioning at each level. Experiments have been conducted using real Google data center workloads based on realistic data center specifications.

Hierarchical and hybrid energy storage devices in data centers: Architecture, control and provisioning

PubMed Central

Xue, Yuankun; Bogdan, Paul; Tang, Jian; Wang, Yanzhi; Lin, Xue

2018-01-01

Recently, a new approach has been introduced that leverages and over-provisions energy storage devices (ESDs) in data centers for performing power capping and facilitating capex/opex reductions, without performance overhead. To fully realize the potential benefits of the hierarchical ESD structure, we propose a comprehensive design, control, and provisioning framework including (i) designing power delivery architecture supporting hierarchical ESD structure and hybrid ESDs for some levels, as well as (ii) control and provisioning of the hierarchical ESD structure including run-time ESD charging/discharging control and design-time determination of ESD types, homogeneous/hybrid options, ESD provisioning at each level. Experiments have been conducted using real Google data center workloads based on realistic data center specifications. PMID:29351553

The Evolution of Educational Objectives: Bloom's Taxonomy and beyond

ERIC Educational Resources Information Center

Fallahi, Carolyn R.; LaMonaca, Frank H., Jr.

2009-01-01

It is crucial for teachers to communicate effectively about educational objectives to students, colleagues, and others in education. In 1956, Bloom developed a cognitive learning taxonomy to enhance communication between college examiners. The Bloom taxonomy consists of 6 hierarchical levels of learning (knowledge, comprehension, application,…

Flexible Visual Processing in Young Adults with Autism: The Effects of Implicit Learning on a Global-Local Task

ERIC Educational Resources Information Center

Hayward, Dana A.; Shore, David I.; Ristic, Jelena; Kovshoff, Hanna; Iarocci, Grace; Mottron, Laurent; Burack, Jacob A.

2012-01-01

We utilized a hierarchical figures task to determine the default level of perceptual processing and the flexibility of visual processing in a group of high-functioning young adults with autism (n = 12) and a typically developing young adults, matched by chronological age and IQ (n = 12). In one task, participants attended to one level of the…

The Development of Object Categorization in Young Children: Hierarchical Inclusiveness, Age, Perceptual Attribute, and Group versus Individual Analyses

ERIC Educational Resources Information Center

Bornstein, Marc H.; Arterberry, Martha E.

2010-01-01

Multiple levels of category inclusiveness in 4 object domains (animals, vehicles, fruit, and furniture) were examined using a sequential touching procedure and assessed in both individual and group analyses in eighty 12-, 18-, 24-, and 30-month-olds. The roles of stimulus discriminability and child motor development, fatigue, and actions were also…

The Synthesis Map Is a Multidimensional Educational Tool That Provides Insight into Students' Mental Models and Promotes Students' Synthetic Knowledge Generation

ERIC Educational Resources Information Center

Ortega, Ryan A.; Brame, Cynthia J.

2015-01-01

Concept mapping was developed as a method of displaying and organizing hierarchical knowledge structures. Using the new, multidimensional presentation software Prezi, we have developed a new teaching technique designed to engage higher-level skills in the cognitive domain. This tool, synthesis mapping, is a natural evolution of concept mapping,…

Hierarchical Levels of Abilities That Constitute Fraction Understanding at Elementary School

ERIC Educational Resources Information Center

Nicolaou, Aristoklis A.; Pitta-Pantazi, Demetra

2016-01-01

This article examines whether the 7 abilities found in a previous study carried out by the authors to constitute fraction understanding of sixth grade elementary school students determine hierarchical levels of fraction understanding. The 7 abilities were as follows: (a) fraction recognition, (b) definitions and mathematical explanations for…

Hierarchical Forms Processing in Adults and Children

ERIC Educational Resources Information Center

Harrison, Tamara B.; Stiles, Joan

2009-01-01

Two experiments examined child and adult processing of hierarchical stimuli composed of geometric forms. Adults (ages 18-23 years) and children (ages 7-10 years) performed a forced-choice task gauging similarity between visual stimuli consisting of large geometric objects (global level) composed of small geometric objects (local level). The…

Organizational and Spatial Dynamics of Attentional Focusing in Hierarchically Structured Objects

ERIC Educational Resources Information Center

Yeari, Menahem; Goldsmith, Morris

2011-01-01

Is the focusing of visual attention object-based, space-based, both, or neither? Attentional focusing latencies in hierarchically structured compound-letter objects were examined, orthogonally manipulating global size (larger vs. smaller) and organizational complexity (two-level structure vs. three-level structure). In a dynamic focusing task,…

Hierarchical analysis of forest bird species-environment relationships in the Oregon Coast Range

Treesearch

Samuel A. Cushman; Kevin McGarigal

2004-01-01

Species in biological communities respond to environmental variation simultaneously across a range of organizational levels. Accordingly, it is important to quantify the effects of environmental factors at multiple levels on species distribution and abundance. Hierarchical methods that explicitly separate the independent and confounded influences of environmental...

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

PubMed Central

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

2016-01-01

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

PubMed

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

2016-09-09

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

Design and measurement of fully digital ternary content addressable memory using ratioless static random access memory cells and hierarchical-AND matching comparator

NASA Astrophysics Data System (ADS)

Nishikata, Daisuke; Ali, Mohammad Alimudin Bin Mohd; Hosoda, Kento; Matsumoto, Hiroshi; Nakamura, Kazuyuki

2018-04-01

A 36-bit × 32-entry fully digital ternary content addressable memory (TCAM) using the ratioless static random access memory (RL-SRAM) technology and fully complementary hierarchical-AND matching comparators (HAMCs) was developed. Since its fully complementary and digital operation enables the effect of device variabilities to be avoided, it can operate with a quite low supply voltage. A test chip incorporating a conventional TCAM and a proposed 24-transistor ratioless TCAM (RL-TCAM) cells and HAMCs was developed using a 0.18 µm CMOS process. The minimum operating voltage of 0.25 V of the developed RL-TCAM, which is less than half of that of the conventional TCAM, was measured via the conventional CMOS push–pull output buffers with the level-shifting and flipping technique using optimized pull-up voltage and resistors.

Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Analyzing Multilevel Data: An Empirical Comparison of Parameter Estimates of Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2011-01-01

Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

Bayesian Hierarchical Random Intercept Model Based on Three Parameter Gamma Distribution

NASA Astrophysics Data System (ADS)

Wirawati, Ika; Iriawan, Nur; Irhamah

2017-06-01

Hierarchical data structures are common throughout many areas of research. Beforehand, the existence of this type of data was less noticed in the analysis. The appropriate statistical analysis to handle this type of data is the hierarchical linear model (HLM). This article will focus only on random intercept model (RIM), as a subclass of HLM. This model assumes that the intercept of models in the lowest level are varied among those models, and their slopes are fixed. The differences of intercepts were suspected affected by some variables in the upper level. These intercepts, therefore, are regressed against those upper level variables as predictors. The purpose of this paper would demonstrate a proven work of the proposed two level RIM of the modeling on per capita household expenditure in Maluku Utara, which has five characteristics in the first level and three characteristics of districts/cities in the second level. The per capita household expenditure data in the first level were captured by the three parameters Gamma distribution. The model, therefore, would be more complex due to interaction of many parameters for representing the hierarchical structure and distribution pattern of the data. To simplify the estimation processes of parameters, the computational Bayesian method couple with Markov Chain Monte Carlo (MCMC) algorithm and its Gibbs Sampling are employed.

Hierarchical optimal control of large-scale nonlinear chemical processes.

PubMed

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

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

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

Hierarchical Diagnosis of Vocal Fold Disorders

NASA Astrophysics Data System (ADS)

Nikkhah-Bahrami, Mansour; Ahmadi-Noubari, Hossein; Seyed Aghazadeh, Babak; Khadivi Heris, Hossein

This paper explores the use of hierarchical structure for diagnosis of vocal fold disorders. The hierarchical structure is initially used to train different second-level classifiers. At the first level normal and pathological signals have been distinguished. Next, pathological signals have been classified into neurogenic and organic vocal fold disorders. At the final level, vocal fold nodules have been distinguished from polyps in organic disorders category. For feature selection at each level of hierarchy, the reconstructed signal at each wavelet packet decomposition sub-band in 5 levels of decomposition with mother wavelet of (db10) is used to extract the nonlinear features of self-similarity and approximate entropy. Also, wavelet packet coefficients are used to measure energy and Shannon entropy features at different spectral sub-bands. Davies-Bouldin criterion has been employed to find the most discriminant features. Finally, support vector machines have been adopted as classifiers at each level of hierarchy resulting in the diagnosis accuracy of 92%.

Detailed requirements for a next generation nuclear data structure.

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

Brown, D.

2016-07-05

This document attempts to compile the requirements for the top-levels of a hierarchical arrangement of nuclear data such as found in the ENDF format. This set of requirements will be used to guide the development of a new data structure to replace the legacy ENDF format.

Examining Elementary Social Studies Marginalization: A Multilevel Model

ERIC Educational Resources Information Center

Fitchett, Paul G.; Heafner, Tina L.; Lambert, Richard G.

2014-01-01

Utilizing data from the National Center for Education Statistics Schools and Staffing Survey (SASS), a multilevel model (Hierarchical Linear Model) was developed to examine the association of teacher/classroom and state level indicators on reported elementary social studies instructional time. Findings indicated that state testing policy was a…

The Alaska vegetation classification.

Treesearch

L.A. Viereck; C.T. Dyrness; A.R. Batten; K.J. Wenzlick

1992-01-01

The Alaska vegetation classification presented here is a comprehensive, statewide system that has been under development since 1976. The classification is based, as much as possible, on the characteristics of the vegetation itself and is designed to categorize existing vegetation, not potential vegetation. A hierarchical system with five levels of resolution is used...

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

NASA Technical Reports Server (NTRS)

Houlahan, Padraig; Scalo, John

1992-01-01

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Age-Related Change in Shifting Attention between Global and Local Levels of Hierarchical Stimuli

ERIC Educational Resources Information Center

Huizinga, Mariette; Burack, Jacob A.; Van der Molen, Maurits W.

2010-01-01

The focus of this study was the developmental pattern of the ability to shift attention between global and local levels of hierarchical stimuli. Children aged 7 years and 11 years and 21-year-old adults were administered a task (two experiments) that allowed for the examination of 1) the direction of attention to global or local stimulus levels;…

A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gossman, W. E.

1986-01-01

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

[The system-oriented model of psychosocial rehabilitation].

PubMed

Iastrebov V S; Mitikhin, V G; Solokhina, T A; Mikhaĭlova, I I

2008-01-01

A model of psychosocial rehabilitation based on the system approach that allows taking into account both the patient-centered approach of the rehabilitation service, the development of its resource basis, the effectiveness of this care system in whole and its patterns as well has been worked out. In the framework of this model, the authors suggest to single out three basic stages of the psychosocial rehabilitation process: evaluation and planning, rehabilitation interventions per se, achievement of the result. In author's opinion, the most successful way for constructing a modern model of psychosocial rehabilitation is a method of hierarchic modeling which can reveal a complex chain of interactions between all participants of the rehabilitation process and factors involved in this process and at the same time specify the multi-level hierarchic character of these interactions and factors. An important advantage of this method is the possibility of obtaining as static as well dynamic evaluations of the rehabilitation service activity that may be used on the following levels: 1) patient; 2) his/her close environment; 3) macrosocial level. The obvious merits of the system-oriented model appear to be the possibility of application of its principles in the organization of specialized care for psychiatric patients on the local, regional and federal levels. The authors emphasize that hierarchic models have universal character and can be implemented in the elaboration of information-analytical systems aimed at solving the problems of monitoring and analysis of social-medical service activity in order to increase its effectiveness.

Wavelet-based hierarchical surface approximation from height fields

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

2004-01-01

This paper presents a novel hierarchical approach to triangular mesh generation from height fields. A wavelet-based multiresolution analysis technique is used to estimate local shape information at different levels of resolution. Using predefined templates at the coarsest level, the method constructs an initial triangulation in which underlying object shapes are well...

A hierarchical-multiobjective framework for risk management

NASA Technical Reports Server (NTRS)

Haimes, Yacov Y.; Li, Duan

1991-01-01

A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.

Hierarchical macroscopic fibrillar adhesives: in situ study of buckling and adhesion mechanisms on wavy substrates.

PubMed

Bauer, Christina T; Kroner, Elmar; Fleck, Norman A; Arzt, Eduard

2015-10-23

Nature uses hierarchical fibrillar structures to mediate temporary adhesion to arbitrary substrates. Such structures provide high compliance such that the flat fibril tips can be better positioned with respect to asperities of a wavy rough substrate. We investigated the buckling and adhesion of hierarchically structured adhesives in contact with flat smooth, flat rough and wavy rough substrates. A macroscopic model for the structural adhesive was fabricated by molding polydimethylsiloxane into pillars of diameter in the range of 0.3-4.8 mm, with up to three different hierarchy levels. Both flat-ended and mushroom-shaped hierarchical samples buckled at preloads one quarter that of the single level structures. We explain this behavior by a change in the buckling mode; buckling leads to a loss of contact and diminishes adhesion. Our results indicate that hierarchical structures can have a strong influence on the degree of adhesion on both flat and wavy substrates. Strategies are discussed that achieve highly compliant substrates which adhere to rough substrates.

Knowledge-based approach to system integration

NASA Technical Reports Server (NTRS)

Blokland, W.; Krishnamurthy, C.; Biegl, C.; Sztipanovits, J.

1988-01-01

To solve complex problems one can often use the decomposition principle. However, a problem is seldom decomposable into completely independent subproblems. System integration deals with problem of resolving the interdependencies and the integration of the subsolutions. A natural method of decomposition is the hierarchical one. High-level specifications are broken down into lower level specifications until they can be transformed into solutions relatively easily. By automating the hierarchical decomposition and solution generation an integrated system is obtained in which the declaration of high level specifications is enough to solve the problem. We offer a knowledge-based approach to integrate the development and building of control systems. The process modeling is supported by using graphic editors. The user selects and connects icons that represent subprocesses and might refer to prewritten programs. The graphical editor assists the user in selecting parameters for each subprocess and allows the testing of a specific configuration. Next, from the definitions created by the graphical editor, the actual control program is built. Fault-diagnosis routines are generated automatically as well. Since the user is not required to write program code and knowledge about the process is present in the development system, the user is not required to have expertise in many fields.

Towards a hierarchical optimization modeling framework for ...

EPA Pesticide Factsheets

Background:Bilevel optimization has been recognized as a 2-player Stackelberg game where players are represented as leaders and followers and each pursue their own set of objectives. Hierarchical optimization problems, which are a generalization of bilevel, are especially difficult because the optimization is nested, meaning that the objectives of one level depend on solutions to the other levels. We introduce a hierarchical optimization framework for spatially targeting multiobjective green infrastructure (GI) incentive policies under uncertainties related to policy budget, compliance, and GI effectiveness. We demonstrate the utility of the framework using a hypothetical urban watershed, where the levels are characterized by multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities), and objectives include minimization of policy cost, implementation cost, and risk; reduction of combined sewer overflow (CSO) events; and improvement in environmental benefits such as reduced nutrient run-off and water availability. Conclusions: While computationally expensive, this hierarchical optimization framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urba

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

PubMed

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

2017-06-27

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

Buckling Load Calculations of the Isotropic Shell A-8 Using a High-Fidelity Hierarchical Approach

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.

2002-01-01

As a step towards developing a new design philosophy, one that moves away from the traditional empirical approach used today in design towards a science-based design technology approach, a test series of 7 isotropic shells carried out by Aristocrat and Babcock at Caltech is used. It is shown how the hierarchical approach to buckling load calculations proposed by Arbocz et al can be used to perform an approach often called 'high fidelity analysis', where the uncertainties involved in a design are simulated by refined and accurate numerical methods. The Delft Interactive Shell DEsign COde (short, DISDECO) is employed for this hierarchical analysis to provide an accurate prediction of the critical buckling load of the given shell structure. This value is used later as a reference to establish the accuracy of the Level-3 buckling load predictions. 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 using a sufficiently refined finite element model with one of the current generation two-dimensional shell analysis codes with the advanced capabilities needed to represent both geometric and material nonlinearities.

On a High-Fidelity Hierarchical Approach to Buckling Load Calculations

NASA Technical Reports Server (NTRS)

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

2001-01-01

As a step towards developing a new design philosophy, one that moves away from the traditional empirical approach used today in design towards a science-based design technology approach, a recent test series of 5 composite shells carried out by Waters at NASA Langley Research Center is used. It is shown how the hierarchical approach to buckling load calculations proposed by Arbocz et al can be used to perform an approach often called "high fidelity analysis", where the uncertainties involved in a design are simulated by refined and accurate numerical methods. The Delft Interactive Shell DEsign COde (short, DISDECO) is employed for this hierarchical analysis to provide an accurate prediction of the critical buckling load of the given shell structure. This value is used later as a reference to establish the accuracy of the Level-3 buckling load predictions. 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 using a sufficiently refined finite element model with one of the current generation two-dimensional shell analysis codes with the advanced capabilities needed to represent both geometric and material nonlinearities.

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

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

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

Predicting helix–helix interactions from residue contacts in membrane proteins

PubMed Central

Lo, Allan; Chiu, Yi-Yuan; Rødland, Einar Andreas; Lyu, Ping-Chiang; Sung, Ting-Yi; Hsu, Wen-Lian

2009-01-01

Motivation: Helix–helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. On the molecular level, the interactions are mediated by one or more residue contacts. Although previous studies focused on helix-packing patterns and sequence motifs, few of them developed methods specifically for contact prediction. Results: We present a new hierarchical framework for contact prediction, with an application in membrane proteins. The hierarchical scheme consists of two levels: in the first level, contact residues are predicted from the sequence and their pairing relationships are further predicted in the second level. Statistical analyses on contact propensities are combined with other sequence and structural information for training the support vector machine classifiers. Evaluated on 52 protein chains using leave-one-out cross validation (LOOCV) and an independent test set of 14 protein chains, the two-level approach consistently improves the conventional direct approach in prediction accuracy, with 80% reduction of input for prediction. Furthermore, the predicted contacts are then used to infer interactions between pairs of helices. When at least three predicted contacts are required for an inferred interaction, the accuracy, sensitivity and specificity are 56%, 40% and 89%, respectively. Our results demonstrate that a hierarchical framework can be applied to eliminate false positives (FP) while reducing computational complexity in predicting contacts. Together with the estimated contact propensities, this method can be used to gain insights into helix-packing in membrane proteins. Availability: http://bio-cluster.iis.sinica.edu.tw/TMhit/ Contact: tsung@iis.sinica.edu.tw Supplementary information:Supplementary data are available at Bioinformatics online. PMID:19244388

Peripheral infrastructure vectors and an extended set of plant parts for the Modular Cloning system

PubMed Central

Kretschmer, Carola; Gruetzner, Ramona; Löfke, Christian; Dagdas, Yasin; Bürstenbinder, Katharina; Marillonnet, Sylvestre

2018-01-01

Standardized DNA assembly strategies facilitate the generation of multigene constructs from collections of building blocks in plant synthetic biology. A common syntax for hierarchical DNA assembly following the Golden Gate principle employing Type IIs restriction endonucleases was recently developed, and underlies the Modular Cloning and GoldenBraid systems. In these systems, transcriptional units and/or multigene constructs are assembled from libraries of standardized building blocks, also referred to as phytobricks, in several hierarchical levels and by iterative Golden Gate reactions. Here, a toolkit containing further modules for the novel DNA assembly standards was developed. Intended for use with Modular Cloning, most modules are also compatible with GoldenBraid. Firstly, a collection of approximately 80 additional phytobricks is provided, comprising e.g. modules for inducible expression systems, promoters or epitope tags. Furthermore, DNA modules were developed for connecting Modular Cloning and Gateway cloning, either for toggling between systems or for standardized Gateway destination vector assembly. Finally, first instances of a “peripheral infrastructure” around Modular Cloning are presented: While available toolkits are designed for the assembly of plant transformation constructs, vectors were created to also use coding sequence-containing phytobricks directly in yeast two hybrid interaction or bacterial infection assays. The presented material will further enhance versatility of hierarchical DNA assembly strategies. PMID:29847550

A structuration framework for bridging the macro-micro divide in health-care governance.

PubMed

Bodolica, Virginia; Spraggon, Martin; Tofan, Gabriela

2016-08-01

Extant studies demonstrate that macro (hierarchical) and micro (relational) governance initiatives in health-care settings continue to be developed in isolation rather than interactively. Government-driven hierarchical governance endeavours that guide health-care reforms and medical practice are disconnected from micro-level physician-patient interactions being unable to account for patient preferences in the macro-level policymaking. We undertake a review of the recent literature to couch our argument for a unified governance framework for bridging the macro-micro divide in medical contexts. Adopting an interdisciplinary approach to health-care delivery, we maintain that the (strong) structuration theory provides a fruitful opportunity for narrowing the gap between hierarchical and relational governance. Emphasizing the coexistence of institutional structures and human agency, the (strong) structuration theory elucidates how macro and micro governance devices shape each other's structure via mutually reinforcing cycles of influence. Micro-level encounters between patients and physicians give rise to social structures that constitute the constraining and enabling forces through which macro-level health-care infrastructures are altered and reproduced over time. Permitting to illustrate how patients' agency can effectively emerge from complex networks of clinical trajectories, the advanced structuration framework for macro-micro governance integration avoids the extremes of paternalism and autonomy through a balanced consideration of professional judgement and patient preferences. The macro-micro integration of governance efforts is a critical issue in both high-income states, where medical institutions attempt to deploy substantial realignment efforts, and developing nations, which are lagging behind due to leadership weaknesses and lower levels of governmental investment. A key priority for regulators is the identification of relevant systems to support this holistic governance by providing clinicians with needed resources for focusing on patient advocacy and installing enabling mechanisms for incorporating patients' inputs in health-care reforms and policymaking. © 2015 John Wiley & Sons Ltd.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Perceptions of societal developmental hierarchies in Europe and beyond: A Bulgarian Perspective

PubMed Central

Melegh, Attila; Thornton, Arland; Philipov, Dimiter; Young-DeMarco, Linda

2012-01-01

We examine how ordinary citizens in Bulgaria view the developmental levels of European countries and certain states outside of Europe. Our research is motivated by the understanding that scholars and policy makers have for centuries used developmental hierarchies to characterize countries and that this perception of differential development has shaped interactions among different groups, countries and regions. We expect that views of such developmental hierarchies and models have great potential for influencing demographic and family behavior and political and cultural identities of ordinary people. Using data from a 2009 survey in Bulgaria we document that developmental hierarchies are widely perceived in Bulgaria, but are distributed differentially by age, education, and degree of urbanization. We also consider internal mechanisms underlying this hierarchical understanding of development and how hierarchical understandings may be related to national identities. PMID:23807821

A Comparison of Reasoning Processes in a Collaborative Modelling Environment: Learning about genetics problems using virtual chat

NASA Astrophysics Data System (ADS)

Pata, Kai; Sarapuu, Tago

2006-09-01

This study investigated the possible activation of different types of model-based reasoning processes in two learning settings, and the influence of various terms of reasoning on the learners’ problem representation development. Changes in 53 students’ problem representations about genetic issue were analysed while they worked with different modelling tools in a synchronous network-based environment. The discussion log-files were used for the “microgenetic” analysis of reasoning types. For studying the stages of students’ problem representation development, individual pre-essays and post-essays and their utterances during two reasoning phases were used. An approach for mapping problem representations was developed. Characterizing the elements of mental models and their reasoning level enabled the description of five hierarchical categories of problem representations. Learning in exploratory and experimental settings was registered as the shift towards more complex stages of problem representations in genetics. The effect of different types of reasoning could be observed as the divergent development of problem representations within hierarchical categories.

Hierarchical chirality transfer in the growth of Towel Gourd tendrils

PubMed Central

Wang, Jian-Shan; Wang, Gang; Feng, Xi-Qiao; Kitamura, Takayuki; Kang, Yi-Lan; Yu, Shou-Wen; Qin, Qing-Hua

2013-01-01

Chirality plays a significant role in the physical properties and biological functions of many biological materials, e.g., climbing tendrils and twisted leaves, which exhibit chiral growth. However, the mechanisms underlying the chiral growth of biological materials remain unclear. In this paper, we investigate how the Towel Gourd tendrils achieve their chiral growth. Our experiments reveal that the tendrils have a hierarchy of chirality, which transfers from the lower levels to the higher. The change in the helical angle of cellulose fibrils at the subcellular level induces an intrinsic torsion of tendrils, leading to the formation of the helical morphology of tendril filaments. A chirality transfer model is presented to elucidate the chiral growth of tendrils. This present study may help understand various chiral phenomena observed in biological materials. It also suggests that chirality transfer can be utilized in the development of hierarchically chiral materials having unique properties. PMID:24173107

Hierarchical Volume Representation with 3{radical}2 Subdivision and Trivariate B-Spline Wavelets

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

Linsen, L; Gray, JT; Pascucci, V

2002-01-11

Multiresolution methods provide a means for representing data at multiple levels of detail. They are typically based on a hierarchical data organization scheme and update rules needed for data value computation. We use a data organization that is based on what we call n{radical}2 subdivision. The main advantage of subdivision, compared to quadtree (n = 2) or octree (n = 3) organizations, is that the number of vertices is only doubled in each subdivision step instead of multiplied by a factor of four or eight, respectively. To update data values we use n-variate B-spline wavelets, which yields better approximations formore » each level of detail. We develop a lifting scheme for n = 2 and n = 3 based on the n{radical}2-subdivision scheme. We obtain narrow masks that could also provide a basis for view-dependent visualization and adaptive refinement.« less

A retrospective study of phonetic inventory complexity in acquisition of Spanish: Implications for phonological universals

PubMed Central

Cataño, Lorena; Barlow, Jessica A.; Moyna, María Irene

2015-01-01

This study evaluates 39 different phonetic inventories of 16 Spanish-speaking children (ages 0;11 to 5;1) in terms of hierarchical complexity. Phonetic featural differences are considered in order to evaluate the proposed implicational hierarchy of Dinnsen et al.’s phonetic inventory typology for English. The children’s phonetic inventories are examined independently and in relation to one another. Five hierarchical complexity levels are proposed, similar to those of English and other languages, although with some language-specific differences. These findings have implications for theoretical assumptions about the universality of phonetic inventory development, and for remediation of Spanish-speaking children with phonological impairments. PMID:19504400

Theoretical aspects of Systems Biology.

PubMed

Bizzarri, Mariano; Palombo, Alessandro; Cucina, Alessandra

2013-05-01

The natural world consists of hierarchical levels of complexity that range from subatomic particles and molecules to ecosystems and beyond. This implies that, in order to explain the features and behavior of a whole system, a theory might be required that would operate at the corresponding hierarchical level, i.e. where self-organization processes take place. In the past, biological research has focused on questions that could be answered by a reductionist program of genetics. The organism (and its development) was considered an epiphenomenona of its genes. However, a profound rethinking of the biological paradigm is now underway and it is likely that such a process will lead to a conceptual revolution emerging from the ashes of reductionism. This revolution implies the search for general principles on which a cogent theory of biology might rely. Because much of the logic of living systems is located at higher levels, it is imperative to focus on them. Indeed, both evolution and physiology work on these levels. Thus, by no means Systems Biology could be considered a 'simple' 'gradual' extension of Molecular Biology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of a simple measurement scale to evaluate the severity of non-specific low back pain for industrial ergonomics.

PubMed

Higuchi, Yoshiyuki; Izumi, Hiroyuki; Kumashiro, Mashaharu

2010-06-01

This study developed an assessment scale that hierarchically classifies degrees of low back pain severity. This assessment scale consists of two subscales: 1) pain intensity; 2) pain interference. First, the assessment scale devised by the authors was used to administer a self-administered questionnaire to 773 male workers in the car manufacturing industry. Subsequently, the validity of the measurement items was examined and some of them were revised. Next, the corrected low back pain scale was used in a self-administered questionnaire, the subjects of which were 5053 ordinary workers. The hierarchical validity between the measurement items was checked based on the results of Mokken Scale analysis. Finally, a low back pain assessment scale consisting of seven items was perfected. Quantitative assessment is made possible by scoring the items and low back pain severity can be classified into four hierarchical levels: none; mild; moderate; severe. STATEMENT OF RELEVANCE: The use of this scale devised by the authors allows a more detailed assessment of the degree of risk factor effect and also should prove useful both in selecting remedial measures for occupational low back pain and evaluating their efficacy.

Developing PFC representations using reinforcement learning.

PubMed

Reynolds, Jeremy R; O'Reilly, Randall C

2009-12-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically [Fuster (1991); Koechlin, E., Ody, C., & Kouneiher, F. (2003). Neuroscience: The architecture of cognitive control in the human prefrontal cortex. Science, 424, 1181-1184; Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt]. However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data.

Relative Contributions of Goal Representation and Kinematic Information to Self-Monitoring by Chimpanzees and Humans

ERIC Educational Resources Information Center

Kaneko, Takaaki; Tomonaga, Masaki

2012-01-01

It is important to monitor feedback related to the intended result of an action while executing that action. This monitoring process occurs hierarchically; that is, sensorimotor processing occurs at a lower level, and conceptual representation of action goals occurs at a higher level. Although the hierarchical nature of self-monitoring may derive…

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…

Hierarchical Control and Skilled Typing: Evidence for Word-Level Control over the Execution of Individual Keystrokes

ERIC Educational Resources Information Center

Crump, Matthew J. C.; Logan, Gordon D.

2010-01-01

Routine actions are commonly assumed to be controlled by hierarchically organized processes and representations. In the domain of typing theories, word-level information is assumed to activate the constituent keystrokes required to type each letter in a word. We tested this assumption directly using a novel single-letter probe technique. Subjects…

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

PubMed

Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

2018-05-01

Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Broadband locally resonant metamaterials with graded hierarchical architecture

NASA Astrophysics Data System (ADS)

Liu, Chenchen; Reina, Celia

2018-03-01

We investigate the effect of hierarchical designs on the bandgap structure of periodic lattice systems with inner resonators. A detailed parameter study reveals various interesting features of structures with two levels of hierarchy as compared with one level systems with identical static mass. In particular: (i) their overall bandwidth is approximately equal, yet bounded above by the bandwidth of the single-resonator system; (ii) the number of bandgaps increases with the level of hierarchy; and (iii) the spectrum of bandgap frequencies is also enlarged. Taking advantage of these features, we propose graded hierarchical structures with ultra-broadband properties. These designs are validated over analogous continuum models via finite element simulations, demonstrating their capability to overcome the bandwidth narrowness that is typical of resonant metamaterials.

Mathematical Methods of System Analysis in Construction Materials

NASA Astrophysics Data System (ADS)

Garkina, Irina; Danilov, Alexander

2017-10-01

System attributes of construction materials are defined: complexity of an object, integrity of set of elements, existence of essential, stable relations between elements defining integrative properties of system, existence of structure, etc. On the basis of cognitive modelling (intensive and extensive properties; the operating parameters) materials (as difficult systems) and creation of the cognitive map the hierarchical modular structure of criteria of quality is under construction. It actually is a basis for preparation of the specification on development of material (the required organization and properties). Proceeding from a modern paradigm (model of statement of problems and their decisions) of development of materials, levels and modules are specified in structure of material. It when using the principles of the system analysis allows to considered technological process as the difficult system consisting of elements of the distinguished specification level: from atomic before separate process. Each element of system depending on an effective objective is considered as separate system with more detailed levels of decomposition. Among them, semantic and qualitative analyses of an object (are considered a research objective, decomposition levels, separate elements and communications between them come to light). Further formalization of the available knowledge in the form of mathematical models (structural identification) is carried out; communications between input and output parameters (parametrical identification) are defined. Hierarchical structures of criteria of quality are under construction for each allocated level. On her the relevant hierarchical structures of system (material) are under construction. Regularities of structurization and formation of properties, generally are considered at the levels from micro to a macrostructure. The mathematical model of material is represented as set of the models corresponding to private criteria by which separate modules and their levels (the mathematical description, a decision algorithm) are defined. Adequacy is established (compliance of results of modelling to experimental data; is defined by the level of knowledge of process and validity of the accepted assumptions). The global criterion of quality of material is considered as a set of private criteria (properties). Synthesis of material is carried out on the basis of one-criteria optimization on each of the chosen private criteria. Results of one-criteria optimization are used at multicriteria optimization. The methods of developing materials as single-purpose, multi-purpose, including contradictory, systems are indicated. The scheme of synthesis of composite materials as difficult systems is developed. The specified system approach effectively was used in case of synthesis of composite materials with special properties.

Evaluating Hierarchical Structure in Music Annotations

PubMed Central

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

2017-01-01

Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement. PMID:28824514

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

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

Analysis hierarchical model for discrete event systems

NASA Astrophysics Data System (ADS)

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.

The Goddard Space Flight Center (GSFC) robotics technology testbed

NASA Technical Reports Server (NTRS)

Schnurr, Rick; Obrien, Maureen; Cofer, Sue

1989-01-01

Much of the technology planned for use in NASA's Flight Telerobotic Servicer (FTS) and the Demonstration Test Flight (DTF) is relatively new and untested. To provide the answers needed to design safe, reliable, and fully functional robotics for flight, NASA/GSFC is developing a robotics technology testbed for research of issues such as zero-g robot control, dual arm teleoperation, simulations, and hierarchical control using a high level programming language. The testbed will be used to investigate these high risk technologies required for the FTS and DTF projects. The robotics technology testbed is centered around the dual arm teleoperation of a pair of 7 degree-of-freedom (DOF) manipulators, each with their own 6-DOF mini-master hand controllers. Several levels of safety are implemented using the control processor, a separate watchdog computer, and other low level features. High speed input/output ports allow the control processor to interface to a simulation workstation: all or part of the testbed hardware can be used in real time dynamic simulation of the testbed operations, allowing a quick and safe means for testing new control strategies. The NASA/National Bureau of Standards Standard Reference Model for Telerobot Control System Architecture (NASREM) hierarchical control scheme, is being used as the reference standard for system design. All software developed for the testbed, excluding some of simulation workstation software, is being developed in Ada. The testbed is being developed in phases. The first phase, which is nearing completion, and highlights future developments is described.

Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

ERIC Educational Resources Information Center

Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

2017-01-01

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we…

A multilevel model of the impact of farm-level best management practices on phosphorus runoff

USDA-ARS?s Scientific Manuscript database

Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analys...

A Hierarchical Approach to Examine Personal and School Effect on Teacher Motivation

ERIC Educational Resources Information Center

Wei, Yi-En

2012-01-01

In order to depict a better picture of teacher motivation, the researcher developed the theoretical framework based on Deci and Ryan's (1985) self-determination theory (SDT) and examined factors affecting teachers' autonomous motivation at both the personal and school level. Several multilevel structural equation models (ML-SEM) were…

The Aging Person as Philosopher: Moral Development in the Adult Years.

ERIC Educational Resources Information Center

Kohlberg, Lawrence; Shulik, Richard

Using four case studies, the paper explores whether the philosophical reflections on the meaning of life by older adults constitute a developmental stage as defined by Piaget. Prefacing his analysis with discussions of the Erikson model of ego stages and the Fowler "Faith Interview" methods, Kohlberg hypothesizes hierarchical levels that…

Toward a Naval Team Taxonomy.

DTIC Science & Technology

1980-12-01

emergency procedures. (AGARDograph No. 248). France: North Atlantic Treaty Organization, Advisory Group for Aerospace Research and Development, 1980. Farace ...International Communication Association, March 1973. Farace , Richard V., Monge, Peter R. and Russell, Hamish. Communicatingand organizing. Reading, MA...Addison-Wesley, 1977. Farace , Richard V. and Pacanowsky, Michael. Organizational communication role, hierarchical level and relative status. Paper

Modular Approach for Ethics

ERIC Educational Resources Information Center

Wyne, Mudasser F.

2010-01-01

It is hard to define a single set of ethics that will cover an entire computer users community. In this paper, the issue is addressed in reference to code of ethics implemented by various professionals, institutes and organizations. The paper presents a higher level model using hierarchical approach. The code developed using this approach could be…

Variability, Negative Evidence, and the Acquisition of Verb Argument Constructions

ERIC Educational Resources Information Center

Perfors, Amy; Tenenbaum, Joshua B.; Wonnacott, Elizabeth

2010-01-01

We present a hierarchical Bayesian framework for modeling the acquisition of verb argument constructions. It embodies a domain-general approach to learning higher-level knowledge in the form of inductive constraints (or overhypotheses), and has been used to explain other aspects of language development such as the shape bias in learning object…

Modern Conditions and the Impacts of the Creation of Architectural Environment

NASA Astrophysics Data System (ADS)

Abyzov, Vadym

2017-10-01

The purpose of this research is an attempt to identify and analyse the modern conditions and impacts of the creation of architectural environment and on this basis to determine the main directions and tasks of the development of architecture at the appropriate hierarchical levels. A comprehensive review and structural analysis of all impact factors and different current conditions that lead to the sustainable architecture design are conducted in the proposal. The main groups of factors and conditions such as social-economical, natural-geographic, urban, ergonomics, ecological, typological, technical, cultural, and aesthetics are determined in accordance with their contemporary specifics. This analysis provides an opportunity to define the appropriative hierarchical levels of the modern trends and prospects of creation an effective, attractive and friendly architectural environment. Some examples of author’s projects and implementations is presented in the article. Such methodological approach will help to create a holistic view of the creation architectural environment, will allow to systematize existing knowledges and concepts, practices and prospects of the means and methods of its formation and development.

Bayesian hierarchical model of ceftriaxone resistance proportions among Salmonella serotype Heidelberg infections.

PubMed

Gu, Weidong; Medalla, Felicita; Hoekstra, Robert M

2018-02-01

The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different specifications of spatio-temporal interaction using 2004-2013 NARMS data for ceftriaxone-resistant Salmonella serotype Heidelberg. Our results show that Bayesian estimates of resistance proportions were smoother than observed values, and the difference between predicted and observed proportions was inversely related to the number of submitted isolates. The model with interaction allowed for tracking of annual changes in resistance proportions at the state level. We demonstrated that Bayesian hierarchical models provide a useful tool to examine spatio-temporal patterns of small sample size such as those found in NARMS. Published by Elsevier Ltd.

A hierarchical dislocation-grain boundary interaction model based on 3D discrete dislocation dynamics and molecular dynamics

NASA Astrophysics Data System (ADS)

Gao, Yuan; Zhuang, Zhuo; You, XiaoChuan

2011-04-01

We develop a new hierarchical dislocation-grain boundary (GB) interaction model to predict the mechanical behavior of polycrystalline metals at micro and submicro scales by coupling 3D Discrete Dislocation Dynamics (DDD) simulation with the Molecular Dynamics (MD) simulation. At the microscales, the DDD simulations are responsible for capturing the evolution of dislocation structures; at the nanoscales, the MD simulations are responsible for obtaining the GB energy and ISF energy which are then transferred hierarchically to the DDD level. In the present model, four kinds of dislocation-GB interactions, i.e. transmission, absorption, re-emission and reflection, are all considered. By this methodology, the compression of a Cu micro-sized bi-crystal pillar is studied. We investigate the characteristic mechanical behavior of the bi-crystal compared with that of the single-crystal. Moreover, the comparison between the present penetrable model of GB and the conventional impenetrable model also shows the accuracy and efficiency of the present model.

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Theoretical and perceived balance of power inside Spanish public hospitals

PubMed Central

2001-01-01

Background The hierarchical pyramid inside Spanish public hospitals was radically changed by the Health Reform Law promulgated in 1986. According to it, the manpower of the hospitals was divided into three divisions (Medical, Nursing, General Services/Administration), which from then on occupied the same level, only subject to the general manager. Ten years after the implementation of the law, the present study was designed in order to investigate if the legal changes had indeed produced a real change in the balance of power inside the hospitals, as perceived by the different workers within them. Materials and Methods A questionnaire was administered to 1,027 workers from four different public hospitals (two university-based and two district hospitals). The participants belonged to all divisions, and to all three operative levels (staff, supervisory and managerial) within them. The questionnaire inquired about the perceived power inside each division and hierarchical level, as well as about that of the other divisions and hierarchical levels. Results Every division attributed the least power to itself. The Nursing and the Administrative division attributed the highest power to the physicians, and these attributed the highest power to the General Services/Administrative division. All hierarchical levels (including the formal top of the pyramid) attributed significantly more power to the other than to them. Conclusions More than ten years after the implementation of the new law, the majority of workers still perceive that the real power within the hospitals is held by the physicians (whereas these feel that it has shifted to the administrators). No division or hierarchical level believes it holds any significant degree of power, and this carries with it the danger of also not accepting any responsibility. PMID:11574049

Theoretical and perceived balance of power inside Spanish public hospitals.

PubMed

Salvadores, P; Schneider, J; Zubero, I

2001-01-01

The hierarchical pyramid inside Spanish public hospitals was radically changed by the Health Reform Law promulgated in 1986. According to it, the manpower of the hospitals was divided into three divisions (Medical, Nursing, General Services/Administration), which from then on occupied the same level, only subject to the general manager. Ten years after the implementation of the law, the present study was designed in order to investigate if the legal changes had indeed produced a real change in the balance of power inside the hospitals, as perceived by the different workers within them. A questionnaire was administered to 1,027 workers from four different public hospitals (two university-based and two district hospitals). The participants belonged to all divisions, and to all three operative levels (staff, supervisory and managerial) within them. The questionnaire inquired about the perceived power inside each division and hierarchical level, as well as about that of the other divisions and hierarchical levels. Every division attributed the least power to itself. The Nursing and the Administrative division attributed the highest power to the physicians, and these attributed the highest power to the General Services/Administrative division. All hierarchical levels (including the formal top of the pyramid) attributed significantly more power to the other than to them. More than ten years after the implementation of the new law, the majority of workers still perceive that the real power within the hospitals is held by the physicians (whereas these feel that it has shifted to the administrators). No division or hierarchical level believes it holds any significant degree of power, and this carries with it the danger of also not accepting any responsibility.

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.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Quantitative analysis to guide orphan drug development.

PubMed

Lesko, L J

2012-08-01

The development of orphan drugs for rare diseases has made impressive strides in the past 10 years. There has been a surge in orphan drug designations, but new drug approvals have not kept up. This article presents a three-pronged hierarchical strategy for quantitative analysis of data at the descriptive, mechanistic, and systems levels of the biological system that could represent a standardized and rational approach to orphan drug development. Examples are provided to illustrate the concept.

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…

Speed-Accuracy Trade-Off in Skilled Typewriting: Decomposing the Contributions of Hierarchical Control Loops

ERIC Educational Resources Information Center

Yamaguchi, Motonori; Crump, Matthew J. C.; Logan, Gordon D.

2013-01-01

Typing performance involves hierarchically structured control systems: At the higher level, an outer loop generates a word or a series of words to be typed; at the lower level, an inner loop activates the keystrokes comprising the word in parallel and executes them in the correct order. The present experiments examined contributions of the outer-…

Hierarchical calibration and validation of computational fluid dynamics models for solid sorbent-based carbon capture

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

Lai, Canhai; Xu, Zhijie; Pan, Wenxiao

2016-01-01

To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesianmore » calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.« less

Diagnostics for generalized linear hierarchical models in network meta-analysis.

PubMed

Zhao, Hong; Hodges, James S; Carlin, Bradley P

2017-09-01

Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

Applications of hierarchically structured porous materials from energy storage and conversion, catalysis, photocatalysis, adsorption, separation, and sensing to biomedicine.

PubMed

Sun, Ming-Hui; Huang, Shao-Zhuan; Chen, Li-Hua; Li, Yu; Yang, Xiao-Yu; Yuan, Zhong-Yong; Su, Bao-Lian

2016-06-13

Over the last decade, significant effort has been devoted to the applications of hierarchically structured porous materials owing to their outstanding properties such as high surface area, excellent accessibility to active sites, and enhanced mass transport and diffusion. The hierarchy of porosity, structural, morphological and component levels in these materials is key for their high performance in all kinds of applications. The introduction of hierarchical porosity into materials has led to a significant improvement in the performance of materials. Herein, recent progress in the applications of hierarchically structured porous materials from energy conversion and storage, catalysis, photocatalysis, adsorption, separation, and sensing to biomedicine is reviewed. Their potential future applications are also highlighted. We particularly dwell on the relationship between hierarchically porous structures and properties, with examples of each type of hierarchically structured porous material according to its chemical composition and physical characteristics. The present review aims to open up a new avenue to guide the readers to quickly obtain in-depth knowledge of applications of hierarchically porous materials and to have a good idea about selecting and designing suitable hierarchically porous materials for a specific application. In addition to focusing on the applications of hierarchically porous materials, this comprehensive review could stimulate researchers to synthesize new advanced hierarchically porous solids.

Hierarchical self-assembly of nanoparticles in polymer matrix and the nature of the interparticle interaction

NASA Astrophysics Data System (ADS)

Lin, Yu-Chiao; Chen, Chun-Yu; Chen, Hsin-Lung; Hashimoto, Takeji; Chen, Show-An; Li, Yen-Cheng

2015-06-01

Using small angle X-ray scattering (SAXS), we elucidated the spatial organization of palladium (Pd) nanoparticles (NPs) in the polymer matrix of poly(2-vinylpyridine) (P2VP) and the nature of inter-nanoparticle interactions, where the NPs were synthesized in the presence of P2VP by the reduction of palladium acetylacetonate (Pd(acac)2). The experimental SAXS profiles were analysed on the basis of a hierarchical structure model considering the following two types of interparticle potential: (i) hard-core repulsion only (i.e., the hard-sphere interaction) and (ii) hard-core repulsion together with an attractive potential well (i.e., the sticky hard-sphere interaction). The corresponding theoretical scattering functions, which were used for analysing the experimental SAXS profiles, were obtained within the context of the Percus-Yevick closure and the Ornstein-Zernike equation in the fundamental liquid theory. The analyses revealed that existence of the attractive potential well is indispensable to account for the experimental SAXS profiles. Moreover, the morphology of the hybrids was found to be characterized by a hierarchical structure with three levels, where about six primary NPs with the diameter of ca. 1.8 nm (level one) formed local clusters (level two), and these clusters aggregated to build up a large-scale mass-fractal structure (level three) with the fractal dimension of ca. 2.3. The scattering function developed here is of general use for quantitatively characterizing the morphological structures of polymer/NP hybrids and, in particular, for exploring the interaction potential of the NPs on the basis of the fundamental liquid theory.

Hierarchical fuzzy control of low-energy building systems

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

Yu, Zhen; Dexter, Arthur

2010-04-15

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profilemore » can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)« less

Issues of organizational cybernetics and viability beyond Beer's viable systems model

NASA Astrophysics Data System (ADS)

Nechansky, Helmut

2013-11-01

The paper starts summarizing the claims of Beer's viable systems model to identify five issues any viable organizations has to deal with in an unequivocal hierarchical structure of five interrelated systems. Then the evidence is introduced for additional issues and related viable structures of organizations, which deviate from Beer's model. These issues are: (1) the establishment and (2) evolution of an organization; (3) systems for independent top-down control (like "Six Sigma"); (4) systems for independent bottom-up correction of performance problems (like "Kaizen"), both working outside a hierarchical structure; (5) pull production systems ("Just in Time") and (6) systems for checks and balances of top-level power (like boards and shareholder meetings). Based on that an evolutionary approach to organizational cybernetics is outlined, addressing the establishment of organizations and possible courses of developments, including recent developments in quality and production engineering, as well as problems of setting and changing goal values determining organizational policies.

Towards a multi-level approach to the emergence of meaning processes in living systems.

PubMed

Queiroz, João; El-Hani, Charbel Niño

2006-09-01

Any description of the emergence and evolution of different types of meaning processes (semiosis, sensu C.S.Peirce) in living systems must be supported by a theoretical framework which makes it possible to understand the nature and dynamics of such processes. Here we propose that the emergence of semiosis of different kinds can be understood as resulting from fundamental interactions in a triadically-organized hierarchical process. To grasp these interactions, we develop a model grounded on Stanley Salthe's hierarchical structuralism. This model can be applied to establish, in a general sense, a set of theoretical constraints for explaining the instantiation of different kinds of meaning processes (iconic, indexical, symbolic) in semiotic systems. We use it to model a semiotic process in the immune system, namely, B-cell activation, in order to offer insights into the heuristic role it can play in the development of explanations for specific semiotic processes.

Use of statistical and neural net approaches in predicting toxicity of chemicals.

PubMed

Basak, S C; Grunwald, G D; Gute, B D; Balasubramanian, K; Opitz, D

2000-01-01

Hierarchical quantitative structure-activity relationships (H-QSAR) have been developed as a new approach in constructing models for estimating physicochemical, biomedicinal, and toxicological properties of interest. This approach uses increasingly more complex molecular descriptors in a graduated approach to model building. In this study, statistical and neural network methods have been applied to the development of H-QSAR models for estimating the acute aquatic toxicity (LC50) of 69 benzene derivatives to Pimephales promelas (fathead minnow). Topostructural, topochemical, geometrical, and quantum chemical indices were used as the four levels of the hierarchical method. It is clear from both the statistical and neural network models that topostructural indices alone cannot adequately model this set of congeneric chemicals. Not surprisingly, topochemical indices greatly increase the predictive power of both statistical and neural network models. Quantum chemical indices also add significantly to the modeling of this set of acute aquatic toxicity data.

Hierarchical video summarization

NASA Astrophysics Data System (ADS)

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

1998-12-01

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

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)

Moving template analysis of crack growth. 1: Procedure development

NASA Astrophysics Data System (ADS)

Padovan, Joe; Guo, Y. H.

1994-06-01

Based on a moving template procedure, this two part series will develop a method to follow the crack tip physics in a self-adaptive manner which provides a uniformly accurate prediction of crack growth. For multiple crack environments, this is achieved by attaching a moving template to each crack tip. The templates are each individually oriented to follow the associated growth orientation and rate. In this part, the essentials of the procedure are derived for application to fatigue crack environments. Overall the scheme derived possesses several hierarchical levels, i.e. the global model, the interpolatively tied moving template, and a multilevel element death option to simulate the crack wake. To speed up computation, the hierarchical polytree scheme is used to reorganize the global stiffness inversion process. In addition to developing the various features of the scheme, the accuracy of predictions for various crack lengths is also benchmarked. Part 2 extends the scheme to multiple crack problems. Extensive benchmarking is also presented to verify the scheme.

A hierarchical community occurrence model for North Carolina stream fish

USGS Publications Warehouse

Midway, S.R.; Wagner, Tyler; Tracy, B.H.

2016-01-01

The southeastern USA is home to one of the richest—and most imperiled and threatened—freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20 years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.

Needed: A Conceptual Framework for Collective Bargaining in Education. AFT QuEST Paper No. 9.

ERIC Educational Resources Information Center

Bhaerman, Robert D.

In response to a nationwide trend toward restructuring the teaching profession and redefining the role of the teacher, this paper suggests a position on developments in these areas. It rejects the idea of establishing hierarchical levels of teacher certification, but considers promising the movement toward vertical or horizontal differentiated…

The Forest, the Trees, and the Leaves: Differences of Processing across Development

ERIC Educational Resources Information Center

Krakowski, Claire-Sara; Poirel, Nicolas; Vidal, Julie; Roëll, Margot; Pineau, Arlette; Borst, Grégoire; Houdé, Olivier

2016-01-01

To act and think, children and adults are continually required to ignore irrelevant visual information to focus on task-relevant items. As real-world visual information is organized into structures, we designed a feature visual search task containing 3-level hierarchical stimuli (i.e., local shapes that constituted intermediate shapes that formed…

Hierarchical modeling for reliability analysis using Markov models. B.S./M.S. Thesis - MIT

NASA Technical Reports Server (NTRS)

Fagundo, Arturo

1994-01-01

Markov models represent an extremely attractive tool for the reliability analysis of many systems. However, Markov model state space grows exponentially with the number of components in a given system. Thus, for very large systems Markov modeling techniques alone become intractable in both memory and CPU time. Often a particular subsystem can be found within some larger system where the dependence of the larger system on the subsystem is of a particularly simple form. This simple dependence can be used to decompose such a system into one or more subsystems. A hierarchical technique is presented which can be used to evaluate these subsystems in such a way that their reliabilities can be combined to obtain the reliability for the full system. This hierarchical approach is unique in that it allows the subsystem model to pass multiple aggregate state information to the higher level model, allowing more general systems to be evaluated. Guidelines are developed to assist in the system decomposition. An appropriate method for determining subsystem reliability is also developed. This method gives rise to some interesting numerical issues. Numerical error due to roundoff and integration are discussed at length. Once a decomposition is chosen, the remaining analysis is straightforward but tedious. However, an approach is developed for simplifying the recombination of subsystem reliabilities. Finally, a real world system is used to illustrate the use of this technique in a more practical context.

Hierarchical graphs for rule-based modeling of biochemical systems

PubMed Central

2011-01-01

Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal) of an edge represents a class of association (dissociation) reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR) complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for specifying rule-based models, such as the BioNetGen language (BNGL). Thus, the proposed use of hierarchical graphs should promote clarity and better understanding of rule-based models. PMID:21288338

Hierarchical coarse-graining transform.

PubMed

Pancaldi, Vera; King, Peter R; Christensen, Kim

2009-03-01

We present a hierarchical transform that can be applied to Laplace-like differential equations such as Darcy's equation for single-phase flow in a porous medium. A finite-difference discretization scheme is used to set the equation in the form of an eigenvalue problem. Within the formalism suggested, the pressure field is decomposed into an average value and fluctuations of different kinds and at different scales. The application of the transform to the equation allows us to calculate the unknown pressure with a varying level of detail. A procedure is suggested to localize important features in the pressure field based only on the fine-scale permeability, and hence we develop a form of adaptive coarse graining. The formalism and method are described and demonstrated using two synthetic toy problems.

TEAM (Technologies Enabling Agile Manufacturing) shop floor control requirements guide: Version 1.0

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

NONE

1995-03-28

TEAM will create a shop floor control system (SFC) to link the pre-production planning to shop floor execution. SFC must meet the requirements of a multi-facility corporation, where control must be maintained between co-located facilities down to individual workstations within each facility. SFC must also meet the requirements of a small corporation, where there may only be one small facility. A hierarchical architecture is required to meet these diverse needs. The hierarchy contains the following levels: Enterprise, Factory, Cell, Station, and Equipment. SFC is focused on the top three levels. Each level of the hierarchy is divided into three basicmore » functions: Scheduler, Dispatcher, and Monitor. The requirements of each function depend on the hierarchical level in which it is to be used. For example, the scheduler at the Enterprise level must allocate production to individual factories and assign due-dates; the scheduler at the Cell level must provide detailed start and stop times of individual operations. Finally the system shall have the following features: distributed and open-architecture. Open architecture software is required in order that the appropriate technology be used at each level of the SFC hierarchy, and even at different instances within the same hierarchical level (for example, Factory A uses discrete-event simulation scheduling software, and Factory B uses an optimization-based scheduler). A distributed implementation is required to reduce the computational burden of the overall system, and allow for localized control. A distributed, open-architecture implementation will also require standards for communication between hierarchical levels.« less

Method for implementation of recursive hierarchical segmentation on parallel computers

NASA Technical Reports Server (NTRS)

Tilton, James C. (Inventor)

2005-01-01

A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.

Cryptanalysis of Chatterjee-Sarkar Hierarchical Identity-Based Encryption Scheme at PKC 06

NASA Astrophysics Data System (ADS)

Park, Jong Hwan; Lee, Dong Hoon

In 2006, Chatterjee and Sarkar proposed a hierarchical identity-based encryption (HIBE) scheme which can support an unbounded number of identity levels. This property is particularly useful in providing forward secrecy by embedding time components within hierarchical identities. In this paper we show that their scheme does not provide the claimed property. Our analysis shows that if the number of identity levels becomes larger than the value of a fixed public parameter, an unintended receiver can reconstruct a new valid ciphertext and decrypt the ciphertext using his or her own private key. The analysis is similarly applied to a multi-receiver identity-based encryption scheme presented as an application of Chatterjee and Sarkar's HIBE scheme.

Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation

PubMed Central

Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2011-01-01

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over the sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to simultaneously learn the patterns of response that are shared across the group, and to estimate the number of these patterns supported by data. Inference based on this model enables automatic discovery and characterization of salient and consistent patterns in functional signals. We apply our method to data from a study that explores the response of the visual cortex to a collection of images. The discovered profiles of activation correspond to selectivity to a number of image categories such as faces, bodies, and scenes. More generally, our results appear superior to the results of alternative data-driven methods in capturing the category structure in the space of stimuli. PMID:21841977

Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure.

PubMed

Teunis, P F M; Ogden, I D; Strachan, N J C

2008-06-01

The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools such as S-plus and @ Risk.

The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints.

PubMed

Lassere, Marissa N

2008-06-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Section 2 is a systematic, historical review of the biomarker-surrogate endpoint literature with special reference to the nomenclature, the systems of classification and statistical methods developed for their evaluation. In Section 3 an explicit, criterion-based, quantitative, multidimensional hierarchical levels of evidence schema - Biomarker-Surrogacy Evaluation Schema - is proposed to evaluate and co-ordinate the multiple dimensions (biological, epidemiological, statistical, clinical trial and risk-benefit evidence) of the biomarker clinical endpoint relationships. The schema systematically evaluates and ranks the surrogacy status of biomarkers and surrogate endpoints using defined levels of evidence. The schema incorporates the three independent domains: Study Design, Target Outcome and Statistical Evaluation. Each domain has items ranked from zero to five. An additional category called Penalties incorporates additional considerations of biological plausibility, risk-benefit and generalizability. The total score (0-15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. The term ;surrogate' is restricted to markers attaining Levels 1 or 2 only. Surrogacy status of markers can then be directly compared within and across different areas of medicine to guide individual, trial-based or drug-development decisions. This schema would facilitate communication between clinical, researcher, regulatory, industry and consumer participants necessary for evaluation of the biomarker-surrogate-clinical endpoint relationship in their different settings.

Hardware proofs using EHDM and the RSRE verification methodology

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Sjogren, Jon A.

1988-01-01

Examined is a methodology for hardware verification developed by Royal Signals and Radar Establishment (RSRE) in the context of the SRI International's Enhanced Hierarchical Design Methodology (EHDM) specification/verification system. The methodology utilizes a four-level specification hierarchy with the following levels: functional level, finite automata model, block model, and circuit level. The properties of a level are proved as theorems in the level below it. This methodology is applied to a 6-bit counter problem and is critically examined. The specifications are written in EHDM's specification language, Extended Special, and the proofs are improving both the RSRE methodology and the EHDM system.

Modeling Heterogeneity in Relationships between Initial Status and Rates of Change: Latent Variable Regression in a Three-Level Hierarchical Model. CSE Report 647

ERIC Educational Resources Information Center

Choi, Kilchan; Seltzer, Michael

2005-01-01

In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a time period of substantive interest relate to differences in subsequent change. This report presents a fully Bayesian approach to estimating three-level hierarchical models in which latent variable…

Construction of a WMR for trajectory tracking control: experimental results.

PubMed

Silva-Ortigoza, R; Márquez-Sánchez, C; Marcelino-Aranda, M; Marciano-Melchor, M; Silva-Ortigoza, G; Bautista-Quintero, R; Ramos-Silvestre, E R; Rivera-Díaz, J C; Muñoz-Carrillo, D

2013-01-01

This paper reports a solution for trajectory tracking control of a differential drive wheeled mobile robot (WMR) based on a hierarchical approach. The general design and construction of the WMR are described. The hierarchical controller proposed has two components: a high-level control and a low-level control. The high-level control law is based on an input-output linearization scheme for the robot kinematic model, which provides the desired angular velocity profiles that the WMR has to track in order to achieve the desired position (x∗, y∗) and orientation (φ∗). Then, a low-level control law, based on a proportional integral (PI) approach, is designed to control the velocity of the WMR wheels to ensure those tracking features. Regarding the trajectories, this paper provides the solution or the following cases: (1) time-varying parametric trajectories such as straight lines and parabolas and (2) smooth curves fitted by cubic splines which are generated by the desired data points {(x₁∗, y₁∗),..., (x(n)∗, y(n)∗)}. A straightforward algorithm is developed for constructing the cubic splines. Finally, this paper includes an experimental validation of the proposed technique by employing a DS1104 dSPACE electronic board along with MATLAB/Simulink software.

Construction of a WMR for Trajectory Tracking Control: Experimental Results

PubMed Central

Silva-Ortigoza, R.; Márquez-Sánchez, C.; Marcelino-Aranda, M.; Marciano-Melchor, M.; Silva-Ortigoza, G.; Bautista-Quintero, R.; Ramos-Silvestre, E. R.; Rivera-Díaz, J. C.; Muñoz-Carrillo, D.

2013-01-01

This paper reports a solution for trajectory tracking control of a differential drive wheeled mobile robot (WMR) based on a hierarchical approach. The general design and construction of the WMR are described. The hierarchical controller proposed has two components: a high-level control and a low-level control. The high-level control law is based on an input-output linearization scheme for the robot kinematic model, which provides the desired angular velocity profiles that the WMR has to track in order to achieve the desired position (x∗, y∗) and orientation (φ∗). Then, a low-level control law, based on a proportional integral (PI) approach, is designed to control the velocity of the WMR wheels to ensure those tracking features. Regarding the trajectories, this paper provides the solution or the following cases: (1) time-varying parametric trajectories such as straight lines and parabolas and (2) smooth curves fitted by cubic splines which are generated by the desired data points {(x1∗, y1∗),..., (xn∗, yn∗)}. A straightforward algorithm is developed for constructing the cubic splines. Finally, this paper includes an experimental validation of the proposed technique by employing a DS1104 dSPACE electronic board along with MATLAB/Simulink software. PMID:23997679

Inheritance rules for Hierarchical Metadata Based on ISO 19115

NASA Astrophysics Data System (ADS)

Zabala, A.; Masó, J.; Pons, X.

2012-04-01

Mainly, ISO19115 has been used to describe metadata for datasets and services. Furthermore, ISO19115 standard (as well as the new draft ISO19115-1) includes a conceptual model that allows to describe metadata at different levels of granularity structured in hierarchical levels, both in aggregated resources such as particularly series, datasets, and also in more disaggregated resources such as types of entities (feature type), types of attributes (attribute type), entities (feature instances) and attributes (attribute instances). In theory, to apply a complete metadata structure to all hierarchical levels of metadata, from the whole series to an individual feature attributes, is possible, but to store all metadata at all levels is completely impractical. An inheritance mechanism is needed to store each metadata and quality information at the optimum hierarchical level and to allow an ease and efficient documentation of metadata in both an Earth observation scenario such as a multi-satellite mission multiband imagery, as well as in a complex vector topographical map that includes several feature types separated in layers (e.g. administrative limits, contour lines, edification polygons, road lines, etc). Moreover, and due to the traditional split of maps in tiles due to map handling at detailed scales or due to the satellite characteristics, each of the previous thematic layers (e.g. 1:5000 roads for a country) or band (Landsat-5 TM cover of the Earth) are tiled on several parts (sheets or scenes respectively). According to hierarchy in ISO 19115, the definition of general metadata can be supplemented by spatially specific metadata that, when required, either inherits or overrides the general case (G.1.3). Annex H of this standard states that only metadata exceptions are defined at lower levels, so it is not necessary to generate the full registry of metadata for each level but to link particular values to the general value that they inherit. Conceptually the metadata registry is complete for each metadata hierarchical level, but at the implementation level most of the metadata elements are not stored at both levels but only at more generic one. This communication defines a metadata system that covers 4 levels, describes which metadata has to support series-layer inheritance and in which way, and how hierarchical levels are defined and stored. Metadata elements are classified according to the type of inheritance between products, series, tiles and the datasets. It explains the metadata elements classification and exemplifies it using core metadata elements. The communication also presents a metadata viewer and edition tool that uses the described model to propagate metadata elements and to show to the user a complete set of metadata for each level in a transparent way. This tool is integrated in the MiraMon GIS software.

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…

Development of terminology for mammographic techniques for radiological technologists.

PubMed

Yagahara, Ayako; Yokooka, Yuki; Tsuji, Shintaro; Nishimoto, Naoki; Uesugi, Masahito; Muto, Hiroshi; Ohba, Hisateru; Kurowarabi, Kunio; Ogasawara, Katsuhiko

2011-07-01

We are developing a mammographic ontology to share knowledge of the mammographic domain for radiologic technologists, with the aim of improving mammographic techniques. As a first step in constructing the ontology, we used mammography reference books to establish mammographic terminology for identifying currently available knowledge. This study proceeded in three steps: (1) determination of the domain and scope of the terminology, (2) lexical extraction, and (3) construction of hierarchical structures. We extracted terms mainly from three reference books and constructed the hierarchical structures manually. We compared features of the terms extracted from the three reference books. We constructed a terminology consisting of 440 subclasses grouped into 19 top-level classes: anatomic entity, image quality factor, findings, material, risk, breast, histological classification of breast tumors, role, foreign body, mammographic technique, physics, purpose of mammography examination, explanation of mammography examination, image development, abbreviation, quality control, equipment, interpretation, and evaluation of clinical imaging. The number of terms that occurred in the subclasses varied depending on which reference book was used. We developed a terminology of mammographic techniques for radiologic technologists consisting of 440 terms.

Parallel and competitive processes in hierarchical analysis: perceptual grouping and encoding of closure.

PubMed

Han, S; Humphreys, G W; Chen, L

1999-10-01

The role of perceptual grouping and the encoding of closure of local elements in the processing of hierarchical patterns was studied. Experiments 1 and 2 showed a global advantage over the local level for 2 tasks involving the discrimination of orientation and closure, but there was a local advantage for the closure discrimination task relative to the orientation discrimination task. Experiment 3 showed a local precedence effect for the closure discrimination task when local element grouping was weakened by embedding the stimuli from Experiment 1 in a background made up of cross patterns. Experiments 4A and 4B found that dissimilarity of closure between the local elements of hierarchical stimuli and the background figures could facilitate the grouping of closed local elements and enhanced the perception of global structure. Experiment 5 showed that the advantage for detecting the closure of local elements in hierarchical analysis also held under divided- and selective-attention conditions. Results are consistent with the idea that grouping between local elements takes place in parallel and competes with the computation of closure of local elements in determining the selection between global and local levels of hierarchical patterns for response.

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.

PubMed

Kim, Jongin; Lee, Boreom

2018-05-07

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which is likely to be very useful for diagnosis of AD and MCI. Therefore, it is possible to develop a more effective and accurate AD/MCI automatic diagnosis method by integrating complementary information of different modalities. In this paper, we propose multi-modal sparse hierarchical extreme leaning machine (MSH-ELM). We used volume and mean intensity extracted from 93 regions of interest (ROIs) as features of MRI and FDG-PET, respectively, and used p-tau, t-tau, and Aβ42 as CSF features. In detail, high-level representation was individually extracted from each of MRI, FDG-PET, and CSF using a stacked sparse extreme learning machine auto-encoder (sELM-AE). Then, another stacked sELM-AE was devised to acquire a joint hierarchical feature representation by fusing the high-level representations obtained from each modality. Finally, we classified joint hierarchical feature representation using a kernel-based extreme learning machine (KELM). The results of MSH-ELM were compared with those of conventional ELM, single kernel support vector machine (SK-SVM), multiple kernel support vector machine (MK-SVM) and stacked auto-encoder (SAE). Performance was evaluated through 10-fold cross-validation. In the classification of AD vs. HC and MCI vs. HC problem, the proposed MSH-ELM method showed mean balanced accuracies of 96.10% and 86.46%, respectively, which is much better than those of competing methods. In summary, the proposed algorithm exhibits consistently better performance than SK-SVM, ELM, MK-SVM and SAE in the two binary classification problems (AD vs. HC and MCI vs. HC). © 2018 Wiley Periodicals, Inc.

Delineating the joint hierarchical structure of clinical and personality disorders in an outpatient psychiatric sample.

PubMed

Forbes, Miriam K; Kotov, Roman; Ruggero, Camilo J; Watson, David; Zimmerman, Mark; Krueger, Robert F

2017-11-01

A large body of research has focused on identifying the optimal number of dimensions - or spectra - to model individual differences in psychopathology. Recently, it has become increasingly clear that ostensibly competing models with varying numbers of spectra can be synthesized in empirically derived hierarchical structures. We examined the convergence between top-down (bass-ackwards or sequential principal components analysis) and bottom-up (hierarchical agglomerative cluster analysis) statistical methods for elucidating hierarchies to explicate the joint hierarchical structure of clinical and personality disorders. Analyses examined 24 clinical and personality disorders based on semi-structured clinical interviews in an outpatient psychiatric sample (n=2900). The two methods of hierarchical analysis converged on a three-tier joint hierarchy of psychopathology. At the lowest tier, there were seven spectra - disinhibition, antagonism, core thought disorder, detachment, core internalizing, somatoform, and compulsivity - that emerged in both methods. These spectra were nested under the same three higher-order superspectra in both methods: externalizing, broad thought dysfunction, and broad internalizing. In turn, these three superspectra were nested under a single general psychopathology spectrum, which represented the top tier of the hierarchical structure. The hierarchical structure mirrors and extends upon past research, with the inclusion of a novel compulsivity spectrum, and the finding that psychopathology is organized in three superordinate domains. This hierarchy can thus be used as a flexible and integrative framework to facilitate psychopathology research with varying levels of specificity (i.e., focusing on the optimal level of detailed information, rather than the optimal number of factors). Copyright © 2017 Elsevier Inc. All rights reserved.

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

NASA Technical Reports Server (NTRS)

Tilton, James C.

2003-01-01

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

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 performance. PMID:25534671

GA-optimization for rapid prototype system demonstration

NASA Technical Reports Server (NTRS)

Kim, Jinwoo; Zeigler, Bernard P.

1994-01-01

An application of the Genetic Algorithm (GA) is discussed. A novel scheme of Hierarchical GA was developed to solve complicated engineering problems which require optimization of a large number of parameters with high precision. High level GAs search for few parameters which are much more sensitive to the system performance. Low level GAs search in more detail and employ a greater number of parameters for further optimization. Therefore, the complexity of the search is decreased and the computing resources are used more efficiently.

Hierarchical matrices implemented into the boundary integral approaches for gravity field modelling

NASA Astrophysics Data System (ADS)

Čunderlík, Róbert; Vipiana, Francesca

2017-04-01

Boundary integral approaches applied for gravity field modelling have been recently developed to solve the geodetic boundary value problems numerically, or to process satellite observations, e.g. from the GOCE satellite mission. In order to obtain numerical solutions of "cm-level" accuracy, such approaches require very refined level of the disretization or resolution. This leads to enormous memory requirements that need to be reduced. An implementation of the Hierarchical Matrices (H-matrices) can significantly reduce a numerical complexity of these approaches. A main idea of the H-matrices is based on an approximation of the entire system matrix that is split into a family of submatrices. Large submatrices are stored in factorized representation, while small submatrices are stored in standard representation. This allows reducing memory requirements significantly while improving the efficiency. The poster presents our preliminary results of implementations of the H-matrices into the existing boundary integral approaches based on the boundary element method or the method of fundamental solution.

Hierarchy in directed random networks.

PubMed

Mones, Enys

2013-02-01

In recent years, the theory and application of complex networks have been quickly developing in a markable way due to the increasing amount of data from real systems and the fruitful application of powerful methods used in statistical physics. Many important characteristics of social or biological systems can be described by the study of their underlying structure of interactions. Hierarchy is one of these features that can be formulated in the language of networks. In this paper we present some (qualitative) analytic results on the hierarchical properties of random network models with zero correlations and also investigate, mainly numerically, the effects of different types of correlations. The behavior of the hierarchy is different in the absence and the presence of giant components. We show that the hierarchical structure can be drastically different if there are one-point correlations in the network. We also show numerical results suggesting that the hierarchy does not change monotonically with the correlations and there is an optimal level of nonzero correlations maximizing the level of hierarchy.

Latino Adolescents' Civic Development in the United States: Research Results from the IEA Civic Education Study

ERIC Educational Resources Information Center

Torney-Purta, Judith; Barber, Carolyn H.; Wilkenfeld, Britt

2007-01-01

Many studies have reported gaps between Latino and non-Latino adolescents in academic and political outcomes. The current study presents possible explanations for such gaps, both at the individual and school level. Hierarchical linear modeling is employed to examine data from 2,811 American ninth graders (approximately 14 years of age) who had…

Ecological Subregions: Sections and Subsections for the conterminous United States

Treesearch

D.T. Cleland; J.A. Freeouf; J.E. Keys; G.J. Nowacki; C.A. Carpenter; W.H. McNab

2007-01-01

This map and accompanying descriptions were developed through participation with numerous individuals from federal and state agencies and non-governmental organizations using criteria defined in the National Hierarchical Framework of Ecological Units. Delineation generally involved the “top-down approach” of subdividing section level units. A “bottom-up approach” was...

Online or on Campus: A Student Tertiary Education Cost Model Comparing the Two, with a Quality Proviso

ERIC Educational Resources Information Center

Ioakimidis, Marilou

2007-01-01

This paper presents the development and validation of a two-level hierarchical cost model for tertiary education, which enables prospective students to compare the total cost of attending a traditional Baccalaureate degree education with that of the same programme taken through distance e-learning. The model was validated by a sample of Greek…

Development and Validation of Big Four Personality Scales for the Schedule for Nonadaptive and Adaptive Personality-Second Edition (SNAP-2)

ERIC Educational Resources Information Center

Calabrese, William R.; Rudick, Monica M.; Simms, Leonard J.; Clark, Lee Anna

2012-01-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality…

School Effects on Educational Achievement in Mathematics and Science: 1985-86. National Assessment of Educational Progress. Research and Development Report.

ERIC Educational Resources Information Center

Arnold, Carolyn L.; Kaufman, Phillip D.

This report examines the effects of both student and school characteristics on mathematics and science achievement levels in the third, seventh, and eleventh grades using data from the 1985-86 National Assessment of Educational Progress (NAEP). Analyses feature hierarchical linear models (HLM), a regression-like statistical technique that…

The Relationship among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model

ERIC Educational Resources Information Center

Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

2016-01-01

Background: Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. Methods: We used hierarchical linear modeling to examine the link…

Ultrasensitive, Real-time and Discriminative Detection of Improvised Explosives by Chemiresistive Thin-film Sensory Array of Mn2+ Tailored Hierarchical ZnS

NASA Astrophysics Data System (ADS)

Zhou, Chaoyu; Wu, Zhaofeng; Guo, Yanan; Li, Yushu; Cao, Hongyu; Zheng, Xuefang; Dou, Xincun

2016-05-01

A simple method combing Mn2+ doping with a hierarchical structure was developed for the improvement of thin-film sensors and efficient detection of the explosives relevant to improvised explosive devices (IEDs). ZnS hierarchical nanospheres (HNs) were prepared via a solution-based route and their sensing performances were manipulated by Mn2+ doping. The responses of the sensors based on ZnS HNs towards 8 explosives generally increase firstly and then decrease with the increase of the doped Mn2+ concentration, reaching the climate at 5% Mn2+. Furthermore, the sensory array based on ZnS HNs with different doping levels achieved the sensitive and discriminative detection of 6 analytes relevant to IEDs and 2 military explosives in less than 5 s at room temperature. Importantly, the superior sensing performances make ZnS HNs material interesting in the field of chemiresistive sensors, and this simple method could be a very promising strategy to put the sensors based on thin-films of one-dimensional (1D) nanostructures into practical IEDs detection.

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

NASA Astrophysics Data System (ADS)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

Ultrasensitive, Real-time and Discriminative Detection of Improvised Explosives by Chemiresistive Thin-film Sensory Array of Mn2+ Tailored Hierarchical ZnS

PubMed Central

Zhou, Chaoyu; Wu, Zhaofeng; Guo, Yanan; Li, Yushu; Cao, Hongyu; Zheng, Xuefang; Dou, Xincun

2016-01-01

A simple method combing Mn2+ doping with a hierarchical structure was developed for the improvement of thin-film sensors and efficient detection of the explosives relevant to improvised explosive devices (IEDs). ZnS hierarchical nanospheres (HNs) were prepared via a solution-based route and their sensing performances were manipulated by Mn2+ doping. The responses of the sensors based on ZnS HNs towards 8 explosives generally increase firstly and then decrease with the increase of the doped Mn2+ concentration, reaching the climate at 5% Mn2+. Furthermore, the sensory array based on ZnS HNs with different doping levels achieved the sensitive and discriminative detection of 6 analytes relevant to IEDs and 2 military explosives in less than 5 s at room temperature. Importantly, the superior sensing performances make ZnS HNs material interesting in the field of chemiresistive sensors, and this simple method could be a very promising strategy to put the sensors based on thin-films of one-dimensional (1D) nanostructures into practical IEDs detection. PMID:27161193

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

Interpreter composition issues in the formal verification of a processor-memory module

NASA Technical Reports Server (NTRS)

Fura, David A.; Cohen, Gerald C.

1994-01-01

This report describes interpreter composition techniques suitable for the formal specification and verification of a processor-memory module using the HOL theorem proving system. The processor-memory module is a multichip subsystem within a fault-tolerant embedded system under development within the Boeing Defense and Space Group. Modeling and verification methods were developed that permit provably secure composition at the transaction-level of specification, significantly reducing the complexity of the hierarchical verification of the system.

The covariates of parent and youth reporting differences on youth secondary exposure to community violence.

PubMed

Zimmerman, Gregory M

2014-09-01

Survey data for studying youth's secondary exposure to community violence (i.e., witnessing or hearing violence in the community) come from both parents and their children. There are benefits of considering multiple informants in psychosocial assessments, but parents and youths often disagree about comparable information. These reporting differences present challenges for both researchers and clinicians. To shed new light on the individual, family, and neighborhood factors that contribute to parent and youth reporting differences regarding youth's secondary exposure to community violence, this study analyzed hierarchical item response models on a sample of youth respondents from the Project on Human Development in Chicago Neighborhoods. Participants were aged approximately 9, 12, and 15 years (trimodal distribution; mean age = 12.0 years) at baseline (N = 2,344; 49.6% female). Descriptive analyses indicated that parents significantly underestimated their children's exposure to community violence. Logistic hierarchical item response models indicated that absolute discrepancies between parent and youth reports were a function of youth demographic characteristics (male, Hispanic or African American as compared to white, age, 3rd as compared to 1st generation immigrant), individual difference factors (lower levels of self-control, higher levels of violent peer exposure), and family factors (lower household socioeconomic status). Parental under-reporting of youth's exposure to violence was associated with youth demographic characteristics (male, age, 2nd as compared to 3rd generation immigrant), family factors (lower levels of parental supervision), and neighborhood characteristics (higher levels of violence, less access to youth services). The results suggest that a constellation of individual and contextual factors may contribute to the understanding of parent and youth reporting differences. The findings speak to the utility of examining parent and youth reporting differences from a hierarchical lens.

Programming Hierarchical Self-Assembly of Patchy Particles into Colloidal Crystals via Colloidal Molecules.

PubMed

Morphew, Daniel; Shaw, James; Avins, Christopher; Chakrabarti, Dwaipayan

2018-03-27

Colloidal self-assembly is a promising bottom-up route to a wide variety of three-dimensional structures, from clusters to crystals. Programming hierarchical self-assembly of colloidal building blocks, which can give rise to structures ordered at multiple levels to rival biological complexity, poses a multiscale design problem. Here we explore a generic design principle that exploits a hierarchy of interaction strengths and employ this design principle in computer simulations to demonstrate the hierarchical self-assembly of triblock patchy colloidal particles into two distinct colloidal crystals. We obtain cubic diamond and body-centered cubic crystals via distinct clusters of uniform size and shape, namely, tetrahedra and octahedra, respectively. Such a conceptual design framework has the potential to reliably encode hierarchical self-assembly of colloidal particles into a high level of sophistication. Moreover, the design framework underpins a bottom-up route to cubic diamond colloidal crystals, which have remained elusive despite being much sought after for their attractive photonic applications.

New physiologically-relevant liver tissue model based on hierarchically cocultured primary rat hepatocytes with liver endothelial cells.

PubMed

Xiao, Wenjin; Perry, Guillaume; Komori, Kikuo; Sakai, Yasuyuki

2015-11-01

To develop an in vitro liver tissue equivalent, hepatocytes should be cocultured with liver non-parenchymal cells to mimic the in vivo physiological microenvironments. In this work, we describe a physiologically-relevant liver tissue model by hierarchically organizing layers of primary rat hepatocytes and human liver sinusoidal endothelial cells (TMNK-1) on an oxygen-permeable polydimethylsiloxane (PDMS) membrane, which facilitates direct oxygenation by diffusion through the membrane. This in vivo-mimicking hierarchical coculture was obtained by simply proceeding the overlay of TMNK-1 cells on the hepatocyte layer re-formed on the collagen immobilized PDMS membranes. The comparison of hepatic functionalities was achieved between coculture and sandwich culture with Matrigel, in the presence and absence of direct oxygenation. A complete double-layered structure of functional liver cells with vertical contact between hepatocytes and TMNK-1 was successfully constructed in the coculture with direct oxygen supply and was well-maintained for 14 days. The hepatocytes in this hierarchical culture exhibited improved survival, functional bile canaliculi formation, cellular level polarization and maintenance of metabolic activities including Cyp1A1/2 activity and albumin production. By contrast, the two cell populations formed discontinuous monolayers on the same surfaces in the non-oxygen-permeable cultures. These results demonstrate that (i) the direct oxygenation through the PDMS membranes enables very simple formation of a hierarchical structure consisting of a hepatocyte layer and a layer of TMNK-1 and (ii) we may include other non-parenchymal cells in this format easily, which can be widely applicable to other epithelial organs.

Vanishing point: Scale independence in geomorphological hierarchies

NASA Astrophysics Data System (ADS)

Phillips, Jonathan D.

2016-08-01

Scale linkage problems in geosciences are often associated with a hierarchy of components. Both dynamical systems perspectives and intuition suggest that processes or relationships operating at fundamentally different scales are independent with respect to influences on system dynamics. But how far apart is ;fundamentally different;-that is, what is the ;vanishing point; at which scales are no longer interdependent? And how do we reconcile that with the idea (again, supported by both theory and intuition) that we can work our way along scale hierarchies from microscale to planetary (and vice-versa)? Graph and network theory are employed here to address these questions. Analysis of two archetypal hierarchical networks shows low algebraic connectivity, indicating low levels of inferential synchronization. This explains the apparent paradox between scale independence and hierarchical linkages. Incorporating more hierarchical levels results in an increase in complexity or entropy of the network as a whole, but at a nonlinear rate. Complexity increases as a power α of the number of levels in the hierarchy, with α < 1 and usually ≤ 0.6. However, algebraic connectivity decreases at a more rapid rate. Thus, the ability to infer one part of the hierarchical network from other level decays rapidly as more levels are added. Relatedness among system components decreases with differences in scale or resolution, analogous to distance decay in the spatial domain. These findings suggest a strategy of identifying and focusing on the most important or interesting scale levels, rather than attempting to identify the smallest or largest scale levels and work top-down or bottom-up from there. Examples are given from soil geomorphology and karst flow networks.

Ecoregions of the conterminous United States: evolution of a hierarchical spatial framework

USGS Publications Warehouse

Omernik, James M.; Griffith, Glenn E.

2014-01-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Ecoregions of the Conterminous United States: Evolution of a Hierarchical Spatial Framework

NASA Astrophysics Data System (ADS)

Omernik, James M.; Griffith, Glenn E.

2014-12-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Unattended processing of hierarchical pitch variations in spoken sentences.

PubMed

Li, Xiaoqing; Chen, Yiya

2018-05-16

An auditory oddball paradigm was employed to examine the unattended processing of pitch variation which functions to signal hierarchically different levels of meaning contrasts. Four oddball conditions were constructed by varying the pitch contour of critical words embedded in a Mandarin Chinese sentence. Two conditions included lexical-level word meaning contrasts (i.e. TONE condition) and the other two sentence-level information-status contrasts (i.e. ACCENTUATION condition). Both included stimuli with early vs. late acoustic cue divergence points. Results showed that the two early-cue conditions elicited earlier Mismatch Negativities, regardless of their functional hierarchy. The deviant stimuli induced theta-band power increases in the TONE condition but beta-band power decreases in the ACCENTUATIION condition, regardless of the timing of their acoustic cues. These results suggest that, in an unattentive state, the human brain can functionally disentangle hierarchically different levels of pitch variation, and the brain responses to these pitch variations are time-locked to the presence of the acoustic cues. Copyright © 2018. Published by Elsevier Inc.

Modeling Heterogeneity in Relationships between Initial Status and Rates of Change: Treating Latent Variable Regression Coefficients as Random Coefficients in a Three-Level Hierarchical Model

ERIC Educational Resources Information Center

Choi, Kilchan; Seltzer, Michael

2010-01-01

In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…

On the importance of avoiding shortcuts in applying cognitive models to hierarchical data.

PubMed

Boehm, Udo; Marsman, Maarten; Matzke, Dora; Wagenmakers, Eric-Jan

2018-06-12

Psychological experiments often yield data that are hierarchically structured. A number of popular shortcut strategies in cognitive modeling do not properly accommodate this structure and can result in biased conclusions. To gauge the severity of these biases, we conducted a simulation study for a two-group experiment. We first considered a modeling strategy that ignores the hierarchical data structure. In line with theoretical results, our simulations showed that Bayesian and frequentist methods that rely on this strategy are biased towards the null hypothesis. Secondly, we considered a modeling strategy that takes a two-step approach by first obtaining participant-level estimates from a hierarchical cognitive model and subsequently using these estimates in a follow-up statistical test. Methods that rely on this strategy are biased towards the alternative hypothesis. Only hierarchical models of the multilevel data lead to correct conclusions. Our results are particularly relevant for the use of hierarchical Bayesian parameter estimates in cognitive modeling.

Supramolecular structure of polymer binders and composites: targeted control based on the hierarchy

NASA Astrophysics Data System (ADS)

Matveeva, Larisa; Belentsov, Yuri

2017-10-01

The article discusses the problem of targeted control over properties by modifying the supramolecular structure of polymer binders and composites based on their hierarchy. Control over the structure formation of polymers and introduction of modifying additives should be tailored to the specific hierarchical structural levels. Characteristics of polymer materials are associated with structural defects, which also display a hierarchical pattern. Classification of structural defects in polymers is presented. The primary structural level (nano level) of supramolecular formations is of great importance to the reinforcement and regulation of strength characteristics.

Object-based task-level control: A hierarchical control architecture for remote operation of space robots

NASA Technical Reports Server (NTRS)

Stevens, H. D.; Miles, E. S.; Rock, S. J.; Cannon, R. H.

1994-01-01

Expanding man's presence in space requires capable, dexterous robots capable of being controlled from the Earth. Traditional 'hand-in-glove' control paradigms require the human operator to directly control virtually every aspect of the robot's operation. While the human provides excellent judgment and perception, human interaction is limited by low bandwidth, delayed communications. These delays make 'hand-in-glove' operation from Earth impractical. In order to alleviate many of the problems inherent to remote operation, Stanford University's Aerospace Robotics Laboratory (ARL) has developed the Object-Based Task-Level Control architecture. Object-Based Task-Level Control (OBTLC) removes the burden of teleoperation from the human operator and enables execution of tasks not possible with current techniques. OBTLC is a hierarchical approach to control where the human operator is able to specify high-level, object-related tasks through an intuitive graphical user interface. Infrequent task-level command replace constant joystick operations, eliminating communications bandwidth and time delay problems. The details of robot control and task execution are handled entirely by the robot and computer control system. The ARL has implemented the OBTLC architecture on a set of Free-Flying Space Robots. The capability of the OBTLC architecture has been demonstrated by controlling the ARL Free-Flying Space Robots from NASA Ames Research Center.

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…

Template-assisted electrostatic spray deposition as a new route to mesoporous, macroporous, and hierarchically porous oxide films.

PubMed

Sokolov, S; Paul, B; Ortel, E; Fischer, A; Kraehnert, R

2011-03-01

A novel film coating technique, template-assisted electrostatic spray deposition (TAESD), was developed for the synthesis of porous metal oxide films and tested on TiO(2). Organic templates are codeposited with the titania precursor by electrostatic spray deposition and then removed during calcination. Resultant films are highly porous with pores casted by uniformly sized templates, which introduced a new level of control over the pore morphology for the ESD method. Employing the amphiphilic block copolymer Pluronic P123, PMMA latex spheres, or a combination of the two, mesoporous, macroporous, and hierarchically porous TiO(2) films are obtained. Decoupled from other coating parameters, film thickness can be controlled by deposition time or depositing multiple layers while maintaining the coating's structure and integrity.

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

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.

The well-designed hierarchical structure of Musa basjoo for supercapacitors

PubMed Central

Zheng, Kaiwen; Fan, Xiaorong; Mao, Yingzhu; Lin, Jingkai; Dai, Wenxuan; Zhang, Junying; Cheng, Jue

2016-01-01

Application of biological structure is one of the hottest topics in the field of science and technology. The unimaginable and excellent architectures of living beings supporting their vital activities have attracted the interests of worldwide researchers. An intriguing example is Musa basjoo which belongs to the herb, while appears like a tree. The profound mystery of structure and potential application of Musa basjoo have not been probed. Here we show the finding of the hierarchical structure of Musa basjoo and the outstanding electrochemical performance of the super-capacitors fabricated through the simple carbonization of Musa basjoo followed by KOH activation. Musa basjoo has three layers of structure: nanometer-level, micrometer-level and millimeter-level. The nanometer-level structure constructs the micrometer-level structure, while the micrometer-level structure constructs the millimeter-level structure. Based on this hierarchical structure, Musa basjoo reduces the unnecessary weight and therefore supports its huge body. The super-capacitors derived from Musa basjoo display a high specific capacitance and a good cycling stability. This enlightening work opens a window for the applications of the natural structure and we hope that more and more people could pay attention to the bio-inspired materials. PMID:26842714

The well-designed hierarchical structure of Musa basjoo for supercapacitors.

PubMed

Zheng, Kaiwen; Fan, Xiaorong; Mao, Yingzhu; Lin, Jingkai; Dai, Wenxuan; Zhang, Junying; Cheng, Jue

2016-02-04

Application of biological structure is one of the hottest topics in the field of science and technology. The unimaginable and excellent architectures of living beings supporting their vital activities have attracted the interests of worldwide researchers. An intriguing example is Musa basjoo which belongs to the herb, while appears like a tree. The profound mystery of structure and potential application of Musa basjoo have not been probed. Here we show the finding of the hierarchical structure of Musa basjoo and the outstanding electrochemical performance of the super-capacitors fabricated through the simple carbonization of Musa basjoo followed by KOH activation. Musa basjoo has three layers of structure: nanometer-level, micrometer-level and millimeter-level. The nanometer-level structure constructs the micrometer-level structure, while the micrometer-level structure constructs the millimeter-level structure. Based on this hierarchical structure, Musa basjoo reduces the unnecessary weight and therefore supports its huge body. The super-capacitors derived from Musa basjoo display a high specific capacitance and a good cycling stability. This enlightening work opens a window for the applications of the natural structure and we hope that more and more people could pay attention to the bio-inspired materials.

The well-designed hierarchical structure of Musa basjoo for supercapacitors

NASA Astrophysics Data System (ADS)

Zheng, Kaiwen; Fan, Xiaorong; Mao, Yingzhu; Lin, Jingkai; Dai, Wenxuan; Zhang, Junying; Cheng, Jue

2016-02-01

Application of biological structure is one of the hottest topics in the field of science and technology. The unimaginable and excellent architectures of living beings supporting their vital activities have attracted the interests of worldwide researchers. An intriguing example is Musa basjoo which belongs to the herb, while appears like a tree. The profound mystery of structure and potential application of Musa basjoo have not been probed. Here we show the finding of the hierarchical structure of Musa basjoo and the outstanding electrochemical performance of the super-capacitors fabricated through the simple carbonization of Musa basjoo followed by KOH activation. Musa basjoo has three layers of structure: nanometer-level, micrometer-level and millimeter-level. The nanometer-level structure constructs the micrometer-level structure, while the micrometer-level structure constructs the millimeter-level structure. Based on this hierarchical structure, Musa basjoo reduces the unnecessary weight and therefore supports its huge body. The super-capacitors derived from Musa basjoo display a high specific capacitance and a good cycling stability. This enlightening work opens a window for the applications of the natural structure and we hope that more and more people could pay attention to the bio-inspired materials.

Towards a hierarchical optimization framework for spatially targeting incentive policies to promote green infrastructure amidst multiple objectives and uncertainty

EPA Science Inventory

We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of polic...

Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

NASA Astrophysics Data System (ADS)

Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

2017-03-01

Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cook, Diane J.

2008-01-01

Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

NASA Technical Reports Server (NTRS)

Caines, P. E.

1999-01-01

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models.

PubMed

Semmens, Brice X; Ward, Eric J; Moore, Jonathan W; Darimont, Chris T

2009-07-09

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

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...

Measuring Service Quality in Higher Education: Development of a Hierarchical Model (HESQUAL)

ERIC Educational Resources Information Center

Teeroovengadum, Viraiyan; Kamalanabhan, T. J.; Seebaluck, Ashley Keshwar

2016-01-01

Purpose: This paper aims to develop and empirically test a hierarchical model for measuring service quality in higher education. Design/methodology/approach: The first phase of the study consisted of qualitative research methods and a comprehensive literature review, which allowed the development of a conceptual model comprising 53 service quality…

Hierarchical Medical System Based on Big Data and Mobile Internet: A New Strategic Choice in Health Care

PubMed Central

2017-01-01

China is setting up a hierarchical medical system to solve the problems of biased resource allocation and high patient flows to large hospitals. The development of big data and mobile Internet technology provides a new perspective for the establishment of hierarchical medical system. This viewpoint discusses the challenges with the hierarchical medical system in China and how big data and mobile Internet can be used to mitigate these challenges. PMID:28790024

Metacoder: An R package for visualization and manipulation of community taxonomic diversity data.

PubMed

Foster, Zachary S L; Sharpton, Thomas J; Grünwald, Niklaus J

2017-02-01

Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.

Metacoder: An R package for visualization and manipulation of community taxonomic diversity data

PubMed Central

Foster, Zachary S. L.; Sharpton, Thomas J.

2017-01-01

Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual. PMID:28222096

Goleman's Leadership styles at different hierarchical levels in medical education.

PubMed

Saxena, Anurag; Desanghere, Loni; Stobart, Kent; Walker, Keith

2017-09-19

With current emphasis on leadership in medicine, this study explores Goleman's leadership styles of medical education leaders at different hierarchical levels and gain insight into factors that contribute to the appropriateness of practices. Forty two leaders (28 first-level with limited formal authority, eight middle-level with wider program responsibility and six senior- level with higher organizational authority) rank ordered their preferred Goleman's styles and provided comments. Eight additional senior leaders were interviewed in-depth. Differences in ranked styles within groups were determined by Friedman tests and Wilcoxon tests. Based upon style descriptions, confirmatory template analysis was used to identify Goleman's styles for each interviewed participant. Content analysis was used to identify themes that affected leadership styles. There were differences in the repertoire and preferred styles at different leadership levels. As a group, first-level leaders preferred democratic, middle-level used coaching while the senior leaders did not have one preferred style and used multiple styles. Women and men preferred democratic and coaching styles respectively. The varied use of styles reflected leadership conceptualizations, leader accountabilities, contextual adaptations, the situation and its evolution, leaders' awareness of how they themselves were situated, and personal preferences and discomfort with styles. The not uncommon use of pace-setting and commanding styles by senior leaders, who were interviewed, was linked to working with physicians and delivering quickly on outcomes. Leaders at different levels in medical education draw from a repertoire of styles. Leadership development should incorporate learning of different leadership styles, especially at first- and mid-level positions.

Design for testability and diagnosis at the system-level

NASA Technical Reports Server (NTRS)

Simpson, William R.; Sheppard, John W.

1993-01-01

The growing complexity of full-scale systems has surpassed the capabilities of most simulation software to provide detailed models or gate-level failure analyses. The process of system-level diagnosis approaches the fault-isolation problem in a manner that differs significantly from the traditional and exhaustive failure mode search. System-level diagnosis is based on a functional representation of the system. For example, one can exercise one portion of a radar algorithm (the Fast Fourier Transform (FFT) function) by injecting several standard input patterns and comparing the results to standardized output results. An anomalous output would point to one of several items (including the FFT circuit) without specifying the gate or failure mode. For system-level repair, identifying an anomalous chip is sufficient. We describe here an information theoretic and dependency modeling approach that discards much of the detailed physical knowledge about the system and analyzes its information flow and functional interrelationships. The approach relies on group and flow associations and, as such, is hierarchical. Its hierarchical nature allows the approach to be applicable to any level of complexity and to any repair level. This approach has been incorporated in a product called STAMP (System Testability and Maintenance Program) which was developed and refined through more than 10 years of field-level applications to complex system diagnosis. The results have been outstanding, even spectacular in some cases. In this paper we describe system-level testability, system-level diagnoses, and the STAMP analysis approach, as well as a few STAMP applications.

Daily Stressors in School-Age Children: A Multilevel Approach

ERIC Educational Resources Information Center

Escobar, Milagros; Alarcón, Rafael; Blanca, María J.; Fernández-Baena, F. Javier; Rosel, Jesús F.; Trianes, María Victoria

2013-01-01

This study uses hierarchical or multilevel modeling to identify variables that contribute to daily stressors in a population of schoolchildren. Four hierarchical levels with several predictive variables were considered: student (age, sex, social adaptation of the student, number of life events and chronic stressors experienced, and educational…

Exploding the Hierarchical Fallacy: The Significance of Foundation-Level Courses

ERIC Educational Resources Information Center

Maimon, Elaine P.

2017-01-01

Reform in American higher education depends on recognizing freshman courses as the foundation of higher-order thinking and learning. These courses must be recognized for their intellectual significance and their inherent possibilities for multi-disciplinary scholarship. The Maimon Hierarchical Fallacy is a phrase coined by Elaine Maimon to refer…

Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

PubMed Central

Spivak, David I.; Giesa, Tristan; Wood, Elizabeth; Buehler, Markus J.

2011-01-01

Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine. PMID:21931622

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

Hierarchically Nanostructured Materials for Sustainable Environmental Applications

NASA Astrophysics Data System (ADS)

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.

Replication and extension of a hierarchical model of social anxiety and depression: fear of positive evaluation as a key unique factor in social anxiety.

PubMed

Weeks, Justin W

2015-01-01

Wang, Hsu, Chiu, and Liang (2012, Journal of Anxiety Disorders, 26, 215-224) recently proposed a hierarchical model of social interaction anxiety and depression to account for both the commonalities and distinctions between these conditions. In the present paper, this model was extended to more broadly encompass the symptoms of social anxiety disorder, and replicated in a large unselected, undergraduate sample (n = 585). Structural equation modeling (SEM) and hierarchical regression analyses were employed. Negative affect and positive affect were conceptualized as general factors shared by social anxiety and depression; fear of negative evaluation (FNE) and disqualification of positive social outcomes were operationalized as specific factors, and fear of positive evaluation (FPE) was operationalized as a factor unique to social anxiety. This extended hierarchical model explicates structural relationships among these factors, in which the higher-level, general factors (i.e., high negative affect and low positive affect) represent vulnerability markers of both social anxiety and depression, and the lower-level factors (i.e., FNE, disqualification of positive social outcomes, and FPE) are the dimensions of specific cognitive features. Results from SEM and hierarchical regression analyses converged in support of the extended model. FPE is further supported as a key symptom that differentiates social anxiety from depression.

Leadership Behaviors of Management for Complex Adaptive Systems

DTIC Science & Technology

2010-04-01

arson • The Five Dysfunctions of a Team - Patrick M. Lencioni Agile Development Practices • Agile Project Management with Scrum – Ken Schwaber...and down to the individual and team level – Relationships are not defined hierarchically, but rather through interactions across References: Mike...n – Consisting of parts intricately combined © Copyright 2009 Northrop GrummanCopyright 2010 Northrop Grumman 5 Predictable or Adaptive Software/IT

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area.

PubMed

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-07-06

We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995-2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model's performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 μ g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

PubMed Central

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-01-01

We implemented a spatial model for analysing PM10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM10 maxima and the longitude and latitude. The relationship between time and the PM10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM10 maxima presenting levels above 1000 μg/m3 (return period: 25 yr) was observed in the northwestern region of the study area. PMID:28684720

Domains and facets: hierarchical personality assessment using the revised NEO personality inventory.

PubMed

Costa, P T; McCrae, R R

1995-02-01

Personality traits are organized hierarchically, with narrow, specific traits combining to define broad, global factors. The Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 1992c) assesses personality at both levels, with six specific facet scales in each of five broad domains. This article describes conceptual issues in specifying facets of a domain and reports evidence on the validity of NEO-PI-R facet scales. Facet analysis-the interpretation of a scale in terms of the specific facets with which it correlates-is illustrated using alternative measures of the five-factor model and occupational scales. Finally, the hierarchical interpretation of personality profiles is discussed. Interpretation on the domain level yields a rapid understanding of the individual interpretation of specific facet scales gives a more detailed assessment.

Empirical links between instruction with teaching tools and the hierarchical model of intrinsic and extrinsic motivation in a Korean college tennis class.

PubMed

Shin, Myoungjin; Kwon, Sungho

2015-04-01

The objective of this study was to demonstrate the sequential process (i.e., social factors→mediators→motivation→consequences) underlying the Hierarchical Model of Intrinsic and Extrinsic Motivation at the contextual level in instruction using three teaching tools, modified balls, a high net, and colored balls and cones in a college-level tennis class in South Korea. 126 students enrolled in a 15-week tennis class participated in the study. The results indicate that the three teaching tools positively affected students' perceived competence, with perceived competence's beta on intrinsic motivation equal to 0.45. Intrinsic motivation was found to reduce negative affect further by -0.33, thereby demonstrating the sequential process of the Hierarchical Model of Intrinsic and Extrinsic Motivation.

Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

EPA Science Inventory

In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

Emergence of the interplay between hierarchy and contact splitting in biological adhesion highlighted through a hierarchical shear lag model.

PubMed

Brely, Lucas; Bosia, Federico; Pugno, Nicola M

2018-06-20

Contact unit size reduction is a widely studied mechanism as a means to improve adhesion in natural fibrillar systems, such as those observed in beetles or geckos. However, these animals also display complex structural features in the way the contact is subdivided in a hierarchical manner. Here, we study the influence of hierarchical fibrillar architectures on the load distribution over the contact elements of the adhesive system, and the corresponding delamination behaviour. We present an analytical model to derive the load distribution in a fibrillar system loaded in shear, including hierarchical splitting of contacts, i.e. a "hierarchical shear-lag" model that generalizes the well-known shear-lag model used in mechanics. The influence on the detachment process is investigated introducing a numerical procedure that allows the derivation of the maximum delamination force as a function of the considered geometry, including statistical variability of local adhesive energy. Our study suggests that contact splitting generates improved adhesion only in the ideal case of extremely compliant contacts. In real cases, to produce efficient adhesive performance, contact splitting needs to be coupled with hierarchical architectures to counterbalance high load concentrations resulting from contact unit size reduction, generating multiple delamination fronts and helping to avoid detrimental non-uniform load distributions. We show that these results can be summarized in a generalized adhesion scaling scheme for hierarchical structures, proving the beneficial effect of multiple hierarchical levels. The model can thus be used to predict the adhesive performance of hierarchical adhesive structures, as well as the mechanical behaviour of composite materials with hierarchical reinforcements.

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

PubMed Central

Ma, Ming-Guo

2012-01-01

Hierarchically nanosized hydroxyapatite (HA) with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours. Objective The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA) with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks. Methods A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Results HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did not decrease with the increasing concentration of hierarchically nanostructured HA added. Conclusion A novel, simple and reliable hydrothermal route had been developed for the synthesis of hierarchically nanosized HA with flower-like structure assembled from nanosheets consisting of nanorod building blocks. The HA with the hierarchical nanostructure was formed via a soft-template assisted self-assembly mechanism. The hierarchically nanostructured HA has a good biocompatibility and essentially no in-vitro cytotoxicity. PMID:22619527

Chimera states in networks of logistic maps with hierarchical connectivities

NASA Astrophysics Data System (ADS)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

NASA Technical Reports Server (NTRS)

Padovan, Joseph; Krishna, Lala; Gute, Douglas

1997-01-01

Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system

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

Shorikov, A. F., E-mail: afshorikov@mail.ru

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 terminalmore » approach process with incomplete information and give a general scheme for its solving.« less

Unsupervised hierarchical partitioning of hyperspectral images: application to marine algae identification

NASA Astrophysics Data System (ADS)

Chen, B.; Chehdi, K.; De Oliveria, E.; Cariou, C.; Charbonnier, B.

2015-10-01

In this paper a new unsupervised top-down hierarchical classification method to partition airborne hyperspectral images is proposed. The unsupervised approach is preferred because the difficulty of area access and the human and financial resources required to obtain ground truth data, constitute serious handicaps especially over large areas which can be covered by airborne or satellite images. The developed classification approach allows i) a successive partitioning of data into several levels or partitions in which the main classes are first identified, ii) an estimation of the number of classes automatically at each level without any end user help, iii) a nonsystematic subdivision of all classes of a partition Pj to form a partition Pj+1, iv) a stable partitioning result of the same data set from one run of the method to another. The proposed approach was validated on synthetic and real hyperspectral images related to the identification of several marine algae species. In addition to highly accurate and consistent results (correct classification rate over 99%), this approach is completely unsupervised. It estimates at each level, the optimal number of classes and the final partition without any end user intervention.

Intelligibility in microbial complex systems: Wittgenstein and the score of life.

PubMed

Baquero, Fernando; Moya, Andrés

2012-01-01

Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the "score of life" metaphor is more accurate to express the complexity of living systems than the classic "book of life." Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life.

Intelligibility in microbial complex systems: Wittgenstein and the score of life

PubMed Central

Baquero, Fernando; Moya, Andrés

2012-01-01

Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the “score of life” metaphor is more accurate to express the complexity of living systems than the classic “book of life.” Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life. PMID:22919679

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

NASA Technical Reports Server (NTRS)

Cornhill, Dennis; Bharadwaj, Raj; Mylaraswamy, Dinkar

2013-01-01

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

Hierarchical rendering of trees from precomputed multi-layer z-buffers

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

Max, N.

1996-02-01

Chen and Williams show how precomputed z-buffer images from different fixed viewing positions can be reprojected to produce an image for a new viewpoint. Here images are precomputed for twigs and branches at various levels in the hierarchical structure of a tree, and adaptively combined, depending on the position of the new viewpoint. The precomputed images contain multiple z levels to avoid missing pixels in the reconstruction, subpixel masks for anti-aliasing, and colors and normals for shading after reprojection.

Radiation efficiency of earthquake sources at different hierarchical levels

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

Kocharyan, G. G., E-mail: gevorgkidg@mail.ru; Moscow Institute of Physics and Technology

Such factors as earthquake size and its mechanism define common trends in alteration of radiation efficiency. The macroscopic parameter that controls the efficiency of a seismic source is stiffness of fault or fracture. The regularities of this parameter alteration with scale define several hierarchical levels, within which earthquake characteristics obey different laws. Small variations of physical and mechanical properties of the fault principal slip zone can lead to dramatic differences both in the amplitude of released stress and in the amount of radiated energy.

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

PubMed

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

2015-05-01

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

Vectorization for Molecular Dynamics on Intel Xeon Phi Corpocessors

NASA Astrophysics Data System (ADS)

Yi, Hongsuk

2014-03-01

Many modern processors are capable of exploiting data-level parallelism through the use of single instruction multiple data (SIMD) execution. The new Intel Xeon Phi coprocessor supports 512 bit vector registers for the high performance computing. In this paper, we have developed a hierarchical parallelization scheme for accelerated molecular dynamics simulations with the Terfoff potentials for covalent bond solid crystals on Intel Xeon Phi coprocessor systems. The scheme exploits multi-level parallelism computing. We combine thread-level parallelism using a tightly coupled thread-level and task-level parallelism with 512-bit vector register. The simulation results show that the parallel performance of SIMD implementations on Xeon Phi is apparently superior to their x86 CPU architecture.

Syntax in language and music: what is the right level of comparison?

PubMed Central

Asano, Rie; Boeckx, Cedric

2015-01-01

It is often claimed that music and language share a process of hierarchical structure building, a mental “syntax.” Although several lines of research point to commonalities, and possibly a shared syntactic component, differences between “language syntax” and “music syntax” can also be found at several levels: conveyed meaning, and the atoms of combination, for example. To bring music and language closer to one another, some researchers have suggested a comparison between music and phonology (“phonological syntax”), but here too, one quickly arrives at a situation of intriguing similarities and obvious differences. In this paper, we suggest that a fruitful comparison between the two domains could benefit from taking the grammar of action into account. In particular, we suggest that what is called “syntax” can be investigated in terms of goal of action, action planning, motor control, and sensory-motor integration. At this level of comparison, we suggest that some of the differences between language and music could be explained in terms of different goals reflected in the hierarchical structures of action planning: the hierarchical structures of music arise to achieve goals with a strong relation to the affective-gestural system encoding tension-relaxation patterns as well as socio-intentional system, whereas hierarchical structures in language are embedded in a conceptual system that gives rise to compositional meaning. Similarities between music and language are most clear in the way several hierarchical plans for executing action are processed in time and sequentially integrated to achieve various goals. PMID:26191034

Oak Ridge Computerized Hierarchical Information System (ORCHIS) status report, July 1973

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

Brooks, A.A.

1974-01-01

This report summarizes the concepts, software, and contents of the Oak Ridge Computerized Hierarchical Information System. This data analysis and text processing system was developed as an integrated, comprehensive information processing capability to meet the needs of an on-going multidisciplinary research and development organization. (auth)

People, Policy and Process in College-Level Academic Management

ERIC Educational Resources Information Center

Nguyen, Thang N.

2016-01-01

Academic institution structure is both hierarchical and committee-based. It is hierarchical in the Administration including staff, similar to business corporations. It is committee-based for the Faculty body in a fashion similar to US Congress. It can exploit the best of both models for better governance and rightfully democratic decisions. The…

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko

2011-01-01

Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…

Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models

ERIC Educational Resources Information Center

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

2015-01-01

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (S) of group-level varying coefficients are often degenerate. One can do better, even from…

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.

Graphical Methods for Reducing, Visualizing and Analyzing Large Data Sets Using Hierarchical Terminologies

PubMed Central

Jing, Xia; Cimino, James J.

2011-01-01

Objective: To explore new graphical methods for reducing and analyzing large data sets in which the data are coded with a hierarchical terminology. Methods: We use a hierarchical terminology to organize a data set and display it in a graph. We reduce the size and complexity of the data set by considering the terminological structure and the data set itself (using a variety of thresholds) as well as contributions of child level nodes to parent level nodes. Results: We found that our methods can reduce large data sets to manageable size and highlight the differences among graphs. The thresholds used as filters to reduce the data set can be used alone or in combination. We applied our methods to two data sets containing information about how nurses and physicians query online knowledge resources. The reduced graphs make the differences between the two groups readily apparent. Conclusions: This is a new approach to reduce size and complexity of large data sets and to simplify visualization. This approach can be applied to any data sets that are coded with hierarchical terminologies. PMID:22195119

A Bayes network approach to uncertainty quantification in hierarchically developed computational models

DOE PAGES

Urbina, Angel; Mahadevan, Sankaran; Paez, Thomas L.

2012-03-01

Here, performance assessment of complex systems is ideally accomplished through system-level testing, but because they are expensive, such tests are seldom performed. On the other hand, for economic reasons, data from tests on individual components that are parts of complex systems are more readily available. The lack of system-level data leads to a need to build computational models of systems and use them for performance prediction in lieu of experiments. Because their complexity, models are sometimes built in a hierarchical manner, starting with simple components, progressing to collections of components, and finally, to the full system. Quantification of uncertainty inmore » the predicted response of a system model is required in order to establish confidence in the representation of actual system behavior. This paper proposes a framework for the complex, but very practical problem of quantification of uncertainty in system-level model predictions. It is based on Bayes networks and uses the available data at multiple levels of complexity (i.e., components, subsystem, etc.). Because epistemic sources of uncertainty were shown to be secondary, in this application, aleatoric only uncertainty is included in the present uncertainty quantification. An example showing application of the techniques to uncertainty quantification of measures of response of a real, complex aerospace system is included.« less

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Benchmarking in pathology: development of an activity-based costing model.

PubMed

Burnett, Leslie; Wilson, Roger; Pfeffer, Sally; Lowry, John

2012-12-01

Benchmarking in Pathology (BiP) allows pathology laboratories to determine the unit cost of all laboratory tests and procedures, and also provides organisational productivity indices allowing comparisons of performance with other BiP participants. We describe 14 years of progressive enhancement to a BiP program, including the implementation of 'avoidable costs' as the accounting basis for allocation of costs rather than previous approaches using 'total costs'. A hierarchical tree-structured activity-based costing model distributes 'avoidable costs' attributable to the pathology activities component of a pathology laboratory operation. The hierarchical tree model permits costs to be allocated across multiple laboratory sites and organisational structures. This has enabled benchmarking on a number of levels, including test profiles and non-testing related workload activities. The development of methods for dealing with variable cost inputs, allocation of indirect costs using imputation techniques, panels of tests, and blood-bank record keeping, have been successfully integrated into the costing model. A variety of laboratory management reports are produced, including the 'cost per test' of each pathology 'test' output. Benchmarking comparisons may be undertaken at any and all of the 'cost per test' and 'cost per Benchmarking Complexity Unit' level, 'discipline/department' (sub-specialty) level, or overall laboratory/site and organisational levels. We have completed development of a national BiP program. An activity-based costing methodology based on avoidable costs overcomes many problems of previous benchmarking studies based on total costs. The use of benchmarking complexity adjustment permits correction for varying test-mix and diagnostic complexity between laboratories. Use of iterative communication strategies with program participants can overcome many obstacles and lead to innovations.

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 multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

PubMed

Fesharaki, Nooshin Jafari; Pourghassem, Hossein

2013-07-01

Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

Future Concepts for Modular, Intelligent Aerospace Power Systems

NASA Technical Reports Server (NTRS)

Button, Robert M.; Soeder, James F.

2004-01-01

Nasa's resent commitment to Human and Robotic Space Exploration obviates the need for more affordable and sustainable systems and missions. Increased use of modularity and on-board intelligent technologies will enable these lofty goals. To support this new paradigm, an advanced technology program to develop modular, intelligent power management and distribution (PMAD) system technologies is presented. The many benefits to developing and including modular functionality in electrical power components and systems are shown to include lower costs and lower mass for highly reliable systems. The details of several modular technologies being developed by NASA are presented, broken down into hierarchical levels. Modularity at the device level, including the use of power electronic building blocks, is shown to provide benefits in lowering the development time and costs of new power electronic components.

Understanding movement data and movement processes: current and emerging directions.

PubMed

Schick, Robert S; Loarie, Scott R; Colchero, Fernando; Best, Benjamin D; Boustany, Andre; Conde, Dalia A; Halpin, Patrick N; Joppa, Lucas N; McClellan, Catherine M; Clark, James S

2008-12-01

Animal movement has been the focus on much theoretical and empirical work in ecology over the last 25 years. By studying the causes and consequences of individual movement, ecologists have gained greater insight into the behavior of individuals and the spatial dynamics of populations at increasingly higher levels of organization. In particular, ecologists have focused on the interaction between individuals and their environment in an effort to understand future impacts from habitat loss and climate change. Tools to examine this interaction have included: fractal analysis, first passage time, Lévy flights, multi-behavioral analysis, hidden markov models, and state-space models. Concurrent with the development of movement models has been an increase in the sophistication and availability of hierarchical bayesian models. In this review we bring these two threads together by using hierarchical structures as a framework for reviewing individual models. We synthesize emerging themes in movement ecology, and propose a new hierarchical model for animal movement that builds on these emerging themes. This model moves away from traditional random walks, and instead focuses inference on how moving animals with complex behavior interact with their landscape and make choices about its suitability.

Process Management and Exception Handling in Multiprocessor Operating Systems Using Object-Oriented Design Techniques. Revised Sep. 1988

NASA Technical Reports Server (NTRS)

Russo, Vincent; Johnston, Gary; Campbell, Roy

1988-01-01

The programming of the interrupt handling mechanisms, process switching primitives, scheduling mechanism, and synchronization primitives of an operating system for a multiprocessor require both efficient code in order to support the needs of high- performance or real-time applications and careful organization to facilitate maintenance. Although many advantages have been claimed for object-oriented class hierarchical languages and their corresponding design methodologies, the application of these techniques to the design of the primitives within an operating system has not been widely demonstrated. To investigate the role of class hierarchical design in systems programming, the authors have constructed the Choices multiprocessor operating system architecture the C++ programming language. During the implementation, it was found that many operating system design concerns can be represented advantageously using a class hierarchical approach, including: the separation of mechanism and policy; the organization of an operating system into layers, each of which represents an abstract machine; and the notions of process and exception management. In this paper, we discuss an implementation of the low-level primitives of this system and outline the strategy by which we developed our solution.

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures

PubMed Central

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui

2016-01-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions. PMID:27087704

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures

NASA Astrophysics Data System (ADS)

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui

2016-05-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions.

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures.

PubMed

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A; Huang, Yonggang; Zhang, Yihui

2016-05-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions.

Experiments in Error Propagation within Hierarchal Combat Models

DTIC Science & Technology

2015-09-01

Bayesian Information Criterion CNO Chief of Naval Operations DOE Design of Experiments DOD Department of Defense MANA Map Aware Non-uniform Automata ...ground up” approach. First, it develops a mission-level model for one on one submarine combat in Map Aware Non-uniform Automata (MANA) simulation, an... Automata (MANA), an agent based simulation that can model the different postures of submarines. It feeds the results from MANA into stochastic

Development of Multidisciplinary, Multifidelity Analysis, Integration, and Optimization of Aerospace Vehicles

DTIC Science & Technology

2010-02-27

investigated in more detail. The intermediate level of fidelity, though more expensive, is then used to refine the analysis , add geometric detail, and...design stage is used to further refine the analysis , narrowing the design to a handful of options. Figure 1. Integrated Hierarchical Framework. In...computational structural and computational fluid modeling. For the structural analysis tool we used McIntosh Structural Dynamics’ finite element code CNEVAL

Effects of environmental disturbance on phenotypic variation: an integrated assessment of canalization, developmental stability, modularity, and allometry in lizard head shape.

PubMed

Lazić, Marko M; Carretero, Miguel A; Crnobrnja-Isailović, Jelka; Kaliontzopoulou, Antigoni

2015-01-01

When populations experience suboptimal conditions, the mechanisms involved in the regulation of phenotypic variation can be challenged, resulting in increased phenotypic variance. This kind of disturbance can be diagnosed by using morphometric tools to study morphological patterns at different hierarchical levels and evaluate canalization, developmental stability, integration, modularity, and allometry. We assess the effect of urbanization on phenotypic variation in the common wall lizard (Podarcis muralis) by using geometric morphometrics to assess disturbance to head shape development. The head shapes of urban lizards were more variable and less symmetric, suggesting that urban living is more likely to disturb development. Head shape variation was congruent within and across individuals, which indicated that canalization and developmental stability are two related phenomena in these organisms. Furthermore, urban lizards exhibited smaller mean head sizes, divergent size-shape allometries, and increased deviation from within-group allometric lines. This suggests that mechanisms regulating head shape allometry may also be disrupted. The integrated evaluation of several measures of developmental instability at different hierarchical levels, which provided in this case congruent results, can be a powerful methodological guide for future studies, as it enhances the detection of environmental disturbances on phenotypic variation and aids biological interpretation of the results.

Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

PubMed

Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

2013-03-27

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

Biominerals- hierarchical nanocomposites: the example of bone

PubMed Central

Beniash, Elia

2010-01-01

Many organisms incorporate inorganic solids in their tissues to enhance their functional, primarily mechanical, properties. These mineralized tissues, also called biominerals, are unique organo-mineral nanocomposites, organized at several hierarchical levels, from nano- to macroscale. Unlike man made composite materials, which often are simple physical blends of their components, the organic and inorganic phases in biominerals interface at the molecular level. Although these tissues are made of relatively weak components at ambient conditions, their hierarchical structural organization and intimate interactions between different elements lead to superior mechanical properties. Understanding basic principles of formation, structure and functional properties of these tissues might lead to novel bioinspired strategies for material design and better treatments for diseases of the mineralized tissues. This review focuses on general principles of structural organization, formation and functional properties of biominerals on the example the bone tissues. PMID:20827739

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

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.

Ultrathin Hierarchical Porous Carbon Nanosheets for High-Performance Supercapacitors and Redox Electrolyte Energy Storage.

PubMed

Jayaramulu, Kolleboyina; Dubal, Deepak P; Nagar, Bhawna; Ranc, Vaclav; Tomanec, Ondrej; Petr, Martin; Datta, Kasibhatta Kumara Ramanatha; Zboril, Radek; Gómez-Romero, Pedro; Fischer, Roland A

2018-04-01

The design of advanced high-energy-density supercapacitors requires the design of unique materials that combine hierarchical nanoporous structures with high surface area to facilitate ion transport and excellent electrolyte permeability. Here, shape-controlled 2D nanoporous carbon sheets (NPSs) with graphitic wall structure through the pyrolysis of metal-organic frameworks (MOFs) are developed. As a proof-of-concept application, the obtained NPSs are used as the electrode material for a supercapacitor. The carbon-sheet-based symmetric cell shows an ultrahigh Brunauer-Emmett-Teller (BET)-area-normalized capacitance of 21.4 µF cm -2 (233 F g -1 ), exceeding other carbon-based supercapacitors. The addition of potassium iodide as redox-active species in a sulfuric acid (supporting electrolyte) leads to the ground-breaking enhancement in the energy density up to 90 Wh kg -1 , which is higher than commercial aqueous rechargeable batteries, maintaining its superior power density. Thus, the new material provides a double profits strategy such as battery-level energy and capacitor-level power density. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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.

Collective helicity switching of a DNA-coat assembly

NASA Astrophysics Data System (ADS)

Kim, Yongju; Li, Huichang; He, Ying; Chen, Xi; Ma, Xiaoteng; Lee, Myongsoo

2017-07-01

Hierarchical assemblies of biomolecular subunits can carry out versatile tasks at the cellular level with remarkable spatial and temporal precision. As an example, the collective motion and mutual cooperation between complex protein machines mediate essential functions for life, such as replication, synthesis, degradation, repair and transport. Nucleic acid molecules are far less dynamic than proteins and need to bind to specific proteins to form hierarchical structures. The simplest example of these nucleic acid-based structures is provided by a rod-shaped tobacco mosaic virus, which consists of genetic material surrounded by coat proteins. Inspired by the complexity and hierarchical assembly of viruses, a great deal of effort has been devoted to design similarly constructed artificial viruses. However, such a wrapping approach makes nucleic acid dynamics insensitive to environmental changes. This limitation generally restricts, for example, the amplification of the conformational dynamics between the right-handed B form to the left-handed Z form of double-stranded deoxyribonucleic acid (DNA). Here we report a virus-like hierarchical assembly in which the native DNA and a synthetic coat undergo repeated collective helicity switching triggered by pH change under physiological conditions. We also show that this collective helicity inversion occurs during translocation of the DNA-coat assembly into intracellular compartments. Translating DNA conformational dynamics into a higher level of hierarchical dynamics may provide an approach to create DNA-based nanomachines.

Argument structure hierarchy system and method for facilitating analysis and decision-making processes

DOEpatents

Janssen, Terry

2000-01-01

A system and method for facilitating decision-making comprising a computer program causing linkage of data representing a plurality of argument structure units into a hierarchical argument structure. Each argument structure unit comprises data corresponding to a hypothesis and its corresponding counter-hypothesis, data corresponding to grounds that provide a basis for inference of the hypothesis or its corresponding counter-hypothesis, data corresponding to a warrant linking the grounds to the hypothesis or its corresponding counter-hypothesis, and data corresponding to backing that certifies the warrant. The hierarchical argument structure comprises a top level argument structure unit and a plurality of subordinate level argument structure units. Each of the plurality of subordinate argument structure units comprises at least a portion of the grounds of the argument structure unit to which it is subordinate. Program code located on each of a plurality of remote computers accepts input from one of a plurality of contributors. Each input comprises data corresponding to an argument structure unit in the hierarchical argument structure and supports the hypothesis or its corresponding counter-hypothesis. A second programming code is adapted to combine the inputs into a single hierarchical argument structure. A third computer program code is responsive to the second computer program code and is adapted to represent a degree of support for the hypothesis and its corresponding counter-hypothesis in the single hierarchical argument structure.

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective

PubMed Central

Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure — the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely considered to reflect prefrontal cortical functions. In this paper, we reexamine behavioral hierarchy and its neural substrates from the point of view of recent developments in computational reinforcement learning. Specifically, we consider a set of approaches known collectively as hierarchical reinforcement learning, which extend the reinforcement learning paradigm by allowing the learning agent to aggregate actions into reusable subroutines or skills. A close look at the components of hierarchical reinforcement learning suggests how they might map onto neural structures, in particular regions within the dorsolateral and orbital prefrontal cortex. It also suggests specific ways in which hierarchical reinforcement learning might provide a complement to existing psychological models of hierarchically structured behavior. A particularly important question that hierarchical reinforcement learning brings to the fore is that of how learning identifies new action routines that are likely to provide useful building blocks in solving a wide range of future problems. Here and at many other points, hierarchical reinforcement learning offers an appealing framework for investigating the computational and neural underpinnings of hierarchically structured behavior. PMID:18926527

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.).…

One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events.

PubMed

Heil, Lieke; Kwisthout, Johan; van Pelt, Stan; van Rooij, Iris; Bekkering, Harold

2018-01-01

Evidence is accumulating that our brains process incoming information using top-down predictions. If lower level representations are correctly predicted by higher level representations, this enhances processing. However, if they are incorrectly predicted, additional processing is required at higher levels to "explain away" prediction errors. Here, we explored the potential nature of the models generating such predictions. More specifically, we investigated whether a predictive processing model with a hierarchical structure and causal relations between its levels is able to account for the processing of agent-caused events. In Experiment 1, participants watched animated movies of "experienced" and "novice" bowlers. The results are in line with the idea that prediction errors at a lower level of the hierarchy (i.e., the outcome of how many pins fell down) slow down reporting of information at a higher level (i.e., which agent was throwing the ball). Experiments 2 and 3 suggest that this effect is specific to situations in which the predictor is causally related to the outcome. Overall, the study supports the idea that a hierarchical predictive processing model can account for the processing of observed action outcomes and that the predictions involved are specific to cases where action outcomes can be predicted based on causal knowledge.

Hierarchical nanostructures for functional materials.

PubMed

Qin, Zhao; Buehler, Markus J

2018-07-13

Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.

Hierarchical nanostructures for functional materials

NASA Astrophysics Data System (ADS)

Qin, Zhao; Buehler, Markus J.

2018-07-01

Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1991-01-01

The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Relation between financial market structure and the real economy: comparison between clustering methods.

PubMed

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

2015-01-01

We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

Personality in Chimpanzees (Pan troglodytes): Exploring the Hierarchical Structure and Associations with the Vasopressin V1A Receptor Gene

PubMed Central

Latzman, Robert D.; Hopkins, William D.; Keebaugh, Alaine C.; Young, Larry J.

2014-01-01

One of the major contributions of recent personality psychology is the finding that traits are related to each other in an organized hierarchy. To date, however, researchers have yet to investigate this hierarchy in nonhuman primates. Such investigations are critical in confirming the cross-species nature of trait personality helping to illuminate personality as neurobiologically-based and evolutionarily-derived dimensions of primate disposition. Investigations of potential genetic polymorphisms associated with hierarchical models of personality among nonhuman primates represent a critical first step. The current study examined the hierarchical structure of chimpanzee personality as well as sex-specific associations with a polymorphism in the promoter region of the vasopressin V1a receptor gene (AVPR1A), a gene associated with dispositional traits, among 174 chimpanzees. Results confirmed a hierarchical structure of personality across species and, despite differences in early rearing experiences, suggest a sexually dimorphic role of AVPR1A polymorphisms on hierarchical personality profiles at a higher-order level. PMID:24752497

Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods

PubMed Central

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T.

2015-01-01

We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover, we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging. PMID:25786703

A Graph-Embedding Approach to Hierarchical Visual Word Mergence.

PubMed

Wang, Lei; Liu, Lingqiao; Zhou, Luping

2017-02-01

Appropriately merging visual words are an effective dimension reduction method for the bag-of-visual-words model in image classification. The approach of hierarchically merging visual words has been extensively employed, because it gives a fully determined merging hierarchy. Existing supervised hierarchical merging methods take different approaches and realize the merging process with various formulations. In this paper, we propose a unified hierarchical merging approach built upon the graph-embedding framework. Our approach is able to merge visual words for any scenario, where a preferred structure and an undesired structure are defined, and, therefore, can effectively attend to all kinds of requirements for the word-merging process. In terms of computational efficiency, we show that our algorithm can seamlessly integrate a fast search strategy developed in our previous work and, thus, well maintain the state-of-the-art merging speed. To the best of our survey, the proposed approach is the first one that addresses the hierarchical visual word mergence in such a flexible and unified manner. As demonstrated, it can maintain excellent image classification performance even after a significant dimension reduction, and outperform all the existing comparable visual word-merging methods. In a broad sense, our work provides an open platform for applying, evaluating, and developing new criteria for hierarchical word-merging tasks.

Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions

PubMed Central

Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.

2014-01-01

We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630

Hierarchy concepts: classification and preparation strategies for zeolite containing materials with hierarchical porosity.

PubMed

Schwieger, Wilhelm; Machoke, Albert Gonche; Weissenberger, Tobias; Inayat, Amer; Selvam, Thangaraj; Klumpp, Michael; Inayat, Alexandra

2016-06-13

'Hierarchy' is a property which can be attributed to a manifold of different immaterial systems, such as ideas, items and organisations or material ones like biological systems within living organisms or artificial, man-made constructions. The property 'hierarchy' is mainly characterised by a certain ordering of individual elements relative to each other, often in combination with a certain degree of branching. Especially mass-flow related systems in the natural environment feature special hierarchically branched patterns. This review is a survey into the world of hierarchical systems with special focus on hierarchically porous zeolite materials. A classification of hierarchical porosity is proposed based on the flow distribution pattern within the respective pore systems. In addition, this review might serve as a toolbox providing several synthetic and post-synthetic strategies to prepare zeolitic or zeolite containing material with tailored hierarchical porosity. Very often, such strategies with their underlying principles were developed for improving the performance of the final materials in different technical applications like adsorptive or catalytic processes. In the present review, besides on the hierarchically porous all-zeolite material, special focus is laid on the preparation of zeolitic composite materials with hierarchical porosity capable to face the demands of industrial application.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

PubMed

Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

2018-01-01

In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

PubMed Central

Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

2018-01-01

In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept. PMID:29593521

Integrating concept ontology and multitask learning to achieve more effective classifier training for multilevel image annotation.

PubMed

Fan, Jianping; Gao, Yuli; Luo, Hangzai

2008-03-01

In this paper, we have developed a new scheme for achieving multilevel annotations of large-scale images automatically. To achieve more sufficient representation of various visual properties of the images, both the global visual features and the local visual features are extracted for image content representation. To tackle the problem of huge intraconcept visual diversity, multiple types of kernels are integrated to characterize the diverse visual similarity relationships between the images more precisely, and a multiple kernel learning algorithm is developed for SVM image classifier training. To address the problem of huge interconcept visual similarity, a novel multitask learning algorithm is developed to learn the correlated classifiers for the sibling image concepts under the same parent concept and enhance their discrimination and adaptation power significantly. To tackle the problem of huge intraconcept visual diversity for the image concepts at the higher levels of the concept ontology, a novel hierarchical boosting algorithm is developed to learn their ensemble classifiers hierarchically. In order to assist users on selecting more effective hypotheses for image classifier training, we have developed a novel hyperbolic framework for large-scale image visualization and interactive hypotheses assessment. Our experiments on large-scale image collections have also obtained very positive results.

Building hierarchical models of avian distributions for the State of Georgia

USGS Publications Warehouse

Howell, J.E.; Peterson, J.T.; Conroy, M.J.

2008-01-01

To predict the distributions of breeding birds in the state of Georgia, USA, we built hierarchical models consisting of 4 levels of nested mapping units of decreasing area: 90,000 ha, 3,600 ha, 144 ha, and 5.76 ha. We used the Partners in Flight database of point counts to generate presence and absence data at locations across the state of Georgia for 9 avian species: Acadian flycatcher (Empidonax virescens), brownheaded nuthatch (Sitta pusilla), Carolina wren (Thryothorus ludovicianus), indigo bunting (Passerina cyanea), northern cardinal (Cardinalis cardinalis), prairie warbler (Dendroica discolor), yellow-billed cuckoo (Coccyxus americanus), white-eyed vireo (Vireo griseus), and wood thrush (Hylocichla mustelina). At each location, we estimated hierarchical-level-specific habitat measurements using the Georgia GAP Analysis18 class land cover and other Geographic Information System sources. We created candidate, species-specific occupancy models based on previously reported relationships, and fit these using Markov chain Monte Carlo procedures implemented in OpenBugs. We then created a confidence model set for each species based on Akaike's Information Criterion. We found hierarchical habitat relationships for all species. Three-fold cross-validation estimates of model accuracy indicated an average overall correct classification rate of 60.5%. Comparisons with existing Georgia GAP Analysis models indicated that our models were more accurate overall. Our results provide guidance to wildlife scientists and managers seeking predict avian occurrence as a function of local and landscape-level habitat attributes.

Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks

PubMed Central

Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.

2014-01-01

Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks. PMID:24949877

Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

NASA Astrophysics Data System (ADS)

Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

2017-12-01

We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

Cellulose nanofiber-templated three-dimension TiO 2 hierarchical nanowire network for photoelectrochemical photoanode

Treesearch

Zhaodong Li; Chunhua Yao; Fei Wang; Zhiyong Cai; Xudong Wang

2014-01-01

Three dimensional (3D) nanostructures with extremely large porosity possess a great promise for the development of high-performance energy harvesting storage devices. In this paper, we developed a high-density 3D TiO2 fiber-nanorod (NR) heterostructure for photoelectrochemical (PEC) water splitting. The hierarchical structure was synthesized on a...

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

PubMed Central

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem. PMID:24489491

An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

PubMed

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony--hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092

A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments--a case study for pulmonary diseases.

PubMed

Maragoudakis, Manolis; Lymberopoulos, Dimitrios; Fakotakis, Nikos; Spiropoulos, Kostas

2008-01-01

The present paper extends work on an existing computer-based Decision Support System (DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The extension deals with allowing for a hierarchical decomposition of the task, at different levels of domain granularity, using a novel approach, i.e. Hierarchical Bayesian Networks. The proposed framework uses data from various networking appliances such as mobile phones and wireless medical sensors to establish a ubiquitous environment for medical treatment of pulmonary diseases. Domain knowledge is encoded at the upper levels of the hierarchy, thus making the process of generalization easier to accomplish. The experimental results were carried out under the Pulmonary Department, University Regional Hospital Patras, Patras, Greece. They have supported our initial beliefs about the ability of Bayesian networks to provide an effective, yet semantically-oriented, means of prognosis and reasoning under conditions of uncertainty.

Stability of glassy hierarchical networks

NASA Astrophysics Data System (ADS)

Zamani, M.; Camargo-Forero, L.; Vicsek, T.

2018-02-01

The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

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.

Reducing the complexity of the software design process with object-oriented design

NASA Technical Reports Server (NTRS)

Schuler, M. P.

1991-01-01

Designing software is a complex process. How object-oriented design (OOD), coupled with formalized documentation and tailored object diagraming techniques, can reduce the complexity of the software design process is described and illustrated. The described OOD methodology uses a hierarchical decomposition approach in which parent objects are decomposed into layers of lower level child objects. A method of tracking the assignment of requirements to design components is also included. Increases in the reusability, portability, and maintainability of the resulting products are also discussed. This method was built on a combination of existing technology, teaching experience, consulting experience, and feedback from design method users. The discussed concepts are applicable to hierarchal OOD processes in general. Emphasis is placed on improving the design process by documenting the details of the procedures involved and incorporating improvements into those procedures as they are developed.

An exploratory analysis of treatment completion and client and organizational factors using hierarchical linear modeling.

PubMed

Woodward, Albert; Das, Abhik; Raskin, Ira E; Morgan-Lopez, Antonio A

2006-11-01

Data from the Alcohol and Drug Services Study (ADSS) are used to analyze the structure and operation of the substance abuse treatment industry in the United States. Published literature contains little systematic empirical analysis of the interaction between organizational characteristics and treatment outcomes. This paper addresses that deficit. It develops and tests a hierarchical linear model (HLM) to address questions about the empirical relationship between treatment inputs (industry costs, types and use of counseling and medical personnel, diagnosis mix, patient demographics, and the nature and level of services used in substance abuse treatment), and patient outcomes (retention and treatment completion rates). The paper adds to the literature by demonstrating a direct and statistically significant link between treatment completion and the organizational and staffing structure of the treatment setting. Related reimbursement issues, questions for future analysis, and limitations of the ADSS for this analysis are discussed.

Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

PubMed Central

Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971

Naturalizing Sense of Agency with a Hierarchical Event-Control Approach

PubMed Central

Kumar, Devpriya; Srinivasan, Narayanan

2014-01-01

Unraveling the mechanisms underlying self and agency has been a difficult scientific problem. We argue for an event-control approach for naturalizing the sense of agency by focusing on the role of perception-action regularities present at different hierarchical levels and contributing to the sense of self as an agent. The amount of control at different levels of the control hierarchy determines the sense of agency. The current study investigates this approach in a set of two experiments using a scenario containing multiple agents sharing a common goal where one of the agents is partially controlled by the participant. The participant competed with other agents for achieving the goal and subsequently answered questions on identification (which agent was controlled by the participant), the degree to which they are confident about their identification (sense of identification) and the degree to which the participant believed he/she had control over his/her actions (sense of authorship). Results indicate a hierarchical relationship between goal-level control (higher level) and perceptual-motor control (lower level) for sense of agency. Sense of identification ratings increased with perceptual-motor control when the goal was not completed but did not vary with perceptual-motor control when the goal was completed. Sense of authorship showed a similar interaction effect only in experiment 2 that had only one competing agent unlike the larger number of competing agents in experiment 1. The effect of hierarchical control can also be seen in the misidentification pattern and misidentification was greater with the agent affording greater control. Results from the two studies support the event-control approach in understanding sense of agency as grounded in control. The study also offers a novel paradigm for empirically studying sense of agency and self. PMID:24642834

Parameter Recovery for the 1-P HGLLM with Non-Normally Distributed Level-3 Residuals

ERIC Educational Resources Information Center

Kara, Yusuf; Kamata, Akihito

2017-01-01

A multilevel Rasch model using a hierarchical generalized linear model is one approach to multilevel item response theory (IRT) modeling and is referred to as a one-parameter hierarchical generalized linear logistic model (1-P HGLLM). Although it has the flexibility to model nested structure of data with covariates, the model assumes the normality…

The contribution of genetics and early rearing experiences to hierarchical personality dimensions in chimpanzees (Pan troglodytes).

PubMed

Latzman, Robert D; Freeman, Hani D; Schapiro, Steven J; Hopkins, William D

2015-11-01

A reliable literature finds that traits are related to each other in an organized hierarchy encompassing various conceptualizations of personality (e.g., Big Three, five-factor model). Recent work suggests the potential of a similar organization among our closest nonhuman relative, chimpanzees (Pan troglodytes), with significant links to neurobiology suggesting an evolutionarily and neurobiologically based hierarchical structure of personality. The current study investigated this hierarchical structure, the heritability of the various personality dimensions across levels of the hierarchy, and associations with early social rearing experience in a large sample (N = 238) of socially housed, captive chimpanzees residing in 2 independent colonies of apes. Results provide support for a hierarchical structure of personality in chimpanzees with significant associations with early rearing experiences. Further, heritabilities of the various dimensions varied by early rearing, with affective dimensions found to be significantly heritable among mother-reared apes, whereas personality dimensions were largely independent of relatedness among the nursery-reared apes. Taken together, these findings provide evidence for the influence of both genetic and environmental factors on personality profiles across levels of the hierarchy, supporting the importance of considering environmental variation in models of quantitative trait evolution. (c) 2015 APA, all rights reserved).

The contribution of genetics and early rearing experiences to hierarchical personality dimensions in chimpanzees (Pan troglodytes)

PubMed Central

Latzman, Robert D.; Freeman, Hani D.; Schapiro, Steven J.; Hopkins, William D.

2015-01-01

A reliable literature finds that traits are related to each other in an organized hierarchy encompassing various conceptualizations of personality (e.g., Big Three, Five Factor Model). Recent work suggests the potential of a similar organization among our closest nonhuman relative, chimpanzees (Pan troglodytes), with significant links to neurobiology suggesting an evolutionarily- and neurobiologically-based hierarchical structure of personality. The current study investigated this hierarchical structure, the heritability of the various personality dimensions across levels of the hierarchy, and associations with early social rearing experience in a large sample (N = 238) of socially-housed, captive chimpanzees residing in two independent colonies of apes. Results provide support for a hierarchical structure of personality in chimpanzees with significant associations with early rearing experiences. Further, heritabilities of the various dimensions varied by early rearing, with affective dimensions found to be significantly heritable among mother-reared apes, while personality dimensions were largely independent of relatedness among the nursery-reared apes. Taken together, these findings provide evidence for the influence of both genetic and environmental factors on personality profiles across levels of the hierarchy, supporting the importance of considering environmental variation in models of quantitative trait evolution. PMID:25915132

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

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

NASA Astrophysics Data System (ADS)

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 new integral differential equation for the theoretical inverse problem of 2-D electromagnetic field in a hierarchic inclusion, embedded in the N-layered medium. References: Hachay O.A. et al.(2008 a) Modeling of seismic and electromagnetic field in the hierarchic heterogeneous media. Proceedings of International conference. Ekaterinburg: IGF UB RAS Hachay O.A. et al. (2008 b).Complex electromagnetic and seismic method of research of the crust and Earth's mantle structure. Proceedings of International conference. Ekaterinburg: IGF UB RAS Hachay O.A. et al. (2013) Modeling of electromagnetic and seismic fields in hierarchic heterogeneous media. Bulletin of South Ural State University. Series:"Computational mathematics and Software Engineering". 2: 48-55.

Children inhibit global information when the forest is dense and local information when the forest is sparse.

PubMed

Krakowski, Claire-Sara; Borst, Grégoire; Vidal, Julie; Houdé, Olivier; Poirel, Nicolas

2018-09-01

Visual environments are composed of global shapes and local details that compete for attentional resources. In adults, the global level is processed more rapidly than the local level, and global information must be inhibited in order to process local information when the local information and global information are in conflict. Compared with adults, children present less of a bias toward global visual information and appear to be more sensitive to the density of local elements that constitute the global level. The current study aimed, for the first time, to investigate the key role of inhibition during global/local processing in children. By including two different conditions of global saliency during a negative priming procedure, the results showed that when the global level was salient (dense hierarchical figures), 7-year-old children and adults needed to inhibit the global level to process the local information. However, when the global level was less salient (sparse hierarchical figures), only children needed to inhibit the local level to process the global information. These results confirm a weaker global bias and the greater impact of saliency in children than in adults. Moreover, the results indicate that, regardless of age, inhibition of the most salient hierarchical level is systematically required to select the less salient but more relevant level. These findings have important implications for future research in this area. Copyright © 2018 Elsevier Inc. All rights reserved.

A pollutant load hierarchical allocation method integrated in an environmental capacity management system for Zhushan Bay, Taihu Lake.

PubMed

Liang, Shidong; Jia, Haifeng; Yang, Cong; Melching, Charles; Yuan, Yongping

2015-11-15

An environmental capacity management (ECM) system was developed to help practically implement a Total Maximum Daily Load (TMDL) for a key bay in a highly eutrophic lake in China. The ECM system consists of a simulation platform for pollutant load calculation and a pollutant load hierarchical allocation (PLHA) system. The simulation platform was developed by linking the Environmental Fluid Dynamics Code (EFDC) and Water Quality Analysis Simulation Program (WASP). In the PLHA, pollutant loads were allocated top-down in several levels based on characteristics of the pollutant sources. Different allocation methods could be used for the different levels with the advantages of each method combined over the entire allocation. Zhushan Bay of Taihu Lake, one of the most eutrophic lakes in China, was selected as a case study. The allowable loads of total nitrogen, total phosphorus, ammonia, and chemical oxygen demand were found to be 2122.2, 94.9, 1230.4, and 5260.0 t·yr(-1), respectively. The PLHA for the case study consists of 5 levels. At level 0, loads are allocated to those from the lakeshore direct drainage, atmospheric deposition, internal release, and tributary inflows. At level 1 the loads allocated to tributary inflows are allocated to the 3 tributaries. At level 2, the loads allocated to one inflow tributary are allocated to upstream areas and local sources along the tributary. At level 3, the loads allocated to local sources are allocated to the point and non-point sources from different towns. At level 4, the loads allocated to non-point sources in each town are allocated to different villages. Compared with traditional forms of pollutant load allocation methods, PLHA can combine the advantages of different methods which put different priority weights on equity and efficiency, and the PLHA is easy to understand for stakeholders and more flexible to adjust when applied in practical cases. Copyright © 2015 Elsevier B.V. All rights reserved.

An exactly solvable model of hierarchical self-assembly

NASA Astrophysics Data System (ADS)

Dudowicz, Jacek; Douglas, Jack F.; Freed, Karl F.

2009-06-01

Many living and nonliving structures in the natural world form by hierarchical organization, but physical theories that describe this type of organization are scarce. To address this problem, a model of equilibrium self-assembly is formulated in which dynamically associating species organize into hierarchical structures that preserve their shape at each stage of assembly. In particular, we consider symmetric m-gons that associate at their vertices into Sierpinski gasket structures involving the hierarchical association of triangles, squares, hexagons, etc., at their corner vertices, thereby leading to fractal structures after many generations of assembly. This rather idealized model of hierarchical assembly yields an infinite sequence of self-assembly transitions as the morphology progressively organizes to higher levels of the hierarchy, and these structures coexists at dynamic equilibrium, as found in real hierarchically self-assembling systems such as amyloid fiber forming proteins. Moreover, the transition sharpness progressively grows with increasing m, corresponding to larger and larger loops in the assembled structures. Calculations are provided for several basic thermodynamic properties (including the order parameters for assembly for each stage of the hierarchy, average mass of clusters, specific heat, transition sharpness, etc.) that are required for characterizing the interaction parameters governing this type of self-assembly and for elucidating other basic qualitative aspects of these systems. Our idealized model of hierarchical assembly gives many insights into this ubiquitous type of self-organization process.

The MIL-88A-Derived Fe3O4-Carbon Hierarchical Nanocomposites for Electrochemical Sensing

PubMed Central

Wang, Li; Zhang, Yayun; Li, Xia; Xie, Yingzhen; He, Juan; Yu, Jie; Song, Yonghai

2015-01-01

Metal or metal oxides/carbon nanocomposites with hierarchical superstructures have become one of the most promising functional materials in sensor, catalysis, energy conversion, etc. In this work, novel hierarchical Fe3O4/carbon superstructures have been fabricated based on metal-organic frameworks (MOFs)-derived method. Three kinds of Fe-MOFs (MIL-88A) with different morphologies were prepared beforehand as templates, and then pyrolyzed to fabricate the corresponding novel hierarchical Fe3O4/carbon superstructures. The systematic studies on the thermal decomposition process of the three kinds of MIL-88A and the effect of template morphology on the products were carried out in detail. Scanning electron microscopy, transmission electron microscopy, X-ray powder diffraction, X-ray photoelectron spectroscopy and thermal analysis were employed to investigate the hierarchical Fe3O4/carbon superstructures. Based on these resulted hierarchical Fe3O4/carbon superstructures, a novel and sensitive nonenzymatic N-acetyl cysteine sensor was developed. The porous and hierarchical superstructures and large surface area of the as-formed Fe3O4/carbon superstructures eventually contributed to the good electrocatalytic activity of the prepared sensor towards the oxidation of N-acetyl cysteine. The proposed preparation method of the hierarchical Fe3O4/carbon superstructures is simple, efficient, cheap and easy to mass production. It might open up a new way for hierarchical superstructures preparation. PMID:26387535

Hierarchically partitioned nonlinear equation solvers

NASA Technical Reports Server (NTRS)

Padovan, Joseph

1987-01-01

By partitioning solution space into a number of subspaces, a new multiply constrained partitioned Newton-Raphson nonlinear equation solver is developed. Specifically, for a given iteration, each of the various separate partitions are individually and simultaneously controlled. Due to the generality of the scheme, a hierarchy of partition levels can be employed. For finite-element-type applications, this includes the possibility of degree-of-freedom, nodal, elemental, geometric substructural, material and kinematically nonlinear group controls. It is noted that such partitioning can be continuously updated, depending on solution conditioning. In this context, convergence is ascertained at the individual partition level.

ENEL power generation and transmission control (PGTC) system

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

Galli, F.; Schiavi

1986-08-01

The ENEL (Italian State Power Board) PGTC System has a multi-level architecture which consists of a National Control Center (NCC), eight Area Control Centers (ACC), and Remote Terminal Units (RTU). Remote Control Centers (RCC), representing the third hierarchical level of the control system, will be integrated into the system beginning in 1987. This paper describes the structure of the PGTC system from the remote stations up to the NCC and the main control functions. The method of implementation, the organizational and managerial problems that were faced in the development of the project are also described.

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.

2017-01-01

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

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...

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...

Using Nested Contractions and a Hierarchical Tensor Format To Compute Vibrational Spectra of Molecules with Seven Atoms.

PubMed

Thomas, Phillip S; Carrington, Tucker

2015-12-31

We propose a method for solving the vibrational Schrödinger equation with which one can compute hundreds of energy levels of seven-atom molecules using at most a few gigabytes of memory. It uses nested contractions in conjunction with the reduced-rank block power method (RRBPM) described in J. Chem. Phys. 2014, 140, 174111. Successive basis contractions are organized into a tree, the nodes of which are associated with eigenfunctions of reduced-dimension Hamiltonians. The RRBPM is used recursively to compute eigenfunctions of nodes in bases of products of reduced-dimension eigenfunctions of nodes with fewer coordinates. The corresponding vectors are tensors in what is called CP-format. The final wave functions are therefore represented in a hierarchical CP-format. Computational efficiency and accuracy are significantly improved by representing the Hamiltonian in the same hierarchical format as the wave function. We demonstrate that with this hierarchical RRBPM it is possible to compute energy levels of a 64-D coupled-oscillator model Hamiltonian and also of acetonitrile (CH3CN) and ethylene oxide (C2H4O), for which we use quartic potentials. The most accurate acetonitrile calculation uses 139 MB of memory and takes 3.2 h on a single processor. The most accurate ethylene oxide calculation uses 6.1 GB of memory and takes 14 d on 63 processors. The hierarchical RRBPM shatters the memory barrier that impedes the calculation of vibrational spectra.

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems

PubMed Central

Choo, Benjamin Y.; Adams, Stephen C.; Weiss, Brian A.; Marvel, Jeremy A.; Beling, Peter A.

2017-01-01

The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM leverages and integrates lower-level PHM information such as from a machine or component with hierarchical relationships across the component, machine, work cell, and assembly line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are then made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. To overcome the issue of exponential explosion of complexity associated with describing a large manufacturing system, the AM-PHM methodology takes a hierarchical Markov Decision Process (MDP) approach into describing the system and solving for an optimized policy. A description of the AM-PHM methodology is followed by a simulated industry-inspired example to demonstrate the effectiveness of AM-PHM. PMID:28736651

The VMC Survey. XXIX. Turbulence-controlled Hierarchical Star Formation in the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sun, Ning-Chen; de Grijs, Richard; Cioni, Maria-Rosa L.; Rubele, Stefano; Subramanian, Smitha; van Loon, Jacco Th.; Bekki, Kenji; Bell, Cameron P. M.; Ivanov, Valentin D.; Marconi, Marcella; Muraveva, Tatiana; Oliveira, Joana M.; Ripepi, Vincenzo

2018-05-01

In this paper we report a clustering analysis of upper main-sequence stars in the Small Magellanic Cloud, using data from the VMC survey (the VISTA near-infrared YJK s survey of the Magellanic system). Young stellar structures are identified as surface overdensities on a range of significance levels. They are found to be organized in a hierarchical pattern, such that larger structures at lower significance levels contain smaller ones at higher significance levels. They have very irregular morphologies, with a perimeter–area dimension of 1.44 ± 0.02 for their projected boundaries. They have a power-law mass–size relation, power-law size/mass distributions, and a log-normal surface density distribution. We derive a projected fractal dimension of 1.48 ± 0.03 from the mass–size relation, or of 1.4 ± 0.1 from the size distribution, reflecting significant lumpiness of the young stellar structures. These properties are remarkably similar to those of a turbulent interstellar medium, supporting a scenario of hierarchical star formation regulated by supersonic turbulence.

Testing the apparent resistance of three dominant plants to chronic drought on the Colorado Plateau

USGS Publications Warehouse

Hoover, David L.; Duniway, Michael C.; Belnap, Jayne

2016-01-01

Many drylands, including the south-western United States, are projected to become more water-limited as these regions become warmer and drier with climate change. Such chronic drought may push individual species or plant functional types beyond key thresholds leading to reduced growth or even mortality. Indeed, recent observational and experimental evidence from the Colorado Plateau suggests that C3 grasses are the most vulnerable to chronic drought, while C4 grasses and C3 shrubs appear to have greater resistance.The effects of chronic, or press-drought are predicted to begin at the physiological level and translate up to higher hierarchical levels. To date, the drought resistance of C4grasses and C3 shrubs in this region has been only evaluated at the community level and thus we lack information on whether there are sensitivities to drought at lower hierarchical levels. In this study, we tested the apparent drought resistance of three dominant species (Pleuraphis jamesii, a C4 rhizomatous grass; Coleogyne ramosissima, a C3 drought-deciduous shrub; and Ephedra viridis, a C3 evergreen shrub) to an ongoing experimental press-drought (-35% precipitation) by comparing individual-level responses (ecophysiology and growth dynamics) to community-level responses (plant cover).For all three species, we observed consistent responses across all hierarchical levels:P. jamesii was sensitive to drought across all measured variables, while the shrubsC. ramosissima and E. viridis had little to no responses to the experimental press-drought at any given level.Synthesis. Our findings suggest that the apparent drought resistance at higher hierarchical levels, such as cover, may serve as good proxies for lower-level responses. Furthermore, it appears the shrubs are avoiding drought, possibly by utilizing moisture at deeper soil layers, while the grasses are limited to shallower layers and must endure the drought conditions. Give this differential sensitivity to drought, a future with less precipitation and higher temperatures may increase the dominance of shrubs on the Colorado Plateau, as grasses succumb to chronic water stress.

Applying macromolecular crowding to 3D bioprinting: fabrication of 3D hierarchical porous collagen-based hydrogel constructs.

PubMed

Ng, Wei Long; Goh, Min Hao; Yeong, Wai Yee; Naing, May Win

2018-02-27

Native tissues and/or organs possess complex hierarchical porous structures that confer highly-specific cellular functions. Despite advances in fabrication processes, it is still very challenging to emulate the hierarchical porous collagen architecture found in most native tissues. Hence, the ability to recreate such hierarchical porous structures would result in biomimetic tissue-engineered constructs. Here, a single-step drop-on-demand (DOD) bioprinting strategy is proposed to fabricate hierarchical porous collagen-based hydrogels. Printable macromolecule-based bio-inks (polyvinylpyrrolidone, PVP) have been developed and printed in a DOD manner to manipulate the porosity within the multi-layered collagen-based hydrogels by altering the collagen fibrillogenesis process. The experimental results have indicated that hierarchical porous collagen structures could be achieved by controlling the number of macromolecule-based bio-ink droplets printed on each printed collagen layer. This facile single-step bioprinting process could be useful for the structural design of collagen-based hydrogels for various tissue engineering applications.

CuO-Decorated ZnO Hierarchical Nanostructures as Efficient and Established Sensing Materials for H2S Gas Sensors

PubMed Central

Vuong, Nguyen Minh; Chinh, Nguyen Duc; Huy, Bui The; Lee, Yong-Ill

2016-01-01

Highly sensitive hydrogen sulfide (H2S) gas sensors were developed from CuO-decorated ZnO semiconducting hierarchical nanostructures. The ZnO hierarchical nanostructure was fabricated by an electrospinning method following hydrothermal and heat treatment. CuO decoration of ZnO hierarchical structures was carried out by a wet method. The H2S gas-sensing properties were examined at different working temperatures using various quantities of CuO as the variable. CuO decoration of the ZnO hierarchical structure was observed to promote sensitivity for H2S gas higher than 30 times at low working temperature (200 °C) compared with that in the nondecorated hierarchical structure. The sensing mechanism of the hybrid sensor structure is also discussed. The morphology and characteristics of the samples were examined by scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), UV-vis absorption, photoluminescence (PL), and electrical measurements. PMID:27231026

Using cluster analysis and a classification and regression tree model to developed cover types in the Sky Islands of southeastern Arizona

Treesearch

Jose M. Iniguez; Joseph L. Ganey; Peter J. Daughtery; John D. Bailey

2005-01-01

The objective of this study was to develop a rule based cover type classification system for the forest and woodland vegetation in the Sky Islands of southeastern Arizona. In order to develop such a system we qualitatively and quantitatively compared a hierarchical (Ward’s) and a non-hierarchical (k-means) clustering method. Ecologically, unique groups represented by...

Using cluster analysis and a classification and regression tree model to developed cover types in the Sky Islands of southeastern Arizona [Abstract

Treesearch

Jose M. Iniguez; Joseph L. Ganey; Peter J. Daugherty; John D. Bailey

2005-01-01

The objective of this study was to develop a rule based cover type classification system for the forest and woodland vegetation in the Sky Islands of southeastern Arizona. In order to develop such system we qualitatively and quantitatively compared a hierarchical (Ward’s) and a non-hierarchical (k-means) clustering method. Ecologically, unique groups and plots...

Template-free synthesis of nitrogen-doped hierarchical porous carbons for CO2 adsorption and supercapacitor electrodes.

PubMed

Bing, Xuefeng; Wei, Yanju; Wang, Mei; Xu, Sheng; Long, Donghui; Wang, Jitong; Qiao, Wenming; Ling, Licheng

2017-02-15

Nitrogen-doped hierarchical porous carbons (NHPCs) with controllable nitrogen content were prepared via a template-free method by direct carbonization of melamine-resorcinol-terephthaldehyde networks. The synthetic approach is facile and gentle, resulting in a hierarchical pore structure with modest micropores and well-developed meso-/macropores, and allowing the easy adjusting of the nitrogen content in the carbon framework. The micropore structure was generated within the highly cross-linked networks of polymer chains, while the mesopore and macropore structure were formed from the interconnected 3D gel network. The as-prepared NHPC has a large specific surface area of 1150m 2 ·g -1 , and a high nitrogen content of 14.5wt.%. CO 2 adsorption performances were measured between 0°C and 75°C, and a high adsorption capacity of 3.96mmol·g -1 was achieved at 1bar and 0°C. Moreover, these nitrogen-doped hierarchical porous carbons exhibit a great potential to act as electrode materials for supercapacitors, which could deliver high specific capacitance of 214.0F·g -1 with an excellent rate capability of 74.7% from 0.1 to 10 A·g -1 . The appropriate nitrogen doping and well-developed hierarchical porosity could accelerate the ion diffusion and the frequency response for excellent capacitive performance. This kind of new nitrogen-doped hierarchical porous carbons with controllable hierarchical porosity and chemical composition may have a good potential in the future applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

Genomic analysis of the hierarchical structure of regulatory networks

PubMed Central

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

Multidisciplinary optimization for engineering systems - Achievements and potential

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1989-01-01

The currently common sequential design process for engineering systems is likely to lead to suboptimal designs. Recently developed decomposition methods offer an alternative for coming closer to optimum by breaking the large task of system optimization into smaller, concurrently executed and, yet, coupled tasks, identified with engineering disciplines or subsystems. The hierarchic and non-hierarchic decompositions are discussed and illustrated by examples. An organization of a design process centered on the non-hierarchic decomposition is proposed.

Multidisciplinary optimization for engineering systems: Achievements and potential

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1989-01-01

The currently common sequential design process for engineering systems is likely to lead to suboptimal designs. Recently developed decomposition methods offer an alternative for coming closer to optimum by breaking the large task of system optimization into smaller, concurrently executed and, yet, coupled tasks, identified with engineering disciplines or subsystems. The hierarchic and non-hierarchic decompositions are discussed and illustrated by examples. An organization of a design process centered on the non-hierarchic decomposition is proposed.

A Comparison of a Relational and Nested-Relational IDEF0 Data Model

DTIC Science & Technology

1990-03-01

develop, some of the problems inherent iu the hierarchical 5 model were circumvented by the more sophisticated network model. Like the hierarchical model...uetwork database consists of a collection of records connected via links. Unlike the hierarchical model, the network model allows arbitrary graphs as...opposed to trees. Thus, each node may have everal owners and may, in turn, own any number of other records. The network model provides a lchanism by

Controllable synthesis of layered Co-Ni hydroxide hierarchical structures for high-performance hybrid supercapacitors

NASA Astrophysics Data System (ADS)

Yuan, Peng; Zhang, Ning; Zhang, Dan; Liu, Tao; Chen, Limiao; Ma, Renzhi; Qiu, Guanzhou; Liu, Xiaohe

2016-01-01

A facile solvothermal method is developed for synthesizing layered Co-Ni hydroxide hierarchical structures by using hexamethylenetetramine (HMT) as alkaline reagent. The electrochemical measurements reveal that the specific capacitances of layered bimetallic (Co-Ni) hydroxides are generally superior to those of layered monometallic (Co, Ni) hydroxides. The as-prepared Co0.5Ni0.5 hydroxide hierarchical structures possesses the highest specific capacitance of 1767 F g-1 at a galvanic current density of 1 A g-1 and an outstanding specific capacitance retention of 87% after 1000 cycles. In comparison with the dispersed nanosheets of Co-Ni hydroxide, layered hydroxide hierarchical structures show much superior electrochemical performance. This study provides a promising method to construct hierarchical structures with controllable transition-metal compositions for enhancing the electrochemical performance in hybrid supercapacitors.

Hierarchical Dirichlet process model for gene expression clustering

PubMed Central

2013-01-01

Clustering is an important data processing tool for interpreting microarray data and genomic network inference. In this article, we propose a clustering algorithm based on the hierarchical Dirichlet processes (HDP). The HDP clustering introduces a hierarchical structure in the statistical model which captures the hierarchical features prevalent in biological data such as the gene express data. We develop a Gibbs sampling algorithm based on the Chinese restaurant metaphor for the HDP clustering. We apply the proposed HDP algorithm to both regulatory network segmentation and gene expression clustering. The HDP algorithm is shown to outperform several popular clustering algorithms by revealing the underlying hierarchical structure of the data. For the yeast cell cycle data, we compare the HDP result to the standard result and show that the HDP algorithm provides more information and reduces the unnecessary clustering fragments. PMID:23587447

Hierarchical mechanism of development of wealth and structure for a premodern local society

NASA Astrophysics Data System (ADS)

Matsuo, Miki Y.

2011-06-01

We propose a hierarchical model of social development composed of two associated hierarchies, each of which describes economic and noneconomic activities in society, respectively. The model is designed to explain the development of wealth distribution and social structure over 50 years in a premodern Japanese local society. Data analysis shows that the wealth distribution has a well-known universal power-law tail throughout the observed period, while the Pareto index gradually decreases with time. We further show that the noneconomic social properties, such as the household number, average family size, and number of collaterals in a household, of the local society, also have decreasing or increasing trends throughout the observed period. We show that the hierarchical model consistently demonstrates the correlations of these economic and noneconomic properties.

The Unification of Space Qualified Integrated Circuits by Example of International Space Project GAMMA-400

NASA Astrophysics Data System (ADS)

Bobkov, S. G.; Serdin, O. V.; Arkhangelskiy, A. I.; Arkhangelskaja, I. V.; Suchkov, S. I.; Topchiev, N. P.

The problem of electronic component unification at the different levels (circuits, interfaces, hardware and software) used in space industry is considered. The task of computer systems for space purposes developing is discussed by example of scientific data acquisition system for space project GAMMA-400. The basic characteristics of high reliable and fault tolerant chips developed by SRISA RAS for space applicable computational systems are given. To reduce power consumption and enhance data reliability, embedded system interconnect made hierarchical: upper level is Serial RapidIO 1x or 4x with rate transfer 1.25 Gbaud; next level - SpaceWire with rate transfer up to 400 Mbaud and lower level - MIL-STD-1553B and RS232/RS485. The Ethernet 10/100 is technology interface and provided connection with the previously released modules too. Systems interconnection allows creating different redundancy systems. Designers can develop heterogeneous systems that employ the peer-to-peer networking performance of Serial RapidIO using multiprocessor clusters interconnected by SpaceWire.

A Comprehensive Meta-Analysis of Triple P-Positive Parenting Program Using Hierarchical Linear Modeling: Effectiveness and Moderating Variables

ERIC Educational Resources Information Center

Nowak, Christoph; Heinrichs, Nina

2008-01-01

A meta-analysis encompassing all studies evaluating the impact of the Triple P-Positive Parenting Program on parent and child outcome measures was conducted in an effort to identify variables that moderate the program's effectiveness. Hierarchical linear models (HLM) with three levels of data were employed to analyze effect sizes. The results (N =…

The influence of visual and phonological features on the hemispheric processing of hierarchical Navon letters.

PubMed

Aiello, Marilena; Merola, Sheila; Lasaponara, Stefano; Pinto, Mario; Tomaiuolo, Francesco; Doricchi, Fabrizio

2018-01-31

The possibility of allocating attentional resources to the "global" shape or to the "local" details of pictorial stimuli helps visual processing. Investigations with hierarchical Navon letters, that are large "global" letters made up of small "local" ones, consistently demonstrate a right hemisphere advantage for global processing and a left hemisphere advantage for local processing. Here we investigated how the visual and phonological features of the global and local components of Navon letters influence these hemispheric advantages. In a first study in healthy participants, we contrasted the hemispheric processing of hierarchical letters with global and local items competing for response selection, to the processing of hierarchical letters in which a letter, a false-letter conveying no phonological information or a geometrical shape presented at the unattended level did not compete for response selection. In a second study, we investigated the hemispheric processing of hierarchical stimuli in which global and local letters were both visually and phonologically congruent (e.g. large uppercase G made of smaller uppercase G), visually incongruent and phonologically congruent (e.g. large uppercase G made of small lowercase g) or visually incongruent and phonologically incongruent (e.g. large uppercase G made of small lowercase or uppercase M). In a third study, we administered the same tasks to a right brain damaged patient with a lesion involving pre-striate areas engaged by global processing. The results of the first two experiments showed that the global abilities of the left hemisphere are limited because of its strong susceptibility to interference from local letters even when these are irrelevant to the task. Phonological features played a crucial role in this interference because the interference was entirely maintained also when letters at the global and local level were presented in different uppercase vs. lowercase formats. In contrast, when local features conveyed no phonological information, the left hemisphere showed preserved global processing abilities. These findings were supported by the study of the right brain damaged patient. These results offer a new look at the hemispheric dominance in the attentional processing of the global and local levels of hierarchical stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

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

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

DOE PAGES

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

2016-08-10

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

A hierarchical modeling approach to estimate regional acute health effects of particulate matter sources

PubMed Central

Krall, J. R.; Hackstadt, A. J.; Peng, R. D.

2017-01-01

Exposure to particulate matter (PM) air pollution has been associated with a range of adverse health outcomes, including cardiovascular disease (CVD) hospitalizations and other clinical parameters. Determining which sources of PM, such as traffic or industry, are most associated with adverse health outcomes could help guide future recommendations aimed at reducing harmful pollution exposure for susceptible individuals. Information obtained from multisite studies, which is generally more precise than information from a single location, is critical to understanding how PM impacts health and to informing local strategies for reducing individual-level PM exposure. However, few methods exist to perform multisite studies of PM sources, which are not generally directly observed, and adverse health outcomes. We developed SHARE, a hierarchical modeling approach that facilitates reproducible, multisite epidemiologic studies of PM sources. SHARE is a two-stage approach that first summarizes information about PM sources across multiple sites. Then, this information is used to determine how community-level (i.e. county- or city-level) health effects of PM sources should be pooled to estimate regional-level health effects. SHARE is a type of population value decomposition that aims to separate out regional-level features from site-level data. Unlike previous approaches for multisite epidemiologic studies of PM sources, the SHARE approach allows the specific PM sources identified to vary by site. Using data from 2000–2010 for 63 northeastern US counties, we estimated regional-level health effects associated with short-term exposure to major types of PM sources. We found PM from secondary sulfate, traffic, and metals sources was most associated with CVD hospitalizations. PMID:28098412

Cybermaterials: materials by design and accelerated insertion of materials

NASA Astrophysics Data System (ADS)

Xiong, Wei; Olson, Gregory B.

2016-02-01

Cybermaterials innovation entails an integration of Materials by Design and accelerated insertion of materials (AIM), which transfers studio ideation into industrial manufacturing. By assembling a hierarchical architecture of integrated computational materials design (ICMD) based on materials genomic fundamental databases, the ICMD mechanistic design models accelerate innovation. We here review progress in the development of linkage models of the process-structure-property-performance paradigm, as well as related design accelerating tools. Extending the materials development capability based on phase-level structural control requires more fundamental investment at the level of the Materials Genome, with focus on improving applicable parametric design models and constructing high-quality databases. Future opportunities in materials genomic research serving both Materials by Design and AIM are addressed.

Biological hierarchies and the nature of extinction.

PubMed

Congreve, Curtis R; Falk, Amanda R; Lamsdell, James C

2018-05-01

Hierarchy theory recognises that ecological and evolutionary units occur in a nested and interconnected hierarchical system, with cascading effects occurring between hierarchical levels. Different biological disciplines have routinely come into conflict over the primacy of different forcing mechanisms behind evolutionary and ecological change. These disconnects arise partly from differences in perspective (with some researchers favouring ecological forcing mechanisms while others favour developmental/historical mechanisms), as well as differences in the temporal framework in which workers operate. In particular, long-term palaeontological data often show that large-scale (macro) patterns of evolution are predominantly dictated by shifts in the abiotic environment, while short-term (micro) modern biological studies stress the importance of biotic interactions. We propose that thinking about ecological and evolutionary interactions in a hierarchical framework is a fruitful way to resolve these conflicts. Hierarchy theory suggests that changes occurring at lower hierarchical levels can have unexpected, complex effects at higher scales due to emergent interactions between simple systems. In this way, patterns occurring on short- and long-term time scales are equally valid, as changes that are driven from lower levels will manifest in different forms at higher levels. We propose that the dual hierarchy framework fits well with our current understanding of evolutionary and ecological theory. Furthermore, we describe how this framework can be used to understand major extinction events better. Multi-generational attritional loss of reproductive fitness (MALF) has recently been proposed as the primary mechanism behind extinction events, whereby extinction is explainable solely through processes that result in extirpation of populations through a shutdown of reproduction. While not necessarily explicit, the push to explain extinction through solely population-level dynamics could be used to suggest that environmentally mediated patterns of extinction or slowed speciation across geological time are largely artefacts of poor preservation or a coarse temporal scale. We demonstrate how MALF fits into a hierarchical framework, showing that MALF can be a primary forcing mechanism at lower scales that still results in differential survivorship patterns at the species and clade level which vary depending upon the initial environmental forcing mechanism. Thus, even if MALF is the primary mechanism of extinction across all mass extinction events, the primary environmental cause of these events will still affect the system and result in differential responses. Therefore, patterns at both temporal scales are relevant. © 2017 Cambridge Philosophical Society.

Algorithm for solving of two-level hierarchical minimax program control problem of final state the regional socio-economic system in the presence of risks

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2017-10-01

In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.

An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

PubMed Central

Butun, Ismail; Ra, In-Ho; Sankar, Ravi

2015-01-01

In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

Hierarchical analytical and simulation modelling of human-machine systems with interference

NASA Astrophysics Data System (ADS)

Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.

2017-01-01

The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

PubMed

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Chemical grafting of the superhydrophobic surface on copper with hierarchical microstructure and its formation mechanism

NASA Astrophysics Data System (ADS)

Cai, Junyan; Wang, Shuhui; Zhang, Junhong; Liu, Yang; Hang, Tao; Ling, Huiqin; Li, Ming

2018-04-01

In this paper, a superhydrophobic surface with hierarchical structure was fabricated by chemical deposition of Cu micro-cones array, followed by chemical grafting of poly(methyl methacrylate) (PMMA). Water contact measurements give contact angle of 131.0° on these surfaces after PMMA grafting of 2 min and 165.2° after 6 min. The superhydrophobicity results from two factors: (1) the hierarchical structure due to Cu micro-cones array and the second level structure caused by intergranular corrosion during grafting of PMMA (confirmed by the scanning electron microscopy) and (2) the chemical modification of a low surface energy PMMA layer (confirmed by Fourier transform infrared spectrometer and X-ray photoelectron spectroscopy). In the chemical grafting process, the spontaneous reduction of nitrobenzene diazonium (NBD) tetrafluoroborate not only causes the corrosion of the Cu surface that leads to a hierarchical structure, but also initiates the polymerization of methyl methacrylate (MMA) monomers and thus the low free energy surface. Such a robust approach to fabricate the hierarchical structured surface with superhydrophobicity is expected to have practical application in anti-corrosion industry.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Impacts of forest fragmentation on species richness: a hierarchical approach to community modelling

USGS Publications Warehouse

Zipkin, Elise F.; DeWan, Amielle; Royle, J. Andrew

2009-01-01

1. Species richness is often used as a tool for prioritizing conservation action. One method for predicting richness and other summaries of community structure is to develop species-specific models of occurrence probability based on habitat or landscape characteristics. However, this approach can be challenging for rare or elusive species for which survey data are often sparse. 2. Recent developments have allowed for improved inference about community structure based on species-specific models of occurrence probability, integrated within a hierarchical modelling framework. This framework offers advantages to inference about species richness over typical approaches by accounting for both species-level effects and the aggregated effects of landscape composition on a community as a whole, thus leading to increased precision in estimates of species richness by improving occupancy estimates for all species, including those that were observed infrequently. 3. We developed a hierarchical model to assess the community response of breeding birds in the Hudson River Valley, New York, to habitat fragmentation and analysed the model using a Bayesian approach. 4. The model was designed to estimate species-specific occurrence and the effects of fragment area and edge (as measured through the perimeter and the perimeter/area ratio, P/A), while accounting for imperfect detection of species. 5. We used the fitted model to make predictions of species richness within forest fragments of variable morphology. The model revealed that species richness of the observed bird community was maximized in small forest fragments with a high P/A. However, the number of forest interior species, a subset of the community with high conservation value, was maximized in large fragments with low P/A. 6. Synthesis and applications. Our results demonstrate the importance of understanding the responses of both individual, and groups of species, to environmental heterogeneity while illustrating the utility of hierarchical models for inference about species richness for conservation. This framework can be used to investigate the impacts of land-use change and fragmentation on species or assemblage richness, and to further understand trade-offs in species-specific occupancy probabilities associated with landscape variability.

A Bayesian hierarchical approach to comparative audit for carotid surgery.

PubMed

Kuhan, G; Marshall, E C; Abidia, A F; Chetter, I C; McCollum, P T

2002-12-01

the aim of this study was to illustrate how a Bayesian hierarchical modelling approach can aid the reliable comparison of outcome rates between surgeons. retrospective analysis of prospective and retrospective data. binary outcome data (death/stroke within 30 days), together with information on 15 possible risk factors specific for CEA were available on 836 CEAs performed by four vascular surgeons from 1992-99. The median patient age was 68 (range 38-86) years and 60% were men. the model was developed using the WinBUGS software. After adjusting for patient-level risk factors, a cross-validatory approach was adopted to identify "divergent" performance. A ranking exercise was also carried out. the overall observed 30-day stroke/death rate was 3.9% (33/836). The model found diabetes, stroke and heart disease to be significant risk factors. There was no significant difference between the predicted and observed outcome rates for any surgeon (Bayesian p -value>0.05). Each surgeon had a median rank of 3 with associated 95% CI 1.0-5.0, despite the variability of observed stroke/death rate from 2.9-4.4%. After risk adjustment, there was very little residual between-surgeon variability in outcome rate. Bayesian hierarchical models can help to accurately quantify the uncertainty associated with surgeons' performance and rank.

The contribution of reinforcement sensitivity to the personality-psychopathology hierarchical structure in childhood and adolescence.

PubMed

Slobodskaya, Helena R

2016-11-01

This study examined the contribution of reinforcement sensitivity to the hierarchical structure of child personality and common psychopathology in community samples of parent reports of children aged 2-18 (N = 968) and self-reports of adolescents aged 10-18 (N = 1,543) using the Inventory of Child Individual Differences-Short version (ICID-S), the Strengths and Difficulties Questionnaire (SDQ), and the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). A joint higher-order factor analysis of the ICID-S and SDQ scales suggested a 4-factor solution; congruence coefficients indicated replicability of the factors across the 2 samples at all levels of the personality-psychopathology hierarchy. The canonical correlation analyses indicated that reinforcement sensitivity and personality-psychopathology dimensions shared much of their variance. The main contribution of reinforcement sensitivity was through opposing effects of reward and punishment sensitivities. The superordinate factors Beta and Internalizing were best predicted by reinforcement sensitivity, followed by the Externalizing and Positive personality factors. These findings provide evidence for consistency of the hierarchical structure of personality and common psychopathology across informants and highlight the role of reinforcement systems in the development of normal and abnormal patterns of behavior and affect. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Predictors of mortality in HIV-associated hospitalizations in Portugal: a hierarchical survival model

PubMed Central

Dias, Sara S; Andreozzi, Valeska; Martins, Maria O; Torgal, Jorge

2009-01-01

Background The beneficial effects of highly active antiretroviral therapy, increasing survival and the prevention of AIDS defining illness development are well established. However, the annual Portuguese hospital mortality is still higher than expected. It is crucial to understand the hospitalization behaviour to better allocate resources. This study investigates the predictors of mortality in HIV associated hospitalizations in Portugal through a hierarchical survival model. Methods The study population consists of 12,078 adult discharges from patients with HIV infection diagnosis attended at Portuguese hospitals from 2005–2007 that were registered on the diagnosis-related groups' database. We used discharge and hospital level variables to develop a hierarchical model. The discharge level variables were: age, gender, type of admission, type of diagnoses-related group, related HIV complication, the region of the patient's residence, the number of diagnoses and procedures, the Euclidean distance from hospital to the centroid of the patient's ward, and if patient lived in the hospital's catchment area. The hospital characteristics include size and hospital classification according to the National Health System. Kaplan-Meier plots were used to examine differences in survival curves. Cox proportional hazard models with frailty were applied to identify independent predictors of hospital mortality and to calculate hazard ratios (HR). Results The Cox proportional model with frailty showed that male gender, older patient, great number of diagnoses and pneumonia increased the hazard of HIV related hospital mortality. On the other hand tuberculosis was associated with a reduced risk of death. Central hospital discharge also presents less risk of mortality. The frailty variance was small but statistically significant, indicating hazard ratio heterogeneity among hospitals that varied between 0.67 and 1.34, and resulted in two hospitals with HR different from the average risk. Conclusion The frailty model suggests that there are unmeasured factors affecting mortality in HIV associated hospitalizations. Consequently, for healthcare policy purposes, hospitals should not all be treated in an equal manner. PMID:19627574

Occupancy Modeling for Improved Accuracy and Understanding of Pathogen Prevalence and Dynamics

PubMed Central

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmon Oncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population: Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/ metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%. PMID:25738709

A hierarchical model combining distance sampling and time removal to estimate detection probability during avian point counts

USGS Publications Warehouse

Amundson, Courtney L.; Royle, J. Andrew; Handel, Colleen M.

2014-01-01

Imperfect detection during animal surveys biases estimates of abundance and can lead to improper conclusions regarding distribution and population trends. Farnsworth et al. (2005) developed a combined distance-sampling and time-removal model for point-transect surveys that addresses both availability (the probability that an animal is available for detection; e.g., that a bird sings) and perceptibility (the probability that an observer detects an animal, given that it is available for detection). We developed a hierarchical extension of the combined model that provides an integrated analysis framework for a collection of survey points at which both distance from the observer and time of initial detection are recorded. Implemented in a Bayesian framework, this extension facilitates evaluating covariates on abundance and detection probability, incorporating excess zero counts (i.e. zero-inflation), accounting for spatial autocorrelation, and estimating population density. Species-specific characteristics, such as behavioral displays and territorial dispersion, may lead to different patterns of availability and perceptibility, which may, in turn, influence the performance of such hierarchical models. Therefore, we first test our proposed model using simulated data under different scenarios of availability and perceptibility. We then illustrate its performance with empirical point-transect data for a songbird that consistently produces loud, frequent, primarily auditory signals, the Golden-crowned Sparrow (Zonotrichia atricapilla); and for 2 ptarmigan species (Lagopus spp.) that produce more intermittent, subtle, and primarily visual cues. Data were collected by multiple observers along point transects across a broad landscape in southwest Alaska, so we evaluated point-level covariates on perceptibility (observer and habitat), availability (date within season and time of day), and abundance (habitat, elevation, and slope), and included a nested point-within-transect and park-level effect. Our results suggest that this model can provide insight into the detection process during avian surveys and reduce bias in estimates of relative abundance but is best applied to surveys of species with greater availability (e.g., breeding songbirds).

Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics

USGS Publications Warehouse

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmonOncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population:Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.

Hierarchical and non-hierarchical mineralisation of collagen

PubMed Central

Liu, Yan; Kim, Young-Kyung; Dai, Lin; Li, Nan; Khan, Sara; Pashley, David H.; Tay, Franklin R.

2010-01-01

Biomineralisation of collagen involves functional motifs incorporated in extracellular matrix protein molecules to accomplish the objectives of stabilising amorphous calcium phosphate into nanoprecursors and directing the nucleation and growth of apatite within collagen fibrils. Here we report the use of small inorganic polyphosphate molecules to template hierarchical intrafibrillar apatite assembly in reconstituted collagen in the presence of polyacrylic acid to sequester calcium and phosphate into transient amorphous nanophases. The use of polyphosphate without a sequestration analogue resulted only in randomly-oriented extrafibrillar precipitations along the fibrillar surface. Conversely, the use of polyacrylic acid without a templating analogue resulted only in non-hierarchical intrafibrillar mineralisation with continuous apatite strands instead of discrete crystallites. The ability of using simple non-protein molecules to recapitulate different levels of structural hierarchy in mineralised collagen signifies the ultimate simplicity in Nature’s biomineralisation design principles and challenges the need for using more complex recombinant matrix proteins in bioengineering applications. PMID:21040969

Land classification of the standing stone state forest and state park on the eastern highland rim in Tennessee: the interaction of geology, topography, and soils

Treesearch

Glendon W. Smalley; Carlie McCowan; S. David Todd; Phillip M. Morrissey; J. Andrew McBride

2013-01-01

This paper summarizes the application of a land classification system developed by the senior author to the Standing Stone State Forest and State Park (SSSF&SP) on the Eastern Highland Rim. Landtypes are the most detailed level in the hierarchical system and represent distinct units of the landscape (mapped at a scale of 1:24,000) as defined by climate, geology,...

Bayesian hierarchical models for cost-effectiveness analyses that use data from cluster randomized trials.

PubMed

Grieve, Richard; Nixon, Richard; Thompson, Simon G

2010-01-01

Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.

Problem of two-level hierarchical minimax program control the final state of regional social and economic system with incomplete information

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2016-12-01

In this article we consider a discrete-time dynamical system consisting of a set a controllable objects (region and forming it municipalities). The dynamics each of these is described by the corresponding linear or nonlinear discrete-time recurrent vector relations and its control system consist from two levels: basic level (control level I) that is dominating level and auxiliary level (control level II) that is subordinate level. Both levels have different criterions of functioning and united by information and control connections which defined in advance. In this article we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks vectors. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final states of this system with incomplete information and the general scheme for its solving.

A hierarchical anatomical classification schema for prediction of phenotypic side effects

PubMed Central

Kanji, Rakesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708

Beyond Negative Affectivity: A Hierarchical Model of Global and Transdiagnostic Vulnerabilities for Emotional Disorders.

PubMed

Paulus, Daniel J; Talkovsky, Alexander M; Heggeness, Luke F; Norton, Peter J

2015-01-01

Negative affectivity (NA) has been linked to anxiety and depression (DEP). Identifying the common factors between anxiety and DEP is important when explaining their overlap and comorbidity. However, general factors such as NA tend to have differential relationships with different disorders, suggesting the need to identify mediators in order to explicate these relationships. The current study tests a theoretically and empirically derived hierarchical model of emotional disorders including both a general factor (NA) and transdiagnostic risk factors [anxiety sensitivity (AS) and intolerance of uncertainty (IoU)] using structural equation modeling. AS was tested as a mid-level factor between NA and panic disorder/agoraphobia, while IoU was tested as a mid-level factor between NA and social phobia, generalized anxiety disorder, obsessive-compulsive disorder, and DEP. Data from 642 clinical outpatients with a heterogeneous presentation of emotional disorders were available for analysis. The hierarchical model fits the data adequately. Moreover, while a simplified model removing AS and IoU fits the data well, it resulted in a significant loss of information for all latent disorder constructs. Data were unavailable to estimate post-traumatic stress disorder or specific phobias. Future work will need to extend to other emotional disorders. This study demonstrates the importance of both general factors that link disorders together and semi-specific transdiagnostic factors partially explaining their heterogeneity. Including these mid-level factors in hierarchical models of psychopathology can help account for additional variance and help to clarify the relationship between disorder constructs and NA.

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

PubMed

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

2018-01-01

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

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.

Sparsey™: event recognition via deep hierarchical sparse distributed codes

PubMed Central

Rinkus, Gerard J.

2014-01-01

The visual cortex's hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally) and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes) in each representational field (which we equate with the cortical macrocolumn, “mac”), at each level. In localism, each represented feature/concept/event (hereinafter “item”) is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC) in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac's units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model's core algorithm, which does both storage and retrieval (inference), makes a single pass over all macs on each time step, the overall model's storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge (“Big Data”) problems. A 2010 paper described a nonhierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level), describing novel model principles like progressive critical periods, dynamic modulation of principal cells' activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of spatiotemporal patterns. PMID:25566046

A new classification scheme of European cold-water coral habitats: Implications for ecosystem-based management of the deep sea

NASA Astrophysics Data System (ADS)

Davies, J. S.; Guillaumont, B.; Tempera, F.; Vertino, A.; Beuck, L.; Ólafsdóttir, S. H.; Smith, C. J.; Fosså, J. H.; van den Beld, I. M. J.; Savini, A.; Rengstorf, A.; Bayle, C.; Bourillet, J.-F.; Arnaud-Haond, S.; Grehan, A.

2017-11-01

Cold-water corals (CWC) can form complex structures which provide refuge, nursery grounds and physical support for a diversity of other living organisms. However, irrespectively from such ecological significance, CWCs are still vulnerable to human pressures such as fishing, pollution, ocean acidification and global warming Providing coherent and representative conservation of vulnerable marine ecosystems including CWCs is one of the aims of the Marine Protected Areas networks being implemented across European seas and oceans under the EC Habitats Directive, the Marine Strategy Framework Directive and the OSPAR Convention. In order to adequately represent ecosystem diversity, these initiatives require a standardised habitat classification that organises the variety of biological assemblages and provides consistent and functional criteria to map them across European Seas. One such classification system, EUNIS, enables a broad level classification of the deep sea based on abiotic and geomorphological features. More detailed lower biotope-related levels are currently under-developed, particularly with regards to deep-water habitats (>200 m depth). This paper proposes a hierarchical CWC biotope classification scheme that could be incorporated by existing classification schemes such as EUNIS. The scheme was developed within the EU FP7 project CoralFISH to capture the variability of CWC habitats identified using a wealth of seafloor imagery datasets from across the Northeast Atlantic and Mediterranean. Depending on the resolution of the imagery being interpreted, this hierarchical scheme allows data to be recorded from broad CWC biotope categories down to detailed taxonomy-based levels, thereby providing a flexible yet valuable information level for management. The CWC biotope classification scheme identifies 81 biotopes and highlights the limitations of the classification framework and guidance provided by EUNIS, the EC Habitats Directive, OSPAR and FAO; which largely underrepresent CWC habitats.

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

Testing adaptive toolbox models: a Bayesian hierarchical approach.

PubMed

Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

Simulating the heterogeneity in braided channel belt deposits: 1. A geometric-based methodology and code

NASA Astrophysics Data System (ADS)

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.; Dominic, David F.; Freedman, Vicky L.; Scheibe, Timothy D.; Lunt, Ian A.

2010-04-01

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the kilometer scale to the centimeter scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing of upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in part 1 of this paper. In part 2 (Guin et al., 2010), models generated by the code are presented and evaluated.

The COMPASS study: a longitudinal hierarchical research platform for evaluating natural experiments related to changes in school-level programs, policies and built environment resources.

PubMed

Leatherdale, Scott T; Brown, K Stephen; Carson, Valerie; Childs, Ruth A; Dubin, Joel A; Elliott, Susan J; Faulkner, Guy; Hammond, David; Manske, Steve; Sabiston, Catherine M; Laxer, Rachel E; Bredin, Chad; Thompson-Haile, Audra

2014-04-08

Few researchers have the data required to adequately understand how the school environment impacts youth health behaviour development over time. COMPASS is a prospective cohort study designed to annually collect hierarchical longitudinal data from a sample of 90 secondary schools and the 50,000+ grade 9 to 12 students attending those schools. COMPASS uses a rigorous quasi-experimental design to evaluate how changes in school programs, policies, and/or built environment (BE) characteristics are related to changes in multiple youth health behaviours and outcomes over time. These data will allow for the quasi-experimental evaluation of natural experiments that will occur within schools over the course of COMPASS, providing a means for generating "practice based evidence" in school-based prevention programming. COMPASS is the first study with the infrastructure to robustly evaluate the impact that changes in multiple school-level programs, policies, and BE characteristics within or surrounding a school might have on multiple youth health behaviours or outcomes over time. COMPASS will provide valuable new insight for planning, tailoring and targeting of school-based prevention initiatives where they are most likely to have impact.

Tensegrity I. Cell structure and hierarchical systems biology

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

Simulating the Heterogeneity in Braided Channel Belt Deposits: Part 1. A Geometric-Based Methodology and Code

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

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the km scale to the cm scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing ofmore » upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in Part 1 of this series. In Part 2, models generated by the code are presented and evaluated.« less

Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics.

PubMed

Wu, Hao-Yang; Wang, Yan-Hui; Xie, Qiang; Ke, Yun-Ling; Bu, Wen-Jun

2016-06-17

With the great development of sequencing technologies and systematic methods, our understanding of evolutionary relationships at deeper levels within the tree of life has greatly improved over the last decade. However, the current taxonomic methodology is insufficient to describe the growing levels of diversity in both a standardised and general way due to the limitations of using only morphological traits to describe clades. Herein, we propose the idea of a molecular classification based on hierarchical and discrete amino acid characters. Clades are classified based on the results of phylogenetic analyses and described using amino acids with group specificity in phylograms. Practices based on the recently published phylogenomic datasets of insects together with 15 de novo sequenced transcriptomes in this study demonstrate that such a methodology can accommodate various higher ranks of taxonomy. Such an approach has the advantage of describing organisms in a standard and discrete way within a phylogenetic framework, thereby facilitating the recognition of clades from the view of the whole lineage, as indicated by PhyloCode. By combining identification keys and phylogenies, the molecular classification based on hierarchical and discrete characters may greatly boost the progress of integrative taxonomy.

Multiscale imaging of bone microdamage

PubMed Central

Poundarik, Atharva A.; Vashishth, Deepak

2015-01-01

Bone is a structural and hierarchical composite that exhibits remarkable ability to sustain complex mechanical loading and resist fracture. Bone quality encompasses various attributes of bone matrix from the quality of its material components (type-I collagen, mineral and non-collagenous matrix proteins) and cancellous microarchitecture, to the nature and extent of bone microdamage. Microdamage, produced during loading, manifests in multiple forms across the scales of hierarchy in bone and functions to dissipate energy and avert fracture. Microdamage formation is a key determinant of bone quality, and through a range of biological and physical mechanisms, accumulates with age and disease. Accumulated microdamage in bone decreases bone strength and increases bone’s propensity to fracture. Thus, a thorough assessment of microdamage, across the hierarchical levels of bone, is crucial to better understand bone quality and bone fracture. This review article details multiple imaging modalities that have been used to study and characterize microdamage; from bulk staining techniques originally developed by Harold Frost to assess linear microcracks, to atomic force microscopy, a modality that revealed mechanistic insights into the formation diffuse damage at the ultrastructural level in bone. New automated techniques using imaging modalities such as microcomputed tomography are also presented for a comprehensive overview. PMID:25664772

Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics

PubMed Central

Wu, Hao-Yang; Wang, Yan-Hui; Xie, Qiang; Ke, Yun-Ling; Bu, Wen-Jun

2016-01-01

With the great development of sequencing technologies and systematic methods, our understanding of evolutionary relationships at deeper levels within the tree of life has greatly improved over the last decade. However, the current taxonomic methodology is insufficient to describe the growing levels of diversity in both a standardised and general way due to the limitations of using only morphological traits to describe clades. Herein, we propose the idea of a molecular classification based on hierarchical and discrete amino acid characters. Clades are classified based on the results of phylogenetic analyses and described using amino acids with group specificity in phylograms. Practices based on the recently published phylogenomic datasets of insects together with 15 de novo sequenced transcriptomes in this study demonstrate that such a methodology can accommodate various higher ranks of taxonomy. Such an approach has the advantage of describing organisms in a standard and discrete way within a phylogenetic framework, thereby facilitating the recognition of clades from the view of the whole lineage, as indicated by PhyloCode. By combining identification keys and phylogenies, the molecular classification based on hierarchical and discrete characters may greatly boost the progress of integrative taxonomy. PMID:27312960

Integration of Hierarchical Goal Network Planning and Autonomous Path Planning

DTIC Science & Technology

2016-03-01

Conference on Robotics and Automation (ICRA); 2010 May 3– 7; Anchorage, AK. p. 2902–2908. 4. Ayan NF, Kuter U, Yaman F, Goldman RP. Hotride...DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Automated planning has...world robotic systems. This report documents work to integrate a hierarchical goal network planning algorithm with low-level path planning. The system

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

PubMed

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

2015-02-03

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

Relating memory to functional performance in normal aging to dementia using hierarchical Bayesian cognitive processing models.

PubMed

Shankle, William R; Pooley, James P; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D

2013-01-01

Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.

Hierarchical prediction errors in midbrain and septum during social learning.

PubMed

Diaconescu, Andreea O; Mathys, Christoph; Weber, Lilian A E; Kasper, Lars; Mauer, Jan; Stephan, Klaas E

2017-04-01

Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser's intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser's trustworthiness, respectively, depend on different neuromodulatory systems. Low-level prediction errors (PEs) about advice accuracy not only activated regions known to support 'theory of mind', but also the dopaminergic midbrain. Furthermore, PE responses in ventral striatum were influenced by the Met/Val polymorphism of the Catechol-O-Methyltransferase (COMT) gene. By contrast, high-level PEs ('expected uncertainty') about the adviser's fidelity activated the cholinergic septum. These findings, replicated in both samples, have important implications: They suggest that social learning rests on hierarchically related PEs encoded by midbrain and septum activity, respectively, in the same manner as other forms of learning under volatility. Furthermore, these hierarchical PEs may be broadcast by dopaminergic and cholinergic projections to induce plasticity specifically in cortical areas known to represent beliefs about others. © The Author (2017). Published by Oxford University Press.

Hierarchical prediction errors in midbrain and septum during social learning

PubMed Central

Mathys, Christoph; Weber, Lilian A. E.; Kasper, Lars; Mauer, Jan; Stephan, Klaas E.

2017-01-01

Abstract Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser’s intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser’s trustworthiness, respectively, depend on different neuromodulatory systems. Low-level prediction errors (PEs) about advice accuracy not only activated regions known to support ‘theory of mind’, but also the dopaminergic midbrain. Furthermore, PE responses in ventral striatum were influenced by the Met/Val polymorphism of the Catechol-O-Methyltransferase (COMT) gene. By contrast, high-level PEs (‘expected uncertainty’) about the adviser’s fidelity activated the cholinergic septum. These findings, replicated in both samples, have important implications: They suggest that social learning rests on hierarchically related PEs encoded by midbrain and septum activity, respectively, in the same manner as other forms of learning under volatility. Furthermore, these hierarchical PEs may be broadcast by dopaminergic and cholinergic projections to induce plasticity specifically in cortical areas known to represent beliefs about others. PMID:28119508

A Formal Investigation of Human Spatial Control Skills: Mathematical Formalization, Skill Development, and Skill Assessment

NASA Astrophysics Data System (ADS)

Li, Bin

Spatial control behaviors account for a large proportion of human everyday activities from normal daily tasks, such as reaching for objects, to specialized tasks, such as driving, surgery, or operating equipment. These behaviors involve intensive interactions within internal processes (i.e. cognitive, perceptual, and motor control) and with the physical world. This dissertation builds on a concept of interaction pattern and a hierarchical functional model. Interaction pattern represents a type of behavior synergy that humans coordinates cognitive, perceptual, and motor control processes. It contributes to the construction of the hierarchical functional model that delineates humans spatial control behaviors as the coordination of three functional subsystems: planning, guidance, and tracking/pursuit. This dissertation formalizes and validates these two theories and extends them for the investigation of human spatial control skills encompassing development and assessment. Specifically, this dissertation first presents an overview of studies in human spatial control skills encompassing definition, characteristic, development, and assessment, to provide theoretical evidence for the concept of interaction pattern and the hierarchical functional model. The following, the human experiments for collecting motion and gaze data and techniques to register and classify gaze data, are described. This dissertation then elaborates and mathematically formalizes the hierarchical functional model and the concept of interaction pattern. These theories then enables the construction of a succinct simulation model that can reproduce a variety of human performance with a minimal set of hypotheses. This validates the hierarchical functional model as a normative framework for interpreting human spatial control behaviors. The dissertation then investigates human skill development and captures the emergence of interaction pattern. The final part of the dissertation applies the hierarchical functional model for skill assessment and introduces techniques to capture interaction patterns both from the top down using their geometric features and from the bottom up using their dynamical characteristics. The validity and generality of the skill assessment is illustrated using two the remote-control flight and laparoscopic surgical training experiments.

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)

The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim

2008-01-01

Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

Determination of dynamic modulus master curves for Oklahoma HMA mixtures.

DOT National Transportation Integrated Search

2007-12-01

The Mechanistic-Empirical Pavement Design Guide (M-EPDG) uses a hierarchical approach with three : levels of material characterization for asphalt materials. The first level provides the highest design : reliability and each succeeding level is a dro...

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Yasar, Murat; Tolani, Devendra; Ray, Asok; Shah, Neerav; Litt, Jonathan S.

2004-01-01

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Adaptive Multi-scale PHM for Robotic Assembly Processes

PubMed Central

Choo, Benjamin Y.; Beling, Peter A.; LaViers, Amy E.; Marvel, Jeremy A.; Weiss, Brian A.

2017-01-01

Adaptive multiscale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. As a rule, PHM information is not used in high-level decision-making in manufacturing systems. AM-PHM leverages and integrates component-level PHM information with hierarchical relationships across the component, machine, work cell, and production line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. A description of the AM-PHM methodology with a simulated canonical robotic assembly process is presented. PMID:28664161

RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations

PubMed Central

2012-01-01

Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html. PMID:22531049

Similarity relations in visual search predict rapid visual categorization

PubMed Central

Mohan, Krithika; Arun, S. P.

2012-01-01

How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation. PMID:23092947

Space versus Place in Complex Human-Natural Systems: Spatial and Multi-level Models of Tropical Land Use and Cover Change (LUCC) in Guatemala

PubMed Central

López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew

2013-01-01

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908

Global/local processing of hierarchical visual stimuli in a conflict-choice task by capuchin monkeys (Sapajus spp.).

PubMed

Truppa, Valentina; Carducci, Paola; De Simone, Diego Antonio; Bisazza, Angelo; De Lillo, Carlo

2017-03-01

In the last two decades, comparative research has addressed the issue of how the global and local levels of structure of visual stimuli are processed by different species, using Navon-type hierarchical figures, i.e. smaller local elements that form larger global configurations. Determining whether or not the variety of procedures adopted to test different species with hierarchical figures are equivalent is of crucial importance to ensure comparability of results. Among non-human species, global/local processing has been extensively studied in tufted capuchin monkeys using matching-to-sample tasks with hierarchical patterns. Local dominance has emerged consistently in these New World primates. In the present study, we assessed capuchins' processing of hierarchical stimuli with a method frequently adopted in studies of global/local processing in non-primate species: the conflict-choice task. Different from the matching-to-sample procedure, this task involved processing local and global information retained in long-term memory. Capuchins were trained to discriminate between consistent hierarchical stimuli (similar global and local shape) and then tested with inconsistent hierarchical stimuli (different global and local shapes). We found that capuchins preferred the hierarchical stimuli featuring the correct local elements rather than those with the correct global configuration. This finding confirms that capuchins' local dominance, typically observed using matching-to-sample procedures, is also expressed as a local preference in the conflict-choice task. Our study adds to the growing body of comparative studies on visual grouping functions by demonstrating that the methods most frequently used in the literature on global/local processing produce analogous results irrespective of extent of the involvement of memory processes.

Parameterizations for ensemble Kalman inversion

NASA Astrophysics Data System (ADS)

Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.

2018-05-01

The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the linear span of the initial ensemble. Choice of the parameterization of the unknown field is thus a key component of the success of the method. We demonstrate how both geometric ideas and hierarchical ideas can be used to design effective parameterizations for a number of applied inverse problems arising in electrical impedance tomography, groundwater flow and source inversion. In particular we show how geometric ideas, including the level set method, can be used to reconstruct piecewise continuous fields, and we show how hierarchical methods can be used to learn key parameters in continuous fields, such as length-scales, resulting in improved reconstructions. Geometric and hierarchical ideas are combined in the level set method to find piecewise constant reconstructions with interfaces of unknown topology.

APHiD: Hierarchical Task Placement to Enable a Tapered Fat Tree Topology for Lower Power and Cost in HPC Networks

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

Michelogiannakis, George; Ibrahim, Khaled Z.; Shalf, John

The power and procurement cost of bandwidth in system-wide networks has forced a steady drop in the byte/flop ratio. This trend of computation becoming faster relative to the network is expected to hold. In this paper, we explore how cost-oriented task placement enables reducing the cost of system-wide networks by enabling high performance even on tapered topologies where more bandwidth is provisioned at lower levels. We describe APHiD, an efficient hierarchical placement algorithm that uses new techniques to improve the quality of heuristic solutions and reduces the demand on high-level, expensive bandwidth in hierarchical topologies. We apply APHiD to amore » tapered fat-tree, demonstrating that APHiD maintains application scalability even for severely tapered network configurations. Using simulation, we show that for tapered networks APHiD improves performance by more than 50% over random placement and even 15% in some cases over costlier, state-of-the-art placement algorithms.« less

Corticosterone manipulation reveals differences in hierarchical organization of multidimensional reproductive trade-offs in r-strategist and K-strategist females.

PubMed

Lancaster, L T; Hazard, L C; Clobert, J; Sinervo, B R

2008-03-01

Life history trade-offs are often hierarchical with decisions at one level affecting lower level trade-offs. We investigated trade-off structure in female side-blotched lizards (Uta stansburiana), which exhibit two evolved strategies: yellow-throated females are K-strategists and orange-throated are r-strategists. Corticosterone treatment was predicted to differentially organize these females' reproductive decisions. Corticosterone-treated yellow females suppressed reproduction but survived well, and augmented egg mass without decreasing clutch size. Conversely, corticosterone enhanced mortality and reproductive rates in orange females, and increased egg mass only after lengthy exposure. Corticosterone did not affect post-laying condition, suggesting that corticosterone increased egg mass through enhanced energy acquisition (income breeding). Corticosterone enhanced survival of lightweight females, but decreased survival of heavy females, introducing a foraging vs. predation trade-off. We conclude that rather than being a direct, functional relationship, observed trade-offs between offspring size and number represent evolved differences in hierarchical organization of multidimensional trade-offs, particularly in response to stress.

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

Building the United States National Vegetation Classification

USGS Publications Warehouse

Franklin, S.B.; Faber-Langendoen, D.; Jennings, M.; Keeler-Wolf, T.; Loucks, O.; Peet, R.; Roberts, D.; McKerrow, A.

2012-01-01

The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.

Mean-field hierarchical equations for some A+BC catalytic reaction models

NASA Astrophysics Data System (ADS)

Cortés, Joaquín; Puschmann, Heinrich; Valencia, Eliana

1998-10-01

A mean-field study of the (A+BC→AC+1/2B2) system is developed from hierarchical equations, considering mechanisms that include dissociation, reaction with finite rates, desorption, and diffusion of the adsorbed species. The phase diagrams are compared to Monte Carlo simulations.

Determining object orientation with a hierarchical database of binary synthetic discriminant function filters

NASA Technical Reports Server (NTRS)

Reid, Max B.; Ma, Paul W.; Downie, John D.

1990-01-01

An optical correlation-based system is demonstrated which recognizes an object and determines its angular orientation by traversing a hierarchical data base of binary filters. The data-base architecture is made possible by the development of binary synthetic discriminant function filters.

Hierarchical fameworks for distributional and life history data: Implementation of a new ecoinformatics tool

EPA Science Inventory

Background/Questions/Methods Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuary scale to climate change at a global scale. To address this range of environmental issues, we developed a hierarchical framewor...

[Study of the accidental thymus involution during the formation of hierarchic communities by a novel physical method for recording the social stress].

PubMed

Kulikov, A V; Arkhipova, L V; Kulikov, D A; Smirnova, G N; Kulikova, P A

2013-01-01

A novel method for recording the aggressive behavior in newly formed hierarchic communities has been developed. A temporal and age-related dynamics of the accidental thymus involution in mammals has been studied.

Multicollinearity in hierarchical linear models.

PubMed

Yu, Han; Jiang, Shanhe; Land, Kenneth C

2015-09-01

This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimizing nursing human resource planning in British Columbia.

PubMed

Lavieri, Mariel S; Puterman, Martin L

2009-06-01

This paper describes a linear programming hierarchical planning model that determines the optimal number of nurses to train, promote to management and recruit over a 20 year planning horizon to achieve specified workforce levels. Age dynamics and attrition rates of the nursing workforce are key model components. The model was developed to help policy makers plan a sustainable nursing workforce for British Columbia, Canada. An easy to use interface and considerable flexibility makes it ideal for scenario and "What-If?" analyses.

MANPRINT Methods Monograph: Aiding the Development of Manpower-Based System Evaluation

DTIC Science & Technology

1989-06-01

zone below tree level where threats are known to be (the actual number of threats may vary). Weather conditions are VFR. The helicopter pops up to...12.0 Replace 13.3 Bearing, connecting Inspect 6.2 Replace 6.2 0105 Camshaft Inspect 7.2 Replace 7.2 Cover, cylinder head Inspect .2 (valve cover...matrix to analyze the data and identify task clusters. . Outputs and Use of Cluster Analysis 1. Hierarchical cluster tree (taxonomy) of system tasks will

Hierarchically Parallelized Constrained Nonlinear Solvers with Automated Substructuring

NASA Technical Reports Server (NTRS)

Padovan, Joe; Kwang, Abel

1994-01-01

This paper develops a parallelizable multilevel multiple constrained nonlinear equation solver. The substructuring process is automated to yield appropriately balanced partitioning of each succeeding level. Due to the generality of the procedure,_sequential, as well as partially and fully parallel environments can be handled. This includes both single and multiprocessor assignment per individual partition. Several benchmark examples are presented. These illustrate the robustness of the procedure as well as its capability to yield significant reductions in memory utilization and calculational effort due both to updating and inversion.

A two-level structure for advanced space power system automation

NASA Technical Reports Server (NTRS)

Loparo, Kenneth A.; Chankong, Vira

1990-01-01

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed.

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

Hierarchical competition models with the Allee effect II: the case of immigration.

PubMed

Assas, Laila; Dennis, Brian; Elaydi, Saber; Kwessi, Eddy; Livadiotis, George

2015-01-01

This is part II of an earlier paper that dealt with hierarchical models with the Allee effect but with no immigration. In this paper, we greatly simplify the proofs in part I and provide a proof of the global dynamics of the non-hyperbolic cases that were previously conjectured. Then, we show how immigration to one of the species or to both would, drastically, change the dynamics of the system. It is shown that if the level of immigration to one or to both species is above a specified level, then there will be no extinction region where both species go to extinction.

Distinctive signatures of recursion.

PubMed

Martins, Maurício Dias

2012-07-19

Although recursion has been hypothesized to be a necessary capacity for the evolution of language, the multiplicity of definitions being used has undermined the broader interpretation of empirical results. I propose that only a definition focused on representational abilities allows the prediction of specific behavioural traits that enable us to distinguish recursion from non-recursive iteration and from hierarchical embedding: only subjects able to represent recursion, i.e. to represent different hierarchical dependencies (related by parenthood) with the same set of rules, are able to generalize and produce new levels of embedding beyond those specified a priori (in the algorithm or in the input). The ability to use such representations may be advantageous in several domains: action sequencing, problem-solving, spatial navigation, social navigation and for the emergence of conventionalized communication systems. The ability to represent contiguous hierarchical levels with the same rules may lead subjects to expect unknown levels and constituents to behave similarly, and this prior knowledge may bias learning positively. Finally, a new paradigm to test for recursion is presented. Preliminary results suggest that the ability to represent recursion in the spatial domain recruits both visual and verbal resources. Implications regarding language evolution are discussed.

Anisotropic constitutive model incorporating multiple damage mechanisms for multiscale simulation of dental enamel.

PubMed

Ma, Songyun; Scheider, Ingo; Bargmann, Swantje

2016-09-01

An anisotropic constitutive model is proposed in the framework of finite deformation to capture several damage mechanisms occurring in the microstructure of dental enamel, a hierarchical bio-composite. It provides the basis for a homogenization approach for an efficient multiscale (in this case: multiple hierarchy levels) investigation of the deformation and damage behavior. The influence of tension-compression asymmetry and fiber-matrix interaction on the nonlinear deformation behavior of dental enamel is studied by 3D micromechanical simulations under different loading conditions and fiber lengths. The complex deformation behavior and the characteristics and interaction of three damage mechanisms in the damage process of enamel are well captured. The proposed constitutive model incorporating anisotropic damage is applied to the first hierarchical level of dental enamel and validated by experimental results. The effect of the fiber orientation on the damage behavior and compressive strength is studied by comparing micro-pillar experiments of dental enamel at the first hierarchical level in multiple directions of fiber orientation. A very good agreement between computational and experimental results is found for the damage evolution process of dental enamel. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modes of Interaction between Individuals Dominate the Topologies of Real World Networks

PubMed Central

Lee, Insuk; Kim, Eiru; Marcotte, Edward M.

2015-01-01

We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Specifically, a major dichotomy in previously studied networks arises from modeling networks in terms of pairwise versus group tasks. The former often intrinsically give rise to scale-free, disassortative, hierarchical networks, whereas the latter often give rise to single- or broad-scale, assortative, nonhierarchical networks. These dependencies explain contrasting observations among previous topological analyses of real world complex systems. We also observe this trend in systems with natural hierarchies, in which alternate representations of the same networks, but which capture different levels of the hierarchy, manifest these signature topological differences. For example, in both the Internet and cellular proteomes, networks of lower-level system components (routers within domains or proteins within biological processes) are assortative and nonhierarchical, whereas networks of upper-level system components (internet domains or biological processes) are disassortative and hierarchical. Our results demonstrate that network topologies of complex systems must be interpreted in light of their hierarchical natures and interaction types. PMID:25793969

Hierarchical Higher Order Crf for the Classification of Airborne LIDAR Point Clouds in Urban Areas

NASA Astrophysics Data System (ADS)

Niemeyer, J.; Rottensteiner, F.; Soergel, U.; Heipke, C.

2016-06-01

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next iteration of the point-based layer. This framework iterates and mutually propagates context to improve the classification results. Potentially wrong decisions can be revised at later stages. The output is a labelled point cloud as well as segments roughly corresponding to object instances. Moreover, we present two new contextual features for the segment classification: the distance and the orientation of a segment with respect to the closest road. It is shown that the classification benefits from these features. In our experiments the hierarchical framework improve the overall accuracies by 2.3% on a point-based level and by 3.0% on a segment-based level, respectively, compared to a purely point-based classification.

[The structure of interaction in romantic relationships: hierarchical data analysis of inter-subjectivity between partners].

PubMed

Shimizu, Hiroshi; Daibo, Ikuo

2008-02-01

A hierarchical data analysis was conducted using data from couples to examine how self-reports of interactions between partners in romantic relationships predict the quality of the relationships. Whereas the social exchange theory has elucidated the quality of relationships from the individual level of subjectivity, this study focused on the structure of interactions between the partners (i.e., the frequency, strength, and diversity) through a process of inter-subjectivity at the couple level. A multilevel covariance structure analysis of 194 university students involved in romantic relationships revealed that the quality of relationships was mainly related to the strength and the diversity of interactions at the couple level, rather than the strength of interactions at the individual level. These results indicate that the inter-subjective process in romantic relationships may primarily explain the quality of relationships.

Universal Method for Creating Hierarchical Wrinkles on Thin-Film Surfaces.

PubMed

Jung, Woo-Bin; Cho, Kyeong Min; Lee, Won-Kyu; Odom, Teri W; Jung, Hee-Tae

2018-01-10

One of the most interesting topics in physical science and materials science is the creation of complex wrinkled structures on thin-film surfaces because of their several advantages of high surface area, localized strain, and stress tolerance. In this study, a significant step was taken toward solving limitations imposed by the fabrication of previous artificial wrinkles. A universal method for preparing hierarchical three-dimensional wrinkle structures of thin films on a multiple scale (e.g., nanometers to micrometers) by sequential wrinkling with different skin layers was developed. Notably, this method was not limited to specific materials, and it was applicable to fabricating hierarchical wrinkles on all of the thin-film surfaces tested thus far, including those of metals, two-dimensional and one-dimensional materials, and polymers. The hierarchical wrinkles with multiscale structures were prepared by sequential wrinkling, in which a sacrificial layer was used as the additional skin layer between sequences. For example, a hierarchical MoS 2 wrinkle exhibited highly enhanced catalytic behavior because of the superaerophobicity and effective surface area, which are related to topological effects. As the developed method can be adopted to a majority of thin films, it is thought to be a universal method for enhancing the physical properties of various materials.

Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates

PubMed Central

Song, Gian; Sun, Zhiqian; Li, Lin; Xu, Xiandong; Rawlings, Michael; Liebscher, Christian H.; Clausen, Bjørn; Poplawsky, Jonathan; Leonard, Donovan N.; Huang, Shenyan; Teng, Zhenke; Liu, Chain T.; Asta, Mark D.; Gao, Yanfei; Dunand, David C.; Ghosh, Gautam; Chen, Mingwei; Fine, Morris E.; Liaw, Peter K.

2015-01-01

There have been numerous efforts to develop creep-resistant materials strengthened by incoherent particles at high temperatures and stresses in response to future energy needs for steam turbines in thermal-power plants. However, the microstructural instability of the incoherent-particle-strengthened ferritic steels limits their application to temperatures below 900 K. Here, we report a novel ferritic alloy with the excellent creep resistance enhanced by coherent hierarchical precipitates, using the integrated experimental (transmission-electron microscopy/scanning-transmission-electron microscopy, in-situ neutron diffraction, and atom-probe tomography) and theoretical (crystal-plasticity finite-element modeling) approaches. This alloy is strengthened by nano-scaled L21-Ni2TiAl (Heusler phase)-based precipitates, which themselves contain coherent nano-scaled B2 zones. These coherent hierarchical precipitates are uniformly distributed within the Fe matrix. Our hierarchical structure material exhibits the superior creep resistance at 973 K in terms of the minimal creep rate, which is four orders of magnitude lower than that of conventional ferritic steels. These results provide a new alloy-design strategy using the novel concept of hierarchical precipitates and the fundamental science for developing creep-resistant ferritic alloys. The present research will broaden the applications of ferritic alloys to higher temperatures. PMID:26548303

Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates

DOE PAGES

Song, Gian; Sun, Zhiqian; Li, Lin; ...

2015-11-09

There have been numerous efforts to develop creep-resistant materials strengthened by incoherent particles at high temperatures and stresses in response to future energy needs for steam turbines in thermal-power plants. However, the microstructural instability of the incoherent-particle-strengthened ferritic steels limits their application to temperatures below 900 K. Here, we report a novel ferritic alloy with the excellent creep resistance enhanced by coherent hierarchical precipitates, using the integrated experimental (transmission-electron microscopy/scanning-transmission-electron microscopy, in-situ neutron diffraction, and atom-probe tomography) and theoretical (crystal-plasticity finite-element modeling) approaches. This alloy is strengthened by nano-scaled L21-Ni2TiAl (Heusler phase)-based precipitates, which themselves contain coherent nano-scaled B2 zones.more » These coherent hierarchical precipitates are uniformly distributed within the Fe matrix. Our hierarchical structure material exhibits the superior creep resistance at 973 K in terms of the minimal creep rate, which is four orders of magnitude lower than that of conventional ferritic steels. These results provide a new alloy-design strategy using the novel concept of hierarchical precipitates and the fundamental science for developing creep-resistant ferritic alloys. Finally, the present research will broaden the applications of ferritic alloys to higher temperatures.« less

A Hierarchical Visualization Analysis Model of Power Big Data

NASA Astrophysics Data System (ADS)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

Applying Hierarchical Model Calibration to Automatically Generated Items.

ERIC Educational Resources Information Center

Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.

This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…

Problem of two-level hierarchical minimax program control the final state of regional social and economic system in the presence of risks

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

Shorikov, A. F., E-mail: afshorikov@mail.ru

This article discusses a discrete-time dynamical system consisting of a set a controllable objects (region and forming it municipalities). The dynamics each of these is described by the corresponding vector nonlinear discrete-time recurrent vector equations and its control system consist from two levels: basic (control level I) that is dominating and subordinate level (control level II). Both levels have different criterions of functioning and united a priori by determined informational and control connections defined in advance. In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economicmore » system in the presence of risks. For this problem we proposed in this work an economical and mathematical model of two-level hierarchical minimax program control the final state of regional social and economic system in the presence of risks and the general scheme for its solving.« less

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Hierarchical semantic structures for medical NLP.

PubMed

Taira, Ricky K; Arnold, Corey W

2013-01-01

We present a framework for building a medical natural language processing (NLP) system capable of deep understanding of clinical text reports. The framework helps developers understand how various NLP-related efforts and knowledge sources can be integrated. The aspects considered include: 1) computational issues dealing with defining layers of intermediate semantic structures to reduce the dimensionality of the NLP problem; 2) algorithmic issues in which we survey the NLP literature and discuss state-of-the-art procedures used to map between various levels of the hierarchy; and 3) implementation issues to software developers with available resources. The objective of this poster is to educate readers to the various levels of semantic representation (e.g., word level concepts, ontological concepts, logical relations, logical frames, discourse structures, etc.). The poster presents an architecture for which diverse efforts and resources in medical NLP can be integrated in a principled way.

The Mission Operations Planning Assistant

NASA Technical Reports Server (NTRS)

Schuetzle, James G.

1987-01-01

The Mission Operations Planning Assistant (MOPA) is a knowledge-based system developed to support the planning and scheduling of instrument activities on the Upper Atmospheric Research Satellite (UARS). The MOPA system represents and maintains instrument plans at two levels of abstraction in order to keep plans comprehensible to both UARS Principal Investigators and Command Management personnel. The hierarchical representation of plans also allows MOPA to automatically create detailed instrument activity plans from which spacecraft command loads may be generated. The MOPA system was developed on a Symbolics 3640 computer using the ZetaLisp and ART languages. MOPA's features include a textual and graphical interface for plan inspection and modification, recognition of instrument operational constraint violations during the planning process, and consistency maintenance between the different planning levels. This paper describes the current MOPA system.

The mission operations planning assistant

NASA Technical Reports Server (NTRS)

Schuetzle, James G.

1987-01-01

The Mission Operations Planning Assistant (MOPA) is a knowledge-based system developed to support the planning and scheduling of instrument activities on the Upper Atmospheric Research Satellite (UARS). The MOPA system represents and maintains instrument plans at two levels of abstraction in order to keep plans comprehensible to both UARS Prinicpal Investigators and Command Management personnel. The hierarchical representation of plans also allows MOPA to automatically create detailed instrument activity plans from which spacecraft command loads may be generated. The MOPA system was developed on a Symbolics 3640 computer using the ZETALISP and ART languages. MOPA's features include a textual and graphical interface for plan inspection and modification, recognition of instrument operational constraint violations during the planning process, and consistency maintenance between the different planning levels. This paper describes the current MOPA system.

Hierarchy Measure for Complex Networks

PubMed Central

Mones, Enys; Vicsek, Lilla; Vicsek, Tamás

2012-01-01

Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure. PMID:22470477

The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem.

PubMed

Puechmaille, Sebastien J

2016-05-01

Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology and conservation biology. Such population structure inferences are routinely investigated via the program structure implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical data sets. In this study, I used simulated and empirical microsatellite data sets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward-biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, while at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled data sets. Additionally, a subsampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved. © 2016 John Wiley & Sons Ltd.

A Bayesian hierarchical model for mortality data from cluster-sampling household surveys in humanitarian crises.

PubMed

Heudtlass, Peter; Guha-Sapir, Debarati; Speybroeck, Niko

2018-05-31

The crude death rate (CDR) is one of the defining indicators of humanitarian emergencies. When data from vital registration systems are not available, it is common practice to estimate the CDR from household surveys with cluster-sampling design. However, sample sizes are often too small to compare mortality estimates to emergency thresholds, at least in a frequentist framework. Several authors have proposed Bayesian methods for health surveys in humanitarian crises. Here, we develop an approach specifically for mortality data and cluster-sampling surveys. We describe a Bayesian hierarchical Poisson-Gamma mixture model with generic (weakly informative) priors that could be used as default in absence of any specific prior knowledge, and compare Bayesian and frequentist CDR estimates using five different mortality datasets. We provide an interpretation of the Bayesian estimates in the context of an emergency threshold and demonstrate how to interpret parameters at the cluster level and ways in which informative priors can be introduced. With the same set of weakly informative priors, Bayesian CDR estimates are equivalent to frequentist estimates, for all practical purposes. The probability that the CDR surpasses the emergency threshold can be derived directly from the posterior of the mean of the mixing distribution. All observation in the datasets contribute to the estimation of cluster-level estimates, through the hierarchical structure of the model. In a context of sparse data, Bayesian mortality assessments have advantages over frequentist ones already when using only weakly informative priors. More informative priors offer a formal and transparent way of combining new data with existing data and expert knowledge and can help to improve decision-making in humanitarian crises by complementing frequentist estimates.

Metastability on the hierarchical lattice

NASA Astrophysics Data System (ADS)

den Hollander, Frank; Jovanovski, Oliver

2017-07-01

We study metastability for Glauber spin-flip dynamics on the N-dimensional hierarchical lattice with n hierarchical levels. Each vertex carries an Ising spin that can take the values -1 or +1 . Spins interact with an external magnetic field h>0 . Pairs of spins interact with each other according to a ferromagnetic pair potential J=\\{J_i\\}i=1n , where J_i>0 is the strength of the interaction between spins at hierarchical distance i. Spins flip according to a Metropolis dynamics at inverse temperature β. In the limit as β\\to∞ , we analyse the crossover time from the metastable state \\boxminus (all spins -1 ) to the stable state \\boxplus (all spins +1 ). Under the assumption that J is non-increasing, we identify the mean transition time up to a multiplicative factor 1+o_β(1) . On the scale of its mean, the transition time is exponentially distributed. We also identify the set of configurations representing the gate for the transition. For the special case where Ji = \\tilde{J}/Ni , 1 ≤slant i ≤slant n , with \\tilde{J}>0 the relevant formulas simplify considerably. Also the hierarchical mean-field limit N\\to∞ can be analysed in detail.

Impact of cell shape in hierarchically structured plant surfaces on the attachment of male Colorado potato beetles (Leptinotarsa decemlineata)

PubMed Central

Seidel, Robin; Bohn, Holger Florian; Speck, Thomas

2012-01-01

Summary Plant surfaces showing hierarchical structuring are frequently found in plant organs such as leaves, petals, fruits and stems. In our study we focus on the level of cell shape and on the level of superimposed microstructuring, leading to hierarchical surfaces if both levels are present. While it has been shown that epicuticular wax crystals and cuticular folds strongly reduce insect attachment, and that smooth papillate epidermal cells in petals improve the grip of pollinators, the impact of hierarchical surface structuring of plant surfaces possessing convex or papillate cells on insect attachment remains unclear. We performed traction experiments with male Colorado potato beetles on nine different plant surfaces with different structures. The selected plant surfaces showed epidermal cells with either tabular, convex or papillate cell shape, covered either with flat films of wax, epicuticular wax crystals or with cuticular folds. On surfaces possessing either superimposed wax crystals or cuticular folds we found traction forces to be almost one order of magnitude lower than on surfaces covered only with flat films of wax. Independent of superimposed microstructures we found that convex and papillate epidermal cell shapes slightly enhance the attachment ability of the beetles. Thus, in plant surfaces, cell shape and superimposed microstructuring yield contrary effects on the attachment of the Colorado potato beetle, with convex or papillate cells enhancing attachment and both wax crystals or cuticular folds reducing attachment. However, the overall magnitude of traction force mainly depends on the presence or absence of superimposed microstructuring. PMID:22428097

A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

NASA Astrophysics Data System (ADS)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global-scale Bayesian calibration of wetland emission models.

A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates

PubMed Central

An, Qian; Kang, Jian; Song, Ruiguang; Hall, H. Irene

2016-01-01

Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA. PMID:26567891

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

NASA Astrophysics Data System (ADS)

Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

2017-07-01

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

Culture Modulates the Brain Response to Harmonic Violations: An EEG Study on Hierarchical Syntactic Structure in Music.

PubMed

Akrami, Haleh; Moghimi, Sahar

2017-01-01

We investigated the role of culture in processing hierarchical syntactic structures in music. We examined whether violation of non-local dependencies manifest in event related potentials (ERP) for Western and Iranian excerpts by recording EEG while participants passively listened to sequences of modified/original excerpts. We also investigated oscillatory and synchronization properties of brain responses during processing of hierarchical structures. For the Western excerpt, subjective ratings of conclusiveness were marginally significant and the difference in the ERP components fell short of significance. However, ERP and behavioral results showed that while listening to culturally familiar music, subjects comprehended whether or not the hierarchical syntactic structure was fulfilled. Irregularities in the hierarchical structures of the Iranian excerpt elicited an early negativity in the central regions bilaterally, followed by two later negativities from 450-700 to 750-950 ms. The latter manifested throughout the scalp. Moreover, violations of hierarchical structure in the Iranian excerpt were associated with (i) an early decrease in the long range alpha phase synchronization, (ii) an early increase in the oscillatory activity in the beta band over the central areas, and (iii) a late decrease in the theta band phase synchrony between left anterior and right posterior regions. Results suggest that rhythmic structures and melodic fragments, representative of Iranian music, created a familiar context in which recognition of complex non-local syntactic structures was feasible for Iranian listeners. Processing of neural responses to the Iranian excerpt indicated neural mechanisms for processing of hierarchical syntactic structures in music at different levels of cortical integration.