A Hierarchical Model and Analysis of Factors Affecting the Adoption of Timber as a Bridge

Treesearch

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1995-01-01

The Analytical Hierarchy Process was used to characterize the bridge material selection decisions of highway engineers and local highway officials across the United States. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in Mississippi, Virginia, Washington, and Wisconsin to identify...

Towards Analytics for Wholistic School Improvement: Hierarchical Process Modelling and Evidence Visualization

ERIC Educational Resources Information Center

Crick, Ruth Deakin; Knight, Simon; Barr, Steven

2017-01-01

Central to the mission of most educational institutions is the task of preparing the next generation of citizens to contribute to society. Schools, colleges, and universities value a range of outcomes--e.g., problem solving, creativity, collaboration, citizenship, service to community--as well as academic outcomes in traditional subjects. Often…

Combining analytical hierarchy process and agglomerative hierarchical clustering in search of expert consensus in green corridors development management.

PubMed

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts-landscape architects, regional planners, and geographers-revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Combining Analytical Hierarchy Process and Agglomerative Hierarchical Clustering in Search of Expert Consensus in Green Corridors Development Management

NASA Astrophysics Data System (ADS)

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts—landscape architects, regional planners, and geographers—revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

PubMed

Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

2016-01-01

With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

Trapping in scale-free networks with hierarchical organization of modularity.

PubMed

Zhang, Zhongzhi; Lin, Yuan; Gao, Shuyang; Zhou, Shuigeng; Guan, Jihong; Li, Mo

2009-11-01

A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynamical processes taking place on such networks. In this paper, we investigate a simple stochastic process--trapping problem, a random walk with a perfect trap fixed at a given location, performed on a family of hierarchical networks that exhibit simultaneously striking scale-free and modular structure. We focus on a particular case with the immobile trap positioned at the hub node having the largest degree. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping problem, which is the mean of the node-to-trap first-passage time over the entire network. The exact expression for the MFPT is calculated through the recurrence relations derived from the special construction of the hierarchical networks. The obtained rigorous formula corroborated by extensive direct numerical calculations exhibits that the MFPT grows algebraically with the network order. Concretely, the MFPT increases as a power-law function of the number of nodes with the exponent much less than 1. We demonstrate that the hierarchical networks under consideration have more efficient structure for transport by diffusion in contrast with other analytically soluble media including some previously studied scale-free networks. We argue that the scale-free and modular topologies are responsible for the high efficiency of the trapping process on the hierarchical networks.

Concordance of Interests in Dynamic Models of Social Partnership in the System of Continuing Professional Education

ERIC Educational Resources Information Center

Tarasenko, Larissa V.; Ougolnitsky, Guennady A.; Usov, Anatoly B.; Vaskov, Maksim A.; Kirik, Vladimir A.; Astoyanz, Margarita S.; Angel, Olga Y.

2016-01-01

A dynamic game theoretic model of concordance of interests in the process of social partnership in the system of continuing professional education is proposed. Non-cooperative, cooperative, and hierarchical setups are examined. Analytical solution for a linear state version of the model is provided. Nash equilibrium algorithms (for non-cooperative…

A Hierarchical Analysis of Bridge Decision Makers ... The Role of New Technology Adoption in the Timber Bridge Market: Special Project

Treesearch

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1995-01-01

Bridge design engineers and local highway officials make bridge replacement decisions across the United States. The Analytical Hierarchy Process was used to characterize the bridge material selection decision of these individuals. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in...

World Wide Web Indexes and Hierarchical Lists: Finding Tools for the Internet.

ERIC Educational Resources Information Center

Munson, Kurt I.

1996-01-01

In World Wide Web indexing: (1) the creation process is automated; (2) the indexes are merely descriptive, not analytical of document content; (3) results may be sorted differently depending on the search engine; and (4) indexes link directly to the resources. This article compares the indexing methods and querying options of the search engines…

Hierarchical zwitterionic modification of a SERS substrate enables real-time drug monitoring in blood plasma

PubMed Central

Sun, Fang; Hung, Hsiang-Chieh; Sinclair, Andrew; Zhang, Peng; Bai, Tao; Galvan, Daniel David; Jain, Priyesh; Li, Bowen; Jiang, Shaoyi; Yu, Qiuming

2016-01-01

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive analytical technique with molecular specificity, making it an ideal candidate for therapeutic drug monitoring (TDM). However, in critical diagnostic media including blood, nonspecific protein adsorption coupled with weak surface affinities and small Raman activities of many analytes hinder the TDM application of SERS. Here we report a hierarchical surface modification strategy, first by coating a gold surface with a self-assembled monolayer (SAM) designed to attract or probe for analytes and then by grafting a non-fouling zwitterionic polymer brush layer to effectively repel protein fouling. We demonstrate how this modification can enable TDM applications by quantitatively and dynamically measuring the concentrations of several analytes—including an anticancer drug (doxorubicin), several TDM-requiring antidepressant and anti-seizure drugs, fructose and blood pH—in undiluted plasma. This hierarchical surface chemistry is widely applicable to many analytes and provides a generalized platform for SERS-based biosensing in complex real-world media. PMID:27834380

Business Intelligence in Process Control

NASA Astrophysics Data System (ADS)

Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol

2013-12-01

The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.

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.

Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process

NASA Astrophysics Data System (ADS)

Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.

2018-01-01

Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials.

PubMed

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R

2017-03-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials

PubMed Central

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R.

2017-01-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers. PMID:28690971

Approaches for advancing scientific understanding of macrosystems

USGS Publications Warehouse

Levy, Ofir; Ball, Becky A.; Bond-Lamberty, Ben; Cheruvelil, Kendra S.; Finley, Andrew O.; Lottig, Noah R.; Surangi W. Punyasena,; Xiao, Jingfeng; Zhou, Jizhong; Buckley, Lauren B.; Filstrup, Christopher T.; Keitt, Tim H.; Kellner, James R.; Knapp, Alan K.; Richardson, Andrew D.; Tcheng, David; Toomey, Michael; Vargas, Rodrigo; Voordeckers, James W.; Wagner, Tyler; Williams, John W.

2014-01-01

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

PubMed

Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Sensory evaluation based fuzzy AHP approach for material selection in customized garment design and development process

NASA Astrophysics Data System (ADS)

Hong, Y.; Curteza, A.; Zeng, X.; Bruniaux, P.; Chen, Y.

2016-06-01

Material selection is the most difficult section in the customized garment product design and development process. This study aims to create a hierarchical framework for material selection. The analytic hierarchy process and fuzzy sets theories have been applied to mindshare the diverse requirements from the customer and inherent interaction/interdependencies among these requirements. Sensory evaluation ensures a quick and effective selection without complex laboratory test such as KES and FAST, using the professional knowledge of the designers. A real empirical application for the physically disabled people is carried out to demonstrate the proposed method. Both the theoretical and practical background of this paper have indicated the fuzzy analytical network process can capture expert's knowledge existing in the form of incomplete, ambiguous and vague information for the mutual influence on attribute and criteria of the material selection.

Epidemic spreading on hierarchical geographical networks with mobile agents

NASA Astrophysics Data System (ADS)

Han, Xiao-Pu; Zhao, Zhi-Dan; Hadzibeganovic, Tarik; Wang, Bing-Hong

2014-05-01

Hierarchical geographical traffic networks are critical for our understanding of scaling laws in human trajectories. Here, we investigate the susceptible-infected epidemic process evolving on hierarchical networks in which agents randomly walk along the edges and establish contacts in network nodes. We employ a metapopulation modeling framework that allows us to explore the contagion spread patterns in relation to multi-scale mobility behaviors. A series of computer simulations revealed that a shifted power-law-like negative relationship between the peak timing of epidemics τ0 and population density, and a logarithmic positive relationship between τ0 and the network size, can both be explained by the gradual enlargement of fluctuations in the spreading process. We employ a semi-analytical method to better understand the nature of these relationships and the role of pertinent demographic factors. Additionally, we provide a quantitative discussion of the efficiency of a border screening procedure in delaying epidemic outbreaks on hierarchical networks, yielding a rather limited feasibility of this mitigation strategy but also its non-trivial dependence on population density, infector detectability, and the diversity of the susceptible region. Our results suggest that the interplay between the human spatial dynamics, network topology, and demographic factors can have important consequences for the global spreading and control of infectious diseases. These findings provide novel insights into the combined effects of human mobility and the organization of geographical networks on spreading processes, with important implications for both epidemiological research and health policy.

Investigation of variety resources and quantitative analysis on Heyin pomegranate in Xingyang City

NASA Astrophysics Data System (ADS)

Li, Wenzeng; Wang, Zhihong

2018-04-01

Various factors that should be considered in variety breeding of Heyin pomegranate, the hierarchical analysis is carried out through analytic hierarchy process (AHP) and its analytic result can be used to help fruit farmers make scientific decision on the variety breeding of pomegranate. In the six main Heyin pomegranate varieties, the ranking weight value of Tunisian soft-seeded pomegranate is 0.3105, which is No.1 in all pomegranate varieties and is obviously better than other varieties in comprehensive feature. It shows that, in the cultivation of pomegranate in Xingyang, the Tunisian soft-seeded pomegranate is the preferred variety for fruit farmers.

Analytical design of intelligent machines

NASA Technical Reports Server (NTRS)

Saridis, George N.; Valavanis, Kimon P.

1987-01-01

The problem of designing 'intelligent machines' to operate in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an 'intelligent machine' is defined to be the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of 'increasing precision with decreasing intelligence', namely: the organizational level, performing general information processing tasks in association with a long-term memory; the coordination level, dealing with specific information processing tasks with a short-term memory; and the control level, which performs the execution of various tasks through hardware using feedback control methods. The behavior of such a machine may be managed by controls with special considerations and its 'intelligence' is directly related to the derivation of a compatible measure that associates the intelligence of the higher levels with the concept of entropy, which is a sufficient analytic measure that unifies the treatment of all the levels of an 'intelligent machine' as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision such that it minimizes its total entropy. A case study on the automatic maintenance of a nuclear plant illustrates the proposed approach.

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.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting.

PubMed

Schmidt, Katharina; Aumann, Ines; Hollander, Ines; Damm, Kathrin; von der Schulenburg, J-Matthias Graf

2015-12-24

The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context. A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: "Analytic Hierarchy Process," "Analytical Hierarchy Process," "multi-criteria decision analysis," "multiple criteria decision," "stated preference," and "pairwise comparison." In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies' reporting. The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30%), followed by the US (25.6%). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria. The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP.

Testing Crites' Model of Career Maturity: A Hierarchical Strategy.

ERIC Educational Resources Information Center

Wallbrown, Fred H.; And Others

1986-01-01

Investigated the construct validity of Crites' model of career maturity and the Career Maturity Inventory (CMI). Results from a nationwide sample of adolescents, using hierarchical factor analytic methodology, indicated confirmatory support for the multidimensionality of Crites' model of career maturity, and the construct validity of the CMI as a…

Evaluating supplier quality performance using fuzzy analytical hierarchy process

NASA Astrophysics Data System (ADS)

Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

2014-12-01

Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

Gating Mechanisms of Mechanosensitive Channels of Large Conductance, I: A Continuum Mechanics-Based Hierarchical Framework

PubMed Central

Chen, Xi; Cui, Qiang; Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun

2008-01-01

A hierarchical simulation framework that integrates information from molecular dynamics (MD) simulations into a continuum model is established to study the mechanical response of mechanosensitive channel of large-conductance (MscL) using the finite element method (FEM). The proposed MD-decorated FEM (MDeFEM) approach is used to explore the detailed gating mechanisms of the MscL in Escherichia coli embedded in a palmitoyloleoylphosphatidylethanolamine lipid bilayer. In Part I of this study, the framework of MDeFEM is established. The transmembrane and cytoplasmic helices are taken to be elastic rods, the loops are modeled as springs, and the lipid bilayer is approximated by a three-layer sheet. The mechanical properties of the continuum components, as well as their interactions, are derived from molecular simulations based on atomic force fields. In addition, analytical closed-form continuum model and elastic network model are established to complement the MDeFEM approach and to capture the most essential features of gating. In Part II of this study, the detailed gating mechanisms of E. coli-MscL under various types of loading are presented and compared with experiments, structural model, and all-atom simulations, as well as the analytical models established in Part I. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction. PMID:18390626

The new model of chemical evolution of r-process elements based on the hierarchical galaxy formation. I. Ba and Eu

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

Komiya, Yutaka; Suda, Takuma; Yamada, Shimako

2014-03-10

We investigate the chemical enrichment of r-process elements in the early evolutionary stages of the Milky Way halo within the framework of hierarchical galaxy formation using a semi-analytic merger tree. In this paper, we focus on heavy r-process elements, Ba and Eu, of extremely metal-poor (EMP) stars and give constraints on their astronomical sites. Our models take into account changes of the surface abundances of EMP stars by the accretion of interstellar medium (ISM). We also consider metal-enrichment of intergalactic medium by galactic winds and the resultant pre-enrichment of proto-galaxies. The trend and scatter of the observed r-process abundances aremore » well reproduced by our hierarchical model with ∼10% of core-collapse supernovae in low-mass end (∼10 M {sub ☉}) as a dominant r-process source and the star formation efficiency of ∼10{sup –10} yr{sup –1}. For neutron star mergers as an r-process source, their coalescence timescale has to be ∼10{sup 7} yr, and the event rates ∼100 times larger than currently observed in the Galaxy. We find that the accretion of ISM is a dominant source of r-process elements for stars with [Ba/H] < –3.5. In this model, a majority of stars at [Fe/H] < –3 are formed without r-process elements, but their surfaces are polluted by the ISM accretion. The pre-enrichment affects ∼4% of proto-galaxies, and yet, is surpassed by the ISM accretion in the surface of EMP stars.« less

An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

PubMed

Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

PubMed Central

Gundogar, Emin; Yılmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

Evidence for a General ADHD Factor from a Longitudinal General School Population Study

ERIC Educational Resources Information Center

Normand, Sebastien; Flora, David B.; Toplak, Maggie E.; Tannock, Rosemary

2012-01-01

Recent factor analytic studies in Attention-Deficit/Hyperactivity Disorder (ADHD) have shown that hierarchical models provide a better fit of ADHD symptoms than correlated models. A hierarchical model includes a general ADHD factor and specific factors for inattention, and hyperactivity/impulsivity. The aim of this 12-month longitudinal study was…

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

ERIC Educational Resources Information Center

Ker, H. W.

2014-01-01

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

Hierarchical Carbon Fibers with ZnO Nanowires for Volatile Sensing in Composite Curing (Postprint)

DTIC Science & Technology

2014-07-01

needed to demonstrate the use of Zinc Oxide (ZnO) nanowire coated carbon fibers as a volatile sensor. ZnO nanowires are demonstrated to function as...processing. For this work, we report on the foundational study needed to demonstrate the use of Zinc Oxide (ZnO) nanowire coated carbon fibers as a...array of ZnO nanowires. Zinc oxide nanowires become more conductive in the presence of ethanol – as analyte sorbs to the surface, electron density

The Hierarchical Factor Model of ADHD: Invariant across Age and National Groupings?

ERIC Educational Resources Information Center

Toplak, Maggie E.; Sorge, Geoff B.; Flora, David B.; Chen, Wai; Banaschewski, Tobias; Buitelaar, Jan; Ebstein, Richard; Eisenberg, Jacques; Franke, Barbara; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Thompson, Margaret; Tannock, Rosemary; Asherson, Philip; Faraone, Stephen V.

2012-01-01

Objective: To examine the factor structure of attention-deficit/hyperactivity disorder (ADHD) in a clinical sample of 1,373 children and adolescents with ADHD and their 1,772 unselected siblings recruited from different countries across a large age range. Hierarchical and correlated factor analytic models were compared separately in the ADHD and…

Analytical stability criteria for the Caledonian Symmetric Four and Five Body Problems

NASA Astrophysics Data System (ADS)

Steves, Bonnie; Shoaib Afridi, Mohammad; Sweatman, Winston

2017-06-01

Analytical studies of the stability of three or more body gravitational systems are difficult because of the greater number of variables involved with the increasing number of bodies and the limitation of 10 integrals that exist in the gravitational n-body problem. Utilisation of symmetries or the neglecting of the masses of some of the bodies compared to others can simplify the dynamical problem and enable global analytical stability solutions to be derived. These symmetric and restricted few body systems with their analytical stability criterion can then provide useful information on the stability of the general few body system when near symmetry or the restricted situation. Even with symmetrical reductions, analytical stability derivations for four and five body problems are rare. In this paper, we develop an analytical stability criterion for the Caledonian Symmetric Five Body Problem (CS5BP) , a dynamically symmetrical planar problem with two pairs of equal masses and a fifth mass located at the centre of mass. Sundman’s inequality is applied to derive boundary surfaces to the allowed real motion of the system. This enables the derivation of a stability criterion valid for all time for the hierarchical stability of the CS5BP and its subset the Caledonian Symmetric Four Body Problem (CSFBP), where the central mass is taken to be equal to zero. We show that the hierarchical stability depends solely on the Szebehely constant C0, which is a function of the total energy H and angular momentum c. The critical value Ccrit at which the system becomes hierarchically stable for all time depends only on the two mass ratios of the symmetric five body system. We then explore the effect on the stability of the whole system of adding an increasing massive central body. It is shown both analytically and numerically that all CS5BPs and CSFBPs of different mass ratios are hierarchically stable if C0 > 0.0659 and C0 > 0.0465, respectively. The Caledonian Symmetric Four and Five Body gravitational models are relevant to the study of the stability and evolution of symmetric quadruple/quintuple stellar clusters and symmetric exoplanetary systems of two planets orbiting a binary/triplet of stars.

Intuitionistic fuzzy analytical hierarchical processes for selecting the paradigms of mangroves in municipal wastewater treatment.

PubMed

Ouyang, Xiaoguang; Guo, Fen

2018-04-01

Municipal wastewater discharge is widespread and one of the sources of coastal eutrophication, and is especially uncontrolled in developing and undeveloped coastal regions. Mangrove forests are natural filters of pollutants in wastewater. There are three paradigms of mangroves for municipal wastewater treatment and the selection of the optimal one is a multi-criteria decision-making problem. Combining intuitionistic fuzzy theory, the Fuzzy Delphi Method and the fuzzy analytical hierarchical process (AHP), this study develops an intuitionistic fuzzy AHP (IFAHP) method. For the Fuzzy Delphi Method, the judgments of experts and representatives on criterion weights are made by linguistic variables and quantified by intuitionistic fuzzy theory, which is also used to weight the importance of experts and representatives. This process generates the entropy weights of criteria, which are combined with indices values and weights to rank the alternatives by the fuzzy AHP method. The IFAHP method was used to select the optimal paradigm of mangroves for treating municipal wastewater. The entropy weights were entrained by the valid evaluation of 64 experts and representatives via online survey. Natural mangroves were found to be the optimal paradigm for municipal wastewater treatment. By assigning different weights to the criteria, sensitivity analysis shows that natural mangroves remain to be the optimal paradigm under most scenarios. This study stresses the importance of mangroves for wastewater treatment. Decision-makers need to contemplate mangrove reforestation projects, especially where mangroves are highly deforested but wastewater discharge is uncontrolled. The IFAHP method is expected to be applied in other multi-criteria decision-making cases. Copyright © 2017 Elsevier Ltd. All rights reserved.

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).

[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.

Identifying and prioritizing the preference criteria using analytical hierarchical process for a student-lecturer allocation problem of internship programme

NASA Astrophysics Data System (ADS)

Faudzi, Syakinah; Abdul-Rahman, Syariza; Rahman, Rosshairy Abd; Hew, Jafri Hj. Zulkepli

2016-10-01

This paper discusses on identifying and prioritizing the student's preference criteria towards supervisor using Analytical Hierarchical Process (AHP) for student-lecturer allocation problem of internship programme. Typically a wide number of students undertake internship every semester and many preferences criteria may involve when assigning students to lecturer for supervision. Thus, identifying and prioritizing the preference criteria of assigning students to lecturer is critically needed especially when involving many preferences. AHP technique is used to prioritize the seven criteria which are capacity, specialization, academic position, availability, professional support, relationship and gender. Student's preference alternative is classified based on lecturer's academic position which are lecturer, senior lecturer, associate professor and professor. Criteria are ranked to find the best preference criteria and alternatives of the supervisor that students prefer to have. This problem is solved using Expert Choice 11 software. A sample of 30 respondents who are from semester 6 and above are randomly selected to participate in the study. By using questionnaire as our medium in collecting the student's data, consistency index is produced to validate the proposed study. Findings and result showed that, the most important preference criteria is professional support. It is followed by specialization, availability, relationship, gender, academic position and capacity. This study found that student would like to have a supportive supervisor because lack of supervision can lead the students to achieve low grade and knowledge from the internship session.

Sinkhole Susceptibility Hazard Zones Using GIS and Analytical Hierarchical Process (ahp): a Case Study of Kuala Lumpur and Ampang Jaya

NASA Astrophysics Data System (ADS)

Rosdi, M. A. H. M.; Othman, A. N.; Zubir, M. A. M.; Latif, Z. A.; Yusoff, Z. M.

2017-10-01

Sinkhole is not classified as new phenomenon in this country, especially surround Klang Valley. Since 1968, the increasing numbers of sinkhole incident have been reported in Kuala Lumpur and the vicinity areas. As the results, it poses a serious threat for human lives, assets and structure especially in the capital city of Malaysia. Therefore, a Sinkhole Hazard Model (SHM) was generated with integration of GIS framework by applying Analytical Hierarchical Process (AHP) technique in order to produced sinkhole susceptibility hazard map for the particular area. Five consecutive parameters for main criteria each categorized by five sub classes were selected for this research which is Lithology (LT), Groundwater Level Decline (WLD), Soil Type (ST), Land Use (LU) and Proximity to Groundwater Wells (PG). A set of relative weights were assigned to each inducing factor and computed through pairwise comparison matrix derived from expert judgment. Lithology and Groundwater Level Decline has been identified gives the highest impact to the sinkhole development. A sinkhole susceptibility hazard zones was classified into five prone areas namely very low, low, moderate, high and very high hazard. The results obtained were validated with thirty three (33) previous sinkhole inventory data. This evaluation shows that the model indicates 64 % and 21 % of the sinkhole events fall within high and very high hazard zones respectively. Based on this outcome, it clearly represents that AHP approach is useful to predict natural disaster such as sinkhole hazard.

An Analytical Index to the Internet: Dreams of Utopia.

ERIC Educational Resources Information Center

Casey, Carol

1999-01-01

Explores the need for analytical indexes to access Internet resources. Considers bibliographic control, Web site design, keyword search engines, hierarchical subject indexes, and special indexes and compilations of links, and concludes that the creation of small, focused indexes may be the best solution for accessing specific types of digital…

Hierarchical Analytical Approaches for Unraveling the Composition of Proprietary Mixtures

EPA Pesticide Factsheets

The composition of commercial mixtures including pesticide inert ingredients, aircraft deicers, and aqueous film-forming foam (AFFF) formulations, and by analogy, fracking fluids, are proprietary. Quantitative analytical methodologies can only be developed for mixture components once their identities are known. Because proprietary mixtures may contain volatile and non-volatile components, a hierarchy of analytical methods is often required for the full identification of all proprietary mixture components.

Ag-NP@Ge-nanotaper/Si-micropillar ordered arrays as ultrasensitive and uniform surface enhanced Raman scattering substrates

NASA Astrophysics Data System (ADS)

Liu, Jing; Meng, Guowen; Li, Zhongbo; Huang, Zhulin; Li, Xiangdong

2015-10-01

Surface-enhanced Raman scattering (SERS) is considered to be an excellent candidate for analytical detection schemes, because of its molecular specificity, rapid response and high sensitivity. Here, SERS-substrates of Ag-nanoparticle (Ag-NP) decorated Ge-nanotapers grafted on hexagonally ordered Si-micropillar (denoted as Ag-NP@Ge-nanotaper/Si-micropillar) arrays are fabricated via a combinatorial process of two-step etching to achieve hexagonal Si-micropillar arrays, chemical vapor deposition of flocky Ge-nanotapers on each Si-micropillar and decoration of Ag-NPs onto the Ge-nanotapers through galvanic displacement. With high density three-dimensional (3D) ``hot spots'' created from the large quantities of the neighboring Ag-NPs and large-scale uniform morphology, the hierarchical Ag-NP@Ge-nanotaper/Si-micropillar arrays exhibit strong and reproducible SERS activity. Using our hierarchical 3D SERS-substrates, both methyl parathion (a commonly used pesticide) and PCB-2 (one congener of highly toxic polychlorinated biphenyls) with concentrations down to 10-7 M and 10-5 M have been detected respectively, showing great potential in SERS-based rapid trace-level detection of toxic organic pollutants in the environment.Surface-enhanced Raman scattering (SERS) is considered to be an excellent candidate for analytical detection schemes, because of its molecular specificity, rapid response and high sensitivity. Here, SERS-substrates of Ag-nanoparticle (Ag-NP) decorated Ge-nanotapers grafted on hexagonally ordered Si-micropillar (denoted as Ag-NP@Ge-nanotaper/Si-micropillar) arrays are fabricated via a combinatorial process of two-step etching to achieve hexagonal Si-micropillar arrays, chemical vapor deposition of flocky Ge-nanotapers on each Si-micropillar and decoration of Ag-NPs onto the Ge-nanotapers through galvanic displacement. With high density three-dimensional (3D) ``hot spots'' created from the large quantities of the neighboring Ag-NPs and large-scale uniform morphology, the hierarchical Ag-NP@Ge-nanotaper/Si-micropillar arrays exhibit strong and reproducible SERS activity. Using our hierarchical 3D SERS-substrates, both methyl parathion (a commonly used pesticide) and PCB-2 (one congener of highly toxic polychlorinated biphenyls) with concentrations down to 10-7 M and 10-5 M have been detected respectively, showing great potential in SERS-based rapid trace-level detection of toxic organic pollutants in the environment. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06001j

The Galics Project: Virtual Galaxy: from Cosmological N-body Simulations

NASA Astrophysics Data System (ADS)

Guiderdoni, B.

The GalICS project develops extensive semi-analytic post-processing of large cosmological simulations to describe hierarchical galaxy formation. The multiwavelength statistical properties of high-redshift and local galaxies are predicted within the large-scale structures. The fake catalogs and mock images that are generated from the outputs are used for the analysis and preparation of deep surveys. The whole set of results is now available in an on-line database that can be easily queried. The GalICS project represents a first step towards a 'Virtual Observatory of virtual galaxies'.

Closing the brain-to-brain loop in laboratory testing.

PubMed

Plebani, Mario; Lippi, Giuseppe

2011-07-01

Abstract The delivery of laboratory services has been described 40 years ago and defined with the foremost concept of "brain-to-brain turnaround time loop". This concept consists of several processes, including the final step which is the action undertaken on the patient based on laboratory information. Unfortunately, the need for systematic feedback to improve the value of laboratory services has been poorly understood and, even more risky, poorly applied in daily laboratory practice. Currently, major problems arise from the unavailability of consensually accepted quality specifications for the extra-analytical phase of laboratory testing. This, in turn, does not allow clinical laboratories to calculate a budget for the "patient-related total error". The definition and use of the term "total error" refers only to the analytical phase, and should be better defined as "total analytical error" to avoid any confusion and misinterpretation. According to the hierarchical approach to classify strategies to set analytical quality specifications, the "assessment of the effect of analytical performance on specific clinical decision-making" is comprehensively at the top and therefore should be applied as much as possible to address analytical efforts towards effective goals. In addition, an increasing number of laboratories worldwide are adopting risk management strategies such as FMEA, FRACAS, LEAN and Six Sigma since these techniques allow the identification of the most critical steps in the total testing process, and to reduce the patient-related risk of error. As a matter of fact, an increasing number of laboratory professionals recognize the importance of understanding and monitoring any step in the total testing process, including the appropriateness of the test request as well as the appropriate interpretation and utilization of test results.

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

The comparative evaluation of expanded national immunization policies in Korea using an analytic hierarchy process.

PubMed

Shin, Taeksoo; Kim, Chun-Bae; Ahn, Yang-Heui; Kim, Hyo-Youl; Cha, Byung Ho; Uh, Young; Lee, Joo-Heon; Hyun, Sook-Jung; Lee, Dong-Han; Go, Un-Yeong

2009-01-29

The purpose of this paper is to propose new evaluation criteria and an analytic hierarchy process (AHP) model to assess the expanded national immunization programs (ENIPs) and to evaluate two alternative health care policies. One of the alternative policies is that private clinics and hospitals would offer free vaccination services to children and the other of them is that public health centers would offer these free vaccination services. Our model to evaluate the ENIPs was developed using brainstorming, Delphi techniques, and the AHP model. We first used the brainstorming and Delphi techniques, as well as literature reviews, to determine 25 criteria with which to evaluate the national immunization policy; we then proposed a hierarchical structure of the AHP model to assess ENIPs. By applying the proposed AHP model to the assessment of ENIPs for Korean immunization policies, we show that free vaccination services should be provided by private clinics and hospitals rather than public health centers.

QFD-ANP Approach for the Conceptual Design of Research Vessels: A Case Study

NASA Astrophysics Data System (ADS)

Venkata Subbaiah, Kambagowni; Yeshwanth Sai, Koneru; Suresh, Challa

2016-10-01

Conceptual design is a subset of concept art wherein a new idea of product is created instead of a visual representation which would directly be used in a final product. The purpose is to understand the needs of conceptual design which are being used in engineering designs and to clarify the current conceptual design practice. Quality function deployment (QFD) is a customer oriented design approach for developing new or improved products and services to enhance customer satisfaction. House of quality (HOQ) has been traditionally used as planning tool of QFD which translates customer requirements (CRs) into design requirements (DRs). Factor analysis is carried out in order to reduce the CR portions of HOQ. The analytical hierarchical process is employed to obtain the priority ratings of CR's which are used in constructing HOQ. This paper mainly discusses about the conceptual design of an oceanographic research vessel using analytical network process (ANP) technique. Finally the QFD-ANP integrated methodology helps to establish the importance ratings of DRs.

Analytic hierarchy process helps select site for limestone quarry expansion in Barbados.

PubMed

Dey, Prasanta Kumar; Ramcharan, Eugene K

2008-09-01

Site selection is a key activity for quarry expansion to support cement production, and is governed by factors such as resource availability, logistics, costs, and socio-economic-environmental factors. Adequate consideration of all the factors facilitates both industrial productivity and sustainable economic growth. This study illustrates the site selection process that was undertaken for the expansion of limestone quarry operations to support cement production in Barbados. First, alternate sites with adequate resources to support a 25-year development horizon were identified. Second, technical and socio-economic-environmental factors were then identified. Third, a database was developed for each site with respect to each factor. Fourth, a hierarchical model in analytic hierarchy process (AHP) framework was then developed. Fifth, the relative ranking of the alternate sites was then derived through pair wise comparison in all the levels and through subsequent synthesizing of the results across the hierarchy through computer software (Expert Choice). The study reveals that an integrated framework using the AHP can help select a site for the quarry expansion project in Barbados.

Superhydrophobic SERS substrates based on silicon hierarchical nanostructures

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Orthogonal Higher Order Structure of the WISC-IV Spanish Using Hierarchical Exploratory Factor Analytic Procedures

ERIC Educational Resources Information Center

McGill, Ryan J.; Canivez, Gary L.

2016-01-01

As recommended by Carroll, the present study examined the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition Spanish (WISC-IV Spanish) normative sample using higher order exploratory factor analytic techniques not included in the WISC-IV Spanish Technical Manual. Results indicated that the WISC-IV Spanish subtests were…

Non-traditional isotopes in analytical ecogeochemistry assessed by MC-ICP-MS

NASA Astrophysics Data System (ADS)

Prohaska, Thomas; Irrgeher, Johanna; Horsky, Monika; Hanousek, Ondřej; Zitek, Andreas

2014-05-01

Analytical ecogeochemistry deals with the development and application of tools of analytical chemistry to study dynamic biological and ecological processes within ecosystems and across ecosystem boundaries in time. It can be best described as a linkage between modern analytical chemistry and a holistic understanding of ecosystems ('The total human ecosystem') within the frame of transdisciplinary research. One focus of analytical ecogeochemistry is the advanced analysis of elements and isotopes in abiotic and biotic matrices and the application of the results to basic questions in different research fields like ecology, environmental science, climatology, anthropology, forensics, archaeometry and provenancing. With continuous instrumental developments, new isotopic systems have been recognized for their potential to study natural processes and well established systems could be analyzed with improved techniques, especially using multi collector inductively coupled plasma mass spectrometry (MC-ICP-MS). For example, in case of S, isotope ratio measurements at high mass resolution could be achieved at much lower S concentrations with ICP-MS as compared to IRMS, still keeping suitable uncertainty. Almost 50 different isotope systems have been investigated by ICP-MS, so far, with - besides Sr, Pb and U - Ca, Mg, Cd, Li, Hg, Si, Ge and B being the most prominent and considerably pushing the limits of plasma based mass spectrometry also by applying high mass resolution. The use of laser ablation in combination with MC-ICP-MS offers the possibility to achieve isotopic information on high spatial (µm-range) and temporal scale (in case of incrementally growing structures). The information gained with these analytical techniques can be linked between different hierarchical scales in ecosystems, offering means to better understand ecosystem processes. The presentation will highlight the use of different isotopic systems in ecosystem studies accomplished by ICP-MS. Selected examples on combining isotopic systems for the study of ecosystem processes on different spatial scales will underpin the great opportunities substantiated by the field of analytical ecogeochemistry. Moreover, recent developments in plasma mass spectrometry and the application of new isotopic systems require sound metrological approaches in order to prevent scientific conclusions drawn from analytical artifacts.

Development of a robust space power system decision model

NASA Astrophysics Data System (ADS)

Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

2001-02-01

NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses.

PubMed

Montenegro-Burke, J Rafael; Phommavongsay, Thiery; Aisporna, Aries E; Huan, Tao; Rinehart, Duane; Forsberg, Erica; Poole, Farris L; Thorgersen, Michael P; Adams, Michael W W; Krantz, Gregory; Fields, Matthew W; Northen, Trent R; Robbins, Paul D; Niedernhofer, Laura J; Lairson, Luke; Benton, H Paul; Siuzdak, Gary

2016-10-04

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

PubMed Central

2016-01-01

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism. PMID:27560777

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

DOE PAGES

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.; ...

2016-08-25

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

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

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

Galaxy formation through hierarchical clustering

NASA Astrophysics Data System (ADS)

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

1991-09-01

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

In situ analysis of the organic framework in the prismatic layer of mollusc shell.

PubMed

Tong, Hua; Hu, Jiming; Ma, Wentao; Zhong, Guirong; Yao, Songnian; Cao, Nianxing

2002-06-01

A novel in situ analytic approach was constructed by means of ion sputtering, decalcification and deprotein techniques combining with scanning electron microscopy (SEM) and transmission electron microscope (TEM) ultrastructural analysis. The method was employed to determine the spatial distribution of the organic framework outside and the inner crystal and organic/inorganic interface spatial geometrical relationship in the prismatic layer of cristaris plicate (leach). The results show that there is a substructure of organic matrix in the intracrystalline region. The prismatic layer forms according to strict hierarchical configuration of regular pattern. Each unit of organic template of prismatic layer can uniquely determine the column crystal growth direction, spatial orientation and size. Cavity templates are responsible for supporting. limiting size and shape and determining the crystal growth spatial orientation, while the intracrystal organic matrix is responsible for providing nucleation point and inducing the nucleation process of calcite. The stereo hierarchical fabrication of prismatic layer was elucidated for the first time.

POLLUTION PREVENTION IN THE EARLY STAGES OF HIERARCHICAL PROCESS DESIGN

EPA Science Inventory

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

Fairness at the collective level: a meta-analytic examination of the consequences and boundary conditions of organizational justice climate.

PubMed

Whitman, Daniel S; Caleo, Suzette; Carpenter, Nichelle C; Horner, Margaret T; Bernerth, Jeremy B

2012-07-01

This article uses meta-analytic methods (k = 38) to examine the relationship between organizational justice climate and unit-level effectiveness. Overall, our results suggest that the relationship between justice and effectiveness is significant (ρ = .40) when both constructs are construed at the collective level. Our results also indicate that distributive justice climate was most strongly linked with unit-level performance (e.g., productivity, customer satisfaction), whereas interactional justice was most strongly related to unit-level processes (e.g., organizational citizenship behavior, cohesion). We also show that a number of factors moderate this relationship, including justice climate strength, the level of referent in the justice measure, the hierarchical level of the unit, and how criteria are classified. We elaborate on these findings and attempt to provide a clearer direction for future research in this area. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Human life support during interplanetary travel and domicile. III - Mars expedition system trade study

NASA Technical Reports Server (NTRS)

Seshan, P. K.; Ferrall, Joseph F.; Rohatgi, Naresh K.

1991-01-01

Several alternative configurations of life-support systems (LSSs) for a Mars missions are compared analytically on a quantitative basis in terms of weight, volume, and power. A baseline technology set is utilized for the illustrations of systems including totally open loop, carbon dioxide removal only, partially closed loop, and totally closed loop. The analytical model takes advantage of a modular, top-down hierarchical breakdown of LSS subsystems into functional elements that represent individual processing technologies. The open-loop systems are not competitive in terms of weight for both long-duration orbiters and short-duration lander vehicles, and power demands are lowest with the open loop and highest with the closed loop. The closed-loop system can reduce vehicle weight by over 70,000 lbs and thereby overcome the power penalty of 1600 W; the closed-loop variety is championed as the preferred system for a Mars expedition.

Whole mind and shared mind in clinical decision-making.

PubMed

Epstein, Ronald Mark

2013-02-01

To review the theory, research evidence and ethical implications regarding "whole mind" and "shared mind" in clinical practice in the context of chronic and serious illnesses. Selective critical review of the intersection of classical and naturalistic decision-making theories, cognitive neuroscience, communication research and ethics as they apply to decision-making and autonomy. Decision-making involves analytic thinking as well as affect and intuition ("whole mind") and sharing cognitive and affective schemas of two or more individuals ("shared mind"). Social relationships can help processing of complex information that otherwise would overwhelm individuals' cognitive capacities. Medical decision-making research, teaching and practice should consider both analytic and non-analytic cognitive processes. Further, research should consider that decisions emerge not only from the individual perspectives of patients, their families and clinicians, but also the perspectives that emerge from the interactions among them. Social interactions have the potential to enhance individual autonomy, as well as to promote relational autonomy based on shared frames of reference. Shared mind has the potential to result in wiser decisions, greater autonomy and self-determination; yet, clinicians and patients should be vigilant for the potential of hierarchical relationships to foster coercion or silencing of the patient's voice. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Processing of hierarchical syntactic structure in music.

PubMed

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

2013-09-17

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

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.

Using a matrix-analytical approach to synthesizing evidence solved incompatibility problem in the hierarchy of evidence.

PubMed

Walach, Harald; Loef, Martin

2015-11-01

The hierarchy of evidence presupposes linearity and additivity of effects, as well as commutativity of knowledge structures. It thereby implicitly assumes a classical theoretical model. This is an argumentative article that uses theoretical analysis based on pertinent literature and known facts to examine the standard view of methodology. We show that the assumptions of the hierarchical model are wrong. The knowledge structures gained by various types of studies are not sequentially indifferent, that is, do not commute. External validity and internal validity are at least partially incompatible concepts. Therefore, one needs a different theoretical structure, typical of quantum-type theories, to model this situation. The consequence of this situation is that the implicit assumptions of the hierarchical model are wrong, if generalized to the concept of evidence in total. The problem can be solved by using a matrix-analytical approach to synthesizing evidence. Here, research methods that produce different types of evidence that complement each other are synthesized to yield the full knowledge. We show by an example how this might work. We conclude that the hierarchical model should be complemented by a broader reasoning in methodology. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-Criteria Analysis of Uavs Regulations in 6 Countries Using the Analytical Hierarchical Process and Expert Knowledge

NASA Astrophysics Data System (ADS)

Morales, A. C.; Paez, D.; Arango, C.

2015-08-01

To analyze the current situation of Colombian regulation, it is necessary to compare some specific aspects with the legislation used in other countries where the UAVs topic dates to many years ago. This study is focused on evaluating all the possibilities to make the Colombian regulation effective without closing opportunities of research and development growth, but still guarantee the privacy and intimacy rights of the population. Results from our study are currently being used in the development of the Colombian regulation and they are proven useful to instigate informative debates and identify areas where specific needs are to be address in Colombia.

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

Magnetic hierarchical deposition

NASA Astrophysics Data System (ADS)

Posazhennikova, Anna I.; Indekeu, Joseph O.

2014-11-01

We consider random deposition of debris or blocks on a line, with block sizes following a rigorous hierarchy: the linear size equals 1/λn in generation n, in terms of a rescaling factor λ. Without interactions between the blocks, this model is described by a logarithmic fractal, studied previously, which is characterized by a constant increment of the length, area or volume upon proliferation. We study to what extent the logarithmic fractality survives, if each block is equipped with an Ising (pseudo-)spin s=±1 and the interactions between those spins are switched on (ranging from antiferromagnetic to ferromagnetic). It turns out that the dependence of the surface topology on the interaction sign and strength is not trivial. For instance, deep in the ferromagnetic regime, our numerical experiments and analytical results reveal a sharp crossover from a Euclidean transient, consisting of aggregated domains of aligned spins, to an asymptotic logarithmic fractal growth. In contrast, deep into the antiferromagnetic regime the surface roughness is important and is shown analytically to be controlled by vacancies induced by frustrated spins. Finally, in the weak interaction regime, we demonstrate that the non-interacting model is extremal in the sense that the effect of the introduction of interactions is only quadratic in the magnetic coupling strength. In all regimes, we demonstrate the adequacy of a mean-field approximation whenever vacancies are rare. In sum, the logarithmic fractal character is robust with respect to the introduction of spatial correlations in the hierarchical deposition process.

Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

PubMed

Zhou, Ronggang; Chan, Alan H S

2017-01-01

In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process.

Configurable product design considering the transition of multi-hierarchical models

NASA Astrophysics Data System (ADS)

Ren, Bin; Qiu, Lemiao; Zhang, Shuyou; Tan, Jianrong; Cheng, Jin

2013-03-01

The current research of configurable product design mainly focuses on how to convert a predefined set of components into a valid set of product structures. With the scale and complexity of configurable products increasing, the interdependencies between customer demands and product structures grow up as well. The result is that existing product structures fails to satisfy the individual customer requirements and hence product variants are needed. This paper is aimed to build a bridge between customer demands and product structures in order to make demand-driven fast response design feasible. First of all, multi-hierarchical models of configurable product design are established with customer demand model, technical requirement model and product structure model. Then, the transition of multi-hierarchical models among customer demand model, technical requirement model and product structure model is solved with fuzzy analytic hierarchy process (FAHP) and the algorithm of multi-level matching. Finally, optimal structure according to the customer demands is obtained with the calculation of Euclidean distance and similarity of some cases. In practice, the configuration design of a clamping unit of injection molding machine successfully performs an optimal search strategy for the product variants with reasonable satisfaction to individual customer demands. The proposed method can automatically generate a configuration design with better alternatives for each product structures, and shorten the time of finding the configuration of a product.

Preparation of a Co-doped hierarchically porous carbon from Co/Zn-ZIF: An efficient adsorbent for the extraction of trizine herbicides from environment water and white gourd samples.

PubMed

Jiao, Caina; Li, Menghua; Ma, Ruiyang; Wang, Chun; Wu, Qiuhua; Wang, Zhi

2016-05-15

A Co-doped hierarchically porous carbon (Co/HPC) was synthesized through a facile carbonization process by using Co/ZIF-8 as the precursor. The textures of the Co/HPC were investigated by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, vibration sample magnetometry and nitrogen adsorption-desorption isotherms. The results showed that the Co/HPC is in good polyhedral shape with uniform size, sufficient magnetism, high surface area as well as hierarchical pores (micro-, meso- and macropores). To evaluate the extraction performance of the Co/HPC, it was applied as a magnetic adsorbent for the enrichment of triazine herbicides from environment water and white gourd samples prior to high performance liquid chromatographic analysis. The main parameters that affected the extraction efficiency were investigated. Under the optimum conditions, a good linearity for the four triazine herbicides was achieved with the correlation coefficients (r) higher than 0.9970. The limits of detection, based on S/N=3, were 0.02 ng/mL for water and 0.1-0.2 ng/g for white gourd samples, respectively. The recoveries of all the analytes for the method fell in the range from 80.3% to 120.6%. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A hierarchical model for estimating change in American Woodcock populations

USGS Publications Warehouse

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

2008-01-01

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

A Hierarchical Multivariate Bayesian Approach to Ensemble Model output Statistics in Atmospheric Prediction

DTIC Science & Technology

2017-09-01

efficacy of statistical post-processing methods downstream of these dynamical model components with a hierarchical multivariate Bayesian approach to...Bayesian hierarchical modeling, Markov chain Monte Carlo methods , Metropolis algorithm, machine learning, atmospheric prediction 15. NUMBER OF PAGES...scale processes. However, this dissertation explores the efficacy of statistical post-processing methods downstream of these dynamical model components

Hierarchical Synthesis of Coastal Ecosystem Health Indicators at Karimunjawa National Marine Park

NASA Astrophysics Data System (ADS)

Danu Prasetya, Johan; Ambariyanto; Supriharyono; Purwanti, Frida

2018-02-01

The coastal ecosystem of Karimunjawa National Marine Park (KNMP) is facing various pressures, including from human activity. Monitoring the health condition of coastal ecosystems periodically is needed as an evaluation of the ecosystem condition. Systematic and consistent indicators are needed in monitoring of coastal ecosystem health. This paper presents hierarchical synthesis of coastal ecosystem health indicators using Analytic Hierarchy Process (AHP) method. Hierarchical synthesis is obtained from process of weighting by paired comparison based on expert judgments. The variables of coastal ecosystem health indicators in this synthesis consist of 3 level of variable, i.e. main variable, sub-variable and operational variable. As a result of assessment, coastal ecosystem health indicators consist of 3 main variables, i.e. State of Ecosystem, Pressure and Management. Main variables State of Ecosystem and Management obtain the same value i.e. 0.400, while Pressure value was 0.200. Each main variable consist of several sub-variable, i.e. coral reef, reef fish, mangrove and seagrass for State of Ecosystem; fisheries and marine tourism activity for Pressure; planning and regulation, institutional and also infrastructure and financing for Management. The highest value of sub-variable of main variable State of Ecosystem, Pressure and Management were coral reef (0.186); marine tourism pressure (0.133) and institutional (0.171), respectively. The highest value of operational variable of main variable State of Ecosystem, Pressure and Management were percent of coral cover (0.058), marine tourism pressure (0.133) and presence of zonation plan, regulation also socialization of monitoring program (0.53), respectively. Potential pressure from marine tourism activity is the variable that most affect the health of the ecosystem. The results of this research suggest that there is a need to develop stronger conservation strategies to facing with pressures from marine tourism activities.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Multi-indicator Evaluation System for Broadsword, Rod, Sword and Spear Athletes Based on Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Luo, Lin

2017-08-01

In the practical selection of Wushu athletes, the objective evaluation of the level of athletes lacks sufficient technical indicators and often relies on the coach’s subjective judgments. It is difficult to accurately and objectively reflect the overall quality of the athletes without a fully quantified indicator system, thus affecting the level improvement of Wushu competition. The analytic hierarchy process (AHP) is a systemic analysis method combining quantitative and qualitative analysis. This paper realizes structured, hierarchized and quantified decision-making process of evaluating broadsword, rod, sword and spear athletes in the AHP. Combing characteristics of the athletes, analysis is carried out from three aspects, i.e., the athlete’s body shape, physical function and sports quality and 18 specific evaluation indicators established, and then combining expert advice and practical experience, pairwise comparison matrix is determined, and then the weight of the indicators and comprehensive evaluation coefficient are obtained to establish the evaluation model for the athletes, thus providing a scientific theoretical basis for the selection of Wushu athletes. The evaluation model proposed in this paper has realized the evaluation system of broadsword, rod, sword and spear athletes, which has effectively improved the scientific level of Wushu athletes selection in practical application.

Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue.

PubMed

El Alami El Hassani, Nadia; Tahri, Khalid; Llobet, Eduard; Bouchikhi, Benachir; Errachid, Abdelhamid; Zine, Nadia; El Bari, Nezha

2018-03-15

Moroccan and French honeys from different geographical areas were classified and characterized by applying a voltammetric electronic tongue (VE-tongue) coupled to analytical methods. The studied parameters include color intensity, free lactonic and total acidity, proteins, phenols, hydroxymethylfurfural content (HMF), sucrose, reducing and total sugars. The geographical classification of different honeys was developed through three-pattern recognition techniques: principal component analysis (PCA), support vector machines (SVMs) and hierarchical cluster analysis (HCA). Honey characterization was achieved by partial least squares modeling (PLS). All the PLS models developed were able to accurately estimate the correct values of the parameters analyzed using as input the voltammetric experimental data (i.e. r>0.9). This confirms the potential ability of the VE-tongue for performing a rapid characterization of honeys via PLS in which an uncomplicated, cost-effective sample preparation process that does not require the use of additional chemicals is implemented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-criteria evaluation of sources for self-help domestic water supply

NASA Astrophysics Data System (ADS)

Nnaji, C. C.; Banigo, A.

2018-03-01

Two multi-criteria decision analysis methods were employed to evaluate six water sources. The analytical hierarchical process (AHP) ranked borehole highest with a rank of 0.321 followed by water board with a rank of 0.284. The other sources ranked far below these two as follows: water tanker (0.139), rainwater harvesting (0.117), shallow well (0.114) and stream (0.130). The Technique for Order Performance by Similarity to the Ideal Solution (TOPSIS) ranked water board highest with a rank of 0.865, followed by borehole with a value of 0.778. Quality and risk of contamination were found to be the most influential criteria while seasonality was the least.

Evaluation and Prediction of Water Resources Based on AHP

NASA Astrophysics Data System (ADS)

Li, Shuai; Sun, Anqi

2017-01-01

Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm. After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

[Big data, medical language and biomedical terminology systems].

PubMed

Schulz, Stefan; López-García, Pablo

2015-08-01

A variety of rich terminology systems, such as thesauri, classifications, nomenclatures and ontologies support information and knowledge processing in health care and biomedical research. Nevertheless, human language, manifested as individually written texts, persists as the primary carrier of information, in the description of disease courses or treatment episodes in electronic medical records, and in the description of biomedical research in scientific publications. In the context of the discussion about big data in biomedicine, we hypothesize that the abstraction of the individuality of natural language utterances into structured and semantically normalized information facilitates the use of statistical data analytics to distil new knowledge out of textual data from biomedical research and clinical routine. Computerized human language technologies are constantly evolving and are increasingly ready to annotate narratives with codes from biomedical terminology. However, this depends heavily on linguistic and terminological resources. The creation and maintenance of such resources is labor-intensive. Nevertheless, it is sensible to assume that big data methods can be used to support this process. Examples include the learning of hierarchical relationships, the grouping of synonymous terms into concepts and the disambiguation of homonyms. Although clear evidence is still lacking, the combination of natural language technologies, semantic resources, and big data analytics is promising.

Controllable fabrication of large-scale hierarchical silver nanostructures for long-term stable and ultrasensitive SERS substrates

NASA Astrophysics Data System (ADS)

Wu, Jing; Fang, Jinghuai; Cheng, Mingfei; Gong, Xiao

2016-09-01

In this work, we aim to prepare effective and long-term stable hierarchical silver nanostructures serving as surface-enhanced Raman scattering (SERS) substrates simply via displacement reaction on Aluminum foils. In our experiments, Hexadecyltrimethylammonium bromide (CTAB) is used as cationic surfactant to control the velocity of displacement reaction as well as the hierarchical morphology of the resultant. We find that the volume ratio of CTAB to AgNO3 plays a dominant role in regulating the hierarchical structures besides the influence of displacement reaction time. These as-prepared hierarchical morphologies demonstrate excellent SERS sensitivity, structural stability and reproducibility with low values of relative standard deviation less than 20 %. The high SERS analytical enhancement factor of ~6.7 × 108 is achieved even at the concentration of Crystal Violet (CV) as low as 10-7 M, which is sufficient for single-molecule detection. The detection limit of CV is 10-9 M in this study. We believe that this simple and rapid approach integrating advantages of low-cost production and high reproducibility would be a promising way to facilitate routine SERS detection and will get wide applications in chemical synthesis.

[Governance of primary health-care-based health-care organization].

PubMed

Báscolo, Ernesto

2010-01-01

An analytical framework was developed for explaining the conditions for the effectiveness of different strategies promoting integrated primary health-care (PHC) service-based systems in Latin-America. Different modes of governance (clan, incentives and hierarchy) were characterised from a political economics viewpoint for representing alternative forms of regulation promoting innovation in health-service-providing organisations. The necessary conditions for guaranteeing the modes of governance's effectiveness are presented, as are their implications in terms of posts in play. The institutional construction of an integrated health system is interpreted as being a product of a social process in which different modes of governance are combined, operating with different ways of resolving normative aspects for regulating service provision (with the hierarchical mode), resource distribution (with the incentives mode) and on the social values legitimising such process (with the clan mode).

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 Poly Tree Configurations for the Solution of Dynamically Refined Finte Element Models

NASA Technical Reports Server (NTRS)

Gute, G. D.; Padovan, J.

1993-01-01

This paper demonstrates how a multilevel substructuring technique, called the Hierarchical Poly Tree (HPT), can be used to integrate a localized mesh refinement into the original finite element model more efficiently. The optimal HPT configurations for solving isoparametrically square h-, p-, and hp-extensions on single and multiprocessor computers is derived. In addition, the reduced number of stiffness matrix elements that must be stored when employing this type of solution strategy is quantified. Moreover, the HPT inherently provides localize 'error-trapping' and a logical, efficient means with which to isolate physically anomalous and analytically singular behavior.

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…

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

NASA Technical Reports Server (NTRS)

Menasce, Daniel A.; Pentakalos, Odysseas I.

1995-01-01

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Preparation of Hierarchical Porous Silicalite-1 Encapsulated Ag NPs and Its Catalytic Performance for 4-Nitrophenol Reduction

NASA Astrophysics Data System (ADS)

Wang, Bin; Wang, Haojiang; Zhang, Fengwei; Sun, Tijian

2018-06-01

A facile and efficient strategy is presented for the encapsulation of Ag NPs within hierarchical porous silicalite-1. The physicochemical properties of the resultant catalyst are characterized by TEM, XRD, FTIR, and N2 adsorption-desorption analytical techniques. It turns out that the Ag NPs are well distributed in MFI zeolite framework, which possesses hierarchical porous characteristics (1.75, 3.96 nm), and the specific surface area is as high as 243 m2 · g-1. More importantly, such catalyst can rapidly transform the 4-nitrophenol to 4-aminophenol in aqueous solution at room temperature, and a quantitative conversion is also obtained after being reused 10 times. The reasons can be attributed to the fast mass transfer, large surface area, and spatial confinement effect of the advanced support.

The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, S.; Williams, D. N.; D'Anca, A.; Nassisi, P.; Aloisio, G.

2015-12-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a "datacube-oriented" framework responsible for atomically processing and manipulating scientific datasets, by providing a common way to run distributive tasks on large set of data fragments (chunks). Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes. The project relies on a strong background on high performance database management and On-Line Analytical Processing (OLAP) systems to manage large scientific datasets. The Ophidia analytics platform provides several data operators to manipulate datacubes (about 50), and array-based primitives (more than 100) to perform data analysis on large scientific data arrays. To address interoperability, Ophidia provides multiple server interfaces (e.g. OGC-WPS). From a client standpoint, a Python interface enables the exploitation of the framework into Python-based eco-systems/applications (e.g. IPython) and the straightforward adoption of a strong set of related libraries (e.g. SciPy, NumPy). The talk will highlight a key feature of the Ophidia framework stack: the "Analytics Workflow Management System" (AWfMS). The Ophidia AWfMS coordinates, orchestrates, optimises and monitors the execution of multiple scientific data analytics and visualization tasks, thus supporting "complex analytics experiments". Some real use cases related to the CMIP5 experiment will be discussed. In particular, with regard to the "Climate models intercomparison data analysis" case study proposed in the EU H2020 INDIGO-DataCloud project, workflows related to (i) anomalies, (ii) trend, and (iii) climate change signal analysis will be presented. Such workflows will be distributed across multiple sites - according to the datasets distribution - and will include intercomparison, ensemble, and outlier analysis. The two-level workflow solution envisioned in INDIGO (coarse grain for distributed tasks orchestration, and fine grain, at the level of a single data analytics cluster instance) will be presented and discussed.

Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework

PubMed Central

Zhou, Ronggang; Chan, Alan H. S.

2016-01-01

BACKGROUND: In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. OBJECTIVE: This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. METHODS: With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. RESULTS AND CONCLUSIONS: Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process. PMID:28035943

HPLC-PDA Combined with Chemometrics for Quantitation of Active Components and Quality Assessment of Raw and Processed Fruits of Xanthium strumarium L.

PubMed

Jiang, Hai; Yang, Liu; Xing, Xudong; Yan, Meiling; Guo, Xinyue; Yang, Bingyou; Wang, Qiuhong; Kuang, Haixue

2018-01-25

As a valuable herbal medicine, the fruits of Xanthium strumarium L. (Xanthii Fructus) have been widely used in raw and processed forms to achieve different therapeutic effects in practice. In this study, a comprehensive strategy was proposed for evaluating the active components in 30 batches of raw and processed Xanthii Fructus (RXF and PXF) samples, based on high-performance liquid chromatography coupled with photodiode array detection (HPLC-PDA). Twelve common peaks were detected and eight compounds of caffeoylquinic acids were simultaneously quantified in RXF and PXF. All the analytes were detected with satisfactory linearity (R² > 0.9991) over wide concentration ranges. Simultaneously, the chemically latent information was revealed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results suggest that there were significant differences between RXF and PXF from different regions in terms of the content of eight caffeoylquinic acids. Potential chemical markers for XF were found during processing by chemometrics.

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

PubMed

Malekmohammadi, Bahram; Tayebzadeh Moghadam, Negar

2018-04-13

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study, ERA was investigated using the Bayesian network (BN) model based on a hierarchical structure of variables in an influence diagram (ID). ID facilitated ranking of the different alternatives under uncertainty that were then used to evaluate comparisons of the different risk factors. BN was used to present a new model for ERA applicable to complicated development projects such as dam construction. The methodology was applied to the Gabric Dam, in southern Iran. The main environmental risk factors in the region, presented by the Gabric Dam, were identified based on the Delphi technique and specific features of the study area. These included the following: flood, water pollution, earthquake, changes in land use, erosion and sedimentation, effects on the population, and ecosensitivity. These risk factors were then categorized based on results from the output decision node of the BN, including expected utility values for risk factors in the decision node. ERA was performed for the Gabric Dam using the analytical hierarchy process (AHP) method to compare results of BN modeling with those of conventional methods. Results determined that a BN-based hierarchical structure to ERA present acceptable and reasonable risk assessment prioritization in proposing suitable solutions to reduce environmental risks and can be used as a powerful decision support system for evaluating environmental risks.

Hierarchical extreme learning machine based reinforcement learning for goal localization

NASA Astrophysics Data System (ADS)

AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini

2017-03-01

The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.

Mental structures and hierarchical brain processing. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

NASA Astrophysics Data System (ADS)

Petkov, C. I.

2014-09-01

Fitch proposes an appealing hypothesis that humans are dendrophiles, who constantly build mental trees supported by analogous hierarchical brain processes [1]. Moreover, it is argued that, by comparison, nonhuman animals build flat or more compact behaviorally-relevant structures. Should we thus expect less impressive hierarchical brain processes in other animals? Not necessarily.

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.

The Hierarchical Cortical Organization of Human Speech Processing

PubMed Central

de Heer, Wendy A.; Huth, Alexander G.; Griffiths, Thomas L.

2017-01-01

Speech comprehension requires that the brain extract semantic meaning from the spectral features represented at the cochlea. To investigate this process, we performed an fMRI experiment in which five men and two women passively listened to several hours of natural narrative speech. We then used voxelwise modeling to predict BOLD responses based on three different feature spaces that represent the spectral, articulatory, and semantic properties of speech. The amount of variance explained by each feature space was then assessed using a separate validation dataset. Because some responses might be explained equally well by more than one feature space, we used a variance partitioning analysis to determine the fraction of the variance that was uniquely explained by each feature space. Consistent with previous studies, we found that speech comprehension involves hierarchical representations starting in primary auditory areas and moving laterally on the temporal lobe: spectral features are found in the core of A1, mixtures of spectral and articulatory in STG, mixtures of articulatory and semantic in STS, and semantic in STS and beyond. Our data also show that both hemispheres are equally and actively involved in speech perception and interpretation. Further, responses as early in the auditory hierarchy as in STS are more correlated with semantic than spectral representations. These results illustrate the importance of using natural speech in neurolinguistic research. Our methodology also provides an efficient way to simultaneously test multiple specific hypotheses about the representations of speech without using block designs and segmented or synthetic speech. SIGNIFICANCE STATEMENT To investigate the processing steps performed by the human brain to transform natural speech sound into meaningful language, we used models based on a hierarchical set of speech features to predict BOLD responses of individual voxels recorded in an fMRI experiment while subjects listened to natural speech. Both cerebral hemispheres were actively involved in speech processing in large and equal amounts. Also, the transformation from spectral features to semantic elements occurs early in the cortical speech-processing stream. Our experimental and analytical approaches are important alternatives and complements to standard approaches that use segmented speech and block designs, which report more laterality in speech processing and associated semantic processing to higher levels of cortex than reported here. PMID:28588065

Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

PubMed

Caesar, Lindsay K; Kvalheim, Olav M; Cech, Nadja B

2018-08-27

Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in all data sets. This work highlights the importance of technical replication in mass spectrometry-based studies, and presents a new application of HCA as a tool for evaluating the effectiveness of data filtering prior to statistical analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

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

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…

Pushing Typists Back on the Learning Curve: Memory Chunking in the Hierarchical Control of Skilled Typewriting

ERIC Educational Resources Information Center

Yamaguchi, Motonori; Logan, Gordon D.

2016-01-01

Hierarchical control of skilled performance depends on the ability of higher level control to process several lower level units as a single chunk. The present study investigated the development of hierarchical control of skilled typewriting, focusing on the process of memory chunking. In the first 3 experiments, skilled typists typed words or…

Development of an intelligent diagnostic system for reusable rocket engine control

NASA Technical Reports Server (NTRS)

Anex, R. P.; Russell, J. R.; Guo, T.-H.

1991-01-01

A description of an intelligent diagnostic system for the Space Shuttle Main Engines (SSME) is presented. This system is suitable for incorporation in an intelligent controller which implements accommodating closed-loop control to extend engine life and maximize available performance. The diagnostic system architecture is a modular, hierarchical, blackboard system which is particularly well suited for real-time implementation of a system which must be repeatedly updated and extended. The diagnostic problem is formulated as a hierarchical classification problem in which the failure hypotheses are represented in terms of predefined data patterns. The diagnostic expert system incorporates techniques for priority-based diagnostics, the combination of analytical and heuristic knowledge for diagnosis, integration of different AI systems, and the implementation of hierarchical distributed systems. A prototype reusable rocket engine diagnostic system (ReREDS) has been implemented. The prototype user interface and diagnostic performance using SSME test data are described.

Insights into the hierarchical structure and digestion rate of alkali-modulated starches with different amylose contents.

PubMed

Qiao, Dongling; Yu, Long; Liu, Hongsheng; Zou, Wei; Xie, Fengwei; Simon, George; Petinakis, Eustathios; Shen, Zhiqi; Chen, Ling

2016-06-25

Combined analytical techniques were used to explore the effects of alkali treatment on the multi-scale structure and digestion behavior of starches with different amylose/amylopectin ratios. Alkali treatment disrupted the amorphous matrix, and partial lamellae and crystallites, which weakened starch molecular packing and eventually enhanced the susceptibility of starch to alkali. Stronger alkali treatment (0.5% w/w) made this effect more prominent and even transformed the dual-phase digestion of starch into a triple-phase pattern. Compared with high-amylose starch, regular maize starch, which possesses some unique structure characteristics typically as pores and crystallite weak points, showed evident changes of hierarchical structure and in digestion rate. Thus, alkali treatment has been demonstrated as a simple method to modulate starch hierarchical structure and thus to realize the rational development of starch-based food products with desired digestibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Topological dimension tunes activity patterns in hierarchical modular networks

NASA Astrophysics Data System (ADS)

Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.

2017-11-01

Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.

Ag-NP@Ge-nanotaper/Si-micropillar ordered arrays as ultrasensitive and uniform surface enhanced Raman scattering substrates.

PubMed

Liu, Jing; Meng, Guowen; Li, Zhongbo; Huang, Zhulin; Li, Xiangdong

2015-11-21

Surface-enhanced Raman scattering (SERS) is considered to be an excellent candidate for analytical detection schemes, because of its molecular specificity, rapid response and high sensitivity. Here, SERS-substrates of Ag-nanoparticle (Ag-NP) decorated Ge-nanotapers grafted on hexagonally ordered Si-micropillar (denoted as Ag-NP@Ge-nanotaper/Si-micropillar) arrays are fabricated via a combinatorial process of two-step etching to achieve hexagonal Si-micropillar arrays, chemical vapor deposition of flocky Ge-nanotapers on each Si-micropillar and decoration of Ag-NPs onto the Ge-nanotapers through galvanic displacement. With high density three-dimensional (3D) "hot spots" created from the large quantities of the neighboring Ag-NPs and large-scale uniform morphology, the hierarchical Ag-NP@Ge-nanotaper/Si-micropillar arrays exhibit strong and reproducible SERS activity. Using our hierarchical 3D SERS-substrates, both methyl parathion (a commonly used pesticide) and PCB-2 (one congener of highly toxic polychlorinated biphenyls) with concentrations down to 10(-7) M and 10(-5) M have been detected respectively, showing great potential in SERS-based rapid trace-level detection of toxic organic pollutants in the environment.

Multicritical points for spin-glass models on hierarchical lattices.

PubMed

Ohzeki, Masayuki; Nishimori, Hidetoshi; Berker, A Nihat

2008-06-01

The locations of multicritical points on many hierarchical lattices are numerically investigated by the renormalization group analysis. The results are compared with an analytical conjecture derived by using the duality, the gauge symmetry, and the replica method. We find that the conjecture does not give the exact answer but leads to locations slightly away from the numerically reliable data. We propose an improved conjecture to give more precise predictions of the multicritical points than the conventional one. This improvement is inspired by a different point of view coming from the renormalization group and succeeds in deriving very consistent answers with many numerical data.

Hierarchical damage mechanisms in composite materials subjected to fatigue loadings

NASA Astrophysics Data System (ADS)

D'Amore, Alberto; Grassia, Luigi

2018-02-01

The strength degradation of fiber reinforced composites subjected to constant amplitude (CA) fatigue loadings can be described by a two-parameter residual strength model. From the analytical approach it results that under moderate loadings the multiple damage mechanisms develop with different kinetics and manifest their effectiveness at different time scales highlighting the three-Stage hierarchical nature of damage accumulation in composites. The model captures the sequence of damage accumulation mechanisms from diffuse matrix cracking (I), to fiber/matrix interface failure (II) to fiber and ply rupture and delamination (III). Further, by increasing the loading severity it appears that the different mechanisms superpose witnessing their simultaneous co-existence.

Impartiality and Hierarchical Evaluations in the Japanese Development Aid Community

ERIC Educational Resources Information Center

Maemura, Yu

2016-01-01

This article presents a discourse analytic study of how the concept of impartiality is socially constructed by members of the development aid community through an examination of linguistic traits and patterns within (a) inter- and intraorganizational interactions and (b) relevant aid evaluation policy documents. A qualitative analysis of…

GC-MS (GAS CHROMATOGRAPHIC-MASS SPECTROMETRIC) SUITABILITY TESTING OF RCRA APPENDIX VIII AND MICHIGAN LIST ANALYTES

EPA Science Inventory

As a first step in a hierarchical scheme to demonstrate the suitability of present U.S. Environmental Protection Agency (USEPA) analysis methods and/or develop new methodology, the gas chromatographic (GC) separation and mass spectrometric (MS) detection characteristics of 328 to...

Recent activities within the Aeroservoelasticity Branch at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Noll, Thomas E.; Perry, Boyd, III; Gilbert, Michael G.

1989-01-01

The objective of research in aeroservoelasticity at the NASA Langley Research Center is to enhance the modeling, analysis, and multidisciplinary design methodologies for obtaining multifunction digital control systems for application to flexible flight vehicles. Recent accomplishments are discussed, and a status report on current activities within the Aeroservoelasticity Branch is presented. In the area of modeling, improvements to the Minimum-State Method of approximating unsteady aerodynamics are shown to provide precise, low-order aeroservoelastic models for design and simulation activities. Analytical methods based on Matched Filter Theory and Random Process Theory to provide efficient and direct predictions of the critical gust profile and the time-correlated gust loads for linear structural design considerations are also discussed. Two research projects leading towards improved design methodology are summarized. The first program is developing an integrated structure/control design capability based on hierarchical problem decomposition, multilevel optimization and analytical sensitivities. The second program provides procedures for obtaining low-order, robust digital control laws for aeroelastic applications. In terms of methodology validation and application the current activities associated with the Active Flexible Wing project are reviewed.

Research on evaluation of third-party governance operation services for environmental pollution

NASA Astrophysics Data System (ADS)

Xu, Bingsheng; Ling, Lin; Jin, Huang

2017-11-01

This paper focuses on the evaluation of third-party governance operation services for environmental pollution, and determines the evaluation indicator system composed of 5 primary indicators as the basic competence of enterprise, operation of equipment, technique economics, environmental benefit and management level, and 26 secondary indicators via policies and regulations, standards, literature research and expert consultation in combination with the composition elements, service value judgment factors and full-life cycle of the work, providing theoretical support for the effect evaluation of third-governance over the environmental pollution in China. Then, the hierarchical analytic matrix is formed by analyzing the environmental pollution governance evaluation indicator system via analytic hierarchy process and scoring the importance of various indicators by experts by applying the Delphi method. The feature vector of the matrix is then calculated to obtain the weight of each indicator and verify the effectiveness of the Delphi method and obtain the comprehensive weight by judging the consistency of the matrix, so as to finally determine the overall ordering level of the importance of secondary indicators.

An Empirical Study of Eight Nonparametric Tests in Hierarchical Regression.

ERIC Educational Resources Information Center

Harwell, Michael; Serlin, Ronald C.

When normality does not hold, nonparametric tests represent an important data-analytic alternative to parametric tests. However, the use of nonparametric tests in educational research has been limited by the absence of easily performed tests for complex experimental designs and analyses, such as factorial designs and multiple regression analyses,…

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.

Generalized Hill-stability criteria for hierarchical three-body systems at arbitrary inclinations

NASA Astrophysics Data System (ADS)

Grishin, Evgeni; Perets, Hagai B.; Zenati, Yossef; Michaely, Erez

2017-04-01

A fundamental aspect of the three-body problem is its stability. Most stability studies have focused on the co-planar three-body problem, deriving analytic criteria for the dynamical stability of such pro/retrograde systems. Numerical studies of inclined systems phenomenologically mapped their stability regions, but neither complement it by theoretical framework, nor provided satisfactory fit for their dependence on mutual inclinations. Here we present a novel approach to study the stability of hierarchical three-body systems at arbitrary inclinations, which accounts not only for the instantaneous stability of such systems, but also for the secular stability and evolution through Lidov-Kozai cycles and evection. We generalize the Hill-stability criteria to arbitrarily inclined triple systems, explain the existence of quasi-stable regimes and characterize the inclination dependence of their stability. We complement the analytic treatment with an extensive numerical study, to test our analytic results. We find excellent correspondence up to high inclinations (˜120°), beyond which the agreement is marginal. At such high inclinations, the stability radius is larger, the ratio between the outer and inner periods becomes comparable and our secular averaging approach is no longer strictly valid. We therefore combine our analytic results with polynomial fits to the numerical results to obtain a generalized stability formula for triple systems at arbitrary inclinations. Besides providing a generalized secular-based physical explanation for the stability of non-co-planar systems, our results have direct implications for any triple systems and, in particular, binary planets and moon/satellite systems; we briefly discuss the latter as a test case for our models.

Parallel-hierarchical processing and classification of laser beam profile images based on the GPU-oriented architecture

NASA Astrophysics Data System (ADS)

Yarovyi, Andrii A.; Timchenko, Leonid I.; Kozhemiako, Volodymyr P.; Kokriatskaia, Nataliya I.; Hamdi, Rami R.; Savchuk, Tamara O.; Kulyk, Oleksandr O.; Surtel, Wojciech; Amirgaliyev, Yedilkhan; Kashaganova, Gulzhan

2017-08-01

The paper deals with a problem of insufficient productivity of existing computer means for large image processing, which do not meet modern requirements posed by resource-intensive computing tasks of laser beam profiling. The research concentrated on one of the profiling problems, namely, real-time processing of spot images of the laser beam profile. Development of a theory of parallel-hierarchic transformation allowed to produce models for high-performance parallel-hierarchical processes, as well as algorithms and software for their implementation based on the GPU-oriented architecture using GPGPU technologies. The analyzed performance of suggested computerized tools for processing and classification of laser beam profile images allows to perform real-time processing of dynamic images of various sizes.

A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

NASA Astrophysics Data System (ADS)

Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

2017-09-01

Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

Modular and hierarchical structure of social contact networks

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

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.

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 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.

ClipCard: Sharable, Searchable Visual Metadata Summaries on the Cloud to Render Big Data Actionable

NASA Astrophysics Data System (ADS)

Saripalli, P.; Davis, D.; Cunningham, R.

2013-12-01

Research firm IDC estimates that approximately 90 percent of the Enterprise Big Data go un-analyzed, as 'dark data' - an enormous corpus of undiscovered, untagged information residing on data warehouses, servers and Storage Area Networks (SAN). In the geosciences, these data range from unpublished model runs to vast survey data assets to raw sensor data. Many of these are now being collected instantaneously, at a greater volume and in new data formats. Not all of these data can be analyzed, nor processed in real time, and their features may not be well described at the time of collection. These dark data are a serious data management problem for science organizations of all types, especially ones with mandated or required data reporting and compliance requirements. Additionally, data curators and scientists are encouraged to quantify the impact of their data holdings as a way to measure research success. Deriving actionable insights is the foremost goal of Big Data Analytics (BDA), which is especially true with geoscience, given its direct impact on most of the pressing global issues. Clearly, there is a pressing need for innovative approaches to making dark data discoverable, measurable, and actionable. We report on ClipCard, a Cloud-based SaaS analytic platform for instant summarization, quick search, visualization and easy sharing of metadata summaries form the Dark Data at hierarchical levels of detail, thus rendering it 'white', i.e., actionable. We present a use case of the ClipCard platform, a cloud-based application which helps generate (abstracted) visual metadata summaries and meta-analytics for environmental data at hierarchical scales within and across big data containers. These summaries and analyses provide important new tools for managing big data and simplifying collaboration through easy to deploy sharing APIs. The ClipCard application solves a growing data management bottleneck by helping enterprises and large organizations to summarize, search, discover, and share the potential in their unused data and information assets. Using Cloud as the base platform enables wider reach, quick dissemination and easy sharing of the metadata summaries, without actually storing or sharing the original data assets per se.

Conceptual hierarchical modeling to describe wetland plant community organization

USGS Publications Warehouse

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

2010-01-01

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

Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram.

PubMed

Colligan, Lacey; Anderson, Janet E; Potts, Henry W W; Berman, Jonathan

2010-01-07

Many quality and safety improvement methods in healthcare rely on a complete and accurate map of the process. Process mapping in healthcare is often achieved using a sequential flow diagram, but there is little guidance available in the literature about the most effective type of process map to use. Moreover there is evidence that the organisation of information in an external representation affects reasoning and decision making. This exploratory study examined whether the type of process map - sequential or hierarchical - affects healthcare practitioners' judgments. A sequential and a hierarchical process map of a community-based anti coagulation clinic were produced based on data obtained from interviews, talk-throughs, attendance at a training session and examination of protocols and policies. Clinic practitioners were asked to specify the parts of the process that they judged to contain quality and safety concerns. The process maps were then shown to them in counter-balanced order and they were asked to circle on the diagrams the parts of the process where they had the greatest quality and safety concerns. A structured interview was then conducted, in which they were asked about various aspects of the diagrams. Quality and safety concerns cited by practitioners differed depending on whether they were or were not looking at a process map, and whether they were looking at a sequential diagram or a hierarchical diagram. More concerns were identified using the hierarchical diagram compared with the sequential diagram and more concerns were identified in relation to clinical work than administrative work. Participants' preference for the sequential or hierarchical diagram depended on the context in which they would be using it. The difficulties of determining the boundaries for the analysis and the granularity required were highlighted. The results indicated that the layout of a process map does influence perceptions of quality and safety problems in a process. In quality improvement work it is important to carefully consider the type of process map to be used and to consider using more than one map to ensure that different aspects of the process are captured.

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.

A strategy for prediction of the elastic properties of epoxy-cellulose nanocrystal-reinforced fiber networks

Treesearch

Johnathan E. Goodsell; Robert J. Moon; Alionso Huizar; R. Byron Pipes

2014-01-01

The reinforcement potential of cellulose nanocrystal (CNC) additions on an idealized 2-dirmensional (2-D) fiber network structure consisting of micron sized fiber elements was investigated. The reinforcement mechanism considered in this study was through the stiffening of the micron sized fiber elements via a CNC-epoxy coating. A hierarchical analytical modeling...

Illustration of a Multilevel Model for Meta-Analysis

ERIC Educational Resources Information Center

de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

2007-01-01

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

The Challenge of Separating Effects of Simultaneous Education Projects on Student Achievement

ERIC Educational Resources Information Center

Ma, Xin; Ma, Lingling

2009-01-01

When multiple education projects operate in an overlapping or rear-ended manner, it is always a challenge to separate unique project effects on schooling outcomes. Our analysis represents a first attempt to address this challenge. A three-level hierarchical linear model (HLM) was presented as a general analytical framework to separate program…

The Ophidia framework: toward cloud-based data analytics for climate change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Elia, Donatello; Mancini, Marco; Mariello, Andrea; Mirto, Maria; Palazzo, Cosimo; Aloisio, Giovanni

2015-04-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in the climate change domain. It provides parallel (server-side) data analysis, an internal storage model and a hierarchical data organization to manage large amount of multidimensional scientific data. The Ophidia analytics platform provides several MPI-based parallel operators to manipulate large datasets (data cubes) and array-based primitives to perform data analysis on large arrays of scientific data. The most relevant data analytics use cases implemented in national and international projects target fire danger prevention (OFIDIA), interactions between climate change and biodiversity (EUBrazilCC), climate indicators and remote data analysis (CLIP-C), sea situational awareness (TESSA), large scale data analytics on CMIP5 data in NetCDF format, Climate and Forecast (CF) convention compliant (ExArch). Two use cases regarding the EU FP7 EUBrazil Cloud Connect and the INTERREG OFIDIA projects will be presented during the talk. In the former case (EUBrazilCC) the Ophidia framework is being extended to integrate scalable VM-based solutions for the management of large volumes of scientific data (both climate and satellite data) in a cloud-based environment to study how climate change affects biodiversity. In the latter one (OFIDIA) the data analytics framework is being exploited to provide operational support regarding processing chains devoted to fire danger prevention. To tackle the project challenges, data analytics workflows consisting of about 130 operators perform, among the others, parallel data analysis, metadata management, virtual file system tasks, maps generation, rolling of datasets, import/export of datasets in NetCDF format. Finally, the entire Ophidia software stack has been deployed at CMCC on 24-nodes (16-cores/node) of the Athena HPC cluster. Moreover, a cloud-based release tested with OpenNebula is also available and running in the private cloud infrastructure of the CMCC Supercomputing Centre.

INCORPORATING INDUSTRIAL ECOLOGY INTO HIERARCHICAL CHEMICAL PROCESS DESIGN

EPA Science Inventory

Incorporating Industrial Ecology into Hierarchical Chemical Process Design: Determining Targets for the Exchange of Waste

The exchange of waste to be used as a recycled feed has long been encouraged by practitioners of industrial ecology. Industrial ecology is a field t...

Decision-Oriented Health Technology Assessment: One Step Forward in Supporting the Decision-Making Process in Hospitals.

PubMed

Ritrovato, Matteo; Faggiano, Francesco C; Tedesco, Giorgia; Derrico, Pietro

2015-06-01

This article outlines the Decision-Oriented Health Technology Assessment: a new implementation of the European network for Health Technology Assessment Core Model, integrating the multicriteria decision-making analysis by using the analytic hierarchy process to introduce a standardized methodological approach as a valued and shared tool to support health care decision making within a hospital. Following the Core Model as guidance (European network for Health Technology Assessment. HTA core model for medical and surgical interventions. Available from: http://www.eunethta.eu/outputs/hta-core-model-medical-and-surgical-interventions-10r. [Accessed May 27, 2014]), it is possible to apply the analytic hierarchy process to break down a problem into its constituent parts and identify priorities (i.e., assigning a weight to each part) in a hierarchical structure. Thus, it quantitatively compares the importance of multiple criteria in assessing health technologies and how the alternative technologies perform in satisfying these criteria. The verbal ratings are translated into a quantitative form by using the Saaty scale (Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci 2008;1:83-98). An eigenvectors analysis is used for deriving the weights' systems (i.e., local and global weights' system) that reflect the importance assigned to the criteria and the priorities related to the performance of the alternative technologies. Compared with the Core Model, this methodological approach supplies a more timely as well as contextualized evidence for a specific technology, making it possible to obtain data that are more relevant and easier to interpret, and therefore more useful for decision makers to make investment choices with greater awareness. We reached the conclusion that although there may be scope for improvement, this implementation is a step forward toward the goal of building a "solid bridge" between the scientific evidence and the final decision maker's choice. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

An Optoelectronic Nose for Detection of Toxic Gases

PubMed Central

Lim, Sung H.; Feng, Liang; Kemling, Jonathan W.; Musto, Christopher J.; Suslick, Kenneth S.

2009-01-01

We have developed a simple colorimetric sensor array (CSA) for the detection of a wide range of volatile analytes and applied it to the detection of toxic gases. The sensor consists of a disposable array of cross-responsive nanoporous pigments whose colors are changed by diverse chemical interactions with analytes. Although no single chemically responsive pigment is specific for any one analyte, the pattern of color change for the array is a unique molecular fingerprint. Clear differentiation among 19 different toxic industrial chemicals (TICs) within two minutes of exposure at IDLH (immediately dangerous to life or health) concentration has been demonstrated. Quantification of each analyte is easily accomplished based on the color change of the array, and excellent detection limits have been demonstrated, generally below the PELs (permissible exposure limits). Identification of the TICs was readily achieved using a standard chemometric approach, i.e., hierarchical clustering analysis (HCA), with no misclassifications over 140 trials. PMID:20160982

An optoelectronic nose for the detection of toxic gases.

PubMed

Lim, Sung H; Feng, Liang; Kemling, Jonathan W; Musto, Christopher J; Suslick, Kenneth S

2009-10-01

We have developed a simple colorimetric sensor array that detects a wide range of volatile analytes and then applied it to the detection of toxic gases. The sensor consists of a disposable array of cross-responsive nanoporous pigments with colours that are changed by diverse chemical interactions with analytes. Although no single chemically responsive pigment is specific for any one analyte, the pattern of colour change for the array is a unique molecular fingerprint. Clear differentiation among 19 different toxic industrial chemicals (TICs) within two minutes of exposure at concentrations immediately dangerous to life or health were demonstrated. Based on the colour change of the array, quantification of each analyte was accomplished easily, and excellent detection limits were achieved, generally below the permissible exposure limits. Different TICs were identified readily using a standard chemometric approach (hierarchical clustering analysis), with no misclassifications over 140 trials.

Parallelized modelling and solution scheme for hierarchically scaled simulations

NASA Technical Reports Server (NTRS)

Padovan, Joe

1995-01-01

This two-part paper presents the results of a benchmarked analytical-numerical investigation into the operational characteristics of a unified parallel processing strategy for implicit fluid mechanics formulations. This hierarchical poly tree (HPT) strategy is based on multilevel substructural decomposition. The Tree morphology is chosen to minimize memory, communications and computational effort. The methodology is general enough to apply to existing finite difference (FD), finite element (FEM), finite volume (FV) or spectral element (SE) based computer programs without an extensive rewrite of code. In addition to finding large reductions in memory, communications, and computational effort associated with a parallel computing environment, substantial reductions are generated in the sequential mode of application. Such improvements grow with increasing problem size. Along with a theoretical development of general 2-D and 3-D HPT, several techniques for expanding the problem size that the current generation of computers are capable of solving, are presented and discussed. Among these techniques are several interpolative reduction methods. It was found that by combining several of these techniques that a relatively small interpolative reduction resulted in substantial performance gains. Several other unique features/benefits are discussed in this paper. Along with Part 1's theoretical development, Part 2 presents a numerical approach to the HPT along with four prototype CFD applications. These demonstrate the potential of the HPT strategy.

Leading processes of patient care and treatment in hierarchical healthcare organizations in Sweden--process managers' experiences.

PubMed

Nilsson, Kerstin; Sandoff, Mette

2015-01-01

The purpose of this study is to gain better understanding of the roles and functions of process managers by describing Swedish process managers' experiences of leading processes involving patient care and treatment when working in a hierarchical health-care organization. This study is based on an explorative design. The data were gathered from interviews with 12 process managers at three Swedish hospitals. These data underwent qualitative and interpretative analysis with a modified editing style. The process managers' experiences of leading processes in a hierarchical health-care organization are described under three themes: having or not having a mandate, exposure to conflict situations and leading process development. The results indicate a need for clarity regarding process manager's responsibility and work content, which need to be communicated to all managers and staff involved in the patient care and treatment process, irrespective of department. There also needs to be an emphasis on realistic expectations and orientation of the goals that are an intrinsic part of the task of being a process manager. Generalizations from the results of the qualitative interview studies are limited, but a deeper understanding of the phenomenon was reached, which, in turn, can be transferred to similar settings. This study contributes qualitative descriptions of leading care and treatment processes in a functional, hierarchical health-care organization from process managers' experiences, a subject that has not been investigated earlier.

Is it time to Leave Behind the Revised Hierarchical Model of Bilingual Language Processing after Fifteen Years of Service?

ERIC Educational Resources Information Center

Brysbaert, Marc; Duyck, Wouter

2010-01-01

The Revised Hierarchical Model (RHM) of bilingual language processing dominates current thinking on bilingual language processing. Recently, basic tenets of the model have been called into question. First, there is little evidence for separate lexicons. Second, there is little evidence for language selective access. Third, the inclusion of…

An assembly process model based on object-oriented hierarchical time Petri Nets

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Liu, Shaoli; Liu, Jianhua; Du, Zenghui

2017-04-01

In order to improve the versatility, accuracy and integrity of the assembly process model of complex products, an assembly process model based on object-oriented hierarchical time Petri Nets is presented. A complete assembly process information model including assembly resources, assembly inspection, time, structure and flexible parts is established, and this model describes the static and dynamic data involved in the assembly process. Through the analysis of three-dimensional assembly process information, the assembly information is hierarchically divided from the whole, the local to the details and the subnet model of different levels of object-oriented Petri Nets is established. The communication problem between Petri subnets is solved by using message database, and it reduces the complexity of system modeling effectively. Finally, the modeling process is presented, and a five layer Petri Nets model is established based on the hoisting process of the engine compartment of a wheeled armored vehicle.

Durable polyorganosiloxane superhydrophobic films with a hierarchical structure by sol-gel and heat treatment method

NASA Astrophysics Data System (ADS)

Jiang, Zhenlin; Fang, Shuying; Wang, Chaosheng; Wang, Huaping; Ji, Chengchang

2016-12-01

For a surface to be superhydrophobic a combination of surface roughness and low surface energy is required. In this study, polyorganosiloxane superhydrophobic surfaces were fabricated using a sol-gel and heat treatment process followed by coating with a nanosilica (SiO2) sol and organosiloxane 1, 1, 1, 3, 5, 5, 5-heptamethyl-3-[2-(trimethoxysilyl)ethyl]-trisiloxane (β-HPEOs). The nano-structure was superimposed using self-assembled, surface-modified silica nanoparticles, forming two-dimensional hierarchical structures. The water contact angle (WCA) of polyorganosiloxane superhydrophobic surface was 143.7 ± 0.6°, which was further increased to 156.7 ± 1.1° with water angle hysteresis of 2.5 ± 0.6° by superimposing nanoparticles using a heat treatment process. An analytical characterization of the surface revealed that the nano-silica and polyorganosiloxane formed a micro/nano structure on the films and the wetting behaviour of the films changed from hydrophilic to superhydrophobic. The WCA of these films were 143.7 ± 0.6° and at heat treatment temperatures of less than 400 °C, the WCA increased from 144.5 ± 0.7° to 156.7 ± 1.1°. The prepared superhydrophobic films were stable even after heat treatment at 430 °C for 30 min and their superhydrophobicity was durable for more than 120 days. The effects of heat treatment process on the surface chemistry structure, wettability and morphology of the polyorganosiloxane superhydrophobic films were investigated in detail. The results indicated that the stability of the chemical structure was required to yield a thermally-stable superhydrophobic surface.

Coastal vulnerability assessment of Puducherry coast, India using analytical hierarchical process

NASA Astrophysics Data System (ADS)

Mani Murali, R.; Ankita, M.; Amrita, S.; Vethamony, P.

2013-03-01

Increased frequency of natural hazards such as storm surge, tsunami and cyclone, as a consequence of change in global climate, is predicted to have dramatic effects on the coastal communities and ecosystems by virtue of the devastation they cause during and after their occurrence. The tsunami of December 2004 and the Thane cyclone of 2011 caused extensive human and economic losses along the coastline of Puducherry and Tamil Nadu. The devastation caused by these events highlighted the need for vulnerability assessment to ensure better understanding of the elements causing different hazards and to consequently minimize the after-effects of the future events. This paper advocates an Analytical Hierarchical Process (AHP) based approach to coastal vulnerability studies as an improvement to the existing methodologies for vulnerability assessment. The paper also encourages the inclusion of socio-economic parameters along with the physical parameters to calculate the coastal vulnerability index using AHP derived weights. Seven physical-geological parameters (slope, geomorphology, elevation, shoreline change, sea level rise, significant wave height and tidal range) and four socio-economic factors (population, Land-use/Land-cover (LU/LC), roads and location of tourist places) are considered to measure the Physical Vulnerability Index (PVI) as well as the Socio-economic Vulnerability Index (SVI) of the Puducherry coast. Based on the weights and scores derived using AHP, vulnerability maps are prepared to demarcate areas with very low, medium and high vulnerability. A combination of PVI and SVI values are further utilized to compute the Coastal Vulnerability Index (CVI). Finally, the various coastal segments are grouped into the 3 vulnerability classes to obtain the final coastal vulnerability map. The entire coastal extent between Muthiapet and Kirumampakkam as well as the northern part of Kalapet is designated as the high vulnerability zone which constitutes 50% of the coastline. The region between the southern coastal extent of Kalapet and Lawspet is the medium vulnerability zone and the rest 25% is the low vulnerability zone. The results obtained, enable to identify and prioritize the more vulnerable areas of the region to further assist the government and the residing coastal communities in better coastal management and conservation.

Coastal vulnerability assessment of Puducherry coast, India, using the analytical hierarchical process

NASA Astrophysics Data System (ADS)

Mani Murali, R.; Ankita, M.; Amrita, S.; Vethamony, P.

2013-12-01

As a consequence of change in global climate, an increased frequency of natural hazards such as storm surges, tsunamis and cyclones, is predicted to have dramatic affects on the coastal communities and ecosystems by virtue of the devastation they cause during and after their occurrence. The tsunami of December 2004 and the Thane cyclone of 2011 caused extensive human and economic losses along the coastline of Puducherry and Tamil Nadu. The devastation caused by these events highlighted the need for vulnerability assessment to ensure better understanding of the elements causing different hazards and to consequently minimize the after- effects of the future events. This paper demonstrates an analytical hierarchical process (AHP)-based approach to coastal vulnerability studies as an improvement to the existing methodologies for vulnerability assessment. The paper also encourages the inclusion of socio-economic parameters along with the physical parameters to calculate the coastal vulnerability index using AHP-derived weights. Seven physical-geological parameters (slope, geomorphology, elevation, shoreline change, sea level rise, significant wave height and tidal range) and four socio-economic factors (population, land use/land cover (LU/LC), roads and location of tourist areas) are considered to measure the physical vulnerability index (PVI) as well as the socio-economic vulnerability index (SVI) of the Puducherry coast. Based on the weights and scores derived using AHP, vulnerability maps are prepared to demarcate areas with very low, medium and high vulnerability. A combination of PVI and SVI values are further utilized to compute the coastal vulnerability index (CVI). Finally, the various coastal segments are grouped into the 3 vulnerability classes to obtain the coastal vulnerability map. The entire coastal extent between Muthiapet and Kirumampakkam as well as the northern part of Kalapet is designated as the high vulnerability zone, which constitutes 50% of the coastline. The region between the southern coastal extent of Kalapet and Lawspet is the medium vulnerability zone and the remaining 25% is the low vulnerability zone. The results obtained enable the identification and prioritization of the more vulnerable areas of the region in order to further assist the government and the residing coastal communities in better coastal management and conservation.

Modeling the risk of transmission of schistosomiasis in Akure North Local Government Area of Ondo State, Nigeria using satellite derived environmental data.

PubMed

Ajakaye, Oluwaremilekun G; Adedeji, Oluwatola I; Ajayi, Paul O

2017-07-01

Schistosomiasis is a parasitic disease and its distribution, in space and time, can be influenced by environmental factors such as rivers, elevation, slope, land surface temperature, land use/cover and rainfall. The aim of this study is to identify the areas with suitable conditions for schistosomiasis transmission on the basis of physical and environmental factors derived from satellite imagery and spatial analysis for Akure North Local Government Area (LGA) of Ondo State. Nigeria. This was done through methodology multicriteria evaluation (MCE) using Saaty's analytical hierarchy process (AHP). AHP is a multi-criteria decision method that uses hierarchical structures to represent a problem and makes decisions based on priority scales. In this research AHP was used to obtain the mapping weight or importance of each individual schistosomiasis risk factor. For the purpose of identifying areas of schistosomiasis risk, this study focused on temperature, drainage, elevation, rainfall, slope and land use/land cover as the factors controlling schistosomiasis incidence in the study area. It is by reclassifying and overlaying these factors that areas vulnerable to schistosomiasis were identified. The weighted overlay analysis was done after each factor was given the appropriate weight derived through the analytical hierarchical process. The prevalence of urinary schistosomiasis in the study area was also determined by parasitological analysis of urine samples collected through random sampling. The results showed varying risk of schistosomiasis with a larger portion of the area (82%) falling under the high and very high risk category. The study also showed that one community (Oba Ile) had the lowest risk of schistosomiasis while the risk increased in the four remaining communities (Iju, Igoba, Ita Ogbolu and Ogbese). The predictions made by the model correlated strongly with observations from field study. The high risk zones corresponded to known endemic communities. This study revealed that environmental factors can be used in identifying and predicting the transmission of schistosomiasis as well as effective monitoring of disease risk in newly established rural and agricultural communities.

A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks

PubMed Central

Krypotos, Angelos-Miltiadis; Beckers, Tom; Kindt, Merel; Wagenmakers, Eric-Jan

2015-01-01

Common methods for analysing response time (RT) tasks, frequently used across different disciplines of psychology, suffer from a number of limitations such as the failure to directly measure the underlying latent processes of interest and the inability to take into account the uncertainty associated with each individual's point estimate of performance. Here, we discuss a Bayesian hierarchical diffusion model and apply it to RT data. This model allows researchers to decompose performance into meaningful psychological processes and to account optimally for individual differences and commonalities, even with relatively sparse data. We highlight the advantages of the Bayesian hierarchical diffusion model decomposition by applying it to performance on Approach–Avoidance Tasks, widely used in the emotion and psychopathology literature. Model fits for two experimental data-sets demonstrate that the model performs well. The Bayesian hierarchical diffusion model overcomes important limitations of current analysis procedures and provides deeper insight in latent psychological processes of interest. PMID:25491372

Improving surface-enhanced Raman scattering effect using gold-coated hierarchical polystyrene bead substrates modified with postgrowth microwave treatment.

PubMed

Yuen, Clement; Zheng, Wei; Huang, Zhiwei

2008-01-01

We report a novel postgrowth microwave heating implementation by selectively modifying hierarchical polystyrene (PS) bead substrates coated with gold (Au) films to effectively improve the surface-enhanced Raman scattering (SERS) effect on the analytes. The SERS signal of probe molecule rhodamine 6G (Rh 6G) on the microwave-treated Au-PS substrates can be improved by 10-fold, while the detection limit of Rh 6G in concentration can be enhanced by two orders of magnitude compared to the as-growth substrates. The high-quality SERS spectrum of saliva can also be acquired using the modified substrates, demonstrating the potential for the realization of the high-performance SERS substrates for biomedical applications.

Formal Multilevel Hierarchical Verification of Synchronous MOS VLSI Circuits.

DTIC Science & Technology

1987-06-01

166 12.4 Capacitance Coupling............................. 166 12.5 Multiple Abstraction Fuctions ....................... 168...depend on whether it is performing flat verification or hierarchical verification. The primary operations of Silica Pithecus when performing flat...signals never arise. The primary operation of Silica Pithecus when performing hierarchical verification is processing constraints to show they hold

Syntactic Structure and Artificial Grammar Learning: The Learnability of Embedded Hierarchical Structures

ERIC Educational Resources Information Center

de Vries, Meinou H.; Monaghan, Padraic; Knecht, Stefan; Zwitserlood, Pienie

2008-01-01

Embedded hierarchical structures, such as "the rat the cat ate was brown", constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures.…

Hierarchical process memory: memory as an integral component of information processing

PubMed Central

Hasson, Uri; Chen, Janice; Honey, Christopher J.

2015-01-01

Models of working memory commonly focus on how information is encoded into and retrieved from storage at specific moments. However, in the majority of real-life processes, past information is used continuously to process incoming information across multiple timescales. Considering single unit, electrocorticography, and functional imaging data, we argue that (i) virtually all cortical circuits can accumulate information over time, and (ii) the timescales of accumulation vary hierarchically, from early sensory areas with short processing timescales (tens to hundreds of milliseconds) to higher-order areas with long processing timescales (many seconds to minutes). In this hierarchical systems perspective, memory is not restricted to a few localized stores, but is intrinsic to information processing that unfolds throughout the brain on multiple timescales. “The present contains nothing more than the past, and what is found in the effect was already in the cause.”Henri L Bergson PMID:25980649

Evaluation of generic types of drilling fluid using a risk-based analytic hierarchy process.

PubMed

Sadiq, Rehan; Husain, Tahir; Veitch, Brian; Bose, Neil

2003-12-01

The composition of drilling muds is based on a mixture of clays and additives in a base fluid. There are three generic categories of base fluid--water, oil, and synthetic. Water-based fluids (WBFs) are relatively environmentally benign, but drilling performance is better with oil-based fluids (OBFs). The oil and gas industry developed synthetic-based fluids (SBFs), such as vegetable esters, olefins, ethers, and others, which provide drilling performance comparable to OBFs, but with lower environmental and occupational health effects. The primary objective of this paper is to present a methodology to guide decision-making in the selection and evaluation of three generic types of drilling fluids using a risk-based analytic hierarchy process (AHP). In this paper a comparison of drilling fluids is made considering various activities involved in the life cycle of drilling fluids. This paper evaluates OBFs, WBFs, and SBFs based on four major impacts--operations, resources, economics, and liabilities. Four major activities--drilling, discharging offshore, loading and transporting, and disposing onshore--cause the operational impacts. Each activity involves risks related to occupational injuries (safety), general public health, environmental impact, and energy use. A multicriteria analysis strategy was used for the selection and evaluation of drilling fluids using a risk-based AHP. A four-level hierarchical structure is developed to determine the final relative scores, and the SBFs are found to be the best option.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks.

PubMed

Dixon, Matthew L; De La Vega, Alejandro; Mills, Caitlin; Andrews-Hanna, Jessica; Spreng, R Nathan; Cole, Michael W; Christoff, Kalina

2018-02-13

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN A exhibited stronger connectivity with the DN than the DAN, whereas FPCN B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN A may be preferentially involved in the regulation of introspective processes, whereas FPCN B may be preferentially involved in the regulation of visuospatial perceptual attention.

a New Model for Fuzzy Personalized Route Planning Using Fuzzy Linguistic Preference Relation

NASA Astrophysics Data System (ADS)

Nadi, S.; Houshyaripour, A. H.

2017-09-01

This paper proposes a new model for personalized route planning under uncertain condition. Personalized routing, involves different sources of uncertainty. These uncertainties can be raised from user's ambiguity about their preferences, imprecise criteria values and modelling process. The proposed model uses Fuzzy Linguistic Preference Relation Analytical Hierarchical Process (FLPRAHP) to analyse user's preferences under uncertainty. Routing is a multi-criteria task especially in transportation networks, where the users wish to optimize their routes based on different criteria. However, due to the lake of knowledge about the preferences of different users and uncertainties available in the criteria values, we propose a new personalized fuzzy routing method based on the fuzzy ranking using center of gravity. The model employed FLPRAHP method to aggregate uncertain criteria values regarding uncertain user's preferences while improve consistency with least possible comparisons. An illustrative example presents the effectiveness and capability of the proposed model to calculate best personalize route under fuzziness and uncertainty.

Social sustainability in healthcare facilities: a rating tool for analysing and improving social aspects in environments of care.

PubMed

Capolongo, Stefano; Gola, Marco; di Noia, Michela; Nickolova, Maria; Nachiero, Dario; Rebecchi, Andrea; Settimo, Gaetano; Vittori, Gail; Buffoli, Maddalena

2016-01-01

Nowadays several rating systems exist for the evaluation of the sustainability of buildings, but often their focus is limited to environmental and efficiency aspects. Hospitals are complex constructions in which many variables affect hospital processes. Therefore, a research group has developed a tool for the evaluation of sustainability in healthcare facilities. The paper analyses social sustainability issues through a tool which evaluates users' perception from a the quality and well-being perspective. It presents a hierarchical structure composed of a criteria and indicators system which is organised through a weighing system calculated by using the Analytic Network Process. The output is the definition of a tool which evaluates how Humanisation, Comfort and Distribution criteria can affect the social sustainability of a building. Starting from its application, it is evident that the instrument enables the improvement of healthcare facilities through several design and organisational suggestions for achieving healing and sustainable architectures.

Influence of personality on care quality of hospital nurses.

PubMed

Teng, Ching-I; Hsu, Kuang-Hung; Chien, Ruey-Cherng; Chang, Hao-Yuan

2007-01-01

This study investigates the relationship between hospital nurse personality and care quality in Taiwan. Hierarchical regression analysis was applied to data for 192 pairs of nurses and patients. Analytical results are as follows: (1) nurse openness was positively correlated with patient perceptions of responsiveness and (2) nurse neuroticism was negatively correlated with patient perceptions of responsiveness, assurance, and empathy.

Environmental Analytical Measurement Uncertainty Estimation: Nested Hierarchical Approach

DTIC Science & Technology

2001-01-01

recognized. The International Organization of Standardization ( ISO / IEC 17025 ) standard for the general requirements for competence of testing and...Uncertainty in Measurement” (GUM) was published by the International Organization of Standardization ( ISO ) in collaboration with the seven member...the American National Standards Institute (ANSI) adoption of the ISO GUM. The ANSI adoption of the ISO GUM provides the mathematical model and

The United States Army Functional Concept for Intelligence, 2016-2028

DTIC Science & Technology

2010-10-13

Intelligence improvement strategies historically addressed the changing operational environment by creating sensors and analytical systems designed to locate...hierarchical centrally- directed combat formations and predict their actions in high-intensity conflict. These strategies assumed that intelligence...4) U.S. operations can be derailed over time through a strategy of exhaustion. (5) U.S. forces distributed over wide areas can be

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)

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…

A convergent functional architecture of the insula emerges across imaging modalities.

PubMed

Kelly, Clare; Toro, Roberto; Di Martino, Adriana; Cox, Christine L; Bellec, Pierre; Castellanos, F Xavier; Milham, Michael P

2012-07-16

Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations. Copyright © 2012 Elsevier Inc. All rights reserved.

A visual analytics approach for pattern-recognition in patient-generated data.

PubMed

Feller, Daniel J; Burgermaster, Marissa; Levine, Matthew E; Smaldone, Arlene; Davidson, Patricia G; Albers, David J; Mamykina, Lena

2018-06-13

To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload. Participatory design was used to develop Glucolyzer, an interactive tool featuring hierarchical clustering and a heatmap visualization to help registered dietitians (RDs) identify associative patterns between blood glucose levels and per-meal macronutrient composition for individuals with type 2 diabetes (T2DM). Ten RDs participated in a within-subjects experiment to compare Glucolyzer to a static logbook format. For each representation, participants had 25 minutes to examine 1 month of diabetes self-monitoring data captured by an individual with T2DM and identify clinically meaningful patterns. We compared the quality and accuracy of the observations generated using each representation. Participants generated 50% more observations when using Glucolyzer (98) than when using the logbook format (64) without any loss in accuracy (69% accuracy vs 62%, respectively, p = .17). Participants identified more observations that included ingredients other than carbohydrates using Glucolyzer (36% vs 16%, p = .027). Fewer RDs reported feelings of information overload using Glucolyzer compared to the logbook format. Study participants displayed variable acceptance of hierarchical clustering. Visual analytics have the potential to mitigate provider concerns about the volume of self-monitoring data. Glucolyzer helped dietitians identify meaningful patterns in self-monitoring data without incurring perceived information overload. Future studies should assess whether similar tools can support clinicians in personalizing behavioral interventions that improve patient outcomes.

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.

Decision-making process of patients with gynecological cancer regarding their cancer treatment choices using the analytic hierarchy process.

PubMed

Kitamura, Yuko

2010-12-01

In order to support patients' decision-making regarding cancer treatments, it is important to clarify which criteria that cancer patients use to set priorities in their treatment choices. Using the analytic hierarchy process (AHP), a mathematical decision-making method, this article investigates the criteria and the priorities of patients with gynecological cancer. In the AHP, multiple and hierarchical criteria in the decision-making process were organized by a repeated pairwise judgment of the participants so as to serialize the alternatives along with the rational order of the priorities. For the alternatives "to receive treatment" and "to not receive treatment," the following five criteria were set: "anxiety about relapse and metastasis", "distress about side-effects", "advice of family", "advice of medical staff", and "economic burden". The participants determined a pairwise priority scale, as well as a priority scale between the alternatives for every criterion. The logical consistency of their answers was checked by a consistency index (CI). The participants were 31 patients with ovarian or endometrial cancer who were being followed up after undergoing surgery and adjuvant chemotherapy. Of the participants who answered the questionnaire, 17 satisfied the logical consistency. Of the five criteria for the treatment choices, "anxiety about relapse and metastasis" and "advice of medical staff" were found to be the important factors for treatment choice; however, the weight attached to the priority criteria differed much among the patients. The AHP made it possible to support patients' decision-making in order to clarify their priority criteria and to quantitatively present their decision-making process. © 2010 The Author. Journal compilation © 2010 Japan Academy of Nursing Science.

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.

Hierarchical Probabilistic Inference of the Color-Magnitude Diagram and Shrinkage of Stellar Distance Uncertainties

NASA Astrophysics Data System (ADS)

Leistedt, Boris; Hogg, David W.

2017-12-01

We present a hierarchical probabilistic model for improving geometric stellar distance estimates using color-magnitude information. This is achieved with a data-driven model of the color-magnitude diagram, not relying on stellar models but instead on the relative abundances of stars in color-magnitude cells, which are inferred from very noisy magnitudes and parallaxes. While the resulting noise-deconvolved color-magnitude diagram can be useful for a range of applications, we focus on deriving improved stellar distance estimates relying on both parallax and photometric information. We demonstrate the efficiency of this approach on the 1.4 million stars of the Gaia TGAS sample that also have AAVSO Photometric All Sky Survey magnitudes. Our hierarchical model has 4 million parameters in total, most of which are marginalized out numerically or analytically. We find that distance estimates are significantly improved for the noisiest parallaxes and densest regions of the color-magnitude diagram. In particular, the average distance signal-to-noise ratio (S/N) and uncertainty improve by 19% and 36%, respectively, with 8% of the objects improving in S/N by a factor greater than 2. This computationally efficient approach fully accounts for both parallax and photometric noise and is a first step toward a full hierarchical probabilistic model of the Gaia data.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Selecting appropriate wastewater treatment technologies using a choosing-by-advantages approach.

PubMed

Arroyo, Paz; Molinos-Senante, María

2018-06-01

Selecting the most sustainable wastewater treatment (WWT) technology among possible alternatives is a very complex task because the choice must integrate economic, environmental, and social criteria. Traditionally, several multi-criteria decision-making approaches have been applied, with the most often used being the analytical hierarchical process (AHP). However, AHP allows users to offset poor environmental and/or social performance with low cost. To overcome this limitation, our study examines a choosing-by-advantages (CBA) approach to rank seven WWT technologies for secondary WWT. CBA results were compared with results obtained by using the AHP approach. The rankings of WWT alternatives differed, depending on whether the CBA or AHP approach was used, which highlights the importance of the method used to support decision-making processes, particularly ones that rely on subjective interpretations by experts. This paper uses a holistic perspective to demonstrate the benefits of using the CBA approach to support a decision-making process when a group of experts must come to a consensus in selecting the most suitable WWT technology among several available. Copyright © 2017 Elsevier B.V. All rights reserved.

HierarchicalTopics: visually exploring large text collections using topic hierarchies.

PubMed

Dou, Wenwen; Yu, Li; Wang, Xiaoyu; Ma, Zhiqiang; Ribarsky, William

2013-12-01

Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be generated in order to capture the meaningful latent themes and nuances in the corpora. However, it is difficult for most of current topic-based visualizations to represent large number of topics without being cluttered or illegible. To facilitate the representation and navigation of a large number of topics, we propose a visual analytics system--HierarchicalTopic (HT). HT integrates a computational algorithm, Topic Rose Tree, with an interactive visual interface. The Topic Rose Tree constructs a topic hierarchy based on a list of topics. The interactive visual interface is designed to present the topic content as well as temporal evolution of topics in a hierarchical fashion. User interactions are provided for users to make changes to the topic hierarchy based on their mental model of the topic space. To qualitatively evaluate HT, we present a case study that showcases how HierarchicalTopics aid expert users in making sense of a large number of topics and discovering interesting patterns of topic groups. We have also conducted a user study to quantitatively evaluate the effect of hierarchical topic structure. The study results reveal that the HT leads to faster identification of large number of relevant topics. We have also solicited user feedback during the experiments and incorporated some suggestions into the current version of HierarchicalTopics.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

PubMed

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Why and when hierarchy impacts team effectiveness: A meta-analytic integration.

PubMed

Greer, Lindred L; de Jong, Bart A; Schouten, Maartje E; Dannals, Jennifer E

2018-06-01

Hierarchy has the potential to both benefit and harm team effectiveness. In this article, we meta-analytically investigate different explanations for why and when hierarchy helps or hurts team effectiveness, drawing on results from 54 prior studies (N = 13,914 teams). Our findings show that, on net, hierarchy negatively impacts team effectiveness (performance: ρ = -.08; viability: ρ = -.11), and that this effect is mediated by increased conflict-enabling states. Additionally, we show that the negative relationship between hierarchy and team performance is exacerbated by aspects of the team structure (i.e., membership instability, skill differentiation) and the hierarchy itself (i.e., mutability), which make hierarchical teams prone to conflict. The predictions regarding the positive effect of hierarchy on team performance as mediated by coordination-enabling processes, and the moderating roles of several aspects of team tasks (i.e., interdependence, complexity) and the hierarchy (i.e., form) were not supported, with the exception that task ambiguity enhanced the positive effects of hierarchy. Given that our findings largely support dysfunctional views on hierarchy, future research is needed to understand when and why hierarchy may be more likely to live up to its purported functional benefits. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease.

PubMed

Liem, David Alexandre; Murali, Sanjana; Sigdel, Dibakar; Shi, Yu; Wang, Xuan; Shen, Jiaming; Choi, Howard; Caufield, J Harry; Wang, Wei; Ping, Peipei; Han, Jiawei

2018-05-18

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the six groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-aware Semantic Online Analytical Processing (CaseOLAP) was applied to semantically rank the association of proteins to each and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein is visualized as a six dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all six CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters associated with a targeted CVD; analyses revealed unexpected insights underlying ECM-pathogenesis of CVDs.

Segregating the core computational faculty of human language from working memory.

PubMed

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

2009-05-19

In contrast to simple structures in animal vocal behavior, hierarchical structures such as center-embedded sentences manifest the core computational faculty of human language. Previous artificial grammar learning studies found that the left pars opercularis (LPO) subserves the processing of hierarchical structures. However, it is not clear whether this area is activated by the structural complexity per se or by the increased memory load entailed in processing hierarchical structures. To dissociate the effect of structural complexity from the effect of memory cost, we conducted a functional magnetic resonance imaging study of German sentence processing with a 2-way factorial design tapping structural complexity (with/without hierarchical structure, i.e., center-embedding of clauses) and working memory load (long/short distance between syntactically dependent elements; i.e., subject nouns and their respective verbs). Functional imaging data revealed that the processes for structure and memory operate separately but co-operatively in the left inferior frontal gyrus; activities in the LPO increased as a function of structural complexity, whereas activities in the left inferior frontal sulcus (LIFS) were modulated by the distance over which the syntactic information had to be transferred. Diffusion tensor imaging showed that these 2 regions were interconnected through white matter fibers. Moreover, functional coupling between the 2 regions was found to increase during the processing of complex, hierarchically structured sentences. These results suggest a neuroanatomical segregation of syntax-related aspects represented in the LPO from memory-related aspects reflected in the LIFS, which are, however, highly interconnected functionally and anatomically.

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.

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.

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

Peculiar velocity effect on galaxy correlation functions in nonlinear clustering regime

NASA Astrophysics Data System (ADS)

Matsubara, Takahiko

1994-03-01

We studied the distortion of the apparent distribution of galaxies in redshift space contaminated by the peculiar velocity effect. Specifically we obtained the expressions for N-point correlation functions in redshift space with given functional form for velocity distribution f(v) and evaluated two- and three-point correlation functions quantitatively. The effect of velocity correlations is also discussed. When the two-point correlation function in real space has a power-law form, Xir(r) is proportional to r(-gamma), the redshift-space counterpart on small scales also has a power-law form but with an increased power-law index: Xis(s) is proportional to s(1-gamma). When the three-point correlation function has the hierarchical form and the two-point correlation function has the power-law form in real space, the hierarchical form of the three-point correlation function is almost preserved in redshift space. The above analytic results are compared with the direct analysis based on N-body simulation data for cold dark matter models. Implications on the hierarchical clustering ansatz are discussed in detail.

Extreme close approaches in hierarchical triple systems with comparable masses

NASA Astrophysics Data System (ADS)

Haim, Niv; Katz, Boaz

2018-06-01

We study close approaches in hierarchical triple systems with comparable masses using full N-body simulations, motivated by a recent model for type Ia supernovae involving direct collisions of white dwarfs (WDs). For stable hierarchical systems where the inner binary components have equal masses, we show that the ability of the inner binary to achieve very close approaches, where the separation between the components of the inner binary reaches values which are orders of magnitude smaller than the semi-major axis, can be analytically predicted from initial conditions. The rate of close approaches is found to be roughly linear with the mass of the tertiary. The rate increases in systems with unequal inner binaries by a marginal factor of ≲ 2 for mass ratios 0.5 ≤ m1/m2 ≤ 1 relevant for the inner white-dwarf binaries. For an average tertiary mass of ˜0.3M⊙ which is representative of typical M-dwarfs, the chance for clean collisions is ˜1% setting challenging constraints on the collisional model for type Ia's.

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

PubMed

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

2016-01-14

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

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

Giunta, G.; Belouettar, S.

In this paper, the static response of three-dimensional beams made of functionally graded materials is investigated through a family of hierarchical one-dimensional finite elements. A wide variety of elements is proposed differing by the kinematic formulation and the number of nodes per elements along the beam axis. Elements’ stiffness matrix and load vector are derived in a unified nuclear form that does not depend upon the a priori expansion order over the cross-section nor the finite element approximation along the beam axis. Results are validated towards three-dimensional finite element models as well as equivalent Navier-type analytical solutions. The numerical investigationsmore » show that accurate and efficient solutions (when compared with full three-dimensional FEM solutions) can be obtained by the proposed family of hierarchical one-dimensional elements’ family.« less

Application of six sigma and AHP in analysis of variable lead time calibration process instrumentation

NASA Astrophysics Data System (ADS)

Rimantho, Dino; Rahman, Tomy Abdul; Cahyadi, Bambang; Tina Hernawati, S.

2017-02-01

Calibration of instrumentation equipment in the pharmaceutical industry is an important activity to determine the true value of a measurement. Preliminary studies indicated that occur lead-time calibration resulted in disruption of production and laboratory activities. This study aimed to analyze the causes of lead-time calibration. Several methods used in this study such as, Six Sigma in order to determine the capability process of the calibration instrumentation of equipment. Furthermore, the method of brainstorming, Pareto diagrams, and Fishbone diagrams were used to identify and analyze the problems. Then, the method of Hierarchy Analytical Process (AHP) was used to create a hierarchical structure and prioritize problems. The results showed that the value of DPMO around 40769.23 which was equivalent to the level of sigma in calibration equipment approximately 3,24σ. This indicated the need for improvements in the calibration process. Furthermore, the determination of problem-solving strategies Lead Time Calibration such as, shortens the schedule preventive maintenance, increase the number of instrument Calibrators, and train personnel. Test results on the consistency of the whole matrix of pairwise comparisons and consistency test showed the value of hierarchy the CR below 0.1.

Hierarchical Bi2Te3 Nanostrings: Green Synthesis and Their Thermoelectric Properties.

PubMed

Song, Shuyan; Liu, Yu; Wang, Qishun; Pan, Jing; Sun, Yabin; Zhang, Lingling

2018-05-20

Bi2Te3 hierarchical nanostrings have been synthesized through a solvothermal approach with the assistance of sucrose. The hierarchical Bi2Te3 was supposed to be fabricated through a self-assembly process. Te nanorods first emerge with the reduction of TeO32- followed by heterogeneous nucleation of Bi2Te3 nanoplates on the surface and tips of Te nanorods. Te nanorods further transform into Bi2Te3 nanorods simultaneously with the nanoplates' growth leading to a hierarchical structure. Through controlling the reaction kinetics by adding different amount of ethylene glycol, the length of nanorods and the number of nanoplates could be tailored. The use of sucrose is vital to the formation of hierarchical structure because it not only serves as a template for the well-defined growth of Te nanorods but also promotes the heterogeneous nucleation of Bi2Te3 in the self-assembly process. The Bi2Te3 nanomaterial shows a moderate thermoelectric performance because of its hierarchical structure. This study shows a promising way to synthesize Bi2Te3-based nanostructures through environmental friendly approach. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adsorption-Induced Deformation of Hierarchically Structured Mesoporous Silica—Effect of Pore-Level Anisotropy

PubMed Central

2017-01-01

The goal of this work is to understand adsorption-induced deformation of hierarchically structured porous silica exhibiting well-defined cylindrical mesopores. For this purpose, we performed an in situ dilatometry measurement on a calcined and sintered monolithic silica sample during the adsorption of N2 at 77 K. To analyze the experimental data, we extended the adsorption stress model to account for the anisotropy of cylindrical mesopores, i.e., we explicitly derived the adsorption stress tensor components in the axial and radial direction of the pore. For quantitative predictions of stresses and strains, we applied the theoretical framework of Derjaguin, Broekhoff, and de Boer for adsorption in mesopores and two mechanical models of silica rods with axially aligned pore channels: an idealized cylindrical tube model, which can be described analytically, and an ordered hexagonal array of cylindrical mesopores, whose mechanical response to adsorption stress was evaluated by 3D finite element calculations. The adsorption-induced strains predicted by both mechanical models are in good quantitative agreement making the cylindrical tube the preferable model for adsorption-induced strains due to its simple analytical nature. The theoretical results are compared with the in situ dilatometry data on a hierarchically structured silica monolith composed by a network of mesoporous struts of MCM-41 type morphology. Analyzing the experimental adsorption and strain data with the proposed theoretical framework, we find the adsorption-induced deformation of the monolithic sample being reasonably described by a superposition of axial and radial strains calculated on the mesopore level. The structural and mechanical parameters obtained from the model are in good agreement with expectations from independent measurements and literature, respectively. PMID:28547995

Adsorption-Induced Deformation of Hierarchically Structured Mesoporous Silica-Effect of Pore-Level Anisotropy.

PubMed

Balzer, Christian; Waag, Anna M; Gehret, Stefan; Reichenauer, Gudrun; Putz, Florian; Hüsing, Nicola; Paris, Oskar; Bernstein, Noam; Gor, Gennady Y; Neimark, Alexander V

2017-06-06

The goal of this work is to understand adsorption-induced deformation of hierarchically structured porous silica exhibiting well-defined cylindrical mesopores. For this purpose, we performed an in situ dilatometry measurement on a calcined and sintered monolithic silica sample during the adsorption of N 2 at 77 K. To analyze the experimental data, we extended the adsorption stress model to account for the anisotropy of cylindrical mesopores, i.e., we explicitly derived the adsorption stress tensor components in the axial and radial direction of the pore. For quantitative predictions of stresses and strains, we applied the theoretical framework of Derjaguin, Broekhoff, and de Boer for adsorption in mesopores and two mechanical models of silica rods with axially aligned pore channels: an idealized cylindrical tube model, which can be described analytically, and an ordered hexagonal array of cylindrical mesopores, whose mechanical response to adsorption stress was evaluated by 3D finite element calculations. The adsorption-induced strains predicted by both mechanical models are in good quantitative agreement making the cylindrical tube the preferable model for adsorption-induced strains due to its simple analytical nature. The theoretical results are compared with the in situ dilatometry data on a hierarchically structured silica monolith composed by a network of mesoporous struts of MCM-41 type morphology. Analyzing the experimental adsorption and strain data with the proposed theoretical framework, we find the adsorption-induced deformation of the monolithic sample being reasonably described by a superposition of axial and radial strains calculated on the mesopore level. The structural and mechanical parameters obtained from the model are in good agreement with expectations from independent measurements and literature, respectively.

Bioinspired Methodology for Artificial Olfaction

PubMed Central

Raman, Baranidharan; Hertz, Joshua L.; Benkstein, Kurt D.; Semancik, Steve

2008-01-01

Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of “electronic noses” typically involves recognition of “pretrained” chemicals, while long-term operation and generalization of training to allow chemical classification of “unknown” analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications. PMID:18855409

Developmental Changes in the Processing of Hierarchical Shapes Continue into Adolescence.

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Geldart, Sybil; Maurer, Daphne; de Schonen, Scania

2003-01-01

Three experiments obtained same-different judgments from children and adults to trace normal development of local and global processing of hierarchical visual forms. Findings indicated that reaction time was faster on global trials than local trials; bias was stronger in children and diminished to adult levels between ages 10 and 14. Reaction time…

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…

Silk-regulated hierarchical hollow magnetite/carbon nanocomposite spheroids for lithium-ion battery anodes.

PubMed

Sheng, Weiqin; Zhu, Guobin; Kaplan, David L; Cao, Chuanbao; Zhu, Hesun; Lu, Qiang

2015-03-20

Hierarchical olive-like structured carbon-Fe3O4 nanocomposite particles composed of a hollow interior and a carbon coated surface are prepared by a facile, silk protein-assisted hydrothermal method. Silk nanofibers as templates and carbon precursors first regulate the formation of hollow Fe2O3 microspheres and then they are converted into carbon by a reduction process into Fe3O4. This process significantly simplifies the fabrication and carbon coating processes to form complex hollow structures. When tested as anode materials for lithium-ion batteries, these hollow carbon-coated particles exhibit high capacity (900 mAh g(-1)), excellent cycle stability (180 cycles) and rate performance due to their unique hierarchical hollow structure and carbon coating.

Interplay between spatially explicit sediment sourcing, hierarchical river-network structure, and in-channel bed material sediment transport and storage dynamics

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Foufoula-Georgiou, Efi; Gran, Karen B.; Belmont, Patrick; Wilcock, Peter R.

2017-05-01

Understanding how sediment moves along source to sink pathways through watersheds—from hillslopes to channels and in and out of floodplains—is a fundamental problem in geomorphology. We contribute to advancing this understanding by modeling the transport and in-channel storage dynamics of bed material sediment on a river network over a 600 year time period. Specifically, we present spatiotemporal changes in bed sediment thickness along an entire river network to elucidate how river networks organize and process sediment supply. We apply our model to sand transport in the agricultural Greater Blue Earth River Basin in Minnesota. By casting the arrival of sediment to links of the network as a Poisson process, we derive analytically (under supply-limited conditions) the time-averaged probability distribution function of bed sediment thickness for each link of the river network for any spatial distribution of inputs. Under transport-limited conditions, the analytical assumptions of the Poisson arrival process are violated (due to in-channel storage dynamics) where we find large fluctuations and periodicity in the time series of bed sediment thickness. The time series of bed sediment thickness is the result of dynamics on a network in propagating, altering, and amalgamating sediment inputs in sometimes unexpected ways. One key insight gleaned from the model is that there can be a small fraction of reaches with relatively low-transport capacity within a nonequilibrium river network acting as "bottlenecks" that control sediment to downstream reaches, whereby fluctuations in bed elevation can dissociate from signals in sediment supply.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

PubMed Central

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

Hydrothermal Fabrication of WO3 Hierarchical Architectures: Structure, Growth and Response

PubMed Central

Wu, Chuan-Sheng

2015-01-01

Recently hierarchical architectures, consisting of two-dimensional (2D) nanostructures, are of great interest for potential applications in energy and environmental. Here, novel rose-like WO3 hierarchical architectures were successfully synthesized via a facile hydrothermal method. The as-prepared WO3 hierarchical architectures were in fact assembled by numerous nanosheets with an average thickness of ~30 nm. We found that the oxalic acid played a significant role in governing morphologies of WO3 during hydrothermal process. Based on comparative studies, a possible formation mechanism was also proposed in detail. Furthermore, gas-sensing measurement showed that the well-defined 3D WO3 hierarchical architectures exhibited the excellent gas sensing properties towards CO. PMID:28347062

Dynamic anticipatory processing of hierarchical sequential events: a common role for Broca's area and ventral premotor cortex across domains?

PubMed

Fiebach, Christian J; Schubotz, Ricarda I

2006-05-01

This paper proposes a domain-general model for the functional contribution of ventral premotor cortex (PMv) and adjacent Broca's area to perceptual, cognitive, and motor processing. We propose to understand this frontal region as a highly flexible sequence processor, with the PMv mapping sequential events onto stored structural templates and Broca's Area involved in more complex, hierarchical or hypersequential processing. This proposal is supported by reference to previous functional neuroimaging studies investigating abstract sequence processing and syntactic processing.

Heterogeneous fractionation profiles of meta-analytic coactivation networks.

PubMed

Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T

2017-04-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Heterogeneous fractionation profiles of meta-analytic coactivation networks

PubMed Central

Laird, Angela R.; Riedel, Michael C.; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L.; Eickhoff, Simon B.; Smith, Stephen M.; Fox, Peter T.; Sutherland, Matthew T.

2017-01-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. PMID:28222386

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

PubMed

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

2016-11-01

Graphene, a novel class of carbon nanostructures, has received great attention as sorbents due to its fascinating structures, ultrahigh specific surface area, and good extraction ability. In this paper, a new type of hierarchical graphene was synthesized through employing a mild and environment-friendly method. Such 3D interconnected graphene own a high specific surface area up to 524m(2)g(-1), which is about 2.5 fold larger than the graphene, since the synthetic material has interlayer pores between nanosheets and in-plane pores. Then a superior solid-phase microextraction fiber was fabricated by sequentially coating the stainless steel fiber with silicone sealant film and hierarchical graphene powder. Since the novel hierarchical graphene possessed large surface area and good adsorption property, the as-prepared fiber exhibited good extraction properties of the organochlorine pesticides (OCPs). As for the analytical performance, the as-prepared fiber achieved low detection limits (0.08-0.80ngL(-1)) and wide linearity (10-30,000ngL(-1)) under the optimal conditions. The repeatability (n=5) for single fiber were between 5.1% and 11%, while the reproducibility (n=3) of fiber-to-fiber were range from 6.2% to14%. Moreover, the fiber was successfully applied to the analysis of OCPs in the Pearl River water. Copyright © 2016 Elsevier B.V. All rights reserved.

Study on Desorption Process of n-Heptane and Methyl Cyclohexane Using UiO-66 with Hierarchical Pores.

PubMed

Chen, Sijia; Zhang, Lin; Zhang, Zhao; Qian, Gang; Liu, Zongjian; Cui, Qun; Wang, Haiyan

2018-06-06

UiO-66 (UiO for University of Oslo), is a zirconium-based MOF with reverse shape selectivity, gives an alternative way to produce high purity n-heptane used for the manufacture of high-purity pharmaceuticals. Couple of studies have shown that UiO-66 gives a high selectivity on the separation of n-/iso-alkanes. However, the microporous structure of UiO-66 causes poor mass transport during the desorption process. In this work, hierarchical-pore UiO-66 (H-UiO-66) was synthesized and utilized as an adsorbent of n-heptane (nHEP) and methyl cyclohexane (MCH) for systematically studying the desorption process of n/iso-alkanes. A suite of physical methods, including XRD patterns verified the UiO-66 structures and HRTEM showed the existence of hierarchical pores. N2 adsorption-desorption isotherms further confirmed the size distribution of hierarchical pores in H-UiO-66. Of particular note, the MCH/nHEP selectivity of H-UiO-66 is similar with UiO-66 in the same adsorption conditions, the desorption process of nHEP/MCH from H-UiO-66 is dramatically enhanced, viz, the desorption rates for nHEP/MCH from H-UiO-66 is enhanced by 30%/23% as comparing to UiO-66 at most. Moreover, desorption activation energy (Ed) derived from temperature-programmed desorption (TPD) experiments indicate that the Ed for nHEP/MCH is lower on H-UiO-66, i.e., the Ed of MCH on H-UiO-66 is ~37% lower than that on UiO-66 at most, leading to a milder condition for the desorption process. The introduction of hierarchical structures will be applicable for the optimization of desorption process during separation on porous materials.

Segregating the core computational faculty of human language from working memory

PubMed Central

Makuuchi, Michiru; Bahlmann, Jörg; Anwander, Alfred; Friederici, Angela D.

2009-01-01

In contrast to simple structures in animal vocal behavior, hierarchical structures such as center-embedded sentences manifest the core computational faculty of human language. Previous artificial grammar learning studies found that the left pars opercularis (LPO) subserves the processing of hierarchical structures. However, it is not clear whether this area is activated by the structural complexity per se or by the increased memory load entailed in processing hierarchical structures. To dissociate the effect of structural complexity from the effect of memory cost, we conducted a functional magnetic resonance imaging study of German sentence processing with a 2-way factorial design tapping structural complexity (with/without hierarchical structure, i.e., center-embedding of clauses) and working memory load (long/short distance between syntactically dependent elements; i.e., subject nouns and their respective verbs). Functional imaging data revealed that the processes for structure and memory operate separately but co-operatively in the left inferior frontal gyrus; activities in the LPO increased as a function of structural complexity, whereas activities in the left inferior frontal sulcus (LIFS) were modulated by the distance over which the syntactic information had to be transferred. Diffusion tensor imaging showed that these 2 regions were interconnected through white matter fibers. Moreover, functional coupling between the 2 regions was found to increase during the processing of complex, hierarchically structured sentences. These results suggest a neuroanatomical segregation of syntax-related aspects represented in the LPO from memory-related aspects reflected in the LIFS, which are, however, highly interconnected functionally and anatomically. PMID:19416819

How hierarchical is language use?

PubMed Central

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

2012-01-01

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

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.

Visual Attention to Global and Local Stimulus Properties in 6-Month-Old Infants: Individual Differences and Event-Related Potentials

ERIC Educational Resources Information Center

Guy, Maggie W.; Reynolds, Greg D.; Zhang, Dantong

2013-01-01

Event-related potentials (ERPs) were utilized in an investigation of 21 six-month-olds' attention to and processing of global and local properties of hierarchical patterns. Overall, infants demonstrated an advantage for processing the overall configuration (i.e., global properties) of local features of hierarchical patterns; however,…

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.

Scholarly Research Program in Fuel Analysis and Combustion Research

DTIC Science & Technology

1993-02-01

Public reporting burden for this collection of information is es•tmated to average I hour per response, ilnduding the time fo," reviwing ...Thermal Oxidative Flask Test 45 9. Advanced Fuel System Configuration Descent Condition 57 10. TGPGC for n-Alkane Mixture 63 11. Hierarchical Cluster ...will include all analytical data, data analysis conclusions, recommendations and rationale. 16 a& k : 05 Titl: Development of Test Cell Assemblies for

Data flow modeling techniques

NASA Technical Reports Server (NTRS)

Kavi, K. M.

1984-01-01

There have been a number of simulation packages developed for the purpose of designing, testing and validating computer systems, digital systems and software systems. Complex analytical tools based on Markov and semi-Markov processes have been designed to estimate the reliability and performance of simulated systems. Petri nets have received wide acceptance for modeling complex and highly parallel computers. In this research data flow models for computer systems are investigated. Data flow models can be used to simulate both software and hardware in a uniform manner. Data flow simulation techniques provide the computer systems designer with a CAD environment which enables highly parallel complex systems to be defined, evaluated at all levels and finally implemented in either hardware or software. Inherent in data flow concept is the hierarchical handling of complex systems. In this paper we will describe how data flow can be used to model computer system.

Cosmic Rays and Gamma-Rays in Large-Scale Structure

NASA Astrophysics Data System (ADS)

Inoue, Susumu; Nagashima, Masahiro; Suzuki, Takeru K.; Aoki, Wako

2004-12-01

During the hierarchical formation of large scale structure in the universe, the progressive collapse and merging of dark matter should inevitably drive shocks into the gas, with nonthermal particle acceleration as a natural consequence. Two topics in this regard are discussed, emphasizing what important things nonthermal phenomena may tell us about the structure formation (SF) process itself. 1. Inverse Compton gamma-rays from large scale SF shocks and non-gravitational effects, and the implications for probing the warm-hot intergalactic medium. We utilize a semi-analytic approach based on Monte Carlo merger trees that treats both merger and accretion shocks self-consistently. 2. Production of 6Li by cosmic rays from SF shocks in the early Galaxy, and the implications for probing Galaxy formation and uncertain physics on sub-Galactic scales. Our new observations of metal-poor halo stars with the Subaru High Dispersion Spectrograph are highlighted.

Hierarchical automated clustering of cloud point set by ellipsoidal skeleton: application to organ geometric modeling from CT-scan images

NASA Astrophysics Data System (ADS)

Banegas, Frederic; Michelucci, Dominique; Roelens, Marc; Jaeger, Marc

1999-05-01

We present a robust method for automatically constructing an ellipsoidal skeleton (e-skeleton) from a set of 3D points taken from NMR or TDM images. To ensure steadiness and accuracy, all points of the objects are taken into account, including the inner ones, which is different from the existing techniques. This skeleton will be essentially useful for object characterization, for comparisons between various measurements and as a basis for deformable models. It also provides good initial guess for surface reconstruction algorithms. On output of the entire process, we obtain an analytical description of the chosen entity, semantically zoomable (local features only or reconstructed surfaces), with any level of detail (LOD) by discretization step control in voxel or polygon format. This capability allows us to handle objects at interactive frame rates once the e-skeleton is computed. Each e-skeleton is stored as a multiscale CSG implicit tree.

[Lab-on-a-chip systems in the point-of-care diagnostics].

PubMed

Szabó, Barnabás; Borbíró, András; Fürjes, Péter

2015-12-27

The need in modern medicine for near-patient diagnostics being able to accelerate therapeutic decisions and possibly replacing laboratory measurements is significantly growing. Reliable and cost-effective bioanalytical measurement systems are required which - acting as a micro-laboratory - contain integrated biomolecular recognition, sensing, signal processing and complex microfluidic sample preparation modules. These micro- and nanofabricated Lab-on-a-chip systems open new perspectives in the diagnostic supply chain, since they are able even for quantitative, high-precision and immediate analysis of special disease specific molecular markers or their combinations from a single drop of sample. Accordingly, crucial requirements regarding the instruments and the analytical methods are the high selectivity, extremely low detection limit, short response time and integrability into the healthcare information networks. All these features can make the hierarchical examination chain shorten, and revolutionize laboratory diagnostics, evolving a brand new situation in therapeutic intervention.

Comparison between cachaça and rum using pattern recognition methods.

PubMed

Cardoso, Daniel R; Andrade-Sobrinho, Luiz G; Leite-Neto, Alexandre F; Reche, Roni V; Isique, William D; Ferreira, Marcia M C; Lima-Neto, Benedito S; Franco, Douglas W

2004-06-02

The differentiation between cachaça and rum using analytical data referred to alcohols (methanol, propanol, isobutanol, and isopentanol), acetaldehyde, ethyl acetate, organic acids (octanoic acid, decanoic acid, and dodecanoic acid), metals (Al, Ca, Co, Cu, Cr, Fe, Mg, Mn, Ni, Na, and Zn), and polyphenols (protocatechuic acid, sinapaldehyde, syringaldehyde, ellagic acid, syringic acid, gallic acid, (-)-epicatechin, vanillic acid, vanillin, p-coumaric acid, coniferaldehyde, coniferyl alcohol, kaempferol, and quercetin) is described. The organic and metal analyte contents were determined in 18 cachaça and 21 rum samples using chromatographic methods (GC-MS, GC-FID, and HPLC-UV-vis) and inductively coupled plasma atomic emission spectrometry, respectively. The analytical data of the above compounds, when treated by principal component analysis, hierarchical cluster analysis, discriminant analysis, and K-nearest neighbor analysis, provide a very good discrimination between the two classes of beverages.

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.

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.

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.

Shared neural coding for social hierarchy and reward value in primate amygdala.

PubMed

Munuera, Jérôme; Rigotti, Mattia; Salzman, C Daniel

2018-03-01

The social brain hypothesis posits that dedicated neural systems process social information. In support of this, neurophysiological data have shown that some brain regions are specialized for representing faces. It remains unknown, however, whether distinct anatomical substrates also represent more complex social variables, such as the hierarchical rank of individuals within a social group. Here we show that the primate amygdala encodes the hierarchical rank of individuals in the same neuronal ensembles that encode the rewards associated with nonsocial stimuli. By contrast, orbitofrontal and anterior cingulate cortices lack strong representations of hierarchical rank while still representing reward values. These results challenge the conventional view that dedicated neural systems process social information. Instead, information about hierarchical rank-which contributes to the assessment of the social value of individuals within a group-is linked in the amygdala to representations of rewards associated with nonsocial stimuli.

Hierarchical species distribution models

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

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

Hydrothermal preparation of hierarchical ZIF-L nanostructures for enhanced CO2 capture.

PubMed

Ding, Bing; Wang, Xianbiao; Xu, Yongfei; Feng, Shaojie; Ding, Yi; Pan, Yang; Xu, Weifan; Wang, Huanting

2018-06-01

A zeolitic imidazolate framework (ZIF-L) with hierarchical morphology was synthesized through hydrothermal method. The hierarchical product consists of ZIF-L leaves with length of several micrometers, width of 1 ∼ 2 μm and thickness of ∼300 nm cross connected symmetrically. It was found that the hydrothermal temperature is crucial for the formation of such hierarchical nanostructure. The formation mechanism was investigated to be a secondary crystal growth process. The hierarchical ZIF-L has larger surface area compared with the two-dimensional (2D) ZIF-L leaves. Subsequently, the hierarchical ZIF-L exhibited enhanced CO 2 adsorption capacity (1.56 mmol·g -1 ) as compared with that of the reported two-dimensional ZIF-L leaves (0.94 mmol·g -1 ). This work not only reveals a new strategy for the formation of hierarchical ZIF-L nanostructures, but also supplies a potential material for CO 2 capture. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of a species distribution model and a process model from a hierarchical perspective to quantify effects of projected climate change on tree species

Treesearch

Jeffrey E. Schneiderman; Hong S. He; Frank R. Thompson; William D. Dijak; Jacob S. Fraser

2015-01-01

Tree species distribution and abundance are affected by forces operating across a hierarchy of ecological scales. Process and species distribution models have been developed emphasizing forces at different scales. Understanding model agreement across hierarchical scales provides perspective on prediction uncertainty and ultimately enables policy makers and managers to...

Synthesis of hollow silica spheres with hierarchical shell structure by the dual action of liquid indium microbeads in vapor-liquid-solid growth.

PubMed

Wang, Jian-Tao; Wang, Hui; Ou, Xue-Mei; Lee, Chun-Sing; Zhang, Xiao-Hong

2011-07-05

Geometry-based adhesion arising from hierarchical surface structure enables microspheres to adhere to cells strongly, which is essential for inorganic microcapsules that function as drug delivery or diagnostic imaging agents. However, constructing a hierarchical structure on the outer shell of the products via the current microcapsule synthesis method is difficult. This work presents a novel approach to fabricating hollow microspheres with a hierarchical shell structure through the vapor-liquid-solid (VLS) process in which liquid indium droplets act as both templates for the formation of silica capsules and catalysts for the growth of hierarchical shell structure. This hierarchical shell structure offers the hollow microsphere an enhanced geometry-based adhesion. The results provide a facile method for fabricating hollow spheres and enriching their function through tailoring the geometry of their outer shells. © 2011 American Chemical Society

CryoTEM as an Advanced Analytical Tool for Materials Chemists.

PubMed

Patterson, Joseph P; Xu, Yifei; Moradi, Mohammad-Amin; Sommerdijk, Nico A J M; Friedrich, Heiner

2017-07-18

Morphology plays an essential role in chemistry through the segregation of atoms and/or molecules into different phases, delineated by interfaces. This is a general process in materials synthesis and exploited in many fields including colloid chemistry, heterogeneous catalysis, and functional molecular systems. To rationally design complex materials, we must understand and control morphology evolution. Toward this goal, we utilize cryogenic transmission electron microscopy (cryoTEM), which can track the structural evolution of materials in solution with nanometer spatial resolution and a temporal resolution of <1 s. In this Account, we review examples of our own research where direct observations by cryoTEM have been essential to understanding morphology evolution in macromolecular self-assembly, inorganic nucleation and growth, and the cooperative evolution of hybrid materials. These three different research areas are at the heart of our approach to materials chemistry where we take inspiration from the myriad examples of complex materials in Nature. Biological materials are formed using a limited number of chemical components and under ambient conditions, and their formation pathways were refined during biological evolution by enormous trial and error approaches to self-organization and biomineralization. By combining the information on what is possible in nature and by focusing on a limited number of chemical components, we aim to provide an essential insight into the role of structure evolution in materials synthesis. Bone, for example, is a hierarchical and hybrid material which is lightweight, yet strong and hard. It is formed by the hierarchical self-assembly of collagen into a macromolecular template with nano- and microscale structure. This template then directs the nucleation and growth of oriented, nanoscale calcium phosphate crystals to form the composite material. Fundamental insight into controlling these structuring processes will eventually allow us to design such complex materials with predetermined and potentially unique properties.

Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor.

PubMed

Hilgetag, C C; O'Neill, M A; Young, M P

2000-01-29

Neuroanatomists have described a large number of connections between the various structures of monkey and cat cortical sensory systems. Because of the complexity of the connection data, analysis is required to unravel what principles of organization they imply. To date, analysis of laminar origin and termination connection data to reveal hierarchical relationships between the cortical areas has been the most widely acknowledged approach. We programmed a network processor that searches for optimal hierarchical orderings of cortical areas given known hierarchical constraints and rules for their interpretation. For all cortical systems and all cost functions, the processor found a multitude of equally low-cost hierarchies. Laminar hierarchical constraints that are presently available in the anatomical literature were therefore insufficient to constrain a unique ordering for any of the sensory systems we analysed. Hierarchical orderings of the monkey visual system that have been widely reported, but which were derived by hand, were not among the optimal orderings. All the cortical systems we studied displayed a significant degree of hierarchical organization, and the anatomical constraints from the monkey visual and somato-motor systems were satisfied with very few constraint violations in the optimal hierarchies. The visual and somato-motor systems in that animal were therefore surprisingly strictly hierarchical. Most inconsistencies between the constraints and the hierarchical relationships in the optimal structures for the visual system were related to connections of area FST (fundus of superior temporal sulcus). We found that the hierarchical solutions could be further improved by assuming that FST consists of two areas, which differ in the nature of their projections. Indeed, we found that perfect hierarchical arrangements of the primate visual system, without any violation of anatomical constraints, could be obtained under two reasonable conditions, namely the subdivision of FST into two distinct areas, whose connectivity we predict, and the abolition of at least one of the less reliable rule constraints. Our analyses showed that the future collection of the same type of laminar constraints, or the inclusion of new hierarchical constraints from thalamocortical connections, will not resolve the problem of multiple optimal hierarchical representations for the primate visual system. Further data, however, may help to specify the relative ordering of some more areas. This indeterminacy of the visual hierarchy is in part due to the reported absence of some connections between cortical areas. These absences are consistent with limited cross-talk between differentiated processing streams in the system. Hence, hierarchical representation of the visual system is affected by, and must take into account, other organizational features, such as processing streams.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

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.

An application of the AHP in water resources management: a case study on urban drainage rehabilitation in Medan City

NASA Astrophysics Data System (ADS)

Tarigan, A. P. M.; Rahmad, D.; Sembiring, R. A.; Iskandar, R.

2018-02-01

This paper illustrates an application of Analytical Hierarchy Process (AHP) as a potential decision-making method in water resource management related to drainage rehabilitation. The prioritization problem of urban drainage rehabilitation in Medan City due to limited budget is used as a study case. A hierarchical structure is formed for the prioritization criteria and the alternative drainages to be rehabilitated. Based on the AHP, the prioritization criteria are ranked and a descending-order list of drainage is made in order to select the most favorable drainages to have rehabilitation. A sensitivity analysis is then conducted to check the consistency of the final decisions in case of minor changes in judgements. The results of AHP computed manually are compared with that using the software Expert Choice. It is observed that the top three ranked drainages are consistent, and both results of the AHP methods, calculated manually and performed using Expert Choice, are in agreement. It is hoped that the application of the AHP will help the decision-making process by the city government in the problem of urban drainage rehabilitation.

Neural architecture underlying classification of face perception paradigms.

PubMed

Laird, Angela R; Riedel, Michael C; Sutherland, Matthew T; Eickhoff, Simon B; Ray, Kimberly L; Uecker, Angela M; Fox, P Mickle; Turner, Jessica A; Fox, Peter T

2015-10-01

We present a novel strategy for deriving a classification system of functional neuroimaging paradigms that relies on hierarchical clustering of experiments archived in the BrainMap database. The goal of our proof-of-concept application was to examine the underlying neural architecture of the face perception literature from a meta-analytic perspective, as these studies include a wide range of tasks. Task-based results exhibiting similar activation patterns were grouped as similar, while tasks activating different brain networks were classified as functionally distinct. We identified four sub-classes of face tasks: (1) Visuospatial Attention and Visuomotor Coordination to Faces, (2) Perception and Recognition of Faces, (3) Social Processing and Episodic Recall of Faces, and (4) Face Naming and Lexical Retrieval. Interpretation of these sub-classes supports an extension of a well-known model of face perception to include a core system for visual analysis and extended systems for personal information, emotion, and salience processing. Overall, these results demonstrate that a large-scale data mining approach can inform the evolution of theoretical cognitive models by probing the range of behavioral manipulations across experimental tasks. Copyright © 2015 Elsevier Inc. All rights reserved.

Selection of remedial alternatives for mine sites: a multicriteria decision analysis approach.

PubMed

Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

2013-04-15

The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

Unveiling the mechanisms of dressed-photon-phonon etching based on hierarchical surface roughness measure

NASA Astrophysics Data System (ADS)

Naruse, Makoto; Yatsui, Takashi; Nomura, Wataru; Kawazoe, Tadashi; Aida, Masaki; Ohtsu, Motoichi

2013-02-01

Dressed-photon-phonon (DPP) etching is a disruptive technology in planarizing material surfaces because it completely eliminates mechanical contact processes. However, adequate metrics for evaluating the surface roughness and the underlying physical mechanisms are still not well understood. Here, we propose a two-dimensional hierarchical surface roughness measure, inspired by the Allan variance, that represents the effectiveness of DPP etching while conserving the original two-dimensional surface topology. Also, we build a simple physical model of DPP etching that agrees well with the experimental observations, which clearly shows the involvement of the intrinsic hierarchical properties of dressed photons, or optical near-fields, in the surface processing.

Cumulative biological impacts framework for solar energy projects in the California Desert

USGS Publications Warehouse

Davis, Frank W.; Kreitler, Jason R.; Soong, Oliver; Stoms, David M.; Dashiell, Stephanie; Hannah, Lee; Wilkinson, Whitney; Dingman, John

2013-01-01

This project developed analytical approaches, tools and geospatial data to support conservation planning for renewable energy development in the California deserts. Research focused on geographical analysis to avoid, minimize and mitigate the cumulative biological effects of utility-scale solar energy development. A hierarchical logic model was created to map the compatibility of new solar energy projects with current biological conservation values. The research indicated that the extent of compatible areas is much greater than the estimated land area required to achieve 2040 greenhouse gas reduction goals. Species distribution models were produced for 65 animal and plant species that were of potential conservation significance to the Desert Renewable Energy Conservation Plan process. These models mapped historical and projected future habitat suitability using 270 meter resolution climate grids. The results were integrated into analytical frameworks to locate potential sites for offsetting project impacts and evaluating the cumulative effects of multiple solar energy projects. Examples applying these frameworks in the Western Mojave Desert ecoregion show the potential of these publicly-available tools to assist regional planning efforts. Results also highlight the necessity to explicitly consider projected land use change and climate change when prioritizing areas for conservation and mitigation offsets. Project data, software and model results are all available online.

Viscoelastic shear lag model to predict the micromechanical behavior of tendon under dynamic tensile loading.

PubMed

Wu, Jiayu; Yuan, Hong; Li, Longyuan; Fan, Kunjie; Qian, Shanguang; Li, Bing

2018-01-21

Owing to its viscoelastic nature, tendon exhibits stress rate-dependent breaking and stiffness function. A Kelvin-Voigt viscoelastic shear lag model is proposed to illustrate the micromechanical behavior of the tendon under dynamic tensile conditions. Theoretical closed-form expressions are derived to predict the deformation and stress transfer between fibrils and interfibrillar matrix while tendon is dynamically stretched. The results from the analytical solutions demonstrate that how the fibril overlap length and fibril volume fraction affect the stress transfer and mechanical properties of tendon. We find that the viscoelastic property of interfibrillar matrix mainly results in collagen fibril failure under fast loading rate or creep rupture of tendon. However, discontinuous fibril model and hierarchical structure of tendon ensure relative sliding under slow loading rate, helping dissipate energy and protecting fibril from damage, which may be a key reason why regularly staggering alignment microstructure is widely selected in nature. According to the growth, injury, healing and healed process of tendon observed by many researchers, the conclusions presented in this paper agrees well with the experimental findings. Additionally, the emphasis of this paper is on micromechanical behavior of tendon, whereas this analytical viscoelastic shear lag model can be equally applicable to other soft or hard tissues, owning the similar microstructure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hierarchically mesostructured porous TiO2 hollow nanofibers for high performance glucose biosensing.

PubMed

Guo, Qiaohui; Liu, Lijuan; Zhang, Man; Hou, Haoqing; Song, Yonghai; Wang, Huadong; Zhong, Baoying; Wang, Li

2017-06-15

Effective immobilization of enzymes on an electrode surface is of great importance for biosensor development, but it still remains challenging because enzymes tend to denaturation and/or form close-packed structures. In this work, a free-standing TiO 2 hollow nanofibers (HNF-TiO 2 ) was successfully prepared by a simple and scalable electrospun nanofiber film template-assisted sol-gel method, and was further explored for glucose oxidase (GOD) immobilization and biosensing. This porous and nanotubular HNF-TiO 2 provides a well-defined hierarchical nanostructure for GOD loading, and the fine TiO 2 nanocrystals facilitate direct electron transfer from GOD to the electrode, also the strong interaction between GOD and HNF-TiO 2 greatly enhances the stability of the biosensor. The as-prepared glucose biosensors show good sensing performances both in O 2 -free and O 2 -containing conditions with good sensitivity, satisfactory selectivity, long-term stability and sound reliability. The novel textile formation, porous and hierarchically mesostructured nature of HNF-TiO 2 with excellent analytical performances make it a superior platform for the construction of high-performance glucose biosensors. Copyright © 2016 Elsevier B.V. All rights reserved.

Breaking through the Glass Ceiling: Consumers in Mental Health Organisations' Hierarchies.

PubMed

Scholz, Brett; Bocking, Julia; Happell, Brenda

2017-05-01

Contemporary mental health policies call for consumers to be engaged in all levels of mental health service planning, implementation, and delivery. Critical approaches to traditional healthcare hierarchies can effectively challenge barriers to better engagement with consumers in mental health organisations. This qualitative exploratory study analyses how particular strategies for consumer leadership facilitate or hinder relationships between consumers and mental health services, and how these strategies influence hierarchical structures. Fourteen participants from a range of mental health organisations were interviewed. These interviews were analysed using thematic analytic and discursive psychological techniques. The findings highlight several benefits of having consumers within mental health organisational hierarchies, and elaborate on ways that employees within mental health services can support integration of consumers into existing hierarchies. Specific barriers to consumers in hierarchies are discussed, including a lack of clarity of structures and roles within hierarchies, and resistance to consumers reaching the highest levels of leadership within organisations. Alternative hierarchical models which privilege consumers' control over resources and power are also discussed. Mental health organisations are encouraged to integrate consumer leaders into their hierarchical structures to improve their organisational offerings, their reputation, and their service innovation.

Secular dynamics of hierarchical multiple systems composed of nested binaries, with an arbitrary number of bodies and arbitrary hierarchical structure - II. External perturbations: flybys and supernovae

NASA Astrophysics Data System (ADS)

Hamers, Adrian S.

2018-05-01

We extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the long-term secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy, provided that the system is composed of nested binary orbits. To model secular encounters, we expand the Hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system, to the separation of the widest orbit. Subsequently, we integrate over the perturber orbit numerically or analytically. We verify our method for secular encounters and illustrate it with an example. Furthermore, we describe a method to compute instantaneous orbital changes to multiple systems, such as asymmetric supernovae and impulsive encounters. The secular code, with implementation of the extensions described in this paper, is publicly available within AMUSE, and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters and asymmetric supernovae. The extensions presented in this paper are a next step towards efficiently modelling the evolution of complex multiple systems embedded in star clusters.

Novel MoSe2 hierarchical microspheres for applications in visible-light-driven advanced oxidation processes.

PubMed

Dai, Chu; Qing, Enping; Li, Yong; Zhou, Zhaoxin; Yang, Chao; Tian, Xike; Wang, Yanxin

2015-12-21

Advanced oxidation processes as a green technology have been adopted by combining the semiconductor catalyst MoSe2 with H2O2 under visible radiation. And novel three-dimensional self-assembled molybdenum diselenide (MoSe2) hierarchical microspheres from nanosheets were produced by using organic, selenium cyanoacetic acid sodium (NCSeCH2COONa) as the source of Se. The obtained products possess good crystallinity and present hierarchical structures with the average diameter of 1 μm. The band gap of MoSe2 microspheres is 1.68 eV and they present excellent photocatalytic activity under visible light irradiation in the MoSe2-H2O2 system. This effective photocatalytic mechanism was investigated in this study and can be attributed to visible-light-driven advanced oxidation processes.

An analytical study on groundwater flow in drainage basins with horizontal wells

NASA Astrophysics Data System (ADS)

Wang, Jun-Zhi; Jiang, Xiao-Wei; Wan, Li; Wang, Xu-Sheng; Li, Hailong

2014-06-01

Analytical studies on release/capture zones are often limited to a uniform background groundwater flow. In fact, for basin-scale problems, the undulating water table would lead to the development of hierarchically nested flow systems, which are more complex than a uniform flow. Under the premise that the water table is a replica of undulating topography and hardly influenced by wells, an analytical solution of hydraulic head is derived for a two-dimensional cross section of a drainage basin with horizontal injection/pumping wells. Based on the analytical solution, distributions of hydraulic head, stagnation points and flow systems (including release/capture zones) are explored. The superposition of injection/pumping wells onto the background flow field leads to the development of new internal stagnation points and new flow systems (including release/capture zones). Generally speaking, the existence of n injection/pumping wells would result in up to n new internal stagnation points and up to 2n new flow systems (including release/capture zones). The analytical study presented, which integrates traditional well hydraulics with the theory of regional groundwater flow, is useful in understanding basin-scale groundwater flow influenced by human activities.

Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE.

PubMed

Krishnan, Ananthanarayan; Gandour, Jackson T

2014-12-01

Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long-term experience shapes this adaptive process wherein the top-down connections provide selective gating of inputs to both cortical and subcortical structures to enhance neural responses to specific behaviorally-relevant attributes of the stimulus. A theoretical framework for a neural network is proposed involving coordination between local, feedforward, and feedback components that can account for experience-dependent enhancement of pitch representations at multiple levels of the auditory pathway. The ability to record brainstem and cortical pitch relevant responses concurrently may provide a new window to evaluate the online interplay between feedback, feedforward, and local intrinsic components in the hierarchical processing of pitch relevant information.

LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE

PubMed Central

Krishnan, Ananthanarayan; Gandour, Jackson T.

2015-01-01

Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long-term experience shapes this adaptive process wherein the top-down connections provide selective gating of inputs to both cortical and subcortical structures to enhance neural responses to specific behaviorally-relevant attributes of the stimulus. A theoretical framework for a neural network is proposed involving coordination between local, feedforward, and feedback components that can account for experience-dependent enhancement of pitch representations at multiple levels of the auditory pathway. The ability to record brainstem and cortical pitch relevant responses concurrently may provide a new window to evaluate the online interplay between feedback, feedforward, and local intrinsic components in the hierarchical processing of pitch relevant information. PMID:25838636

Hierarchically macro–mesoporous TiO{sub 2} film via self-assembled strategy for enhanced efficiency of dye sensitized solar cells

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

Wang, Ping; Wang, Jin; Yu, Huogen, E-mail: yuhuogen@whut.edu.cn

2016-02-15

Highlights: • A new hierarchically macro–mesoporous TiO{sub 2} film is fabricated via TiF{sub 4} hydrolysis. • TiF{sub 4} hydrolysis is accompanied with self-assembled process of TiO{sub 2} nanoparticles. • The hierarchically porous TiO{sub 2} films show higher performance than nonporous film. - Abstract: The hierarchically porous structure of TiO{sub 2} film plays an important role on improved photoelectric conversion efficiency in dye-sensitized solar cells (DSSCs). It is highly required to develop a facile strategy to prepare the hierarchical porous photoelectrode. In this study, a novel hierarchically macro–mesoporous TiO{sub 2} film as photoelectrode of DSSCs is fabricated by a self-assembled processmore » of TiO{sub 2} nanoparticles via TiF{sub 4} hydrolysis. The hydrolysis of TiF{sub 4} is accompanied with self-assembled process of TiO{sub 2} nanoparticles on the surface of electrophoretic-deposited titanate nanotube film which provides effective active sites for the deposition of TiO{sub 2} nanoparticles owing to a large amount of hydroxyl groups, resulting in the formation of hierarchically porous structures. The hierarchically porous TiO{sub 2} film is mainly composed of mesopores with a size of 2–50 nm and macropores with a wide range of 0.5–5 μm, which contribute to an obviously higher conversion performance (6.70%) than nonporous P25-TiO{sub 2} film (4.01%). The main reasons for enhanced conversion efficiency of hierarchically porous TiO{sub 2} film can be attributed to adsorption of more dye molecules, rapid diffusion and efficient transport of electrolyte, and longer electron lifetime. This work may provide new insights into preparing porous structure of TiO{sub 2} films in DSSCs for modification of photoelectric conversion efficiency.« less

Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

Hierarchical Self Assembly of Patterns from the Robinson Tilings: DNA Tile Design in an Enhanced Tile Assembly Model

PubMed Central

Padilla, Jennifer E.; Liu, Wenyan; Seeman, Nadrian C.

2012-01-01

We introduce a hierarchical self assembly algorithm that produces the quasiperiodic patterns found in the Robinson tilings and suggest a practical implementation of this algorithm using DNA origami tiles. We modify the abstract Tile Assembly Model, (aTAM), to include active signaling and glue activation in response to signals to coordinate the hierarchical assembly of Robinson patterns of arbitrary size from a small set of tiles according to the tile substitution algorithm that generates them. Enabling coordinated hierarchical assembly in the aTAM makes possible the efficient encoding of the recursive process of tile substitution. PMID:23226722

Hierarchical Self Assembly of Patterns from the Robinson Tilings: DNA Tile Design in an Enhanced Tile Assembly Model.

PubMed

Padilla, Jennifer E; Liu, Wenyan; Seeman, Nadrian C

2012-06-01

We introduce a hierarchical self assembly algorithm that produces the quasiperiodic patterns found in the Robinson tilings and suggest a practical implementation of this algorithm using DNA origami tiles. We modify the abstract Tile Assembly Model, (aTAM), to include active signaling and glue activation in response to signals to coordinate the hierarchical assembly of Robinson patterns of arbitrary size from a small set of tiles according to the tile substitution algorithm that generates them. Enabling coordinated hierarchical assembly in the aTAM makes possible the efficient encoding of the recursive process of tile substitution.

Soft modes in the perceptron model for jamming.

NASA Astrophysics Data System (ADS)

Franz, Silvio

I will show how a well known neural network model \\x9Dthe perceptro provides a simple solvable model of glassy behavior and jamming. The glassy minima of the energy function of this model can be studied in full analytic detail. This allows the identification of two kind of soft modes the first ones associated to the existence a marginal glass phase and a hierarchical structure of the energy landscape, the second ones associated to isostaticity and marginality of jamming. These results highlight the universality of the spectrum of normal modes in disordered systems, and open the way toward a detailed analytical understanding of the vibrational spectrum of low-temperature glasses. This work was supported by a Grant from the Simons Foundation (454941 to Silvio Franz).

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.

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…

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.

Should metacognition be measured by logistic regression?

PubMed

Rausch, Manuel; Zehetleitner, Michael

2017-03-01

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

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.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

NASA Astrophysics Data System (ADS)

Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-05-01

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

Flexible fabrication of biomimetic compound eye array via two-step thermal reflow of simply pre-modeled hierarchic microstructures

NASA Astrophysics Data System (ADS)

Huang, Shengzhou; Li, Mujun; Shen, Lianguan; Qiu, Jinfeng; Zhou, Youquan

2017-06-01

A flexible fabrication method for the biomimetic compound eye (BCE) array is proposed. In this method, a triple-layer sandwich-like coating configuration was introduced, and the required hierarchic microstructures are formed with a simple single-scan exposure in maskless digital lithography. Taking advantage of the difference of glass transition point (Tg) between photoresists of each layer, the pre-formed hierarchic microstructures are in turn reflowed to the curved substrate and the BCE ommatidia in a two-step thermal reflow process. To avoid affecting the spherical substrate formed in the first thermal reflow, a non-contact strategy was proposed in the second reflow process. The measurement results were in good agreement with the designed BCE profiles. Results also showed that the fabricated BCE had good performances in optical test. The presented method is flexible, convenient, low-cost and can easily adapt to the fabrications of other optical elements with hierarchic microstructures.

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.

A three-dimensional hierarchical collagen scaffold fabricated by a combined solid freeform fabrication (SFF) and electrospinning process to enhance mesenchymal stem cell (MSC) proliferation

NASA Astrophysics Data System (ADS)

Ahn, SeungHyun; Koh, Young Ho; Kim, GeunHyung

2010-06-01

Collagen has the advantage of being very similar to macromolecular substances that can be recognized and metabolized in the biological environment. Although the natural material has superior property for this purpose, its use to fabricate reproducible and pore-structure-controlled 3D structures, which are designed to allow the entry of sufficient cells and the easy diffusion of nutrients, has been limited due to its low processability. Here, we propose a hybrid technology that combines a cryogenic plotting system with an electrospinning process. Using this technique, an easily pore-size-controllable hierarchical 3D scaffold consisting of micro-sized highly porous collagen strands and micro/nano-sized collagen fibers was fabricated. The pore structure of the collagen scaffold was controlled by the collagen micro/nanofibers, which were layered in the scaffold. The hierarchical scaffolds were characterized with respect to initial cell attachment and proliferation of bone marrow-derived mesenchymal stem cells within the scaffolds. The hierarchical scaffold exhibited incredibly enhanced initial cell attachment and cell compactness between pores of the plotted scaffold relative to the normally designed 3D collagen scaffold.

Gravity or turbulence? IV. Collapsing cores in out-of-virial disguise

NASA Astrophysics Data System (ADS)

Ballesteros-Paredes, Javier; Vázquez-Semadeni, Enrique; Palau, Aina; Klessen, Ralf S.

2018-06-01

We study the dynamical state of massive cores by using a simple analytical model, an observational sample, and numerical simulations of collapsing massive cores. From the analytical model, we find that cores increase their column density and velocity dispersion as they collapse, resulting in a time evolution path in the Larson velocity dispersion-size diagram from large sizes and small velocity dispersions to small sizes and large velocity dispersions, while they tend to equipartition between gravity and kinetic energy. From the observational sample, we find that: (a) cores with substantially different column densities in the sample do not follow a Larson-like linewidth-size relation. Instead, cores with higher column densities tend to be located in the upper-left corner of the Larson velocity dispersion σv, 3D-size R diagram, a result explained in the hierarchical and chaotic collapse scenario. (b) Cores appear to have overvirial values. Finally, our numerical simulations reproduce the behavior predicted by the analytical model and depicted in the observational sample: collapsing cores evolve towards larger velocity dispersions and smaller sizes as they collapse and increase their column density. More importantly, however, they exhibit overvirial states. This apparent excess is due to the assumption that the gravitational energy is given by the energy of an isolated homogeneous sphere. However, such excess disappears when the gravitational energy is correctly calculated from the actual spatial mass distribution. We conclude that the observed energy budget of cores is consistent with their non-thermal motions being driven by their self-gravity and in the process of dynamical collapse.

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.

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.

Synthesis of multi-hierarchical structured yttria-stabilized zirconia powders and their enhanced thermophysical properties

NASA Astrophysics Data System (ADS)

Cao, Fengmei; Gao, Yanfeng; Chen, Hongfei; Liu, Xinling; Tang, Xiaoping; Luo, Hongjie

2013-06-01

Multi-hierarchical structured yttria-stabilized zirconia (YSZ) powders were successfully synthesized by a hydrothermal-calcination process. The morphology, crystallinity, and microstructure of the products were characterized by SEM, XRD, TEM, and BET. A possible formation mechanism of the unique structure formed during hydrothermal processing was also investigated. The measured thermophysical results indicated that the prepared YSZ powders had a low thermal conductivity (0.63-1.27 W m-1 K-1), good short-term high-temperature stability up to 1300 °C. The influence of the morphology and microstructure on their thermophysical properties was briefly discussed. The unique multi-hierarchical structure makes the prepared YSZ powders candidates for use in enhanced applications involving thermal barrier coatings.

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

Qian, Song S.; Cuffney, Thomas F.; Alameddine, Ibrahim; McMahon, Gerard; Reckhow, Kenneth H.

2010-01-01

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

CoMn2O4 Spinel Hierarchical Microspheres Assembled with Porous Nanosheets as Stable Anodes for Lithium-ion Batteries

PubMed Central

Hu, Lin; Zhong, Hao; Zheng, Xinrui; Huang, Yimin; Zhang, Ping; Chen, Qianwang

2012-01-01

Herein, we report the feasibility to enhance the capacity and stability of CoMn2O4 anode materials by fabricating hierarchical mesoporous structure. The open space between neighboring nanosheets allows for easy diffusion of the electrolyte. The hierarchical microspheres assembled with nanosheets can ensure that every nanosheet participates in the electrochemical reaction, because every nanosheet is contacted with the electrolyte solution. The hierarchical structure and well interconnected pores on the surface of nanosheets will enhance the CoMn2O4/electrolyte contact area, shorten the Li+ ion diffusion length in the nanosheets, and accommodate the strain induced by the volume change during the electrochemical reaction. The last, hierarchical architecture with spherical morphology possesses relatively low surface energy, which results in less extent of self-aggregation during charge/discharge process. As a result, CoMn2O4 hierarchical microspheres can achieve a good cycle ability and high rate capability. PMID:23248749

Exact hierarchical clustering in one dimension. [in universe

NASA Technical Reports Server (NTRS)

Williams, B. G.; Heavens, A. F.; Peacock, J. A.; Shandarin, S. F.

1991-01-01

The present adhesion model-based one-dimensional simulations of gravitational clustering have yielded bound-object catalogs applicable in tests of analytical approaches to cosmological structure formation. Attention is given to Press-Schechter (1974) type functions, as well as to their density peak-theory modifications and the two-point correlation function estimated from peak theory. The extent to which individual collapsed-object locations can be predicted by linear theory is significant only for objects of near-characteristic nonlinear mass.

Models and techniques for evaluating the effectiveness of aircraft computing systems

NASA Technical Reports Server (NTRS)

Meyer, J. F.

1978-01-01

The development of system models that can provide a basis for the formulation and evaluation of aircraft computer system effectiveness, the formulation of quantitative measures of system effectiveness, and the development of analytic and simulation techniques for evaluating the effectiveness of a proposed or existing aircraft computer are described. Specific topics covered include: system models; performability evaluation; capability and functional dependence; computation of trajectory set probabilities; and hierarchical modeling of an air transport mission.

Hierarchical analysis of the degradation of fibre-reinforced polymers under the presence of void imperfections

PubMed Central

2016-01-01

The subject of this work is the investigation of the influence of voids on the mechanical properties of fibre-reinforced polymers (FRPs) under compression loading. To specify the damage accumulation of FRPs in the presence of voids, the complex three-dimensional structure of the composite including voids was analysed and a reduced mechanical model composite was derived. The hierarchical analysis of the model composite on a micro-scale level implies the description of the stress and strain behaviour of the matrix using the photoelasticity technique and digital image correlation technology. These studies are presented along with an analytical examination of the stability of a single fibre. As a result of the experimental and analytical studies, the stiffness of the matrix and fibre as well as their bonding, the initial fibre orientation and the fibre diameter have the highest impact on the failure initiation. All these facts lead to a premature fibre–matrix debonding with ongoing loss of stability of the fibre and followed by kink-band formation. Additional studies on the meso-scale of transparent glass FRPs including a unique void showed that the experiments carried out on the model composites could be transferred to real composites. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242296

Simple and Hierarchical Models for Stochastic Test Misgrading.

ERIC Educational Resources Information Center

Wang, Jianjun

1993-01-01

Test misgrading is treated as a stochastic process. The expected number of misgradings, inter-occurrence time of misgradings, and waiting time for the "n"th misgrading are discussed based on a simple Poisson model and a hierarchical Beta-Poisson model. Examples of model construction are given. (SLD)

Hierarchical representation of shapes in visual cortex—from localized features to figural shape segregation

PubMed Central

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy. PMID:25157228

Hierarchical representation of shapes in visual cortex-from localized features to figural shape segregation.

PubMed

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1-V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.

Morphology evolution of hierarchical ZnO nanostructures modulated by supersaturation and growth temperature

NASA Astrophysics Data System (ADS)

Yan, Youguo; Zhou, Lixia; Yu, Lianqing; Zhang, Ye

2008-07-01

Three kinds of ZnO hierarchical structures, nanocombs with tube- and needle-shaped teeth and hierarchical nanorod arrays, were successfully synthesized through the chemical vapor deposition method. Combining the experimental parameters, the microcosmic growing conditions (growth temperature and supersaturation) along the flux was discussed at length, and, based on the conclusions, three reasonable growth processes were proposed. The results and discussions were beneficial to further realize the relation between the growing behavior of the nanomaterial and microcosmic conditions, and the hierarchical nanostructures obtained were also expected to have potential applications as functional blocks in future nanodevices. Furthermore, the study of photoluminescence further indicated that the physical properties were strongly dependent on the crystal structure.

Ranging through Gabor logons-a consistent, hierarchical approach.

PubMed

Chang, C; Chatterjee, S

1993-01-01

In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.

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

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.

Uniform Cu{sub 2}Cl(OH){sub 3} hierarchical microspheres: A novel adsorbent for methylene blue adsorptive removal from aqueous solution

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

Wei, Wei; Gao, Pin; Xie, Jimin, E-mail: xiejm391@sohu.com

2013-08-15

Using the solution phase method without any surfactants or templates, the hierarchical of Cu{sub 2}Cl(OH){sub 3} microspheres were synthesized by freeze drying. The size and surface area of the microspheres are ca. 1–2 µm and 76.61 m{sup 2} g{sup −1}, respectively. A possible formation mechanism is presented based on the experimental results. Methylene blue was chosen to investigate the adsorption capacity of the as-prepared adsorbent. The effects of various experimental parameters, such as pH, initial dye concentration, and contact time were investigated. The results showed that the dye removal increased with the increasing in the initial concentration of the dyemore » and also increased in the amount of microspheres used and initial pH. Adsorption data fitted well with the Freundlich adsorption isotherm. The thermodynamic analysis presented the exothermic, spontaneous and more ordered arrangement process. The microspheres could be employed effective for removal of dyes from aqueous solution. - Graphical abstract: The single-crystalline hierarchical Cu{sub 2}Cl(OH){sub 3} spheres can be prepared for the first time by using a template-free process through freeze-drying. Meanwhile, the hierarchical spheres exhibited high adsorption capacity to methylene blue. Display Omitted - Highlights: • Cu{sub 2}Cl(OH){sub 3} microspheres were successfully synthesized through a freeze drying process. • A possible formation mechanism of hierarchical microspheres was presented. • The Cu{sub 2}Cl(OH){sub 3} microspheres have high methylene blue adsorption capacity. • Methylene blue adsorption is a spontaneous and exothermic process. • The adsorption mechanism of microspheres onto dye was proposed in detail.« less

Quantitative Analysis of the Educational Infrastructure in Colombia Through the Use of a Georeferencing Software and Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Cala Estupiñan, Jose Luis; María González Bernal, Lina; Ponz Tienda, Jose Luis; Gutierrez Bucheli, Laura Andrea; Alejandro Arboleda, Carlos

2017-10-01

The distribution policies of the national budget have been showing an increasing trend of the investment in education infrastructure. This is the reason that makes it necessary to identify the territories with the greatest number of facilities (such as schools, colleges, universities and libraries) and those lacking this type of infrastructure, in order to know where a possible government intervention is required. This work is not intended to give a judgment on the qualitative state of the national infrastructure. It focuses, in terms of infrastructure, on Colombia’s quantitative status of the educational sector, by identifying the territories with more facilities, such as schools, colleges, universities and public libraries. To do this a quantitative index will be created to identify if the coverage of educational infrastructure at departmental level is enough, by taking into account not only the number of facilities, but also the population and the area of influence each one has. The above study is framed within a project of the University of the Andes called “visible Infrastructure”. The index is obtained through a hierarchical analytical process (AHP) and subsequently a linear equation that reflects the variables investigated. The validation of this index is performed through correlations and regressions of social, economic and cultural indicators determined by official entities. All the information on which the analysis is based is official and public. With the end of the armed conflict, it is necessary to focus the planning of public policies to heal the social gaps that the most vulnerable population needs.

Extending a Tandem Mass Spectral Library to Include MS2 Spectra of Fragment Ions Produced In-Source and MSn Spectra.

PubMed

Yang, Xiaoyu; Neta, Pedatsur; Stein, Stephen E

2017-11-01

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS 2 spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS 3 and MS 4 spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS 1 scans for an analyte acquired during an infusion experiment. The MS 2 spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS 2 spectra of the original precursors and of the in-source fragments as well as the MS n spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. Graphical Abstract ᅟ.

Optimality and stability of intentional and unintentional actions: I. Origins of drifts in performance.

PubMed

Parsa, Behnoosh; Terekhov, Alexander; Zatsiorsky, Vladimir M; Latash, Mark L

2017-02-01

We address the nature of unintentional changes in performance in two papers. This first paper tested a hypothesis that unintentional changes in performance variables during continuous tasks without visual feedback are due to two processes. First, there is a drift of the referent coordinate for the salient performance variable toward the actual coordinate of the effector. Second, there is a drift toward minimum of a cost function. We tested this hypothesis in four-finger isometric pressing tasks that required the accurate production of a combination of total moment and total force with natural and modified finger involvement. Subjects performed accurate force-moment production tasks under visual feedback, and then visual feedback was removed for some or all of the salient variables. Analytical inverse optimization was used to compute a cost function. Without visual feedback, both force and moment drifted slowly toward lower absolute magnitudes. Over 15 s, the force drop could reach 20% of its initial magnitude while moment drop could reach 30% of its initial magnitude. Individual finger forces could show drifts toward both higher and lower forces. The cost function estimated using the analytical inverse optimization reduced its value as a consequence of the drift. We interpret the results within the framework of hierarchical control with referent spatial coordinates for salient variables at each level of the hierarchy combined with synergic control of salient variables. The force drift is discussed as a natural relaxation process toward states with lower potential energy in the physical (physiological) system involved in the task.

Optimality and stability of intentional and unintentional actions: I. Origins of drifts in performance

PubMed Central

Parsa, Behnoosh; Terekhov, Alexander; Zatsiorsky, Vladimir M.; Latash, Mark L.

2016-01-01

We address the nature of unintentional changes in performance in two papers. This first paper tested a hypothesis that unintentional changes in performance variables during continuous tasks without visual feedback are due to two processes. First, there is a drift of the referent coordinate for the salient performance variable toward the actual coordinate of the effector. Second, there is a drift toward minimum of a cost function. We tested this hypothesis in four-finger isometric pressing tasks that required the accurate production of a combination of total moment and total force with natural and modified finger involvement. Subjects performed accurate force/moment production tasks under visual feedback, and then visual feedback was removed for some or all of the salient variables. Analytical inverse optimization was used to compute a cost function. Without visual feedback, both force and moment drifted slowly toward lower absolute magnitudes. Over 15 s, the force drop could reach 20% of its initial magnitude while moment drop could reach 30% of its initial magnitude. Individual finger forces could show drifts toward both higher and lower forces. The cost function estimated using the analytical inverse optimization reduced its value as a consequence of the drift. We interpret the results within the framework of hierarchical control with referent spatial coordinates for salient variables at each level of the hierarchy combined with synergic control of salient variables. The force drift is discussed as a natural relaxation process toward states with lower potential energy in the physical (physiological) system involved in the task. PMID:27785549

Hierarchical Spatiotemporal Dynamics of Speech Rhythm and Articulation

ERIC Educational Resources Information Center

Tilsen, Samuel Edward

2009-01-01

Hierarchy is one of the most important concepts in the scientific study of language. This dissertation aims to understand why we observe hierarchical structures in speech by investigating the cognitive processes from which they emerge. To that end, the dissertation explores how articulatory, rhythmic, and prosodic patterns of speech interact.…

Anisotropic and Hierarchical Porosity in Multifunctional Ceramics

NASA Astrophysics Data System (ADS)

Lichtner, Aaron Zev

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

Control/structure interaction conceptual design tool

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1990-01-01

The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

Stochastic dynamics of virus capsid formation: direct versus hierarchical self-assembly

PubMed Central

2012-01-01

Background In order to replicate within their cellular host, many viruses have developed self-assembly strategies for their capsids which are sufficiently robust as to be reconstituted in vitro. Mathematical models for virus self-assembly usually assume that the bonds leading to cluster formation have constant reactivity over the time course of assembly (direct assembly). In some cases, however, binding sites between the capsomers have been reported to be activated during the self-assembly process (hierarchical assembly). Results In order to study possible advantages of such hierarchical schemes for icosahedral virus capsid assembly, we use Brownian dynamics simulations of a patchy particle model that allows us to switch binding sites on and off during assembly. For T1 viruses, we implement a hierarchical assembly scheme where inter-capsomer bonds become active only if a complete pentamer has been assembled. We find direct assembly to be favorable for reversible bonds allowing for repeated structural reorganizations, while hierarchical assembly is favorable for strong bonds with small dissociation rate, as this situation is less prone to kinetic trapping. However, at the same time it is more vulnerable to monomer starvation during the final phase. Increasing the number of initial monomers does have only a weak effect on these general features. The differences between the two assembly schemes become more pronounced for more complex virus geometries, as shown here for T3 viruses, which assemble through homogeneous pentamers and heterogeneous hexamers in the hierarchical scheme. In order to complement the simulations for this more complicated case, we introduce a master equation approach that agrees well with the simulation results. Conclusions Our analysis shows for which molecular parameters hierarchical assembly schemes can outperform direct ones and suggests that viruses with high bond stability might prefer hierarchical assembly schemes. These insights increase our physical understanding of an essential biological process, with many interesting potential applications in medicine and materials science. PMID:23244740

Hierarchical FeTiO3-TiO2 hollow spheres for efficient simulated sunlight-driven water oxidation.

PubMed

Han, Taoran; Chen, Yajie; Tian, Guohui; Wang, Jian-Qiang; Ren, Zhiyu; Zhou, Wei; Fu, Honggang

2015-10-14

Oxygen generation is the key step for the photocatalytic overall water splitting and considered to be kinetically more challenging than hydrogen generation. Here, an effective water oxidation catalyst of hierarchical FeTiO3-TiO2 hollow spheres are prepared via a two-step sequential solvothermal processes and followed by thermal treatment. The existence of an effective heterointerface and built-in electric field in the surface space charge region in FeTiO3-TiO2 hollow spheres plays a positive role in promoting the separation of photoinduced electron-hole pairs. Surface photovoltage, transient-state photovoltage, fluorescence and electrochemical characterization are used to investigate the transfer process of photoinduced charge carriers. The photogenerated charge carriers in the hierarchical FeTiO3-TiO2 hollow spheres with a proper molar ratio display much higher separation efficiency and longer lifetime than those in the FeTiO3 alone. Moreover, it is suggested that the hierarchical porous hollow structure can contribute to the enhancement of light utilization, surface active sites and material transportation through the framework walls. This specific synergy significantly contributes to the remarkable improvement of the photocatalytic water oxidation activity of the hierarchical FeTiO3-TiO2 hollow spheres under simulated sunlight (AM1.5).

Application of advanced multidisciplinary analysis and optimization methods to vehicle design synthesis

NASA Technical Reports Server (NTRS)

Consoli, Robert David; Sobieszczanski-Sobieski, Jaroslaw

1990-01-01

Advanced multidisciplinary analysis and optimization methods, namely system sensitivity analysis and non-hierarchical system decomposition, are applied to reduce the cost and improve the visibility of an automated vehicle design synthesis process. This process is inherently complex due to the large number of functional disciplines and associated interdisciplinary couplings. Recent developments in system sensitivity analysis as applied to complex non-hierarchic multidisciplinary design optimization problems enable the decomposition of these complex interactions into sub-processes that can be evaluated in parallel. The application of these techniques results in significant cost, accuracy, and visibility benefits for the entire design synthesis process.

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.

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

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.

General monogamy of Tsallis q -entropy entanglement in multiqubit systems

NASA Astrophysics Data System (ADS)

Luo, Yu; Tian, Tian; Shao, Lian-He; Li, Yongming

2016-06-01

In this paper, we study the monogamy inequality of Tsallis q -entropy entanglement. We first provide an analytic formula of Tsallis q -entropy entanglement in two-qubit systems for 5/-√{13 } 2 ≤q ≤5/+√{13 } 2 . The analytic formula of Tsallis q -entropy entanglement in 2 ⊗d system is also obtained and we show that Tsallis q -entropy entanglement satisfies a set of hierarchical monogamy equalities. Furthermore, we prove the squared Tsallis q -entropy entanglement follows a general inequality in the qubit systems. Based on the monogamy relations, a set of multipartite entanglement indicators is constructed, which can detect all genuine multiqubit entangled states even in the case of N -tangle vanishes. Moreover, we study some examples in multipartite higher-dimensional system for the monogamy inequalities.

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.

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.

The Role of Discrete Global Grid Systems in the Global Statistical Geospatial Framework

NASA Astrophysics Data System (ADS)

Purss, M. B. J.; Peterson, P.; Minchin, S. A.; Bermudez, L. E.

2016-12-01

The United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) has proposed the development of a Global Statistical Geospatial Framework (GSGF) as a mechanism for the establishment of common analytical systems that enable the integration of statistical and geospatial information. Conventional coordinate reference systems address the globe with a continuous field of points suitable for repeatable navigation and analytical geometry. While this continuous field is represented on a computer in a digitized and discrete fashion by tuples of fixed-precision floating point values, it is a non-trivial exercise to relate point observations spatially referenced in this way to areal coverages on the surface of the Earth. The GSGF states the need to move to gridded data delivery and the importance of using common geographies and geocoding. The challenges associated with meeting these goals are not new and there has been a significant effort within the geospatial community to develop nested gridding standards to tackle these issues over many years. These efforts have recently culminated in the development of a Discrete Global Grid Systems (DGGS) standard which has been developed under the auspices of Open Geospatial Consortium (OGC). DGGS provide a fixed areal based geospatial reference frame for the persistent location of measured Earth observations, feature interpretations, and modelled predictions. DGGS address the entire planet by partitioning it into a discrete hierarchical tessellation of progressively finer resolution cells, which are referenced by a unique index that facilitates rapid computation, query and analysis. The geometry and location of the cell is the principle aspect of a DGGS. Data integration, decomposition, and aggregation is optimised in the DGGS hierarchical structure and can be exploited for efficient multi-source data processing, storage, discovery, transmission, visualization, computation, analysis, and modelling. During the 6th Session of the UN-GGIM in August 2016 the role of DGGS in the context of the GSGF was formally acknowledged. This paper proposes to highlight the synergies and role of DGGS in the Global Statistical Geospatial Framework and to show examples of the use of DGGS to combine geospatial statistics with traditional geoscientific data.

Comparison of the performance of the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with the Charlson and Elixhauser comorbidity measures in predicting mortality.

PubMed

Li, Pengxiang; Kim, Michelle M; Doshi, Jalpa A

2010-08-20

The Centers for Medicare and Medicaid Services (CMS) has implemented the CMS-Hierarchical Condition Category (CMS-HCC) model to risk adjust Medicare capitation payments. This study intends to assess the performance of the CMS-HCC risk adjustment method and to compare it to the Charlson and Elixhauser comorbidity measures in predicting in-hospital and six-month mortality in Medicare beneficiaries. The study used the 2005-2006 Chronic Condition Data Warehouse (CCW) 5% Medicare files. The primary study sample included all community-dwelling fee-for-service Medicare beneficiaries with a hospital admission between January 1st, 2006 and June 30th, 2006. Additionally, four disease-specific samples consisting of subgroups of patients with principal diagnoses of congestive heart failure (CHF), stroke, diabetes mellitus (DM), and acute myocardial infarction (AMI) were also selected. Four analytic files were generated for each sample by extracting inpatient and/or outpatient claims for each patient. Logistic regressions were used to compare the methods. Model performance was assessed using the c-statistic, the Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and their 95% confidence intervals estimated using bootstrapping. The CMS-HCC had statistically significant higher c-statistic and lower AIC and BIC values than the Charlson and Elixhauser methods in predicting in-hospital and six-month mortality across all samples in analytic files that included claims from the index hospitalization. Exclusion of claims for the index hospitalization generally led to drops in model performance across all methods with the highest drops for the CMS-HCC method. However, the CMS-HCC still performed as well or better than the other two methods. The CMS-HCC method demonstrated better performance relative to the Charlson and Elixhauser methods in predicting in-hospital and six-month mortality. The CMS-HCC model is preferred over the Charlson and Elixhauser methods if information about the patient's diagnoses prior to the index hospitalization is available and used to code the risk adjusters. However, caution should be exercised in studies evaluating inpatient processes of care and where data on pre-index admission diagnoses are unavailable.

Odor Recognition vs. Classification in Artificial Olfaction

NASA Astrophysics Data System (ADS)

Raman, Baranidharan; Hertz, Joshua; Benkstein, Kurt; Semancik, Steve

2011-09-01

Most studies in chemical sensing have focused on the problem of precise identification of chemical species that were exposed during the training phase (the recognition problem). However, generalization of training to predict the chemical composition of untrained gases based on their similarity with analytes in the training set (the classification problem) has received very limited attention. These two analytical tasks pose conflicting constraints on the system. While correct recognition requires detection of molecular features that are unique to an analyte, generalization to untrained chemicals requires detection of features that are common across a desired class of analytes. A simple solution that addresses both issues simultaneously can be obtained from biological olfaction, where the odor class and identity information are decoupled and extracted individually over time. Mimicking this approach, we proposed a hierarchical scheme that allowed initial discrimination between broad chemical classes (e.g. contains oxygen) followed by finer refinements using additional data into sub-classes (e.g. ketones vs. alcohols) and, eventually, specific compositions (e.g. ethanol vs. methanol) [1]. We validated this approach using an array of temperature-controlled chemiresistors. We demonstrated that a small set of training analytes is sufficient to allow generalization to novel chemicals and that the scheme provides robust categorization despite aging. Here, we provide further characterization of this approach.

Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

USGS Publications Warehouse

Gotelli, Nicholas J.; Dorazio, Robert M.; Ellison, Aaron M.; Grossman, Gary D.

2010-01-01

Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.

Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Elliott, James R. (Inventor); Stoakley, Diane M. (Inventor); Chu, Sang-Hyon (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Choi, Sang Hyouk (Inventor); Lillehei, Peter T. (Inventor)

2011-01-01

A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

Correlation between Hierarchical Structure and Processing Control of Large-area Spray-coated Polymer Solar Cells toward High Performance

PubMed Central

Huang, Yu-Ching; Tsao, Cheng-Si; Cha, Hou-Chin; Chuang, Chih-Min; Su, Chun-Jen; Jeng, U-Ser; Chen, Charn-Ying

2016-01-01

The formation mechanism of a spray-coated film is different from that of a spin-coated film. This study employs grazing incidence small- and wide-angle X-ray Scattering (GISAXS and GIWAXS, respectively) quantitatively and systematically to investigate the hierarchical structure and phase-separated behavior of a spray-deposited blend film. The formation of PCBM clusters involves mutual interactions with both the P3HT crystal domains and droplet boundary. The processing control and the formed hierarchical structure of the active layer in the spray-coated polymer/fullerene blend film are compared to those in the spin-coated film. How the different post-treatments, such as thermal and solvent vapor annealing, tailor the hierarchical structure of the spray-coated films is quantitatively studied. Finally, the relationship between the processing control and tailored BHJ structures and the performance of polymer solar cell devices is established here, taking into account the evolution of the device area from 1 × 0.3 and 1 × 1 cm2. The formation and control of the special networks formed by the PCBM cluster and P3HT crystallites, respectively, are related to the droplet boundary. These structures are favorable for the transverse transport of electrons and holes. PMID:26817585

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

ERIC Educational Resources Information Center

Denson, Nida; Seltzer, Michael H.

2011-01-01

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

Formulation and Application of the Hierarchical Generalized Random-Situation Random-Weight MIRID

ERIC Educational Resources Information Center

Hung, Lai-Fa

2011-01-01

The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…

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…

Pushing typists back on the learning curve: revealing chunking in skilled typewriting.

PubMed

Yamaguchi, Motonori; Logan, Gordon D

2014-04-01

Theories of skilled performance propose that highly trained skills involve hierarchically structured control processes. The present study examined and demonstrated hierarchical control at several levels of processing in skilled typewriting. In the first two experiments, we scrambled the order of letters in words to prevent skilled typists from chunking letters, and compared typing words and scrambled words. Experiment 1 manipulated stimulus quality to reveal chunking in perception, and Experiment 2 manipulated concurrent memory load to reveal chunking in short-term memory (STM). Both experiments manipulated the number of letters in words and nonwords to reveal chunking in motor planning. In the next two experiments, we degraded typing skill by altering the usual haptic feedback by using a laser-projection keyboard, so that typists had to monitor keystrokes. Neither the number of motor chunks (Experiment 3) nor the number of STM items (Experiment 4) was influenced by the manipulation. The results indicate that the utilization of hierarchical control depends on whether the input allows chunking but not on whether the output is generated automatically. We consider the role of automaticity in hierarchical control of skilled performance.

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

Emulsion-Assisted Polymerization-Induced Hierarchical Self-Assembly of Giant Sea Urchin-like Aggregates in a Large Scale.

PubMed

Xu, Qingsong; Huang, Tong; Li, Shanlong; Li, Ke; Li, Chuanlong; Liu, Yannan; Wang, Yuling; Yu, Chunyang; Zhou, Yongfeng

2018-05-09

Hierarchical solution self-assembly has nowadays become an important biomimetic method to prepare highly complex and multifunctional supramolecular structures. However, despites the great progress, it is still highly challenging to prepare hierarchical self-assemblies in a large scale since the self-assembly processes are generally performed at high dilution. Herein, we report an emulsion-assisted polymerization-induced self-assembly (EAPISA) method with the advantages of in-situ self-assembly process, scalable preparation and facile functionalization to prepare hierarchical multiscale sea urchin-like aggregates (SUAs). It also extends horizons of PISA in monomers and in polymerization method. The obtained SUAs from amphiphilic alternating copolymers represent a novel self-assembled structure with micron-sized rattan ball-like capsule (RBC) acting as the hollow core body and radiating nanotubes tens of micrometers in length as the hollow spines. They can effectively capture model proteins at an ultra-low concentration (≈10 nM) after functionalized with amino groups through click copolymerization. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

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.

Defining and Enabling Resiliency of Electric Distribution Systems With Multiple Microgrids

DOE PAGES

Chanda, Sayonsom; Srivastava, Anurag K.

2016-05-02

This paper presents a method for quantifying and enabling the resiliency of a power distribution system (PDS) using analytical hierarchical process and percolation theory. Using this metric, quantitative analysis can be done to analyze the impact of possible control decisions to pro-actively enable the resilient operation of distribution system with multiple microgrids and other resources. Developed resiliency metric can also be used in short term distribution system planning. The benefits of being able to quantify resiliency can help distribution system planning engineers and operators to justify control actions, compare different reconfiguration algorithms, develop proactive control actions to avert power systemmore » outage due to impending catastrophic weather situations or other adverse events. Validation of the proposed method is done using modified CERTS microgrids and a modified industrial distribution system. Furthermore, simulation results show topological and composite metric considering power system characteristics to quantify the resiliency of a distribution system with the proposed methodology, and improvements in resiliency using two-stage reconfiguration algorithm and multiple microgrids.« less

Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy

DOE PAGES

Liu, Yijin; Meirer, Florian; Krest, Courtney M.; ...

2016-08-30

To understand how hierarchically structured functional materials operate, analytical tools are needed that can reveal small structural and chemical details in large sample volumes. Often, a single method alone is not sufficient to get a complete picture of processes happening at multiple length scales. Here we present a correlative approach combining three-dimensional X-ray imaging techniques at different length scales for the analysis of metal poisoning of an individual catalyst particle. The correlative nature of the data allowed establishing a macro-pore network model that interprets metal accumulations as a resistance to mass transport and can, by tuning the effect of metalmore » deposition, simulate the response of the network to a virtual ageing of the catalyst particle. In conclusion, the developed approach is generally applicable and provides an unprecedented view on dynamic changes in a material’s pore space, which is an essential factor in the rational design of functional porous materials.« less

Evidentiary Pluralism as a Strategy for Research and Evidence-Based Practice in Rehabilitation Psychology

PubMed Central

Tucker, Jalie A.; Reed, Geoffrey M.

2008-01-01

This paper examines the utility of evidentiary pluralism, a research strategy that selects methods in service of content questions, in the context of rehabilitation psychology. Hierarchical views that favor randomized controlled clinical trials (RCTs) over other evidence are discussed, and RCTs are considered as they intersect with issues in the field. RCTs are vital for establishing treatment efficacy, but whether they are uniformly the best evidence to inform practice is critically evaluated. We argue that because treatment is only one of several variables that influence functioning, disability, and participation over time, an expanded set of conceptual and data analytic approaches should be selected in an informed way to support an expanded research agenda that investigates therapeutic and extra-therapeutic influences on rehabilitation processes and outcomes. The benefits of evidentiary pluralism are considered, including helping close the gap between the narrower clinical rehabilitation model and a public health disability model. KEY WORDS: evidence-based practice, evidentiary pluralism, rehabilitation psychology, randomized controlled trials PMID:19649150

Prioritizing lean management practices in public and private hospitals.

PubMed

Hussain, Matloub; Malik, Mohsin

2016-05-16

Purpose - The purpose of this paper is to prioritize 21 healthcare wastes in public and private hospitals of United Arab Emirates (UAE). Design/methodology/approach - Seven healthcare wastes linked with lean management are further decomposed in to sub-criteria and to deal with this complexity of multi criteria decision-making process, analytical hierarchical process (AHP) method is used in this research. Findings - AHP framework for this study resulted in a ranking of 21 healthcare wastes in public and private hospitals of UAE. It has been found that management in private healthcare systems of UAE is putting more emphasis on the inventory waste. On the other hand, over processing waste has got highest weight in public hospitals of UAE. Research limitations/implications - The future directions of this research would be to apply a lean set of tools for the value stream optimization of the prioritized key improvement areas. Practical implications - This is a contribution to the continuing research into lean management, giving practitioners and designers a practical way for measuring and implementing lean practices across health organizations. Originality/value - The contribution of this research, through successive stages of data collection, measurement analysis and refinement, is a set of reliable and valid framework that can be subsequently used in conceptualization, prioritization of the waste reduction strategies in healthcare management.

Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

PubMed

Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

2015-12-01

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

Do new concepts for deriving permissible limits for analytical imprecision and bias have any advantages over existing consensus?

PubMed

Petersen, Per Hyltoft; Sandberg, Sverre; Fraser, Callum G

2011-04-01

The Stockholm conference held in 1999 on "Strategies to set global analytical quality specifications (AQS) in laboratory medicine" reached a consensus and advocated the ubiquitous application of a hierarchical structure of approaches to setting AQS. This approach has been widely used over the last decade, although several issues remain unanswered. A number of new suggestions have been recently proposed for setting AQS. One of these recommendations is described by Haeckel and Wosniok in this issue of Clinical Chemistry and Laboratory Medicine. Their concept is to estimate the increase in false-positive results using conventional population-based reference intervals, the delta false-positive rate due to analytical imprecision and bias, and relate the results directly to the current analytical quality attained. Thus, the actual estimates in the laboratory for imprecision and bias are compared to the AQS. These values are classified in a ranking system according to the closeness to the AQS, and this combination is the new idea of the proposal. Other new ideas have been proposed recently. We wait, with great interest, as should others, to see if these newer approaches become widely used and worthy of incorporation into the hierarchy.

Hierarchical hollow microsphere and flower-like indium oxide: Controllable synthesis and application as H{sub 2}S cataluminescence sensing materials

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

Cai, Pingyang, E-mail: cpyxx@163.com; Bai, Wei, E-mail: weibaiscu@gmail.com; Zhang, Lichun, E-mail: lichun0203@yahoo.cn

Graphical abstract: Hierarchical hollow microsphere and flower-like In{sub 2}O{sub 3} were controllable fabricated through a novel and simple hydrothermal process, and the former showed superior cataluminescence sensing performance to H{sub 2}S. Highlights: ► In{sub 2}O{sub 3} hierarchical hollow sphere were prepared via a hydrothermal route. ► The growth process of In{sub 2}O{sub 3} hierarchical hollow sphere has been investigated. ► The sensor based on prepared In{sub 2}O{sub 3} shows good sensing performance to H{sub 2}S. -- Abstract: In the present work, In{sub 2}O{sub 3} hierarchical hollow microsphere and flower-like microstructure were achieved controllably by a hydrothermal process in the sodiummore » dodecyl sulfate (SDS)-N,N-dimethyl-formamide (DMF) system. XRD, SEM, HRTEM and N{sub 2} adsorption measurements were used to characterize the as-prepared indium oxide materials and the possible mechanism for the microstructures formation was briefly discussed. The cataluminescence gas sensor based on the as-prepared In{sub 2}O{sub 3} was utilized to detect H{sub 2}S concentrations in flowing air. Comparative gas sensing results revealed that the sensor based on hierarchical hollow microsphere exhibited much higher sensing sensitivity in detecting H{sub 2}S gas than the sensor based on flower-like microstructure. The present gas sensor had a fast response time of 5 s and a recovery time of less than 25 s, furthermore, the cataluminescence intensity vs. H{sub 2}S concentration was linear in range of 2–20 μg mL{sup −1} with a detection limit of 0.5 μg mL{sup −1}. The present highly sensitive, fast-responding, and low-cost In{sub 2}O{sub 3}-based gas sensor for H{sub 2}S would have many practical applications.« less

Activating the Microscale Edge Effect in a Hierarchical Surface for Frosting Suppression and Defrosting Promotion

PubMed Central

Chen, Xuemei; Ma, Ruiyuan; Zhou, Hongbo; Zhou, Xiaofeng; Che, Lufeng; Yao, Shuhuai; Wang, Zuankai

2013-01-01

Despite extensive progress, current icephobic materials are limited by the breakdown of their icephobicity in the condensation frosting environment. In particular, the frost formation over the entire surface is inevitable as a result of undesired inter-droplet freezing wave propagation initiated by the sample edges. Moreover, the frost formation directly results in an increased frost adhesion, posing severe challenges for the subsequent defrosting process. Here, we report a hierarchical surface which allows for interdroplet freezing wave propagation suppression and efficient frost removal. The enhanced performances are mainly owing to the activation of the microscale edge effect in the hierarchical surface, which increases the energy barrier for ice bridging as well as engendering the liquid lubrication during the defrosting process. We believe the concept of harnessing the surface morphology to achieve superior performances in two opposite phase transition processes might shed new light on the development of novel materials for various applications. PMID:23981909

The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas

PubMed Central

Friston, K. J.

2010-01-01

This article explores the notion that Freudian constructs may have neurobiological substrates. Specifically, we propose that Freud’s descriptions of the primary and secondary processes are consistent with self-organized activity in hierarchical cortical systems and that his descriptions of the ego are consistent with the functions of the default-mode and its reciprocal exchanges with subordinate brain systems. This neurobiological account rests on a view of the brain as a hierarchical inference or Helmholtz machine. In this view, large-scale intrinsic networks occupy supraordinate levels of hierarchical brain systems that try to optimize their representation of the sensorium. This optimization has been formulated as minimizing a free-energy; a process that is formally similar to the treatment of energy in Freudian formulations. We substantiate this synthesis by showing that Freud’s descriptions of the primary process are consistent with the phenomenology and neurophysiology of rapid eye movement sleep, the early and acute psychotic state, the aura of temporal lobe epilepsy and hallucinogenic drug states. PMID:20194141

Hierarchical Parallelization of Gene Differential Association Analysis

PubMed Central

2011-01-01

Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels. PMID:21936916

Hierarchical parallelization of gene differential association analysis.

PubMed

Needham, Mark; Hu, Rui; Dwarkadas, Sandhya; Qiu, Xing

2011-09-21

Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

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.

Mesoporous titanium dioxide (TiO2) with hierarchically 3D dendrimeric architectures: formation mechanism and highly enhanced photocatalytic activity.

PubMed

Li, Xiao-Yun; Chen, Li-Hua; Rooke, Joanna Claire; Deng, Zhao; Hu, Zhi-Yi; Wang, Shao-Zhuan; Wang, Li; Li, Yu; Krief, Alain; Su, Bao-Lian

2013-03-15

Mesoporous TiO(2) with a hierarchically 3D dendrimeric nanostructure comprised of nanoribbon building units has been synthesized via a spontaneous self-formation process from various titanium alkoxides. These hierarchically 3D dendrimeric architectures can be obtained by a very facile, template-free method, by simply dropping a titanium butoxide precursor into methanol solution. The novel configuration of the mesoporous TiO(2) nanostructure in nanoribbon building units yields a high surface area. The calcined samples show significantly enhanced photocatalytic activity and degradation rates owing to the mesoporosity and their improved crystallinity after calcination. Furthermore, the 3D dendrimeric architectures can be preserved after phase transformation from amorphous TiO(2) to anatase or rutile, which occurs during calcination. In addition, the spontaneous self-formation process of mesoporous TiO(2) with hierarchically 3D dendrimeric architectures from the hydrolysis and condensation reaction of titanium butoxide in methanol has been followed by in situ optical microscopy (OM), revealing the secret on the formation of hierarchically 3D dendrimeric nanostructures. Moreover, mesoporous TiO(2) nanostructures with similar hierarchically 3D dendrimeric architectures can also be obtained using other titanium alkoxides. The porosities and nanostructures of the resultant products were characterized by SEM, TEM, XRD, and N(2) adsorption-desorption measurements. The present work provides a facile and reproducible method for the synthesis of novel mesoporous TiO(2) nanoarchitectures, which in turn could herald the fabrication of more efficient photocatalysts. Copyright © 2012 Elsevier Inc. All rights reserved.

A highly efficient electrocatalyst for oxygen reduction reaction: phosphorus and nitrogen co-doped hierarchically ordered porous carbon derived from an iron-functionalized polymer

NASA Astrophysics Data System (ADS)

Deng, Chengwei; Zhong, Hexiang; Li, Xianfeng; Yao, Lan; Zhang, Huamin

2016-01-01

Heteroatom-doped carbon materials have shown respectable activity for the oxygen reduction reaction (ORR) in alkaline media. However, the performances of these materials are not satisfactory for energy conversion devices, such as fuel cells. Here, we demonstrate a new type of phosphorus and nitrogen co-doped hierarchically ordered porous carbon (PNHOPC) derived from an iron-functionalized mesoporous polymer through an evaporation-induced self-assembly process that simultaneously combines the carbonization and nitrogen doping processes. The soft template and the nitrogen doping process facilitate the formation of the hierarchically ordered structure for the PNHOPC. The catalyst possesses a large surface area (1118 cm2 g-1) and a pore volume of 1.14 cm3 g-1. Notably, it exhibits excellent ORR catalytic performance, superior stability and methanol tolerance in acidic electrolytes, thus making the catalyst promising for fuel cells. The correlations between the unique pore structure and the nitrogen and phosphorus configuration of the catalysts with high catalytic activity are thoroughly investigated.Heteroatom-doped carbon materials have shown respectable activity for the oxygen reduction reaction (ORR) in alkaline media. However, the performances of these materials are not satisfactory for energy conversion devices, such as fuel cells. Here, we demonstrate a new type of phosphorus and nitrogen co-doped hierarchically ordered porous carbon (PNHOPC) derived from an iron-functionalized mesoporous polymer through an evaporation-induced self-assembly process that simultaneously combines the carbonization and nitrogen doping processes. The soft template and the nitrogen doping process facilitate the formation of the hierarchically ordered structure for the PNHOPC. The catalyst possesses a large surface area (1118 cm2 g-1) and a pore volume of 1.14 cm3 g-1. Notably, it exhibits excellent ORR catalytic performance, superior stability and methanol tolerance in acidic electrolytes, thus making the catalyst promising for fuel cells. The correlations between the unique pore structure and the nitrogen and phosphorus configuration of the catalysts with high catalytic activity are thoroughly investigated. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06749a

Cascade process modeling with mechanism-based hierarchical neural networks.

PubMed

Cong, Qiumei; Yu, Wen; Chai, Tianyou

2010-02-01

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

Accelerating Electrostatic Surface Potential Calculation with Multiscale Approximation on Graphics Processing Units

PubMed Central

Anandakrishnan, Ramu; Scogland, Tom R. W.; Fenley, Andrew T.; Gordon, John C.; Feng, Wu-chun; Onufriev, Alexey V.

2010-01-01

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multiscale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone. PMID:20452792

Risk-based design of process plants with regard to domino effects and land use planning.

PubMed

Khakzad, Nima; Reniers, Genserik

2015-12-15

Land use planning (LUP) as an effective and crucial safety measure has widely been employed by safety experts and decision makers to mitigate off-site risks posed by major accidents. Accordingly, the concept of LUP in chemical plants has traditionally been considered from two perspectives: (i) land developments around existing chemical plants considering potential off-site risks posed by major accidents and (ii) development of existing chemical plants considering nearby land developments and the level of additional off-site risks the land developments would be exposed to. However, the attempts made to design chemical plants with regard to LUP requirements have been few, most of which have neglected the role of domino effects in risk analysis of major accidents. To overcome the limitations of previous work, first, we developed a Bayesian network methodology to calculate both on-site and off-site risks of major accidents while taking domino effects into account. Second, we combined the results of risk analysis with Analytic Hierarchical Process to design an optimal layout for which the levels of on-site and off-site risks would be minimum. Copyright © 2015 Elsevier B.V. All rights reserved.

The fluency of social hierarchy: the ease with which hierarchical relationships are seen, remembered, learned, and liked.

PubMed

Zitek, Emily M; Tiedens, Larissa Z

2012-01-01

We tested the hypothesis that social hierarchies are fluent social stimuli; that is, they are processed more easily and therefore liked better than less hierarchical stimuli. In Study 1, pairs of people in a hierarchy based on facial dominance were identified faster than pairs of people equal in their facial dominance. In Study 2, a diagram representing hierarchy was memorized more quickly than a diagram representing equality or a comparison diagram. This faster processing led the hierarchy diagram to be liked more than the equality diagram. In Study 3, participants were best able to learn a set of relationships that represented hierarchy (asymmetry of power)--compared to relationships in which there was asymmetry of friendliness, or compared to relationships in which there was symmetry--and this processing ease led them to like the hierarchy the most. In Study 4, participants found it easier to make decisions about a company that was more hierarchical and thus thought the hierarchical organization had more positive qualities. In Study 5, familiarity as a basis for the fluency of hierarchy was demonstrated by showing greater fluency for male than female hierarchies. This study also showed that when social relationships are difficult to learn, people's preference for hierarchy increases. Taken together, these results suggest one reason people might like hierarchies--hierarchies are easy to process. This fluency for social hierarchies might contribute to the construction and maintenance of hierarchies.

Facility Monitoring: A Qualitative Theory for Sensor Fusion

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2001-01-01

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

A Feasible One-Step Synthesis of Hierarchical Zeolite Beta with Uniform Nanocrystals via CTAB

PubMed Central

Zhang, Weimin; Hu, Sufang; Qin, Bo; Li, Ruifeng

2018-01-01

A hierarchical zeolite Beta has been prepared by a feasible one-pot and one-step method, which is suitable for application in industrial production. The synthesis is a simple hydrothermal process with low-cost raw materials, without adding alcohol or adding seeds, and without aging, recrystallization, and other complex steps. The hierarchical zeolite Beta is a uniform nanocrystal (20–50 nm) aggregation with high external surface area (300 m2/g) and mesoporous volume (0.50 cm3/g), with the mesoporous structure composed of intercrystal and intracrystal pores. As an acid catalyst in benzylation of naphthalene with benzyl chloride, the hierarchical zeolite Beta has shown high activity in the bulky molecule reaction due to its introduction of mesostructure. PMID:29695044

Asymmetric block copolymer membranes with ultrahigh porosity and hierarchical pore structure by plain solvent evaporation.

PubMed

Yu, H; Qiu, X; Behzad, A R; Musteata, V; Smilgies, D-M; Nunes, S P; Peinemann, K-V

2016-10-04

Membranes with a hierarchical porous structure could be manufactured from a block copolymer blend by pure solvent evaporation. Uniform pores in a 30 nm thin skin layer supported by a macroporous structure were formed. This new process is attractive for membrane production because of its simplicity and the lack of liquid waste.

A hierarchical linear model for tree height prediction.

Treesearch

Vicente J. Monleon

2003-01-01

Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...

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…

Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items

ERIC Educational Resources Information Center

Mariano, Louis T.; Junker, Brian W.

2007-01-01

When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…

A simple phenomenological model for grain clustering in turbulence

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-01-01

We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.

High-Dimensional Bayesian Geostatistics

PubMed Central

Banerjee, Sudipto

2017-01-01

With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as “priors” for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has ~ n floating point operations (flops), where n the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings. PMID:29391920

High-Dimensional Bayesian Geostatistics.

PubMed

Banerjee, Sudipto

2017-06-01

With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as "priors" for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has ~ n floating point operations (flops), where n the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

PubMed Central

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

PubMed

Colas, Jaron T

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

PubMed

Leung, S C; Fung, W K; Wong, K H

1999-01-01

The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

Hierarchically Superstructured Prussian Blue Analogues: Spontaneous Assembly Synthesis and Applications as Pseudocapacitive Materials

DOE PAGES

Yue, Yanfeng; Zhang, Zhiyong; Binder, Andrew J.; ...

2014-11-10

Hierarchically superstructured Prussian blue analogues (hexa- conventional hybrid graphene/MnO 2 nanostructured textiles. cyanoferrate, M = Ni II, Co II and Cu II) are synthesized through Because sodium or potassium ions are involved in energy stor- a spontaneous assembly technique. In sharp contrast to mac- age processes, more environmentally neutral electrolytes can roporous-only Prussian blue analogues, the hierarchically su- be utilized, making the superstructured porous Prussian blue perstructured porous Prussian blue materials are demonstrated analogues a great contender for applications as high-per- to possess a high capacitance, which is similar to those of the formance pseudocapacitors.

Self-organized emergence of multilayer structure and chimera states in dynamical networks with adaptive couplings

NASA Astrophysics Data System (ADS)

Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.

2017-12-01

We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.

Palm: Easing the Burden of Analytical Performance Modeling

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

Tallent, Nathan R.; Hoisie, Adolfy

2014-06-01

Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexitymore » (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.« less

E-HOSPITAL - A Digital Workbench for Hospital Operations and Services Planning Using Information Technology and Algebraic Languages.

PubMed

Gartner, Daniel; Padman, Rema

2017-01-01

In this paper, we describe the development of a unified framework and a digital workbench for the strategic, tactical and operational hospital management plan driven by information technology and analytics. The workbench can be used not only by multiple stakeholders in the healthcare delivery setting, but also for pedagogical purposes on topics such as healthcare analytics, services management, and information systems. This tool combines the three classical hierarchical decision-making levels in one integrated environment. At each level, several decision problems can be chosen. Extensions of mathematical models from the literature are presented and incorporated into the digital platform. In a case study using real-world data, we demonstrate how we used the workbench to inform strategic capacity planning decisions in a multi-hospital, multi-stakeholder setting in the United Kingdom.

A multi-scalar approach for modelling river channel change in the Anthropocene

NASA Astrophysics Data System (ADS)

Downs, Peter; Piégay, Hervé; Piffady, Jeremy; Valette, Laurent; Vaudor, Lise

2017-04-01

Adjustments in river channel morphology during the 'Anthropocene' arise as a cumulative impact from the influence of numerous natural and human stressors operating at multiple spatial and temporal scales. However, the research requirement for data on impacts at multiple scales, and at sufficiently high spatial and temporal resolution to determine reach-level effect, largely prevented such studies until recent improvements in digital technologies and data availability. A meta-analysis of recent cumulative impact studies indicates that the analytical component is still overwhelmingly interpretative, with cause-and-effect reasoning based largely on temporal synchronicity and spatial proximity, whereas our conceptual understanding of adjustment processes is far more nuanced. We propose, instead, that studies of cumulative impact should be underpinned by an analytical model of cause and effect, partly to test and enhance our predictive capabilities and allow scenario setting, but also to learn about the relative sensitivities involved in different parts of the model and thus to prioritize future research endeavours. Our requirements are that the model should be inherently designed to detect reach-level changes over Anthropocene timescales, be capable of integrating co-existing and hierarchical human and natural pressures on fluvial systems, be able to accommodate time-lagged effects and upstream-downstream connectivity, and be based on an explicit conceptual model that can be refined as our process understanding improves. Bayesian Belief Networks (BBNs) offer some potential in this regard and are becoming an increasingly popular option for dealing with complex, multi-scalar relationships in ecology and other environmental sciences. BBNs consist of a conceptual model of nodes and edges (i.e., graph theory) that qualitatively describe the structure of causal relationships between chains of variables, and a quantitative expression of the relative strength of the hypothesized relationships, described by probability distributions. BBNs offer the flexibility of incorporating different variables taken at various scales from within the catchment (thus accommodating geographical and historical differences in climate and human occupation), can be implemented even when there is some missing data, and can be rapidly optimised to improve data fit by modifying individual parts of the internal probability distributions. They are particularly well-suited to hierarchical cause and effect structuring because data uncertainties are inherently 'internalised' in the development of the model's structure, thus potentially mediating the overall error in a complex chain of relationships. We detail tests in progress to develop models for channel width and depth changes for the main stem of the Santa Clara River, which drains a 4,200 km2 catchment in coastal Southern California.

Fabrication of free-standing hierarchical carbon nanofiber/graphene oxide/polyaniline films for supercapacitors.

PubMed

Xu, Dongdong; Xu, Qun; Wang, Kaixi; Chen, Jun; Chen, Zhimin

2014-01-08

A hierarchical high-performance electrode with nanoacanthine-style polyaniline (PANI) deposited onto a carbon nanofiber/graphene oxide (CNF/GO) template was successfully prepared via an in situ polymerization process. The morphology analysis shows that introducing one-dimensional (1D) CNF could significantly decrease/inhibit the staking of laminated GO to form an open-porous CNF/GO architecture. Followed with in situ facial deposition of PANI, the as-synthesized PANI modified CNF/GO exhibits three-dimensional (3D) hierarchical layered nanoarchitecture, which favors the diffusion of the electrolyte ions into the inner region of active materials. The hierarchical free-standing electrodes were directly fabricated into sandwich structured supercapacitors using 1 M H2SO4 as the electrolyte showing a significant specific capacitance of 450.2 F/g at the voltage scan rate of 10 mV/s. The electrochemical properties of the hierarchical structure can be further improved by a reduction procedure of GO before the deposition of PANI.

Simultaneous formation of multiscale hierarchical surface morphologies through sequential wrinkling and folding

NASA Astrophysics Data System (ADS)

Wang, Yu; Sun, Qingyang; Xiao, Jianliang

2018-02-01

Highly organized hierarchical surface morphologies possess various intriguing properties that could find important potential applications. In this paper, we demonstrate a facile approach to simultaneously form multiscale hierarchical surface morphologies through sequential wrinkling. This method combines surface wrinkling induced by thermal expansion and mechanical strain on a three-layer structure composed of an aluminum film, a hard Polydimethylsiloxane (PDMS) film, and a soft PDMS substrate. Deposition of the aluminum film on hard PDMS induces biaxial wrinkling due to thermal expansion mismatch, and recovering the prestrain in the soft PDMS substrate leads to wrinkling of the hard PDMS film. In total, three orders of wrinkling patterns form in this process, with wavelength and amplitude spanning 3 orders of magnitude in length scale. By increasing the prestrain in the soft PDMS substrate, a hierarchical wrinkling-folding structure was also obtained. This approach can be easily extended to other thin films for fabrication of multiscale hierarchical surface morphologies with potential applications in different areas.

Tubular structured hierarchical mesoporous titania material derived from natural cellulosic substances and application as photocatalyst for degradation of methylene blue

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

Huang, Haiqing; Liu, Xiaoyan; Huang, Jianguo, E-mail: jghuang@zju.edu.cn

Graphical abstract: Bio-inspired, tubular structured hierarchical mesoporous titania material with high photocatalytic activity under UV light was fabricated employing natural cellulosic substance (cotton) as hard template and cetyltrimethylammonium bromide (CTAB) surfactant as soft template using a one-pot sol-gel method. Highlights: {yields} Tubular structured mesoporous titania material was fabricated by sol-gel method. {yields} The titania material faithfully recorded the hierarchical structure of the template substrate (cotton). {yields} The titania material exhibited high photocatalytic activity in decomposition of methylene blue. -- Abstract: Bio-inspired, tubular structured hierarchical mesoporous titania material was designed and fabricated employing natural cellulosic substance (cotton) as hard template andmore » cetyltrimethylammonium bromide (CTAB) surfactant as soft template by one-pot sol-gel method. The tubular structured hierarchical mesoporous titania material processes large specific surface area (40.23 m{sup 2}/g) and shows high photocatalytic activity in the photodegradation of methylene blue under UV light irradiation.« less

Band-gap analysis of a novel lattice with a hierarchical periodicity using the spectral element method

NASA Astrophysics Data System (ADS)

Wu, Zhijing; Li, Fengming; Zhang, Chuanzeng

2018-05-01

Inspired by the hierarchical structures of butterfly wing surfaces, a new kind of lattice structures with a two-order hierarchical periodicity is proposed and designed, and the band-gap properties are investigated by the spectral element method (SEM). The equations of motion of the whole structure are established considering the macro and micro periodicities of the system. The efficiency of the SEM is exploited in the modeling process and validated by comparing the results with that of the finite element method (FEM). Based on the highly accurate results in the frequency domain, the dynamic behaviors of the proposed two-order hierarchical structures are analyzed. An original and interesting finding is the existence of the distinct macro and micro stop-bands in the given frequency domain. The mechanisms for these two types of band-gaps are also explored. Finally, the relations between the hierarchical periodicities and the different types of the stop-bands are investigated by analyzing the parametrical influences.

Fabrication of hierarchical porous ZnO/NiO hollow microspheres for adsorptive removal of Congo red

NASA Astrophysics Data System (ADS)

Lei, Chunsheng; Pi, Meng; Cheng, Bei; Jiang, Chuanjia; Qin, Jiaqian

2018-03-01

Hierarchical porous zinc oxide (ZnO)/nickel(II) oxide (NiO) hollow microspheres were fabricated by a facile hydrothermal approach and subsequent calcination process. The synthesized samples were used as adsorbent for removing Congo red (CR), a commercial azo dye. The synthesized hierarchical porous ZnO/NiO composites exhibit a superior adsorption capacity for CR (518 mg/g), compared with pure NiO (397 mg/g) and ZnO (304 mg/g). The high CR adsorption capacity of ZnO/NiO composites was associated with its hierarchical porous hollow structures and large specific surface area (130 m2/g), which provide a large quantity of active sites for CR molecules. The adsorption kinetics data were perfectly fitted to a pseudo-second-order model. The isotherms were accurately described by the Langmuir model. The results suggest that the as-prepared hierarchical porous ZnO/NiO composites are a highly efficient adsorbent for treating organic dye-impacted wastewater.

Conceptual Chemical Process Design for Sustainability.

EPA Science Inventory

This chapter examines the sustainable design of chemical processes, with a focus on conceptual design, hierarchical and short-cut methods, and analyses of process sustainability for alternatives. The chapter describes a methodology for incorporating process sustainability analyse...

General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.

PubMed

Reis, Matthias; Kromer, Justus A; Klipp, Edda

2018-01-20

Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour.

PubMed

Zhang, Y; Paris, O; Terrill, N J; Gupta, H S

2016-05-23

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

Dynamics of Gas Exchange through the Fractal Architecture of the Human Lung, Modeled as an Exactly Solvable Hierarchical Tree

NASA Astrophysics Data System (ADS)

Mayo, Michael; Pfeifer, Peter; Gheorghiu, Stefan

2008-03-01

The acinar airways lie at the periphery of the human lung and are responsible for the transfer of oxygen from air to the blood during respiration. This transfer occurs by the diffusion-reaction of oxygen over the irregular surface of the alveolar membranes lining the acinar airways. We present an exactly solvable diffusion-reaction model on a hierarchically branched tree, allowing a quantitative prediction of the oxygen current over the entire system of acinar airways responsible for the gas exchange. We discuss the effect of diffusional screening, which is strongly coupled to oxygen transport in the human lung. We show that the oxygen current is insensitive to a loss of permeability of the alveolar membranes over a wide range of permeabilities, similar to a ``constant-current source'' in an electric network. Such fault tolerance has been observed in other treatments of the gas exchange in the lung and is obtained here as a fully analytical result.

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.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

NASA Astrophysics Data System (ADS)

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-05-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

PubMed Central

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-01-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales. PMID:27211574

Analysis of genetic diversity in banana cultivars (Musa cvs.) from the South of Oman using AFLP markers and classification by phylogenetic, hierarchical clustering and principal component analyses*

PubMed Central

Opara, Umezuruike Linus; Jacobson, Dan; Al-Saady, Nadiya Abubakar

2010-01-01

Banana is an important crop grown in Oman and there is a dearth of information on its genetic diversity to assist in crop breeding and improvement programs. This study employed amplified fragment length polymorphism (AFLP) to investigate the genetic variation in local banana cultivars from the southern region of Oman. Using 12 primer combinations, a total of 1094 bands were scored, of which 1012 were polymorphic. Eighty-two unique markers were identified, which revealed the distinct separation of the seven cultivars. The results obtained show that AFLP can be used to differentiate the banana cultivars. Further classification by phylogenetic, hierarchical clustering and principal component analyses showed significant differences between the clusters found with molecular markers and those clusters created by previous studies using morphological analysis. Based on the analytical results, a consensus dendrogram of the banana cultivars is presented. PMID:20443211

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.

Large-Area Direct Laser-Shock Imprinting of a 3D Biomimic Hierarchical Metal Surface for Triboelectric Nanogenerators.

PubMed

Jin, Shengyu; Wang, Yixiu; Motlag, Maithilee; Gao, Shengjie; Xu, Jin; Nian, Qiong; Wu, Wenzhuo; Cheng, Gary J

2018-03-01

Ongoing efforts in triboelectric nanogenerators (TENGs) focus on enhancing power generation, but obstacles concerning the economical and cost-effective production of TENGs continue to prevail. Micro-/nanostructure engineering of polymer surfaces has been dominantly utilized for boosting the contact triboelectrification, with deposited metal electrodes for collecting the scavenged energy. Nevertheless, this state-of-the-art approach is limited by the vague potential for producing 3D hierarchical surface structures with conformable coverage of high-quality metal. Laser-shock imprinting (LSI) is emerging as a potentially scalable approach for directly surface patterning of a wide range of metals with 3D nanoscale structures by design, benefiting from the ultrahigh-strain-rate forming process. Here, a TENG device is demonstrated with LSI-processed biomimetic hierarchically structured metal electrodes for efficient harvesting of water-drop energy in the environment. Mimicking and transferring hierarchical microstructures from natural templates, such as leaves, into these water-TENG devices is effective regarding repelling water drops from the device surface, since surface hydrophobicity from these biomicrostructures maximizes the TENG output. Among various leaves' microstructures, hierarchical microstructures from dried bamboo leaves are preferable regarding maximizing power output, which is attributed to their unique structures, containing both dense nanostructures and microscale features, compared with other types of leaves. Also, the triboelectric output is significantly improved by closely mimicking the hydrophobic nature of the leaves in the LSI-processed metal surface after functionalizing it with low-surface-energy self-assembled-monolayers. The approach opens doors to new manufacturable TENG technologies for economically feasible and ecologically friendly production of functional devices with directly patterned 3D biomimic metallic surfaces in energy, electronics, and sensor applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A distributed, hierarchical and recurrent framework for reward-based choice

PubMed Central

Hunt, Laurence T.; Hayden, Benjamin Y.

2017-01-01

Many accounts of reward-based choice argue for distinct component processes that are serial and functionally localized. In this article, we argue for an alternative viewpoint, in which choices emerge from repeated computations that are distributed across many brain regions. We emphasize how several features of neuroanatomy may support the implementation of choice, including mutual inhibition in recurrent neural networks and the hierarchical organisation of timescales for information processing across the cortex. This account also suggests that certain correlates of value may be emergent rather than represented explicitly in the brain. PMID:28209978

TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

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

Chang, X; Mazur, T; Yang, D

Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformationmore » and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants from ViewRay Inc. and Varian Medical System.« less

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.

PEDOT-PSS coated ZnO/C hierarchical porous nanorods as ultralong-life anode material for lithium ion batteries

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

Xu, Gui-Liang; Li, Yan; Ma, Tianyuan

2015-11-01

ZnO/C hierarchical porous nanorods were synthesized through one-pot wet-chemical reaction followed by thermal calcination. It was found that ZnO/C porous nanorods are composed of numerous nanograins, exhibiting a hierarchical micro/nanostructure. In-situ synchrotron high energy X-ray diffraction study revealed that ZnO/C hierarchical porous nanorods involve a two-step reversible lithiation mechanism during charge/discharge; and part of ZnO and Zn remains at the end of the first discharge and charge process, respectively, leading to a low coulombic efficiency in the initial few cycles. The electrochemical test demonstrated that the reversible capacity and the rate performance of ZnO/C hierarchical porous nanorods anode have beenmore » greatly improved by PEDOT-PSS coating, which could maintain a reversible capacity of 623.94 mA h g(-1) after 1500 cycles at 1 C. Its excellent high rate capability and long cycle stability were attributed to the high electronic conductivity of PEDOT-PSS coating layer and the hierarchical structures of ZnO/C porous nanorods. (C) 2015 Elsevier Ltd. All rights reserved.« less

Amyloid causes intermittent network disruptions in cognitively intact older subjects.

PubMed

Mueller, Susanne G

2018-05-16

Recent findings in AD models but also human patients suggest that amyloid can cause intermittent neuronal hyperactivity. The overall goal of this study was to use dynamic fMRI analysis combined with graph analysis to a) characterize the graph analytical signature of two types of intermittent hyperactivity (spike-like (spike) and hypersynchronus-like (synchron)) in simulated data and b) to attempt to identify one of these signatures in task-free fMRIs of cognitively intact subjects (CN) with or without increased brain amyloid. The toolbox simtb was used to generate 33 data sets with 2 short spike events, 33 with 2 synchron and 33 baseline data sets. A combination of sliding windows, hierarchical cluster analysis and graph analysis was used to characterize the spike and the synchron signature. Florbetapir-F18 PET and task-free 3 T fMRI was acquired in 49 CN (age = 70.7 ± 6.4). Processing the real data with the same approach as the simulated data identified phases whose graph analytical signature resembled that of the synchron signature in the simulated data. The duration of these phases was positively correlated with amyloid load (r = 0.42, p < 0.05) and negatively with memory performance (r = -0.43, p < 0.05). In conclusion, amyloid positivity is associated with intermittent hyperactivity that is caused by short phases of hypersynchronous activity. The negative association with memory performance suggests that these disturbances have the potential to interfere with cognitive processes and could lead to cognitive impairment if they become more frequent or more severe with increasing amyloid deposition.

IBiSA_Tools: A Computational Toolkit for Ion-Binding State Analysis in Molecular Dynamics Trajectories of Ion Channels.

PubMed

Kasahara, Kota; Kinoshita, Kengo

2016-01-01

Ion conduction mechanisms of ion channels are a long-standing conundrum. Although the molecular dynamics (MD) method has been extensively used to simulate ion conduction dynamics at the atomic level, analysis and interpretation of MD results are not straightforward due to complexity of the dynamics. In our previous reports, we proposed an analytical method called ion-binding state analysis to scrutinize and summarize ion conduction mechanisms by taking advantage of a variety of analytical protocols, e.g., the complex network analysis, sequence alignment, and hierarchical clustering. This approach effectively revealed the ion conduction mechanisms and their dependence on the conditions, i.e., ion concentration and membrane voltage. Here, we present an easy-to-use computational toolkit for ion-binding state analysis, called IBiSA_tools. This toolkit consists of a C++ program and a series of Python and R scripts. From the trajectory file of MD simulations and a structure file, users can generate several images and statistics of ion conduction processes. A complex network named ion-binding state graph is generated in a standard graph format (graph modeling language; GML), which can be visualized by standard network analyzers such as Cytoscape. As a tutorial, a trajectory of a 50 ns MD simulation of the Kv1.2 channel is also distributed with the toolkit. Users can trace the entire process of ion-binding state analysis step by step. The novel method for analysis of ion conduction mechanisms of ion channels can be easily used by means of IBiSA_tools. This software is distributed under an open source license at the following URL: http://www.ritsumei.ac.jp/~ktkshr/ibisa_tools/.

Transparent conductors based on microscale/nanoscale materials for high performance devices

NASA Astrophysics Data System (ADS)

Gao, Tongchuan

Transparent conductors are important as the top electrode for a variety of optoelectronic devices, including solar cells, light-emitting diodes (LEDs), at panel displays, and touch screens. Doped indium tin oxide (ITO) thin films are the predominant transparent conductor material. However, ITO thin films are brittle, making them unsuitable for the emerging flexible devices, and suffer from high material and processing cost. In my thesis, we developed a variety of transparent conductors toward a performance comparable with or superior to ITO thin films, with lower cost and potential for scalable manufacturing. Metal nanomesh (NM), hierarchical graphene/metal microgrid (MG), and hierarchical metal NM/MG materials were investigated. Simulation methods were used as a powerful tool to predict the transparency and sheet resistance of the transparent conductors by solving Maxwell's equations and Poisson's equation. Affordable and scalable fabrication processes were developed thereafter. Transparent conductors with over 90% transparency and less than 10 O/square sheet resistance were successfully fabricated on both rigid and flexible substrates. Durability tests, such as bending, heating and tape tests, were carried out to evaluate the robustness of the samples. Haze factor, which characterizes how blurry a transparent conductor appears, was also studied in-depth using analytical calculation and numerical simulation. We demonstrated a tunable haze factor for metal NM transparent conductors and analyzed the principle for tuning the haze factor. Plasmonic effects, excited by some transparent conductors, can lead to enhanced performance in photovoltaic devices. We systematically studied the effect of incorporating metal NM into ultrathin film silicon solar cells using numerical simulation, with the aid of optimization algorithms to reduce the optimization time. Mechanisms contributing to the enhanced performance were then identified and analyzed. Over 72% enhancement in short-circuit current-density was demonstrated by the optimal solar cell compared with 300-nm-thick Si solar cell with antireflection coating and silver back reflector.

Regional landslide hazard assesment for Kulon Progo Area, Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Karnawati, D.

2009-12-01

Karanganyar region is situated in a dynamic volcanic region in Java Island, where rain-induced landslides are frequent and widespread. Shallow-rapid earth slides triggered by heavy rainfall are the most common landslide type occurring on the steep slope and had resulted in major casualties, whilst deep soil creeping is more prominant on the gentle slope which creat a lot of damages on the houses and infrastructure. A landslide hazard assessment had been conducted to support the landslide mitigation program in this region. Such assessment was carried out by applying a semi qualitative approach (Analytical Hierarchical Process) where a weighting system was applied to assess the level of importance of each controlling parameter as suggested by Saaty (1980). Existing conditions of each controlling parameters were also assessed based on relative hierarchical system by applying scoring. Geographical Information System was used as a tool in such analysis and mapping process. The isohyet map was also prepared from statistical and spatial analyses on rain fall data. Finally, two different scenarios of landslide hazard maps were established, i.e. the scenario without any rainfall (Scenario 1) and with the reainfall (Scenario 2). It was found that the most susceptible zone of landslide was localised on the steep slope (with the inclination beyond 45o ) of jointed andesitic breccia, which was covered by thinck silty clay and situated close to the stream zone (Scenario 1). However from the hazard map and analysis on scenario 2, it can be identified that the susceptible zone expanded larger due to the rainfall, covering most region of the west-slope area of Lawu Volcano. Therefore, it can be concluded that the rainfall intensity is very crucial to induce the landslide not only in the most susceptible zone, but also in the larger area which also include the less susceptbile zone. This findings is also crucial to support the development of landslide spatial-early-warning system in the region.

The hierarchical expert tuning of PID controllers using tools of soft computing.

PubMed

Karray, F; Gueaieb, W; Al-Sharhan, S

2002-01-01

We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

USGS Publications Warehouse

Fiske, Ian J.; Chandler, Richard B.

2011-01-01

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

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.

Broca's area processes the hierarchical organization of observed action

PubMed Central

Wakita, Masumi

2014-01-01

Broca's area has been suggested as the area responsible for the domain-general hierarchical processing of language and music. Although meaningful action shares a common hierarchical structure with language and music, the role of Broca's area in this domain remains controversial. To address the involvement of Broca's area in the processing action hierarchy, the activation of Broca's area was measured using near-infrared spectroscopy. Measurements were taken while participants watched silent movies that featured hand movements playing familiar and unfamiliar melodies. The unfamiliar melodies were reversed versions of the familiar melodies. Additionally, to investigate the effect of a motor experience on the activation of Broca's area, the participants were divided into well-trained and less-trained groups. The results showed that Broca's area in the well-trained participants demonstrated a significantly larger activation in response to the hand motion when an unfamiliar melody was played than when a familiar melody was played. However, Broca's area in the less-trained participants did not show a contrast between conditions despite identical abilities of the two participant groups to identify the melodies by watching key pressing actions. These results are consistent with previous findings that Broca's area exhibits increased activation in response to grammatically violated sentences and musically deviated chord progressions as well as the finding that this region does not represent the processing of grammatical structure in less-proficient foreign language speakers. Thus, the current study suggests that Broca's area represents action hierarchy and that sufficiently long motor training is necessary for it to become sensitive to motor syntax. Therefore, the notion that hierarchical processing in Broca's area is a common function shared between language and music may help to explain the role of Broca's area in action perception. PMID:24478668

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…

The Role of Prototype Learning in Hierarchical Models of Vision

ERIC Educational Resources Information Center

Thomure, Michael David

2014-01-01

I conduct a study of learning in HMAX-like models, which are hierarchical models of visual processing in biological vision systems. Such models compute a new representation for an image based on the similarity of image sub-parts to a number of specific patterns, called prototypes. Despite being a central piece of the overall model, the issue of…

Hierarchical 3D ordered meso-/macroporous metal-organic framework produced through a facile template-free self-assembly

NASA Astrophysics Data System (ADS)

Yang, Xiaoli; Wu, Suilan; Wang, Panhao; Yang, Lin

2018-02-01

The synthesis of well-ordered hierarchical metal-organic frameworks (MOFs) in an efficient manner is a great challenge. Here, a 3D regular ordered meso-/macroporous MOF of Cu-TATAB (referred to as MM-MOF) was synthesized through a facile template-free self-assembly process with pore sizes of 31 nm and 119 nm.

A unique patterned diamond stamp for a periodically hierarchical nanoarray structure.

PubMed

Wang, Yi; Shen, Yanting; Xu, Weiqing; Xu, Shuping; Li, Hongdong

2016-09-23

A diamond stamp with a hierarchical pattern was designed for the direct preparation of a periodic nanoarray structure, which was prepared by the reactive ion etching technique with a hierarchical ultrathin alumina membrane (HUTAM) as a mask. The optimal etching conditions for fabricating the diamond stamp were discussed in order to realize a vertical nanopore structure, avoiding structural damage from lateral etching. By using this diamond stamp, a polymer film with the desired hierarchical nanorod array structure can be obtained easily via the simple stamping process, which greatly simplifies the processing procedure. More importantly, the stamp is reusable because of its super-hardness, which ensures the reproducibility of the nanorod array pattern. Another merit is that the smooth surface of the etched diamond can avoid the use of a release agent. Our results prove that this hard stamp can be used for quick preparation of an elaborate periodic nanoarray structure. This study is significant in that it solves the problems of high cost and easy damage of stamps in nanoimprint lithography, and it might inspire more sophisticated applications of such an ordered structure in nanoplasmonics, biochemical sensing and nanophotonic devices.

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

PubMed

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

Alkali-corrosion synthesis and excellent DSSC performance of novel jujube-like hierarchical TiO2 microspheres

NASA Astrophysics Data System (ADS)

Xiao, Jiajia; Li, Po; Wen, Xiaogang

2018-04-01

Novel jujube-like hierarchical TiO2 microspheres (HTMs) were synthesized by an alkali-corrosion process of titanium phosphate (Ti2O3(H2PO4)2 · 2H2O) microspheres. The hierarchical titanium phosphate microsphere (HTPM) intermediates consisting of nanoflakes with a thickness of 20 nm were firstly prepared by a facile hydrothermal method. After reacting with diluted NaOH at low temperature and atmospheric pressure, followed by subsequent acid washing and a calcination process, the HTPM intermediates were transformed to TiO2 with the microsphere morphology well retained, while the nanoflakes became porous, and some new nanowires were formed between the nanoflakes. Finally, HTMs consisting of porous nanoflakes and nanowires were obtained. The possible growth mechanisms of HTPMs and HTMs are discussed. The HTMs demonstrate high specific surface area and excellent light-scattering ability. The performance of the dye sensitized solar cells (DSSCs) of the HTMs synthesized under different conditions is studied, and a total conversion efficiency of up to 8.93% was obtained. The improved DSSC performance was attributed to the enhanced dye loading, light-scattering, and charge transporting ability of the HTMs with a unique hierarchical nanostructure.

Alkali-corrosion synthesis and excellent DSSC performance of novel jujube-like hierarchical TiO2 microspheres.

PubMed

Xiao, Jiajia; Li, Po; Wen, Xiaogang

2018-04-27

Novel jujube-like hierarchical TiO 2 microspheres (HTMs) were synthesized by an alkali-corrosion process of titanium phosphate (Ti 2 O 3 (H 2 PO 4 ) 2  · 2H 2 O) microspheres. The hierarchical titanium phosphate microsphere (HTPM) intermediates consisting of nanoflakes with a thickness of 20 nm were firstly prepared by a facile hydrothermal method. After reacting with diluted NaOH at low temperature and atmospheric pressure, followed by subsequent acid washing and a calcination process, the HTPM intermediates were transformed to TiO 2 with the microsphere morphology well retained, while the nanoflakes became porous, and some new nanowires were formed between the nanoflakes. Finally, HTMs consisting of porous nanoflakes and nanowires were obtained. The possible growth mechanisms of HTPMs and HTMs are discussed. The HTMs demonstrate high specific surface area and excellent light-scattering ability. The performance of the dye sensitized solar cells (DSSCs) of the HTMs synthesized under different conditions is studied, and a total conversion efficiency of up to 8.93% was obtained. The improved DSSC performance was attributed to the enhanced dye loading, light-scattering, and charge transporting ability of the HTMs with a unique hierarchical nanostructure.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Discovering, Exploring, and Mapping Spatiotemporal Patterns Across Heterogenous Space-Time Data

NASA Astrophysics Data System (ADS)

Morton, A.; Stewart, R.; Held, E.; Piburn, J.; Allen, M. R.; McManamay, R.; Sanyal, J.; Sorokine, A.; Bhaduri, B. L.

2017-12-01

Spatiotemporal (ST) analytics applied to major spatio-temporal data sources from major vendors such as USGS, NOAA, World Bank and World Health Organization have tremendous value in shedding light on the evolution of physical, cultural, and geopolitical landscapes on a local and global level. Especially powerful is the integration of these physical and cultural datasets across multiple and disparate formats, facilitating new interdisciplinary analytics and insights. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, changing attributes, and content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at the Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 16000+ attributes covering 200+ countries for over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We report on these advances, provide an illustrative case study, and inform how others may freely access the tool.

New insight in magnetic saturation behavior of nickel hierarchical structures

NASA Astrophysics Data System (ADS)

Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng

2017-09-01

It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.

Fabrication of malachite with a hierarchical sphere-like architecture.

PubMed

Xu, Jiasheng; Xue, Dongfeng

2005-09-15

Malachite (Cu2(OH)2CO3) with a hierarchical sphere-like architecture has been successfully synthesized via a simple and mild hydrothermal route in the absence of any external inorganic additives or organic structure-directing templates. Powder X-ray diffraction, scanning electron microscopy, and Fourier transmission infrared spectrometry are used to characterize various properties of the obtained malachite samples. The hierarchical malachite particles are uniform spheres with a diameter of 10-20 microm, which are comprised of numerous two-dimensional microplatelets paralleling the sphere surface. The initial concentration of reagents, the hydrothermal reaction time, and temperature are important factors which dominantly affect the evolution of crystal morphologies. The growth of the hierarchical architecture is believed to be a layer-by-layer growth process. Further, copper oxide with the similar morphology can be easily obtained from the as-prepared malachite.

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.

The right inferior frontal gyrus processes nested non-local dependencies in music.

PubMed

Cheung, Vincent K M; Meyer, Lars; Friederici, Angela D; Koelsch, Stefan

2018-02-28

Complex auditory sequences known as music have often been described as hierarchically structured. This permits the existence of non-local dependencies, which relate elements of a sequence beyond their temporal sequential order. Previous studies in music have reported differential activity in the inferior frontal gyrus (IFG) when comparing regular and irregular chord-transitions based on theories in Western tonal harmony. However, it is unclear if the observed activity reflects the interpretation of hierarchical structure as the effects are confounded by local irregularity. Using functional magnetic resonance imaging (fMRI), we found that violations to non-local dependencies in nested sequences of three-tone musical motifs in musicians elicited increased activity in the right IFG. This is in contrast to similar studies in language which typically report the left IFG in processing grammatical syntax. Effects of increasing auditory working demands are moreover reflected by distributed activity in frontal and parietal regions. Our study therefore demonstrates the role of the right IFG in processing non-local dependencies in music, and suggests that hierarchical processing in different cognitive domains relies on similar mechanisms that are subserved by domain-selective neuronal subpopulations.

Architecture of the parallel hierarchical network for fast image recognition

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule

2016-09-01

Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.

Neural basis of hierarchical visual form processing of Japanese Kanji characters.

PubMed

Higuchi, Hiroki; Moriguchi, Yoshiya; Murakami, Hiroki; Katsunuma, Ruri; Mishima, Kazuo; Uno, Akira

2015-12-01

We investigated the neural processing of reading Japanese Kanji characters, which involves unique hierarchical visual processing, including the recognition of visual components specific to Kanji, such as "radicals." We performed functional MRI to measure brain activity in response to hierarchical visual stimuli containing (1) real Kanji characters (complete structure with semantic information), (2) pseudo Kanji characters (subcomponents without complete character structure), (3) artificial characters (character fragments), and (4) checkerboard (simple photic stimuli). As we expected, the peaks of the activation in response to different stimulus types were aligned within the left occipitotemporal visual region along the posterior-anterior axis in order of the structural complexity of the stimuli, from fragments (3) to complete characters (1). Moreover, only the real Kanji characters produced functional connectivity between the left inferotemporal area and the language area (left inferior frontal triangularis), while pseudo Kanji characters induced connectivity between the left inferotemporal area and the bilateral cerebellum and left putamen. Visual processing of Japanese Kanji takes place in the left occipitotemporal cortex, with a clear hierarchy within the region such that the neural activation differentiates the elements in Kanji characters' fragments, subcomponents, and semantics, with different patterns of connectivity to remote regions among the elements.

Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

PubMed

Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

2000-03-01

Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

Hierarchical Matching and Regression with Application to Photometric Redshift Estimation

NASA Astrophysics Data System (ADS)

Murtagh, Fionn

2017-06-01

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

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

PubMed

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

2018-01-01

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

An effective hierarchical model for the biomolecular covalent bond: an approach integrating artificial chemistry and an actual terrestrial life system.

PubMed

Oohashi, Tsutomu; Ueno, Osamu; Maekawa, Tadao; Kawai, Norie; Nishina, Emi; Honda, Manabu

2009-01-01

Under the AChem paradigm and the programmed self-decomposition (PSD) model, we propose a hierarchical model for the biomolecular covalent bond (HBCB model). This model assumes that terrestrial organisms arrange their biomolecules in a hierarchical structure according to the energy strength of their covalent bonds. It also assumes that they have evolutionarily selected the PSD mechanism of turning biological polymers (BPs) into biological monomers (BMs) as an efficient biomolecular recycling strategy We have examined the validity and effectiveness of the HBCB model by coordinating two complementary approaches: biological experiments using existent terrestrial life, and simulation experiments using an AChem system. Biological experiments have shown that terrestrial life possesses a PSD mechanism as an endergonic, genetically regulated process and that hydrolysis, which decomposes a BP into BMs, is one of the main processes of such a mechanism. In simulation experiments, we compared different virtual self-decomposition processes. The virtual species in which the self-decomposition process mainly involved covalent bond cleavage from a BP to BMs showed evolutionary superiority over other species in which the self-decomposition process involved cleavage from BP to classes lower than BM. These converging findings strongly support the existence of PSD and the validity and effectiveness of the HBCB model.

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.

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.

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.

Hierarchical coarse-graining model for photosystem II including electron and excitation-energy transfer processes.

PubMed

Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi

2014-03-01

We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comparative analysis of global and local processing of hierarchical visual stimuli in young children (Homo sapiens) and monkeys (Cebus apella).

PubMed

De Lillo, Carlo; Spinozzi, Giovanna; Truppa, Valentina; Naylor, Donna M

2005-05-01

Results obtained with preschool children (Homo sapiens) were compared with results previously obtained from capuchin monkeys (Cebus apella) in matching-to-sample tasks featuring hierarchical visual stimuli. In Experiment 1, monkeys, in contrast with children, showed an advantage in matching the stimuli on the basis of their local features. These results were replicated in a 2nd experiment in which control trials enabled the authors to rule out that children used spurious cues to solve the matching task. In a 3rd experiment featuring conditions in which the density of the stimuli was manipulated, monkeys' accuracy in the processing of the global shape of the stimuli was negatively affected by the separation of the local elements, whereas children's performance was robust across testing conditions. Children's response latencies revealed a global precedence in the 2nd and 3rd experiments. These results show differences in the processing of hierarchical stimuli by humans and monkeys that emerge early during childhood. 2005 APA, all rights reserved

A hierarchical model of the evolution of human brain specializations

PubMed Central

Barrett, H. Clark

2012-01-01

The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised. PMID:22723350

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

PubMed Central

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

Hydrothermal synthesis and photoluminescent properties of hierarchical GdPO4·H2O:Ln3+ (Ln3+ = Eu3+, Ce3+, Tb3+) flower-like clusters

NASA Astrophysics Data System (ADS)

Amurisana, Bao.; Zhiqiang, Song.; Haschaolu, O.; Yi, Chen; Tegus, O.

2018-02-01

3D hierarchical GdPO4·H2O:Ln3+ (Ln3+ = Eu3+, Ce3+, Tb3+) flower clusters were successfully prepared on glass slide substrate by a simple, economical hydrothermal process with the assistance of disodium ethylenediaminetetraacetic acid (Na2H2L, where L4- = (CH2COO)2N(CH2)2N(CH2COO)24-). In this process, Na2H2L was used as both a chelating agent and a structure-director. The hierarchical flower clusters have an average diameter of 7-12 μm and are composed of well-aligned microrods. The influence of the molar ratio of Na2H2L/Gd3+ and reaction time on the morphology was systematically studied. A possible crystal growth and formation mechanism of hierarchical flower clusters is proposed based on the evolution of morphology as a function of reaction time. The self-assembled GdPO4·H2O:Ln3+ superstructures exhibit strong orange-red (Eu3+, 5D0 → 7F1), green (Tb3+, 5D4 → 7F5) and near ultraviolet emissions (Ce3+, 5d → 7F5/2) under ultraviolet excitation, respectively. This study may provide a new channel for building hierarchically superstructued oxide micro/nanomaterials with optical and new properties.

Novel hierarchical tantalum oxide-PDMS hybrid coating for medical implants: One pot synthesis, characterization and modulation of fibroblast proliferation.

PubMed

Tran, Phong A; Fox, Kate; Tran, Nhiem

2017-01-01

Surface properties such as morphology, roughness and charge density have a strong influence on the interaction of biomaterials and cells. Hierarchical materials with a combination of micron/submicron and nanoscale features for coating of medical implants could therefore have significant potential to modulate cellular responses and eventually improve the performance of the implants. In this study, we report a simple, one pot wet chemistry preparation of a hybrid coating system with hierarchical surface structures consisting of polydimethylsiloxane (PDMS) and tantalum oxide. Medical grade, amine functional PDMS was mixed with tantalum ethoxide which subsequently formed Ta 2 O 5 in situ through hydrolysis and condensation during coating process. The coatings were characterized by SEM, EDS, XPS, confocal scanning microscopy, contact angle measurement and in vitro cell culture. Varying PDMS and tantalum ethoxide ratios resulted in coatings of different surface textures ranging from smooth to submicro- and nano-structured. Strikingly, hierarchical surfaces containing both microscale (1-1.5μm) and nanoscale (86-163nm) particles were found on coatings synthesized with 20% and 40% (v/v) tantalum ethoxide. The coatings were similar in term of hydrophobicity but showed different surface roughness and chemical composition. Importantly, higher cell proliferation was observed on hybrid surface with hierarchical structures compared to pure PDMS or pure tantalum oxide. The coating process is simple, versatile, carried out under ambient condition and requires no special equipment. Copyright © 2016 Elsevier Inc. All rights reserved.

Convex clustering: an attractive alternative to hierarchical clustering.

PubMed

Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth

2015-05-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.

Fuzzy logic control and optimization system

DOEpatents

Lou, Xinsheng [West Hartford, CT

2012-04-17

A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Glycol-modified silanes: novel possibilities for the synthesis of hierarchically organized (hybrid) porous materials.

PubMed

Hartmann, Sarah; Brandhuber, Doris; Hüsing, Nicola

2007-09-01

The preparation of porous hierarchical architectures that have structural features spanning from the nanometer to micrometer and even larger dimensions and that exhibit certain functionalities is one of the new challenging frontiers in materials chemistry. The sol-gel process is one of the most promising synthesis routes toward such materials because it not only offers the possibility to incorporate organic functions into the porous host but also offers the possibility to deliberately tailor the pore structure. In this Account, the opportunities given by the application of novel diol-modified silanes are discussed for the synthesis of hierarchically organized inorganic and also inorganic-organic porous monoliths.

Fabrication of hierarchical feather-mimetic polymer nanofibres

NASA Astrophysics Data System (ADS)

Ouyang, Shenshen; Wang, Tao; Zhong, Longgang; Peng, Meiling; Yao, Juming; Wang, Sheng

2018-01-01

In this study, hierarchically feather-mimetic structures formed of poly(m-phenylene isophthalamide) (PMIA) nanofibres were prepared by electrospinning and subsequent crystallisation for superwettability applications. X-ray diffraction measurementsand scanning electron microscopy show that a feather-mimetic structure of crystallised nanoflakes was formed following a hydrothermal treatment process. The nanoflakes formed a nanosized fine texture on top of a coarser-textured membrane, which greatly improved the membrane roughness and yielded a hierarchical topography. After fluorination, the membrane exhibited superamphiphobicity, with surface contact angles of 151° and 136° for water and hexadecane, respectively. The method provides new insight for the design and development of functional bionic membranes based on PMIA.

Hierarchical Process Control of Chemical Vapor Infiltration.

DTIC Science & Technology

1995-05-31

convergence artificial neural network and used it to discover improved regions of the CVI processing parameter space; also, the Technology Assessment...identify in situ process sensors of considerable promise and as artificial neural network training pairs.

Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Fabrication of hierarchical porous nickel based metal-organic framework (Ni-MOF) constructed with nanosheets as novel pseudo-capacitive material for asymmetric supercapacitor.

PubMed

Du, Pengcheng; Dong, Yuman; Liu, Chang; Wei, Wenli; Liu, Dong; Liu, Peng

2018-05-15

Hierarchical porous nickel based metal-organic framework (Ni-MOF) constructed with nanosheets is fabricated by a facile hydrothermal process with the existence of trimesic acid and nickel ions. Various structures of Ni-MOFs can be obtained through adjusting the molar ratio of trimesic acid and nickel ion, the obtained hierarchical porous Ni-MOF exhibits optimal porous structure, which also possesses largest specific surface area. The hierarchical porous structure constructed with nanosheets can supply more active sites for electrochemical reactions to realize the excellent electrochemical properties, thus the hierarchical porous Ni-MOF reveals an outstanding specific capacitance of 1057 F/g at current density of 1 A/g, and delivers high specific capacitance of 649 F/g at current density of 30 A/g, indicating that it exhibits good rate capability of 63.4% even up to 30 A/g. The hierarchical porous Ni-MOF keeps 70% of its original value up to 2 500 charge-discharge cycles at the current density of 10 A/g. Furthermore, asymmetric supercapacitors (ASCs) were assembled based on hierarchical porous Ni-MOF and activated carbon (AC), the ASCs reveal specific capacitance of 87 F/g at current density of 0.5 A/g, and exhibit high energy density of 21.05 Wh/kg and power density of 6.03 kW/kg. Additionally, the tandem ASCs can light up a red LED. The hierarchical porous Ni-MOF exhibits promising applications in high performance supercapacitors. Copyright © 2018 Elsevier Inc. All rights reserved.

World Spatiotemporal Analytics and Mapping Project (wstamp): Discovering, Exploring, and Mapping Spatiotemporal Patterns across the World's Largest Open Soruce Data Sets

NASA Astrophysics Data System (ADS)

Stewart, R.; Piburn, J.; Sorokine, A.; Myers, A.; Moehl, J.; White, D.

2015-07-01

The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 10,000+ attributes covering over 200 nation states spanning over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We discuss the status of this work and report on major findings.

Design a New Strategy Based on Nanoparticle-Enhanced Chemiluminescence Sensor Array for Biothiols Discrimination

NASA Astrophysics Data System (ADS)

Shahrajabian, Maryam; Hormozi-Nezhad, M. Reza

2016-08-01

Array-based sensor is an interesting approach that suggests an alternative to expensive analytical methods. In this work, we introduce a novel, simple, and sensitive nanoparticle-based chemiluminescence (CL) sensor array for discrimination of biothiols (e.g., cysteine, glutathione and glutathione disulfide). The proposed CL sensor array is based on the CL efficiencies of four types of enhanced nanoparticle-based CL systems. The intensity of CL was altered to varying degrees upon interaction with biothiols, producing unique CL response patterns. These distinct CL response patterns were collected as “fingerprints” and were then identified through chemometric methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA). The developed array was able to successfully differentiate between cysteine, glutathione and glutathione disulfide in a wide concentration range. Moreover, it was applied to distinguish among the above analytes in human plasma.

Automation effects in a multiloop manual control system

NASA Technical Reports Server (NTRS)

Hess, R. A.; Mcnally, B. D.

1986-01-01

An experimental and analytical study was undertaken to investigate human interaction with a simple multiloop manual control system in which the human's activity was systematically varied by changing the level of automation. The system simulated was the longitudinal dynamics of a hovering helicopter. The automation-systems-stabilized vehicle responses from attitude to velocity to position and also provided for display automation in the form of a flight director. The control-loop structure resulting from the task definition can be considered a simple stereotype of a hierarchical control system. The experimental study was complemented by an analytical modeling effort which utilized simple crossover models of the human operator. It was shown that such models can be extended to the description of multiloop tasks involving preview and precognitive human operator behavior. The existence of time optimal manual control behavior was established for these tasks and the role which internal models may play in establishing human-machine performance was discussed.

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.

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

NASA Astrophysics Data System (ADS)

Chu, Fuqiang; Wu, Xiaomin

2016-05-01

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

Growth of hierarchical GaN nanowires for optoelectronic device applications

NASA Astrophysics Data System (ADS)

Raj, Rishabh; Vignesh, Veeramuthu; Ra, Yong-Ho; Nirmala, Rajkumar; Lee, Cheul-Ro; Navamathavan, Rangaswamy

2017-01-01

Gallium nitride nanostructures have been receiving considerable attention as building blocks for nanophotonic technologies due to their unique high aspect ratios, promising the realization of photonic and biological nanodevices such as blue light emitting diodes (LEDs), short-wavelength ultraviolet nanolasers, and nanofluidic biochemical sensors. We report on the growth of hierarchical GaN nanowires (NWs) by dynamically adjusting the growth parameters using the pulsed flow metal-organic chemical vapor deposition technique. We carried out two step growth processes to grow hierarchical GaN NWs. In the first step, the GaN NWs were grown at 950°C, and in the second, we suitably decreased the growth temperature to 630°C and 710°C to grow the hierarchical structures. The surface morphology and optical characterization of the grown GaN NWs were studied by field-emission scanning electron microscopy, high-resolution transmission electron microscopy, photoluminescence, and cathodoluminescence measurements. These kinds of hierarchical GaN NWs are promising for allowing flat band quantum structures that are shown to improve the efficiency of LEDs.

Selective hierarchical patterning of silicon nanostructures via soft nanostencil lithography

NASA Astrophysics Data System (ADS)

Du, Ke; Ding, Junjun; Wathuthanthri, Ishan; Choi, Chang-Hwan

2017-11-01

It is challenging to hierarchically pattern high-aspect-ratio nanostructures on microstructures using conventional lithographic techniques, where photoresist (PR) film is not able to uniformly cover on the microstructures as the aspect ratio increases. Such non-uniformity causes poor definition of nanopatterns over the microstructures. Nanostencil lithography can provide an alternative means to hierarchically construct nanostructures on microstructures via direct deposition or plasma etching through a free-standing nanoporous membrane. In this work, we demonstrate the multiscale hierarchical fabrication of high-aspect-ratio nanostructures on microstructures of silicon using a free-standing nanostencil, which is a nanoporous membrane consisting of metal (Cr), PR, and anti-reflective coating. The nanostencil membrane is used as a deposition mask to define Cr nanodot patterns on the predefined silicon microstructures. Then, deep reactive ion etching is used to hierarchically create nanostructures on the microstructures using the Cr nanodots as an etch mask. With simple modification of the main fabrication processes, high-aspect-ratio nanopillars are selectively defined only on top of the microstructures, on bottom, or on both top and bottom.

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.

Selective hierarchical patterning of silicon nanostructures via soft nanostencil lithography.

PubMed

Du, Ke; Ding, Junjun; Wathuthanthri, Ishan; Choi, Chang-Hwan

2017-11-17

It is challenging to hierarchically pattern high-aspect-ratio nanostructures on microstructures using conventional lithographic techniques, where photoresist (PR) film is not able to uniformly cover on the microstructures as the aspect ratio increases. Such non-uniformity causes poor definition of nanopatterns over the microstructures. Nanostencil lithography can provide an alternative means to hierarchically construct nanostructures on microstructures via direct deposition or plasma etching through a free-standing nanoporous membrane. In this work, we demonstrate the multiscale hierarchical fabrication of high-aspect-ratio nanostructures on microstructures of silicon using a free-standing nanostencil, which is a nanoporous membrane consisting of metal (Cr), PR, and anti-reflective coating. The nanostencil membrane is used as a deposition mask to define Cr nanodot patterns on the predefined silicon microstructures. Then, deep reactive ion etching is used to hierarchically create nanostructures on the microstructures using the Cr nanodots as an etch mask. With simple modification of the main fabrication processes, high-aspect-ratio nanopillars are selectively defined only on top of the microstructures, on bottom, or on both top and bottom.

Application of Bayesian inference to the study of hierarchical organization in self-organized complex adaptive systems

NASA Astrophysics Data System (ADS)

Knuth, K. H.

2001-05-01

We consider the application of Bayesian inference to the study of self-organized structures in complex adaptive systems. In particular, we examine the distribution of elements, agents, or processes in systems dominated by hierarchical structure. We demonstrate that results obtained by Caianiello [1] on Hierarchical Modular Systems (HMS) can be found by applying Jaynes' Principle of Group Invariance [2] to a few key assumptions about our knowledge of hierarchical organization. Subsequent application of the Principle of Maximum Entropy allows inferences to be made about specific systems. The utility of the Bayesian method is considered by examining both successes and failures of the hierarchical model. We discuss how Caianiello's original statements suffer from the Mind Projection Fallacy [3] and we restate his assumptions thus widening the applicability of the HMS model. The relationship between inference and statistical physics, described by Jaynes [4], is reiterated with the expectation that this realization will aid the field of complex systems research by moving away from often inappropriate direct application of statistical mechanics to a more encompassing inferential methodology.

Spine-like Nanostructured Carbon Interconnected by Graphene for High-performance Supercapacitors

NASA Astrophysics Data System (ADS)

Park, Sang-Hoon; Yoon, Seung-Beom; Kim, Hyun-Kyung; Han, Joong Tark; Park, Hae-Woong; Han, Joah; Yun, Seok-Min; Jeong, Han Gi; Roh, Kwang Chul; Kim, Kwang-Bum

2014-08-01

Recent studies on supercapacitors have focused on the development of hierarchical nanostructured carbons by combining two-dimensional graphene and other conductive sp2 carbons, which differ in dimensionality, to improve their electrochemical performance. Herein, we report a strategy for synthesizing a hierarchical graphene-based carbon material, which we shall refer to as spine-like nanostructured carbon, from a one-dimensional graphitic carbon nanofiber by controlling the local graphene/graphitic structure via an expanding process and a co-solvent exfoliation method. Spine-like nanostructured carbon has a unique hierarchical structure of partially exfoliated graphitic blocks interconnected by thin graphene sheets in the same manner as in the case of ligaments. Owing to the exposed graphene layers and interconnected sp2 carbon structure, this hierarchical nanostructured carbon possesses a large, electrochemically accessible surface area with high electrical conductivity and exhibits high electrochemical performance.

Spine-like nanostructured carbon interconnected by graphene for high-performance supercapacitors.

PubMed

Park, Sang-Hoon; Yoon, Seung-Beom; Kim, Hyun-Kyung; Han, Joong Tark; Park, Hae-Woong; Han, Joah; Yun, Seok-Min; Jeong, Han Gi; Roh, Kwang Chul; Kim, Kwang-Bum

2014-08-19

Recent studies on supercapacitors have focused on the development of hierarchical nanostructured carbons by combining two-dimensional graphene and other conductive sp(2) carbons, which differ in dimensionality, to improve their electrochemical performance. Herein, we report a strategy for synthesizing a hierarchical graphene-based carbon material, which we shall refer to as spine-like nanostructured carbon, from a one-dimensional graphitic carbon nanofiber by controlling the local graphene/graphitic structure via an expanding process and a co-solvent exfoliation method. Spine-like nanostructured carbon has a unique hierarchical structure of partially exfoliated graphitic blocks interconnected by thin graphene sheets in the same manner as in the case of ligaments. Owing to the exposed graphene layers and interconnected sp(2) carbon structure, this hierarchical nanostructured carbon possesses a large, electrochemically accessible surface area with high electrical conductivity and exhibits high electrochemical performance.

Spine-like Nanostructured Carbon Interconnected by Graphene for High-performance Supercapacitors

PubMed Central

Park, Sang-Hoon; Yoon, Seung-Beom; Kim, Hyun-Kyung; Han, Joong Tark; Park, Hae-Woong; Han, Joah; Yun, Seok-Min; Jeong, Han Gi; Roh, Kwang Chul; Kim, Kwang-Bum

2014-01-01

Recent studies on supercapacitors have focused on the development of hierarchical nanostructured carbons by combining two-dimensional graphene and other conductive sp2 carbons, which differ in dimensionality, to improve their electrochemical performance. Herein, we report a strategy for synthesizing a hierarchical graphene-based carbon material, which we shall refer to as spine-like nanostructured carbon, from a one-dimensional graphitic carbon nanofiber by controlling the local graphene/graphitic structure via an expanding process and a co-solvent exfoliation method. Spine-like nanostructured carbon has a unique hierarchical structure of partially exfoliated graphitic blocks interconnected by thin graphene sheets in the same manner as in the case of ligaments. Owing to the exposed graphene layers and interconnected sp2 carbon structure, this hierarchical nanostructured carbon possesses a large, electrochemically accessible surface area with high electrical conductivity and exhibits high electrochemical performance. PMID:25134517

Hierarchical Mesoporous Zinc-Nickel-Cobalt Ternary Oxide Nanowire Arrays on Nickel Foam as High-Performance Electrodes for Supercapacitors.

PubMed

Wu, Chun; Cai, Junjie; Zhang, Qiaobao; Zhou, Xiang; Zhu, Ying; Shen, Pei Kang; Zhang, Kaili

2015-12-09

Nickel foam supported hierarchical mesoporous Zn-Ni-Co ternary oxide (ZNCO) nanowire arrays are synthesized by a simple two-step approach including a hydrothermal method and subsequent calcination process and directly utilized for supercapacitive investigation for the first time. The nickel foam supported hierarchical mesoporous ZNCO nanowire arrays possess an ultrahigh specific capacitance value of 2481.8 F g(-1) at 1 A g(-1) and excellent rate capability of about 91.9% capacitance retention at 5 A g(-1). More importantly, an asymmetric supercapacitor with a high energy density (35.6 Wh kg(-1)) and remarkable cycle stability performance (94% capacitance retention over 3000 cycles) is assembled successfully by employing the ZNCO electrode as positive electrode and activated carbon as negative electrode. The remarkable electrochemical behaviors demonstrate that the nickel foam supported hierarchical mesoporous ZNCO nanowire array electrodes are highly desirable for application as advanced supercapacitor electrodes.

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

PubMed

Yu, Ziyi; Zheng, Yu; Parker, Richard M; Lan, Yang; Wu, Yuchao; Coulston, Roger J; Zhang, Jing; Scherman, Oren A; Abell, Chris

2016-04-06

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

Leading virtual teams: hierarchical leadership, structural supports, and shared team leadership.

PubMed

Hoch, Julia E; Kozlowski, Steve W J

2014-05-01

Using a field sample of 101 virtual teams, this research empirically evaluates the impact of traditional hierarchical leadership, structural supports, and shared team leadership on team performance. Building on Bell and Kozlowski's (2002) work, we expected structural supports and shared team leadership to be more, and hierarchical leadership to be less, strongly related to team performance when teams were more virtual in nature. As predicted, results from moderation analyses indicated that the extent to which teams were more virtual attenuated relations between hierarchical leadership and team performance but strengthened relations for structural supports and team performance. However, shared team leadership was significantly related to team performance regardless of the degree of virtuality. Results are discussed in terms of needed research extensions for understanding leadership processes in virtual teams and practical implications for leading virtual teams. (c) 2014 APA, all rights reserved.

Hierarchical MFMO Circuit Modules for an Energy-Efficient SDR DBF

NASA Astrophysics Data System (ADS)

Mar, Jeich; Kuo, Chi-Cheng; Wu, Shin-Ru; Lin, You-Rong

The hierarchical multi-function matrix operation (MFMO) circuit modules are designed using coordinate rotations digital computer (CORDIC) algorithm for realizing the intensive computation of matrix operations. The paper emphasizes that the designed hierarchical MFMO circuit modules can be used to develop a power-efficient software-defined radio (SDR) digital beamformer (DBF). The formulas of the processing time for the scalable MFMO circuit modules implemented in field programmable gate array (FPGA) are derived to allocate the proper logic resources for the hardware reconfiguration. The hierarchical MFMO circuit modules are scalable to the changing number of array branches employed for the SDR DBF to achieve the purpose of power saving. The efficient reuse of the common MFMO circuit modules in the SDR DBF can also lead to energy reduction. Finally, the power dissipation and reconfiguration function in the different modes of the SDR DBF are observed from the experiment results.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Metal hierarchical patterning by direct nanoimprint lithography

PubMed Central

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

2013-01-01

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

When mechanism matters: Bayesian forecasting using models of ecological diffusion

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

2017-01-01

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Epidemic spreading in a hierarchical social network.

PubMed

Grabowski, A; Kosiński, R A

2004-09-01

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

Aerial surveillance based on hierarchical object classification for ground target detection

NASA Astrophysics Data System (ADS)

Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

2015-03-01

Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

Oscillatory Critical Amplitudes in Hierarchical Models and the Harris Function of Branching Processes

NASA Astrophysics Data System (ADS)

Costin, Ovidiu; Giacomin, Giambattista

2013-02-01

Oscillatory critical amplitudes have been repeatedly observed in hierarchical models and, in the cases that have been taken into consideration, these oscillations are so small to be hardly detectable. Hierarchical models are tightly related to iteration of maps and, in fact, very similar phenomena have been repeatedly reported in many fields of mathematics, like combinatorial evaluations and discrete branching processes. It is precisely in the context of branching processes with bounded off-spring that T. Harris, in 1948, first set forth the possibility that the logarithm of the moment generating function of the rescaled population size, in the super-critical regime, does not grow near infinity as a power, but it has an oscillatory prefactor (the Harris function). These oscillations have been observed numerically only much later and, while the origin is clearly tied to the discrete character of the iteration, the amplitude size is not so well understood. The purpose of this note is to reconsider the issue for hierarchical models and in what is arguably the most elementary setting—the pinning model—that actually just boils down to iteration of polynomial maps (and, notably, quadratic maps). In this note we show that the oscillatory critical amplitude for pinning models and the Harris function coincide. Moreover we make explicit the link between these oscillatory functions and the geometry of the Julia set of the map, making thus rigorous and quantitative some ideas set forth in Derrida et al. (Commun. Math. Phys. 94:115-132, 1984).

Multi-Scale and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

PubMed

Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

2017-04-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy, and nearly a six-fold improvement over a commonly available network file system (NFS) approach even for relatively small file sets. Moreover, file access latency is lower than network attached storage.

Hierarchical and Well-Ordered Porous Copper for Liquid Transport Properties Control.

PubMed

Pham, Quang N; Shao, Bowen; Kim, Yongsung; Won, Yoonjin

2018-05-09

Liquid delivery through interconnected pore network is essential for various interfacial transport applications ranging from energy storage to evaporative cooling. The liquid transport performance in porous media can be significantly improved through the use of hierarchical morphology that leverages transport phenomena at different length scales. Traditional surface engineering techniques using chemical or thermal reactions often show nonuniform surface nanostructuring within three-dimensional pore network due to uncontrollable diffusion and reactivity in geometrically complex porous structures. Here, we demonstrate hierarchical architectures on the basis of crystalline copper inverse opals using an electrochemistry approach, which offers volumetric controllability of structural and surface properties within the complex porous metal. The electrochemical process sequentially combines subtractive and additive steps-electrochemical polishing and electrochemical oxidation-to improve surface wetting properties without sacrificing structural permeability. We report the transport performance of the hierarchical inverse opals by measuring the capillary-driven liquid rise. The capillary performance parameter of hierarchically engineered inverse opal ( K/ R eff = ∼5 × 10 -3 μm) is shown to be higher than that of a typical crystalline inverse opal ( K/ R eff = ∼1 × 10 -3 μm) owing to the enhancement in fluid permeable and hydrophilic pathways. The new surface engineering method presented in this work provides a rational approach in designing hierarchical porous copper for transport performance enhancements.

Results of an integrated structure-control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1988-01-01

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Catalyst-free "click" functionalization of polymer brushes preserves antifouling properties enabling detection in blood plasma.

PubMed

Parrillo, Viviana; de Los Santos Pereira, Andres; Riedel, Tomas; Rodriguez-Emmenegger, Cesar

2017-06-08

Progress in biosensors for clinical detection critically relies on modifications of the transducer surface to prevent non-specific adsorption from matrix components (i.e. antifouling) while supporting biomolecular recognition elements to capture the analyte. Such combination of properties presents a significant challenge. Hierarchically structured polymer brushes comprising an antifouling polymer bottom block and a functionalizable top block are proposed as a promising strategy to achieve this goal. We employed the catalyst-free strain-promoted alkyne-azide cycloaddition (SPAAC) "click" reaction to biofunctionalize antifouling polymer brushes without impairing their resistance to fouling. The functionalization was performed on the side chains along the top polymer block or only on the end-groups of the polymer brush. The immobilized amounts of bioreceptors (streptavidin followed by biotin-conjugated proteins) and the resistance to fouling from blood plasma of the surfaces obtained were evaluated via surface plasmon resonance. The end group functionalization approach resulted in very low immobilization of bioreceptor. On the other hand, the side group modification of a top polymer block led to immobilization of 83% of a monolayer of streptavidin. Following binding of a biotin-conjugated antibody (66 ng cm -2 ) the functionalized layer was able to reduce the fouling from undiluted human blood plasma by 89% in comparison with bare gold. Finally, the functionalized hierarchical polymer brushes were applied to the label-free detection of a model analyte in diluted human blood plasma, highlighting the potential for translation to medical applications. Copyright © 2017. Published by Elsevier B.V.

Possible Outcomes of Coplanar High-eccentricity Migration: Hot Jupiters, Close-in Super-Earths, and Counter-orbiting Planets

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

Xue, Yuxin; Masuda, Kento; Suto, Yasushi, E-mail: yuxin@utap.phys.s.u-tokyo.ac.jp

We investigate the formation of close-in planets in near-coplanar eccentric hierarchical triple systems via the secular interaction between an inner planet and an outer perturber (Coplanar High-eccentricity Migration; CHEM). We generalize the previous work on the analytical condition for successful CHEM for point masses interacting only through gravity by taking into account the finite mass effect of the inner planet. We find that efficient CHEM requires that the systems should have m {sub 1}≪m {sub 0} and m {sub 1} ≪ m {sub 2}. In addition to the gravity for point masses, we examine the importance of the short-range forces,more » and provide an analytical estimate of the migration timescale. We perform a series of numerical simulations in CHEM for systems consisting of a Sun-like central star, giant gas inner planet, and planetary outer perturber, including the short-range forces and stellar and planetary dissipative tides. We find that most of such systems end up with a tidal disruption; a small fraction of the systems produce prograde hot Jupiters (HJs), but no retrograde HJ. In addition, we extend CHEM to super-Earth mass range, and show that the formation of close-in super-Earths in prograde orbits is also possible. Finally, we carry out CHEM simulation for the observed hierarchical triple and counter-orbiting HJ systems. We find that CHEM can explain a part of the former systems, but it is generally very difficult to reproduce counter-orbiting HJ systems.« less

New Materials and Methods for Hierarchically Structured Tissue Scaffolds

DTIC Science & Technology

2005-01-01

to the fabrication of hierarchically structured scaffolds. In order to achieve this goal, photopolymerizable materials must be developed that are... photopolymerizable materials that can also be selectively chemically modified during the SL part building process. This paper provides an update on our work...which uses a laser to "write" patterns into a vat containing a photopolymerizable resin. The first step in performing SL is generating a computer

Hierarchical Porous Carbon Materials Derived from Sheep Manure for High-Capacity Supercapacitors.

PubMed

Zhang, Caiyun; Zhu, Xiaohong; Cao, Min; Li, Menglin; Li, Na; Lai, Liuqin; Zhu, Jiliang; Wei, Dacheng

2016-05-10

3 D capacitance: Hierarchical porous carbon-based electrode materials with a composite structure are prepared from a biomass waste by a facile carbonization and activation process without using any additional templates. Benefiting from the composite structure, the ions experience a variety of environments, which contribute significantly to the excellent electrochemical properties of supercapacitors. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Studies on the formation of hierarchical zeolite T aggregates with well-defined morphology in different template systems

NASA Astrophysics Data System (ADS)

Yin, Xiaoyan; Chu, Naibo; Lu, Xuewei; Li, Zhongfang; Guo, Hong

2016-01-01

In this paper, the disk-like and pumpkin-like hierarchical zeolite T aggregates consisted of primary nano-grains have been hydrothermally synthesized with and without the aid of the second template. The first template is used with tetramethylammonium hydroxide (TMAOH) and the second template is used with triethanolamine (TEA) or polyving akohol (PVA). A combination of characterization techniques, including XRD, SEM, TEM and N2 adsorption-desorption to examine the crystal crystallinity, morphology and surface properties of hierarchical zeolite T aggregates. In the single-template preparation process, the two-step varying-temperature treatment has been used to improve the meso-porosity of zeolite T aggregates. In the double-template preparation process, the amounts of PVA or TEA on the crystallinity, morphology and meso-porosity of zeolite T aggregates have been studied. It has been proved that the interstitial voids between the primary grains of aggregates are the origin of additional mesopores of samples. The micro- and meso-porosities of samples prepared with and without the second template have been contrasted in detail at last. In particular, the sample synthesized with the addition of PVA presents a hierarchical pore structure with the highest Sext value of 122 m2/g and Vmeso value of 0.255 cm3/g.

How Semantic Radicals in Chinese characters Facilitate Hierarchical Category-Based Induction.

PubMed

Wang, Xiaoxi; Ma, Xie; Tao, Yun; Tao, Yachen; Li, Hong

2018-04-03

Prior studies indicate that the semantic radical in Chinese characters contains category information that can support the independent retrieval of category information through the lexical network to the conceptual network. Inductive reasoning relies on category information; thus, semantic radicals may influence inductive reasoning. As most natural concepts are hierarchically structured in the human brain, this study examined how semantic radicals impact inductive reasoning for hierarchical concepts. The study used animal and plant nouns, organized in basic, superordinate, and subordinate levels; half had a semantic radical and half did not. Eighteen participants completed an inductive reasoning task. Behavioural and event-related potential (ERP) data were collected. The behavioural results showed that participants reacted faster and more accurately in the with-semantic-radical condition than in the without-semantic-radical condition. For the ERPs, differences between the conditions were found, and these differences lasted from the very early cognitive processing stage (i.e., the N1 time window) to the relatively late processing stages (i.e., the N400 and LPC time windows). Semantic radicals can help to distinguish the hierarchies earlier (in the N400 period) than characters without a semantic radical (in the LPC period). These results provide electrophysiological evidence that semantic radicals may improve sensitivity to distinguish between hierarchical concepts.

Processing prosodic structure by adults with language-based learning disability.

PubMed

Bahl, Megha; Plante, Elena; Gerken, LouAnn

2009-01-01

Two experiments investigated the ability of adults with a history of language-based learning disability (hLLD) and their normal language (NL) peers to learn prosodic patterns of a novel language. Participants were exposed to stimuli from an artificial language and tested on items that required generalization of the stress patterns and the hierarchical principles of stress assignment that could be inferred from the input. In Study 1, the NL group successfully generalized the patterns of stress heard during familiarization, but failed to show generalization of the hierarchical principles. The hLLD group performed at chance for both types of generalization items. In Study 2, the intensity of stress elements was increased. The performance of the NL group improved whereas the hLLD groups' performance decreased on both types of generalization items. The results indicate that NL adults are able to successfully abstract the complex hierarchical rules of stress if the prosodic cues are made sufficiently salient, but this same task is difficult for adults with hLLD. The reader will be able to understand: (1) the difference in the ability of hLLD and NL adults to process stress assignment in an implicit learning context and (2) that typical adults can abstract complex hierarchical rules of stress assignment when provided with strong cues.

Health sciences descriptors in the brazilian speech-language and hearing science.

PubMed

Campanatti-Ostiz, Heliane; Andrade, Claudia Regina Furquim de

2010-01-01

Terminology in Speech-Language and Hearing Science. To propose a specific thesaurus about the Speech-Language and Hearing Science, for the English, Portuguese and Spanish languages, based on the existing keywords available on the Health Sciences Descriptors (DeCS). Methodology was based on the pilot study developed by Campanatti-Ostiz and Andrade; that had as a purpose to verify the methodological viability for the creation of a Speech-Language and Hearing Science category in the DeCS. The scientific journals selected for analyses of the titles, abstracts and keywords of all scientific articles were those in the field of the Speech-Language and Hearing Science, indexed on the SciELO. 1. Recovery of the Descriptors in the English language (Medical Subject Headings--MeSH); 2. Recovery and hierarchic organization of the descriptors in the Portuguese language was done (DeCS). The obtained data was analyzed as follows: descriptive analyses and relative relevance analyses of the DeCS areas. Based on the first analyses, we decided to select all 761 descriptors, with all the hierarchic numbers, independently of their occurrence (occurrence number--ON), and based on the second analyses, we decided to propose to exclude the less relevant areas and the exclusive DeCS areas. The proposal was finished with a total of 1676 occurrences of DeCS descriptors, distributed in the following areas: Anatomy; Diseases; Analytical, Diagnostic and Therapeutic Techniques and Equipments; Psychiatry and Psychology; Phenomena and Processes; Health Care. The presented proposal of a thesaurus contains the specific terminology of the Brazilian Speech-Language and Hearing Sciences and reflects the descriptors of the published scientific production. Being the DeCS a trilingual vocabulary (Portuguese, English and Spanish), the present descriptors organization proposition can be used in these three languages, allowing greater cultural interchange between different nations.

Exploring electrolyte preference of vanadium nitride supercapacitor electrodes

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

Wang, Bo; Chen, Zhaohui; Lu, Gang

Highlights: • Hierarchical VN nanostructures were prepared on graphite foam. • Electrolyte preference of VN supercapacitor electrodes was explored. • VN showed better capacitive property in organic and alkaline electrolytes than LiCl. - Abstract: Vanadium nitride hierarchical nanostructures were prepared through an ammonia annealing procedure utilizing vanadium pentoxide nanostructures grown on graphite foam. The electrochemical properties of hierarchical vanadium nitride was tested in aqueous and organic electrolytes. As a result, the vanadium nitride showed better capacitive energy storage property in organic and alkaline electrolytes. This work provides insight into the charge storage process of vanadium nitride and our findings canmore » shed light on other transition metal nitride-based electrochemical energy storage systems.« less

Efficiency of the energy transfer in the FMO complex using hierarchical equations on Graphics Processing Units

NASA Astrophysics Data System (ADS)

Kramer, Tobias; Kreisbeck, Christoph; Rodriguez, Mirta; Hein, Birgit

2011-03-01

We study the efficiency of the energy transfer in the Fenna-Matthews-Olson complex solving the non-Markovian hierarchical equations (HE) proposed by Ishizaki and Fleming in 2009, which include properly the reorganization process. We compare it to the Markovian approach and find that the Markovian dynamics overestimates the thermalization rate, yielding higher efficiencies than the HE. Using the high-performance of graphics processing units (GPU) we cover a large range of reorganization energies and temperatures and find that initial quantum beatings are important for the energy distribution, but of limited influence to the efficiency. Our efficient GPU implementation of the HE allows us to calculate nonlinear spectra of the FMO complex. References see www.quantumdynamics.de

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

Compiling software for a hierarchical distributed processing system

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-12-31

Compiling software for a hierarchical distributed processing system including providing to one or more compiling nodes software to be compiled, wherein at least a portion of the software to be compiled is to be executed by one or more nodes; compiling, by the compiling node, the software; maintaining, by the compiling node, any compiled software to be executed on the compiling node; selecting, by the compiling node, one or more nodes in a next tier of the hierarchy of the distributed processing system in dependence upon whether any compiled software is for the selected node or the selected node's descendents; sending to the selected node only the compiled software to be executed by the selected node or selected node's descendent.

Competitive cluster growth in complex networks.

PubMed

Moreira, André A; Paula, Demétrius R; Costa Filho, Raimundo N; Andrade, José S

2006-06-01

In this work we propose an idealized model for competitive cluster growth in complex networks. Each cluster can be thought of as a fraction of a community that shares some common opinion. Our results show that the cluster size distribution depends on the particular choice for the topology of the network of contacts among the agents. As an application, we show that the cluster size distributions obtained when the growth process is performed on hierarchical networks, e.g., the Apollonian network, have a scaling form similar to what has been observed for the distribution of a number of votes in an electoral process. We suggest that this similarity may be due to the fact that social networks involved in the electoral process may also possess an underlining hierarchical structure.

Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

PubMed Central

Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

2012-01-01

Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT 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 six 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. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

Process-based principles for restoring river ecosystems

Treesearch

Timothy J. Beechie; David A. Sear; Julian D. Olden; George R. Pess; John M. Buffington; Hamish Moir; Philip Roni; Michael M. Pollock

2010-01-01

Process-based restoration aims to reestablish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes; floodplain and aquatic habitat...

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

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

PubMed

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

2017-08-01

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

Feature integration and object representations along the dorsal stream visual hierarchy

PubMed Central

Perry, Carolyn Jeane; Fallah, Mazyar

2014-01-01

The visual system is split into two processing streams: a ventral stream that receives color and form information and a dorsal stream that receives motion information. Each stream processes that information hierarchically, with each stage building upon the previous. In the ventral stream this leads to the formation of object representations that ultimately allow for object recognition regardless of changes in the surrounding environment. In the dorsal stream, this hierarchical processing has classically been thought to lead to the computation of complex motion in three dimensions. However, there is evidence to suggest that there is integration of both dorsal and ventral stream information into motion computation processes, giving rise to intermediate object representations, which facilitate object selection and decision making mechanisms in the dorsal stream. First we review the hierarchical processing of motion along the dorsal stream and the building up of object representations along the ventral stream. Then we discuss recent work on the integration of ventral and dorsal stream features that lead to intermediate object representations in the dorsal stream. Finally we propose a framework describing how and at what stage different features are integrated into dorsal visual stream object representations. Determining the integration of features along the dorsal stream is necessary to understand not only how the dorsal stream builds up an object representation but also which computations are performed on object representations instead of local features. PMID:25140147

Unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

USGS Publications Warehouse

Fiske, I.J.; Chandler, R.B.

2011-01-01

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientic questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mecha- nisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unied modeling in- terface. The R package unmarked provides such a unied modeling framework, including tools for data exploration, model tting, model criticism, post-hoc analysis, and model comparison.

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.

Bioinspired Diatomite Membrane with Selective Superwettability for Oil/Water Separation.

PubMed

Lo, Yu-Hsiang; Yang, Ching-Yu; Chang, Haw-Kai; Hung, Wei-Chen; Chen, Po-Yu

2017-05-03

Membranes with selective superwettability for oil/water separation have received significant attention during the past decades. Hierarchical structures and surface roughness are believed to improve the oil repellency and the stability of Cassie-Baxter state. Diatoms, unicellular photosynthetic algae, possess sophisticated skeletal shells (called frustules) which are made of hydrated silica. Motivated by the hierarchical micro- and nanoscale features of diatom, we fabricate a hierarchical diatomite membrane which consists of aligned micro-sized channels by the freeze casting process. The fine nano-porous structures of frustules are well preserved after the post sintering process. The bioinspired diatomite membrane performs both underwater superoleophobicity and superhydrophobicity under various oils. Additionally, we demonstrate the highly efficient oil/water separation capabililty of the membranes in various harsh environments. The water flux can be further adjusted by tuning the cooling rates. The eco-friendly and robust bioinspired membranes produced by the simple, cost-effective freeze casting method can be potentially applied for large scale and efficient oil/water separation.

Hierarchical self-assembly of a bow-shaped molecule bearing self-complementary hydrogen bonding sites into extended supramolecular assemblies.

PubMed

Ikeda, Masato; Nobori, Tadahito; Schmutz, Marc; Lehn, Jean-Marie

2005-01-07

The bow-shaped molecule 1 bearing a self-complementary DAAD-ADDA (D=donor A=acceptor) hydrogen-bonding array generates, in hydrocarbon solvents, highly ordered supramolecular sheet aggregates that subsequently give rise to gels by formation of an entangled network. The process of hierarchical self-assembly of compound 1 was investigated by the concentration and temperature dependence of UV-visible and (1)H NMR spectra, fluorescence spectra, and electron microscopy data. The temperature dependence of the UV-visible spectra indicates a highly cooperative process for the self-assembly of compound 1 in decaline. The electron micrograph of the decaline solution of compound 1 (1.0 mM) revealed supramolecular sheet aggregates forming an entangled network. The selected area electronic diffraction patterns of the supramolecular sheet aggregates were typical for single crystals, indicative of a highly ordered assembly. The results exemplify the generation, by hierarchical self-assembly, of highly organized supramolecular materials presenting novel collective properties at each level of organization.

Near-Infrared Trigged Stimulus-Responsive Photonic Crystals with Hierarchical Structures.

PubMed

Lu, Tao; Pan, Hui; Ma, Jun; Li, Yao; Zhu, Shenmin; Zhang, Di

2017-10-04

Stimuli-responsive photonic crystals (PCs) trigged by light would provide a novel intuitive and quantitative method for noninvasive detection. Inspired by the flame-detecting aptitude of fire beetles and the hierarchical photonic structures of butterfly wings, we herein developed near-infrared stimuli-responsive PCs through coupling photothermal Fe 3 O 4 nanoparticles with thermoresponsive poly(N-isopropylacrylamide) (PNIPAM), with hierarchical photonic structured butterfly wing scales as the template. The nanoparticles within 10 s transferred near-infrared radiation into heat that triggered the phase transition of PNIPAM; this almost immediately posed an anticipated effect on the PNIPAM refractive index and resulted in a composite spectrum change of ∼26 nm, leading to the direct visual readout. It is noteworthy that the whole process is durable and stable mainly owing to the chemical bonding formed between PNIPAM and the biotemplate. We envision that this biologically inspired approach could be utilized in a broad range of applications and would have a great impact on various monitoring processes and medical sensing.

Chitin/clay microspheres with hierarchical architecture for highly efficient removal of organic dyes.

PubMed

Xu, Rui; Mao, Jie; Peng, Na; Luo, Xiaogang; Chang, Chunyu

2018-05-15

Numerous adsorbents have been reported for efficient removal of dye from water, but the high cost raw materials and complicated fabrication process limit their practical applications. Herein, novel nanocomposite microspheres were fabricated from chitin and clay by a simple thermally induced sol-gel transition. Clay nanosheets were uniformly embedded in a nanofiber weaved chitin microsphere matrix, leading to their hierarchical architecture. Benefiting from this unique structure, microspheres could efficiently remove methylene blue (MB) through a spontaneous physic-sorption process which fit well with pseudo-second-order and Langmuir isotherm models. The maximal values of adsorption capability obtained by calculation and experiment were 152.2 and 156.7 mg g -1 , respectively. Chitin/clay microspheres (CCM2) could remove 99.99% MB from its aqueous solution (10 mg g -1 ) within 20 min. These findings provide insight into a new strategy for fabrication of dye adsorbents with hierarchical structure from low cost raw materials. Copyright © 2018 Elsevier Ltd. All rights reserved.

Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

PubMed

Anandakrishnan, Ramu; Scogland, Tom R W; Fenley, Andrew T; Gordon, John C; Feng, Wu-chun; Onufriev, Alexey V

2010-06-01

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed-up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson-Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multi-scale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Nonequilibrium dynamics of probe filaments in actin-myosin networks

NASA Astrophysics Data System (ADS)

Gladrow, J.; Broedersz, C. P.; Schmidt, C. F.

2017-08-01

Active dynamic processes of cells are largely driven by the cytoskeleton, a complex and adaptable semiflexible polymer network, motorized by mechanoenzymes. Small dimensions, confined geometries, and hierarchical structures make it challenging to probe dynamics and mechanical response of such networks. Embedded semiflexible probe polymers can serve as nonperturbing multiscale probes to detect force distributions in active polymer networks. We show here that motor-induced forces transmitted to the probe polymers are reflected in nonequilibrium bending dynamics, which we analyze in terms of spatial eigenmodes of an elastic beam under steady-state conditions. We demonstrate how these active forces induce correlations among the mode amplitudes, which furthermore break time-reversal symmetry. This leads to a breaking of detailed balance in this mode space. We derive analytical predictions for the magnitude of resulting probability currents in mode space in the white-noise limit of motor activity. We relate the structure of these currents to the spatial profile of motor-induced forces along the probe polymers and provide a general relation for observable currents on two-dimensional hyperplanes.

Detached breakwaters: communities' preferences for sustainable coastal protection.

PubMed

Saengsupavanich, Cherdvong

2013-01-30

Detached breakwaters have been implemented for coastal protection. As society evolves and community livelihood has been acknowledged as an ingredient for sustainable coastal development, the breakwaters must do more than just dissipate wave forces. Using detached breakwaters in Nakhon Si Thammarat province, Thailand as a case study, this research provides empirical proof of such a concept. Interviewing coastal communities who have lived with the breakwaters revealed numerous expectations. Since each community's requirement might be entangled with other functions and incur more costs, coastal engineers had to prioritize preferences. Seven breakwater scenarios were synthesized based on the interview results. For each scenario, the shoreline position was simulated using calibrated LITPACK software, the construction cost was estimated, and a set of illustrations was drawn in order to standardize respondents' perceptions. An analytical hierarchical process (AHP) was applied. The AHP results suggested that the preferred breakwater scenarios were those that promoted the existing ways of life. Other aspects such as construction practice, environmental, and social aspects should also be thoroughly considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

Factors that influence the efficiency of beef and dairy cattle recording system in Kenya: A SWOT-AHP analysis.

PubMed

Wasike, Chrilukovian B; Magothe, Thomas M; Kahi, Alexander K; Peters, Kurt J

2011-01-01

Animal recording in Kenya is characterised by erratic producer participation and high drop-out rates from the national recording scheme. This study evaluates factors influencing efficiency of beef and dairy cattle recording system. Factors influencing efficiency of animal identification and registration, pedigree and performance recording, and genetic evaluation and information utilisation were generated using qualitative and participatory methods. Pairwise comparison of factors was done by strengths, weaknesses, opportunities and threats-analytical hierarchical process analysis and priority scores to determine their relative importance to the system calculated using Eigenvalue method. For identification and registration, and evaluation and information utilisation, external factors had high priority scores. For pedigree and performance recording, threats and weaknesses had the highest priority scores. Strengths factors could not sustain the required efficiency of the system. Weaknesses of the system predisposed it to threats. Available opportunities could be explored as interventions to restore efficiency in the system. Defensive strategies such as reorienting the system to offer utility benefits to recording, forming symbiotic and binding collaboration between recording organisations and NARS, and development of institutions to support recording were feasible.

Discriminative Bayesian Dictionary Learning for Classification.

PubMed

Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

2016-12-01

We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

Analysis of Alternatives for Dismantling of the Equipment in Building 117/1 at Ignalina NPP - 13278

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

Poskas, Povilas; Simonis, Audrius; Poskas, Gintautas

2013-07-01

Ignalina NPP was operating two RBMK-1500 reactors which are under decommissioning now. In this paper dismantling alternatives of the equipment in Building 117/1 are analyzed. After situation analysis and collection of the primary information related to components' physical and radiological characteristics, location and other data, two different alternatives for dismantling of the equipment are formulated - the first (A1), when major components (vessels and pipes of Emergency Core Cooling System - ECCS) are segmented/halved in situ using flame cutting (oxy-acetylene) and the second one (A2), when these components are segmented/halved at the workshop using CAMC (Contact Arc Metal Cutting) technique.more » To select the preferable alternative MCDA method - AHP (Analytic Hierarchy Process) is applied. Hierarchical list of decision criteria, necessary for assessment of alternatives performance, are formulated. Quantitative decision criteria values for these alternatives are calculated using software DECRAD, which was developed by Lithuanian Energy Institute Nuclear engineering laboratory. While qualitative decision criteria are evaluated using expert judgment. Analysis results show that alternative A1 is better than alternative A2. (authors)« less

Chemical and Biological Sensing Using Diatom Photonic Crystal Biosilica With In-Situ Growth Plasmonic Nanoparticles.

PubMed

Kong, Xianming; Squire, Kenny; Li, Erwen; LeDuff, Paul; Rorrer, Gregory L; Tang, Suning; Chen, Bin; McKay, Christopher P; Navarro-Gonzalez, Rafael; Wang, Alan X

2016-12-01

In this paper, we described a new type of bioenabled nano-plasmonic sensors based on diatom photonic crystal biosilica with in-situ growth silver nanoparticles and demonstrated label-free chemical and biological sensing based on surface-enhanced Raman scattering (SERs) from complex samples. Diatoms are photosynthetic marine micro-organisms that create their own skeletal shells of hydrated amorphous silica, called frustules, which possess photonic crystal-like hierarchical micro- & nanoscale periodic pores. Our research shows that such hybrid plasmonic-biosilica nanostructures formed by cost-effective and eco-friendly bottom-up processes can achieve ultra-high limit of detection for medical applications, food sensing, water/air quality monitoring and geological/space research. The enhanced sensitivity comes from the optical coupling of the guided-mode resonance of the diatom frustules and the localized surface plasmons of the silver nanoparticles. Additionally, the nanoporous, ultra-hydrophilic diatom biosilica with large surface-to-volume ratio can concentrate more analyte molecules to the surface of the SERS substrates, which can help to detect biomolecules that cannot be easily adsorbed by metallic nanoparticles.

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

Hierarchical Active Inference: A Theory of Motivated Control.

PubMed

Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl J

2018-04-01

Motivated control refers to the coordination of behaviour to achieve affectively valenced outcomes or goals. The study of motivated control traditionally assumes a distinction between control and motivational processes, which map to distinct (dorsolateral versus ventromedial) brain systems. However, the respective roles and interactions between these processes remain controversial. We offer a novel perspective that casts control and motivational processes as complementary aspects - goal propagation and prioritization, respectively - of active inference and hierarchical goal processing under deep generative models. We propose that the control hierarchy propagates prior preferences or goals, but their precision is informed by the motivational context, inferred at different levels of the motivational hierarchy. The ensuing integration of control and motivational processes underwrites action and policy selection and, ultimately, motivated behaviour, by enabling deep inference to prioritize goals in a context-sensitive way. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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.

Coma Recovery Scale-Revised: evidentiary support for hierarchical grading of level of consciousness.

PubMed

Gerrard, Paul; Zafonte, Ross; Giacino, Joseph T

2014-12-01

To investigate the neurobehavioral pattern of recovery of consciousness as reflected by performance on the subscales of the Coma Recovery Scale-Revised (CRS-R). Retrospective item response theory (IRT) and factor analysis. Inpatient rehabilitation facilities. Rehabilitation inpatients (N=180) with posttraumatic disturbance in consciousness who participated in a double-blinded, randomized, controlled drug trial. Not applicable. Scores on CRS-R subscales. The CRS-R was found to fit factor analytic models adhering to the assumptions of unidimensionality and monotonicity. In addition, subscales were mutually independent based on residual correlations. Nonparametric IRT reaffirmed the finding of monotonicity. A highly constrained confirmatory factor analysis model, which imposed equal factor loadings on all items, was found to fit the data well and was used to estimate a 1-parameter IRT model. This study provides evidence of the unidimensionality of the CRS-R and supports the hierarchical structure of the CRS-R subscales, suggesting that it is an effective tool for establishing diagnosis and monitoring recovery of consciousness after severe traumatic brain injury. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Hierarchical charge distribution controls self-assembly process of silk in vitro

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhang, Cencen; Liu, Lijie; Kaplan, David L.; Zhu, Hesun; Lu, Qiang

2015-12-01

Silk materials with different nanostructures have been developed without the understanding of the inherent transformation mechanism. Here we attempt to reveal the conversion road of the various nanostructures and determine the critical regulating factors. The regulating conversion processes influenced by a hierarchical charge distribution were investigated, showing different transformations between molecules, nanoparticles and nanofibers. Various repulsion and compressive forces existed among silk fibroin molecules and aggregates due to the exterior and interior distribution of charge, which further controlled their aggregating and deaggregating behaviors and finally formed nanofibers with different sizes. Synergistic action derived from molecular mobility and concentrations could also tune the assembly process and final nanostructures. It is suggested that the complicated silk fibroin assembly processes comply a same rule based on charge distribution, offering a promising way to develop silk-based materials with designed nanostructures.

Primordial Evolution in the Finitary Process Soup

NASA Astrophysics Data System (ADS)

Görnerup, Olof; Crutchfield, James P.

A general and basic model of primordial evolution—a soup of reacting finitary and discrete processes—is employed to identify and analyze fundamental mechanisms that generate and maintain complex structures in prebiotic systems. The processes—ɛ-machines as defined in computational mechanics—and their interaction networks both provide well defined notions of structure. This enables us to quantitatively demonstrate hierarchical self-organization in the soup in terms of complexity. We found that replicating processes evolve the strategy of successively building higher levels of organization by autocatalysis. Moreover, this is facilitated by local components that have low structural complexity, but high generality. In effect, the finitary process soup spontaneously evolves a selection pressure that favors such components. In light of the finitary process soup's generality, these results suggest a fundamental law of hierarchical systems: global complexity requires local simplicity.

The Inversion Effect for Chinese Characters is Modulated by Radical Organization.

PubMed

Luo, Canhuang; Chen, Wei; Zhang, Ye

2017-06-01

In studies of visual object recognition, strong inversion effects accompany the acquisition of expertise and imply the involvement of configural processing. Chinese literacy results in sensitivity to the orthography of Chinese characters. While there is some evidence that this orthographic sensitivity results in an inversion effect, and thus involves configural processing, that processing might depend on exact orthographic properties. Chinese character recognition is believed to involve a hierarchical process, involving at least two lower levels of representation: strokes and radicals. Radicals are grouped into characters according to certain types of structure, i.e. left-right structure, top-bottom structure, or simple characters with only one radical by itself. These types of radical structures vary in both familiarity, and in hierarchical level (compound versus simple characters). In this study, we investigate whether the hierarchical-level or familiarity of radical-structure has an impact on the magnitude of the inversion effect. Participants were asked to do a matching task on pairs of either upright or inverted characters with all the types of structure. Inversion effects were measured based on both reaction time and response sensitivity. While an inversion effect was observed in all 3 conditions, the magnitude of the inversion effect varied with radical structure, being significantly larger for the most familiar type of structure: characters consisting of 2 radicals organized from left to right. These findings indicate that character recognition involves extraction of configural structure as well as radical processing which play different roles in the processing of compound characters and simple characters.

Delineating wetland catchments and modeling hydrologic ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

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.

Real-time hierarchically distributed processing network interaction simulation

NASA Technical Reports Server (NTRS)

Zimmerman, W. F.; Wu, C.

1987-01-01

The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

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.

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

NASA Astrophysics Data System (ADS)

Ono, Junichi; Takada, Shoji; Saito, Shinji

2015-06-01

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchical conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.

Neural network modeling of associative memory: Beyond the Hopfield model

NASA Astrophysics Data System (ADS)

Dasgupta, Chandan

1992-07-01

A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

Nonlinear analysis of damaged stiffened fuselage shells subjected to combined loads

NASA Technical Reports Server (NTRS)

Starnes, James H., Jr.; Britt, Vicki O.; Young, Richard D.; Rankin, Charles C.; Shore, Charles P.; Bains, Jane C.

1994-01-01

The results of an analytical study of the nonlinear response of stiffened fuselage shells with long cracks are presented. The shells are modeled with a hierarchical modeling strategy that accounts for global and local response phenomena accurately. Results are presented for internal pressure and mechanical bending loads. The effects of crack location and orientation on shell response are described. The effects of mechanical fasteners on the response of a lap joint and the effects of elastic and elastic-plastic material properties on the buckling response of tension-loaded flat panels with cracks are also addressed.

Random walk on p-adics and hierarchical systems

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

Lukierska-Walasek, K.; Topolski, K.; Institute of Mathematics, Wroclaw University, pl. Grunwaldzki 2/4, 50-384 Wroclaw

2006-02-01

We show that p-adic analysis provides a quite natural basis for the description of relaxation in hierarchical systems. For our purposes, we specify the Markov stochastic process considered by Albeverio and Karwowski. As a result we have obtained a random walk on the p-adic integer numbers, which provides the generalization of Cayley tree proposed by Ogielski and Stein. The temperature-dependent power-law decay and the Kohlrausch law are derived.

Automated Hierarchical to CODASYL (Conference on Data Systems Languages) Database Interface Schema Translator.

DTIC Science & Technology

1983-12-16

management system (DBMS) is to record and maintain information used by an organization in the organization’s decision-making process. Some advantages of a...independence. Database Management Systems are classified into three major models; relational, network, and hierarchical. Each model uses a software...feeling impedes the overall effectiveness of the 4-" Acquisition Management Information System (AMIS), which currently uses S2k. The size of the AMIS

Panarchy

USGS Publications Warehouse

Garmestani, Ahjond S.; Allen, Craig R.; El-Shaarawi, Abdel H.; Piegorsch, Walter W.

2012-01-01

Panarchy is the term coined to describe hierarchical systems where control is not only top down, as typically considered, but also bottom up. A panarchy is composed of adaptive cycles, and an adaptive cycle describes the processes of development and decay in a system. Complex systems self-organize into hierarchies because this structure limits the possible spread of destructive phenomena (e.g., forest fires, epidemics) that could result in catastrophic system failure. Thus, hierarchical organization enhances the resilience of complex systems.

Musculoskeletal motion flow fields using hierarchical variable-sized block matching in ultrasonographic video sequences.

PubMed

Revell, J D; Mirmehdi, M; McNally, D S

2004-04-01

We examine tissue deformations using non-invasive dynamic musculoskeletal ultrasonograhy, and quantify its performance on controlled in vitro gold standard (groundtruth) sequences followed by clinical in vivo data. The proposed approach employs a two-dimensional variable-sized block matching algorithm with a hierarchical full search. We extend this process by refining displacements to sub-pixel accuracy. We show by application that this technique yields quantitatively reliable results.

Hierarchical nanostructures of copper(II) phthalocyanine on electrospun TiO(2) nanofibers: controllable solvothermal-fabrication and enhanced visible photocatalytic properties.

PubMed

Zhang, Mingyi; Shao, Changlu; Guo, Zengcai; Zhang, Zhenyi; Mu, Jingbo; Cao, Tieping; Liu, Yichun

2011-02-01

In the present work, 2,9,16,23-tetranitrophthalocyanine copper(II) (TNCuPc)/TiO(2) hierarchical nanostructures were successfully fabricated by a simple combination method of electrospinning technique and solvothermal processing. Scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, X-ray diffraction (XRD), UV-vis diffuse reflectance (DR), Fourier transform infrared spectrum (FT-IR), X-ray photoelectron spectroscopy (XPS), and thermal gravimetric and differential thermal analysis (TG-DTA) were used to characterize the as-synthesized TNCuPc/TiO(2) hierarchical nanostructures. The results showed that the secondary TNCuPc nanostructures were not only successfully grown on the primary TiO(2) nanofibers substrates but also uniformly distributed without aggregation. By adjusting the solvothermal fabrication parameters, the TNCuPc nanowires or nanoflowers were facilely fabricated, and also the loading amounts of TNCuPc could be controlled on the TNCuPc/TiO(2) hierarchical nanostructural nanofibers. And, there might exist the interaction between TNCuPc and TiO(2). A possible mechanism for the formation of TNCuPc/TiO(2) hierarchical nanostructures was suggested. The photocatalytic studies revealed that the TNCuPc/TiO(2) hierarchical nanostructures exhibited enhanced photocatalytic efficiency of photodegradation of Rhodamine B (RB) compared with the pure TNCuPc or TiO(2) nanofibers under visible-light irradiation.

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

PubMed

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

2014-08-27

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

Pore-scale study of effects of macroscopic pores and their distributions on reactive transport in hierarchical porous media

DOE PAGES

Chen, Li; Zhang, Ruiyuan; Min, Ting; ...

2018-05-19

For applications of reactive transport in porous media, optimal porous structures should possess both high surface area for reactive sites loading and low mass transport resistance. Hierarchical porous media with a combination of pores at different scales are designed for this purpose. In this paper, using the lattice Boltzmann method, pore-scale numerical studies are conducted to investigate diffusion-reaction processes in 2D hierarchical porous media generated by self-developed reconstruction scheme. Complex interactions between porous structures and reactive transport are revealed under different conditions. Simulation results show that adding macropores can greatly enhance the mass transport, but at the same time reducemore » the reactive surface, leading to complex change trend of the total reaction rate. Effects of gradient distribution of macropores within the porous medium are also investigated. It is found that a front-loose, back-tight (FLBT) hierarchical structure is desirable for enhancing mass transport, increasing total reaction rate, and improving catalyst utilization. Finally, on the whole, from the viewpoint of reducing cost and improving material performance, hierarchical porous structures, especially gradient structures with the size of macropores gradually decreasing along the transport direction, are desirable for catalyst application.« less

Pore-scale study of effects of macroscopic pores and their distributions on reactive transport in hierarchical porous media

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

Chen, Li; Zhang, Ruiyuan; Min, Ting

For applications of reactive transport in porous media, optimal porous structures should possess both high surface area for reactive sites loading and low mass transport resistance. Hierarchical porous media with a combination of pores at different scales are designed for this purpose. In this paper, using the lattice Boltzmann method, pore-scale numerical studies are conducted to investigate diffusion-reaction processes in 2D hierarchical porous media generated by self-developed reconstruction scheme. Complex interactions between porous structures and reactive transport are revealed under different conditions. Simulation results show that adding macropores can greatly enhance the mass transport, but at the same time reducemore » the reactive surface, leading to complex change trend of the total reaction rate. Effects of gradient distribution of macropores within the porous medium are also investigated. It is found that a front-loose, back-tight (FLBT) hierarchical structure is desirable for enhancing mass transport, increasing total reaction rate, and improving catalyst utilization. Finally, on the whole, from the viewpoint of reducing cost and improving material performance, hierarchical porous structures, especially gradient structures with the size of macropores gradually decreasing along the transport direction, are desirable for catalyst application.« less

Nanowire-Assembled Hierarchical ZnCo2O4 Microstructure Integrated with a Low-Power Microheater for Highly Sensitive Formaldehyde Detection.

PubMed

Long, Hu; Harley-Trochimczyk, Anna; Cheng, Siyi; Hu, Hao; Chi, Won Seok; Rao, Ameya; Carraro, Carlo; Shi, Tielin; Tang, Zirong; Maboudian, Roya

2016-11-23

Nanowire-assembled 3D hierarchical ZnCo 2 O 4 microstructure is synthesized by a facile hydrothermal route and a subsequent annealing process. In comparison to simple nanowires, the resulting dandelion-like structure yields more open spaces between nanowires, which allow for better gas diffusion and provide more active sites for gas adsorption while maintaining good electrical conductivity. The hierarchical ZnCo 2 O 4 microstructure is integrated on a low-power microheater platform without using binders or conductive additives. The hierarchical structure of the ZnCo 2 O 4 sensing material provides reliable electrical connection across the sensing electrodes. The resulting sensor exhibits an ultralow detection limit of 3 ppb toward formaldehyde with fast response and recovery as well as good selectivity to CO, H 2 , and hydrocarbons such as n-pentane, propane, and CH 4 . The sensor only consumes ∼5.7 mW for continuous operation at 300 °C with good long-term stability. The excellent sensing performance of this hierarchical structure based sensor suggests the advantages of combining such structures with microfabricated heaters for practical low-power sensing applications.

POLLUTION PREVENTION IN THE DESIGN OF CHEMICAL PROCESSES USING HIERARCHICAL DESIGN AND SIMULATION

EPA Science Inventory

The design of chemical processes is normally an interactive process of synthesis and analysis. When one also desires or needs to limit the amount of pollution generated by the process the difficulty of the task can increase substantially. In this work, we show how combining hier...

Tracking Hierarchical Processing in Morphological Decomposition with Brain Potentials

ERIC Educational Resources Information Center

Lavric, Aureliu; Elchlepp, Heike; Rastle, Kathleen

2012-01-01

One important debate in psycholinguistics concerns the nature of morphological decomposition processes in visual word recognition (e.g., darkness = {dark} + {-ness}). One theory claims that these processes arise during orthographic analysis and prior to accessing meaning (Rastle & Davis, 2008), and another argues that these processes arise through…

The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

PubMed

Carroll, Adam J; Badger, Murray R; Harvey Millar, A

2010-07-14

Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.

A new artefacts resistant method for automatic lineament extraction using Multi-Hillshade Hierarchic Clustering (MHHC)

NASA Astrophysics Data System (ADS)

Šilhavý, Jakub; Minár, Jozef; Mentlík, Pavel; Sládek, Ján

2016-07-01

This paper presents a new method of automatic lineament extraction which includes the removal of the 'artefacts effect' which is associated with the process of raster based analysis. The core of the proposed Multi-Hillshade Hierarchic Clustering (MHHC) method incorporates a set of variously illuminated and rotated hillshades in combination with hierarchic clustering of derived 'protolineaments'. The algorithm also includes classification into positive and negative lineaments. MHHC was tested in two different territories in Bohemian Forest and Central Western Carpathians. The original vector-based algorithm was developed for comparison of the individual lineaments proximity. Its use confirms the compatibility of manual and automatic extraction and their similar relationships to structural data in the study areas.

Mechanically durable superoleophobic aluminum surfaces with microstep and nanoreticula hierarchical structure for self-cleaning and anti-smudge properties.

PubMed

Peng, Shan; Bhushan, Bharat

2016-01-01

Superoleophobic aluminum surfaces are of interest for self-cleaning, anti-smudge (fingerprint resistance), anti-fouling, and corrosion resistance applications. In the published literature on superoleophobic aluminum surfaces, mechanical durability, self-cleaning, and anti-smudge properties data are lacking. Microstep structure has often been used to prepare superhydrophobic aluminum surfaces which produce the microstructure. The nanoreticula structure has also been used, and is reported to be able to trap air-pockets, which are desirable for a high contact angle. In this work, the microstep and nanoreticula structures were produced on aluminum surfaces to form a hierarchical micro/nanostructure by a simple two-step chemical etching process. The hierarchical structure, when modified with fluorosilane, made the surface superoleophobic. The effect of nanostructure, microstructure, and hierarchical structure on wettability and durability were studied and compared. The superoleophobic aluminum surfaces were found to be wear resistant, self-cleaning, and have anti-smudge and corrosion resistance properties. Copyright © 2015 Elsevier Inc. All rights reserved.