Structural and Functional Insights from the Metagenome of an Acidic Hot Spring Microbial Planktonic Community in the Colombian Andes

PubMed Central

Jiménez, Diego Javier; Andreote, Fernando Dini; Chaves, Diego; Montaña, José Salvador; Osorio-Forero, Cesar; Junca, Howard; Zambrano, María Mercedes; Baena, Sandra

2012-01-01

A taxonomic and annotated functional description of microbial life was deduced from 53 Mb of metagenomic sequence retrieved from a planktonic fraction of the Neotropical high Andean (3,973 meters above sea level) acidic hot spring El Coquito (EC). A classification of unassembled metagenomic reads using different databases showed a high proportion of Gammaproteobacteria and Alphaproteobacteria (in total read affiliation), and through taxonomic affiliation of 16S rRNA gene fragments we observed the presence of Proteobacteria, micro-algae chloroplast and Firmicutes. Reads mapped against the genomes Acidiphilium cryptum JF-5, Legionella pneumophila str. Corby and Acidithiobacillus caldus revealed the presence of transposase-like sequences, potentially involved in horizontal gene transfer. Functional annotation and hierarchical comparison with different datasets obtained by pyrosequencing in different ecosystems showed that the microbial community also contained extensive DNA repair systems, possibly to cope with ultraviolet radiation at such high altitudes. Analysis of genes involved in the nitrogen cycle indicated the presence of dissimilatory nitrate reduction to N2 (narGHI, nirS, norBCDQ and nosZ), associated with Proteobacteria-like sequences. Genes involved in the sulfur cycle (cysDN, cysNC and aprA) indicated adenylsulfate and sulfite production that were affiliated to several bacterial species. In summary, metagenomic sequence data provided insight regarding the structure and possible functions of this hot spring microbial community, describing some groups potentially involved in the nitrogen and sulfur cycling in this environment. PMID:23251687

Hierarchically Organized Behavior and Its Neural Foundations: A Reinforcement Learning Perspective

ERIC Educational Resources Information Center

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

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…

Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

NASA Astrophysics Data System (ADS)

Bai, Hao; Zhang, Xi-wen

2017-06-01

While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

PubMed

Sepúlveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain, Arnab; Clark, Taane G

2013-02-26

The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.

Myrtenal, a controversial molecule for the proper application of the CIP Sequence Rule for multiple bonds.

PubMed

Zepeda, L Gerardo; Burgueño-Tapia, Eleuterio; Joseph-Nathan, Pedro

2011-04-01

This communication highlights the need of building hierarchical digraphs for the unequivocal assignment of stereochemical descriptors of (-)-myrtenal, a naturally-occurring oxygenated monoterpene whose absolute configuration (AC) is sometimes misrepresented in its structural formulae. Differentiation between duplicated atoms and phantom atoms for the proper application of the sequence rules is shown to be an essential step to get a proper construction of hierarchical digraphs.

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.

Hierarchic models for laminated plates

NASA Technical Reports Server (NTRS)

Szabo, Barna A.; Actis, Ricardo L.

1991-01-01

The research conducted in the formulation of hierarchic models for laminated plates is described. The work is an extension of the work done for laminated strips. The use of a single parameter, beta, is investigated that represents the degree to which the equilibrium equations of three dimensional elasticity are satisfied. The powers of beta identify members in the hierarchic sequence. Numerical examples that were analyzed with the proposed sequence of models are included. The results obtained for square plates with uniform loading and homogeneous boundary conditions are very encouraging. Several cross-ply and angle-ply laminates were evaluated and the results compared with those of the fully three dimensional model, computed using MSC/PROBE, and with previously reported work on laminated strips.

Hierarchic plate and shell models based on p-extension

NASA Technical Reports Server (NTRS)

Szabo, Barna A.; Sahrmann, Glenn J.

1988-01-01

Formulations of finite element models for beams, arches, plates and shells based on the principle of virtual work was studied. The focus is on computer implementation of hierarchic sequences of finite element models suitable for numerical solution of a large variety of practical problems which may concurrently contain thin and thick plates and shells, stiffeners, and regions where three dimensional representation is required. The approximate solutions corresponding to the hierarchic sequence of models converge to the exact solution of the fully three dimensional model. The stopping criterion is based on: (1) estimation of the relative error in energy norm; (2) equilibrium tests, and (3) observation of the convergence of quantities of interest.

High Potential Source for Biomass Degradation Enzyme Discovery and Environmental Aspects Revealed through Metagenomics of Indian Buffalo Rumen

PubMed Central

Singh, K. M.; Reddy, Bhaskar; Patel, Dishita; Patel, A. K.; Patel, J. B.; Joshi, C. G.

2014-01-01

The complex microbiomes of the rumen functions as an effective system for plant cell wall degradation, and biomass utilization provide genetic resource for degrading microbial enzymes that could be used in the production of biofuel. Therefore the buffalo rumen microbiota was surveyed using shot gun sequencing. This metagenomic sequencing generated 3.9 GB of sequences and data were assembled into 137270 contiguous sequences (contigs). We identified potential 2614 contigs encoding biomass degrading enzymes including glycoside hydrolases (GH: 1943 contigs), carbohydrate binding module (CBM: 23 contigs), glycosyl transferase (GT: 373 contigs), carbohydrate esterases (CE: 259 contigs), and polysaccharide lyases (PE: 16 contigs). The hierarchical clustering of buffalo metagenomes demonstrated the similarities and dissimilarity in microbial community structures and functional capacity. This demonstrates that buffalo rumen microbiome was considerably enriched in functional genes involved in polysaccharide degradation with great prospects to obtain new molecules that may be applied in the biofuel industry. PMID:25136572

An Eccentric Binary Millisecond Pulsar in the Galactic Plane

NASA Technical Reports Server (NTRS)

Champion, David J.; Ransom, Scott M.; Lazarus, Patrick; Camilo, Fernando; Bassa, Cess; Kaspi, Victoria M.; Nice, David J.; Freire, Paulo C. C.; Stairs, Ingrid H.; vanLeeuwen, Joeri;

Exploiting long read sequencing technologies to establish high quality highly contiguous pig reference genome assemblies

USDA-ARS?s Scientific Manuscript database

The current pig reference genome sequence (Sscrofa10.2) was established using Sanger sequencing and following the clone-by-clone hierarchical shotgun sequencing approach used in the public human genome project. However, as sequence coverage was low (4-6x) the resulting assembly was only of draft qua...

Command in a field hospital.

PubMed

Bricknell, M C M

2003-03-01

This paper examines the challenges involved in commanding a field hospital. There are frequent, dynamic tensions between the military culture that is based on a task-focussed, hierarchical structure and the clinical culture that is based on flat, process-focussed, multidisciplinary teams. The paper outlines the cultural environment of the field hospital and then examines the deployment sequence whereby a functioning clinical facility may be created from a group of disparate individuals. There are a number of tools that may assist with this including the personality of the Commanding Officer, individual skills, the creation of an organizational identity and the choice of command structure.

ERP Responses to Violations in the Hierarchical Structure of Functional Categories in Japanese Verb Conjugation.

PubMed

Kobayashi, Yuki; Sugioka, Yoko; Ito, Takane

2018-02-01

An event-related potential experiment was conducted in order to investigate readers' response to violations in the hierarchical structure of functional categories in Japanese, an agglutinative language where functional heads like Negation (Neg) as well as Tense (Tns) are realized as suffixes. A left-lateralized negativity followed by a P600 was elicited for the anomaly of attaching a Neg morpheme outside a Tns-marking suffix (i.e., syntactic violation of the form *[[V - Tns] - Neg]), while only P600 was observed for the anomalous form with a purely morphological/morpho-phonological violation, i.e., a Neg morpheme attached to ren'yo form instead of Neg-selecting form. The findings suggest that the syntactic structure involving Tns and Neg in Japanese, realized within a word as a sequence of suffixes, is processed in a similar manner to the syntactic structures that are phrasally realized in well-studied European languages like English.

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

PubMed Central

2013-01-01

Background The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Results Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. Conclusions In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. PMID:23442253

SND1 Transcription Factor–Directed Quantitative Functional Hierarchical Genetic Regulatory Network in Wood Formation in Populus trichocarpa[C][W

PubMed Central

Lin, Ying-Chung; Li, Wei; Sun, Ying-Hsuan; Kumari, Sapna; Wei, Hairong; Li, Quanzi; Tunlaya-Anukit, Sermsawat; Sederoff, Ronald R.; Chiang, Vincent L.

2013-01-01

Wood is an essential renewable raw material for industrial products and energy. However, knowledge of the genetic regulation of wood formation is limited. We developed a genome-wide high-throughput system for the discovery and validation of specific transcription factor (TF)–directed hierarchical gene regulatory networks (hGRNs) in wood formation. This system depends on a new robust procedure for isolation and transfection of Populus trichocarpa stem differentiating xylem protoplasts. We overexpressed Secondary Wall-Associated NAC Domain 1s (Ptr-SND1-B1), a TF gene affecting wood formation, in these protoplasts and identified differentially expressed genes by RNA sequencing. Direct Ptr-SND1-B1–DNA interactions were then inferred by integration of time-course RNA sequencing data and top-down Graphical Gaussian Modeling–based algorithms. These Ptr-SND1-B1-DNA interactions were verified to function in differentiating xylem by anti-PtrSND1-B1 antibody-based chromatin immunoprecipitation (97% accuracy) and in stable transgenic P. trichocarpa (90% accuracy). In this way, we established a Ptr-SND1-B1–directed quantitative hGRN involving 76 direct targets, including eight TF and 61 enzyme-coding genes previously unidentified as targets. The network can be extended to the third layer from the second-layer TFs by computation or by overexpression of a second-layer TF to identify a new group of direct targets (third layer). This approach would allow the sequential establishment, one two-layered hGRN at a time, of all layers involved in a more comprehensive hGRN. Our approach may be particularly useful to study hGRNs in complex processes in plant species resistant to stable genetic transformation and where mutants are unavailable. PMID:24280390

A whole-genome assembly of the domestic cow, Bos taurus

USDA-ARS?s Scientific Manuscript database

Background: The genome of the domestic cow, Bos taurus, was sequenced using a mixture of hierarchical and whole-genome shotgun sequencing methods. Results: We have assembled the 35 million sequence reads and applied a variety of assembly improvement techniques, creating an assembly of 2.86 billion b...

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

PubMed Central

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

2014-01-01

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

Constructing storyboards based on hierarchical clustering analysis

NASA Astrophysics Data System (ADS)

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

2005-07-01

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

Evaluating, Comparing, and Interpreting Protein Domain Hierarchies

PubMed Central

2014-01-01

Abstract Arranging protein domain sequences hierarchically into evolutionarily divergent subgroups is important for investigating evolutionary history, for speeding up web-based similarity searches, for identifying sequence determinants of protein function, and for genome annotation. However, whether or not a particular hierarchy is optimal is often unclear, and independently constructed hierarchies for the same domain can often differ significantly. This article describes methods for statistically evaluating specific aspects of a hierarchy, for probing the criteria underlying its construction and for direct comparisons between hierarchies. Information theoretical notions are used to quantify the contributions of specific hierarchical features to the underlying statistical model. Such features include subhierarchies, sequence subgroups, individual sequences, and subgroup-associated signature patterns. Underlying properties are graphically displayed in plots of each specific feature's contributions, in heat maps of pattern residue conservation, in “contrast alignments,” and through cross-mapping of subgroups between hierarchies. Together, these approaches provide a deeper understanding of protein domain functional divergence, reveal uncertainties caused by inconsistent patterns of sequence conservation, and help resolve conflicts between competing hierarchies. PMID:24559108

Analysis of composition-based metagenomic classification.

PubMed

Higashi, Susan; Barreto, André da Motta Salles; Cantão, Maurício Egidio; de Vasconcelos, Ana Tereza Ribeiro

2012-01-01

An essential step of a metagenomic study is the taxonomic classification, that is, the identification of the taxonomic lineage of the organisms in a given sample. The taxonomic classification process involves a series of decisions. Currently, in the context of metagenomics, such decisions are usually based on empirical studies that consider one specific type of classifier. In this study we propose a general framework for analyzing the impact that several decisions can have on the classification problem. Instead of focusing on any specific classifier, we define a generic score function that provides a measure of the difficulty of the classification task. Using this framework, we analyze the impact of the following parameters on the taxonomic classification problem: (i) the length of n-mers used to encode the metagenomic sequences, (ii) the similarity measure used to compare sequences, and (iii) the type of taxonomic classification, which can be conventional or hierarchical, depending on whether the classification process occurs in a single shot or in several steps according to the taxonomic tree. We defined a score function that measures the degree of separability of the taxonomic classes under a given configuration induced by the parameters above. We conducted an extensive computational experiment and found out that reasonable values for the parameters of interest could be (i) intermediate values of n, the length of the n-mers; (ii) any similarity measure, because all of them resulted in similar scores; and (iii) the hierarchical strategy, which performed better in all of the cases. As expected, short n-mers generate lower configuration scores because they give rise to frequency vectors that represent distinct sequences in a similar way. On the other hand, large values for n result in sparse frequency vectors that represent differently metagenomic fragments that are in fact similar, also leading to low configuration scores. Regarding the similarity measure, in contrast to our expectations, the variation of the measures did not change the configuration scores significantly. Finally, the hierarchical strategy was more effective than the conventional strategy, which suggests that, instead of using a single classifier, one should adopt multiple classifiers organized as a hierarchy.

Automated plant, production management system

NASA Astrophysics Data System (ADS)

Aksenova, V. I.; Belov, V. I.

1984-12-01

The development of a complex of tasks for the operational management of production (OUP) within the framework of an automated system for production management (ASUP) shows that it is impossible to have effective computations without reliable initial information. The influence of many factors involving the production and economic activity of the entire enterprise upon the plan and course of production are considered. It is suggested that an adequate model should be available which covers all levels of the hierarchical system: workplace, section (bridgade), shop, enterprise, and the model should be incorporated into the technological sequence of performance and there should be provisions for an adequate man machine system.

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

2011-01-01

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

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

PubMed Central

Nee, Derek Evan; Brown, Joshua W.

2013-01-01

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

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.

Generation of animation sequences of three dimensional models

NASA Technical Reports Server (NTRS)

Poi, Sharon (Inventor); Bell, Brad N. (Inventor)

1990-01-01

The invention is directed toward a method and apparatus for generating an animated sequence through the movement of three-dimensional graphical models. A plurality of pre-defined graphical models are stored and manipulated in response to interactive commands or by means of a pre-defined command file. The models may be combined as part of a hierarchical structure to represent physical systems without need to create a separate model which represents the combined system. System motion is simulated through the introduction of translation, rotation and scaling parameters upon a model within the system. The motion is then transmitted down through the system hierarchy of models in accordance with hierarchical definitions and joint movement limitations. The present invention also calls for a method of editing hierarchical structure in response to interactive commands or a command file such that a model may be included, deleted, copied or moved within multiple system model hierarchies. The present invention also calls for the definition of multiple viewpoints or cameras which may exist as part of a system hierarchy or as an independent camera. The simulated movement of the models and systems is graphically displayed on a monitor and a frame is recorded by means of a video controller. Multiple movement and hierarchy manipulations are then recorded as a sequence of frames which may be played back as an animation sequence on a video cassette recorder.

The minimalist grammar of action

PubMed Central

Pastra, Katerina; Aloimonos, Yiannis

2012-01-01

Language and action have been found to share a common neural basis and in particular a common ‘syntax’, an analogous hierarchical and compositional organization. While language structure analysis has led to the formulation of different grammatical formalisms and associated discriminative or generative computational models, the structure of action is still elusive and so are the related computational models. However, structuring action has important implications on action learning and generalization, in both human cognition research and computation. In this study, we present a biologically inspired generative grammar of action, which employs the structure-building operations and principles of Chomsky's Minimalist Programme as a reference model. In this grammar, action terminals combine hierarchically into temporal sequences of actions of increasing complexity; the actions are bound with the involved tools and affected objects and are governed by certain goals. We show, how the tool role and the affected-object role of an entity within an action drives the derivation of the action syntax in this grammar and controls recursion, merge and move, the latter being mechanisms that manifest themselves not only in human language, but in human action too. PMID:22106430

CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database

PubMed Central

Jia, Baofeng; Raphenya, Amogelang R.; Alcock, Brian; Waglechner, Nicholas; Guo, Peiyao; Tsang, Kara K.; Lago, Briony A.; Dave, Biren M.; Pereira, Sheldon; Sharma, Arjun N.; Doshi, Sachin; Courtot, Mélanie; Lo, Raymond; Williams, Laura E.; Frye, Jonathan G.; Elsayegh, Tariq; Sardar, Daim; Westman, Erin L.; Pawlowski, Andrew C.; Johnson, Timothy A.; Brinkman, Fiona S.L.; Wright, Gerard D.; McArthur, Andrew G.

2017-01-01

The Comprehensive Antibiotic Resistance Database (CARD; http://arpcard.mcmaster.ca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR. CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance. It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization. Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence. Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats. CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis. PMID:27789705

From Movements to Actions: Two Mechanisms for Learning Action Sequences

ERIC Educational Resources Information Center

Endress, Ansgar D.; Wood, Justin N.

2011-01-01

When other individuals move, we interpret their movements as discrete, hierarchically-organized, goal-directed actions. However, the mechanisms that integrate visible movement features into actions are poorly understood. Here, we consider two sequence learning mechanisms--transitional probability-based (TP) and position-based encoding…

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

PubMed

Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

2018-02-01

Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

Hierarchical Structure in Polymeric Solids and Its Influence on Properties.

DTIC Science & Technology

1988-03-01

AD-l4193 538 NI U*CHLCAL cIUI8 IN~~ EIS LIDIANDtIIS 1/ UMCLASSrIrIDq foMS) r/G 7𔃽 ML UU P1. barkel (1.25) AD-A193 538 HIERARCHICAL STRUCTURE IN... upecer sequence anoula DsOM Identifiable# which In turn shouldcorrelate with the scheme of mesogen spacer packing established during S previous period

Language, music, syntax and the brain.

PubMed

Patel, Aniruddh D

2003-07-01

The comparative study of music and language is drawing an increasing amount of research interest. Like language, music is a human universal involving perceptually discrete elements organized into hierarchically structured sequences. Music and language can thus serve as foils for each other in the study of brain mechanisms underlying complex sound processing, and comparative research can provide novel insights into the functional and neural architecture of both domains. This review focuses on syntax, using recent neuroimaging data and cognitive theory to propose a specific point of convergence between syntactic processing in language and music. This leads to testable predictions, including the prediction that that syntactic comprehension problems in Broca's aphasia are not selective to language but influence music perception as well.

Learning of Chunking Sequences in Cognition and Behavior

PubMed Central

Rabinovich, Mikhail

2015-01-01

We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson’s disease and Schizophrenia. PMID:26584306

Epigenetic regulation of vascular smooth muscle cell function in atherosclerosis.

PubMed

Findeisen, Hannes M; Kahles, Florian K; Bruemmer, Dennis

2013-04-01

Epigenetics involve heritable and acquired changes in gene transcription that occur independently of the DNA sequence. Epigenetic mechanisms constitute a hierarchic upper-level of transcriptional control through complex modifications of chromosomal components and nuclear structures. These modifications include, for example, DNA methylation or post-translational modifications of core histones; they are mediated by various chromatin-modifying enzymes; and ultimately they define the accessibility of a transcriptional complex to its target DNA. Integrating epigenetic mechanisms into the pathophysiologic concept of complex and multifactorial diseases such as atherosclerosis may significantly enhance our understanding of related mechanisms and provide promising therapeutic approaches. Although still in its infancy, intriguing scientific progress has begun to elucidate the role of epigenetic mechanisms in vascular biology, particularly in the control of smooth muscle cell phenotypes. In this review, we will summarize epigenetic pathways in smooth muscle cells, focusing on mechanisms involved in the regulation of vascular remodeling.

Epigenetic regulation of vascular smooth muscle cell function in atherosclerosis.

PubMed

Findeisen, Hannes M; Kahles, Florian K; Bruemmer, Dennis

2013-05-01

Epigenetics involve heritable and acquired changes in gene transcription that occur independently of the DNA sequence. Epigenetic mechanisms constitute a hierarchic upper-level of transcriptional control through complex modifications of chromosomal components and nuclear structures. These modifications include, for example, DNA methylation or post-translational modifications of core histones; they are mediated by various chromatin-modifying enzymes; and ultimately they define the accessibility of a transcriptional complex to its target DNA. Integrating epigenetic mechanisms into the pathophysiologic concept of complex and multifactorial diseases such as atherosclerosis may significantly enhance our understanding of related mechanisms and provide promising therapeutic approaches. Although still in its infancy, intriguing scientific progress has begun to elucidate the role of epigenetic mechanisms in vascular biology, particularly in the control of smooth muscle cell phenotypes. In this review, we will summarize epigenetic pathways in smooth muscle cells, focusing on mechanisms involved in the regulation of vascular remodeling.

DNA Barcode Sequence Identification Incorporating Taxonomic Hierarchy and within Taxon Variability

PubMed Central

Little, Damon P.

2011-01-01

For DNA barcoding to succeed as a scientific endeavor an accurate and expeditious query sequence identification method is needed. Although a global multiple–sequence alignment can be generated for some barcoding markers (e.g. COI, rbcL), not all barcoding markers are as structurally conserved (e.g. matK). Thus, algorithms that depend on global multiple–sequence alignments are not universally applicable. Some sequence identification methods that use local pairwise alignments (e.g. BLAST) are unable to accurately differentiate between highly similar sequences and are not designed to cope with hierarchic phylogenetic relationships or within taxon variability. Here, I present a novel alignment–free sequence identification algorithm–BRONX–that accounts for observed within taxon variability and hierarchic relationships among taxa. BRONX identifies short variable segments and corresponding invariant flanking regions in reference sequences. These flanking regions are used to score variable regions in the query sequence without the production of a global multiple–sequence alignment. By incorporating observed within taxon variability into the scoring procedure, misidentifications arising from shared alleles/haplotypes are minimized. An explicit treatment of more inclusive terminals allows for separate identifications to be made for each taxonomic level and/or for user–defined terminals. BRONX performs better than all other methods when there is imperfect overlap between query and reference sequences (e.g. mini–barcode queries against a full–length barcode database). BRONX consistently produced better identifications at the genus–level for all query types. PMID:21857897

A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data

PubMed Central

Feng, Hao; Conneely, Karen N.; Wu, Hao

2014-01-01

DNA methylation is an important epigenetic modification that has essential roles in cellular processes including gene regulation, development and disease and is widely dysregulated in most types of cancer. Recent advances in sequencing technology have enabled the measurement of DNA methylation at single nucleotide resolution through methods such as whole-genome bisulfite sequencing and reduced representation bisulfite sequencing. In DNA methylation studies, a key task is to identify differences under distinct biological contexts, for example, between tumor and normal tissue. A challenge in sequencing studies is that the number of biological replicates is often limited by the costs of sequencing. The small number of replicates leads to unstable variance estimation, which can reduce accuracy to detect differentially methylated loci (DML). Here we propose a novel statistical method to detect DML when comparing two treatment groups. The sequencing counts are described by a lognormal-beta-binomial hierarchical model, which provides a basis for information sharing across different CpG sites. A Wald test is developed for hypothesis testing at each CpG site. Simulation results show that the proposed method yields improved DML detection compared to existing methods, particularly when the number of replicates is low. The proposed method is implemented in the Bioconductor package DSS. PMID:24561809

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

PubMed Central

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

2009-01-01

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

Control of Task Sequences: What Is the Role of Language?

ERIC Educational Resources Information Center

Mayr, Ulrich; Kleffner-Canucci, Killian; Kikumoto, Atsushi; Redford, Melissa A.

2014-01-01

It is almost a truism that language aids serial-order control through self-cuing of upcoming sequential elements. We measured speech onset latencies as subjects performed hierarchically organized task sequences while "thinking aloud" each task label. Surprisingly, speech onset latencies and response times (RTs) were highly synchronized,…

A Developmental Sequence Model to University Adjustment of International Undergraduate Students

ERIC Educational Resources Information Center

Chavoshi, Saeid; Wintre, Maxine Gallander; Dentakos, Stella; Wright, Lorna

2017-01-01

The current study proposes a Developmental Sequence Model to University Adjustment and uses a multifaceted measure, including academic, social and psychological adjustment, to examine factors predictive of undergraduate international student adjustment. A hierarchic regression model is carried out on the Student Adaptation to College Questionnaire…

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

NASA Technical Reports Server (NTRS)

Gossman, W. E.

1986-01-01

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

Genomics dataset on unclassified published organism (patent US 7547531).

PubMed

Khan Shawan, Mohammad Mahfuz Ali; Hasan, Md Ashraful; Hossain, Md Mozammel; Hasan, Md Mahmudul; Parvin, Afroza; Akter, Salina; Uddin, Kazi Rasel; Banik, Subrata; Morshed, Mahbubul; Rahman, Md Nazibur; Rahman, S M Badier

2016-12-01

Nucleotide (DNA) sequence analysis provides important clues regarding the characteristics and taxonomic position of an organism. With the intention that, DNA sequence analysis is very crucial to learn about hierarchical classification of that particular organism. This dataset (patent US 7547531) is chosen to simplify all the complex raw data buried in undisclosed DNA sequences which help to open doors for new collaborations. In this data, a total of 48 unidentified DNA sequences from patent US 7547531 were selected and their complete sequences were retrieved from NCBI BioSample database. Quick response (QR) code of those DNA sequences was constructed by DNA BarID tool. QR code is useful for the identification and comparison of isolates with other organisms. AT/GC content of the DNA sequences was determined using ENDMEMO GC Content Calculator, which indicates their stability at different temperature. The highest GC content was observed in GP445188 (62.5%) which was followed by GP445198 (61.8%) and GP445189 (59.44%), while lowest was in GP445178 (24.39%). In addition, New England BioLabs (NEB) database was used to identify cleavage code indicating the 5, 3 and blunt end and enzyme code indicating the methylation site of the DNA sequences was also shown. These data will be helpful for the construction of the organisms' hierarchical classification, determination of their phylogenetic and taxonomic position and revelation of their molecular characteristics.

Linear SFM: A hierarchical approach to solving structure-from-motion problems by decoupling the linear and nonlinear components

NASA Astrophysics Data System (ADS)

Zhao, Liang; Huang, Shoudong; Dissanayake, Gamini

2018-07-01

This paper presents a novel hierarchical approach to solving structure-from-motion (SFM) problems. The algorithm begins with small local reconstructions based on nonlinear bundle adjustment (BA). These are then joined in a hierarchical manner using a strategy that requires solving a linear least squares optimization problem followed by a nonlinear transform. The algorithm can handle ordered monocular and stereo image sequences. Two stereo images or three monocular images are adequate for building each initial reconstruction. The bulk of the computation involves solving a linear least squares problem and, therefore, the proposed algorithm avoids three major issues associated with most of the nonlinear optimization algorithms currently used for SFM: the need for a reasonably accurate initial estimate, the need for iterations, and the possibility of being trapped in a local minimum. Also, by summarizing all the original observations into the small local reconstructions with associated information matrices, the proposed Linear SFM manages to preserve all the information contained in the observations. The paper also demonstrates that the proposed problem formulation results in a sparse structure that leads to an efficient numerical implementation. The experimental results using publicly available datasets show that the proposed algorithm yields solutions that are very close to those obtained using a global BA starting with an accurate initial estimate. The C/C++ source code of the proposed algorithm is publicly available at https://github.com/LiangZhaoPKUImperial/LinearSFM.

Hierarchical Control Using Networks Trained with Higher-Level Forward Models

PubMed Central

Wayne, Greg; Abbott, L.F.

2015-01-01

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

Observing complex action sequences: The role of the fronto-parietal mirror neuron system.

PubMed

Molnar-Szakacs, Istvan; Kaplan, Jonas; Greenfield, Patricia M; Iacoboni, Marco

2006-11-15

A fronto-parietal mirror neuron network in the human brain supports the ability to represent and understand observed actions allowing us to successfully interact with others and our environment. Using functional magnetic resonance imaging (fMRI), we wanted to investigate the response of this network in adults during observation of hierarchically organized action sequences of varying complexity that emerge at different developmental stages. We hypothesized that fronto-parietal systems may play a role in coding the hierarchical structure of object-directed actions. The observation of all action sequences recruited a common bilateral network including the fronto-parietal mirror neuron system and occipito-temporal visual motion areas. Activity in mirror neuron areas varied according to the motoric complexity of the observed actions, but not according to the developmental sequence of action structures, possibly due to the fact that our subjects were all adults. These results suggest that the mirror neuron system provides a fairly accurate simulation process of observed actions, mimicking internally the level of motoric complexity. We also discuss the results in terms of the links between mirror neurons, language development and evolution.

A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

PubMed

Li, Haohan; Mao, Yunxiang; Yin, Zhaozheng; Xu, Yingke

2017-09-01

Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neural Network (HCNN) method to automatically identify vesicle fusion events in time-lapse Total Internal Reflection Fluorescence Microscopy (TIRFM) image sequences. Firstly, a detection and tracking method is developed to extract image patch sequences containing potential fusion events. Then, a Gaussian Mixture Model (GMM) is applied on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. By utilizing the high-level time-series intensity change features introduced by GMM and the visual appearance features embedded in some key moments of the fusion process, the proposed HCNN architecture is able to classify each candidate patch sequence into three classes: full fusion event, partial fusion event and non-fusion event. Finally, we validate the performance of our method on 9 challenging datasets that have been annotated by cell biologists, and our method achieves better performances when comparing with three previous methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Principles of Quantitative MR Imaging with Illustrated Review of Applicable Modular Pulse Diagrams.

PubMed

Mills, Andrew F; Sakai, Osamu; Anderson, Stephan W; Jara, Hernan

2017-01-01

Continued improvements in diagnostic accuracy using magnetic resonance (MR) imaging will require development of methods for tissue analysis that complement traditional qualitative MR imaging studies. Quantitative MR imaging is based on measurement and interpretation of tissue-specific parameters independent of experimental design, compared with qualitative MR imaging, which relies on interpretation of tissue contrast that results from experimental pulse sequence parameters. Quantitative MR imaging represents a natural next step in the evolution of MR imaging practice, since quantitative MR imaging data can be acquired using currently available qualitative imaging pulse sequences without modifications to imaging equipment. The article presents a review of the basic physical concepts used in MR imaging and how quantitative MR imaging is distinct from qualitative MR imaging. Subsequently, the article reviews the hierarchical organization of major applicable pulse sequences used in this article, with the sequences organized into conventional, hybrid, and multispectral sequences capable of calculating the main tissue parameters of T1, T2, and proton density. While this new concept offers the potential for improved diagnostic accuracy and workflow, awareness of this extension to qualitative imaging is generally low. This article reviews the basic physical concepts in MR imaging, describes commonly measured tissue parameters in quantitative MR imaging, and presents the major available pulse sequences used for quantitative MR imaging, with a focus on the hierarchical organization of these sequences. © RSNA, 2017.

A Unified Theoretical Framework for Cognitive Sequencing.

PubMed

Savalia, Tejas; Shukla, Anuj; Bapi, Raju S

2016-01-01

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks.

A Unified Theoretical Framework for Cognitive Sequencing

PubMed Central

Savalia, Tejas; Shukla, Anuj; Bapi, Raju S.

2016-01-01

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks. PMID:27917146

General cognitive principles for learning structure in time and space.

PubMed

Goldstein, Michael H; Waterfall, Heidi R; Lotem, Arnon; Halpern, Joseph Y; Schwade, Jennifer A; Onnis, Luca; Edelman, Shimon

2010-06-01

How are hierarchically structured sequences of objects, events or actions learned from experience and represented in the brain? When several streams of regularities present themselves, which will be learned and which ignored? Can statistical regularities take effect on their own, or are additional factors such as behavioral outcomes expected to influence statistical learning? Answers to these questions are starting to emerge through a convergence of findings from naturalistic observations, behavioral experiments, neurobiological studies, and computational analyses and simulations. We propose that a small set of principles are at work in every situation that involves learning of structure from patterns of experience and outline a general framework that accounts for such learning. (c) 2010 Elsevier Ltd. All rights reserved.

Hierarchical recruitment of ribosomal proteins and assembly factors remodels nucleolar pre-60S ribosomes.

PubMed

Biedka, Stephanie; Micic, Jelena; Wilson, Daniel; Brown, Hailey; Diorio-Toth, Luke; Woolford, John L

2018-04-24

Ribosome biogenesis involves numerous preribosomal RNA (pre-rRNA) processing events to remove internal and external transcribed spacer sequences, ultimately yielding three mature rRNAs. Removal of the internal transcribed spacer 2 spacer RNA is the final step in large subunit pre-rRNA processing and begins with endonucleolytic cleavage at the C 2 site of 27SB pre-rRNA. C 2 cleavage requires the hierarchical recruitment of 11 ribosomal proteins and 14 ribosome assembly factors. However, the function of these proteins in C 2 cleavage remained unclear. In this study, we have performed a detailed analysis of the effects of depleting proteins required for C 2 cleavage and interpreted these results using cryo-electron microscopy structures of assembling 60S subunits. This work revealed that these proteins are required for remodeling of several neighborhoods, including two major functional centers of the 60S subunit, suggesting that these remodeling events form a checkpoint leading to C 2 cleavage. Interestingly, when C 2 cleavage is directly blocked by depleting or inactivating the C 2 endonuclease, assembly progresses through all other subsequent steps. © 2018 Biedka et al.

Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

NASA Astrophysics Data System (ADS)

Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

2017-07-01

Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

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

Dissecting children's observational learning of complex actions through selective video displays.

PubMed

Flynn, Emma; Whiten, Andrew

2013-10-01

Children can learn how to use complex objects by watching others, yet the relative importance of different elements they may observe, such as the interactions of the individual parts of the apparatus, a model's movements, and desirable outcomes, remains unclear. In total, 140 3-year-olds and 140 5-year-olds participated in a study where they observed a video showing tools being used to extract a reward item from a complex puzzle box. Conditions varied according to the elements that could be seen in the video: (a) the whole display, including the model's hands, the tools, and the box; (b) the tools and the box but not the model's hands; (c) the model's hands and the tools but not the box; (d) only the end state with the box opened; and (e) no demonstration. Children's later attempts at the task were coded to establish whether they imitated the hierarchically organized sequence of the model's actions, the action details, and/or the outcome. Children's successful retrieval of the reward from the box and the replication of hierarchical sequence information were reduced in all but the whole display condition. Only once children had attempted the task and witnessed a second demonstration did the display focused on the tools and box prove to be better for hierarchical sequence information than the display focused on the tools and hands only. Copyright © 2013 Elsevier Inc. All rights reserved.

A low-cost hierarchical nanostructured beta-titanium alloy with high strength

PubMed Central

Devaraj, Arun; Joshi, Vineet V.; Srivastava, Ankit; Manandhar, Sandeep; Moxson, Vladimir; Duz, Volodymyr A.; Lavender, Curt

2016-01-01

Lightweighting of automobiles by use of novel low-cost, high strength-to-weight ratio structural materials can reduce the consumption of fossil fuels and in turn CO2 emission. Working towards this goal we achieved high strength in a low cost β-titanium alloy, Ti–1Al–8V–5Fe (Ti185), by hierarchical nanostructure consisting of homogenous distribution of micron-scale and nanoscale α-phase precipitates within the β-phase matrix. The sequence of phase transformation leading to this hierarchical nanostructure is explored using electron microscopy and atom probe tomography. Our results suggest that the high number density of nanoscale α-phase precipitates in the β-phase matrix is due to ω assisted nucleation of α resulting in high tensile strength, greater than any current commercial titanium alloy. Thus hierarchical nanostructured Ti185 serves as an excellent candidate for replacing costlier titanium alloys and other structural alloys for cost-effective lightweighting applications. PMID:27034109

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

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

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

Identification of transcriptome involved in atrazine detoxification and degradation in alfalfa (Medicago sativa) exposed to realistic environmental contamination.

PubMed

Zhang, Jing Jing; Lu, Yi Chen; Zhang, Shu Hao; Lu, Feng Fan; Yang, Hong

2016-08-01

Plants are constantly exposed to a variety of toxic compounds (or xenobiotics) such as pesticides (or herbicides). Atrazine (ATZ) as herbicide has become one of the environmental contaminants due to its intensive use during crop production. Plants have evolved strategies to cope with the adverse impact of ATZ. However, the mechanism for ATZ degradation and detoxification in plants is largely unknown. Here we employed a global RNA-sequencing (RNA-Seq) strategy to dissect transcriptome variation in alfalfa (Medicago sativa) exposed to ATZ. Four libraries were constructed including Root-ATZ (root control, ATZ-free), Shoot-ATZ, Root+ATZ (root treated with ATZ) and Shoot+ATZ. Hierarchical clustering was performed to display the expression patterns for all differentially expressed genes (DEGs) under ATZ exposure. Transcripts involved in ATZ detoxification, stress responses (e.g. oxidation and reduction, conjugation and hydrolytic reactions), and regulations of cysteine biosynthesis were identified. Several genes encoding glycosyltransferases, glutathione S-transferases or ABC transporters were up-regulated notably. Also, many other genes involved in oxidation-reduction, conjugation, and hydrolysis for herbicide degradation were differentially expressed. These results suggest that ATZ in alfalfa can be detoxified or degraded through different pathways. The expression patterns of some DEGs by high-throughput sequencing were well confirmed by qRT-PCR. Our results not only highlight the transcriptional complexity in alfalfa exposed to ATZ but represent a major improvement for analyzing transcriptional changes on a large scale as well. Copyright © 2016 Elsevier Inc. All rights reserved.

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 structure in sharply divided phase space for the piecewise linear map

NASA Astrophysics Data System (ADS)

Akaishi, Akira; Aoki, Kazuki; Shudo, Akira

2017-05-01

We have studied a two-dimensional piecewise linear map to examine how the hierarchical structure of stable regions affects the slow dynamics in Hamiltonian systems. In the phase space there are infinitely many stable regions, each of which is polygonal-shaped, and the rest is occupied by chaotic orbits. By using symbolic representation of stable regions, a procedure to compute the edges of the polygons is presented. The stable regions are hierarchically distributed in phase space and the edges of the stable regions show the marginal instability. The cumulative distribution of the recurrence time obeys a power law as ˜t-2 , the same as the one for the system with phase space, which is composed of a single stable region and chaotic components. By studying the symbol sequence of recurrence trajectories, we show that the hierarchical structure of stable regions has no significant effect on the power-law exponent and that only the marginal instability on the boundary of stable regions is responsible for determining the exponent. We also discuss the relevance of the hierarchical structure to those in more generic chaotic systems.

Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics

PubMed Central

Nakai, Tomoya; Sakai, Kuniyoshi L.

2014-01-01

Whether mathematical and linguistic processes share the same neural mechanisms has been a matter of controversy. By examining various sentence structures, we recently demonstrated that activations in the left inferior frontal gyrus (L. IFG) and left supramarginal gyrus (L. SMG) were modulated by the Degree of Merger (DoM), a measure for the complexity of tree structures. In the present study, we hypothesize that the DoM is also critical in mathematical calculations, and clarify whether the DoM in the hierarchical tree structures modulates activations in these regions. We tested an arithmetic task that involved linear and quadratic sequences with recursive computation. Using functional magnetic resonance imaging, we found significant activation in the L. IFG, L. SMG, bilateral intraparietal sulcus (IPS), and precuneus selectively among the tested conditions. We also confirmed that activations in the L. IFG and L. SMG were free from memory-related factors, and that activations in the bilateral IPS and precuneus were independent from other possible factors. Moreover, by fitting parametric models of eight factors, we found that the model of DoM in the hierarchical tree structures was the best to explain the modulation of activations in these five regions. Using dynamic causal modeling, we showed that the model with a modulatory effect for the connection from the L. IPS to the L. IFG, and with driving inputs into the L. IFG, was highly probable. The intrinsic, i.e., task-independent, connection from the L. IFG to the L. IPS, as well as that from the L. IPS to the R. IPS, would provide a feedforward signal, together with negative feedback connections. We indicate that mathematics and language share the network of the L. IFG and L. IPS/SMG for the computation of hierarchical tree structures, and that mathematics recruits the additional network of the L. IPS and R. IPS. PMID:25379713

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.

Multiple bottlenecks in hierarchical control of action sequences: what does "response selection" select in skilled typewriting?

PubMed

Yamaguchi, Motonori; Logan, Gordon D; Li, Vanessa

2013-08-01

Does response selection select words or letters in skilled typewriting? Typing performance involves hierarchically organized control processes: an outer loop that controls word level processing, and an inner loop that controls letter (or keystroke) level processing. The present study addressed whether response selection occurs in the outer loop or the inner loop by using the psychological refractory period (PRP) paradigm in which Task1 required typing single words and Task2 required vocal responses to tones. The number of letters (string length) in the words was manipulated to discriminate selection of words from selection of keystrokes. In Experiment 1, the PRP effect depended on string length of words in Task1, suggesting that response selection occurs in the inner loop. To assess contributions of the outer loop, the influence of string length was examined in a lexical-decision task that also involves word encoding and lexical access (Experiment 2), or to-be-typed words were preexposed so outer-loop processing could finish before typing started (Experiment 3). Response time for Task2 (RT2) did not depend on string length with lexical decision, and RT2 still depended on string length with typing preexposed strings. These results support the inner-loop locus of the PRP effect. In Experiment 4, typing was performed as Task2, and the effect of string length on typing RT interacted with stimulus onset asynchrony superadditively, implying that another bottleneck also exists in the outer loop. We conclude that there are at least two bottleneck processes in skilled typewriting. 2013 APA, all rights reserved

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.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Contrasting patterns of variation in weedy traits and unique crop features in divergent populations of US weedy rice (Oryza sativa sp.) in Arkansas and California.

PubMed

Kanapeckas, Kimberly L; Tseng, Te-Ming; Vigueira, Cynthia C; Ortiz, Aida; Bridges, William C; Burgos, Nilda R; Fischer, Albert J; Lawton-Rauh, Amy

2018-06-01

Weed evolution from crops involves changes in key traits, but it is unclear how genetic and phenotypic variation contribute to weed diversification and productivity. Weedy rice is a conspecific weed of rice (Oryza sativa) worldwide. We used principal component analysis and hierarchical clustering to understand how morphologically and evolutionarily distinct US weedy rice populations persist in rice fields in different locations under contrasting management regimes. Further, we used a representative subset of 15 sequence-tagged site fragments of expressed genes from global Oryza to assess genome-wide sequence variation among populations. Crop hull color and crop-overlapping maturity dates plus awns, seed (panicle) shattering (> 50%), pigmented pericarp and stature variation (30.2% of total phenotypic variance) characterize genetically less diverse California weedy rice. By contrast, wild-like hull color, seed shattering (> 50%) and stature differences (55.8% of total phenotypic variance) typify genetically diverse weedy rice ecotypes in Arkansas. Recent de-domestication of weedy species - such as in California weedy rice - can involve trait combinations indistinguishable from the crop. This underscores the need for strict seed certification with genetic monitoring and proactive field inspection to prevent proliferation of weedy plant types. In established populations, tillage practice may affect weed diversity and persistence over time. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Context and meter enhance long-range planning in music performance

PubMed Central

Mathias, Brian; Pfordresher, Peter Q.; Palmer, Caroline

2015-01-01

Neural responses demonstrate evidence of resonance, or oscillation, during the production of periodic auditory events. Music contains periodic auditory events that give rise to a sense of beat, which in turn generates a sense of meter on the basis of multiple periodicities. Metrical hierarchies may aid memory for music by facilitating similarity-based associations among sequence events at different periodic distances that unfold in longer contexts. A fundamental question is how metrical associations arising from a musical context influence memory during music performance. Longer contexts may facilitate metrical associations at higher hierarchical levels more than shorter contexts, a prediction of the range model, a formal model of planning processes in music performance (Palmer and Pfordresher, 2003; Pfordresher et al., 2007). Serial ordering errors, in which intended sequence events are produced in incorrect sequence positions, were measured as skilled pianists performed musical pieces that contained excerpts embedded in long or short musical contexts. Pitch errors arose from metrically similar positions and further sequential distances more often when the excerpt was embedded in long contexts compared to short contexts. Musicians’ keystroke intensities and error rates also revealed influences of metrical hierarchies, which differed for performances in long and short contexts. The range model accounted for contextual effects and provided better fits to empirical findings when metrical associations between sequence events were included. Longer sequence contexts may facilitate planning during sequence production by increasing conceptual similarity between hierarchically associated events. These findings are consistent with the notion that neural oscillations at multiple periodicities may strengthen metrical associations across sequence events during planning. PMID:25628550

A low-cost hierarchical nanostructured beta-titanium alloy with high strength

DOE PAGES

Devaraj, Arun; Joshi, Vineet V.; Srivastava, Ankit; ...

2016-04-01

Lightweighting of automobiles by use of novel low-cost, high strength-to-weight ratio structural materials can reduce the consumption of fossil fuels and in turn CO 2 emission. Working towards this goal we achieved high strength in a low cost β-titanium alloy, Ti-1Al-8V-5Fe (Ti185), by hierarchical nanostructure consisting of homogenous distribution of micron-scale and nanoscale α-phase precipitates within the β-phase matrix. The sequence of phase transformation leading to this hierarchical nanostructure is explored using electron microscopy and atom probe tomography. Our results suggest that the high number density of nanoscale α-phase precipitates in the β-phase matrix is due to ω assisted nucleationmore » of α resulting in high tensile strength, greater than any current commercial titanium alloy. Furthermore hierarchical nanostructured Ti185 serves as an excellent candidate for replacing costlier titanium alloys and other structural alloys for cost-effective lightweighting applications.« less

A low-cost hierarchical nanostructured beta-titanium alloy with high strength

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

Devaraj, Arun; Joshi, Vineet V.; Srivastava, Ankit

Lightweighting of automobiles by use of novel low-cost, high strength-to-weight ratio structural materials can reduce the consumption of fossil fuels and in turn CO 2 emission. Working towards this goal we achieved high strength in a low cost β-titanium alloy, Ti-1Al-8V-5Fe (Ti185), by hierarchical nanostructure consisting of homogenous distribution of micron-scale and nanoscale α-phase precipitates within the β-phase matrix. The sequence of phase transformation leading to this hierarchical nanostructure is explored using electron microscopy and atom probe tomography. Our results suggest that the high number density of nanoscale α-phase precipitates in the β-phase matrix is due to ω assisted nucleationmore » of α resulting in high tensile strength, greater than any current commercial titanium alloy. Furthermore hierarchical nanostructured Ti185 serves as an excellent candidate for replacing costlier titanium alloys and other structural alloys for cost-effective lightweighting applications.« less

Three-dimensional information hierarchical encryption based on computer-generated holograms

NASA Astrophysics Data System (ADS)

Kong, Dezhao; Shen, Xueju; Cao, Liangcai; Zhang, Hao; Zong, Song; Jin, Guofan

2016-12-01

A novel approach for encrypting three-dimensional (3-D) scene information hierarchically based on computer-generated holograms (CGHs) is proposed. The CGHs of the layer-oriented 3-D scene information are produced by angular-spectrum propagation algorithm at different depths. All the CGHs are then modulated by different chaotic random phase masks generated by the logistic map. Hierarchical encryption encoding is applied when all the CGHs are accumulated one by one, and the reconstructed volume of the 3-D scene information depends on permissions of different users. The chaotic random phase masks could be encoded into several parameters of the chaotic sequences to simplify the transmission and preservation of the keys. Optical experiments verify the proposed method and numerical simulations show the high key sensitivity, high security, and application flexibility of the method.

Multi person detection and tracking based on hierarchical level-set method

NASA Astrophysics Data System (ADS)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

Hierarchical planning for a surface mounting machine placement.

PubMed

Zeng, You-jiao; Ma, Deng-ze; Jin, Ye; Yan, Jun-qi

2004-11-01

For a surface mounting machine (SMM) in printed circuit board (PCB) assembly line, there are four problems, e.g. CAD data conversion, nozzle selection, feeder assignment and placement sequence determination. A hierarchical planning for them to maximize the throughput rate of an SMM is presented here. To minimize set-up time, a CAD data conversion system was first applied that could automatically generate the data for machine placement from CAD design data files. Then an effective nozzle selection approach implemented to minimize the time of nozzle changing. And then, to minimize picking time, an algorithm for feeder assignment was used to make picking multiple components simultaneously as much as possible. Finally, in order to shorten pick-and-place time, a heuristic algorithm was used to determine optimal component placement sequence according to the decided feeder positions. Experiments were conducted on a four head SMM. The experimental results were used to analyse the assembly line performance.

Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants.

PubMed

Werchan, Denise M; Collins, Anne G E; Frank, Michael J; Amso, Dima

2016-10-05

Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object-label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. Copyright © 2016 the authors 0270-6474/16/3610314-09$15.00/0.

Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants

PubMed Central

Werchan, Denise M.; Collins, Anne G.E.; Frank, Michael J.

2016-01-01

Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object–label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. SIGNIFICANCE STATEMENT Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. PMID:27707968

Highly efficient decomposition of organic dye by aqueous-solid phase transfer and in situ photocatalysis using hierarchical copper phthalocyanine hollow spheres.

PubMed

Zhang, Mingyi; Shao, Changlu; Guo, Zengcai; Zhang, Zhenyi; Mu, Jingbo; Zhang, Peng; Cao, Tieping; Liu, Yichun

2011-07-01

The hierarchical tetranitro copper phthalocyanine (TNCuPc) hollow spheres were fabricated by a simple solvothermal method. The formation mechanism was proposed based on the evolution of morphology as a function of solvothermal time, which involved the initial formation of nanoparticles followed by their self-aggregation to microspheres and transformation into hierarchical hollow spheres by Ostwald ripening. Furthermore, the hierarchical TNCuPc hollow spheres exhibited high adsorption capacity and excellent simultaneously visible-light-driven photocatalytic performance for Rhodamine B (RB) under visible light. A possible mechanism for the "aqueous-solid phase transfer and in situ photocatalysis" was suggested. Repetitive tests showed that the hierarchical TNCuPc hollow spheres maintained high catalytic activity over several cycles, and it had a better regeneration capability under mild conditions.

Exploring Dance Movement Data Using Sequence Alignment Methods

PubMed Central

Chavoshi, Seyed Hossein; De Baets, Bernard; Neutens, Tijs; De Tré, Guy; Van de Weghe, Nico

2015-01-01

Despite the abundance of research on knowledge discovery from moving object databases, only a limited number of studies have examined the interaction between moving point objects in space over time. This paper describes a novel approach for measuring similarity in the interaction between moving objects. The proposed approach consists of three steps. First, we transform movement data into sequences of successive qualitative relations based on the Qualitative Trajectory Calculus (QTC). Second, sequence alignment methods are applied to measure the similarity between movement sequences. Finally, movement sequences are grouped based on similarity by means of an agglomerative hierarchical clustering method. The applicability of this approach is tested using movement data from samba and tango dancers. PMID:26181435

Predicting helix–helix interactions from residue contacts in membrane proteins

PubMed Central

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

2009-01-01

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

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

NASA Technical Reports Server (NTRS)

Padovan, Joseph; Krishna, Lala; Gute, Douglas

1997-01-01

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

Spatial-area selective retrieval of multiple object-place associations in a hierarchical cognitive map formed by theta phase coding.

PubMed

Sato, Naoyuki; Yamaguchi, Yoko

2009-06-01

The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.

Neural evidence for predictive coding in auditory cortex during speech production.

PubMed

Okada, Kayoko; Matchin, William; Hickok, Gregory

2018-02-01

Recent models of speech production suggest that motor commands generate forward predictions of the auditory consequences of those commands, that these forward predications can be used to monitor and correct speech output, and that this system is hierarchically organized (Hickok, Houde, & Rong, Neuron, 69(3), 407--422, 2011; Pickering & Garrod, Behavior and Brain Sciences, 36(4), 329--347, 2013). Recent psycholinguistic research has shown that internally generated speech (i.e., imagined speech) produces different types of errors than does overt speech (Oppenheim & Dell, Cognition, 106(1), 528--537, 2008; Oppenheim & Dell, Memory & Cognition, 38(8), 1147-1160, 2010). These studies suggest that articulated speech might involve predictive coding at additional levels than imagined speech. The current fMRI experiment investigates neural evidence of predictive coding in speech production. Twenty-four participants from UC Irvine were recruited for the study. Participants were scanned while they were visually presented with a sequence of words that they reproduced in sync with a visual metronome. On each trial, they were cued to either silently articulate the sequence or to imagine the sequence without overt articulation. As expected, silent articulation and imagined speech both engaged a left hemisphere network previously implicated in speech production. A contrast of silent articulation with imagined speech revealed greater activation for articulated speech in inferior frontal cortex, premotor cortex and the insula in the left hemisphere, consistent with greater articulatory load. Although both conditions were silent, this contrast also produced significantly greater activation in auditory cortex in dorsal superior temporal gyrus in both hemispheres. We suggest that these activations reflect forward predictions arising from additional levels of the perceptual/motor hierarchy that are involved in monitoring the intended speech output.

Comparing the loss of functional independence of older adults in the U.S. and China.

PubMed

Fong, Joelle H; Feng, Jun

2018-01-01

Functional loss among older adults is known to follow a hierarchical sequence, but little is known about whether such sequences differ across socio-cultural contexts. The aim of this study is to construct activities of daily livings (ADL) scales for oldest-old adults in the United States and China so as to compare their functional loss sequences. We use data from the Asset and Health Dynamics of the Oldest Old (n=1607) and Chinese Longitudinal Healthy Longevity Survey (n=5570) for years 1998-2008. ADL items are calibrated within a scale using the Rasch measurement model. Rasch scores are averaged across survey waves to identify the ADL loss sequence for each study population. We also assess scale stability over measurement periods. Factor analyses confirm that the ADL items in each study population can be combined meaningfully to form a hierarchical sequence. Internal consistency assessed by Cronbach's alpha is high (0.81 to 0.95). We find that bathing is the first activity that both older Americans and Chinese have difficulty with, while eating is the last activity. There are, however, differences in the rank order for toileting (ranked more challenging in the Chinese sample) and dressing (ranked more challenging in the U.S. sample). Item orderings are stable over time. The results highlight the relative importance of bathing in the functional loss sequence for older adults, regardless of socio-cultural context. Health interventions are needed to address deficits in the bathroom environment, especially in developing countries like China. Copyright © 2017 Elsevier B.V. All rights reserved.

Top 10 Lines of Evidence for Human Evolution.

ERIC Educational Resources Information Center

Nickels, Martin

2001-01-01

Provides 10 lines of evidence that support the theory of human evolution. The evidence relates to hierarchical taxonomic classification, comparative anatomy, comparative embryology and development, comparative biochemistry, adaptive compromises, vestigial structures, biogeography, the fossil sequence, ecological coherence of fossil assemblages,…

Sequential stages and distribution patterns of aging-related tau astrogliopathy (ARTAG) in the human brain.

PubMed

Kovacs, Gabor G; Xie, Sharon X; Robinson, John L; Lee, Edward B; Smith, Douglas H; Schuck, Theresa; Lee, Virginia M-Y; Trojanowski, John Q

2018-06-11

Aging-related tau astrogliopathy (ARTAG) describes tau pathology in astrocytes in different locations and anatomical regions. In the present study we addressed the question of whether sequential distribution patterns can be recognized for ARTAG or astroglial tau pathologies in both primary FTLD-tauopathies and non-FTLD-tauopathy cases. By evaluating 687 postmortem brains with diverse disorders we identified ARTAG in 455. We evaluated frequencies and hierarchical clustering of anatomical involvement and used conditional probability and logistic regression to model the sequential distribution of ARTAG and astroglial tau pathologies across different brain regions. For subpial and white matter ARTAG we recognize three and two patterns, respectively, each with three stages initiated or ending in the amygdala. Subependymal ARTAG does not show a clear sequential pattern. For grey matter (GM) ARTAG we recognize four stages including a striatal pathway of spreading towards the cortex and/or amygdala, and the brainstem, and an amygdala pathway, which precedes the involvement of the striatum and/or cortex and proceeds towards the brainstem. GM ARTAG and astrocytic plaque pathology in corticobasal degeneration follows a predominantly frontal-parietal cortical to temporal-occipital cortical, to subcortical, to brainstem pathway (four stages). GM ARTAG and tufted astrocyte pathology in progressive supranuclear palsy shows a striatum to frontal-parietal cortical to temporal to occipital, to amygdala, and to brainstem sequence (four stages). In Pick's disease cases with astroglial tau pathology an overlapping pattern with PSP can be appreciated. We conclude that tau-astrogliopathy type-specific sequential patterns cannot be simplified as neuron-based staging systems. The proposed cytopathological and hierarchical stages provide a conceptual approach to identify the initial steps of the pathogenesis of tau pathologies in ARTAG and primary FTLD-tauopathies.

The time course of auditory-visual processing of speech and body actions: evidence for the simultaneous activation of an extended neural network for semantic processing.

PubMed

Meyer, Georg F; Harrison, Neil R; Wuerger, Sophie M

2013-08-01

An extensive network of cortical areas is involved in multisensory object and action recognition. This network draws on inferior frontal, posterior temporal, and parietal areas; activity is modulated by familiarity and the semantic congruency of auditory and visual component signals even if semantic incongruences are created by combining visual and auditory signals representing very different signal categories, such as speech and whole body actions. Here we present results from a high-density ERP study designed to examine the time-course and source location of responses to semantically congruent and incongruent audiovisual speech and body actions to explore whether the network involved in action recognition consists of a hierarchy of sequentially activated processing modules or a network of simultaneously active processing sites. We report two main results:1) There are no significant early differences in the processing of congruent and incongruent audiovisual action sequences. The earliest difference between congruent and incongruent audiovisual stimuli occurs between 240 and 280 ms after stimulus onset in the left temporal region. Between 340 and 420 ms, semantic congruence modulates responses in central and right frontal areas. Late differences (after 460 ms) occur bilaterally in frontal areas.2) Source localisation (dipole modelling and LORETA) reveals that an extended network encompassing inferior frontal, temporal, parasaggital, and superior parietal sites are simultaneously active between 180 and 420 ms to process auditory–visual action sequences. Early activation (before 120 ms) can be explained by activity in mainly sensory cortices. . The simultaneous activation of an extended network between 180 and 420 ms is consistent with models that posit parallel processing of complex action sequences in frontal, temporal and parietal areas rather than models that postulate hierarchical processing in a sequence of brain regions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automated hierarchical time gain compensation for in-vivo ultrasound imaging

NASA Astrophysics Data System (ADS)

Moshavegh, Ramin; Hemmsen, Martin C.; Martins, Bo; Brandt, Andreas H.; Hansen, Kristoffer L.; Nielsen, Michael B.; Jensen, Jørgen A.

2015-03-01

Time gain compensation (TGC) is essential to ensure the optimal image quality of the clinical ultrasound scans. When large fluid collections are present within the scan plane, the attenuation distribution is changed drastically and TGC compensation becomes challenging. This paper presents an automated hierarchical TGC (AHTGC) algorithm that accurately adapts to the large attenuation variation between different types of tissues and structures. The algorithm relies on estimates of tissue attenuation, scattering strength, and noise level to gain a more quantitative understanding of the underlying tissue and the ultrasound signal strength. The proposed algorithm was applied to a set of 44 in vivo abdominal movie sequences each containing 15 frames. Matching pairs of in vivo sequences, unprocessed and processed with the proposed AHTGC were visualized side by side and evaluated by two radiologists in terms of image quality. Wilcoxon signed-rank test was used to evaluate whether radiologists preferred the processed sequences or the unprocessed data. The results indicate that the average visual analogue scale (VAS) is positive ( p-value: 2.34 × 10-13) and estimated to be 1.01 (95% CI: 0.85; 1.16) favoring the processed data with the proposed AHTGC algorithm.

Sequence-Mandated, Distinct Assembly of Giant Molecules

DOE PAGES

Zhang, Wei; Lu, Xinlin; Mao, Jialin; ...

2017-10-24

Although controlling the primary structure of synthetic polymers is itself a great challenge, the potential of sequence control for tailoring hierarchical structures remains to be exploited, especially in the creation of new and unconventional phases. A series of model amphiphilic chain-like giant molecules was designed and synthesized by interconnecting both hydrophobic and hydrophilic molecular nanoparticles in precisely defined sequence and composition to investigate their sequence-dependent phase structures. Not only compositional variation changed the self-assembled supramolecular phases, but also specific sequences induce unconventional phase formation, including Frank-Kasper phases. The formation mechanism was attributed to the conformational change driven by the collectivemore » hydrogen bonding and the sequence-mandated topology of the molecules. Lastly, these results show that sequence control in synthetic polymers can have a dramatic impact on polymer properties and self-assembly.« less

Sequence-Mandated, Distinct Assembly of Giant Molecules

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

Zhang, Wei; Lu, Xinlin; Mao, Jialin

Although controlling the primary structure of synthetic polymers is itself a great challenge, the potential of sequence control for tailoring hierarchical structures remains to be exploited, especially in the creation of new and unconventional phases. A series of model amphiphilic chain-like giant molecules was designed and synthesized by interconnecting both hydrophobic and hydrophilic molecular nanoparticles in precisely defined sequence and composition to investigate their sequence-dependent phase structures. Not only compositional variation changed the self-assembled supramolecular phases, but also specific sequences induce unconventional phase formation, including Frank-Kasper phases. The formation mechanism was attributed to the conformational change driven by the collectivemore » hydrogen bonding and the sequence-mandated topology of the molecules. Lastly, these results show that sequence control in synthetic polymers can have a dramatic impact on polymer properties and self-assembly.« less

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.

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

ERIC Educational Resources Information Center

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

2013-01-01

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

Construction of a map-based reference genome sequence for barley, Hordeum vulgare L.

PubMed Central

Beier, Sebastian; Himmelbach, Axel; Colmsee, Christian; Zhang, Xiao-Qi; Barrero, Roberto A.; Zhang, Qisen; Li, Lin; Bayer, Micha; Bolser, Daniel; Taudien, Stefan; Groth, Marco; Felder, Marius; Hastie, Alex; Šimková, Hana; Staňková, Helena; Vrána, Jan; Chan, Saki; Muñoz-Amatriaín, María; Ounit, Rachid; Wanamaker, Steve; Schmutzer, Thomas; Aliyeva-Schnorr, Lala; Grasso, Stefano; Tanskanen, Jaakko; Sampath, Dharanya; Heavens, Darren; Cao, Sujie; Chapman, Brett; Dai, Fei; Han, Yong; Li, Hua; Li, Xuan; Lin, Chongyun; McCooke, John K.; Tan, Cong; Wang, Songbo; Yin, Shuya; Zhou, Gaofeng; Poland, Jesse A.; Bellgard, Matthew I.; Houben, Andreas; Doležel, Jaroslav; Ayling, Sarah; Lonardi, Stefano; Langridge, Peter; Muehlbauer, Gary J.; Kersey, Paul; Clark, Matthew D.; Caccamo, Mario; Schulman, Alan H.; Platzer, Matthias; Close, Timothy J.; Hansson, Mats; Zhang, Guoping; Braumann, Ilka; Li, Chengdao; Waugh, Robbie; Scholz, Uwe; Stein, Nils; Mascher, Martin

2017-01-01

Barley (Hordeum vulgare L.) is a cereal grass mainly used as animal fodder and raw material for the malting industry. The map-based reference genome sequence of barley cv. ‘Morex’ was constructed by the International Barley Genome Sequencing Consortium (IBSC) using hierarchical shotgun sequencing. Here, we report the experimental and computational procedures to (i) sequence and assemble more than 80,000 bacterial artificial chromosome (BAC) clones along the minimum tiling path of a genome-wide physical map, (ii) find and validate overlaps between adjacent BACs, (iii) construct 4,265 non-redundant sequence scaffolds representing clusters of overlapping BACs, and (iv) order and orient these BAC clusters along the seven barley chromosomes using positional information provided by dense genetic maps, an optical map and chromosome conformation capture sequencing (Hi-C). Integrative access to these sequence and mapping resources is provided by the barley genome explorer (BARLEX). PMID:28448065

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.

Universal Method for Creating Hierarchical Wrinkles on Thin-Film Surfaces.

PubMed

Jung, Woo-Bin; Cho, Kyeong Min; Lee, Won-Kyu; Odom, Teri W; Jung, Hee-Tae

2018-01-10

One of the most interesting topics in physical science and materials science is the creation of complex wrinkled structures on thin-film surfaces because of their several advantages of high surface area, localized strain, and stress tolerance. In this study, a significant step was taken toward solving limitations imposed by the fabrication of previous artificial wrinkles. A universal method for preparing hierarchical three-dimensional wrinkle structures of thin films on a multiple scale (e.g., nanometers to micrometers) by sequential wrinkling with different skin layers was developed. Notably, this method was not limited to specific materials, and it was applicable to fabricating hierarchical wrinkles on all of the thin-film surfaces tested thus far, including those of metals, two-dimensional and one-dimensional materials, and polymers. The hierarchical wrinkles with multiscale structures were prepared by sequential wrinkling, in which a sacrificial layer was used as the additional skin layer between sequences. For example, a hierarchical MoS 2 wrinkle exhibited highly enhanced catalytic behavior because of the superaerophobicity and effective surface area, which are related to topological effects. As the developed method can be adopted to a majority of thin films, it is thought to be a universal method for enhancing the physical properties of various materials.

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

PubMed Central

Badre, David

2012-01-01

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

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

The VMC Survey. XXVII. Young Stellar Structures in the LMC’s Bar Star-forming Complex

NASA Astrophysics Data System (ADS)

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

2017-11-01

Star formation is a hierarchical process, forming young stellar structures of star clusters, associations, and complexes over a wide range of scales. The star-forming complex in the bar region of the Large Magellanic Cloud is investigated with upper main-sequence stars observed by the VISTA Survey of the Magellanic Clouds. The upper main-sequence stars exhibit highly nonuniform distributions. Young stellar structures inside the complex are identified from the stellar density map as density enhancements of different significance levels. We find that these structures are hierarchically organized such that larger, lower-density structures contain one or several smaller, higher-density ones. They follow power-law size and mass distributions, as well as a lognormal surface density distribution. All these results support a scenario of hierarchical star formation regulated by turbulence. The temporal evolution of young stellar structures is explored by using subsamples of upper main-sequence stars with different magnitude and age ranges. While the youngest subsample, with a median age of log(τ/yr) = 7.2, contains the most substructure, progressively older ones are less and less substructured. The oldest subsample, with a median age of log(τ/yr) = 8.0, is almost indistinguishable from a uniform distribution on spatial scales of 30-300 pc, suggesting that the young stellar structures are completely dispersed on a timescale of ˜100 Myr. These results are consistent with the characteristics of the 30 Doradus complex and the entire Large Magellanic Cloud, suggesting no significant environmental effects. We further point out that the fractal dimension may be method dependent for stellar samples with significant age spreads.

A Structural Approach to the Validation of Hierarchical Training Sequences

DTIC Science & Technology

1981-06-01

consideration as can be examinedI -11- within existing constraints on time and resources. Second, for each con- nection to be studied, identify groups ... one group of learners who are taught all skills in a linear sequence whereas many groups learning different skills are needed to implement the White...meability. For example, suppose that a group of item sets were used to assess performance on three academic tasks, A, B, and C. Assume that task A was

Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

PubMed

Chang, Xiao; Liu, Shuai; Yu, Yong-Tao; Li, Yi-Xue; Li, Yuan-Yuan

2010-08-12

The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.

Cross-validation to select Bayesian hierarchical models in phylogenetics.

PubMed

Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C

2016-05-26

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

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.

The Origin of Time in the Songbird Motor Pathway

NASA Astrophysics Data System (ADS)

Long, Michael

2010-03-01

Many complex behaviors, like speech or music, have a hierarchical organization with structure on many timescales. How does the brain control the timing and ordering of behavioral sequences? Do different circuits control different timescales of the behavior? To begin answering these questions, we use temperature to manipulate the biophysical dynamics in different regions of the songbird forebrain involved in song production. We found that cooling premotor nucleus HVC (high vocal center) uniformly slows song speed by up to 40% while only slightly altering the acoustic structure, whereas cooling downstream motor nucleus RA (robust nucleus of the arcopallium) has no observable effect on song timing, despite a marked affect of RA spiking activity. To better understand the circuit mechanisms of precise premotor timing, we perform intracellular recordings in RA-projecting HVC neurons during singing. Our observations suggest highly ordered dynamics within HVC which are consistent with a synfire-like neuronal architecture.

The coach-athlete relationship: a motivational model.

PubMed

Mageau, Geneviève A; Vallerand, Robert J

2003-11-01

The aim of this paper is to present a motivational model of the coach-athlete relationship that describes how coaches may influence athletes' motivation. In line with cognitive evaluation theory (Deci and Ryan, 1980, 1985) and the hierarchical model of intrinsic and extrinsic motivation (Vallerand, 1997, 2000), a motivational sequence is proposed where coaches' personal orientation towards coaching, the context within which they operate, and their perceptions of their athletes' behaviour and motivation influence coaches' behaviours. Also, coaches' behaviours in the form of autonomy-supportive behaviours, provision of structure and involvement have a beneficial impact on athletes' needs for autonomy, competence and relatedness, which, in turn, nurture athletes' intrinsic motivation and self-determined types of extrinsic motivation. Here, we first review coaches' autonomy-supportive behaviours. We then describe the psychological processes through which coaching behaviours have a positive influence on athletes' intrinsic and self-determined extrinsic motivation. Finally, we identify social and personality processes that determine coaching behaviours.

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

Clausen, Drew; Wade, Richard A., E-mail: dclausen@astro.psu.edu, E-mail: wade@astro.psu.edu

Many hot subdwarf B stars (sdBs) are in close binaries, and the favored formation channels for subdwarfs rely on mass transfer in a binary system to strip a core He-burning star of its envelope. However, these channels cannot account for sdBs that have been observed in long-period binaries nor the narrow mass distribution of isolated (or 'singleton') sdBs. We propose a new formation channel involving the merger of a helium white dwarf and a low-mass, hydrogen-burning star, which addresses these issues. Hierarchical triples whose inner binaries merge and form sdBs by this process could explain the observed long-period subdwarf+main-sequence binaries.more » This process would also naturally explain the observed slow rotational speeds of singleton sdBs. We also briefly discuss the implications of this formation channel for extreme horizontal branch morphology in globular clusters and the UV upturn in elliptical galaxies.« less

Liquid crystalline spinning of spider silk

NASA Astrophysics Data System (ADS)

Vollrath, Fritz; Knight, David P.

2001-03-01

Spider silk has outstanding mechanical properties despite being spun at close to ambient temperatures and pressures using water as the solvent. The spider achieves this feat of benign fibre processing by judiciously controlling the folding and crystallization of the main protein constituents, and by adding auxiliary compounds, to create a composite material of defined hierarchical structure. Because the `spinning dope' (the material from which silk is spun) is liquid crystalline, spiders can draw it during extrusion into a hardened fibre using minimal forces. This process involves an unusual internal drawdown within the spider's spinneret that is not seen in industrial fibre processing, followed by a conventional external drawdown after the dope has left the spinneret. Successful copying of the spider's internal processing and precise control over protein folding, combined with knowledge of the gene sequences of its spinning dopes, could permit industrial production of silk-based fibres with unique properties under benign conditions.

Hierarchical assembly of viral nanotemplates with encoded microparticles via nucleic acid hybridization.

PubMed

Tan, Wui Siew; Lewis, Christina L; Horelik, Nicholas E; Pregibon, Daniel C; Doyle, Patrick S; Yi, Hyunmin

2008-11-04

We demonstrate hierarchical assembly of tobacco mosaic virus (TMV)-based nanotemplates with hydrogel-based encoded microparticles via nucleic acid hybridization. TMV nanotemplates possess a highly defined structure and a genetically engineered high density thiol functionality. The encoded microparticles are produced in a high throughput microfluidic device via stop-flow lithography (SFL) and consist of spatially discrete regions containing encoded identity information, an internal control, and capture DNAs. For the hybridization-based assembly, partially disassembled TMVs were programmed with linker DNAs that contain sequences complementary to both the virus 5' end and a selected capture DNA. Fluorescence microscopy, atomic force microscopy (AFM), and confocal microscopy results clearly indicate facile assembly of TMV nanotemplates onto microparticles with high spatial and sequence selectivity. We anticipate that our hybridization-based assembly strategy could be employed to create multifunctional viral-synthetic hybrid materials in a rapid and high-throughput manner. Additionally, we believe that these viral-synthetic hybrid microparticles may find broad applications in high capacity, multiplexed target sensing.

A self-similar hierarchy of the Korean stock market

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Min, Seungsik; Yoo, Kun-Woo

2013-01-01

A scaling analysis is performed on market values of stocks listed on Korean stock exchanges such as the KOSPI and the KOSDAQ. Different from previous studies on price fluctuations, market capitalizations are dealt with in this work. First, we show that the sum of the two stock exchanges shows a clear rank-size distribution, i.e., the Zipf's law, just as each separate one does. Second, by abstracting Zipf's law as a γ-sequence, we define a self-similar hierarchy consisting of many levels, with the numbers of firms at each level forming a geometric sequence. We also use two exponential functions to describe the hierarchy and derive a scaling law from them. Lastly, we propose a self-similar hierarchical process and perform an empirical analysis on our data set. Based on our findings, we argue that all money invested in the stock market is distributed in a hierarchical way and that a slight difference exists between the two exchanges.

Building a Lego wall: Sequential action selection.

PubMed

Arnold, Amy; Wing, Alan M; Rotshtein, Pia

2017-05-01

The present study draws together two distinct lines of enquiry into the selection and control of sequential action: motor sequence production and action selection in everyday tasks. Participants were asked to build 2 different Lego walls. The walls were designed to have hierarchical structures with shared and dissociated colors and spatial components. Participants built 1 wall at a time, under low and high load cognitive states. Selection times for correctly completed trials were measured using 3-dimensional motion tracking. The paradigm enabled precise measurement of the timing of actions, while using real objects to create an end product. The experiment demonstrated that action selection was slowed at decision boundary points, relative to boundaries where no between-wall decision was required. Decision points also affected selection time prior to the actual selection window. Dual-task conditions increased selection errors. Errors mostly occurred at boundaries between chunks and especially when these required decisions. The data support hierarchical control of sequenced behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Phylogenetic classification and the universal tree.

PubMed

Doolittle, W F

1999-06-25

From comparative analyses of the nucleotide sequences of genes encoding ribosomal RNAs and several proteins, molecular phylogeneticists have constructed a "universal tree of life," taking it as the basis for a "natural" hierarchical classification of all living things. Although confidence in some of the tree's early branches has recently been shaken, new approaches could still resolve many methodological uncertainties. More challenging is evidence that most archaeal and bacterial genomes (and the inferred ancestral eukaryotic nuclear genome) contain genes from multiple sources. If "chimerism" or "lateral gene transfer" cannot be dismissed as trivial in extent or limited to special categories of genes, then no hierarchical universal classification can be taken as natural. Molecular phylogeneticists will have failed to find the "true tree," not because their methods are inadequate or because they have chosen the wrong genes, but because the history of life cannot properly be represented as a tree. However, taxonomies based on molecular sequences will remain indispensable, and understanding of the evolutionary process will ultimately be enriched, not impoverished.

Hierarchical HMM based learning of navigation primitives for cooperative robotic endovascular catheterization.

PubMed

Rafii-Tari, Hedyeh; Liu, Jindong; Payne, Christopher J; Bicknell, Colin; Yang, Guang-Zhong

2014-01-01

Despite increased use of remote-controlled steerable catheter navigation systems for endovascular intervention, most current designs are based on master configurations which tend to alter natural operator tool interactions. This introduces problems to both ergonomics and shared human-robot control. This paper proposes a novel cooperative robotic catheterization system based on learning-from-demonstration. By encoding the higher-level structure of a catheterization task as a sequence of primitive motions, we demonstrate how to achieve prospective learning for complex tasks whilst incorporating subject-specific variations. A hierarchical Hidden Markov Model is used to model each movement primitive as well as their sequential relationship. This model is applied to generation of motion sequences, recognition of operator input, and prediction of future movements for the robot. The framework is validated by comparing catheter tip motions against the manual approach, showing significant improvements in the quality of catheterization. The results motivate the design of collaborative robotic systems that are intuitive to use, while reducing the cognitive workload of the operator.

Tutorial on Protein Ontology Resources

PubMed Central

Arighi, Cecilia; Drabkin, Harold; Christie, Karen R.; Ross, Karen; Natale, Darren

2017-01-01

The Protein Ontology (PRO) is the reference ontology for proteins in the Open Biomedical Ontologies (OBO) foundry and consists of three sub-ontologies representing protein classes of homologous genes, proteoforms (e.g., splice isoforms, sequence variants, and post-translationally modified forms), and protein complexes. PRO defines classes of proteins and protein complexes, both species-specific and species non-specific, and indicates their relationships in a hierarchical framework, supporting accurate protein annotation at the appropriate level of granularity, analyses of protein conservation across species, and semantic reasoning. In this first section of this chapter, we describe the PRO framework including categories of PRO terms and the relationship of PRO to other ontologies and protein resources. Next, we provide a tutorial about the PRO website (proconsortium.org) where users can browse and search the PRO hierarchy, view reports on individual PRO terms, and visualize relationships among PRO terms in a hierarchical table view, a multiple sequence alignment view, and a Cytoscape network view. Finally, we describe several examples illustrating the unique and rich information available in PRO. PMID:28150233

The transcriptional regulatory network mediated by banana (Musa acuminata) dehydration-responsive element binding (MaDREB) transcription factors in fruit ripening.

PubMed

Kuang, Jian-Fei; Chen, Jian-Ye; Liu, Xun-Cheng; Han, Yan-Chao; Xiao, Yun-Yi; Shan, Wei; Tang, Yang; Wu, Ke-Qiang; He, Jun-Xian; Lu, Wang-Jin

2017-04-01

Fruit ripening is a complex, genetically programmed process involving the action of critical transcription factors (TFs). Despite the established significance of dehydration-responsive element binding (DREB) TFs in plant abiotic stress responses, the involvement of DREBs in fruit ripening is yet to be determined. Here, we identified four genes encoding ripening-regulated DREB TFs in banana (Musa acuminata), MaDREB1, MaDREB2, MaDREB3, and MaDREB4, and demonstrated that they play regulatory roles in fruit ripening. We showed that MaDREB1-MaDREB4 are nucleus-localized, induced by ethylene and encompass transcriptional activation activities. We performed a genome-wide chromatin immunoprecipitation and high-throughput sequencing (ChIP-Seq) experiment for MaDREB2 and identified 697 genomic regions as potential targets of MaDREB2. MaDREB2 binds to hundreds of loci with diverse functions and its binding sites are distributed in the promoter regions proximal to the transcriptional start site (TSS). Most of the MaDREB2-binding targets contain the conserved (A/G)CC(G/C)AC motif and MaDREB2 appears to directly regulate the expression of a number of genes involved in fruit ripening. In combination with transcriptome profiling (RNA sequencing) data, our results indicate that MaDREB2 may serve as both transcriptional activator and repressor during banana fruit ripening. In conclusion, our study suggests a hierarchical regulatory model of fruit ripening in banana and that the MaDREB TFs may act as transcriptional regulators in the regulatory network. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

MYC2 Orchestrates a Hierarchical Transcriptional Cascade That Regulates Jasmonate-Mediated Plant Immunity in Tomato.

PubMed

Du, Minmin; Zhao, Jiuhai; Tzeng, David T W; Liu, Yuanyuan; Deng, Lei; Yang, Tianxia; Zhai, Qingzhe; Wu, Fangming; Huang, Zhuo; Zhou, Ming; Wang, Qiaomei; Chen, Qian; Zhong, Silin; Li, Chang-Bao; Li, Chuanyou

2017-08-01

The hormone jasmonate (JA), which functions in plant immunity, regulates resistance to pathogen infection and insect attack through triggering genome-wide transcriptional reprogramming in plants. We show that the basic helix-loop-helix transcription factor (TF) MYC2 in tomato ( Solanum lycopersicum ) acts downstream of the JA receptor to orchestrate JA-mediated activation of both the wounding and pathogen responses. Using chromatin immunoprecipitation sequencing (ChIP-seq) coupled with RNA sequencing (RNA-seq) assays, we identified 655 MYC2-targeted JA-responsive genes. These genes are highly enriched in Gene Ontology categories related to TFs and the early response to JA, indicating that MYC2 functions at a high hierarchical level to regulate JA-mediated gene transcription. We also identified a group of MYC2-targeted TFs (MTFs) that may directly regulate the JA-induced transcription of late defense genes. Our findings suggest that MYC2 and its downstream MTFs form a hierarchical transcriptional cascade during JA-mediated plant immunity that initiates and amplifies transcriptional output. As proof of concept, we showed that during plant resistance to the necrotrophic pathogen Botrytis cinerea , MYC2 and the MTF JA2-Like form a transcription module that preferentially regulates wounding-responsive genes, whereas MYC2 and the MTF ETHYLENE RESPONSE FACTOR.C3 form a transcription module that preferentially regulates pathogen-responsive genes. © 2017 American Society of Plant Biologists. All rights reserved.

MYC2 Orchestrates a Hierarchical Transcriptional Cascade That Regulates Jasmonate-Mediated Plant Immunity in Tomato[OPEN

PubMed Central

Liu, Yuanyuan; Deng, Lei; Wu, Fangming; Huang, Zhuo; Zhou, Ming; Chen, Qian; Zhong, Silin

2017-01-01

The hormone jasmonate (JA), which functions in plant immunity, regulates resistance to pathogen infection and insect attack through triggering genome-wide transcriptional reprogramming in plants. We show that the basic helix-loop-helix transcription factor (TF) MYC2 in tomato (Solanum lycopersicum) acts downstream of the JA receptor to orchestrate JA-mediated activation of both the wounding and pathogen responses. Using chromatin immunoprecipitation sequencing (ChIP-seq) coupled with RNA sequencing (RNA-seq) assays, we identified 655 MYC2-targeted JA-responsive genes. These genes are highly enriched in Gene Ontology categories related to TFs and the early response to JA, indicating that MYC2 functions at a high hierarchical level to regulate JA-mediated gene transcription. We also identified a group of MYC2-targeted TFs (MTFs) that may directly regulate the JA-induced transcription of late defense genes. Our findings suggest that MYC2 and its downstream MTFs form a hierarchical transcriptional cascade during JA-mediated plant immunity that initiates and amplifies transcriptional output. As proof of concept, we showed that during plant resistance to the necrotrophic pathogen Botrytis cinerea, MYC2 and the MTF JA2-Like form a transcription module that preferentially regulates wounding-responsive genes, whereas MYC2 and the MTF ETHYLENE RESPONSE FACTOR.C3 form a transcription module that preferentially regulates pathogen-responsive genes. PMID:28733419

Hierarchically nested river landform sequences

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Emergence of Functional Hierarchy in a Multiple Timescale Neural Network Model: A Humanoid Robot Experiment

PubMed Central

Yamashita, Yuichi; Tani, Jun

2008-01-01

It is generally thought that skilled behavior in human beings results from a functional hierarchy of the motor control system, within which reusable motor primitives are flexibly integrated into various sensori-motor sequence patterns. The underlying neural mechanisms governing the way in which continuous sensori-motor flows are segmented into primitives and the way in which series of primitives are integrated into various behavior sequences have, however, not yet been clarified. In earlier studies, this functional hierarchy has been realized through the use of explicit hierarchical structure, with local modules representing motor primitives in the lower level and a higher module representing sequences of primitives switched via additional mechanisms such as gate-selecting. When sequences contain similarities and overlap, however, a conflict arises in such earlier models between generalization and segmentation, induced by this separated modular structure. To address this issue, we propose a different type of neural network model. The current model neither makes use of separate local modules to represent primitives nor introduces explicit hierarchical structure. Rather than forcing architectural hierarchy onto the system, functional hierarchy emerges through a form of self-organization that is based on two distinct types of neurons, each with different time properties (“multiple timescales”). Through the introduction of multiple timescales, continuous sequences of behavior are segmented into reusable primitives, and the primitives, in turn, are flexibly integrated into novel sequences. In experiments, the proposed network model, coordinating the physical body of a humanoid robot through high-dimensional sensori-motor control, also successfully situated itself within a physical environment. Our results suggest that it is not only the spatial connections between neurons but also the timescales of neural activity that act as important mechanisms leading to functional hierarchy in neural systems. PMID:18989398

Simulating protein folding initiation sites using an alpha-carbon-only knowledge-based force field

PubMed Central

Buck, Patrick M.; Bystroff, Christopher

2015-01-01

Protein folding is a hierarchical process where structure forms locally first, then globally. Some short sequence segments initiate folding through strong structural preferences that are independent of their three-dimensional context in proteins. We have constructed a knowledge-based force field in which the energy functions are conditional on local sequence patterns, as expressed in the hidden Markov model for local structure (HMMSTR). Carbon-alpha force field (CALF) builds sequence specific statistical potentials based on database frequencies for α-carbon virtual bond opening and dihedral angles, pairwise contacts and hydrogen bond donor-acceptor pairs, and simulates folding via Brownian dynamics. We introduce hydrogen bond donor and acceptor potentials as α-carbon probability fields that are conditional on the predicted local sequence. Constant temperature simulations were carried out using 27 peptides selected as putative folding initiation sites, each 12 residues in length, representing several different local structure motifs. Each 0.6 μs trajectory was clustered based on structure. Simulation convergence or representativeness was assessed by subdividing trajectories and comparing clusters. For 21 of the 27 sequences, the largest cluster made up more than half of the total trajectory. Of these 21 sequences, 14 had cluster centers that were at most 2.6 Å root mean square deviation (RMSD) from their native structure in the corresponding full-length protein. To assess the adequacy of the energy function on nonlocal interactions, 11 full length native structures were relaxed using Brownian dynamics simulations. Equilibrated structures deviated from their native states but retained their overall topology and compactness. A simple potential that folds proteins locally and stabilizes proteins globally may enable a more realistic understanding of hierarchical folding pathways. PMID:19137613

Application of hybrid clustering using parallel k-means algorithm and DIANA algorithm

NASA Astrophysics Data System (ADS)

Umam, Khoirul; Bustamam, Alhadi; Lestari, Dian

2017-03-01

DNA is one of the carrier of genetic information of living organisms. Encoding, sequencing, and clustering DNA sequences has become the key jobs and routine in the world of molecular biology, in particular on bioinformatics application. There are two type of clustering, hierarchical clustering and partitioning clustering. In this paper, we combined two type clustering i.e. K-Means (partitioning clustering) and DIANA (hierarchical clustering), therefore it called Hybrid clustering. Application of hybrid clustering using Parallel K-Means algorithm and DIANA algorithm used to clustering DNA sequences of Human Papillomavirus (HPV). The clustering process is started with Collecting DNA sequences of HPV are obtained from NCBI (National Centre for Biotechnology Information), then performing characteristics extraction of DNA sequences. The characteristics extraction result is store in a matrix form, then normalize this matrix using Min-Max normalization and calculate genetic distance using Euclidian Distance. Furthermore, the hybrid clustering is applied by using implementation of Parallel K-Means algorithm and DIANA algorithm. The aim of using Hybrid Clustering is to obtain better clusters result. For validating the resulted clusters, to get optimum number of clusters, we use Davies-Bouldin Index (DBI). In this study, the result of implementation of Parallel K-Means clustering is data clustered become 5 clusters with minimal IDB value is 0.8741, and Hybrid Clustering clustered data become 13 sub-clusters with minimal IDB values = 0.8216, 0.6845, 0.3331, 0.1994 and 0.3952. The IDB value of hybrid clustering less than IBD value of Parallel K-Means clustering only that perform at 1ts stage. Its means clustering using Hybrid Clustering have the better result to clustered DNA sequence of HPV than perform parallel K-Means Clustering only.

Hierarchical clustering using mutual information

NASA Astrophysics Data System (ADS)

Kraskov, A.; Stögbauer, H.; Andrzejak, R. G.; Grassberger, P.

2005-04-01

We present a conceptually simple method for hierarchical clustering of data called mutual information clustering (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X, Y, and Z is equal to the sum of the MI between X and Y, plus the MI between Z and the combined object (XY). We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov (algorithmic) version. We apply our method to the construction of phylogenetic trees from mitochondrial DNA sequences and to the output of independent components analysis (ICA) as illustrated with the ECG of a pregnant woman.

Hierarchical self-assembly of actin in micro-confinements using microfluidics

PubMed Central

Deshpande, Siddharth; Pfohl, Thomas

2012-01-01

We present a straightforward microfluidics system to achieve step-by-step reaction sequences in a diffusion-controlled manner in quasi two-dimensional micro-confinements. We demonstrate the hierarchical self-organization of actin (actin monomers—entangled networks of filaments—networks of bundles) in a reversible fashion by tuning the Mg2+ ion concentration in the system. We show that actin can form networks of bundles in the presence of Mg2+ without any cross-linking proteins. The properties of these networks are influenced by the confinement geometry. In square microchambers we predominantly find rectangular networks, whereas triangular meshes are predominantly found in circular chambers. PMID:24032070

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.

Genomics dataset of unidentified disclosed isolates.

PubMed

Rekadwad, Bhagwan N

2016-09-01

Analysis of DNA sequences is necessary for higher hierarchical classification of the organisms. It gives clues about the characteristics of organisms and their taxonomic position. This dataset is chosen to find complexities in the unidentified DNA in the disclosed patents. A total of 17 unidentified DNA sequences were thoroughly analyzed. The quick response codes were generated. AT/GC content of the DNA sequences analysis was carried out. The QR is helpful for quick identification of isolates. AT/GC content is helpful for studying their stability at different temperatures. Additionally, a dataset on cleavage code and enzyme code studied under the restriction digestion study, which helpful for performing studies using short DNA sequences was reported. The dataset disclosed here is the new revelatory data for exploration of unique DNA sequences for evaluation, identification, comparison and analysis.

Natural or Artificial: Is the Route of L2 Development Teachable?

ERIC Educational Resources Information Center

Zhang, Xian; Lantolf, James P.

2015-01-01

The current study was designed to assess the central claim of the Teachability Hypothesis (TH), a corollary of general Processability Theory (PT), which predicts instruction cannot alter posited universal, hierarchically organized psycholinguistic constraints behind PT's developmental sequences. We employed an interventional design, which adhered…

Laboratory Activities for Developing Process Skills.

ERIC Educational Resources Information Center

Institute for Services to Education, Inc., Washington, DC.

This workbook contains laboratory exercises designed for use in a college introductory biology course. Each exercise helps the student develop a basic science skill. The exercises are arranged in a hierarchical sequence suggesting the scientific method. Each skill facilitates the development of succeeding ones. Activities include Use of the…

Genetic diversity and structure of Phakopsora pachyrhizi infecting soybean in Nigeria

USDA-ARS?s Scientific Manuscript database

The genetic structure of Nigerian field populations of the soybean rust pathogen Phakopsora pachyrhizi was determined using 18 simple sequence repeat markers. A total of 113 fungal isolates was collected by hierarchical sampling infected leaves from soybean fields in three agroecological zones in 2...

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

PubMed

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-07-01

UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

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.

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

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

2005-04-01

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

Reconciling mass functions with the star-forming main sequence via mergers

NASA Astrophysics Data System (ADS)

Steinhardt, Charles L.; Yurk, Dominic; Capak, Peter

2017-06-01

We combine star formation along the 'main sequence', quiescence and clustering and merging to produce an empirical model for the evolution of individual galaxies. Main-sequence star formation alone would significantly steepen the stellar mass function towards low redshift, in sharp conflict with observation. However, a combination of star formation and merging produces a consistent result for correct choice of the merger rate function. As a result, we are motivated to propose a model in which hierarchical merging is disconnected from environmentally independent star formation. This model can be tested via correlation functions and would produce new constraints on clustering and merging.

Developing JSequitur to Study the Hierarchical Structure of Biological Sequences in a Grammatical Inference Framework of String Compression Algorithms.

PubMed

Galbadrakh, Bulgan; Lee, Kyung-Eun; Park, Hyun-Seok

2012-12-01

Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.

Toward a Unified Componential Theory of Human Reasoning. Technical Report No. 4.

ERIC Educational Resources Information Center

Sternberg, Robert J.

The unified theory described in this paper characterizes human reasoning as an information processing system with a hierarchical sequence of components and subtheories that account for performance on successively narrower tasks. Both deductive and inductive theories are subsumed in the unified componential theory, including transitive chain theory…

Secondary Mathematics Course Trajectories: Understanding Accumulated Disadvantages in Mathematics in Grades 9-12

ERIC Educational Resources Information Center

Schiller, Kathryn S.; Hunt, Donald J.

2011-01-01

Schools are institutions in which students' course taking creates series of linked learning opportunities continually shaped by not only curricular structures but demographic and academic backgrounds. In contrast to a seven-step normative course sequence reflecting the conventional hierarchical structure of mathematics, analysis of more than…

An Ecological Perspective on Deafness.

ERIC Educational Resources Information Center

Harvey, Michael A.; Dym, Barry

1988-01-01

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

Developing Conceptions of Authority and Contract across the Lifespan: Two Perspectives.

ERIC Educational Resources Information Center

Dawson, Theo L.; Gabrielian, Sonya

2003-01-01

Compares concepts defining Kohlbergian stages of moral development with those associated with orders of hierarchical complexity determined with a generalized content-independent stage-scoring system. Finds that Kohlberg's sequence generally matches that identified with the scoring system and that contract and authority concepts match the concepts…

A Hierarchical System for Evaluating the Biogenicity of Metavolcanic- and Ultramafic-Hosted Microalteration Textures in the Search for Extraterrestrial Life.

PubMed

McLoughlin, Nicola; Grosch, Eugene G

2015-10-01

The low-temperature alteration of submarine volcanic glasses has been argued to involve the activity of microorganisms, and analogous fluid-rock-microbial-mediated alteration has also been postulated on Mars. However, establishing the extent to which microbes are involved in volcanic glass alteration has proven to be difficult, and the reliability of resulting textural biosignatures is debated, particularly in the early rock record. We therefore propose a hierarchical scheme to evaluate the biogenicity of candidate textural biosignatures found in altered terrestrial and extraterrestrial basaltic glasses and serpentinized ultramafic rocks. The hierarchical scheme is formulated to give increasing confidence of a biogenic origin and involves (i) investigation of the textural context and syngenicity of the candidate biosignature; (ii) characterization of the morphology and size range of the microtextures; (iii) mapping of the geological and physicochemical variables controlling the occurrence and preservation of the microtextures; (iv) in situ investigation of chemical signatures that are syngenetic to the microtexture; and (v) identification of growth patterns suggestive of biological behavior and redox variations in the host minerals. The scheme results in five categories of candidate biosignature as follows: Category 1 indicates preservation of very weak evidence for biogenicity, Categories 2 through 4 indicate evidence for increasing confidence of a biogenic origin, and Category 5 indicates that biogenic origin is most likely. We apply this hierarchical approach to examine the evidence for a biogenic origin of several examples, including candidate bacterial encrustations in altered pillow lavas, granular and tubular microtextures in volcanic glass from the subseafloor and a Phanerozoic ophiolite, mineralized microtextures in Archean metavolcanic glass, and alteration textures in olivines of the martian meteorite Yamato 000593. The aim of this hierarchical approach is to provide a framework for identifying robust biosignatures of microbial life in the altered oceanic crust on Earth, and in extraterrestrial altered mafic-ultramafic rocks, particularly on Mars.

How Hierarchical Topics Evolve in Large Text Corpora.

PubMed

Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

2014-12-01

Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

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

Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Eils, Roland

2006-06-14

The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request.

The Effect of Emotional Labor on Job Involvement in Preschool Teachers: Verifying the Mediating Effect of Psychological Capital

ERIC Educational Resources Information Center

Fu, Ching-Sheue

2015-01-01

In this study, the participants comprised 385 preschool teachers. The relationship among their emotional labor, Job Involvement, and psychological capital were examined using hierarchical regression analysis. In addition, whether psychological capital exerted a mediating effect on Job Involvement was investigated. The results show that "deep…

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring

PubMed Central

2012-01-01

Background Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. Results The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Conclusions Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family. PMID:22793672

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.

PubMed

Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl

2012-07-13

Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family.

Hierarchical and non-hierarchical mineralisation of collagen

PubMed Central

Liu, Yan; Kim, Young-Kyung; Dai, Lin; Li, Nan; Khan, Sara; Pashley, David H.; Tay, Franklin R.

2010-01-01

Biomineralisation of collagen involves functional motifs incorporated in extracellular matrix protein molecules to accomplish the objectives of stabilising amorphous calcium phosphate into nanoprecursors and directing the nucleation and growth of apatite within collagen fibrils. Here we report the use of small inorganic polyphosphate molecules to template hierarchical intrafibrillar apatite assembly in reconstituted collagen in the presence of polyacrylic acid to sequester calcium and phosphate into transient amorphous nanophases. The use of polyphosphate without a sequestration analogue resulted only in randomly-oriented extrafibrillar precipitations along the fibrillar surface. Conversely, the use of polyacrylic acid without a templating analogue resulted only in non-hierarchical intrafibrillar mineralisation with continuous apatite strands instead of discrete crystallites. The ability of using simple non-protein molecules to recapitulate different levels of structural hierarchy in mineralised collagen signifies the ultimate simplicity in Nature’s biomineralisation design principles and challenges the need for using more complex recombinant matrix proteins in bioengineering applications. PMID:21040969

Development of new smart materials and spinning systems inspired by natural silks and their applications

NASA Astrophysics Data System (ADS)

Cheng, Jie; Lee, Sang-Hoon

2015-12-01

Silks produced by spiders and silkworms are charming natural biological materials with highly optimized hierarchical structures and outstanding physicomechanical properties. The superior performance of silks relies on the integration of a unique protein sequence, a distinctive spinning process, and complex hierarchical structures. Silks have been prepared to form a variety of morphologies and are widely used in diverse applications, for example, in the textile industry, as drug delivery vehicles, and as tissue engineering scaffolds. This review presents an overview of the organization of natural silks, in which chemical and physical functions are optimized, as well as a range of new materials inspired by the desire to mimic natural silk structure and synthesis.

Chunking dynamics: heteroclinics in mind

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S.

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics. PMID:24672469

Hierarchical compression of Caenorhabditis elegans locomotion reveals phenotypic differences in the organization of behaviour.

PubMed

Gomez-Marin, Alex; Stephens, Greg J; Brown, André E X

2016-08-01

Regularities in animal behaviour offer insights into the underlying organizational and functional principles of nervous systems and automated tracking provides the opportunity to extract features of behaviour directly from large-scale video data. Yet how to effectively analyse such behavioural data remains an open question. Here, we explore whether a minimum description length principle can be exploited to identify meaningful behaviours and phenotypes. We apply a dictionary compression algorithm to behavioural sequences from the nematode worm Caenorhabditis elegans freely crawling on an agar plate both with and without food and during chemotaxis. We find that the motifs identified by the compression algorithm are rare but relevant for comparisons between worms in different environments, suggesting that hierarchical compression can be a useful step in behaviour analysis. We also use compressibility as a new quantitative phenotype and find that the behaviour of wild-isolated strains of C. elegans is more compressible than that of the laboratory strain N2 as well as the majority of mutant strains examined. Importantly, in distinction to more conventional phenotypes such as overall motor activity or aggregation behaviour, the increased compressibility of wild isolates is not explained by the loss of function of the gene npr-1, which suggests that erratic locomotion is a laboratory-derived trait with a novel genetic basis. Because hierarchical compression can be applied to any sequence, we anticipate that compressibility can offer insights into the organization of behaviour in other animals including humans. © 2016 The Authors.

Chunking dynamics: heteroclinics in mind.

PubMed

Rabinovich, Mikhail I; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components-brain modes-participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles-metastable states-connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

Evaluation of the scientific underpinnings for identifying ...

EPA Pesticide Factsheets

A major challenge in chemical risk assessment is extrapolation of toxicity data from tested to untested species. Successful cross-species extrapolation involves understanding similarities and differences in toxicokinetic and toxicodynamic processes among species. Herein we consider the toxicodynamic challenge, and propose a hierarchal framework, based on the adverse outcome pathway (AOP) concept, to transparently and systematically assess cross-species conservation of biological pathways that could be perturbed by toxic chemicals. The approach features consideration of computational, in vitro and in vivo evidence to assess molecular initiating and intermediate key events of an AOP in a systematic, comparative manner. To demonstrate practical application of the framework, we consider an assessment question arising from the legislatively-mandated USEPA endocrine disruptor screening program, which involves the degree to which data generated using mammalian systems can be translated to non-mammalian species. Specifically, there is a need to define cross-species conservation of pathways controlled by activation of estrogen receptor-á (ERá), as a basis for using mammalian (primarily human) high-throughput (HTP) in vitro data to prioritize subsequent testing to assess human health and ecological risks of estrogenic chemicals. The initial phase of our analysis revealed good structural conservation the ERá across vertebrate species in terms of amino acid sequence

Introduction to multiresolution modeling (MMR) with an example involving precision fires

NASA Astrophysics Data System (ADS)

Davis, Paul K.; Bigelow, James H.

1998-08-01

In this paper we review motivations for multilevel resolution modeling (MRM) within a single model, an integrated hierarchical family of models, or both. We then present a new depiction of consistency criteria for models at different levels. After describing our hypotheses for studying the process of MRM with examples, we define a simple but policy-relevant problem involving the use of precision fires to halt an invading army. We then illustrate MRM with a sequence of abstractions suggested by formal theory, visual representation, and approximation. We milk the example for insights about why MRM is different and often difficult, and how it might be accomplished more routinely. It should be feasible even in complex systems such as JWARS and JSIMS, but it is by no means easy. Comprehensive MRM designs are unlikely. It is useful to take the view that some MRM is a great deal better than none and that approximate MRM relationships are often quite adequate. Overall, we conclude that high-quality MRM requires new theory, design practices, modeling tools, and software tools, all of which will take some years to develop. Current object-oriented programming practices may actually be a hindrance.

Spatio-Temporal Structure, Path Characteristics, and Perceptual Grouping in Immediate Serial Spatial Recall

PubMed Central

De Lillo, Carlo; Kirby, Melissa; Poole, Daniel

2016-01-01

Immediate serial spatial recall measures the ability to retain sequences of locations in short-term memory and is considered the spatial equivalent of digit span. It is tested by requiring participants to reproduce sequences of movements performed by an experimenter or displayed on a monitor. Different organizational factors dramatically affect serial spatial recall but they are often confounded or underspecified. Untangling them is crucial for the characterization of working-memory models and for establishing the contribution of structure and memory capacity to spatial span. We report five experiments assessing the relative role and independence of factors that have been reported in the literature. Experiment 1 disentangled the effects of spatial clustering and path-length by manipulating the distance of items displayed on a touchscreen monitor. Long-path sequences segregated by spatial clusters were compared with short-path sequences not segregated by clusters. Recall was more accurate for sequences segregated by clusters independently from path-length. Experiment 2 featured conditions where temporal pauses were introduced between or within cluster boundaries during the presentation of sequences with the same paths. Thus, the temporal structure of the sequences was either consistent or inconsistent with a hierarchical representation based on segmentation by spatial clusters but the effect of structure could not be confounded with effects of path-characteristics. Pauses at cluster boundaries yielded more accurate recall, as predicted by a hierarchical model. In Experiment 3, the systematic manipulation of sequence structure, path-length, and presence of path-crossings of sequences showed that structure explained most of the variance, followed by the presence/absence of path-crossings, and path-length. Experiments 4 and 5 replicated the results of the previous experiments in immersive virtual reality navigation tasks where the viewpoint of the observer changed dynamically during encoding and recall. This suggested that the effects of structure in spatial span are not dependent on perceptual grouping processes induced by the aerial view of the stimulus array typically afforded by spatial recall tasks. These results demonstrate the independence of coding strategies based on structure from effects of path characteristics and perceptual grouping in immediate serial spatial recall. PMID:27891101

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.

OP17MICRORNA PROFILING USING SMALL RNA-SEQ IN PAEDIATRIC LOW GRADE GLIOMAS

PubMed Central

Jeyapalan, Jennie N.; Jones, Tania A.; Tatevossian, Ruth G.; Qaddoumi, Ibrahim; Ellison, David W.; Sheer, Denise

2014-01-01

INTRODUCTION: MicroRNAs regulate gene expression by targeting mRNAs for translational repression or degradation at the post-transcriptional level. In paediatric low-grade gliomas a few key genetic mutations have been identified, including BRAF fusions, FGFR1 duplications and MYB rearrangements. Our aim in the current study is to profile aberrant microRNA expression in paediatric low-grade gliomas and determine the role of epigenetic changes in the aetiology and behaviour of these tumours. METHOD: MicroRNA profiling of tumour samples (6 pilocytic, 2 diffuse, 2 pilomyxoid astrocytomas) and normal brain controls (4 adult normal brain samples and a primary glial progenitor cell-line) was performed using small RNA sequencing. Bioinformatic analysis included sequence alignment, analysis of the number of reads (CPM, counts per million) and differential expression. RESULTS: Sequence alignment identified 695 microRNAs, whose expression was compared in tumours v. normal brain. PCA and hierarchical clustering showed separate groups for tumours and normal brain. Computational analysis identified approximately 400 differentially expressed microRNAs in the tumours compared to matched location controls. Our findings will then be validated and integrated with extensive genetic and epigenetic information we have previously obtained for the full tumour cohort. CONCLUSION: We have identified microRNAs that are differentially expressed in paediatric low-grade gliomas. As microRNAs are known to target genes involved in the initiation and progression of cancer, they provide critical information on tumour pathogenesis and are an important class of biomarkers.

The VMC Survey. XXII. Hierarchical Star Formation in the 30 Doradus-N158-N159-N160 Star-forming Complex

NASA Astrophysics Data System (ADS)

Sun, Ning-Chen; de Grijs, Richard; Subramanian, Smitha; Cioni, Maria-Rosa L.; Rubele, Stefano; Bekki, Kenji; Ivanov, Valentin D.; Piatti, Andrés E.; Ripepi, Vincenzo

2017-02-01

We study the hierarchical stellar structures in a ˜1.5 deg2 area covering the 30 Doradus-N158-N159-N160 star-forming complex with the VISTA Survey of Magellanic Clouds. Based on the young upper main-sequence stars, we find that the surface densities cover a wide range of values, from log({{Σ }}\\cdot pc2) ≲ -2.0 to log({{Σ }}\\cdot pc2) ≳ 0.0. Their distributions are highly non-uniform, showing groups that frequently have subgroups inside. The sizes of the stellar groups do not exhibit characteristic values, and range continuously from several parsecs to more than 100 pc the cumulative size distribution can be well described by a single power law, with the power-law index indicating a projected fractal dimension D2 = 1.6 ± 0.3. We suggest that the phenomena revealed here support a scenario of hierarchical star formation. Comparisons with other star-forming regions and galaxies are also discussed.

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.

Using experimental and computational energy equilibration to understand hierarchical self-assembly of Fmoc-dipeptide amphiphiles.

PubMed

Sasselli, I R; Pappas, C G; Matthews, E; Wang, T; Hunt, N T; Ulijn, R V; Tuttle, T

2016-10-12

Despite progress, a fundamental understanding of the relationships between the molecular structure and self-assembly configuration of Fmoc-dipeptides is still in its infancy. In this work, we provide a combined experimental and computational approach that makes use of free energy equilibration of a number of related Fmoc-dipeptides to arrive at an atomistic model of Fmoc-threonine-phenylalanine-amide (Fmoc-TF-NH 2 ) which forms twisted fibres. By using dynamic peptide libraries where closely related dipeptide sequences are dynamically exchanged to eventually favour the formation of the thermodynamically most stable configuration, the relative importance of C-terminus modifications (amide versus methyl ester) and contributions of aliphatic versus aromatic amino acids (phenylalanine F vs. leucine L) is determined (F > L and NH 2 > OMe). The approach enables a comparative interpretation of spectroscopic data, which can then be used to aid the construction of the atomistic model of the most stable structure (Fmoc-TF-NH 2 ). The comparison of the relative stabilities of the models using molecular dynamic simulations and the correlation with experimental data using dynamic peptide libraries and a range of spectroscopy methods (FTIR, CD, fluorescence) allow for the determination of the nanostructure with atomistic resolution. The final model obtained through this process is able to reproduce the experimentally observed formation of intertwining fibres for Fmoc-TF-NH 2 , providing information of the interactions involved in the hierarchical supramolecular self-assembly. The developed methodology and approach should be of general use for the characterization of supramolecular structures.

Resting blood pressure differentially predicts time course in a tonic pain experiment.

PubMed

Horing, Bjoern; McCubbin, James A; Moore, Dewayne; Muth, Eric R

2016-10-01

Resting blood pressure (BP) shows a negative relationship with pain sensitivity (BP-related hypoalgesia). In chronic pain conditions, this relationship is inverted. The precise mechanisms responsible for the inversion are unknown. Using a tonic pain protocol, we report findings closely resembling this inversion in healthy participants. Resting BP and state measures of anxiety and mood were assessed from 33 participants (21 female). Participants then immersed their dominant hand in painfully hot water (47 °C) for five trials of 1-min duration, with 30-s intertrial intervals. Throughout the trials, participants continually registered their pain. After a 35-min intermission, the trial sequence was repeated. A disassociation of the negative relationship of resting systolic BP (as per Trial 1) was found using hierarchical linear modeling (p < .001, R(2)  = .07). The disassociation unfolds over each consecutive trial, with an increasingly positive relationship. In Sequence 2, the initially negative relationship is almost completely absent. Furthermore, the association of BP and pain was found to be moderated by anxiety, such that only persons with low anxiety exhibited BP hypoalgesia. Our findings expand the existing literature by incorporating anxiety as a moderator of BP hypoalgesia. Furthermore, the protocol emulates the changing relationship between BP and pain observed in chronic pain patients. The protocol has potential as a model for chronic pain; however, future research should determine if similar physiological systems are involved. The finding holds potential diagnostic or prognostic relevance for certain clinical pain conditions, especially those involving dysfunction of the descending modulation of pain. © 2016 Society for Psychophysiological Research.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

PubMed Central

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-01-01

Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. Results: We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. Availability: A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request. Contact: lonshy@cs.huji.ac.il PMID:18586742

Use Hierarchical Storage and Analysis to Exploit Intrinsic Parallelism

NASA Astrophysics Data System (ADS)

Zender, C. S.; Wang, W.; Vicente, P.

2013-12-01

Big Data is an ugly name for the scientific opportunities and challenges created by the growing wealth of geoscience data. How to weave large, disparate datasets together to best reveal their underlying properties, to exploit their strengths and minimize their weaknesses, to continually aggregate more information than the world knew yesterday and less than we will learn tomorrow? Data analytics techniques (statistics, data mining, machine learning, etc.) can accelerate pattern recognition and discovery. However, often researchers must, prior to analysis, organize multiple related datasets into a coherent framework. Hierarchical organization permits entire dataset to be stored in nested groups that reflect their intrinsic relationships and similarities. Hierarchical data can be simpler and faster to analyze by coding operators to automatically parallelize processes over isomorphic storage units, i.e., groups. The newest generation of netCDF Operators (NCO) embody this hierarchical approach, while still supporting traditional analysis approaches. We will use NCO to demonstrate the trade-offs involved in processing a prototypical Big Data application (analysis of CMIP5 datasets) using hierarchical and traditional analysis approaches.

The Emergence of Sub-Syllabic Representations

ERIC Educational Resources Information Center

Lee, Yongeun; Goldrick, Matthew

2008-01-01

In a variety of experimental paradigms speakers do not treat all sub-syllabic sequences equally. In languages like English, participants tend to group vowels and codas together to the exclusion of onsets (i.e., /bet/=/b/-/et/). Three possible accounts of these patterns are examined. A hierarchical account attributes these results to the presence…

Drawing the Line between Constituent Structure and Coherence Relations in Visual Narratives

ERIC Educational Resources Information Center

Cohn, Neil; Bender, Patrick

2017-01-01

Theories of visual narrative understanding have often focused on the changes in meaning across a sequence, like shifts in characters, spatial location, and causation, as cues for breaks in the structure of a discourse. In contrast, the theory of visual narrative grammar posits that hierarchic "grammatical" structures operate at the…

Why Children Are Left Behind and What We Can Do about It.

ERIC Educational Resources Information Center

Reigeluth, Charles M.; Beatty, Brian J.

2003-01-01

Proposes four main reasons that children are left behind in schools: unmet needs, lack of motivation, lack of foundation and prior knowledge, and lack of support for learning. Discusses Maslow's hierarch of needs; partnerships with parents; connecting to student interests; insisting on mastery; curriculum sequencing; brain-based research; and…

Traversing Bloom's Taxonomy in an Introductory Scripture Course

ERIC Educational Resources Information Center

Bruehler, Bart B.

2018-01-01

Many courses in higher education rely on the hierarchical organization of Bloom's taxonomy to categorize and sequence learning. Introductory courses on scripture often emphasize remembering content and background as a basis for applying the sacred text to one's life. However, a review of the literature demonstrates little support for the widely…

Doing Without Schema Hierarchies: A Recurrent Connectionist Approach to Normal and Impaired Routine Sequential Action

ERIC Educational Resources Information Center

Botvinick, Matthew; Plaut, David C.

2004-01-01

In everyday tasks, selecting actions in the proper sequence requires a continuously updated representation of temporal context. Previous models have addressed this problem by positing a hierarchy of processing units, mirroring the roughly hierarchical structure of naturalistic tasks themselves. The present study considers an alternative framework,…

Applying Toulmin: Teaching Logical Reasoning and Argumentative Writing

ERIC Educational Resources Information Center

Rex, Lesley A.; Thomas, Ebony Elizabeth; Engel, Steven

2010-01-01

To learn to write well-reasoned persuasive arguments, students need in situ help thinking through the complexity and complications of an issue, making inferences based on evidence, and hierarchically grouping and logically sequencing ideas. They rely on teachers to make this happen. In this article, the authors explain the framework they used and…

Alignment-free inference of hierarchical and reticulate phylogenomic relationships.

PubMed

Bernard, Guillaume; Chan, Cheong Xin; Chan, Yao-Ban; Chua, Xin-Yi; Cong, Yingnan; Hogan, James M; Maetschke, Stefan R; Ragan, Mark A

2017-06-30

We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed. © The Author 2017. Published by Oxford University Press.

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

PubMed

Duarte, Francisco; Martins, Bruno; Pinto, Cátia Sousa; Silva, Mário J

2018-04-01

We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep neural network that combines word embeddings, recurrent units, and neural attention, for the generation of intermediate representations of the textual contents. The neural network also explores the hierarchical nature of the input data, by building representations from the sequences of words within individual fields, which are then combined according to the sequences of fields that compose the inputs. Moreover, we explore innovative mechanisms for initializing the weights of the final nodes of the network, leveraging co-occurrences between classes together with the hierarchical structure of ICD-10. Experimental results attest to the contribution of the different neural network components. Our best model achieves accuracy scores over 89%, 81%, and 76%, respectively for ICD-10 chapters, blocks, and full-codes. Through examples, we also show that our method can produce interpretable results, useful for public health surveillance. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data.

PubMed

Chin, Chen-Shan; Alexander, David H; Marks, Patrick; Klammer, Aaron A; Drake, James; Heiner, Cheryl; Clum, Alicia; Copeland, Alex; Huddleston, John; Eichler, Evan E; Turner, Stephen W; Korlach, Jonas

2013-06-01

We present a hierarchical genome-assembly process (HGAP) for high-quality de novo microbial genome assemblies using only a single, long-insert shotgun DNA library in conjunction with Single Molecule, Real-Time (SMRT) DNA sequencing. Our method uses the longest reads as seeds to recruit all other reads for construction of highly accurate preassembled reads through a directed acyclic graph-based consensus procedure, which we follow with assembly using off-the-shelf long-read assemblers. In contrast to hybrid approaches, HGAP does not require highly accurate raw reads for error correction. We demonstrate efficient genome assembly for several microorganisms using as few as three SMRT Cell zero-mode waveguide arrays of sequencing and for BACs using just one SMRT Cell. Long repeat regions can be successfully resolved with this workflow. We also describe a consensus algorithm that incorporates SMRT sequencing primary quality values to produce de novo genome sequence exceeding 99.999% accuracy.

Comprehensive analysis of orthologous protein domains using the HOPS database.

PubMed

Storm, Christian E V; Sonnhammer, Erik L L

2003-10-01

One of the most reliable methods for protein function annotation is to transfer experimentally known functions from orthologous proteins in other organisms. Most methods for identifying orthologs operate on a subset of organisms with a completely sequenced genome, and treat proteins as single-domain units. However, it is well known that proteins are often made up of several independent domains, and there is a wealth of protein sequences from genomes that are not completely sequenced. A comprehensive set of protein domain families is found in the Pfam database. We wanted to apply orthology detection to Pfam families, but first some issues needed to be addressed. First, orthology detection becomes impractical and unreliable when too many species are included. Second, shorter domains contain less information. It is therefore important to assess the quality of the orthology assignment and avoid very short domains altogether. We present a database of orthologous protein domains in Pfam called HOPS: Hierarchical grouping of Orthologous and Paralogous Sequences. Orthology is inferred in a hierarchic system of phylogenetic subgroups using ortholog bootstrapping. To avoid the frequent errors stemming from horizontally transferred genes in bacteria, the analysis is presently limited to eukaryotic genes. The results are accessible in the graphical browser NIFAS, a Java tool originally developed for analyzing phylogenetic relations within Pfam families. The method was tested on a set of curated orthologs with experimentally verified function. In comparison to tree reconciliation with a complete species tree, our approach finds significantly more orthologs in the test set. Examples for investigating gene fusions and domain recombination using HOPS are given.

Toward a General Approach for RNA-Templated Hierarchical Assembly of Split-Proteins

PubMed Central

Furman, Jennifer L.; Badran, Ahmed H.; Ajulo, Oluyomi; Porter, Jason R.; Stains, Cliff I.; Segal, David J.; Ghosh, Indraneel

2010-01-01

The ability to conditionally turn on a signal or induce a function in the presence of a user-defined RNA target has potential applications in medicine and synthetic biology. Although sequence-specific pumilio repeat proteins can target a limited set of ssRNA sequences, there are no general methods for targeting ssRNA with designed proteins. As a first step toward RNA recognition, we utilized the RNA binding domain of argonaute, implicated in RNA interference, for specifically targeting generic 2-nucleotide, 3' overhangs of any dsRNA. We tested the reassembly of a split-luciferase enzyme guided by argonaute-mediated recognition of newly generated nucleotide overhangs when ssRNA is targeted by a designed complementary guide sequence. This approach was successful when argonaute was utilized in conjunction with a pumilio repeat and expanded the scope of potential ssRNA targets. However, targeting any desired ssRNA remained elusive as two argonaute domains provided minimal reassembled split-luciferase. We next designed and tested a second hierarchical assembly, wherein ssDNA guides are appended to DNA hairpins that serve as a scaffold for high affinity zinc fingers attached to split-luciferase. In the presence of a ssRNA target containing adjacent sequences complementary to the guides, the hairpins are brought into proximity, allowing for zinc finger binding and concomitant reassembly of the fragmented luciferase. The scope of this new approach was validated by specifically targeting RNA encoding VEGF, hDM2, and HER2. These approaches provide potentially general design paradigms for the conditional reassembly of fragmented proteins in the presence of any desired ssRNA target. PMID:20681585

High speed clinical data retrieval system with event time sequence feature: with 10 years of clinical data of Hamamatsu University Hospital CPOE.

PubMed

Kimura, M; Tani, S; Watanabe, H; Naito, Y; Sakusabe, T; Watanabe, H; Nakaya, J; Sasaki, F; Numano, T; Furuta, T; Furuta, T

2008-01-01

This paper illustrates a high speed clinical data retrieving system, from 10 years of data of operating hospital information system for the purposes of research, evidence creation, patient safety, etc., even incorporating time sequence of causal relations. Total of 73,709,298 records of 10 years at Hamamatsu University Hospital (as of June 2008) are sent from HIS to retrieval system in HL7 v2.5 format. Hierarchical variable length database is used to install them. A search for "listing patients who were prescribed Pravastatin (Mevalotin and generic drugs, any titer)" took 1.92 seconds. "Pravastatin (any) prescribed and recorded AST >150 within two weeks" took 112.22 seconds. Searching conditions can be set to be more complex, connected by Boolean operator and/or. This system called D*D is in operation at Hamamatsu University Hospital since August 2002. It is used for 48,518 times (monthly average of 703 searches). Neither searching, nor background export of data from HIS caused delay of routine operating CPOE. Search database outside of routine operating CPOE, with daily export of order data in HL7 v2.5 format, is proved to provide excellent search environment without causing trouble. Hierarchical representation gives high-speed search response, especially with time sequence of events.

Directing folding pathways for multi-component DNA origami nanostructures with complex topology

NASA Astrophysics Data System (ADS)

Marras, A. E.; Zhou, L.; Kolliopoulos, V.; Su, H.-J.; Castro, C. E.

2016-05-01

Molecular self-assembly has become a well-established technique to design complex nanostructures and hierarchical mesoscale assemblies. The typical approach is to design binding complementarity into nucleotide or amino acid sequences to achieve the desired final geometry. However, with an increasing interest in dynamic nanodevices, the need to design structures with motion has necessitated the development of multi-component structures. While this has been achieved through hierarchical assembly of similar structural units, here we focus on the assembly of topologically complex structures, specifically with concentric components, where post-folding assembly is not feasible. We exploit the ability to direct folding pathways to program the sequence of assembly and present a novel approach of designing the strand topology of intermediate folding states to program the topology of the final structure, in this case a DNA origami slider structure that functions much like a piston-cylinder assembly in an engine. The ability to program the sequence and control orientation and topology of multi-component DNA origami nanostructures provides a foundation for a new class of structures with internal and external moving parts and complex scaffold topology. Furthermore, this work provides critical insight to guide the design of intermediate states along a DNA origami folding pathway and to further understand the details of DNA origami self-assembly to more broadly control folding states and landscapes.

Genetic variation in scaly hair-fin anchovy Setipinna tenuifilis (Engraulididae) based on the mitochondrial DNA control region.

PubMed

Xu, Shengyong; Song, Na; Lu, Zhichuang; Wang, Jun; Cai, Shanshan; Gao, Tianxiang

2014-06-01

Scaly hair-fin anchovy (Setipinna tenuifilis) is a small, pelagic and economical species and widely distributed in Chinese coastal water. However, resources of S. tenuifilis have been reduced due to overfishing. For better fishery management, it is necessary to understand the pattern of S. tenuifilis's biogeography. Genetic analyses were taken place to detect their population genetic variation. A total of 153 individuals from 7 locations (Dongying, Yantai, Qingdao, Nantong, Wenzhou, Xiamen and Beibu Bay) were sequenced at the 5' end of mtDNA control region. A 39-bp tandem repeated sequence was found at the 5' end of the segment and a polymorphism of tandem repeated sequence was detected among 7 populations. Both mismatch distribution analysis and neutrality tests showed S. tenuifilis had experienced a recent population expansion. The topology of neighbor-joining tree and Bayesian evolutionary tree showed no significant genealogical branches or clusters of samples corresponding to sampling locality. Hierarchical analysis of molecular variance and conventional pairwise population Fst value at group hierarchical level implied that there might have genetic divergence between southern group (population WZ, XM and BB) and northern group (population DY, YT, QD and NT). We concluded that there might have three different fishery management groups of S. tenuifilis and the late Pleistocene glacial event might have a crucial effect on present-day demography of S. tenuifilis in this region.

Social structure in a family group of Guanaco (Lama guanicoe, Ungulate): is female hierarchy based on 'prior attributes' or 'social dynamics'?

PubMed

Correa, Loreto A; Zapata, Beatriz; Samaniego, Horacio; Soto-Gamboa, Mauricio

2013-09-01

Social life involves costs and benefits mostly associated with how individuals interact with each other. The formation of hierarchies inside social groups has evolved as a common strategy to avoid high costs stemming from social interactions. Hierarchical relationships seem to be associated with different features such as body size, body condition and/or age, which determine dominance ability ('prior attributes' hypothesis). In contrast, the 'social dynamic' hypothesis suggests that an initial social context is a determinant in the formation of the hierarchy, more so than specific individual attributes. Hierarchical rank places individuals in higher positions, which presumably increases resource accessibility to their benefit, including opportunities for reproduction. We evaluate the maintenance of hierarchy in a family group of guanacos (Lama guanicoe) and evaluate the possible mechanisms involved in the stability of these interactions and their consequences. We estimate the linearity of social hierarchy and their dynamics. We find evidence of the formation of a highly linear hierarchy among females with males positioned at the bottom of the hierarchy. This hierarchy is not affected by physical characteristics or age, suggesting that it is established only through intra-group interactions. Rank is not related with calves' weight gain either; however, subordinated females, with lower rank, exhibit higher rates of allosuckling. We found no evidence of hierarchical structure in calves suggesting that hierarchical relationship in guanacos could be established during the formation of the family group. Hence, our results suggest that hierarchical dynamics could be related more to social dynamics than to prior attributes. We finally discuss the importance of hierarchies established by dominance and their role in minimizing social costs of interactions. Copyright © 2013 Elsevier B.V. All rights reserved.

The Relationship of School-Based Parental Involvement with Student Achievement: A Comparison of Principal and Parent Survey Reports from PISA 2012

ERIC Educational Resources Information Center

Sebastian, James; Moon, Jeong-Mi; Cunningham, Matt

2017-01-01

This paper explores parental involvement using principal and parent survey reports to examine whether parents' involvement in their children's schools predicts academic achievement. Survey data from principals and parents of seven countries from the PISA 2012 database and hierarchical linear modelling were used to analyse between- and within-…

Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis.

PubMed

Li, Ben; Li, Yunxiao; Qin, Zhaohui S

2017-06-01

Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package "adaptiveHM", which is freely available from https://github.com/benliemory/adaptiveHM.

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.

Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis

PubMed Central

Li, Ben; Li, Yunxiao; Qin, Zhaohui S.

2016-01-01

Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical ‘large p, small n’ problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package “adaptiveHM”, which is freely available from https://github.com/benliemory/adaptiveHM. PMID:28919931

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.

Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

PubMed Central

2012-01-01

Background The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches. Results Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day. Conclusions This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain annotation by identifying those pattern residues that most distinguish each protein domain subgroup from other related subgroups. PMID:22726767

The Effectiveness of Concept Mapping and Retrieval Practice as Learning Strategies in an Undergraduate Physiology Course

ERIC Educational Resources Information Center

Burdo, Joseph; O'Dwyer, Laura

2015-01-01

Concept mapping and retrieval practice are both educational methods that have separately been reported to provide significant benefits for learning in diverse settings. Concept mapping involves diagramming a hierarchical representation of relationships between distinct pieces of information, whereas retrieval practice involves retrieving…

Attention to Hierarchical Level Influences Attentional Selection of Spatial Scale

ERIC Educational Resources Information Center

Flevaris, Anastasia V.; Bentin, Shlomo; Robertson, Lynn C.

2011-01-01

Ample evidence suggests that global perception may involve low spatial frequency (LSF) processing and that local perception may involve high spatial frequency (HSF) processing (Shulman, Sullivan, Gish, & Sakoda, 1986; Shulman & Wilson, 1987; Robertson, 1996). It is debated whether SF selection is a low-level mechanism associating global…

The Implications of Contamination for Educational Experiments with Two Levels of Nesting

ERIC Educational Resources Information Center

Rhoads, Christopher

2016-01-01

Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…

Parental Behavioural Control and Academic Achievement: Striking the Balance between Control and Involvement

ERIC Educational Resources Information Center

Kramer, Karen Z.

2012-01-01

Using a longitudinal US dataset (N = 6,134) we examine the relationship between parental behavioural control and academic achievement and explore the moderating role of parental involvement and parental warmth. Analyses using multiple hierarchical regression with clustering controls shows that parental behavioural control is negatively associated…

Embryological Development: Evolutionary History, Genetic Bias, and Cellular Environment Control the Flow of Developmental Events. Part I.

ERIC Educational Resources Information Center

Caplan, Arnold I.

1981-01-01

Describes development of the limb and various interactions necessary for the expression of its unique form and phenotypes to uncover the hierarchical controlling steps in the development process for the potential of avoiding abnormal events and manipulating what might be detrimental genetic events into a normal sequence. (Author/SK)

Hierarchically ordered carbon tubes

NASA Astrophysics Data System (ADS)

Pan, Zheng-Wei; Zhu, Hao-Guo; Zhang, Zong-Tao; Im, Hee-Jung; Dai, Sheng; Beach, David B.; Lowndes, Douglas H.

2003-04-01

Micropatterns of hierarchically ordered carbon tubes (i.e., ordered carbon microtubes composed of aligned carbon nanotubes) were grown on a film-like iron/silica substrate consisting of ring-like catalyst patterns. The substrates were prepared by a combined technique, in which the sol-gel method was used to prepare catalyst film and transmission electron microscope grids were used as a shadow mask. In comparison with other techniques that involve sophisticated lithography, this approach represents a simple and low-cost way to the micropatterning of aligned carbon nanotubes.

Brain networks for confidence weighting and hierarchical inference during probabilistic learning.

PubMed

Meyniel, Florent; Dehaene, Stanislas

2017-05-09

Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences.

Brain networks for confidence weighting and hierarchical inference during probabilistic learning

PubMed Central

Meyniel, Florent; Dehaene, Stanislas

2017-01-01

Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This “confidence weighting” implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain’s learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences. PMID:28439014

Hierarchical VOOH hollow spheres for symmetrical and asymmetrical supercapacitor devices.

PubMed

Jing, Xuyang; Wang, Cong; Feng, Wenjing; Xing, Na; Jiang, Hanmei; Lu, Xiangyu; Zhang, Yifu; Meng, Changgong

2018-01-01

Hierarchical VOOH hollow spheres with low crystallinity composed of nanoparticles were prepared by a facile and template-free method, which involved a precipitation of precursor microspheres in aqueous solution at room temperature and subsequent hydrothermal reaction. Quasi-solid-state symmetric and asymmetric supercapacitor (SSC and ASC) devices were fabricated using hierarchical VOOH hollow spheres as the electrodes, and the electrochemical properties of the VOOH//VOOH SSC device and the VOOH//AC ASC device were studied by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). Results demonstrated that the electrochemical performance of the VOOH//AC ASC device was better than that of the VOOH//VOOH SSC device. After 3000 cycles, the specific capacitance of the VOOH//AC ASC device retains 83% of the initial capacitance, while the VOOH//VOOH SSC device retains only 7.7%. Findings in this work proved that hierarchical VOOH hollow spheres could be a promising candidate as an ideal electrode material for supercapacitor devices.

Hierarchical VOOH hollow spheres for symmetrical and asymmetrical supercapacitor devices

NASA Astrophysics Data System (ADS)

Jing, Xuyang; Wang, Cong; Feng, Wenjing; Xing, Na; Jiang, Hanmei; Lu, Xiangyu; Zhang, Yifu; Meng, Changgong

2018-01-01

Hierarchical VOOH hollow spheres with low crystallinity composed of nanoparticles were prepared by a facile and template-free method, which involved a precipitation of precursor microspheres in aqueous solution at room temperature and subsequent hydrothermal reaction. Quasi-solid-state symmetric and asymmetric supercapacitor (SSC and ASC) devices were fabricated using hierarchical VOOH hollow spheres as the electrodes, and the electrochemical properties of the VOOH//VOOH SSC device and the VOOH//AC ASC device were studied by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). Results demonstrated that the electrochemical performance of the VOOH//AC ASC device was better than that of the VOOH//VOOH SSC device. After 3000 cycles, the specific capacitance of the VOOH//AC ASC device retains 83% of the initial capacitance, while the VOOH//VOOH SSC device retains only 7.7%. Findings in this work proved that hierarchical VOOH hollow spheres could be a promising candidate as an ideal electrode material for supercapacitor devices.

The traveling salesman problem: a hierarchical model.

PubMed

Graham, S M; Joshi, A; Pizlo, Z

2000-10-01

Our review of prior literature on spatial information processing in perception, attention, and memory indicates that these cognitive functions involve similar mechanisms based on a hierarchical architecture. The present study extends the application of hierarchical models to the area of problem solving. First, we report results of an experiment in which human subjects were tested on a Euclidean traveling salesman problem (TSP) with 6 to 30 cities. The subject's solutions were either optimal or near-optimal in length and were produced in a time that was, on average, a linear function of the number of cities. Next, the performance of the subjects is compared with that of five representative artificial intelligence and operations research algorithms, that produce approximate solutions for Euclidean problems. None of these algorithms was found to be an adequate psychological model. Finally, we present a new algorithm for solving the TSP, which is based on a hierarchical pyramid architecture. The performance of this new algorithm is quite similar to the performance of the subjects.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

3D hierarchical Ag nanostructures formed on poly(acrylic acid) brushes grafted graphene oxide as promising SERS substrates

NASA Astrophysics Data System (ADS)

Xing, Guoke; Wang, Ke; Li, Ping; Wang, Wenqin; Chen, Tao

2018-03-01

In this study, in situ generation of Ag nanostructures with various morphology on poly(acrylic acid) (PAA) brushes grafted onto graphene oxide (GO), for use as substrates for surface-enhanced Raman scattering (SERS), is demonstrated. The overall synthetic strategy involves the loading of Ag precursor ions ((Ag+ and [Ag(NH3)2]+) onto PAA brush-grafted GO, followed by their in situ reduction to Ag nanostructures of various morphology using a reducing agent (NaBH4 or ascorbic acid). Novel 3D hierarchical flowerlike Ag nanostructures were obtained by using AgNO3 as precursor and ascorbic acid as reducing agent. Using 4-aminothiophenol as probe molecules, the as-prepared hierarchical Ag nanostructures exhibited excellent SERS performance, providing enhancement factors of ˜107.

Gene Expression Profiles in Paired Gingival Biopsies from Periodontitis-Affected and Healthy Tissues Revealed by Massively Parallel Sequencing

PubMed Central

Båge, Tove; Lagervall, Maria; Jansson, Leif; Lundeberg, Joakim; Yucel-Lindberg, Tülay

2012-01-01

Periodontitis is a chronic inflammatory disease affecting the soft tissue and bone that surrounds the teeth. Despite extensive research, distinctive genes responsible for the disease have not been identified. The objective of this study was to elucidate transcriptome changes in periodontitis, by investigating gene expression profiles in gingival tissue obtained from periodontitis-affected and healthy gingiva from the same patient, using RNA-sequencing. Gingival biopsies were obtained from a disease-affected and a healthy site from each of 10 individuals diagnosed with periodontitis. Enrichment analysis performed among uniquely expressed genes for the periodontitis-affected and healthy tissues revealed several regulated pathways indicative of inflammation for the periodontitis-affected condition. Hierarchical clustering of the sequenced biopsies demonstrated clustering according to the degree of inflammation, as observed histologically in the biopsies, rather than clustering at the individual level. Among the top 50 upregulated genes in periodontitis-affected tissues, we investigated two genes which have not previously been demonstrated to be involved in periodontitis. These included interferon regulatory factor 4 and chemokine (C-C motif) ligand 18, which were also expressed at the protein level in gingival biopsies from patients with periodontitis. In conclusion, this study provides a first step towards a quantitative comprehensive insight into the transcriptome changes in periodontitis. We demonstrate for the first time site-specific local variation in gene expression profiles of periodontitis-affected and healthy tissues obtained from patients with periodontitis, using RNA-seq. Further, we have identified novel genes expressed in periodontitis tissues, which may constitute potential therapeutic targets for future treatment strategies of periodontitis. PMID:23029519

Hierarchical video summarization based on context clustering

NASA Astrophysics Data System (ADS)

Tseng, Belle L.; Smith, John R.

2003-11-01

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

Methods For Self-Organizing Software

DOEpatents

Bouchard, Ann M.; Osbourn, Gordon C.

2005-10-18

A method for dynamically self-assembling and executing software is provided, containing machines that self-assemble execution sequences and data structures. In addition to ordered functions calls (found commonly in other software methods), mutual selective bonding between bonding sites of machines actuates one or more of the bonding machines. Two or more machines can be virtually isolated by a construct, called an encapsulant, containing a population of machines and potentially other encapsulants that can only bond with each other. A hierarchical software structure can be created using nested encapsulants. Multi-threading is implemented by populations of machines in different encapsulants that are interacting concurrently. Machines and encapsulants can move in and out of other encapsulants, thereby changing the functionality. Bonding between machines' sites can be deterministic or stochastic with bonding triggering a sequence of actions that can be implemented by each machine. A self-assembled execution sequence occurs as a sequence of stochastic binding between machines followed by their deterministic actuation. It is the sequence of bonding of machines that determines the execution sequence, so that the sequence of instructions need not be contiguous in memory.

Improving phylogenetic analyses by incorporating additional information from genetic sequence databases.

PubMed

Liang, Li-Jung; Weiss, Robert E; Redelings, Benjamin; Suchard, Marc A

2009-10-01

Statistical analyses of phylogenetic data culminate in uncertain estimates of underlying model parameters. Lack of additional data hinders the ability to reduce this uncertainty, as the original phylogenetic dataset is often complete, containing the entire gene or genome information available for the given set of taxa. Informative priors in a Bayesian analysis can reduce posterior uncertainty; however, publicly available phylogenetic software specifies vague priors for model parameters by default. We build objective and informative priors using hierarchical random effect models that combine additional datasets whose parameters are not of direct interest but are similar to the analysis of interest. We propose principled statistical methods that permit more precise parameter estimates in phylogenetic analyses by creating informative priors for parameters of interest. Using additional sequence datasets from our lab or public databases, we construct a fully Bayesian semiparametric hierarchical model to combine datasets. A dynamic iteratively reweighted Markov chain Monte Carlo algorithm conveniently recycles posterior samples from the individual analyses. We demonstrate the value of our approach by examining the insertion-deletion (indel) process in the enolase gene across the Tree of Life using the phylogenetic software BALI-PHY; we incorporate prior information about indels from 82 curated alignments downloaded from the BAliBASE database.

Dual Sticky Hierarchical Dirichlet Process Hidden Markov Model and Its Application to Natural Language Description of Motions.

PubMed

Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen

2017-09-25

In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.

Hierarchical processing in music, language, and action: Lashley revisited.

PubMed

Fitch, W Tecumseh; Martins, Mauricio D

2014-05-01

Sixty years ago, Karl Lashley suggested that complex action sequences, from simple motor acts to language and music, are a fundamental but neglected aspect of neural function. Lashley demonstrated the inadequacy of then-standard models of associative chaining, positing a more flexible and generalized "syntax of action" necessary to encompass key aspects of language and music. He suggested that hierarchy in language and music builds upon a more basic sequential action system, and provided several concrete hypotheses about the nature of this system. Here, we review a diverse set of modern data concerning musical, linguistic, and other action processing, finding them largely consistent with an updated neuroanatomical version of Lashley's hypotheses. In particular, the lateral premotor cortex, including Broca's area, plays important roles in hierarchical processing in language, music, and at least some action sequences. Although the precise computational function of the lateral prefrontal regions in action syntax remains debated, Lashley's notion-that this cortical region implements a working-memory buffer or stack scannable by posterior and subcortical brain regions-is consistent with considerable experimental data. © 2014 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

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

PubMed

Baquero, Fernando; Moya, Andrés

2012-01-01

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

Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics.

PubMed

Wu, Hao-Yang; Wang, Yan-Hui; Xie, Qiang; Ke, Yun-Ling; Bu, Wen-Jun

2016-06-17

With the great development of sequencing technologies and systematic methods, our understanding of evolutionary relationships at deeper levels within the tree of life has greatly improved over the last decade. However, the current taxonomic methodology is insufficient to describe the growing levels of diversity in both a standardised and general way due to the limitations of using only morphological traits to describe clades. Herein, we propose the idea of a molecular classification based on hierarchical and discrete amino acid characters. Clades are classified based on the results of phylogenetic analyses and described using amino acids with group specificity in phylograms. Practices based on the recently published phylogenomic datasets of insects together with 15 de novo sequenced transcriptomes in this study demonstrate that such a methodology can accommodate various higher ranks of taxonomy. Such an approach has the advantage of describing organisms in a standard and discrete way within a phylogenetic framework, thereby facilitating the recognition of clades from the view of the whole lineage, as indicated by PhyloCode. By combining identification keys and phylogenies, the molecular classification based on hierarchical and discrete characters may greatly boost the progress of integrative taxonomy.

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

PubMed Central

Baquero, Fernando; Moya, Andrés

2012-01-01

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

Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics

PubMed Central

Wu, Hao-Yang; Wang, Yan-Hui; Xie, Qiang; Ke, Yun-Ling; Bu, Wen-Jun

2016-01-01

With the great development of sequencing technologies and systematic methods, our understanding of evolutionary relationships at deeper levels within the tree of life has greatly improved over the last decade. However, the current taxonomic methodology is insufficient to describe the growing levels of diversity in both a standardised and general way due to the limitations of using only morphological traits to describe clades. Herein, we propose the idea of a molecular classification based on hierarchical and discrete amino acid characters. Clades are classified based on the results of phylogenetic analyses and described using amino acids with group specificity in phylograms. Practices based on the recently published phylogenomic datasets of insects together with 15 de novo sequenced transcriptomes in this study demonstrate that such a methodology can accommodate various higher ranks of taxonomy. Such an approach has the advantage of describing organisms in a standard and discrete way within a phylogenetic framework, thereby facilitating the recognition of clades from the view of the whole lineage, as indicated by PhyloCode. By combining identification keys and phylogenies, the molecular classification based on hierarchical and discrete characters may greatly boost the progress of integrative taxonomy. PMID:27312960

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

PubMed Central

Li, Pinghao; Jiang, Xiaoqian; Wang, Shuang; Kim, Jihoon; Xiong, Hongkai; Ohno-Machado, Lucila

2014-01-01

Background and objective Short-read sequencing is becoming the standard of practice for the study of structural variants associated with disease. However, with the growth of sequence data largely surpassing reasonable storage capability, the biomedical community is challenged with the management, transfer, archiving, and storage of sequence data. Methods We developed Hierarchical mUlti-reference Genome cOmpression (HUGO), a novel compression algorithm for aligned reads in the sorted Sequence Alignment/Map (SAM) format. We first aligned short reads against a reference genome and stored exactly mapped reads for compression. For the inexact mapped or unmapped reads, we realigned them against different reference genomes using an adaptive scheme by gradually shortening the read length. Regarding the base quality value, we offer lossy and lossless compression mechanisms. The lossy compression mechanism for the base quality values uses k-means clustering, where a user can adjust the balance between decompression quality and compression rate. The lossless compression can be produced by setting k (the number of clusters) to the number of different quality values. Results The proposed method produced a compression ratio in the range 0.5–0.65, which corresponds to 35–50% storage savings based on experimental datasets. The proposed approach achieved 15% more storage savings over CRAM and comparable compression ratio with Samcomp (CRAM and Samcomp are two of the state-of-the-art genome compression algorithms). The software is freely available at https://sourceforge.net/projects/hierachicaldnac/with a General Public License (GPL) license. Limitation Our method requires having different reference genomes and prolongs the execution time for additional alignments. Conclusions The proposed multi-reference-based compression algorithm for aligned reads outperforms existing single-reference based algorithms. PMID:24368726

The plant virus microscope image registration method based on mismatches removing.

PubMed

Wei, Lifang; Zhou, Shucheng; Dong, Heng; Mao, Qianzhuo; Lin, Jiaxiang; Chen, Riqing

2016-01-01

The electron microscopy is one of the major means to observe the virus. The view of virus microscope images is limited by making specimen and the size of the camera's view field. To solve this problem, the virus sample is produced into multi-slice for information fusion and image registration techniques are applied to obtain large field and whole sections. Image registration techniques have been developed in the past decades for increasing the camera's field of view. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Alternatively, the methods are conceived just to provide visually pleasant registration for high overlap ratio image sequence. This work presents a method for virus microscope image registration acquired with detailed visual information and subpixel accuracy, even when overlap ratio of image sequence is 10% or less. The method proposed focus on the correspondence set and interimage transformation. A mismatch removal strategy is proposed by the spatial consistency and the components of keypoint to enrich the correspondence set. And the translation model parameter as well as tonal inhomogeneities is corrected by the hierarchical estimation and model select. In the experiments performed, we tested different registration approaches and virus images, confirming that the translation model is not always stationary, despite the fact that the images of the sample come from the same sequence. The mismatch removal strategy makes building registration of virus microscope images at subpixel accuracy easier and optional parameters for building registration according to the hierarchical estimation and model select strategies make the proposed method high precision and reliable for low overlap ratio image sequence. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hierarchical brain mapping via a generalized Dirichlet solution for mapping brain manifolds

NASA Astrophysics Data System (ADS)

Joshi, Sarang C.; Miller, Michael I.; Christensen, Gary E.; Banerjee, Ayan; Coogan, Tom; Grenander, Ulf

1995-08-01

In this paper we present a coarse-to-fine approach for the transformation of digital anatomical textbooks from the ideal to the individual that unifies the work on landmark deformations and volume based transformation. The Hierarchical approach is linked to the Biological problem itself, coming out of the various kinds of information which is provided by the anatomists. This information is in the form of points, lines, surfaces and sub-volumes corresponding to 0, 1, 2, and 3 dimensional sub-manifolds respectively. The algorithm is driven by these sub- manifolds. We follow the approach that the highest dimensional transformation is a result from the solution of a sequence of lower dimensional problems driven by successive refinements or partitions of the images into various Biologically meaningful sub-structures.

Development of hierarchical structures for actions and motor imagery: a constructivist view from synthetic neuro-robotics study.

PubMed

Nishimoto, Ryunosuke; Tani, Jun

2009-07-01

The current paper shows a neuro-robotics experiment on developmental learning of goal-directed actions. The robot was trained to predict visuo-proprioceptive flow of achieving a set of goal-directed behaviors through iterative tutor training processes. The learning was conducted by employing a dynamic neural network model which is characterized by their multiple time-scale dynamics. The experimental results showed that functional hierarchical structures emerge through stages of developments where behavior primitives are generated in earlier stages and their sequences of achieving goals appear in later stages. It was also observed that motor imagery is generated in earlier stages compared to actual behaviors. Our claim that manipulatable inner representation should emerge through the sensory-motor interactions is corresponded to Piaget's constructivist view.

Diversity of pufM genes, involved in aerobic anoxygenic photosynthesis, in the bacterial communities associated with colonial ascidians.

PubMed

Martínez-García, Manuel; Díaz-Valdés, Marta; Antón, Josefa

2010-03-01

Ascidians are invertebrate filter feeders widely distributed in benthic marine environments. A total of 14 different ascidian species were collected from the Western Mediterranean and their bacterial communities were analyzed by denaturing gradient gel electrophoresis (DGGE) of 16S rRNA gene. Results showed that ascidian tissues harbored Bacteria belonging to Gamma- and Alphaproteobacteria classes, some of them phylogenetically related to known aerobic anoxygenic phototrophs (AAPs), such as Roseobacter sp. In addition, hierarchical cluster analysis of DGGE patterns showed a large variability in the bacterial diversity among the different ascidians analyzed, which indicates that they would harbor different bacterial communities. Furthermore, pufM genes, involved in aerobic anoxygenic photosynthesis in marine and freshwater systems, were widely detected within the ascidians analyzed, because nine out of 14 species had pufM genes inside their tissues. The pufM gene was only detected in those specimens that inhabited shallow waters (<77 m of depth). Most pufM gene sequences were very closely related to that of uncultured marine bacteria. Thus, our results suggest that the association of ascidians with bacteria related to AAPs could be a general phenomenon and that ascidian-associated microbiota could use the light that penetrates through the tunic tissue as an energy source.

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism

PubMed Central

2015-01-01

Background Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. Results ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and vitamins. Conclusions The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems. PMID:26099921

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.

PubMed

Mohammed, Akram; Guda, Chittibabu

2015-01-01

Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and vitamins. The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems.

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

PubMed

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

2017-02-01

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

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

PubMed Central

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

2017-01-01

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

A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila

PubMed Central

Seeds, Andrew M; Ravbar, Primoz; Chung, Phuong; Hampel, Stefanie; Midgley, Frank M; Mensh, Brett D; Simpson, Julie H

2014-01-01

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences. DOI: http://dx.doi.org/10.7554/eLife.02951.001 PMID:25139955

Lithofacies and sequence stratigraphic description of the upper part of the Avon Park Formation and the Arcadia Formation in U.S. Geological Survey G–2984 test corehole, Broward County, Florida

USGS Publications Warehouse

Cunningham, Kevin J.; Robinson, Edward

2017-07-18

Rock core and sediment from U.S. Geological Survey test corehole G–2984 completed in 2011 in Broward County, Florida, provide an opportunity to improve the understanding of the lithostratigraphic, sequence stratigraphic, and hydrogeologic framework of the intermediate confining unit and Floridan aquifer system in southeastern Florida. A multidisciplinary approach including characterization of sequence stratigraphy, lithofacies, ichnology, foraminiferal paleontology, depositional environments, porosity, and permeability was used to describe the geologic samples from this test corehole. This information has produced a detailed characterization of the lithofacies and sequence stratigraphy of the upper part of the middle Eocene Avon Park Formation and Oligocene to middle Miocene Arcadia Formation. This enhancement of the knowledge of the sequence stratigraphic framework is especially important, because subaerial karst unconformities at the upper boundary of depositional cycles at various hierarchical scales are commonly associated with secondary porosity and enhanced permeability in the Floridan aquifer system.

Cognitive representation of "musical fractals": Processing hierarchy and recursion in the auditory domain.

PubMed

Martins, Mauricio Dias; Gingras, Bruno; Puig-Waldmueller, Estela; Fitch, W Tecumseh

2017-04-01

The human ability to process hierarchical structures has been a longstanding research topic. However, the nature of the cognitive machinery underlying this faculty remains controversial. Recursion, the ability to embed structures within structures of the same kind, has been proposed as a key component of our ability to parse and generate complex hierarchies. Here, we investigated the cognitive representation of both recursive and iterative processes in the auditory domain. The experiment used a two-alternative forced-choice paradigm: participants were exposed to three-step processes in which pure-tone sequences were built either through recursive or iterative processes, and had to choose the correct completion. Foils were constructed according to generative processes that did not match the previous steps. Both musicians and non-musicians were able to represent recursion in the auditory domain, although musicians performed better. We also observed that general 'musical' aptitudes played a role in both recursion and iteration, although the influence of musical training was somehow independent from melodic memory. Moreover, unlike iteration, recursion in audition was well correlated with its non-auditory (recursive) analogues in the visual and action sequencing domains. These results suggest that the cognitive machinery involved in establishing recursive representations is domain-general, even though this machinery requires access to information resulting from domain-specific processes. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Student Input, Student Involvement, and College Environment Factors Impacting the Choice of Academic Major.

ERIC Educational Resources Information Center

Coperthwaite, Corby A.; Knight, William E.

This study investigated the ability of student inputs, student involvements, and college environments to predict seven groups of academic majors. The research was conducted using a sample of college sophomores extracted from High School and Beyond 1982 follow-up cohort, N=43,614 (weighted). Among the findings of the hierarchical discriminant…

Exploring the Relations between Parent Depressive Symptoms, Family Religious Involvement, and Adolescent Depressive Symptoms: A Test of Moderation

ERIC Educational Resources Information Center

Hooper, Lisa M.; Caroline R. Newman

2011-01-01

Building on previous research, the current study examined the relations between parent depressive symptoms, family religious involvement, and adolescent depressive symptoms in a convenience sample of 74 parent-adolescent dyads of southern U.S. families. We used hierarchical regression analysis to explore whether family religious involvement…

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Efficient electronic structure theory via hierarchical scale-adaptive coupled-cluster formalism: I. Theory and computational complexity analysis

NASA Astrophysics Data System (ADS)

Lyakh, Dmitry I.

2018-03-01

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.

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.

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

PubMed

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

2013-03-27

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

A Motivational Model of Physical Education and Links to Enjoyment, Knowledge, Performance, Total Physical Activity and Body Mass Index

PubMed Central

Gråstén, Arto; Watt, Anthony

2017-01-01

The present paper examined the full sequence of the Hierarchical Model of Motivation in physical education (PE) including motivational climate, basic psychological needs, intrinsic motivation, and related links to contextual enjoyment, knowledge, performance, and total moderate to vigorous physical activity (MVPA). Gender differences and correlations with body mass index (BMI) were also analyzed. Cross-sectional data was represented by self-reports and objective assessments of 770 middle school students (52% of girls) in North-East Finland. The results showed that task-involving climate in girls’ PE classes was related to enjoyment and knowledge through physical competence and intrinsic motivation, whereas task-involving climate was associated with enjoyment and knowledge via competence and autonomy, and total MVPA via autonomy, intrinsic motivation, and knowledge within boys. This may indicate that girls and boys perceive PE classes in a different way. Graded PE assessments appeared to be essential in motivating both girls and boys to participate in greater total MVPA, whereas BMI was negatively linked with competence and social relatedness only among girls. Although, the current and previous empirical findings supported task-involving teaching methods in PE, in some cases, ego-involving climate should be considered. Therefore, both task- and ego-involving teaching practices can be useful ways of developing preferred behaviors in PE classes. Key points The present findings indicated that girls and boys perceive PE classes in a different way. Graded PE assessments appeared to be essential in motivating both girls and boys to participate in greater total MVPA, whereas BMI was negatively linked with competence and social relatedness only among girls. Although, the current and previous empirical findings supported task-involving teaching methods in PE, in some cases, ego-involving climate should be considered. Both task- and ego-involving teaching practices can be useful ways of developing preferred behaviors in PE classes. PMID:28912648

The Intelligent Management System: An Overview.

DTIC Science & Technology

1982-12-07

comprises of hundreds of subprocesses concerned with bulb grasping, positioning, heating, cooling, etc. Each is sequentially related with others in time...activity. Activity schemata can be constructed into a network to define both parallel and sequential precedence, and hierarchical to describe...The flow of work is controlled by the "operation- lineup " associated with the product being manufactured. The operation- lineup specifies the sequence of

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.

Creating Hierarchical Pores by Controlled Linker Thermolysis in Multivariate Metal-Organic Frameworks.

PubMed

Feng, Liang; Yuan, Shuai; Zhang, Liang-Liang; Tan, Kui; Li, Jia-Luo; Kirchon, Angelo; Liu, Ling-Mei; Zhang, Peng; Han, Yu; Chabal, Yves J; Zhou, Hong-Cai

2018-02-14

Sufficient pore size, appropriate stability, and hierarchical porosity are three prerequisites for open frameworks designed for drug delivery, enzyme immobilization, and catalysis involving large molecules. Herein, we report a powerful and general strategy, linker thermolysis, to construct ultrastable hierarchically porous metal-organic frameworks (HP-MOFs) with tunable pore size distribution. Linker instability, usually an undesirable trait of MOFs, was exploited to create mesopores by generating crystal defects throughout a microporous MOF crystal via thermolysis. The crystallinity and stability of HP-MOFs remain after thermolabile linkers are selectively removed from multivariate metal-organic frameworks (MTV-MOFs) through a decarboxylation process. A domain-based linker spatial distribution was found to be critical for creating hierarchical pores inside MTV-MOFs. Furthermore, linker thermolysis promotes the formation of ultrasmall metal oxide nanoparticles immobilized in an open framework that exhibits high catalytic activity for Lewis acid-catalyzed reactions. Most importantly, this work provides fresh insights into the connection between linker apportionment and vacancy distribution, which may shed light on probing the disordered linker apportionment in multivariate systems, a long-standing challenge in the study of MTV-MOFs.

Testing comparative phylogeographic models of marine vicariance and dispersal using a hierarchical Bayesian approach

PubMed Central

2008-01-01

Background Marine allopatric speciation is an enigma because pelagic larval dispersal can potentially connect disjunct populations thereby preventing reproductive and morphological divergence. Here we present a new hierarchical approximate Bayesian computation model (HABC) that tests two hypotheses of marine allopatric speciation: 1.) "soft vicariance", where a speciation involves fragmentation of a large widespread ancestral species range that was previously connected by long distance gene flow; and 2.) peripatric colonization, where speciations in peripheral archipelagos emerge from sweepstakes colonizations from central source regions. The HABC approach analyzes all the phylogeographic datasets at once in order to make across taxon-pair inferences about biogeographic processes while explicitly allowing for uncertainty in the demographic differences within each taxon-pair. Our method uses comparative phylogeographic data that consists of single locus mtDNA sequences from multiple co-distributed taxa containing pairs of central and peripheral populations. We use the method on two comparative phylogeographic data sets consisting of cowrie gastropod endemics co-distributed in the Hawaiian (11 taxon-pairs) and Marquesan archipelagos (7 taxon-pairs). Results Given the Marquesan data, we find strong evidence of simultaneous colonization across all seven cowrie gastropod endemics co-distributed in the Marquesas. In contrast, the lower sample sizes in the Hawaiian data lead to greater uncertainty associated with the Hawaiian estimates. Although, the hyper-parameter estimates point to soft vicariance in a subset of the 11 Hawaiian taxon-pairs, the hyper-prior and hyper-posterior are too similar to make a definitive conclusion. Both results are not inconsistent with what is known about the geologic history of the archipelagos. Simulations verify that our method can successfully distinguish these two histories across a wide range of conditions given sufficient sampling. Conclusion Although soft vicariance and colonization are likely to produce similar genetic patterns when a single taxon-pair is used, our hierarchical Bayesian model can potentially detect if either history is a dominant process across co-distributed taxon-pairs. As comparative phylogeographic datasets grow to include > 100 co-distributed taxon-pairs, the HABC approach will be well suited to dissect temporal patterns in community assembly and evolution, thereby providing a bridge linking comparative phylogeography with community ecology. PMID:19038027

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.

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.

PubMed

Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.

A stage is a stage is a stage: a direct comparison of two scoring systems.

PubMed

Dawson, Theo L

2003-09-01

L. Kohlberg (1969) argued that his moral stages captured a developmental sequence specific to the moral domain. To explore that contention, the author compared stage assignments obtained with the Standard Issue Scoring System (A. Colby & L. Kohlberg, 1987a, 1987b) and those obtained with a generalized content-independent stage-scoring system called the Hierarchical Complexity Scoring System (T. L. Dawson, 2002a), on 637 moral judgment interviews (participants' ages ranged from 5 to 86 years). The correlation between stage scores produced with the 2 systems was .88. Although standard issue scoring and hierarchical complexity scoring often awarded different scores up to Kohlberg's Moral Stage 2/3, from his Moral Stage 3 onward, scores awarded with the two systems predominantly agreed. The author explores the implications for developmental research.

3D knee segmentation based on three MRI sequences from different planes.

PubMed

Zhou, L; Chav, R; Cresson, T; Chartrand, G; de Guise, J

2016-08-01

In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

probeBase—an online resource for rRNA-targeted oligonucleotide probes and primers: new features 2016

PubMed Central

Greuter, Daniel; Loy, Alexander; Horn, Matthias; Rattei, Thomas

2016-01-01

probeBase http://www.probebase.net is a manually maintained and curated database of rRNA-targeted oligonucleotide probes and primers. Contextual information and multiple options for evaluating in silico hybridization performance against the most recent rRNA sequence databases are provided for each oligonucleotide entry, which makes probeBase an important and frequently used resource for microbiology research and diagnostics. Here we present a major update of probeBase, which was last featured in the NAR Database Issue 2007. This update describes a complete remodeling of the database architecture and environment to accommodate computationally efficient access. Improved search functions, sequence match tools and data output now extend the opportunities for finding suitable hierarchical probe sets that target an organism or taxon at different taxonomic levels. To facilitate the identification of complementary probe sets for organisms represented by short rRNA sequence reads generated by amplicon sequencing or metagenomic analysis with next generation sequencing technologies such as Illumina and IonTorrent, we introduce a novel tool that recovers surrogate near full-length rRNA sequences for short query sequences and finds matching oligonucleotides in probeBase. PMID:26586809

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.

Rhythmic cognition in humans and animals: distinguishing meter and pulse perception

PubMed Central

Fitch, W. Tecumseh

2013-01-01

This paper outlines a cognitive and comparative perspective on human rhythmic cognition that emphasizes a key distinction between pulse perception and meter perception. Pulse perception involves the extraction of a regular pulse or “tactus” from a stream of events. Meter perception involves grouping of events into hierarchical trees with differing levels of “strength”, or perceptual prominence. I argue that metrically-structured rhythms are required to either perform or move appropriately to music (e.g., to dance). Rhythms, from this metrical perspective, constitute “trees in time.” Rhythmic syntax represents a neglected form of musical syntax, and warrants more thorough neuroscientific investigation. The recent literature on animal entrainment clearly demonstrates the capacity to extract the pulse from rhythmic music, and to entrain periodic movements to this pulse, in several parrot species and a California sea lion, and a more limited ability to do so in one chimpanzee. However, the ability of these or other species to infer hierarchical rhythmic trees remains, for the most part, unexplored (with some apparent negative results from macaques). The results from this animal comparative research, combined with new methods to explore rhythmic cognition neurally, provide exciting new routes for understanding not just rhythmic cognition, but hierarchical cognition more generally, from a biological and neural perspective. PMID:24198765

Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

USGS Publications Warehouse

Royle, J. Andrew; Converse, Sarah J.

2014-01-01

Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

The problem of gestalt in neurobiology.

PubMed

Sokolov, E N

1997-01-01

The question of gestalts is discussed within the framework of its neuronal mechanisms. Two basic hypotheses are considered: 1) that of gestalts as a result of the hierarchical organization of neurons (gnostic units), and 2) that of gestalts as a result of the synchronization of neurons of a given level. Analysis of published data led to the conclusion that gestalts result from vector coding in the hierarchical organization of neurons. High-frequency oscillations in the gamma range (40-200 Hz) are of endogenous origin, and their function is to reinforce the synaptic inputs to those neurons which are involved in the synthesis of a gestalt.

Distinctive signatures of recursion.

PubMed

Martins, Maurício Dias

2012-07-19

Although recursion has been hypothesized to be a necessary capacity for the evolution of language, the multiplicity of definitions being used has undermined the broader interpretation of empirical results. I propose that only a definition focused on representational abilities allows the prediction of specific behavioural traits that enable us to distinguish recursion from non-recursive iteration and from hierarchical embedding: only subjects able to represent recursion, i.e. to represent different hierarchical dependencies (related by parenthood) with the same set of rules, are able to generalize and produce new levels of embedding beyond those specified a priori (in the algorithm or in the input). The ability to use such representations may be advantageous in several domains: action sequencing, problem-solving, spatial navigation, social navigation and for the emergence of conventionalized communication systems. The ability to represent contiguous hierarchical levels with the same rules may lead subjects to expect unknown levels and constituents to behave similarly, and this prior knowledge may bias learning positively. Finally, a new paradigm to test for recursion is presented. Preliminary results suggest that the ability to represent recursion in the spatial domain recruits both visual and verbal resources. Implications regarding language evolution are discussed.

Refined hierarchical kinematics quasi-3D Ritz models for free vibration analysis of doubly curved FGM shells and sandwich shells with FGM core

NASA Astrophysics Data System (ADS)

Fazzolari, Fiorenzo A.; Carrera, Erasmo

2014-02-01

In this paper, the Ritz minimum energy method, based on the use of the Principle of Virtual Displacements (PVD), is combined with refined Equivalent Single Layer (ESL) and Zig Zag (ZZ) shell models hierarchically generated by exploiting the use of Carrera's Unified Formulation (CUF), in order to engender the Hierarchical Trigonometric Ritz Formulation (HTRF). The HTRF is then employed to carry out the free vibration analysis of doubly curved shallow and deep functionally graded material (FGM) shells. The PVD is further used in conjunction with the Gauss theorem to derive the governing differential equations and related natural boundary conditions. Donnell-Mushtari's shallow shell-type equations are given as a particular case. Doubly curved FGM shells and doubly curved sandwich shells made up of isotropic face sheets and FGM core are investigated. The proposed shell models are widely assessed by comparison with the literature results. Two benchmarks are provided and the effects of significant parameters such as stacking sequence, boundary conditions, length-to-thickness ratio, radius-to-length ratio and volume fraction index on the circular frequency parameters and modal displacements are discussed.

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

PubMed

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Fostering radical conceptual change through dual-situated learning model

NASA Astrophysics Data System (ADS)

She, Hsiao-Ching

2004-02-01

This article examines how the Dual-Situated Learning Model (DSLM) facilitates a radical change of concepts that involve the understanding of matter, process, and hierarchical attributes. The DSLM requires knowledge of students' prior beliefs of science concepts and the nature of these concepts. In addition, DSLM also serves two functions: it creates dissonance with students' prior knowledge by challenging their epistemological and ontological beliefs about science concepts, and it provides essential mental sets for students to reconstruct a more scientific view of the concepts. In this study, the concept heat transfer: heat conduction and convection, which requires an understanding of matter, process, and hierarchical attributes, was chosen to examine how DSLM can facilitate radical conceptual change among students. Results show that DSLM has great potential to foster a radical conceptual change process in learning heat transfer. Radical conceptual change can definitely be achieved and does not necessarily involve a slow or gradual process.

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

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

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

Biomimetic wall-shaped hierarchical microstructure for gecko-like attachment.

PubMed

Kasem, Haytam; Tsipenyuk, Alexey; Varenberg, Michael

2015-04-21

Most biological hairy adhesive systems involved in locomotion rely on spatula-shaped terminal elements, whose operation has been actively studied during the last decade. However, though functional principles underlying their amazing performance are now well understood, due to technical difficulties in manufacturing the complex structure of hierarchical spatulate systems, a biomimetic surface structure featuring true shear-induced dynamic attachment still remains elusive. To try bridging this gap, a novel method of manufacturing gecko-like attachment surfaces is devised based on a laser-micromachining technology. This method overcomes the inherent disadvantages of photolithography techniques and opens wide perspectives for future production of gecko-like attachment systems. Advanced smart-performance surfaces featuring thin-film-based hierarchical shear-activated elements are fabricated and found capable of generating friction force of several tens of times the contact load, which makes a significant step forward towards a true gecko-like adhesive.

One-pot synthesis of hierarchical FeZSM-5 zeolites from natural aluminosilicates for selective catalytic reduction of NO by NH3

PubMed Central

Yue, Yuanyuan; Liu, Haiyan; Yuan, Pei; Yu, Chengzhong; Bao, Xiaojun

2015-01-01

Iron-modified ZSM-5 zeolites (FeZSM-5s) have been considered to be a promising catalyst system to reduce nitrogen oxide emissions, one of the most important global environmental issues, but their synthesis faces enormous economic and environmental challenges. Herein we report a cheap and green strategy to fabricate hierarchical FeZSM-5 zeolites from natural aluminosilicate minerals via a nanoscale depolymerization-reorganization method. Our strategy is featured by neither using any aluminum-, silicon-, or iron-containing inorganic chemical nor involving any mesoscale template and any post-synthetic modification. Compared with the conventional FeZSM-5 synthesized from inorganic chemicals with the similar Fe content, the resulting hierarchical FeZSM-5 with highly-dispersed iron species showed superior catalytic activity in the selective catalytic reduction of NO by NH3. PMID:25791958

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.

The Fragility of Individual-Based Explanations of Social Hierarchies: A Test Using Animal Pecking Orders

PubMed Central

2016-01-01

The standard approach in accounting for hierarchical differentiation in biology and the social sciences considers a hierarchy as a static distribution of individuals possessing differing amounts of some valued commodity, assumes that the hierarchy is generated by micro-level processes involving individuals, and attempts to reverse engineer the processes that produced the hierarchy. However, sufficient experimental and analytical results are available to evaluate this standard approach in the case of animal dominance hierarchies (pecking orders). Our evaluation using evidence from hierarchy formation in small groups of both hens and cichlid fish reveals significant deficiencies in the three tenets of the standard approach in accounting for the organization of dominance hierarchies. In consequence, we suggest that a new approach is needed to explain the organization of pecking orders and, very possibly, by implication, for other kinds of social hierarchies. We develop an example of such an approach that considers dominance hierarchies to be dynamic networks, uses dynamic sequences of interaction (dynamic network motifs) to explain the organization of dominance hierarchies, and derives these dynamic sequences directly from observation of hierarchy formation. We test this dynamical explanation using computer simulation and find a good fit with actual dynamics of hierarchy formation in small groups of hens. We hypothesize that the same dynamic sequences are used in small groups of many other animal species forming pecking orders, and we discuss the data required to evaluate our hypothesis. Finally, we briefly consider how our dynamic approach may be generalized to other kinds of social hierarchies using the example of the distribution of empty gastropod (snail) shells occupied in populations of hermit crabs. PMID:27410230

Regional differences in mitochondrial DNA methylation in human post-mortem brain tissue.

PubMed

Devall, Matthew; Smith, Rebecca G; Jeffries, Aaron; Hannon, Eilis; Davies, Matthew N; Schalkwyk, Leonard; Mill, Jonathan; Weedon, Michael; Lunnon, Katie

2017-01-01

DNA methylation is an important epigenetic mechanism involved in gene regulation, with alterations in DNA methylation in the nuclear genome being linked to numerous complex diseases. Mitochondrial DNA methylation is a phenomenon that is receiving ever-increasing interest, particularly in diseases characterized by mitochondrial dysfunction; however, most studies have been limited to the investigation of specific target regions. Analyses spanning the entire mitochondrial genome have been limited, potentially due to the amount of input DNA required. Further, mitochondrial genetic studies have been previously confounded by nuclear-mitochondrial pseudogenes. Methylated DNA Immunoprecipitation Sequencing is a technique widely used to profile DNA methylation across the nuclear genome; however, reads mapped to mitochondrial DNA are often discarded. Here, we have developed an approach to control for nuclear-mitochondrial pseudogenes within Methylated DNA Immunoprecipitation Sequencing data. We highlight the utility of this approach in identifying differences in mitochondrial DNA methylation across regions of the human brain and pre-mortem blood. We were able to correlate mitochondrial DNA methylation patterns between the cortex, cerebellum and blood. We identified 74 nominally significant differentially methylated regions ( p  < 0.05) in the mitochondrial genome, between anatomically separate cortical regions and the cerebellum in matched samples ( N  = 3 matched donors). Further analysis identified eight significant differentially methylated regions between the total cortex and cerebellum after correcting for multiple testing. Using unsupervised hierarchical clustering analysis of the mitochondrial DNA methylome, we were able to identify tissue-specific patterns of mitochondrial DNA methylation between blood, cerebellum and cortex. Our study represents a comprehensive analysis of the mitochondrial methylome using pre-existing Methylated DNA Immunoprecipitation Sequencing data to identify brain region-specific patterns of mitochondrial DNA methylation.

Constructing and Classifying Email Networks from Raw Forensic Images

DTIC Science & Technology

2016-09-01

data mining for sequence and pattern mining ; in medical imaging for image segmentation; and in computer vision for object recognition” [28]. 2.3.1...machine learning and data mining suite that is written in Python. It provides a platform for experiment selection, recommendation systems, and...predictivemod- eling. The Orange library is a hierarchically-organized toolbox of data mining components. Data filtering and probability assessment are at the

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei

PubMed Central

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-01-01

Abstract Background For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. Findings We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. Conclusions We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei’s genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control. PMID:29267857

Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

NASA Astrophysics Data System (ADS)

Ren, Z.; Jensch, P.; Ameling, W.

1989-03-01

The success of knowledge-based image analysis methodology and implementation tools depends largely on an appropriately and efficiently built model wherein the domain-specific context information about and the inherent structure of the observed image scene have been encoded. For identifying an object in an application environment a computer vision system needs to know firstly the description of the object to be found in an image or in an image sequence, secondly the corresponding relationships between object descriptions within the image sequence. This paper presents models of image objects scenes by means of hierarchically structured classes. Using the topovisual formalism of graph and higraph, we are currently studying principally the relational aspect and data abstraction of the modeling in order to visualize the structural nature resident in image objects and scenes, and to formalize. their descriptions. The goal is to expose the structure of image scene and the correspondence of image objects in the low level image interpretation. process. The object-based system design approach has been applied to build the model base. We utilize the object-oriented programming language C + + for designing, testing and implementing the abstracted entity classes and the operation structures which have been modeled topovisually. The reference images used for modeling prototypes of objects and scenes are from industrial environments as'well as medical applications.

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei.

PubMed

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-02-01

For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei's genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control.

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

DOE PAGES

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

2017-11-09

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Musical melody and speech intonation: singing a different tune.

PubMed

Zatorre, Robert J; Baum, Shari R

2012-01-01

Music and speech are often cited as characteristically human forms of communication. Both share the features of hierarchical structure, complex sound systems, and sensorimotor sequencing demands, and both are used to convey and influence emotions, among other functions [1]. Both music and speech also prominently use acoustical frequency modulations, perceived as variations in pitch, as part of their communicative repertoire. Given these similarities, and the fact that pitch perception and production involve the same peripheral transduction system (cochlea) and the same production mechanism (vocal tract), it might be natural to assume that pitch processing in speech and music would also depend on the same underlying cognitive and neural mechanisms. In this essay we argue that the processing of pitch information differs significantly for speech and music; specifically, we suggest that there are two pitch-related processing systems, one for more coarse-grained, approximate analysis and one for more fine-grained accurate representation, and that the latter is unique to music. More broadly, this dissociation offers clues about the interface between sensory and motor systems, and highlights the idea that multiple processing streams are a ubiquitous feature of neuro-cognitive architectures.

Individualised cancer therapeutics: dream or reality? Therapeutics construction.

PubMed

Shen, Yuqiao; Senzer, Neil; Nemunaitis, John

2005-11-01

The analysis of DNA microarray and proteomic data, and the subsequent integration into functional expression sets, provides a circuit map of the hierarchical cellular networks responsible for sustaining the viability and environmental competitiveness of cancer cells, that is, their robust systematics. These technologies can be used to 'snapshot' the unique patterns of molecular derangements and modified interactions in cancer, and allow for strategic selection of therapeutics that best match the individual profile of the tumour. This review highlights technology that can be used to selectively disrupt critical molecular targets and describes possible vehicles to deliver the synthesised molecular therapeutics to the relevant cellular compartments of the malignant cells. RNA interference (RNAi) involves a group of evolutionarily conserved gene silencing mechanisms in which small sequences of double-stranded RNA or intrinsic antisense RNA trigger mRNA cleavage or translational repression, respectively. Although RNAi molecules can be synthesised to 'silence' virtually any gene, even if upregulated, a mechanism for selective delivery of RNAi effectors to sites of malignant disease remains challenging. The authors will discuss gene-modified conditionally replicating viruses as candidate vehicles for the delivery of RNAi.

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

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

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Speed-accuracy trade-off in skilled typewriting: decomposing the contributions of hierarchical control loops.

PubMed

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

2013-06-01

Typing performance involves hierarchically structured control systems: At the higher level, an outer loop generates a word or a series of words to be typed; at the lower level, an inner loop activates the keystrokes comprising the word in parallel and executes them in the correct order. The present experiments examined contributions of the outer- and inner-loop processes to the control of speed and accuracy in typewriting. Experiments 1 and 2 involved discontinuous typing of single words, and Experiments 3 and 4 involved continuous typing of paragraphs. Across experiments, typists were able to trade speed for accuracy but were unable to type at rates faster than 100 ms/keystroke, implying limits to the flexibility of the underlying processes. The analyses of the component latencies and errors indicated that the majority of the trade-offs were due to inner-loop processing. The contribution of outer-loop processing to the trade-offs was small, but it resulted in large costs in error rate. Implications for strategic control of automatic processes are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Fmoc-RGDS based fibrils: atomistic details of their hierarchical assembly.

PubMed

Zanuy, David; Poater, Jordi; Solà, Miquel; Hamley, Ian W; Alemán, Carlos

2016-01-14

We describe the 3D supramolecular structure of Fmoc-RGDS fibrils, where Fmoc and RGDS refer to the hydrophobic N-(fluorenyl-9-methoxycarbonyl) group and the hydrophilic Arg-Gly-Asp-Ser peptide sequence, respectively. For this purpose, we performed atomistic all-atom molecular dynamics simulations of a wide variety of packing modes derived from both parallel and antiparallel β-sheet configurations. The proposed model, which closely resembles the cross-β core structure of amyloids, is stabilized by π-π stacking interactions between hydrophobic Fmoc groups. More specifically, in this organization, the Fmoc-groups of β-strands belonging to the same β-sheet form columns of π-stacked aromatic rings arranged in a parallel fashion. Eight of such columns pack laterally forming a compact and dense hydrophobic core, in which two central columns are surrounded by three adjacent columns on each side. In addition to such Fmoc···Fmoc interactions, the hierarchical assembly of the constituent β-strands involves a rich variety of intra- and inter-strand interactions. Accordingly, hydrogen bonding, salt bridges and π-π stacking interactions coexist in the highly ordered packing network proposed for the Fmoc-RGDS amphiphile. Quantum mechanical calculations, which have been performed to quantify the above referred interactions, confirm the decisive role played by the π-π stacking interactions between the rings of the Fmoc groups, even though both inter-strand and intra-strand hydrogen bonds and salt bridges also play a non-negligible role. Overall, these results provide a solid reference to complement the available experimental data, which are not precise enough to determine the fibril structure, and reconcile previous independent observations.

An Analysis of a Typical Instructional Unit in Junior High School Science to Determine the Explicit and Implicit Concept Loading Involved. Final Report.

ERIC Educational Resources Information Center

Smith, Herbert A.

This study involved examining an instructional unit with regard to its concept content and appropriateness for its target audience. The study attempted to determine (1) what concepts are treated explicitly or implicitly, (2) whether there is a hierarchical conceptual structure within the unit, (3) what level of sophistication is required to…

Effects of Traditional and Nontraditional Forms of Parental Involvement on School-Level Achievement Outcome: An HLM Study Using SASS 2007-2008

ERIC Educational Resources Information Center

Shen, Jianping; Washington, Alandra L.; Bierlein Palmer, Louann; Xia, Jiangang

2014-01-01

The authors examined parental involvement's (PI) impact on school performance. The hierarchical linear modeling method was applied to national Schools and Staffing Survey 2007-2008 data. They found that PI variables explained significant variance for the outcomes of (a) meeting adequate yearly progress (AYP) and (b) being free from sanctions. The…

In Situ Hi-C Library Preparation for Plants to Study Their Three-Dimensional Chromatin Interactions on a Genome-Wide Scale.

PubMed

Liu, Chang

2017-01-01

The spatial organization of the genome in the nucleus is critical for many cellular processes. It has been broadly accepted that the packing of chromatin inside the nucleus is not random, but structured at several hierarchical levels. The Hi-C method combines Chromatin Conformation Capture and high-throughput sequencing, which allows interrogating genome-wide chromatin interactions. Depending on the sequencing depth, chromatin packing patterns derived from Hi-C experiments can be viewed on a chromosomal scale or at a local genic level. Here, I describe a protocol of plant in situ Hi-C library preparation, which covers procedures starting from tissue fixation to library amplification.

COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

PubMed

Cui, Licong

Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance qualities of biomedical ontologies by performing cross-ontology examination.

Multiscale Inorganic Hierarchically Materials: Towards an Improved Orthopaedic Regenerative Medicine.

PubMed

Ruso, Juan M; Sartuqui, Javier; Messina, Paula V

2015-01-01

Bone is a biologically and structurally sophisticated multifunctional tissue. It dynamically responds to biochemical, mechanical and electrical clues by remodelling itself and accordingly the maximum strength and toughness are along the lines of the greatest applied stress. The challenge is to develop an orthopaedic biomaterial that imitates the micro- and nano-structural elements and compositions of bone to locally match the properties of the host tissue resulting in a biologically fixed implant. Looking for the ideal implant, the convergence of life and materials sciences occurs. Researchers in many different fields apply their expertise to improve implantable devices and regenerative medicine. Materials of all kinds, but especially hierarchical nano-materials, are being exploited. The application of nano-materials with hierarchical design to calcified tissue reconstructive medicine involve intricate systems including scaffolds with multifaceted shapes that provides temporary mechanical function; materials with nano-topography modifications that guarantee their integration to tissues and that possesses functionalized surfaces to transport biologic factors to stimulate tissue growth in a controlled, safe, and rapid manner. Furthermore materials that should degrade on a timeline coordinated to the time that takes the tissues regrow, are prepared. These implantable devices are multifunctional and for its construction they involve the use of precise strategically techniques together with specific material manufacturing processes that can be integrated to achieve in the design, the required multifunctionality. For such reasons, even though the idea of displacement from synthetic implants and tissue grafts to regenerative-medicine-based tissue reconstruction has been guaranteed for well over a decade, the reality has yet to emerge. In this paper, we examine the recent approaches to create enhanced bioactive materials. Their design and manufacturing procedures as well as the experiments to integrate them into engineer hierarchical inorganic materials for their practical application in calcified tissue reparation are evaluated.

Reflections on the pathogenesis of Down syndrome.

PubMed

Opitz, J M; Gilbert-Barness, E F

1990-01-01

Present efforts to identify, isolate, and characterize in molecular terms the "consensus" segment of 21q sufficient to cause most of the major and some of the most characteristic minor manifestations of Down syndrome will soon provide answers to many questions. However, we think that a reductionist approach to explain the Down syndrome phenotype in a "linear" manner from the DNA sequence of the segment will be doomed to failure from the outset because of the open, complex, nonlinear, hierarchical nature of morphogenetic systems. Neo-Darwinism is under strong attack; most genetic changes accumulated over time may very well be of neutral effect, and detailed studies in several related groups of vertebrate species has shown that molecular and organismal evolution are largely independent of one another. It has been pointed out recently that biology lacks a theory of ontogenetic and phylogenetic development, and that a purely "genocentric" view of biology at the expense of the complexly hierarchical intrinsic epigenetic attributes of developmental systems is "out of focus with respect to ... biological organization and morphogenesis," and may be "a residue of nineteenth century romantic idealism." Down syndrome impresses us as a paradigm of increased developmental variability due to a deceleration of the rate of development (neoteny) with many anomalies of incomplete morphogenesis (vestigia), atavisms, increased morphometric variability with many decreased means, increased variances, and increased fluctuating asymmetry. These abnormalities, together with highly increased risk of prenatal death and postnatal morbidity, impaired growth, and abnormal CNS and gonadal structure and function characteristic of most aneuploidy syndromes, suggest to us that the pathogenesis of Down syndrome is best viewed in terms of the mechanisms of speciation. Transgenic experiment involving sequential or overlapping pieces of "the consensus segment" on distal 21q22.1-22.3 may help decide to what extent the Down syndrome phenotype can be resolved into the additive effect of several pleiotropic oligogenes with epistatic interaction or the indirect secondary "mass" effect of a specific segment of 21q with epistatic interaction involving multiple loci on 21q and other chromosomes.

Development of self-compressing BLSOM for comprehensive analysis of big sequence data.

PubMed

Kikuchi, Akihito; Ikemura, Toshimichi; Abe, Takashi

2015-01-01

With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM), which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM) for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method's suitability for efficient knowledge discovery from big sequence data.

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers.

PubMed

Amalric, Marie; Wang, Liping; Pica, Pierre; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a "geometrical language" with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them.

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers

PubMed Central

Amalric, Marie; Wang, Liping; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a “geometrical language” with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them. PMID:28125595

Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

PubMed Central

Freitas, Tracey Allen K.; Li, Po-E; Scholz, Matthew B.; Chain, Patrick S. G.

2015-01-01

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. PMID:25765641

Building an Unusual White-Dwarf Duo

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-09-01

A new study has examined how the puzzling wide binary system HS 2220+2146 which consists of two white dwarfs orbiting each other might have formed. This system may be an example of a new evolutionary pathway for wide white-dwarf binaries.Evolution of a BinaryMore than 100 stellar systems have been discovered consisting of two white dwarfs in a wide orbit around each other. How do these binaries form? In the traditional picture, the system begins as a binary consisting of two main-sequence stars. Due to the large separation between the stars, the stars evolve independently, each passing through the main-sequence and giant branches and ending their lives as white dwarfs.An illustration of a hierarchical triple star system, in which two stars orbit each other, and a third star orbits the pair. [NASA/JPL-Caltech]Because more massive stars evolve more quickly, the most massive of the two stars in a binary pair should be the first to evolve into a white dwarf. Consequently, when we observe a double-white-dwarf binary, its usually a safe bet that the more massive of the two white dwarfs will also be the older and cooler of the pair, since it should have formed first.But in the case of the double-white-dwarf binary HS 2220+2146, the opposite is true: the more massive of the two white dwarfs appears to be the younger and hotter of the pair. If it wasnt created in the traditional way, then how did this system form?Two From Three?Led by Jeff Andrews (Foundation for Research and Technology-Hellas, Greece and Columbia University), a team of scientists recently examined this system more carefully, analyzing its spectra to confirm our understanding of the white dwarfs temperatures and masses.Based on their observations, Andrews and collaborators determined that there are no hidden additional companions that could have caused the unusual evolution of this system. Instead, the team proposed that this unusual binary might be an example of an evolutionary channel that involves three stars.The authors proposed formation scenario for H220+2146. In this picture, the inner binary merges to form a blue straggler. This star and the remaining main-sequence star then evolve independently into white dwarfs, forming the system observed today. [Andrews et al. 2016]An Early MergerIn the model the authors propose for HS 2220+2146, the binary system began as a hierarchical triple system of main-sequence stars. The innermost binary then merged to form a large star known as a blue straggler a star that, due to the merger, will evolve more slowly than its larger mass implies it should.The blue straggler and the remaining main-sequence star, still in a wide orbit, then continued to evolve independently of each other. The smaller star ended its main-sequence lifetime and became a white dwarf first, followed by the more massive but slowly evolving blue straggler thus forming the system we observe today.If the authors model is correct, then HS 2220+2146 would be the first binary double white dwarf known to have formed through this channel. ESAs Gaia mission, currently underway, is expected to discover up to a million new white dwarfs, many of which will likely be in wide binary systems. Among these, we may well find many other systems like HS 2220+2146 that formed in the same way.CitationJeff J. Andrews et al 2016 ApJ 828 38. doi:10.3847/0004-637X/828/1/38

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

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.

2002-01-01

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

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling

PubMed Central

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision. PMID:27303323

Biomass-derived nitrogen-doped porous carbons with tailored hierarchical porosity and high specific surface area for high energy and power density supercapacitors

NASA Astrophysics Data System (ADS)

Sun, Junting; Niu, Jin; Liu, Mengyue; Ji, Jing; Dou, Meiling; Wang, Feng

2018-01-01

Porous carbon materials with hierarchical structures attract intense interest for the development of high-performance supercapacitors. Herein, we demonstrate a facile and efficient strategy to synthesize nitrogen-doped hierarchically porous carbons with tailored porous structure combined with high specific surface area (SSA), which involves a pre-carbonization and a subsequent carbonization combined with KOH activation of silkworm cocoon precursors. Through adjusting the mass ratio of the activator (KOH) to pre-carbonized precursor in the activation process, the hierarchically porous carbon prepared at the mass ratio of 2 (referred to as NHPC-2) possesses a high defect density and a high SSA of 3386 m2 g-1 as well as the relatively high volumetric proportion of mesopores and macropores (45.5%). As a result, the energy density and power density of the symmetric supercapacitor based on NHPC-2 electrode are as high as 34.41 Wh kg-1 and 31.25 kW kg-1 in organic-solvent electrolyte, and are further improved to 112.1 Wh kg-1 and 23.91 kW kg-1 in ionic-liquid electrolyte.

On a High-Fidelity Hierarchical Approach to Buckling Load Calculations

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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.

Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

NASA Astrophysics Data System (ADS)

Parlett, Christopher M. A.; Isaacs, Mark A.; Beaumont, Simon K.; Bingham, Laura M.; Hondow, Nicole S.; Wilson, Karen; Lee, Adam F.

2016-02-01

The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol-gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous-mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

Hierarchical organization of butterfly gyroid nanostructures provide a time-frozen glimpse of intracellular membrane development

NASA Astrophysics Data System (ADS)

Wilts, Bodo; Winter, Benjamin; Klatt, Michael; Butz, Benjamin; Fischer, Michael; Kelly, Stephen; Spieker, Erdmann; Steiner, Ullrich; Schroeder-Turk, Gerd

The formation of the biophotonic gyroid material in butterfly wing scales is an exceptional feat of evolutionary engineering of functional nanostructures. Previous work hypothesized that this nanostructure forms by chitin polymerization inside a convoluted membrane of corresponding shape in the endoplasmic reticulum. In vivo imaging however cannot yet elucidate this dynamic formation process, including whether membrane folding and chitin expression are simultaneous or subsequent processes. Here we show an unusual hierarchical ultrastructure in a Hairstreak butterfly that allows high-resolution 3D microscopy. Rather than the conventional polycrystalline space-filling arrangement, the gyroid occurs in isolated facetted crystallites with a pronounced size-gradient. This arrangement is interpreted as a sequence of time-frozen snapshots of the morphogenesis. This provides insight into the formation mechanisms of the nanoporous gyroid material, especially when compared among other butterflies with different arrangements. Financially supported through DFG, the NCCR Bio-inspired Mateirals and the SNF Ambizione programme.

A fully automatic evolutionary classification of protein folds: Dali Domain Dictionary version 3

PubMed Central

Dietmann, Sabine; Park, Jong; Notredame, Cedric; Heger, Andreas; Lappe, Michael; Holm, Liisa

2001-01-01

The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families. PMID:11125048

On the Generation of the Hubble Sequence Through an Internal Secular Dynamical Process

DTIC Science & Technology

2004-01-01

is apparently brought about by the fact that spiral galaxies still have varying reserves of baryonic dark matter to form stars, therefore as the...central baryonic dark matter supply, thus the ellipticals in more advanced stage of evolution (which also generally have larger L) will experi- ence...This view is particularly favored by the currently popular hierarchical clustering/cold dark matter (CDM) paradigm of structure formation and evolution

Decision net, directed graph, and neural net processing of imaging spectrometer data

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki; Barnard, Etienne

1989-01-01

A decision-net solution involving a novel hierarchical classifier and a set of multiple directed graphs, as well as a neural-net solution, are respectively presented for large-class problem and mixture problem treatments of imaging spectrometer data. The clustering method for hierarchical classifier design, when used with multiple directed graphs, yields an efficient decision net. New directed-graph rules for reducing local maxima as well as the number of perturbations required, and the new starting-node rules for extending the reachability and reducing the search time of the graphs, are noted to yield superior results, as indicated by an illustrative 500-class imaging spectrometer problem.

De novo assembly of a haplotype-resolved human genome.

PubMed

Cao, Hongzhi; Wu, Honglong; Luo, Ruibang; Huang, Shujia; Sun, Yuhui; Tong, Xin; Xie, Yinlong; Liu, Binghang; Yang, Hailong; Zheng, Hancheng; Li, Jian; Li, Bo; Wang, Yu; Yang, Fang; Sun, Peng; Liu, Siyang; Gao, Peng; Huang, Haodong; Sun, Jing; Chen, Dan; He, Guangzhu; Huang, Weihua; Huang, Zheng; Li, Yue; Tellier, Laurent C A M; Liu, Xiao; Feng, Qiang; Xu, Xun; Zhang, Xiuqing; Bolund, Lars; Krogh, Anders; Kristiansen, Karsten; Drmanac, Radoje; Drmanac, Snezana; Nielsen, Rasmus; Li, Songgang; Wang, Jian; Yang, Huanming; Li, Yingrui; Wong, Gane Ka-Shu; Wang, Jun

2015-06-01

The human genome is diploid, and knowledge of the variants on each chromosome is important for the interpretation of genomic information. Here we report the assembly of a haplotype-resolved diploid genome without using a reference genome. Our pipeline relies on fosmid pooling together with whole-genome shotgun strategies, based solely on next-generation sequencing and hierarchical assembly methods. We applied our sequencing method to the genome of an Asian individual and generated a 5.15-Gb assembled genome with a haplotype N50 of 484 kb. Our analysis identified previously undetected indels and 7.49 Mb of novel coding sequences that could not be aligned to the human reference genome, which include at least six predicted genes. This haplotype-resolved genome represents the most complete de novo human genome assembly to date. Application of our approach to identify individual haplotype differences should aid in translating genotypes to phenotypes for the development of personalized medicine.

Control of Task Sequences: What is the Role of Language?

PubMed Central

Mayr, Ulrich; Kleffner, Killian; Kikumoto, Atsushi; Redford, Melissa A.

2015-01-01

It is almost a truism that language aids serial-order control through self-cuing of upcoming sequential elements. We measured speech onset latencies as subjects performed hierarchically organized task sequences while "thinking aloud" each task label. Surprisingly, speech onset latencies and response times (RTs) were highly synchronized, a pattern that is not consistent with the hypothesis that speaking aids proactive retrieval of upcoming sequential elements during serial-order control. We also found that when instructed to do so, participants were able to speak task labels prior to presentation of response-relevant stimuli and that this substantially reduced RT signatures of retrieval—however at the cost of more sequencing errors. Thus, while proactive retrieval is possible in principle, in natural situations it seems to be prevented through a strong, "gestalt-like" tendency to synchronize speech and action. We suggest that this tendency may support context updating rather than proactive control. PMID:24274386

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

PubMed Central

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

2014-01-01

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

Hierarchical animal movement models for population-level inference

USGS Publications Warehouse

Hooten, Mevin B.; Buderman, Frances E.; Brost, Brian M.; Hanks, Ephraim M.; Ivans, Jacob S.

2016-01-01

New methods for modeling animal movement based on telemetry data are developed regularly. With advances in telemetry capabilities, animal movement models are becoming increasingly sophisticated. Despite a need for population-level inference, animal movement models are still predominantly developed for individual-level inference. Most efforts to upscale the inference to the population level are either post hoc or complicated enough that only the developer can implement the model. Hierarchical Bayesian models provide an ideal platform for the development of population-level animal movement models but can be challenging to fit due to computational limitations or extensive tuning required. We propose a two-stage procedure for fitting hierarchical animal movement models to telemetry data. The two-stage approach is statistically rigorous and allows one to fit individual-level movement models separately, then resample them using a secondary MCMC algorithm. The primary advantages of the two-stage approach are that the first stage is easily parallelizable and the second stage is completely unsupervised, allowing for an automated fitting procedure in many cases. We demonstrate the two-stage procedure with two applications of animal movement models. The first application involves a spatial point process approach to modeling telemetry data, and the second involves a more complicated continuous-time discrete-space animal movement model. We fit these models to simulated data and real telemetry data arising from a population of monitored Canada lynx in Colorado, USA.

Histoimmunogenetics Markup Language 1.0: Reporting next generation sequencing-based HLA and KIR genotyping.

PubMed

Milius, Robert P; Heuer, Michael; Valiga, Daniel; Doroschak, Kathryn J; Kennedy, Caleb J; Bolon, Yung-Tsi; Schneider, Joel; Pollack, Jane; Kim, Hwa Ran; Cereb, Nezih; Hollenbach, Jill A; Mack, Steven J; Maiers, Martin

2015-12-01

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and Sequence Based Typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Participatory Decision Making.

ERIC Educational Resources Information Center

King, M. Bruce; And Others

Shifting from traditional, hierarchical bureaucracies to participatory governance and decision making is a major theme in school restructuring. This paper focuses on the involvement of teachers in key aspects of school decision making. Specifically, the paper describes how changes in power relations supported teachers' focus on improving the…

Application of growing hierarchical SOM for visualisation of network forensics traffic data.

PubMed

Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

2012-08-01

Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2018-01-01

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

A deep learning pipeline for Indian dance style classification

NASA Astrophysics Data System (ADS)

Dewan, Swati; Agarwal, Shubham; Singh, Navjyoti

2018-04-01

In this paper, we address the problem of dance style classification to classify Indian dance or any dance in general. We propose a 3-step deep learning pipeline. First, we extract 14 essential joint locations of the dancer from each video frame, this helps us to derive any body region location within the frame, we use this in the second step which forms the main part of our pipeline. Here, we divide the dancer into regions of important motion in each video frame. We then extract patches centered at these regions. Main discriminative motion is captured in these patches. We stack the features from all such patches of a frame into a single vector and form our hierarchical dance pose descriptor. Finally, in the third step, we build a high level representation of the dance video using the hierarchical descriptors and train it using a Recurrent Neural Network (RNN) for classification. Our novelty also lies in the way we use multiple representations for a single video. This helps us to: (1) Overcome the RNN limitation of learning small sequences over big sequences such as dance; (2) Extract more data from the available dataset for effective deep learning by training multiple representations. Our contributions in this paper are three-folds: (1) We provide a deep learning pipeline for classification of any form of dance; (2) We prove that a segmented representation of a dance video works well with sequence learning techniques for recognition purposes; (3) We extend and refine the ICD dataset and provide a new dataset for evaluation of dance. Our model performs comparable or better in some cases than the state-of-the-art on action recognition benchmarks.

Learning of goal-relevant and -irrelevant complex visual sequences in human V1.

PubMed

Rosenthal, Clive R; Mallik, Indira; Caballero-Gaudes, Cesar; Sereno, Martin I; Soto, David

2018-06-12

Learning and memory are supported by a network involving the medial temporal lobe and linked neocortical regions. Emerging evidence indicates that primary visual cortex (i.e., V1) may contribute to recognition memory, but this has been tested only with a single visuospatial sequence as the target memorandum. The present study used functional magnetic resonance imaging to investigate whether human V1 can support the learning of multiple, concurrent complex visual sequences involving discontinous (second-order) associations. Two peripheral, goal-irrelevant but structured sequences of orientated gratings appeared simultaneously in fixed locations of the right and left visual fields alongside a central, goal-relevant sequence that was in the focus of spatial attention. Pseudorandom sequences were introduced at multiple intervals during the presentation of the three structured visual sequences to provide an online measure of sequence-specific knowledge at each retinotopic location. We found that a network involving the precuneus and V1 was involved in learning the structured sequence presented at central fixation, whereas right V1 was modulated by repeated exposure to the concurrent structured sequence presented in the left visual field. The same result was not found in left V1. These results indicate for the first time that human V1 can support the learning of multiple concurrent sequences involving complex discontinuous inter-item associations, even peripheral sequences that are goal-irrelevant. Copyright © 2018. Published by Elsevier Inc.

A hierarchical model for clustering m(6)A methylation peaks in MeRIP-seq data.

PubMed

Cui, Xiaodong; Meng, Jia; Zhang, Shaowu; Rao, Manjeet K; Chen, Yidong; Huang, Yufei

2016-08-22

The recent advent of the state-of-art high throughput sequencing technology, known as Methylated RNA Immunoprecipitation combined with RNA sequencing (MeRIP-seq) revolutionizes the area of mRNA epigenetics and enables the biologists and biomedical researchers to have a global view of N (6)-Methyladenosine (m(6)A) on transcriptome. Yet there is a significant need for new computation tools for processing and analysing MeRIP-Seq data to gain a further insight into the function and m(6)A mRNA methylation. We developed a novel algorithm and an open source R package ( http://compgenomics.utsa.edu/metcluster ) for uncovering the potential types of m(6)A methylation by clustering the degree of m(6)A methylation peaks in MeRIP-Seq data. This algorithm utilizes a hierarchical graphical model to model the reads account variance and the underlying clusters of the methylation peaks. Rigorous statistical inference is performed to estimate the model parameter and detect the number of clusters. MeTCluster is evaluated on both simulated and real MeRIP-seq datasets and the results demonstrate its high accuracy in characterizing the clusters of methylation peaks. Our algorithm was applied to two different sets of real MeRIP-seq datasets and reveals a novel pattern that methylation peaks with less peak enrichment tend to clustered in the 5' end of both in both mRNAs and lncRNAs, whereas those with higher peak enrichment are more likely to be distributed in CDS and towards the 3'end of mRNAs and lncRNAs. This result might suggest that m(6)A's functions could be location specific. In this paper, a novel hierarchical graphical model based algorithm was developed for clustering the enrichment of methylation peaks in MeRIP-seq data. MeTCluster is written in R and is publicly available.

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

Serial, parallel and hierarchical decision making in primates

PubMed Central

Zylberberg, Ariel; Lorteije, Jeannette AM; Ouellette, Brian G; De Zeeuw, Chris I; Sigman, Mariano; Roelfsema, Pieter

2017-01-01

The study of decision-making has mainly focused on isolated decisions where choices are associated with motor actions. However, problem-solving often involves considering a hierarchy of sub-decisions. In a recent study (Lorteije et al. 2015), we reported behavioral and neuronal evidence for hierarchical decision making in a task with a small decision tree. We observed a first phase of parallel evidence integration for multiple sub-decisions, followed by a phase in which the overall strategy formed. It has been suggested that a 'flat' competition between the ultimate motor actions might also explain these results. A reanalysis of the data does not support the critical predictions of flat models. We also examined the time-course of decision making in other, related tasks and report conditions where evidence integration for successive decisions is decoupled, which excludes flat models. We conclude that the flexibility of decision-making implies that the strategies are genuinely hierarchical. DOI: http://dx.doi.org/10.7554/eLife.17331.001 PMID:28648172

Regulation of osteogenesis by micro/nano hierarchical titanium surfaces through a Rock-Wnt5a feedback loop.

PubMed

Yu, Yonglin; Shen, Xinkun; Liu, Junjie; Hu, Yan; Ran, Qichun; Mu, Caiyun; Cai, Kaiyong

2018-05-28

Titanium substrates with micro/nano hierarchical features could positively mediate the osteogenesis of a titanium implant; nevertheless, the underlying molecular mechanism needs to be further revealed. In this work, we fabricated a micro/nano hierarchically structured Ti (MNT) sample and attempted to evaluate its topography-mediated biological effects and potential molecular mechanisms in vitro. The results proved that MNT could not only affect cell morphology and osteogenic differentiation, but also regulate ROCK activity cell biological functions of osteoblasts involved in ROCK activation, β-catenin accumulation, and high-Wnt5a expression in respect to topographical features. Moreover, blockade of ROCK activation resulted in significant inhibition of cell differentiation and Wnt5a expression. Furthermore, the anti-Wnt5a significantly down-regulated ROCK activity. In short, these results indicate the important role of ROCK-Wnt5a feedback loop in regulating cell differentiation by topographies. Copyright © 2018. Published by Elsevier B.V.

Predictive Coding Strategies for Invariant Object Recognition and Volitional Motion Control in Neuromorphic Agents

DTIC Science & Technology

2015-09-02

human behavior. In this project, we hypothesized that visual memory of past motion trajectories may be used for selecting future behavior. In other...34Decoding sequence of actions using fMRI ", Society for Neuroscience Annual Meeting, San Diego, CA, USA, Nov 9-13 2013 (only abstract) 3. Hansol Choi, Dae...Shik Kim, "Planning as inference in a Hierarchical Predictive Memory ", Proceedings of International Conference on Neural Information Processing

Taxa: An R package implementing data standards and methods for taxonomic data

PubMed Central

Foster, Zachary S.L.; Chamberlain, Scott; Grünwald, Niklaus J.

2018-01-01

The taxa R package provides a set of tools for defining and manipulating taxonomic data. The recent and widespread application of DNA sequencing to community composition studies is making large data sets with taxonomic information commonplace. However, compared to typical tabular data, this information is encoded in many different ways and the hierarchical nature of taxonomic classifications makes it difficult to work with. There are many R packages that use taxonomic data to varying degrees but there is currently no cross-package standard for how this information is encoded and manipulated. We developed the R package taxa to provide a robust and flexible solution to storing and manipulating taxonomic data in R and any application-specific information associated with it. Taxa provides parsers that can read common sources of taxonomic information (taxon IDs, sequence IDs, taxon names, and classifications) from nearly any format while preserving associated data. Once parsed, the taxonomic data and any associated data can be manipulated using a cohesive set of functions modeled after the popular R package dplyr. These functions take into account the hierarchical nature of taxa and can modify the taxonomy or associated data in such a way that both are kept in sync. Taxa is currently being used by the metacoder and taxize packages, which provide broadly useful functionality that we hope will speed adoption by users and developers. PMID:29707201

[Ecological niches of sucking lice (Phthiraptera: Anoplura) and their coevolution relationship with small mammal hosts in Yunnan, China].

PubMed

Meng, Yan-Fen; Guo, Xian-Guo; Men, Xing-Yuan; Wu, Dian

2008-02-28

To investigate the ecological niches of sucking lice (Phthiraptera: Anoplura) on the body surface of small mammal hosts and the co-evolutionary relationship between lice and mammal hosts in Yunnan Province. Thirty species of small mammals were captured and used as 30 resource sequences. The distribution and composition of the dominant 22 species of sucking lice on the body surface of the 30 species small mammal hosts were analyzed as the utilization proportion for each resource sequence. The niche breadth and proportional similarity were measured. SPSS 13.0 statistical software was used for analyzing the niche overlap matrix of sucking lice by hierarchical clustering analysis, and a dendrogram was made. The niche breadth was narrow for most species of sucking louse. Among the detected species, Hoplopleura pacifica showed the widest niche breadth, but only 0.1536. Indices of niche proportional similarity of most sucking lice were relatively small from 0.0005 to 0.4695. The 22 species of sucking lice were classified into 16 niche overlap groups, by lambda = 5.5, through a hierarchical clustering analysis for the niche overlaps, and the clustering process of most sucking lice was late. The sucking lice have a high specificity for hosts, of which different species show an apparent niche divergence on host selection. The results reveal a high coevolution between sucking lice and the mammal hosts.

Effect of the pollution level on the functional bacterial groups aiming at degrading bisphenol A and nonylphenol in natural biofilms of an urban river.

PubMed

Cai, Wei; Li, Yi; Wang, Peifang; Niu, Lihua; Zhang, Wenlong; Wang, Chao

2016-08-01

Bisphenol A (BPA) and 4-nonylphenol (NP) are ubiquitous pollutants with estrogenic activity in aquatic environment and have attracted global concern due to their disruption of endocrine systems. This study investigated the spatial distribution characteristics of the bacterial groups involved in the degradation of BPA and NP within biofilms in an urban river using terminal restriction fragment length polymorphism based on 16S rRNA gene sequences. The effects of the pollution level and water parameters on these groups were also assessed. Hierarchical cluster analysis grouped the sampling sites into three clusters reflecting their varying nutrient pollution levels of relatively slight pollution (SP), moderate pollution (MP), and high pollution (HP) based on water quality data and Environmental Quality Standard for Surface Water of China (GB3838-2002). The BPA and NP concentration in river water ranged from 0.8 to 77.5 and 10.2 to 162.9 ng L(-1), respectively. Comamonadaceae, Pseudomonadaceae, Alcaligenaceae, Bacillaceae, Sphingomonadacea, Burkholderiaceae, and Rhizobiaceae were the dominant bacterial taxa involved in BPA and NP degradation, comprising an average of 9.8, 8.1, 7.6, 6.7, 6.2, 4.1, and 2.8 % of total sequences, respectively. The total abundance of these groups showed a slight upward trend and subsequently rapidly decreased with increasing pollution levels. The average proportion of Comamonadaceae in MP river sections was almost 1.5-2 times than that in SP or HP one. The distribution of functional groups was found related to environmental variables, especially pH, conductivity, ammonium nitrogen (NH3-N), and BPA. The abundance of Comamonadaceae and Rhizobiaceae was both closely related to higher values of pH and conductivity as well as lower concentrations of NP and BPA. Alcaligenaceae and Pseudomonadaceae were associated with higher concentrations of TP and CODMn and inversely correlated with DO concentration. This study might provide effective data on bacterial group changes in polluted urban rivers.

Predictors of Cyberloafing among Preservice Information Technology Teachers

ERIC Educational Resources Information Center

Dursun, Ozcan Ozgur; Donmez, Onur; Akbulut, Yavuz

2018-01-01

The current mixed-method study investigated the extent of involvement in cyberloafing within classroom settings among preservice information technology teachers. Thirteen state universities were picked randomly from hierarchical clusters, which were determined according to the national university rankings. Then, a recent five-factor cyberloafing…

The Impact of Religious Orientation in Conjugal Bereavement among Older Adults.

ERIC Educational Resources Information Center

Rosik, Christopher H.

1989-01-01

Explored relationship between religious commitment and adaptation to widowhood among 159 widowed elderly involved in southern Californian support groups. Grief, depression, and intrinsic-extrinsic religiousness were assessed and then analyzed via hierarchical multiple regression procedures. Higher extrinsicness (religion as a means to…

Hierarchical Architectural Considerations in Econometric Modeling of Manufacturing Systems

DTIC Science & Technology

1981-06-01

behavioral factors must also be considered. A proposed economic model, to be aligned with ICAM program intentions, should be generic and have the... relevant to the effort and to identify contractors, if any, involved in economic model development. Due to the nature of involvement of other con...tractors with the ICAM program office, information which was thought relevant to the initiation of the current effort was in a lag-time and was

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

Periorbital melasma: Hierarchical cluster analysis of clinical features in Asian patients.

PubMed

Jung, Y S; Bae, J M; Kim, B J; Kang, J-S; Cho, S B

2017-11-01

Studies have shown melasma lesions to be distributed across the face in centrofacial, malar, and mandibular patterns. Meanwhile, however, melasma lesions of the periorbital area have yet to be thoroughly described. We analyzed normal and ultraviolet light-exposed photographs of patients with melasma. The periorbital melasma lesions were measured according to anatomical reference points and a hierarchical cluster analysis was performed. The periorbital melasma lesions showed clinical features of fine and homogenous melasma pigmentation, involving both the upper and lower eyelids that extended to other anatomical sites with a darker and coarser appearance. The hierarchical cluster analysis indicated that patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. Significant differences between cluster 1 and cluster 2 were found in lateral distance and inferolateral distance, but not in medial distance and superior distance. Comparing the two clusters, patients in cluster 2 were found to be significantly older and more commonly accompanied by melasma lesions of the temple and medial cheek. Our hierarchical cluster analysis of periorbital melasma lesions demonstrated that Asian patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A hierarchical model for spatial capture-recapture data

USGS Publications Warehouse

Royle, J. Andrew; Young, K.V.

2008-01-01

Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

Hierarchical group testing for multiple infections.

PubMed

Hou, Peijie; Tebbs, Joshua M; Bilder, Christopher R; McMahan, Christopher S

2017-06-01

Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11% reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. © 2016, The International Biometric Society.

Hierarchical group testing for multiple infections

PubMed Central

Hou, Peijie; Tebbs, Joshua M.; Bilder, Christopher R.; McMahan, Christopher S.

2016-01-01

Summary Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11 percent reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. PMID:27657666

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

PubMed

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

2017-11-01

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

Encoding and choice in the task span paradigm.

PubMed

Reiman, Kaitlin M; Weaver, Starla M; Arrington, Catherine M

2015-03-01

Cognitive control during sequences of planned behaviors requires both plan-level processes such as generating, maintaining, and monitoring the plan, as well as task-level processes such as selecting, establishing and implementing specific task sets. The task span paradigm (Logan in J Exp Psychol Gen 133:218-236, 2004) combines two common cognitive control paradigms, task switching and working memory span, to investigate the integration of plan-level and task-level processes during control of sequential behavior. The current study expands past task span research to include measures of encoding processes and choice behavior with volitional sequence generation, using the standard task span as well as a novel voluntary task span paradigm. In two experiments, we consider how sequence complexity, defined separately for plan-level and task-level complexity, influences sequence encoding (Experiment 1), sequence choice (Experiment 2), sequence memory, and task performance of planned sequences of action. Results indicate that participants were sensitive to sequence complexity, but that different aspects of behavior are most strongly influenced by different types of complexity. Hierarchical complexity at the plan level best predicts voluntary sequence generation and memory; while switch frequency at the task level best predicts encoding of externally defined sequences and task performance. Furthermore, performance RTs were similar for externally and internally defined plans, whereas memory was improved for internally defined sequences. Finally, participants demonstrated a significant sequence choice bias in the voluntary task span. Consistent with past research on choice behavior, volitional selection of plans was markedly influenced by both the ease of memory and performance.

Basic characteristics and realization of production system control

NASA Astrophysics Data System (ADS)

Cheng, Shaopeng; Shell, Richard; Hall, Ernest L.

1992-11-01

This paper analyzes the issues involved in developing an intelligent production control system. It describes the basic characteristics of a production control system and an effective design methodology to realize the production control functions. Petri net, subsystem and hierarchical control concepts are applied to a computer integrated material handling system (MHS). Some communication and interface requirements of the MHS are also considered in this paper. The control system solution is illustrated with an actual MHS operation case which indicates that a truly flexible and integrated production system can be realized with a Petri net operation model and a hierarchical control structure. The significance of this work is related to the different operation testing and evaluation requirements encountered in manufacturing.

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

PubMed Central

Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor

2011-01-01

Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759

DNA tetrominoes: the construction of DNA nanostructures using self-organised heterogeneous deoxyribonucleic acids shapes.

PubMed

Ong, Hui San; Rahim, Mohd Syafiq; Firdaus-Raih, Mohd; Ramlan, Effirul Ikhwan

2015-01-01

The unique programmability of nucleic acids offers alternative in constructing excitable and functional nanostructures. This work introduces an autonomous protocol to construct DNA Tetris shapes (L-Shape, B-Shape, T-Shape and I-Shape) using modular DNA blocks. The protocol exploits the rich number of sequence combinations available from the nucleic acid alphabets, thus allowing for diversity to be applied in designing various DNA nanostructures. Instead of a deterministic set of sequences corresponding to a particular design, the protocol promotes a large pool of DNA shapes that can assemble to conform to any desired structures. By utilising evolutionary programming in the design stage, DNA blocks are subjected to processes such as sequence insertion, deletion and base shifting in order to enrich the diversity of the resulting shapes based on a set of cascading filters. The optimisation algorithm allows mutation to be exerted indefinitely on the candidate sequences until these sequences complied with all the four fitness criteria. Generated candidates from the protocol are in agreement with the filter cascades and thermodynamic simulation. Further validation using gel electrophoresis indicated the formation of the designed shapes. Thus, supporting the plausibility of constructing DNA nanostructures in a more hierarchical, modular, and interchangeable manner.

Information entropy of humpback whale songs.

PubMed

Suzuki, Ryuji; Buck, John R; Tyack, Peter L

2006-03-01

The structure of humpback whale (Megaptera novaeangliae) songs was examined using information theory techniques. The song is an ordered sequence of individual sound elements separated by gaps of silence. Song samples were converted into sequences of discrete symbols by both human and automated classifiers. This paper analyzes the song structure in these symbol sequences using information entropy estimators and autocorrelation estimators. Both parametric and nonparametric entropy estimators are applied to the symbol sequences representing the songs. The results provide quantitative evidence consistent with the hierarchical structure proposed for these songs by Payne and McVay [Science 173, 587-597 (1971)]. Specifically, this analysis demonstrates that: (1) There is a strong structural constraint, or syntax, in the generation of the songs, and (2) the structural constraints exhibit periodicities with periods of 6-8 and 180-400 units. This implies that no empirical Markov model is capable of representing the songs' structure. The results are robust to the choice of either human or automated song-to-symbol classifiers. In addition, the entropy estimates indicate that the maximum amount of information that could be communicated by the sequence of sounds made is less than 1 bit per second.

Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes.

PubMed

King, Paula; Pham, Long K; Waltz, Shannon; Sphar, Dan; Yamamoto, Robert T; Conrad, Douglas; Taplitz, Randy; Torriani, Francesca; Forsyth, R Allyn

2016-01-01

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

Conserved structures formed by heterogeneous RNA sequences drive silencing of an inflammation responsive post-transcriptional operon

PubMed Central

Basu, Abhijit; Jain, Niyati; Tolbert, Blanton S.; Komar, Anton A.

2017-01-01

Abstract RNA–protein interactions with physiological outcomes usually rely on conserved sequences within the RNA element. By contrast, activity of the diverse gamma-interferon-activated inhibitor of translation (GAIT)-elements relies on the conserved RNA folding motifs rather than the conserved sequence motifs. These elements drive the translational silencing of a group of chemokine (CC/CXC) and chemokine receptor (CCR) mRNAs, thereby helping to resolve physiological inflammation. Despite sequence dissimilarity, these RNA elements adopt common secondary structures (as revealed by 2D-1H NMR spectroscopy), providing a basis for their interaction with the RNA-binding GAIT complex. However, many of these elements (e.g. those derived from CCL22, CXCL13, CCR4 and ceruloplasmin (Cp) mRNAs) have substantially different affinities for GAIT complex binding. Toeprinting analysis shows that different positions within the overall conserved GAIT element structure contribute to differential affinities of the GAIT protein complex towards the elements. Thus, heterogeneity of GAIT elements may provide hierarchical fine-tuning of the resolution of inflammation. PMID:29069516

Initial characterization of the large genome of the salamander Ambystoma mexicanum using shotgun and laser capture chromosome sequencing

PubMed Central

Keinath, Melissa C.; Timoshevskiy, Vladimir A.; Timoshevskaya, Nataliya Y.; Tsonis, Panagiotis A.; Voss, S. Randal; Smith, Jeramiah J.

2015-01-01

Vertebrates exhibit substantial diversity in genome size, and some of the largest genomes exist in species that uniquely inform diverse areas of basic and biomedical research. For example, the salamander Ambystoma mexicanum (the Mexican axolotl) is a model organism for studies of regeneration, development and genome evolution, yet its genome is ~10× larger than the human genome. As part of a hierarchical approach toward improving genome resources for the species, we generated 600 Gb of shotgun sequence data and developed methods for sequencing individual laser-captured chromosomes. Based on these data, we estimate that the A. mexicanum genome is ~32 Gb. Notably, as much as 19 Gb of the A. mexicanum genome can potentially be considered single copy, which presumably reflects the evolutionary diversification of mobile elements that accumulated during an ancient episode of genome expansion. Chromosome-targeted sequencing permitted the development of assemblies within the constraints of modern computational platforms, allowed us to place 2062 genes on the two smallest A. mexicanum chromosomes and resolves key events in the history of vertebrate genome evolution. Our analyses show that the capture and sequencing of individual chromosomes is likely to provide valuable information for the systematic sequencing, assembly and scaffolding of large genomes. PMID:26553646

Initial characterization of the large genome of the salamander Ambystoma mexicanum using shotgun and laser capture chromosome sequencing.

PubMed

Keinath, Melissa C; Timoshevskiy, Vladimir A; Timoshevskaya, Nataliya Y; Tsonis, Panagiotis A; Voss, S Randal; Smith, Jeramiah J

2015-11-10

Vertebrates exhibit substantial diversity in genome size, and some of the largest genomes exist in species that uniquely inform diverse areas of basic and biomedical research. For example, the salamander Ambystoma mexicanum (the Mexican axolotl) is a model organism for studies of regeneration, development and genome evolution, yet its genome is ~10× larger than the human genome. As part of a hierarchical approach toward improving genome resources for the species, we generated 600 Gb of shotgun sequence data and developed methods for sequencing individual laser-captured chromosomes. Based on these data, we estimate that the A. mexicanum genome is ~32 Gb. Notably, as much as 19 Gb of the A. mexicanum genome can potentially be considered single copy, which presumably reflects the evolutionary diversification of mobile elements that accumulated during an ancient episode of genome expansion. Chromosome-targeted sequencing permitted the development of assemblies within the constraints of modern computational platforms, allowed us to place 2062 genes on the two smallest A. mexicanum chromosomes and resolves key events in the history of vertebrate genome evolution. Our analyses show that the capture and sequencing of individual chromosomes is likely to provide valuable information for the systematic sequencing, assembly and scaffolding of large genomes.

Task analysis in curriculum design: a hierarchically sequenced introductory mathematics curriculum1

PubMed Central

Resnick, Lauren B.; Wang, Margaret C.; Kaplan, Jerome

1973-01-01

A method of systematic task analysis is applied to the problem of designing a sequence of learning objectives that will provide an optimal match for the child's natural sequence of acquisition of mathematical skills and concepts. The authors begin by proposing an operational definition of the number concept in the form of a set of behaviors which, taken together, permit the inference that the child has an abstract concept of “number”. These are the “objectives” of the curriculum. Each behavior in the defining set is then subjected to an analysis that identifies hypothesized components of skilled performance and prerequisites for learning these components. On the basis of these analyses, specific sequences of learning objectives are proposed. The proposed sequences are hypothesized to be those that will best facilitate learning, by maximizing transfer from earlier to later objectives. Relevant literature on early learning and cognitive development is considered in conjunction with the analyses and the resulting sequences. The paper concludes with a discussion of the ways in which the curriculum can be implemented and studied in schools. Examples of data on individual children are presented, and the use of such data for improving the curriculum itself, as well as for examining the effects of other treatment variables, is considered. PMID:16795452

Top Down Implementation Plan for system performance test software

NASA Technical Reports Server (NTRS)

Jacobson, G. N.; Spinak, A.

1982-01-01

The top down implementation plan used for the development of system performance test software during the Mark IV-A era is described. The plan is based upon the identification of the hierarchical relationship of the individual elements of the software design, the development of a sequence of functionally oriented demonstrable steps, the allocation of subroutines to the specific step where they are first required, and objective status reporting. The results are: determination of milestones, improved managerial visibility, better project control, and a successful software development.

Hierarchical graphs for better annotations of rule-based models of biochemical systems

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

Hu, Bin; Hlavacek, William

2009-01-01

In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of amore » molecular component. A set of rules comprises a mathematical/computational model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Here, for purposes of model annotation, we propose an extension of BNGL that involves the use of hierarchical graphs to represent (1) relationships among components and subcomponents of molecules and (2) relationships among classes of reactions defined by rules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR)/CD3 complex. Likewise, we illustrate how hierarchical graphs can be used to document the similarity of two related rules for kinase-catalyzed phosphorylation of a protein substrate. We also demonstrate how a hierarchical graph representing a protein can be encoded in an XML-based format.« less

'New' and distributed leadership in quality and safety in health care, or 'old' and hierarchical? An interview study with strategic stakeholders.

PubMed

McKee, Lorna; Charles, Kathryn; Dixon-Woods, Mary; Willars, Janet; Martin, Graham

2013-10-01

We aimed to explore the views of strategic level stakeholders on leadership for quality and safety in the UK National Health Service. We interviewed 107 stakeholders with close involvement in quality and safety as professionals, managers, policy makers or commentators. Analysis was based on the constant comparative method. Participants identified the crucial role of leadership in ensuring safe, high quality care. Consistent with the academic literature, participants distinguished between traditional hierarchical 'concentrated' leadership associated with particular positions, and distributed leadership involving those with particular skills and abilities across multiple institutional levels. They clearly and explicitly saw a role for distributed leadership, emphasizing that all staff had responsibility for leading on patient safety and quality. They described the particular value of leadership coalitions between managers and clinicians. However, concern was expressed that distributed leadership could mean confusion about who was in charge, and that at national level it risked creating a vacuum of authority, mixed messages, and conflicting expectations and demands. Participants also argued that hierarchically based leadership was needed to complement distributed leadership, not least to provide focus, practical support and expertise, and managerial clout. Strategic level stakeholders see the most effective form of leadership for quality and safety as one that blends distributed and concentrated leadership. Policy and academic prescriptions about leadership may benefit from the sophisticated and pragmatic know-how of insiders who work in organizations that remain permeated by traditional structures, cleavages and power relationships.

Using Shaping to Increase Foods Consumed by Children with Autism

ERIC Educational Resources Information Center

Hodges, Abby; Davis, Tonya; Crandall, Madison; Phipps, Laura; Weston, Regan

2017-01-01

The current study used differential reinforcement and shaping to increase the variety of foods accepted by children with autism who demonstrated significant feeding inflexibility. Participants were introduced to four new food items via a hierarchical exposure, which involved systematically increasing the desired response with the food item. Level…

Centering in on Professional Choices.

ERIC Educational Resources Information Center

Harris, Muriel

2001-01-01

Examines the author's involvement with writing centers as an example of how educators can look at the choices made within their areas of expertise to see why the choices attract them. Notes that in her case, the flexible, collaborative, individualized, non-evaluative, experimental, non-hierarchical, student-centered nature of writing centers is an…

Fuzzy coordinator in control problems

NASA Technical Reports Server (NTRS)

Rueda, A.; Pedrycz, W.

1992-01-01

In this paper a hierarchical control structure using a fuzzy system for coordination of the control actions is studied. The architecture involves two levels of control: a coordination level and an execution level. Numerical experiments will be utilized to illustrate the behavior of the controller when it is applied to a nonlinear plant.

Using Participatory Management in a Traditional Environment.

ERIC Educational Resources Information Center

Tavarone, Antonia R.

This paper describes the use of a participatory management process in an older, public-sector bureaucracy with an extremely traditional, hierarchical, and entrenched culture. Into this culture, two separate projects were introduced: an employee involvement program using the quality circle concept and a task force that would design and implement an…

Cognitive Mapping Tobacco Control Advice for Dentistry: A Dental PBRN Study

ERIC Educational Resources Information Center

Qu, Haiyan; Houston, Thomas K.; Williams, Jessica H.; Gilbert, Gregg H.; Shewchuk, Richard M.

2011-01-01

Objective: To identify facilitative strategies that could be used in developing a tobacco cessation program for community dental practices. Methods: Nominal group technique (NGT) meetings and a card-sort task were used to obtain formative data. A cognitive mapping approach involving multidimensional scaling and hierarchical cluster analysis was…

Reconciling Feminism and Psychoanalysis: The Patient as Therapist to the Therapist.

ERIC Educational Resources Information Center

Kanefield, Linda

Although incompatible differences appear to exist between psychoanalytic therapy, which involves a hierarchical relationship, and feminism, which stresses egalitarian values, some versions of psychoanalytic theory are able to maintain their hierarchy within a context consistent with feminist values. Freud touched on the importance of the…

Psychosocial Factors Predicting First-Year College Student Success

ERIC Educational Resources Information Center

Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

2013-01-01

This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

Effects of Technology Immersion on Middle School Students' Learning Opportunities and Achievement

ERIC Educational Resources Information Center

Shapley, Kelly; Sheehan, Daniel; Maloney, Catherine; Caranikas-Walker, Fanny

2011-01-01

An experimental study of the Technology Immersion model involved comparisons between 21 middle schools that received laptops for each teacher and student, instructional and learning resources, professional development, and technical and pedagogical support, and 21 control schools. Using hierarchical linear modeling to analyze longitudinal survey…

A HIERARCHICAL MODELING FRAMEWORK FOR GEOLOGICAL STORAGE OF CARBON DIOXIDE

EPA Science Inventory

Carbon Capture and Storage, or CCS, is likely to be an important technology in a carbonconstrained world. CCS will involve subsurface injection of massive amounts of captured CO₂, on a scale that has not previously been approached. The unprecedented scale of t...

Bayesian state space models for dynamic genetic network construction across multiple tissues.

PubMed

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Autoplan: A self-processing network model for an extended blocks world planning environment

NASA Technical Reports Server (NTRS)

Dautrechy, C. Lynne; Reggia, James A.; Mcfadden, Frank

1990-01-01

Self-processing network models (neural/connectionist models, marker passing/message passing networks, etc.) are currently undergoing intense investigation for a variety of information processing applications. These models are potentially very powerful in that they support a large amount of explicit parallel processing, and they cleanly integrate high level and low level information processing. However they are currently limited by a lack of understanding of how to apply them effectively in many application areas. The formulation of self-processing network methods for dynamic, reactive planning is studied. The long-term goal is to formulate robust, computationally effective information processing methods for the distributed control of semiautonomous exploration systems, e.g., the Mars Rover. The current research effort is focusing on hierarchical plan generation, execution and revision through local operations in an extended blocks world environment. This scenario involves many challenging features that would be encountered in a real planning and control environment: multiple simultaneous goals, parallel as well as sequential action execution, action sequencing determined not only by goals and their interactions but also by limited resources (e.g., three tasks, two acting agents), need to interpret unanticipated events and react appropriately through replanning, etc.

Terminological aspects of data elements

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

Strehlow, R.A.; Kenworthey, W.H. Jr.; Schuldt, R.E.

1991-01-01

The creation and display of data comprise a process that involves a sequence of steps requiring both semantic and systems analysis. An essential early step in this process is the choice, definition, and naming of data element concepts and is followed by the specification of other needed data element concept attributes. The attributes and the values of data element concept remain associated with them from their birth as a concept to a generic data element that serves as a template for final application. Terminology is, therefore, centrally important to the entire data creation process. Smooth mapping from natural language tomore » a database is a critical aspect of database, and consequently, it requires terminology standardization from the outset of database work. In this paper the semantic aspects of data elements are analyzed and discussed. Seven kinds of data element concept information are considered and those that require terminological development and standardization are identified. The four terminological components of a data element are the hierarchical type of a concept, functional dependencies, schematas showing conceptual structures, and definition statements. These constitute the conventional role of terminology in database design. 12 refs., 8 figs., 1 tab.« less

Thin and thick primary cutaneous melanomas reveal distinct patterns of somatic copy number alterations

PubMed Central

Apollo, Alessandro; Pescucci, Chiara; Licastro, Danilo; Urso, Carmelo; Gerlini, Gianni; Borgognoni, Lorenzo; Luzzatto, Lucio; Stecca, Barbara

2016-01-01

Cutaneous melanoma is one of the most aggressive type of skin tumor. Early stage melanoma can be often cured by surgery; therefore current management guidelines dictate a different approach for thin (<1mm) versus thick (>4mm) melanomas. We have carried out whole-exome sequencing in 5 thin and 5 thick fresh-frozen primary cutaneous melanomas. Unsupervised hierarchical clustering analysis of somatic copy number alterations (SCNAs) identified two groups corresponding to thin and thick melanomas. The most striking difference between them was the much greater abundance of SCNAs in thick melanomas, whereas mutation frequency did not significantly change between the two groups. We found novel mutations and focal SCNAs in genes that are embryonic regulators of axon guidance, predominantly in thick melanomas. Analysis of publicly available microarray datasets provided further support for a potential role of Ephrin receptors in melanoma progression. In addition, we have identified a set of SCNAs, including amplification of BRAF and ofthe epigenetic modifier EZH2, that are specific for the group of thick melanomas that developed metastasis during the follow-up. Our data suggest that mutations occur early during melanoma development, whereas SCNAs might be involved in melanoma progression. PMID:27095580

Thin and thick primary cutaneous melanomas reveal distinct patterns of somatic copy number alterations.

PubMed

Montagnani, Valentina; Benelli, Matteo; Apollo, Alessandro; Pescucci, Chiara; Licastro, Danilo; Urso, Carmelo; Gerlini, Gianni; Borgognoni, Lorenzo; Luzzatto, Lucio; Stecca, Barbara

2016-05-24

Cutaneous melanoma is one of the most aggressive type of skin tumor. Early stage melanoma can be often cured by surgery; therefore current management guidelines dictate a different approach for thin (<1mm) versus thick (>4mm) melanomas. We have carried out whole-exome sequencing in 5 thin and 5 thick fresh-frozen primary cutaneous melanomas. Unsupervised hierarchical clustering analysis of somatic copy number alterations (SCNAs) identified two groups corresponding to thin and thick melanomas. The most striking difference between them was the much greater abundance of SCNAs in thick melanomas, whereas mutation frequency did not significantly change between the two groups. We found novel mutations and focal SCNAs in genes that are embryonic regulators of axon guidance, predominantly in thick melanomas. Analysis of publicly available microarray datasets provided further support for a potential role of Ephrin receptors in melanoma progression. In addition, we have identified a set of SCNAs, including amplification of BRAF and ofthe epigenetic modifier EZH2, that are specific for the group of thick melanomas that developed metastasis during the follow-up. Our data suggest that mutations occur early during melanoma development, whereas SCNAs might be involved in melanoma progression.

Recognizing human actions by learning and matching shape-motion prototype trees.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.

Orthogonal Polynomials Associated with Complementary Chain Sequences

NASA Astrophysics Data System (ADS)

Behera, Kiran Kumar; Sri Ranga, A.; Swaminathan, A.

2016-07-01

Using the minimal parameter sequence of a given chain sequence, we introduce the concept of complementary chain sequences, which we view as perturbations of chain sequences. Using the relation between these complementary chain sequences and the corresponding Verblunsky coefficients, the para-orthogonal polynomials and the associated Szegő polynomials are analyzed. Two illustrations, one involving Gaussian hypergeometric functions and the other involving Carathéodory functions are also provided. A connection between these two illustrations by means of complementary chain sequences is also observed.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Generalising Ward's Method for Use with Manhattan Distances.

PubMed

Strauss, Trudie; von Maltitz, Michael Johan

2017-01-01

The claim that Ward's linkage algorithm in hierarchical clustering is limited to use with Euclidean distances is investigated. In this paper, Ward's clustering algorithm is generalised to use with l1 norm or Manhattan distances. We argue that the generalisation of Ward's linkage method to incorporate Manhattan distances is theoretically sound and provide an example of where this method outperforms the method using Euclidean distances. As an application, we perform statistical analyses on languages using methods normally applied to biology and genetic classification. We aim to quantify differences in character traits between languages and use a statistical language signature based on relative bi-gram (sequence of two letters) frequencies to calculate a distance matrix between 32 Indo-European languages. We then use Ward's method of hierarchical clustering to classify the languages, using the Euclidean distance and the Manhattan distance. Results obtained from using the different distance metrics are compared to show that the Ward's algorithm characteristic of minimising intra-cluster variation and maximising inter-cluster variation is not violated when using the Manhattan metric.

ENCOMPASS: A SAGA based environment for the compositon of programs and specifications, appendix A

NASA Technical Reports Server (NTRS)

Terwilliger, Robert B.; Campbell, Roy H.

1985-01-01

ENCOMPASS is an example integrated software engineering environment being constructed by the SAGA project. ENCOMPASS supports the specification, design, construction and maintenance of efficient, validated, and verified programs in a modular programming language. The life cycle paradigm, schema of software configurations, and hierarchical library structure used by ENCOMPASS is presented. In ENCOMPASS, the software life cycle is viewed as a sequence of developments, each of which reuses components from the previous ones. Each development proceeds through the phases planning, requirements definition, validation, design, implementation, and system integration. The components in a software system are modeled as entities which have relationships between them. An entity may have different versions and different views of the same project are allowed. The simple entities supported by ENCOMPASS may be combined into modules which may be collected into projects. ENCOMPASS supports multiple programmers and projects using a hierarchical library system containing a workspace for each programmer; a project library for each project, and a global library common to all projects.

Adaptive Skin Meshes Coarsening for Biomolecular Simulation

PubMed Central

Shi, Xinwei; Koehl, Patrice

2011-01-01

In this paper, we present efficient algorithms for generating hierarchical molecular skin meshes with decreasing size and guaranteed quality. Our algorithms generate a sequence of coarse meshes for both the surfaces and the bounded volumes. Each coarser surface mesh is adaptive to the surface curvature and maintains the topology of the skin surface with guaranteed mesh quality. The corresponding tetrahedral mesh is conforming to the interface surface mesh and contains high quality tetrahedral that decompose both the interior of the molecule and the surrounding region (enclosed in a sphere). Our hierarchical tetrahedral meshes have a number of advantages that will facilitate fast and accurate multigrid PDE solvers. Firstly, the quality of both the surface triangulations and tetrahedral meshes is guaranteed. Secondly, the interface in the tetrahedral mesh is an accurate approximation of the molecular boundary. In particular, all the boundary points lie on the skin surface. Thirdly, our meshes are Delaunay meshes. Finally, the meshes are adaptive to the geometry. PMID:21779137

Inter-subject synchronization of brain responses during natural music listening

PubMed Central

Abrams, Daniel A.; Ryali, Srikanth; Chen, Tianwen; Chordia, Parag; Khouzam, Amirah; Levitin, Daniel J.; Menon, Vinod

2015-01-01

Music is a cultural universal and a rich part of the human experience. However, little is known about common brain systems that support the processing and integration of extended, naturalistic ‘real-world’ music stimuli. We examined this question by presenting extended excerpts of symphonic music, and two pseudomusical stimuli in which the temporal and spectral structure of the Natural Music condition were disrupted, to non-musician participants undergoing functional brain imaging and analysing synchronized spatiotemporal activity patterns between listeners. We found that music synchronizes brain responses across listeners in bilateral auditory midbrain and thalamus, primary auditory and auditory association cortex, right-lateralized structures in frontal and parietal cortex, and motor planning regions of the brain. These effects were greater for natural music compared to the pseudo-musical control conditions. Remarkably, inter-subject synchronization in the inferior colliculus and medial geniculate nucleus was also greater for the natural music condition, indicating that synchronization at these early stages of auditory processing is not simply driven by spectro-temporal features of the stimulus. Increased synchronization during music listening was also evident in a right-hemisphere fronto-parietal attention network and bilateral cortical regions involved in motor planning. While these brain structures have previously been implicated in various aspects of musical processing, our results are the first to show that these regions track structural elements of a musical stimulus over extended time periods lasting minutes. Our results show that a hierarchical distributed network is synchronized between individuals during the processing of extended musical sequences, and provide new insight into the temporal integration of complex and biologically salient auditory sequences. PMID:23578016

Navigating comics: an empirical and theoretical approach to strategies of reading comic page layouts.

PubMed

Cohn, Neil

2013-01-01

Like the sequence of words in written language, comic book page layouts direct images into a deliberate reading sequence. Conventional wisdom would expect that comic panels follow the order of text: left-to-right and down - a "Z-path" - though several layouts can violate this order, such as Gestalt groupings of panels that deny a Z-path of reading. To examine how layouts pressure readers to choose pathways deviating from the Z-path, we presented participants with comic pages empty of content, and asked them to number the panels in the order they would read them. Participants frequently used strategies departing from both the traditional Z-path and Gestalt groupings. These preferences reveal a system of constraints that organizes panels into hierarchic constituents, guiding readers through comic page layouts.

Motivation of extended behaviors by anterior cingulate cortex.

PubMed

Holroyd, Clay B; Yeung, Nick

2012-02-01

Intense research interest over the past decade has yielded diverse and often discrepant theories about the function of anterior cingulate cortex (ACC). In particular, a dichotomy has emerged between neuropsychological theories suggesting a primary role for ACC in motivating or 'energizing' behavior, and neuroimaging-inspired theories emphasizing its contribution to cognitive control and reinforcement learning. To reconcile these views, we propose that ACC supports the selection and maintenance of 'options' - extended, context-specific sequences of behavior directed toward particular goals - that are learned through a process of hierarchical reinforcement learning. This theory accounts for ACC activity in relation to learning and control while simultaneously explaining the effects of ACC damage as disrupting the motivational context supporting the production of goal-directed action sequences. Copyright © 2011 Elsevier Ltd. All rights reserved.

Visual exploration of parameter influence on phylogenetic trees.

PubMed

Hess, Martin; Bremm, Sebastian; Weissgraeber, Stephanie; Hamacher, Kay; Goesele, Michael; Wiemeyer, Josef; von Landesberger, Tatiana

2014-01-01

Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

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

Weighill, Deborah; Jones, Piet; Shah, Manesh

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

DOE PAGES

Weighill, Deborah; Jones, Piet; Shah, Manesh; ...

2018-05-11

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Hierarchical Strategy for Rapid Analysis Environment

NASA Technical Reports Server (NTRS)

Whitcomb, John

2003-01-01

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

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Programming molecular self-assembly of intrinsically disordered proteins containing sequences of low complexity

NASA Astrophysics Data System (ADS)

Simon, Joseph R.; Carroll, Nick J.; Rubinstein, Michael; Chilkoti, Ashutosh; López, Gabriel P.

2017-06-01

Dynamic protein-rich intracellular structures that contain phase-separated intrinsically disordered proteins (IDPs) composed of sequences of low complexity (SLC) have been shown to serve a variety of important cellular functions, which include signalling, compartmentalization and stabilization. However, our understanding of these structures and our ability to synthesize models of them have been limited. We present design rules for IDPs possessing SLCs that phase separate into diverse assemblies within droplet microenvironments. Using theoretical analyses, we interpret the phase behaviour of archetypal IDP sequences and demonstrate the rational design of a vast library of multicomponent protein-rich structures that ranges from uniform nano-, meso- and microscale puncta (distinct protein droplets) to multilayered orthogonally phase-separated granular structures. The ability to predict and program IDP-rich assemblies in this fashion offers new insights into (1) genetic-to-molecular-to-macroscale relationships that encode hierarchical IDP assemblies, (2) design rules of such assemblies in cell biology and (3) molecular-level engineering of self-assembled recombinant IDP-rich materials.

Generalized species sampling priors with latent Beta reinforcements

PubMed Central

Airoldi, Edoardo M.; Costa, Thiago; Bassetti, Federico; Leisen, Fabrizio; Guindani, Michele

2014-01-01

Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appropriate. We introduce a novel and probabilistically coherent family of non-exchangeable species sampling sequences characterized by a tractable predictive probability function with weights driven by a sequence of independent Beta random variables. We compare their theoretical clustering properties with those of the Dirichlet Process and the two parameters Poisson-Dirichlet process. The proposed construction provides a complete characterization of the joint process, differently from existing work. We then propose the use of such process as prior distribution in a hierarchical Bayes modeling framework, and we describe a Markov Chain Monte Carlo sampler for posterior inference. We evaluate the performance of the prior and the robustness of the resulting inference in a simulation study, providing a comparison with popular Dirichlet Processes mixtures and Hidden Markov Models. Finally, we develop an application to the detection of chromosomal aberrations in breast cancer by leveraging array CGH data. PMID:25870462

RNA 3D Structural Motifs: Definition, Identification, Annotation, and Database Searching

NASA Astrophysics Data System (ADS)

Nasalean, Lorena; Stombaugh, Jesse; Zirbel, Craig L.; Leontis, Neocles B.

Structured RNA molecules resemble proteins in the hierarchical organization of their global structures, folding and broad range of functions. Structured RNAs are composed of recurrent modular motifs that play specific functional roles. Some motifs direct the folding of the RNA or stabilize the folded structure through tertiary interactions. Others bind ligands or proteins or catalyze chemical reactions. Therefore, it is desirable, starting from the RNA sequence, to be able to predict the locations of recurrent motifs in RNA molecules. Conversely, the potential occurrence of one or more known 3D RNA motifs may indicate that a genomic sequence codes for a structured RNA molecule. To identify known RNA structural motifs in new RNA sequences, precise structure-based definitions are needed that specify the core nucleotides of each motif and their conserved interactions. By comparing instances of each recurrent motif and applying base pair isosteriCity relations, one can identify neutral mutations that preserve its structure and function in the contexts in which it occurs.

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

PubMed

He, Yan; Caporaso, J Gregory; Jiang, Xiao-Tao; Sheng, Hua-Fang; Huse, Susan M; Rideout, Jai Ram; Edgar, Robert C; Kopylova, Evguenia; Walters, William A; Knight, Rob; Zhou, Hong-Wei

2015-01-01

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

Wavelet Algorithms for Illumination Computations

NASA Astrophysics Data System (ADS)

Schroder, Peter

One of the core problems of computer graphics is the computation of the equilibrium distribution of light in a scene. This distribution is given as the solution to a Fredholm integral equation of the second kind involving an integral over all surfaces in the scene. In the general case such solutions can only be numerically approximated, and are generally costly to compute, due to the geometric complexity of typical computer graphics scenes. For this computation both Monte Carlo and finite element techniques (or hybrid approaches) are typically used. A simplified version of the illumination problem is known as radiosity, which assumes that all surfaces are diffuse reflectors. For this case hierarchical techniques, first introduced by Hanrahan et al. (32), have recently gained prominence. The hierarchical approaches lead to an asymptotic improvement when only finite precision is required. The resulting algorithms have cost proportional to O(k^2 + n) versus the usual O(n^2) (k is the number of input surfaces, n the number of finite elements into which the input surfaces are meshed). Similarly a hierarchical technique has been introduced for the more general radiance problem (which allows glossy reflectors) by Aupperle et al. (6). In this dissertation we show the equivalence of these hierarchical techniques to the use of a Haar wavelet basis in a general Galerkin framework. By so doing, we come to a deeper understanding of the properties of the numerical approximations used and are able to extend the hierarchical techniques to higher orders. In particular, we show the correspondence of the geometric arguments underlying hierarchical methods to the theory of Calderon-Zygmund operators and their sparse realization in wavelet bases. The resulting wavelet algorithms for radiosity and radiance are analyzed and numerical results achieved with our implementation are reported. We find that the resulting algorithms achieve smaller and smoother errors at equivalent work.

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.

High surface area electrodes by template-free self-assembled hierarchical porous gold architecture.

PubMed

Morag, Ahiud; Golub, Tatiana; Becker, James; Jelinek, Raz

2016-06-15

The electrode active surface area is a crucial determinant in many electrochemical applications and devices. Porous metal substrates have been employed in electrode design, however construction of such materials generally involves multistep processes, generating in many instances electrodes exhibiting incomplete access to internal pore surfaces. Here we describe fabrication of electrodes comprising hierarchical, nano-to-microscale porous gold matrix, synthesized through spontaneous crystallization of gold thiocyanate in water. Cyclic voltammetry analysis revealed that the specific surface area of the conductive nanoporous Au microwires was very high and depended only upon the amount of gold used, not electrode areas or geometries. Application of the electrode in a pseudo-capacitor device is presented. Copyright © 2016 Elsevier Inc. All rights reserved.

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

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.

On the usefulness of 'what' and 'where' pathways in vision.

PubMed

de Haan, Edward H F; Cowey, Alan

2011-10-01

The primate visual brain is classically portrayed as a large number of separate 'maps', each dedicated to the processing of specific visual cues, such as colour, motion or faces and their many features. In order to understand this fractionated architecture, the concept of cortical 'pathways' or 'streams' was introduced. In the currently prevailing view, the different maps are organised hierarchically into two major pathways, one involved in recognition and memory (the ventral stream or 'what' pathway) and the other in the programming of action (the dorsal stream or 'where' pathway). In this review, we question this heuristically influential but potentially misleading linear hierarchical pathway model and argue instead for a 'patchwork' or network model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Drosophila histone locus bodies form by hierarchical recruitment of components

PubMed Central

White, Anne E.; Burch, Brandon D.; Yang, Xiao-cui; Gasdaska, Pamela Y.; Dominski, Zbigniew; Marzluff, William F.

2011-01-01

Nuclear bodies are protein- and RNA-containing structures that participate in a wide range of processes critical to genome function. Molecular self-organization is thought to drive nuclear body formation, but whether this occurs stochastically or via an ordered, hierarchical process is not fully understood. We addressed this question using RNAi and proteomic approaches in Drosophila melanogaster to identify and characterize novel components of the histone locus body (HLB), a nuclear body involved in the expression of replication-dependent histone genes. We identified the transcription elongation factor suppressor of Ty 6 (Spt6) and a homologue of mammalian nuclear protein of the ataxia telangiectasia–mutated locus that is encoded by the homeotic gene multisex combs (mxc) as novel HLB components. By combining genetic manipulation in both cell culture and embryos with cytological observations of Mxc, Spt6, and the known HLB components, FLICE-associated huge protein, Mute, U7 small nuclear ribonucleoprotein, and MPM-2 phosphoepitope, we demonstrated sequential recruitment and hierarchical dependency for localization of factors to HLBs during development, suggesting that ordered assembly can play a role in nuclear body formation. PMID:21576393

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures.

PubMed

Oldenkamp, Rik; Hendriks, Harrie W M; van de Meent, Dik; Ragas, Ad M J

2015-09-01

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.

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

NASA Technical Reports Server (NTRS)

Caines, P. E.

1999-01-01

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

Hierarchical honeycomb-like Co3O4 pores coating on CoMoO4 nanosheets as bifunctional efficient electrocatalysts for overall water splitting

NASA Astrophysics Data System (ADS)

Pei, Zhihao; Xu, Li; Xu, Wei

2018-03-01

Efficient electrocatalytic water splitting is one of the most effective ways to solve the global energy crisis. In this paper, we report on a novel self-assembled hierarchical structure of Co3O4/CoMoO4 grown in situ on a bare nickel foam. The unique, three-dimensional honeycomb-like Co3O4 pores were constructed from one-dimensional nanowires and coated on two-dimensional CoMoO4 nanosheets structures grown on nickel foam. The synthesis involved a step-wise solvothermal method followed by an annealing treatment. Benefiting from the synergistic effect of the hierarchical nanostructures, the materials had more reaction active sites and a smaller electron transfer impedance, and they exhibited excellent electrocatalytic performances for the HER and OER of 143 and 244 mV, respectively, at 10 mA cm-2 in an alkaline solution. Furthermore, the materials remained stable during the long electrolysis period, over 10 h, presenting promising application prospects in the field of electrocatalytic water splitting.

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.

Hierarchical Nanomorphologies Promote Exciton Dissociation in Polymer: Fullerene Bulk Heterojunction Solar Cells

NASA Astrophysics Data System (ADS)

Chen, Wei; Darling, Seth

2012-02-01

In the last fifteen years, research efforts have led to organic photovoltaic (OPV) devices with power conversion efficiencies (PCEs) up to ˜8%, but these values are still insufficient for the devices to become widely marketable. To further improve solar cell performance a thorough understanding of the complex structure-property relationships in the OPV devices is required. In this work, we demonstrated that the OPV active layer of PTB7:fullerene bulk heterojunction (BHJ) solar cells, which set a historic record of PCE (7.4%), involves hierarchical nanomorphologies ranging from several nanometers of crystallites to tens of nanometers of nanocrystallite aggregates in PTB7-rich and fullerene-rich domains, themselves hundreds of nanometers in size. These hierarchical nanomorphologies with optimum crystallinity and intermixing of PTB7 with fullerenes are coupled to significantly enhanced exciton dissociation, which consequently contribute to photocurrent, leading to the superior performance of PTB7:fullerene BHJ solar cells. New insights of performance-related structures afforded by the current study should aid in the rational design of even higher performance polymeric solar cells.

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.

Facile synthesis of hierarchical porous γ-Al2O3 hollow microspheres for water treatment.

PubMed

Li, Mingyang; Si, Zhichun; Wu, Xiaodong; Weng, Duan; Kang, Feiyu

2014-03-01

Hierarchical porous γ-Al2O3 hollow microspheres were synthesized by a modified spray drying method. Ageing the precipitated precursor and spray-drying assisted by NH4Cl salts are considered as two key steps for the synthesis of γ-Al2O3 hollow microspheres. The mechanism of the formation of hierarchical porous γ-Al2O3 hollow microsphere was proposed involving phase transformation from aluminum hydroxide to laminar boehmite during ageing and a following self-assembling process with NH4Cl as the template during spray drying. The meso-/macro-pores in γ-Al2O3 mainly arise from the stacking of the laminar boehmites which are obtained by ageing the precipitated precursors at 90°C. NH4Cl, which was the byproduct from the reaction between AlCl3·6H2O and NH3·H2O, was demonstrated to be an excellent template to act as the core and the barrier for separation of laminar boehmites. No extra NH4Cl was added. The as-synthesized hierarchical porous γ-Al2O3 hollow microsphere presented remarkably higher adsorption capacity, which is thirty times higher adsorption rate for Congo Red than the solid microsphere containing only small mesopores. Copyright © 2013 Elsevier Inc. All rights reserved.

Disagreement in Parental Reports of Father Involvement

PubMed Central

Charles, Pajarita; Spielfogel, Jill; Gorman-Smith, Deborah; Schoeny, Michael; Henry, David; Tolan, Patrick

2016-01-01

Despite agreement on the value of father involvement in children’s lives, research has been limited due to the exclusion of fathers in studies, questionable validity of mothers’ reports on father involvement, and simple measures of fathering behavior. Our study extends previous research by comparing reports of father involvement using robust, multidimensional father involvement measures. Data from 113 fathers and 126 mothers reporting on 221 children were used to assess father involvement. Results indicate that fathers reported significantly higher levels of involvement than mothers reported. Findings from hierarchical linear models suggest that race/ethnicity and mothers’ reports of positive relationship quality were associated with smaller discrepancies in reports of father involvement, whereas nonmarried partnerships, older children, father residence, and biological status predicted larger discrepancies. Our study demonstrates the importance of obtaining father involvement reports directly from fathers and why father involvement should be assessed as a multidimensional construct to examine fathering behavior. PMID:29515272

A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

Cerebral responses to local and global auditory novelty under general anesthesia

PubMed Central

Uhrig, Lynn; Janssen, David; Dehaene, Stanislas; Jarraya, Béchir

2017-01-01

Primate brains can detect a variety of unexpected deviations in auditory sequences. The local-global paradigm dissociates two hierarchical levels of auditory predictive coding by examining the brain responses to first-order (local) and second-order (global) sequence violations. Using the macaque model, we previously demonstrated that, in the awake state, local violations cause focal auditory responses while global violations activate a brain circuit comprising prefrontal, parietal and cingulate cortices. Here we used the same local-global auditory paradigm to clarify the encoding of the hierarchical auditory regularities in anesthetized monkeys and compared their brain responses to those obtained in the awake state as measured with fMRI. Both, propofol, a GABAA-agonist, and ketamine, an NMDA-antagonist, left intact or even enhanced the cortical response to auditory inputs. The local effect vanished during propofol anesthesia and shifted spatially during ketamine anesthesia compared with wakefulness. Under increasing levels of propofol, we observed a progressive disorganization of the global effect in prefrontal, parietal and cingulate cortices and its complete suppression under ketamine anesthesia. Anesthesia also suppressed thalamic activations to the global effect. These results suggest that anesthesia preserves initial auditory processing, but disturbs both short-term and long-term auditory predictive coding mechanisms. The disorganization of auditory novelty processing under anesthesia relates to a loss of thalamic responses to novelty and to a disruption of higher-order functional cortical networks in parietal, prefrontal and cingular cortices. PMID:27502046

Waveform Classification of the 2016 Gyeongju Earthquake Sequence Using Hierarchical Clustering

NASA Astrophysics Data System (ADS)

Shin, J. S.; Son, M.; Cho, C.

2017-12-01

The 2016 Gyeongju earthquakes, including the ML 5.8 earthquake of September 12, 2016 ccurred around the Yangsan Fault System, which is the most prominent set of lineaments on the Korean Peninsula. The main event is the largest earthquake recorded since instrumental recording began in South Korea We analysed the waveforms of earthquake sequence to better understand the seismicity around this fault system. We defined groups of relocated hypocenters using hierarchical clustering based on waveform similarity. The 2016 Gyeongju events are classified into three major groups: Group A with 185 events, Group B with 134 events, and Group C with 45 events. The waveform similarity of each group was confirmed by the matrix of correlation coefficients. The three groups of waveforms wereare identified in space: the events of Group A occurred at shallower depths than those of Group B, while those of Group C occurred at intermediate depths at the north side. The eight major events occurred in the area including Group A and Group B, whereas the area of Group C produceds no major events. Therefore, the area of Group C couldcan be excluded in considering a major asperity for the Gyeongju earthquakes. Earthquakes that are close together spatially with similar rupture mechanisms produce similar waveforms at the same common station. Thus, the hypocenters classified from the three groups of waveforms, based on waveform similarity imply that the inferred fault plane contains three zones locked under slightly different conditions.

A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

Marine Structural Biomaterials in Medical Biomimicry.

PubMed

Green, David W; Lee, Jong-Min; Jung, Han-Sung

2015-10-01

Marine biomaterials display properties, behaviors, and functions that have not been artificially matched in relation to their hierarchical construction, crack-stopping properties, growth adaptation, and energy efficiency. The discovery and understanding of such features that are characteristic of natural biomaterials can be used to manufacture more energy-efficient and lightweight materials. However, a more detailed understanding of the design of natural biomaterials with good performance and the mechanism of their design is required. Far-reaching biomolecular characterization of biomaterials and biostructures from the ocean world is possible with sophisticated analytical methods, such as whole-genome RNA-seq, and de novo transcriptome sequencing and mass spectrophotometry-based sequencing. In combination with detailed material characterization, the elements in newly discovered biomaterials and their properties can be reconstituted into biomimetic or bio-inspired materials. A major aim of harnessing marine biomaterials is their translation into biomimetic counterparts. To achieve full translation, the genome, proteome, and hierarchical material characteristics, and their profiles in space and time, have to be associated to allow for smooth biomimetic translation. In this article, we highlight the novel science of marine biomimicry from a materials perspective. We focus on areas of material design and fabrication that have excelled in marine biological models, such as embedded interfaces, chiral organization, and the use of specialized composite material-on-material designs. Our emphasis is primarily on key materials with high value in healthcare in which we evaluate their future prospects. Marine biomaterials are among the most exquisite and powerful aspects in materials science today.

Simultaneous growth of self-patterned carbon nanotube forests with dual height scales

NASA Astrophysics Data System (ADS)

Sam, Ebru Devrim; Kucukayan-Dogu, Gokce; Baykal, Beril; Dalkilic, Zeynep; Rana, Kuldeep; Bengu, Erman

2012-05-01

In this study, we report on a unique, one-step fabrication technique enabling the simultaneous synthesis of vertically aligned multi-walled carbon nanotubes (VA-MWCNTs) with dual height scales through alcohol catalyzed chemical vapor deposition (ACCVD). Regions of VA-MWCNTs with different heights were well separated from each other leading to a self-patterning on the surface. We devised a unique layer-by-layer process for application of catalyst and inhibitor precursors on oxidized Si (100) surfaces before the ACCVD step to achieve a hierarchical arrangement. Patterning could be controlled by adjusting the molarity and application sequence of precursors. Contact angle measurements on these self-patterned surfaces indicated that manipulation of these hierarchical arrays resulted in a wide range of hydrophobic behavior changing from that of a sticky rose petal to a lotus leaf.In this study, we report on a unique, one-step fabrication technique enabling the simultaneous synthesis of vertically aligned multi-walled carbon nanotubes (VA-MWCNTs) with dual height scales through alcohol catalyzed chemical vapor deposition (ACCVD). Regions of VA-MWCNTs with different heights were well separated from each other leading to a self-patterning on the surface. We devised a unique layer-by-layer process for application of catalyst and inhibitor precursors on oxidized Si (100) surfaces before the ACCVD step to achieve a hierarchical arrangement. Patterning could be controlled by adjusting the molarity and application sequence of precursors. Contact angle measurements on these self-patterned surfaces indicated that manipulation of these hierarchical arrays resulted in a wide range of hydrophobic behavior changing from that of a sticky rose petal to a lotus leaf. Electronic supplementary information (ESI) available: Fig. S1; AFM image of the Co-O layer which was first dried at 40 °C and then oxidized at 200 °C. Fig. S2; graph relative to the area of CNT islands for different catalyst configurations. Fig. S3; representative XPS spectra of (a) Si 2p, (b) Al 2p, (c) Fe 2p and (d) Co 2p for a reduced Al/Fe/Al/Co (20/20/20/20) catalyst film (grey line in all figures shows the peak backgrounds and orange line shows the curve fitted). Contact angle movies, Video S1 and Video S2, of Al/Fe/Al/Co samples 40/20/20/20 and 20/40/20/20, respectively. See DOI: 10.1039/c2nr30258f

Prognostic impact of location and extent of vessel-related ischemia at myocardial perfusion scintigraphy in patients with or at risk for coronary artery disease.

PubMed

Nudi, Francesco; Schillaci, Orazio; Neri, Giandomenico; Pinto, Annamaria; Procaccini, Enrica; Vetere, Maurizio; Frati, Giacomo; Tomai, Fabrizio; Biondi-Zoccai, Giuseppe

2016-04-01

Myocardial perfusion scintigraphy (MPS) has an established diagnostic and prognostic role in patients with or at risk for coronary artery disease, with ischemia severity and extent having already been identified as key predictors. Whether this is affected by the location of myocardial ischemia is uncertain. We aimed at comparing the prognostic outlook of patients undergoing MPS according to the site of ischemia. Our institutional database was queried for subjects undergoing MPS, without myocardial necrosis or recent revascularization. We focused on the prognostic impact of location of vessel-related ischemia (VRI) at MPS, distinguishing four mutually exclusive groups: single-VRI involving left anterior descending (LAD), single-VRI not involving LAD, multi-VRI involving LAD, and multi-VRI not involving LAD. The primary outcome was the long-term (>1 year) rate of death or myocardial infarction (D/MI). A total of 13,254 patients were included. Moderate or severe VRI occurred in 2,627 (20%) patients. Clinical outcomes were significantly different among the groups of patients with moderate or severe VRI, including death, cardiac death, non-fatal myocardial infarction or their composites (overall P < .001). Specifically, and excluding subjects undergoing revascularization as first follow-up event, D/MI occurred in 8.4% of patients with single-VRI involving LAD, 5.5% of subjects with single-VRI not involving LAD, 16.5% of those with multi-VRI involving LAD, and 7.3% of patients with multi-VRI not involving LAD (overall P < .001). Even at incremental multivariable Cox proportional analysis, hierarchical VRI was independently associated with an increased risk of D/MI [hazard ratio = 1.17 (1.04-1.08) for each class increment, P = .010]. Location and extent of myocardial ischemia at MPS according to the VRI concept have a hierarchical predictive impact, with multi-VRI involving LAD being significantly and independently more prognostically ominous than other types of VRI.

The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing.

PubMed

Kennedy, Nicholas A; Walker, Alan W; Berry, Susan H; Duncan, Sylvia H; Farquarson, Freda M; Louis, Petra; Thomson, John M; Satsangi, Jack; Flint, Harry J; Parkhill, Julian; Lees, Charlie W; Hold, Georgina L

2014-01-01

Determining bacterial community structure in fecal samples through DNA sequencing is an important facet of intestinal health research. The impact of different commercially available DNA extraction kits upon bacterial community structures has received relatively little attention. The aim of this study was to analyze bacterial communities in volunteer and inflammatory bowel disease (IBD) patient fecal samples extracted using widely used DNA extraction kits in established gastrointestinal research laboratories. Fecal samples from two healthy volunteers (H3 and H4) and two relapsing IBD patients (I1 and I2) were investigated. DNA extraction was undertaken using MoBio Powersoil and MP Biomedicals FastDNA SPIN Kit for Soil DNA extraction kits. PCR amplification for pyrosequencing of bacterial 16S rRNA genes was performed in both laboratories on all samples. Hierarchical clustering of sequencing data was done using the Yue and Clayton similarity coefficient. DNA extracted using the FastDNA kit and the MoBio kit gave median DNA concentrations of 475 (interquartile range 228-561) and 22 (IQR 9-36) ng/µL respectively (p<0.0001). Hierarchical clustering of sequence data by Yue and Clayton coefficient revealed four clusters. Samples from individuals H3 and I2 clustered by patient; however, samples from patient I1 extracted with the MoBio kit clustered with samples from patient H4 rather than the other I1 samples. Linear modelling on relative abundance of common bacterial families revealed significant differences between kits; samples extracted with MoBio Powersoil showed significantly increased Bacteroidaceae, Ruminococcaceae and Porphyromonadaceae, and lower Enterobacteriaceae, Lachnospiraceae, Clostridiaceae, and Erysipelotrichaceae (p<0.05). This study demonstrates significant differences in DNA yield and bacterial DNA composition when comparing DNA extracted from the same fecal sample with different extraction kits. This highlights the importance of ensuring that samples in a study are prepared with the same method, and the need for caution when cross-comparing studies that use different methods.

Reasoning about Evolution's Grand Patterns: College Students' Understanding of the Tree of Life

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2013-01-01

Tree thinking involves using cladograms, hierarchical diagrams depicting the evolutionary history of a set of taxa, to reason about evolutionary relationships and support inferences. Tree thinking is indispensable in modern science. College students' tree-thinking skills were investigated using tree (much more common in professional biology) and…

Differential Personality Correlates of Early Adolescents' Bullying-Related Outsider and Defender Behavior

ERIC Educational Resources Information Center

Pronk, Jeroen; Olthof, Tjeert; Goossens, Frits A.

2015-01-01

This study investigated personality correlates of early adolescents' tendency to either defend victims of bullying or to avoid involvement in bullying situations. Participants were 591 Dutch fifth- and sixth-grade students (X-bar[subscript age] = 11.42 years). Hierarchical regression models were run to predict these students' peer-reported…

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Fostering Radical Conceptual Change through Dual-Situated Learning Model

ERIC Educational Resources Information Center

She, Hsiao-Ching

2004-01-01

This article examines how the Dual-Situated Learning Model (DSLM) facilitates a radical change of concepts that involve the understanding of matter, process, and hierarchical attributes. The DSLM requires knowledge of students' prior beliefs of science concepts and the nature of these concepts. In addition, DSLM also serves two functions: it…

Hierarchical filters determine community assembly of urban species pools

Treesearch

Myla F.J. Aronson; Charles H. Nilon; Christopher A. Lepczyk; Tommy S. Parker; Paige S. Warren; Sarel S. Cilliers; Mark A. Goddard; Amy K. Hahs; Cecilia Herzog; Madhusudan Katti; Frank A. La Sorte; Nicholas S.G. Williams; Wayne  Zipperer

2016-01-01

The majority of humanity now lives in cities or towns, with this proportion expected to continue increasing for the foreseeable future. As novel ecosystems, urban areas offer an ideal opportunity to examine multi-scalar processes involved in community assembly as well as the role of human activities in modulating environmental drivers of biodiversity. Although...

Suppressor Variables and Multilevel Mixture Modelling

ERIC Educational Resources Information Center

Darmawan, I Gusti Ngurah; Keeves, John P.

2006-01-01

A major issue in educational research involves taking into consideration the multilevel nature of the data. Since the late 1980s, attempts have been made to model social science data that conform to a nested structure. Among other models, two-level structural equation modelling or two-level path modelling and hierarchical linear modelling are two…

The Role of Schools, Families, and Psychological Variables on Math Achievement of Black High School Students

ERIC Educational Resources Information Center

Strayhorn, Terrell L.

2010-01-01

Using data from the National Education Longitudinal Study (NELS;1988/2000), the author conducted hierarchical linear regression analyses, with a nested design, to estimate the influence of affective variables--parent involvement, teacher perceptions, and school environments--on Black students' math achievement in grade 10. Drawing on…

The Human EST Ontology Explorer: a tissue-oriented visualization system for ontologies distribution in human EST collections.

PubMed

Merelli, Ivan; Caprera, Andrea; Stella, Alessandra; Del Corvo, Marcello; Milanesi, Luciano; Lazzari, Barbara

2009-10-15

The NCBI dbEST currently contains more than eight million human Expressed Sequenced Tags (ESTs). This wide collection represents an important source of information for gene expression studies, provided it can be inspected according to biologically relevant criteria. EST data can be browsed using different dedicated web resources, which allow to investigate library specific gene expression levels and to make comparisons among libraries, highlighting significant differences in gene expression. Nonetheless, no tool is available to examine distributions of quantitative EST collections in Gene Ontology (GO) categories, nor to retrieve information concerning library-dependent EST involvement in metabolic pathways. In this work we present the Human EST Ontology Explorer (HEOE) http://www.itb.cnr.it/ptp/human_est_explorer, a web facility for comparison of expression levels among libraries from several healthy and diseased tissues. The HEOE provides library-dependent statistics on the distribution of sequences in the GO Direct Acyclic Graph (DAG) that can be browsed at each GO hierarchical level. The tool is based on large-scale BLAST annotation of EST sequences. Due to the huge number of input sequences, this BLAST analysis was performed with the aid of grid computing technology, which is particularly suitable to address data parallel task. Relying on the achieved annotation, library-specific distributions of ESTs in the GO Graph were inferred. A pathway-based search interface was also implemented, for a quick evaluation of the representation of libraries in metabolic pathways. EST processing steps were integrated in a semi-automatic procedure that relies on Perl scripts and stores results in a MySQL database. A PHP-based web interface offers the possibility to simultaneously visualize, retrieve and compare data from the different libraries. Statistically significant differences in GO categories among user selected libraries can also be computed. The HEOE provides an alternative and complementary way to inspect EST expression levels with respect to approaches currently offered by other resources. Furthermore, BLAST computation on the whole human EST dataset was a suitable test of grid scalability in the context of large-scale bioinformatics analysis. The HEOE currently comprises sequence analysis from 70 non-normalized libraries, representing a comprehensive overview on healthy and unhealthy tissues. As the analysis procedure can be easily applied to other libraries, the number of represented tissues is intended to increase.

Modelling dynamics with context-free grammars

NASA Astrophysics Data System (ADS)

García-Huerta, Juan-M.; Jiménez-Hernández, Hugo; Herrera-Navarro, Ana-M.; Hernández-Díaz, Teresa; Terol-Villalobos, Ivan

2014-03-01

This article presents a strategy to model the dynamics performed by vehicles in a freeway. The proposal consists on encode the movement as a set of finite states. A watershed-based segmentation is used to localize regions with high-probability of motion. Each state represents a proportion of a camera projection in a two-dimensional space, where each state is associated to a symbol, such that any combination of symbols is expressed as a language. Starting from a sequence of symbols through a linear algorithm a free-context grammar is inferred. This grammar represents a hierarchical view of common sequences observed into the scene. Most probable grammar rules express common rules associated to normal movement behavior. Less probable rules express themselves a way to quantify non-common behaviors and they might need more attention. Finally, all sequences of symbols that does not match with the grammar rules, may express itself uncommon behaviors (abnormal). The grammar inference is built with several sequences of images taken from a freeway. Testing process uses the sequence of symbols emitted by the scenario, matching the grammar rules with common freeway behaviors. The process of detect abnormal/normal behaviors is managed as the task of verify if any word generated by the scenario is recognized by the grammar.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Analysis of sequence repeats of proteins in the PDB.

PubMed

Mary Rajathei, David; Selvaraj, Samuel

2013-12-01

Internal repeats in protein sequences play a significant role in the evolution of protein structure and function. Applications of different bioinformatics tools help in the identification and characterization of these repeats. In the present study, we analyzed sequence repeats in a non-redundant set of proteins available in the Protein Data Bank (PDB). We used RADAR for detecting internal repeats in a protein, PDBeFOLD for assessing structural similarity, PDBsum for finding functional involvement and Pfam for domain assignment of the repeats in a protein. Through the analysis of sequence repeats, we found that identity of the sequence repeats falls in the range of 20-40% and, the superimposed structures of the most of the sequence repeats maintain similar overall folding. Analysis sequence repeats at the functional level reveals that most of the sequence repeats are involved in the function of the protein through functionally involved residues in the repeat regions. We also found that sequence repeats in single and two domain proteins often contained conserved sequence motifs for the function of the domain. Copyright © 2013 Elsevier Ltd. All rights reserved.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Tree-Structured Digital Organisms Model

NASA Astrophysics Data System (ADS)

Suzuki, Teruhiko; Nobesawa, Shiho; Tahara, Ikuo

Tierra and Avida are well-known models of digital organisms. They describe a life process as a sequence of computation codes. A linear sequence model may not be the only way to describe a digital organism, though it is very simple for a computer-based model. Thus we propose a new digital organism model based on a tree structure, which is rather similar to the generic programming. With our model, a life process is a combination of various functions, as if life in the real world is. This implies that our model can easily describe the hierarchical structure of life, and it can simulate evolutionary computation through mutual interaction of functions. We verified our model by simulations that our model can be regarded as a digital organism model according to its definitions. Our model even succeeded in creating species such as viruses and parasites.

Navigating Comics: An Empirical and Theoretical Approach to Strategies of Reading Comic Page Layouts

PubMed Central

Cohn, Neil

2013-01-01

Like the sequence of words in written language, comic book page layouts direct images into a deliberate reading sequence. Conventional wisdom would expect that comic panels follow the order of text: left-to-right and down – a “Z-path” – though several layouts can violate this order, such as Gestalt groupings of panels that deny a Z-path of reading. To examine how layouts pressure readers to choose pathways deviating from the Z-path, we presented participants with comic pages empty of content, and asked them to number the panels in the order they would read them. Participants frequently used strategies departing from both the traditional Z-path and Gestalt groupings. These preferences reveal a system of constraints that organizes panels into hierarchic constituents, guiding readers through comic page layouts. PMID:23616776

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

Unsupervised learning of natural languages

PubMed Central

Solan, Zach; Horn, David; Ruppin, Eytan; Edelman, Shimon

2005-01-01

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The adios (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics. PMID:16087885

Unsupervised learning of natural languages.

PubMed

Solan, Zach; Horn, David; Ruppin, Eytan; Edelman, Shimon

2005-08-16

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The adios (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale

PubMed Central

Schmidt, Thomas S. B.; Matias Rodrigues, João F.; von Mering, Christian

2014-01-01

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale. PMID:24763141

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

Jason L. Wright; Milos Manic

Time synchronization and event time correlation are important in wireless sensor networks. In particular, time is used to create a sequence events or time line to answer questions of cause and effect. Time is also used as a basis for determining the freshness of received packets and the validity of cryptographic certificates. This paper presents secure method of time synchronization and event time correlation for TESLA-based hierarchical wireless sensor networks. The method demonstrates that events in a TESLA network can be accurately timestamped by adding only a few pieces of data to the existing protocol.

Nanoscale structure in AgSbTe2 determined by diffuse elastic neutron scattering

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

Specht, Eliot D; Ma, Jie; Delaire, Olivier A

2015-01-01

Diffuse elastic neutron scattering measurements confirm that AgSbTe2 has a hierarchical structure, with defects on length scales from nanometers to microns. While scattering from mesoscale structure is consistent with previously-proposed structures in which Ag and Sb order on a NaCl lattice, more diffuse scattering from nanoscale structure suggests a structural rearrangement in which hexagonal layers form a combination of (ABC), (ABA), and (AAB) stacking sequences. The AgCrSe2 structure is the best-fitting model for the local atomic arrangements.

Whole-Genome Sequencing and Assembly with High-Throughput, Short-Read Technologies

PubMed Central

Sundquist, Andreas; Ronaghi, Mostafa; Tang, Haixu; Pevzner, Pavel; Batzoglou, Serafim

2007-01-01

While recently developed short-read sequencing technologies may dramatically reduce the sequencing cost and eventually achieve the $1000 goal for re-sequencing, their limitations prevent the de novo sequencing of eukaryotic genomes with the standard shotgun sequencing protocol. We present SHRAP (SHort Read Assembly Protocol), a sequencing protocol and assembly methodology that utilizes high-throughput short-read technologies. We describe a variation on hierarchical sequencing with two crucial differences: (1) we select a clone library from the genome randomly rather than as a tiling path and (2) we sample clones from the genome at high coverage and reads from the clones at low coverage. We assume that 200 bp read lengths with a 1% error rate and inexpensive random fragment cloning on whole mammalian genomes is feasible. Our assembly methodology is based on first ordering the clones and subsequently performing read assembly in three stages: (1) local assemblies of regions significantly smaller than a clone size, (2) clone-sized assemblies of the results of stage 1, and (3) chromosome-sized assemblies. By aggressively localizing the assembly problem during the first stage, our method succeeds in assembling short, unpaired reads sampled from repetitive genomes. We tested our assembler using simulated reads from D. melanogaster and human chromosomes 1, 11, and 21, and produced assemblies with large sets of contiguous sequence and a misassembly rate comparable to other draft assemblies. Tested on D. melanogaster and the entire human genome, our clone-ordering method produces accurate maps, thereby localizing fragment assembly and enabling the parallelization of the subsequent steps of our pipeline. Thus, we have demonstrated that truly inexpensive de novo sequencing of mammalian genomes will soon be possible with high-throughput, short-read technologies using our methodology. PMID:17534434

Molecular evidence of Burkholderia pseudomallei genotypes based on geographical distribution.

PubMed

Zulkefli, Noorfatin Jihan; Mariappan, Vanitha; Vellasamy, Kumutha Malar; Chong, Chun Wie; Thong, Kwai Lin; Ponnampalavanar, Sasheela; Vadivelu, Jamuna; Teh, Cindy Shuan Ju

2016-01-01

Background. Central intermediary metabolism (CIM) in bacteria is defined as a set of metabolic biochemical reactions within a cell, which is essential for the cell to survive in response to environmental perturbations. The genes associated with CIM are commonly found in both pathogenic and non-pathogenic strains. As these genes are involved in vital metabolic processes of bacteria, we explored the efficiency of the genes in genotypic characterization of Burkholderia pseudomallei isolates, compared with the established pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) schemes. Methods. Nine previously sequenced B. pseudomallei isolates from Malaysia were characterized by PFGE, MLST and CIM genes. The isolates were later compared to the other 39 B. pseudomallei strains, retrieved from GenBank using both MLST and sequence analysis of CIM genes. UniFrac and hierachical clustering analyses were performed using the results generated by both MLST and sequence analysis of CIM genes. Results. Genetic relatedness of nine Malaysian B. pseudomallei isolates and the other 39 strains was investigated. The nine Malaysian isolates were subtyped into six PFGE profiles, four MLST profiles and five sequence types based on CIM genes alignment. All methods demonstrated the clonality of OB and CB as well as CMS and THE. However, PFGE showed less than 70% similarity between a pair of morphology variants, OS and OB. In contrast, OS was identical to the soil isolate, MARAN. To have a better understanding of the genetic diversity of B. pseudomallei worldwide, we further aligned the sequences of genes used in MLST and genes associated with CIM for the nine Malaysian isolates and 39 B. pseudomallei strains from NCBI database. Overall, based on the CIM genes, the strains were subtyped into 33 profiles where majority of the strains from Asian countries were clustered together. On the other hand, MLST resolved the isolates into 31 profiles which formed three clusters. Hierarchical clustering using UniFrac distance suggested that the isolates from Australia were genetically distinct from the Asian isolates. Nevertheless, statistical significant differences were detected between isolates from Malaysia, Thailand and Australia. Discussion. Overall, PFGE showed higher discriminative power in clustering the nine Malaysian B. pseudomallei isolates and indicated its suitability for localized epidemiological study. Compared to MLST, CIM genes showed higher resolution in distinguishing those non-related strains and better clustering of strains from different geographical regions. A closer genetic relatedness of Malaysian isolates with all Asian strains in comparison to Australian strains was observed. This finding was supported by UniFrac analysis which resulted in geographical segregation between Australia and the Asian countries.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks

PubMed Central

2011-01-01

Background Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. Results A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Conclusions Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced. PMID:21849086

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks.

PubMed

Xie, Xueying; Jin, Jing; Mao, Yongyi

2011-08-18

Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced.

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

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

Compromise decision support problems for hierarchical design involving uncertainty

NASA Astrophysics Data System (ADS)

Vadde, S.; Allen, J. K.; Mistree, F.

1994-08-01

In this paper an extension to the traditional compromise Decision Support Problem (DSP) formulation is presented. Bayesian statistics is used in the formulation to model uncertainties associated with the information being used. In an earlier paper a compromise DSP that accounts for uncertainty using fuzzy set theory was introduced. The Bayesian Decision Support Problem is described in this paper. The method for hierarchical design is demonstrated by using this formulation to design a portal frame. The results are discussed and comparisons are made with those obtained using the fuzzy DSP. Finally, the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation is discussed and some pending research issues are described. Our emphasis in this paper is on the method rather than the results per se.

Design and control of active vision based mechanisms for intelligent robots

NASA Technical Reports Server (NTRS)

Wu, Liwei; Marefat, Michael M.

1994-01-01

In this paper, we propose a design of an active vision system for intelligent robot application purposes. The system has the degrees of freedom of pan, tilt, vergence, camera height adjustment, and baseline adjustment with a hierarchical control system structure. Based on this vision system, we discuss two problems involved in the binocular gaze stabilization process: fixation point selection and vergence disparity extraction. A hierarchical approach to determining point of fixation from potential gaze targets using evaluation function representing human visual behavior to outside stimuli is suggested. We also characterize different visual tasks in two cameras for vergence control purposes, and a phase-based method based on binarized images to extract vergence disparity for vergence control is presented. A control algorithm for vergence control is discussed.

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

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qui

2009-01-01

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

People First: A New Zealand Approach to Staff, Structure and Service

ERIC Educational Resources Information Center

Hill, Jane

2007-01-01

This article uses Wellington City Libraries as the basis for a case study of a future-focused, reorganized staffing structure in a public library network. It covers the change from why, how, departure from a building-based hierarchical structure, new staff and line responsibilities, union involvement, implications for staff training to culture and…

An Investigation of the Hierarchical and Developmental Structure of Selected Science Concepts.

ERIC Educational Resources Information Center

Griffiths, Alan Keith

This report describes the results of an attempt to identify a learning hierarchy for each of a number of science concepts mainly encountered first in the high school grades. The concepts studied relate to stoichiometric calculations and molarity, both from chemistry; to food web relationships and problems involving Mendel's laws from biology; to…

Training Class Inclusion Responding in Typically Developing Children and Individuals with Autism

ERIC Educational Resources Information Center

Ming, Siri; Mulhern, Teresa; Stewart, Ian; Moran, Laura; Bynum, Kellie

2018-01-01

In a "class inclusion" task, a child must respond to stimuli as being involved in two different though hierarchically related categories. This study used a Relational Frame Theory (RFT) paradigm to assess and train this ability in three typically developing preschoolers and three individuals with autism spectrum disorder, all of whom had…

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

hierarchical control architecture that enables a hybrid control approach, where centralized control systems will be complemented by distributed control algorithms for solar inverters and autonomous control of ), involves developing a novel control scheme that provides system-wide monitoring and control using a small

Parent Involvement and Children's Academic and Social Development in Elementary School

ERIC Educational Resources Information Center

El Nokali, Nermeen E.; Bachman, Heather J.; Votruba-Drzal, Elizabeth

2010-01-01

Data from the National Institute of Child Health and Human Development (NICHD) Study of Early Childcare and Youth Development (N = 1,364) were used to investigate children's trajectories of academic and social development across 1st, 3rd, and 5th grades. Hierarchical linear modeling was used to examine within- and between-child associations among…

Getting a Jump on the Future: Everything You'll Ever Need to Know about Multimedia Authoring Tools.

ERIC Educational Resources Information Center

D'Ignazio, Fred

1992-01-01

Discusses issues involved with buying and using multimedia authoring programs. Six programs are compared: (1) MediaText, (2) HyperCard, (3) LinkWay Live!, (4) AmigaVision, (5) Director, and (6) Multimedia Desktop. Highlights include the use of multimedia in education, sequential versus hierarchical organization, price, system requirements, digital…

Making Sense of Students' Actions in an Open-Ended Virtual Laboratory Environment

ERIC Educational Resources Information Center

Gal, Ya'akov; Uzan, Oriel; Belford, Robert; Karabinos, Michael; Yaron, David

2015-01-01

A process for analyzing log files collected from open-ended learning environments is developed and tested on a virtual lab problem involving reaction stoichiometry. The process utilizes a set of visualization tools that, by grouping student actions in a hierarchical manner, helps experts make sense of the linear list of student actions recorded in…

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering

PubMed Central

Sul, Woo Jun; Cole, James R.; Jesus, Ederson da C.; Wang, Qiong; Farris, Ryan J.; Fish, Jordan A.; Tiedje, James M.

2011-01-01

High-throughput sequencing of 16S rRNA genes has increased our understanding of microbial community structure, but now even higher-throughput methods to the Illumina scale allow the creation of much larger datasets with more samples and orders-of-magnitude more sequences that swamp current analytic methods. We developed a method capable of handling these larger datasets on the basis of assignment of sequences into an existing taxonomy using a supervised learning approach (taxonomy-supervised analysis). We compared this method with a commonly used clustering approach based on sequence similarity (taxonomy-unsupervised analysis). We sampled 211 different bacterial communities from various habitats and obtained ∼1.3 million 16S rRNA sequences spanning the V4 hypervariable region by pyrosequencing. Both methodologies gave similar ecological conclusions in that β-diversity measures calculated by using these two types of matrices were significantly correlated to each other, as were the ordination configurations and hierarchical clustering dendrograms. In addition, our taxonomy-supervised analyses were also highly correlated with phylogenetic methods, such as UniFrac. The taxonomy-supervised analysis has the advantages that it is not limited by the exhaustive computation required for the alignment and clustering necessary for the taxonomy-unsupervised analysis, is more tolerant of sequencing errors, and allows comparisons when sequences are from different regions of the 16S rRNA gene. With the tremendous expansion in 16S rRNA data acquisition underway, the taxonomy-supervised approach offers the potential to provide more rapid and extensive community comparisons across habitats and samples. PMID:21873204

HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold.

PubMed

Pagnuco, Inti Anabela; Revuelta, María Victoria; Bondino, Hernán Gabriel; Brun, Marcel; Ten Have, Arjen

2018-01-01

Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear subfamily hallmarks that would allow pattern-based function assignation by which this task is mostly achieved based on the similarity principle. This is hampered by the lack of a score cut-off that is both sensitive and specific. HMMER Cut-off Threshold Tool (HMMERCTTER) adds a reliable cut-off threshold to the popular HMMER. Using a high quality superfamily phylogeny, it clusters a set of training sequences such that the cluster-specific HMMER profiles show cluster or subfamily member detection with 100% precision and recall (P&R), thereby generating a specific threshold as inclusion cut-off. Profiles and thresholds are then used as classifiers to screen a target dataset. Iterative inclusion of novel sequences to groups and the corresponding HMMER profiles results in high sensitivity while specificity is maintained by imposing 100% P&R self detection. In three presented case studies of protein superfamilies, classification of large datasets with 100% precision was achieved with over 95% recall. Limits and caveats are presented and explained. HMMERCTTER is a promising protein superfamily sequence classifier provided high quality training datasets are used. It provides a decision support system that aids in the difficult task of sequence function assignation in the twilight zone of sequence similarity. All relevant data and source codes are available from the Github repository at the following URL: https://github.com/BBCMdP/HMMERCTTER.

HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold

PubMed Central

Pagnuco, Inti Anabela; Revuelta, María Victoria; Bondino, Hernán Gabriel; Brun, Marcel

2018-01-01

Background Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear subfamily hallmarks that would allow pattern-based function assignation by which this task is mostly achieved based on the similarity principle. This is hampered by the lack of a score cut-off that is both sensitive and specific. Results HMMER Cut-off Threshold Tool (HMMERCTTER) adds a reliable cut-off threshold to the popular HMMER. Using a high quality superfamily phylogeny, it clusters a set of training sequences such that the cluster-specific HMMER profiles show cluster or subfamily member detection with 100% precision and recall (P&R), thereby generating a specific threshold as inclusion cut-off. Profiles and thresholds are then used as classifiers to screen a target dataset. Iterative inclusion of novel sequences to groups and the corresponding HMMER profiles results in high sensitivity while specificity is maintained by imposing 100% P&R self detection. In three presented case studies of protein superfamilies, classification of large datasets with 100% precision was achieved with over 95% recall. Limits and caveats are presented and explained. Conclusions HMMERCTTER is a promising protein superfamily sequence classifier provided high quality training datasets are used. It provides a decision support system that aids in the difficult task of sequence function assignation in the twilight zone of sequence similarity. All relevant data and source codes are available from the Github repository at the following URL: https://github.com/BBCMdP/HMMERCTTER. PMID:29579071

Parent Involvement and Children's Academic and Social Development in Elementary School

PubMed Central

El Nokali, Nermeen E.; Bachman, Heather J.; Votruba-Drzal, Elizabeth

2010-01-01

Data from the NICHD Study of Early Childcare and Youth Development (N= 1364) were used to investigate children's trajectories of academic and social development across first, third and fifth grade. Hierarchical linear modeling was used to examine within- and between-child associations among maternal- and teacher-reports of parent involvement and children's standardized achievement scores, social skills, and problem behaviors. Findings suggest that within-child improvements in parent involvement predict declines in problem behaviors and improvements in social skills but do not predict changes in achievement. Between-child analyses demonstrated that children with highly involved parents had enhanced social functioning and fewer behavior problems. Similar patterns of findings emerged for teacher- and parent-reports of parent involvement. Implications for policy and practice are discussed. PMID:20573118

Cognitive and neural foundations of discrete sequence skill: a TMS study.

PubMed

Ruitenberg, Marit F L; Verwey, Willem B; Schutter, Dennis J L G; Abrahamse, Elger L

2014-04-01

Executing discrete movement sequences typically involves a shift with practice from a relatively slow, stimulus-based mode to a fast mode in which performance is based on retrieving and executing entire motor chunks. The dual processor model explains the performance of (skilled) discrete key-press sequences in terms of an interplay between a cognitive processor and a motor system. In the present study, we tested and confirmed the core assumptions of this model at the behavioral level. In addition, we explored the involvement of the pre-supplementary motor area (pre-SMA) in discrete sequence skill by applying inhibitory 20 min 1-Hz off-line repetitive transcranial magnetic stimulation (rTMS). Based on previous work, we predicted pre-SMA involvement in the selection/initiation of motor chunks, and this was confirmed by our results. The pre-SMA was further observed to be more involved in more complex than in simpler sequences, while no evidence was found for pre-SMA involvement in direct stimulus-response translations or associative learning processes. In conclusion, support is provided for the dual processor model, and for pre-SMA involvement in the initiation of motor chunks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiple directed graph large-class multi-spectral processor

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki

1988-01-01

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

Relationship between School Administrators’ Reports of Parental Involvement in School and Students’ Substance Use: A National Study

PubMed Central

Kumar, Revathy; O’Malley, Patrick M; Johnston, Lloyd D.

2013-01-01

This study examines the relationship between student substance use and school-level parental involvement as reported by administrators. Questionnaires were administered to school administrators and 111,652 students in 1,011 U.S. schools. Hierarchical logistic regression analyses conducted on 1998–2003 data from students and administrators indicate significantly lower prevalence of alcohol use among 8th graders in schools where administrators reported high parental involvement. Overall, administrators’ reports of high parental involvement were unrelated to prevalence of substance use among 10th graders, and were associated with higher prevalence of alcohol use among 12th-graders. Implications and limitations are discussed, along with suggestions for future research. PMID:26430355

Fabrication of hierarchical hybrid structures using bio-enabled layer-by-layer self-assembly.

PubMed

Hnilova, Marketa; Karaca, Banu Taktak; Park, James; Jia, Carol; Wilson, Brandon R; Sarikaya, Mehmet; Tamerler, Candan

2012-05-01

Development of versatile and flexible assembly systems for fabrication of functional hybrid nanomaterials with well-defined hierarchical and spatial organization is of a significant importance in practical nanobiotechnology applications. Here we demonstrate a bio-enabled self-assembly technique for fabrication of multi-layered protein and nanometallic assemblies utilizing a modular gold-binding (AuBP1) fusion tag. To accomplish the bottom-up assembly we first genetically fused the AuBP1 peptide sequence to the C'-terminus of maltose-binding protein (MBP) using two different linkers to produce MBP-AuBP1 hetero-functional constructs. Using various spectroscopic techniques, surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR), we verified the exceptional binding and self-assembly characteristics of AuBP1 peptide. The AuBP1 peptide tag can direct the organization of recombinant MBP protein on various gold surfaces through an efficient control of the organic-inorganic interface at the molecular level. Furthermore using a combination of soft-lithography, self-assembly techniques and advanced AuBP1 peptide tag technology, we produced spatially and hierarchically controlled protein multi-layered assemblies on gold nanoparticle arrays with high molecular packing density and pattering efficiency in simple, reproducible steps. This model system offers layer-by-layer assembly capability based on specific AuBP1 peptide tag and constitutes novel biological routes for biofabrication of various protein arrays, plasmon-active nanometallic assemblies and devices with controlled organization, packing density and architecture. Copyright © 2011 Wiley Periodicals, Inc.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture.

PubMed

Baquero, Fernando

2017-11-01

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Trait-based diversification shifts reflect differential extinction among fossil taxa.

PubMed

Wagner, Peter J; Estabrook, George F

2014-11-18

Evolution provides many cases of apparent shifts in diversification associated with particular anatomical traits. Three general models connect these patterns to anatomical evolution: (i) elevated net extinction of taxa bearing particular traits, (ii) elevated net speciation of taxa bearing particular traits, and (iii) elevated evolvability expanding the range of anatomies available to some species. Trait-based diversification shifts predict elevated hierarchical stratigraphic compatibility (i.e., primitive→derived→highly derived sequences) among pairs of anatomical characters. The three specific models further predict (i) early loss of diversity for taxa retaining primitive conditions (elevated net extinction), (ii) increased diversification among later members of a clade (elevated net speciation), and (iii) increased disparity among later members in a clade (elevated evolvability). Analyses of 319 anatomical and stratigraphic datasets for fossil species and genera show that hierarchical stratigraphic compatibility exceeds the expectations of trait-independent diversification in the vast majority of cases, which was expected if trait-dependent diversification shifts are common. Excess hierarchical stratigraphic compatibility correlates with early loss of diversity for groups retaining primitive conditions rather than delayed bursts of diversity or disparity across entire clades. Cambrian clades (predominantly trilobites) alone fit null expectations well. However, it is not clear whether evolution was unusual among Cambrian taxa or only early trilobites. At least among post-Cambrian taxa, these results implicate models, such as competition and extinction selectivity/resistance, as major drivers of trait-based diversification shifts at the species and genus levels while contradicting the predictions of elevated net speciation and elevated evolvability models.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Inter-subject synchronization of brain responses during natural music listening.

PubMed

Abrams, Daniel A; Ryali, Srikanth; Chen, Tianwen; Chordia, Parag; Khouzam, Amirah; Levitin, Daniel J; Menon, Vinod

2013-05-01

Music is a cultural universal and a rich part of the human experience. However, little is known about common brain systems that support the processing and integration of extended, naturalistic 'real-world' music stimuli. We examined this question by presenting extended excerpts of symphonic music, and two pseudomusical stimuli in which the temporal and spectral structure of the Natural Music condition were disrupted, to non-musician participants undergoing functional brain imaging and analysing synchronized spatiotemporal activity patterns between listeners. We found that music synchronizes brain responses across listeners in bilateral auditory midbrain and thalamus, primary auditory and auditory association cortex, right-lateralized structures in frontal and parietal cortex, and motor planning regions of the brain. These effects were greater for natural music compared to the pseudo-musical control conditions. Remarkably, inter-subject synchronization in the inferior colliculus and medial geniculate nucleus was also greater for the natural music condition, indicating that synchronization at these early stages of auditory processing is not simply driven by spectro-temporal features of the stimulus. Increased synchronization during music listening was also evident in a right-hemisphere fronto-parietal attention network and bilateral cortical regions involved in motor planning. While these brain structures have previously been implicated in various aspects of musical processing, our results are the first to show that these regions track structural elements of a musical stimulus over extended time periods lasting minutes. Our results show that a hierarchical distributed network is synchronized between individuals during the processing of extended musical sequences, and provide new insight into the temporal integration of complex and biologically salient auditory sequences. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

An improved model for whole genome phylogenetic analysis by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees and demonstrates that the improved DFT dissimilarity measure is an efficient and effective similarity measure of DNA sequences. Due to its high efficiency and accuracy, the proposed DFT similarity measure is successfully applied on phylogenetic analysis for individual genes and large whole bacterial genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

3D deformable image matching: a hierarchical approach over nested subspaces

NASA Astrophysics Data System (ADS)

Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

2000-06-01

This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

Lineage-specific evolutionary rate in plants: Contributions of a screening for Cereus (Cactaceae).

PubMed

Romeiro-Brito, Monique; Moraes, Evandro M; Taylor, Nigel P; Zappi, Daniela C; Franco, Fernando F

2016-01-01

Predictable chloroplast DNA (cpDNA) sequences have been listed for the shallowest taxonomic studies in plants. We investigated whether plastid regions that vary between closely allied species could be applied for intraspecific studies and compared the variation of these plastid segments with two nuclear regions. We screened 16 plastid and two nuclear intronic regions for species of the genus Cereus (Cactaceae) at three hierarchical levels (species from different clades, species of the same clade, and allopatric populations). Ten plastid regions presented interspecific variation, and six of them showed variation at the intraspecific level. The two nuclear regions showed both inter- and intraspecific variation, and in general they showed higher levels of variability in almost all hierarchical levels than the plastid segments. Our data suggest no correspondence between variation of plastid regions at the interspecific and intraspecific level, probably due to lineage-specific variation in cpDNA, which appears to have less effect in nuclear data. Despite the heterogeneity in evolutionary rates of cpDNA, we highlight three plastid segments that may be considered in initial screenings in plant phylogeographic studies.

Genetically encoded lipid-polypeptide hybrid biomaterials that exhibit temperature-triggered hierarchical self-assembly

NASA Astrophysics Data System (ADS)

Mozhdehi, Davoud; Luginbuhl, Kelli M.; Simon, Joseph R.; Dzuricky, Michael; Berger, Rüdiger; Varol, H. Samet; Huang, Fred C.; Buehne, Kristen L.; Mayne, Nicholas R.; Weitzhandler, Isaac; Bonn, Mischa; Parekh, Sapun H.; Chilkoti, Ashutosh

2018-05-01

Post-translational modification of proteins is a strategy widely used in biological systems. It expands the diversity of the proteome and allows for tailoring of both the function and localization of proteins within cells as well as the material properties of structural proteins and matrices. Despite their ubiquity in biology, with a few exceptions, the potential of post-translational modifications in biomaterials synthesis has remained largely untapped. As a proof of concept to demonstrate the feasibility of creating a genetically encoded biohybrid material through post-translational modification, we report here the generation of a family of three stimulus-responsive hybrid materials—fatty-acid-modified elastin-like polypeptides—using a one-pot recombinant expression and post-translational lipidation methodology. These hybrid biomaterials contain an amphiphilic domain, composed of a β-sheet-forming peptide that is post-translationally functionalized with a C14 alkyl chain, fused to a thermally responsive elastin-like polypeptide. They exhibit temperature-triggered hierarchical self-assembly across multiple length scales with varied structure and material properties that can be controlled at the sequence level.

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

PubMed Central

Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

2013-01-01

Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Hierarchical Self-Organization of AB n Dendron-like Molecules into a Supramolecular Lattice Sequence

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

Feng, Xueyan; Zhang, Ruimeng; Li, Yiwen

To understand the hierarchical self-organization behaviors of soft materials as well as their dependence on molecular geometry, a series of ABn dendron-type giant molecules based on polyhedral oligomeric silsesquioxane (POSS) nanoparticles were designed and synthesized. The apex of these molecules is a hydrophilic POSS cage with fourteen hydroxyl groups (denoted DPOSS). At its periphery, there are different numbers (n = 1–8) of hydrophobic POSS cages with seven isobutyl groups (denoted BPOSS), connected to the apical DPOSS via flexible dendron type linker(s). With varying the BPOSS number from one to seven, a supramolecular lattice formation sequence ranging from lamella (DPOSS-BPOSS), doublemore » gyroid (space group of Ia3d, DPOSS-BPOSS2), hexagonal cylinder (space group of P6mm, DPOSS-BPOSS3), Frank-Kasper A15 (space group of Pm3n, DPOSS-BPOSS4, DPOSS-BPOSS5, and DPOSS-BPOSS6), to Frank-Kasper sigma (space group of P42/mnm, DPOSS-BPOSS7) phases can be observed. The nanostructure formations in this series of ABn dendron-type giant molecules are mainly directed by the macromolecular geometric shapes. Furthermore, within each spherical motif, the soft spherical core is consisted of hydrophilic DPOSS cages with flexible linkages, while the hydrophobic BPOSS cages form the relative rigid shell and contact with neighbors to provide decreased interfaces among the spherical motifs for constructing final polyhedral motifs in these Frank-Kasper lattices. This study provides the design principle of macromolecules with specific geometric shapes and functional groups to achieve anticipated structures and macroscopic properties.« less

Surface enhanced Raman spectroscopy (SERS) for the discrimination of Arthrobacter strains based on variations in cell surface composition.

PubMed

Stephen, Kate E; Homrighausen, Darren; DePalma, Glen; Nakatsu, Cindy H; Irudayaraj, Joseph

2012-09-21

Surface enhanced Raman spectroscopy (SERS) is a rapid and highly sensitive spectroscopic technique that has the potential to measure chemical changes in bacterial cell surface in response to environmental changes. The objective of this study was to determine whether SERS had sufficient resolution to differentiate closely related bacteria within a genus grown on solid and liquid medium, and a single Arthrobacter strain grown in multiple chromate concentrations. Fourteen closely related Arthrobacter strains, based on their 16S rRNA gene sequences, were used in this study. After performing principal component analysis in conjunction with Linear Discriminant Analysis, we used a novel, adapted cross-validation method, which more faithfully models the classification of spectra. All fourteen strains could be classified with up to 97% accuracy. The hierarchical trees comparing SERS spectra from the liquid and solid media datasets were different. Additionally, hierarchical trees created from the Raman data were different from those obtained using 16S rRNA gene sequences (a phylogenetic measure). A single bacterial strain grown on solid media culture with three different chromate levels also showed significant spectral distinction at discrete points identified by the new Elastic Net regularized regression method demonstrating the ability of SERS to detect environmentally induced changes in cell surface composition. This study demonstrates that SERS is effective in distinguishing between a large number of very closely related Arthrobacter strains and could be a valuable tool for rapid monitoring and characterization of phenotypic variations in a single population in response to environmental conditions.

Discrimination of multilocus sequence typing-based Campylobacter jejuni subgroups by MALDI-TOF mass spectrometry.

PubMed

Zautner, Andreas Erich; Masanta, Wycliffe Omurwa; Tareen, Abdul Malik; Weig, Michael; Lugert, Raimond; Groß, Uwe; Bader, Oliver

2013-11-07

Campylobacter jejuni, the most common bacterial pathogen causing gastroenteritis, shows a wide genetic diversity. Previously, we demonstrated by the combination of multi locus sequence typing (MLST)-based UPGMA-clustering and analysis of 16 genetic markers that twelve different C. jejuni subgroups can be distinguished. Among these are two prominent subgroups. The first subgroup contains the majority of hyperinvasive strains and is characterized by a dimeric form of the chemotaxis-receptor Tlp7(m+c). The second has an extended amino acid metabolism and is characterized by the presence of a periplasmic asparaginase (ansB) and gamma-glutamyl-transpeptidase (ggt). Phyloproteomic principal component analysis (PCA) hierarchical clustering of MALDI-TOF based intact cell mass spectrometry (ICMS) spectra was able to group particular C. jejuni subgroups of phylogenetic related isolates in distinct clusters. Especially the aforementioned Tlp7(m+c)(+) and ansB+/ ggt+ subgroups could be discriminated by PCA. Overlay of ICMS spectra of all isolates led to the identification of characteristic biomarker ions for these specific C. jejuni subgroups. Thus, mass peak shifts can be used to identify the C. jejuni subgroup with an extended amino acid metabolism. Although the PCA hierarchical clustering of ICMS-spectra groups the tested isolates into a different order as compared to MLST-based UPGMA-clustering, the isolates of the indicator-groups form predominantly coherent clusters. These clusters reflect phenotypic aspects better than phylogenetic clustering, indicating that the genes corresponding to the biomarker ions are phylogenetically coupled to the tested marker genes. Thus, PCA clustering could be an additional tool for analyzing the relatedness of bacterial isolates.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Cable deformation simulation and a hierarchical framework for Nb3Sn Rutherford cables

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

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

2009-09-13

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

In-situ preparation of hierarchical flower-like TiO2/carbon nanostructures as fillers for polymer composites with enhanced dielectric properties

PubMed Central

Xu, Nuoxin; Zhang, Qilong; Yang, Hui; Xia, Yuting; Jiang, Yongchang

2017-01-01

Novel three-dimensional hierarchical flower-like TiO2/carbon (TiO2/C) nanostructures were in-situ synthesized via a solvothermal method involving calcination of organic precursor under inert atmosphere. The composite films comprised of P (VDF-HFP) and as-prepared hierarchical flower-like TiO2/C were fabricated by a solution casting and hot-pressing approach. The results reveal that loading the fillers with a small amount of carbon is an effective way to improve the dielectric constant and suppress the dielectric loss. In addition, TiO2/C particles with higher carbon contents exhibit superiority in promoting the dielectric constants of composites when compared with their noncarbon counterparts. For instance, the highest dielectric constant (330.6) of the TiO2/C composites is 10 times over that of noncarbon-TiO2-filled ones at the same filler volume fraction, and 32 times over that of pristine P (VDF-HFP). The enhancement in the dielectric constant can be attributed to the formation of a large network, which is composed of local micro-capacitors with carbon particles as electrodes and TiO2 as the dielectric in between. PMID:28262766

EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases.

PubMed

Wang, Yongbo; Liu, Zexian; Cheng, Han; Gao, Tianshun; Pan, Zhicheng; Yang, Qing; Guo, Anyuan; Xue, Yu

2014-01-01

We present here EKPD (http://ekpd.biocuckoo.org), a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs), the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes. As extensive experimental and computational efforts have been carried out to identify PKs and PPs, an integrative resource with detailed classification and annotation information would be of great value for both experimentalists and computational biologists. In this work, we first collected 1855 PKs and 347 PPs from the scientific literature and various public databases. Based on previously established rationales, we classified all of the known PKs and PPs into a hierarchical structure with three levels, i.e. group, family and individual PK/PP. There are 10 groups with 149 families for the PKs and 10 groups with 33 families for the PPs. We constructed 139 and 27 Hidden Markov Model profiles for PK and PP families, respectively. Then we systematically characterized ∼50,000 PKs and >10,000 PPs in eukaryotes. In addition, >500 PKs and >400 PPs were computationally identified by ortholog search. Finally, the online service of the EKPD database was implemented in PHP + MySQL + JavaScript.

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.

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.

You’re a good structure, Charlie Brown: The distribution of narrative categories in comic strips

PubMed Central

Cohn, Neil

2014-01-01

Cohn’s (2013) theory of “Visual Narrative Grammar” argues that sequential images take on categorical roles in a narrative structure, which organizes them into hierarchic constituents analogous to the organization of syntactic categories in sentences. This theory proposes that narrative categories, like syntactic categories, can be identified through diagnostic tests that reveal tendencies for their distribution throughout a sequence. This paper describes four experiments testing these diagnostics to provide support for the validity of these narrative categories. In Experiment 1, participants reconstructed unordered panels of a comic strip into an order that makes sense. Experiment 2 measured viewing times to panels in sequences where the order of panels was reversed. In Experiment 3 participants again reconstructed strips, but also deleted a panel from the sequence. Finally, in Experiment 4 participants identified where a panel had been deleted from a comic strip, and rated that strip’s coherence. Overall, categories had consistent distributional tendencies within experiments and complementary tendencies across experiments. These results point toward an interaction between categorical roles and a global narrative structure. PMID:24646175

RaptorX-Property: a web server for protein structure property prediction.

PubMed

Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo

2016-07-08

RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Drawing the line between constituent structure and coherence relations in visual narratives

PubMed Central

Cohn, Neil; Bender, Patrick

2016-01-01

Theories of visual narrative understanding have often focused on the changes in meaning across a sequence, like shifts in characters, spatial location, and causation, as cues for breaks in the structure of a discourse. In contrast, the theory of Visual Narrative Grammar posits that hierarchic “grammatical” structures operate at the discourse level using categorical roles for images, which may or may not co-occur with shifts in coherence. We therefore examined the relationship between narrative structure and coherence shifts in the segmentation of visual narrative sequences using a “segmentation task” where participants drew lines between images in order to divide them into sub-episodes. We used regressions to analyze the influence of the expected constituent structure boundary, narrative categories, and semantic coherence relationships on the segmentation of visual narrative sequences. Narrative categories were a stronger predictor of segmentation than linear coherence relationships between panels, though both influenced participants’ divisions. Altogether, these results support the theory that meaningful sequential images use a narrative grammar that extends above and beyond linear semantic shifts between discourse units. PMID:27709982

You're a good structure, Charlie Brown: the distribution of narrative categories in comic strips.

PubMed

Cohn, Neil

2014-01-01

Cohn's (2013) theory of "Visual Narrative Grammar" argues that sequential images take on categorical roles in a narrative structure, which organizes them into hierarchic constituents analogous to the organization of syntactic categories in sentences. This theory proposes that narrative categories, like syntactic categories, can be identified through diagnostic tests that reveal tendencies for their distribution throughout a sequence. This paper describes four experiments testing these diagnostics to provide support for the validity of these narrative categories. In Experiment 1, participants reconstructed unordered panels of a comic strip into an order that makes sense. Experiment 2 measured viewing times to panels in sequences where the order of panels was reversed. In Experiment 3, participants again reconstructed strips but also deleted a panel from the sequence. Finally, in Experiment 4 participants identified where a panel had been deleted from a comic strip and rated that strip's coherence. Overall, categories had consistent distributional tendencies within experiments and complementary tendencies across experiments. These results point toward an interaction between categorical roles and a global narrative structure. © 2014 Cognitive Science Society, Inc.

Role of monomer sequence and backbone chemistry in polypeptoid copolymers for marine antifouling coatings

NASA Astrophysics Data System (ADS)

Patterson, Anastasia; Wenning, Brandon; Rizis, Georgios; Calabrese, David; Finlay, John; Franco, Sofia; Clare, Anthony; Kramer, Edward; Ober, Christopher; Segalman, Rachel

The design rules elucidated in this work suggest that antifouling coatings bearing pendant peptoid side chains perform better overall in marine fouling tests than those with peptide side chains, with extremely low attachment of N. incerta and high removal of U. linza. This difference in performance is likely due to the lack of a hydrogen bond donor in the peptoid backbone. Furthermore, we show that the bulk polymer material of these hierarchical coatings (based on PEO or PDMS) plays a key role in determining both surface presentation and fouling release performance. We demonstrate these trends utilizing a modular coating based on a triblock copolymer consisting of polystyrene and a vinyl-containing midblock, to which sequence-defined pendant oligomers (peptides or peptoids with sequences of oligo-PEO and fluoroalkyl groups) are attached via thiol-ene ``click'' chemistry. Surface presentation was analyzed with X-ray photoelectron spectroscopy and captive bubble water contact angle, and antifouling performance was evaluated with attachment and removal bioassays of the marine macroalga U. linza and diatom N. incerta. NSF GRFP and ONR PECASE.

Multiple vehicle tracking in aerial video sequence using driver behavior analysis and improved deterministic data association

NASA Astrophysics Data System (ADS)

Zhang, Xunxun; Xu, Hongke; Fang, Jianwu

2018-01-01

Along with the rapid development of the unmanned aerial vehicle technology, multiple vehicle tracking (MVT) in aerial video sequence has received widespread interest for providing the required traffic information. Due to the camera motion and complex background, MVT in aerial video sequence poses unique challenges. We propose an efficient MVT algorithm via driver behavior-based Kalman filter (DBKF) and an improved deterministic data association (IDDA) method. First, a hierarchical image registration method is put forward to compensate the camera motion. Afterward, to improve the accuracy of the state estimation, we propose the DBKF module by incorporating the driver behavior into the Kalman filter, where artificial potential field is introduced to reflect the driver behavior. Then, to implement the data association, a local optimization method is designed instead of global optimization. By introducing the adaptive operating strategy, the proposed IDDA method can also deal with the situation in which the vehicles suddenly appear or disappear. Finally, comprehensive experiments on the DARPA VIVID data set and KIT AIS data set demonstrate that the proposed algorithm can generate satisfactory and superior results.

Petri net modeling of high-order genetic systems using grammatical evolution.

PubMed

Moore, Jason H; Hahn, Lance W

2003-11-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two DNA sequence variations. In the present study, we evaluate whether the Petri net approach is capable of identifying biochemical networks that are consistent with disease susceptibility due to higher order nonlinear interactions between three DNA sequence variations. The results indicate that our model-building approach is capable of routinely identifying good, but not perfect, Petri net models. Ideas for improving the algorithm for this high-dimensional problem are presented.

Drawing the line between constituent structure and coherence relations in visual narratives.

PubMed

Cohn, Neil; Bender, Patrick

2017-02-01

Theories of visual narrative understanding have often focused on the changes in meaning across a sequence, like shifts in characters, spatial location, and causation, as cues for breaks in the structure of a discourse. In contrast, the theory of visual narrative grammar posits that hierarchic "grammatical" structures operate at the discourse level using categorical roles for images, which may or may not co-occur with shifts in coherence. We therefore examined the relationship between narrative structure and coherence shifts in the segmentation of visual narrative sequences using a "segmentation task" where participants drew lines between images in order to divide them into subepisodes. We used regressions to analyze the influence of the expected constituent structure boundary, narrative categories, and semantic coherence relationships on the segmentation of visual narrative sequences. Narrative categories were a stronger predictor of segmentation than linear coherence relationships between panels, though both influenced participants' divisions. Altogether, these results support the theory that meaningful sequential images use a narrative grammar that extends above and beyond linear semantic shifts between discourse units. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Methodological considerations of acoustic playbacks to test the behavioral significance of call directionality in male northern elephant seals (Mirounga angustirostris)

NASA Astrophysics Data System (ADS)

Holt, Marla M.; Insley, Stephen J.; Southall, Brandon L.; Schusterman, Ronald J.

2005-09-01

While attempting to gain access to receptive females, male northern elephant seals form dominance hierarchies through multiple dyadic interactions involving visual and acoustic signals. These signals are both highly stereotyped and directional. Previous behavioral observations suggested that males attend to the directional cues of these signals. We used in situ vocal playbacks to test whether males attend to directional cues of the acoustic components of a competitors calls (i.e., variation in call spectra and source levels). Here, we will focus on playback methodology. Playback calls were multiple exemplars of a marked dominant male from an isolated area, recorded with a directional microphone and DAT recorder and edited into a natural sequence that controlled call amplitude. Control calls were recordings of ambient rookery sounds with the male calls removed. Subjects were 20 marked males (10 adults and 10 subadults) all located at An~o Nuevo, CA. Playback presentations, calibrated for sound-pressure level, were broadcast at a distance of 7 m from each subject. Most responses were classified into the following categories: visual orientation, postural change, calling, movement toward or away from the loudspeaker, and re-directed aggression. We also investigated developmental, hierarchical, and ambient noise variables that were thought to influence male behavior.

Phylogenetic Analyses of Shigella and Enteroinvasive Escherichia coli for the Identification of Molecular Epidemiological Markers: Whole-Genome Comparative Analysis Does Not Support Distinct Genera Designation

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

Pettengill, Emily A.; Pettengill, James B.; Binet, Rachel

As a leading cause of bacterial dysentery, Shigella represents a significant threat to public health and food safety. Related, but often overlooked, enteroinvasive Escherichia coli (EIEC) can also cause dysentery. Current typing methods have limited ability to identify and differentiate between these pathogens despite the need for rapid and accurate identification of pathogens for clinical treatment and outbreak response. We present a comprehensive phylogeny of Shigella and EIEC using whole genome sequencing of 169 samples, constituting unparalleled strain diversity, and observe a lack of monophyly between Shigella and EIEC and among Shigella taxonomic groups. The evolutionary relationships in the phylogenymore » are supported by analyses of population structure and hierarchical clustering patterns of translated gene homolog abundance. Lastly, we identified a panel of 404 single nucleotide polymorphism (SNP) markers specific to each phylogenetic cluster for more accurate identification of Shigella and EIEC. Our findings show that Shigella and EIEC are not distinct evolutionary groups within the E. coli genus and, thus, EIEC as a group is not the ancestor to Shigella. The multiple analyses presented provide evidence for reconsidering the taxonomic placement of Shigella. The SNP markers offer more discriminatory power to molecular epidemiological typing methods involving these bacterial pathogens.« less

Phylogenetic Analyses of Shigella and Enteroinvasive Escherichia coli for the Identification of Molecular Epidemiological Markers: Whole-Genome Comparative Analysis Does Not Support Distinct Genera Designation

DOE PAGES

Pettengill, Emily A.; Pettengill, James B.; Binet, Rachel

2016-01-19

As a leading cause of bacterial dysentery, Shigella represents a significant threat to public health and food safety. Related, but often overlooked, enteroinvasive Escherichia coli (EIEC) can also cause dysentery. Current typing methods have limited ability to identify and differentiate between these pathogens despite the need for rapid and accurate identification of pathogens for clinical treatment and outbreak response. We present a comprehensive phylogeny of Shigella and EIEC using whole genome sequencing of 169 samples, constituting unparalleled strain diversity, and observe a lack of monophyly between Shigella and EIEC and among Shigella taxonomic groups. The evolutionary relationships in the phylogenymore » are supported by analyses of population structure and hierarchical clustering patterns of translated gene homolog abundance. Lastly, we identified a panel of 404 single nucleotide polymorphism (SNP) markers specific to each phylogenetic cluster for more accurate identification of Shigella and EIEC. Our findings show that Shigella and EIEC are not distinct evolutionary groups within the E. coli genus and, thus, EIEC as a group is not the ancestor to Shigella. The multiple analyses presented provide evidence for reconsidering the taxonomic placement of Shigella. The SNP markers offer more discriminatory power to molecular epidemiological typing methods involving these bacterial pathogens.« less

The synovial microenvironment of osteoarthritic joints alters RNA-seq expression profiles of human primary articular chondrocytes

PubMed Central

Lewallen, Eric A.; Bonin, Carolina A.; Li, Xin; Smith, Jay; Karperien, Marcel; Larson, A. Noelle; Lewallen, David G.; Cool, Simon M.; Westendorf, Jennifer J.; Krych, Aaron J.; Leontovich, Alexey A.; Im, Hee-Jeong; van Wijnen, Andre J.

2018-01-01

Osteoarthritis (OA) is a disabling degenerative joint disease that prompts pain with limited treatment options. To permit early diagnosis and treatment of OA, a high resolution mechanistic understanding of human chondrocytes in normal and diseased states is necessary. In this study, we assessed the biological effects of OA-related changes in the synovial microenvironment on chondrocytes embedded within anatomically intact cartilage from joints with different pathological grades by next generation RNA-sequencing (RNA-seq). We determined the transcriptome of primary articular chondrocytes derived from pristine knees and ankles, as well as from joints affected by OA. The GALAXY bioinformatics platform was used to facilitate biological interpretations. Comparisons of patient samples by k-means, hierarchical clustering and principal component analysis reveal that primary chondrocytes exhibit OA grade-related differences in gene expression, including genes involved in cell-adhesion, ECM production and immune response. We conclude that diseased synovial microenvironments in joints with different histopathological OA grades directly alter gene expression in chondrocytes. One ramification of this finding is that sampling anatomically intact cartilage from OA joints is not an ideal source of healthy chondrocytes, nor should they be used to generate a normal baseline for the molecular characterization of diseased joints. PMID:27378743

Caspase-8-mediated intracellular acidification precedes mitochondrial dysfunction in somatostatin-induced apoptosis.

PubMed

Liu, D; Martino, G; Thangaraju, M; Sharma, M; Halwani, F; Shen, S H; Patel, Y C; Srikant, C B

2000-03-31

Activation of initiator and effector caspases, mitochondrial changes involving a reduction in its membrane potential and release of cytochrome c (cyt c) into the cytosol, are characteristic features of apoptosis. These changes are associated with cell acidification in some models of apoptosis. The hierarchical relationship between these events has, however, not been deciphered. We have shown that somatostatin (SST), acting via the Src homology 2 bearing tyrosine phosphatase SHP-1, exerts cytotoxic action in MCF-7 cells, and triggers cell acidification and apoptosis. We investigated the temporal sequence of apoptotic events linking caspase activation, acidification, and mitochondrial dysfunction in this system and report here that (i) SHP-1-mediated caspase-8 activation is required for SST-induced decrease in pH(i). (ii) Effector caspases are induced only when there is concomitant acidification. (iii) Decrease in pH(i) is necessary to induce reduction in mitochondrial membrane potential, cyt c release and caspase-9 activation and (iv) depletion of ATP ablates SST-induced cyt c release and caspase-9 activation, but not its ability to induce effector caspases and apoptosis. These data reveal that SHP-1-/caspase-8-mediated acidification occurs at a site other than the mitochondrion and that SST-induced apoptosis is not dependent on disruption of mitochondrial function and caspase-9 activation.

The pangenome of the genus Clostridium.

PubMed

Udaondo, Zulema; Duque, Estrella; Ramos, Juan-Luis

2017-07-01

The pangenome for the genus Clostridium sensu stricto, which was obtained using highly curated and annotated genomes from 16 species is presented; some of these cause disease, while others are used for the production of added-value chemicals. Multilocus sequencing analysis revealed that species of this genus group into at least two clades that include non-pathogenic and pathogenic strains, suggesting that pathogenicity is dispersed across the phylogenetic tree. The core genome of the genus includes 546 protein families, which mainly comprise those involved in protein translation and DNA repair. The GS-GOGAT may represent the central pathway for generating organic nitrogen from inorganic nitrogen sources. Glycerol and glucose metabolism genes are well represented in the core genome together with a set of energy conservation systems. A metabolic network comprising proteins/enzymes, RNAs and metabolites, whose topological structure is a non-random and scale-free network with hierarchically structured modules was built. These modules shed light on the interactions between RNAs, proteins and metabolites, revealing biological features of transcription and translation, cell wall biosynthesis, C1 metabolism and N metabolism. Network analysis identified four nodes that function as hubs and bottlenecks, namely, coenzyme A, HPr kinases, S-adenosylmethionine and the ribonuclease P-protein, suggesting pivotal roles for them in Clostridium. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Biclustering as a method for RNA local multiple sequence alignment.

PubMed

Wang, Shu; Gutell, Robin R; Miranker, Daniel P

2007-12-15

Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment; precisely the kind of dual situation biclustering is intended to address. We define a representation of the MSA problem enabling the application of biclustering algorithms. We develop a computer program for local MSA, BlockMSA, that combines biclustering with divide-and-conquer. BlockMSA simultaneously finds groups of similar sequences and locally aligns subsequences within them. Further alignment is accomplished by dividing both the set of sequences and their contents. The net result is both a multiple sequence alignment and a hierarchical clustering of the sequences. BlockMSA was tested on the subsets of the BRAliBase 2.1 benchmark suite that display high variability and on an extension to that suite to larger problem sizes. Also, alignments were evaluated of two large datasets of current biological interest, T box sequences and Group IC1 Introns. The results were compared with alignments computed by ClustalW, MAFFT, MUCLE and PROBCONS alignment programs using Sum of Pairs (SPS) and Consensus Count. Results for the benchmark suite are sensitive to problem size. On problems of 15 or greater sequences, BlockMSA is consistently the best. On none of the problems in the test suite are there appreciable differences in scores among BlockMSA, MAFFT and PROBCONS. On the T box sequences, BlockMSA does the most faithful job of reproducing known annotations. MAFFT and PROBCONS do not. On the Intron sequences, BlockMSA, MAFFT and MUSCLE are comparable at identifying conserved regions. BlockMSA is implemented in Java. Source code and supplementary datasets are available at http://aug.csres.utexas.edu/msa/

A new method to improve network topological similarity search: applied to fold recognition

PubMed Central

Lhota, John; Hauptman, Ruth; Hart, Thomas; Ng, Clara; Xie, Lei

2015-01-01

Motivation: Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework—Enrichment of Network Topological Similarity (ENTS)—to improve the performance of large scale similarity searches in bioinformatics. Results: We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network. Availability and implementation: Source code freely available upon request Contact: lxie@iscb.org PMID:25717198

Identification of Sinorhizobium (Ensifer) medicae based on a specific genomic sequence unveiled by M13-PCR fingerprinting.

PubMed

Dourado, Ana Catarina; Alves, Paula I L; Tenreiro, Tania; Ferreira, Eugénio M; Tenreiro, Rogério; Fareleira, Paula; Crespo, M Teresa Barreto

2009-12-01

A collection of nodule isolates from Medicago polymorpha obtained from southern and central Portugal was evaluated by M13-PCR fingerprinting and hierarchical cluster analysis. Several genomic clusters were obtained which, by 16S rRNA gene sequencing of selected representatives, were shown to be associated with particular taxonomic groups of rhizobia and other soil bacteria. The method provided a clear separation between rhizobia and co-isolated non-symbiotic soil contaminants. Ten M13-PCR groups were assigned to Sinorhizobium (Ensifer) medicae and included all isolates responsible for the formation of nitrogen-fixing nodules upon re-inoculation of M. polymorpha test-plants. In addition, enterobacterial repetitive intergenic consensus (ERIC)-PCR fingerprinting indicated a high genomic heterogeneity within the major M13- PCR clusters of S. medicae isolates. Based on nucleotide sequence data of an M13-PCR amplicon of ca. 1500 bp, observed only in S. medicae isolates and spanning locus Smed_3707 to Smed_3709 from the pSMED01 plasmid sequence of S. medicae WSM419 genome's sequence, a pair of PCR primers was designed and used for direct PCR amplification of a 1399-bp sequence within this fragment. Additional in silico and in vitro experiments, as well as phylogenetic analysis, confirmed the specificity of this primer combination and therefore the reliability of this approach in the prompt identification of S. medicae isolates and their distinction from other soil bacteria.

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina

2007-01-01

Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300

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

PubMed

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

2016-12-01

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

Antibiotic resistance shaping multi-level population biology of bacteria

PubMed Central

Baquero, Fernando; Tedim, Ana P.; Coque, Teresa M.

2013-01-01

Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent “population biologies.” Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of “clinical” antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria. PMID:23508522

Antibiotic resistance shaping multi-level population biology of bacteria.

PubMed

Baquero, Fernando; Tedim, Ana P; Coque, Teresa M

2013-01-01

Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria.

Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics.

PubMed

Moore, Jason H; Boczko, Erik M; Summar, Marshall L

2005-02-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two or more DNA sequence variations. We review here this approach and then discuss how it can be used to model biochemical and metabolic data in the context of genetic studies of human disease susceptibility.

j5 DNA assembly design automation.

PubMed

Hillson, Nathan J

2014-01-01

Modern standardized methodologies, described in detail in the previous chapters of this book, have enabled the software-automated design of optimized DNA construction protocols. This chapter describes how to design (combinatorial) scar-less DNA assembly protocols using the web-based software j5. j5 assists biomedical and biotechnological researchers construct DNA by automating the design of optimized protocols for flanking homology sequence as well as type IIS endonuclease-mediated DNA assembly methodologies. Unlike any other software tool available today, j5 designs scar-less combinatorial DNA assembly protocols, performs a cost-benefit analysis to identify which portions of an assembly process would be less expensive to outsource to a DNA synthesis service provider, and designs hierarchical DNA assembly strategies to mitigate anticipated poor assembly junction sequence performance. Software integrated with j5 add significant value to the j5 design process through graphical user-interface enhancement and downstream liquid-handling robotic laboratory automation.

Modularity and hierarchical organization of action programs in children's acquisition of graphic skills.

PubMed

Manoel, Edison de J; Dantas, Luiz; Gimenez, Roberto; de Oliveira, Dalton Lustosa

2011-10-01

The organization of actions is based on modules in memory as a result of practice, easing the demand of performing more complex actions. If this modularization occurs, the elements of the module must remain invariant in new tasks. To test this hypothesis, 35 children, age 10 yr., practiced a graphic criterion task on a digital tablet and completed a complex graphic task enclosing the previous one. Total movement and pause times to draw the figure indicated skill acquisition. A module was identified by the variability of relative timing, pause time, and sequencing. Total movement to perform the criterion task did not increase significantly when it was embedded in the more complex task. Modularity was evidenced by the stability of relative timing and pause time and sequencing. The spatial position of new elements did not perturb the module, so the grammar of action may still have been forming.

Development and Molecular Characterization of Novel Polymorphic Genomic DNA SSR Markers in Lentinula edodes.

PubMed

Moon, Suyun; Lee, Hwa-Yong; Shim, Donghwan; Kim, Myungkil; Ka, Kang-Hyeon; Ryoo, Rhim; Ko, Han-Gyu; Koo, Chang-Duck; Chung, Jong-Wook; Ryu, Hojin

2017-06-01

Sixteen genomic DNA simple sequence repeat (SSR) markers of Lentinula edodes were developed from 205 SSR motifs present in 46.1-Mb long L. edodes genome sequences. The number of alleles ranged from 3-14 and the major allele frequency was distributed from 0.17-0.96. The values of observed and expected heterozygosity ranged from 0.00-0.76 and 0.07-0.90, respectively. The polymorphic information content value ranged from 0.07-0.89. A dendrogram, based on 16 SSR markers clustered by the paired hierarchical clustering' method, showed that 33 shiitake cultivars could be divided into three major groups and successfully identified. These SSR markers will contribute to the efficient breeding of this species by providing diversity in shiitake varieties. Furthermore, the genomic information covered by the markers can provide a valuable resource for genetic linkage map construction, molecular mapping, and marker-assisted selection in the shiitake mushroom.

Phylogeny of the owlet-nightjars (Aves: Aegothelidae) based on mitochondrial DNA sequence

USGS Publications Warehouse

Dumbacher, J.P.; Pratt, T.K.; Fleischer, R.C.

2003-01-01

The avian family Aegothelidae (Owlet-nightjars) comprises nine extant species and one extinct species, all of which are currently classified in a single genus, Aegotheles. Owlet-nightjars are secretive nocturnal birds of the South Pacific. They are relatively poorly studied and some species are known from only a few specimens. Furthermore, their confusing morphological variation has made it difficult to cluster existing specimens unambiguously into hierarchical taxonomic units. Here we sample all extant owlet-nightjar species and all but three currently recognized subspecies. We use DNA extracted primarily from museum specimens to obtain mitochondrial gene sequences and construct a molecular phylogeny. Our phylogeny suggests that most species are reciprocally monophyletic, however A. albertisi appears paraphyletic. Our data also suggest splitting A. bennettii into two species and splitting A. insignis and A. tatei as suggested in another recent paper. ?? 2003 Elsevier Science (USA). All rights reserved.

Research and Theory on Predecision Processes.

DTIC Science & Technology

1983-11-30

probl -sm detection process.........,.,......3.2 A problem detection taxonomy..*.......................,......3.6 Examples of the taxonomy gained from...large, and can be managed . A hierarchical tree structure is also necessary for distinguishing minor variations of ideas from major variations. Second...construct a scenario that involves forming a company to manufacture and market widgets. Widgets catch on, and soon every household has one, and the

Ecological Subregions: Sections and Subsections for the conterminous United States

Treesearch

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

2007-01-01

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

Supporting Semantic Annotation of Educational Content by Automatic Extraction of Hierarchical Domain Relationships

ERIC Educational Resources Information Center

Vrablecová, Petra; Šimko, Marián

2016-01-01

The domain model is an essential part of an adaptive learning system. For each educational course, it involves educational content and semantics, which is also viewed as a form of conceptual metadata about educational content. Due to the size of a domain model, manual domain model creation is a challenging and demanding task for teachers or…

Modeling Dynamic Tactical Behaviors in Combatxxi using Hierarchical Task Networks

DTIC Science & Technology

2014-06-01

concept; many aspects of HTN implementation have not been researched in depth. Work in this thesis involved development and testing of HTNs capable of...tactics. The use of HTNs within COMBATXXI is a relatively new concept; many aspects of HTN im- plementation have not been researched in depth. Work in...5 1.4 Focus of Research . . . . . . . . . . . . . . . . . . . . . . . . 6 1.5 Research Questions

Making Graphical Inferences: A Hierarchical Framework

DTIC Science & Technology

2004-08-01

from graphs is considered one of the more complex skills graph readers should possess. According to the National Council of Teachers of Mathematics ...understanding graphical perception. Human Computer Interaction, 8, 353-388. NCTM : Standards for Mathematics . (2003, 2003). Pinker, S. (1990). A theory... NCTM ) the simplest type of question involves the extraction or comparison of a few explicitly represented data points (read-offs) ( NCTM : Standards

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy

PubMed Central

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-01-01

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling. PMID:28287497

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy.

PubMed

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-03-12

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling.

Potential suicide ideation and its association with observing bullying at school.

PubMed

Rivers, Ian; Noret, Nathalie

2013-07-01

To explore those contextual factors that predict potential suicide ideation among students who observe bullying at school. 1,592 students of whom 1,009 who reported having observed bullying at school were surveyed from 14 secondary schools in the North of England. Role-related (not-involved, victim, perpetrator, 'bully-victim' and observer) and gender-wise comparisons of key variables were undertaken prior to hierarchical multiple regressions to determine those associated with potential suicide ideation. Analyses indicated that students who observed bullying behavior were significantly more likely than those not involved in bullying to report symptoms of interpersonal sensitivity, to indicate greater helplessness and potential suicide ideation. Hierarchical multiple regression analyses indicated that, among boys, helplessness (β = .48, p < .001) followed by frequency of bullying perpetration (β = .11, p < .001), and a less supportive home climate (β = -.10, p < .004) were associated with potential suicide ideation. Helplessness was found to be the only variable associated with potential suicide ideation among girls (β = .49, p < .001). Perceived helplessness is significantly associated with potential suicide ideation among students who observe bullying at school. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Interplay Between Conceptual Expectations and Movement Predictions Underlies Action Understanding.

PubMed

Ondobaka, Sasha; de Lange, Floris P; Wittmann, Marco; Frith, Chris D; Bekkering, Harold

2015-09-01

Recent accounts of understanding goal-directed action underline the importance of a hierarchical predictive architecture. However, the neural implementation of such an architecture remains elusive. In the present study, we used functional neuroimaging to quantify brain activity associated with predicting physical movements, as they were modulated by conceptual-expectations regarding the purpose of the object involved in the action. Participants observed object-related actions preceded by a cue that generated both conceptual goal expectations and movement goal predictions. In 2 tasks, observers judged whether conceptual or movement goals matched or mismatched the cue. At the conceptual level, expected goals specifically recruited the posterior cingulate cortex, irrespectively of the task and the perceived movement goal. At the movement level, neural activation of the parieto-frontal circuit, including inferior frontal gyrus and the inferior parietal lobe, reflected unpredicted movement goals. Crucially, this movement prediction error was only present when the purpose of the involved object was expected. These findings provide neural evidence that prior conceptual expectations influence processing of physical movement goals and thereby support the hierarchical predictive account of action processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Complete telomere-to-telomere de novo assembly of the Plasmodium falciparum genome through long-read (>11 kb), single molecule, real-time sequencing

PubMed Central

Vembar, Shruthi Sridhar; Seetin, Matthew; Lambert, Christine; Nattestad, Maria; Schatz, Michael C.; Baybayan, Primo; Scherf, Artur; Smith, Melissa Laird

2016-01-01

The application of next-generation sequencing to estimate genetic diversity of Plasmodium falciparum, the most lethal malaria parasite, has proved challenging due to the skewed AT-richness [∼80.6% (A + T)] of its genome and the lack of technology to assemble highly polymorphic subtelomeric regions that contain clonally variant, multigene virulence families (Ex: var and rifin). To address this, we performed amplification-free, single molecule, real-time sequencing of P. falciparum genomic DNA and generated reads of average length 12 kb, with 50% of the reads between 15.5 and 50 kb in length. Next, using the Hierarchical Genome Assembly Process, we assembled the P. falciparum genome de novo and successfully compiled all 14 nuclear chromosomes telomere-to-telomere. We also accurately resolved centromeres [∼90–99% (A + T)] and subtelomeric regions and identified large insertions and duplications that add extra var and rifin genes to the genome, along with smaller structural variants such as homopolymer tract expansions. Overall, we show that amplification-free, long-read sequencing combined with de novo assembly overcomes major challenges inherent to studying the P. falciparum genome. Indeed, this technology may not only identify the polymorphic and repetitive subtelomeric sequences of parasite populations from endemic areas but may also evaluate structural variation linked to virulence, drug resistance and disease transmission. PMID:27345719

Social Influences on Abstinence Self-Efficacy among Justice-Involved Persons

PubMed Central

Majer, John M.; Callahan, Sarah; Stevick, Kate; Jason, Leonard A.

2016-01-01

Social influences (social support for alcohol/drug use and social support for abstinence) were examined in relation to abstinence self-efficacy among a sample of 250 justice involved persons exiting inpatient treatment for substance use disorders. Hierarchical linear regression was used to examine social influences in relation to abstinence self-efficacy. Social influences were significantly related to abstinence self-efficacy when examined independently. However, only social support for alcohol/drug use was significant when both social influences were entered into the model. Findings suggest social support for alcohol/drug use compromises abstinence social support, particularly among justice involved persons who are early in their recovery from substance use disorders. PMID:27594810

PAQ: Partition Analysis of Quasispecies.

PubMed

Baccam, P; Thompson, R J; Fedrigo, O; Carpenter, S; Cornette, J L

2001-01-01

The complexities of genetic data may not be accurately described by any single analytical tool. Phylogenetic analysis is often used to study the genetic relationship among different sequences. Evolutionary models and assumptions are invoked to reconstruct trees that describe the phylogenetic relationship among sequences. Genetic databases are rapidly accumulating large amounts of sequences. Newly acquired sequences, which have not yet been characterized, may require preliminary genetic exploration in order to build models describing the evolutionary relationship among sequences. There are clustering techniques that rely less on models of evolution, and thus may provide nice exploratory tools for identifying genetic similarities. Some of the more commonly used clustering methods perform better when data can be grouped into mutually exclusive groups. Genetic data from viral quasispecies, which consist of closely related variants that differ by small changes, however, may best be partitioned by overlapping groups. We have developed an intuitive exploratory program, Partition Analysis of Quasispecies (PAQ), which utilizes a non-hierarchical technique to partition sequences that are genetically similar. PAQ was used to analyze a data set of human immunodeficiency virus type 1 (HIV-1) envelope sequences isolated from different regions of the brain and another data set consisting of the equine infectious anemia virus (EIAV) regulatory gene rev. Analysis of the HIV-1 data set by PAQ was consistent with phylogenetic analysis of the same data, and the EIAV rev variants were partitioned into two overlapping groups. PAQ provides an additional tool which can be used to glean information from genetic data and can be used in conjunction with other tools to study genetic similarities and genetic evolution of viral quasispecies.

[The structure of interaction in romantic relationships: hierarchical data analysis of inter-subjectivity between partners].

PubMed

Shimizu, Hiroshi; Daibo, Ikuo

2008-02-01

A hierarchical data analysis was conducted using data from couples to examine how self-reports of interactions between partners in romantic relationships predict the quality of the relationships. Whereas the social exchange theory has elucidated the quality of relationships from the individual level of subjectivity, this study focused on the structure of interactions between the partners (i.e., the frequency, strength, and diversity) through a process of inter-subjectivity at the couple level. A multilevel covariance structure analysis of 194 university students involved in romantic relationships revealed that the quality of relationships was mainly related to the strength and the diversity of interactions at the couple level, rather than the strength of interactions at the individual level. These results indicate that the inter-subjective process in romantic relationships may primarily explain the quality of relationships.

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

PubMed

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

2010-09-21

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