Whole Brain Functional Connectivity Pattern Homogeneity Mapping.

PubMed

Wang, Lijie; Xu, Jinping; Wang, Chao; Wang, Jiaojian

2018-01-01

Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall's coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated that FcHo is a reliable method to delineate the whole brain functional connectivity pattern similarity and may provide a new way to study the functional organization and to reveal neuropathological basis for brain disorders.

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

PubMed

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

PubMed

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

Fast targeted gene transfection and optogenetic modification of single neurons using femtosecond laser irradiation

PubMed Central

Antkowiak, Maciej; Torres-Mapa, Maria Leilani; Witts, Emily C.; Miles, Gareth B.; Dholakia, Kishan; Gunn-Moore, Frank J.

2013-01-01

A prevailing problem in neuroscience is the fast and targeted delivery of DNA into selected neurons. The development of an appropriate methodology would enable the transfection of multiple genes into the same cell or different genes into different neighboring cells as well as rapid cell selective functionalization of neurons. Here, we show that optimized femtosecond optical transfection fulfills these requirements. We also demonstrate successful optical transfection of channelrhodopsin-2 in single selected neurons. We extend the functionality of this technique for wider uptake by neuroscientists by using fast three-dimensional laser beam steering enabling an image-guided “point-and-transfect” user-friendly transfection of selected cells. A sub-second transfection timescale per cell makes this method more rapid by at least two orders of magnitude when compared to alternative single-cell transfection techniques. This novel technology provides the ability to carry out large-scale cell selective genetic studies on neuronal ensembles and perform rapid genetic programming of neural circuits. PMID:24257461

Fast targeted gene transfection and optogenetic modification of single neurons using femtosecond laser irradiation.

PubMed

Antkowiak, Maciej; Torres-Mapa, Maria Leilani; Witts, Emily C; Miles, Gareth B; Dholakia, Kishan; Gunn-Moore, Frank J

2013-11-21

A prevailing problem in neuroscience is the fast and targeted delivery of DNA into selected neurons. The development of an appropriate methodology would enable the transfection of multiple genes into the same cell or different genes into different neighboring cells as well as rapid cell selective functionalization of neurons. Here, we show that optimized femtosecond optical transfection fulfills these requirements. We also demonstrate successful optical transfection of channelrhodopsin-2 in single selected neurons. We extend the functionality of this technique for wider uptake by neuroscientists by using fast three-dimensional laser beam steering enabling an image-guided "point-and-transfect" user-friendly transfection of selected cells. A sub-second transfection timescale per cell makes this method more rapid by at least two orders of magnitude when compared to alternative single-cell transfection techniques. This novel technology provides the ability to carry out large-scale cell selective genetic studies on neuronal ensembles and perform rapid genetic programming of neural circuits.

On the consistency between nearest-neighbor peridynamic discretizations and discretized classical elasticity models

DOE PAGES

Seleson, Pablo; Du, Qiang; Parks, Michael L.

2016-08-16

The peridynamic theory of solid mechanics is a nonlocal reformulation of the classical continuum mechanics theory. At the continuum level, it has been demonstrated that classical (local) elasticity is a special case of peridynamics. Such a connection between these theories has not been extensively explored at the discrete level. This paper investigates the consistency between nearest-neighbor discretizations of linear elastic peridynamic models and finite difference discretizations of the Navier–Cauchy equation of classical elasticity. While nearest-neighbor discretizations in peridynamics have been numerically observed to present grid-dependent crack paths or spurious microcracks, this paper focuses on a different, analytical aspect of suchmore » discretizations. We demonstrate that, even in the absence of cracks, such discretizations may be problematic unless a proper selection of weights is used. Specifically, we demonstrate that using the standard meshfree approach in peridynamics, nearest-neighbor discretizations do not reduce, in general, to discretizations of corresponding classical models. We study nodal-based quadratures for the discretization of peridynamic models, and we derive quadrature weights that result in consistency between nearest-neighbor discretizations of peridynamic models and discretized classical models. The quadrature weights that lead to such consistency are, however, model-/discretization-dependent. We motivate the choice of those quadrature weights through a quadratic approximation of displacement fields. The stability of nearest-neighbor peridynamic schemes is demonstrated through a Fourier mode analysis. Finally, an approach based on a normalization of peridynamic constitutive constants at the discrete level is explored. This approach results in the desired consistency for one-dimensional models, but does not work in higher dimensions. The results of the work presented in this paper suggest that even though nearest-neighbor discretizations should be avoided in peridynamic simulations involving cracks, such discretizations are viable, for example for verification or validation purposes, in problems characterized by smooth deformations. Furthermore, we demonstrate that better quadrature rules in peridynamics can be obtained based on the functional form of solutions.« less

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Con-nectin axons and dendrites.

PubMed

Beaudoin, Gerard M J

2006-07-03

Unlike adherens junctions, synapses are asymmetric connections, usually between axons and dendrites, that rely on various cell adhesion molecules for structural stability and function. Two cell types of adhesion molecules found at adherens junctions, cadherins and nectins, are thought to mediate homophilic interaction between neighboring cells. In this issue, Togashi et al. (see p. 141) demonstrate that the differential localization of two heterophilic interacting nectins mediates the selective attraction of axons and dendrites in cooperation with cadherins.

Automating the Transformational Development of Software. Volume 1.

DTIC Science & Technology

1983-03-01

DRACO system [Neighbors 80] uses meta-rules to derive information about which new transformations will be applicable after a particular transformation has...transformation over another. The new model, as Incorporated in a system called Glitter, explicitly represents transformation goals, methods, and selection...done anew for each new problem (compare this with Neighbor’s Draco system [Neighbors 80] which attempts to reuse domain analysis). o Is the user

AVNM: A Voting based Novel Mathematical Rule for Image Classification.

PubMed

Vidyarthi, Ankit; Mittal, Namita

2016-12-01

In machine learning, the accuracy of the system depends upon classification result. Classification accuracy plays an imperative role in various domains. Non-parametric classifier like K-Nearest Neighbor (KNN) is the most widely used classifier for pattern analysis. Besides its easiness, simplicity and effectiveness characteristics, the main problem associated with KNN classifier is the selection of a number of nearest neighbors i.e. "k" for computation. At present, it is hard to find the optimal value of "k" using any statistical algorithm, which gives perfect accuracy in terms of low misclassification error rate. Motivated by the prescribed problem, a new sample space reduction weighted voting mathematical rule (AVNM) is proposed for classification in machine learning. The proposed AVNM rule is also non-parametric in nature like KNN. AVNM uses the weighted voting mechanism with sample space reduction to learn and examine the predicted class label for unidentified sample. AVNM is free from any initial selection of predefined variable and neighbor selection as found in KNN algorithm. The proposed classifier also reduces the effect of outliers. To verify the performance of the proposed AVNM classifier, experiments are made on 10 standard datasets taken from UCI database and one manually created dataset. The experimental result shows that the proposed AVNM rule outperforms the KNN classifier and its variants. Experimentation results based on confusion matrix accuracy parameter proves higher accuracy value with AVNM rule. The proposed AVNM rule is based on sample space reduction mechanism for identification of an optimal number of nearest neighbor selections. AVNM results in better classification accuracy and minimum error rate as compared with the state-of-art algorithm, KNN, and its variants. The proposed rule automates the selection of nearest neighbor selection and improves classification rate for UCI dataset and manually created dataset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Regulation of the Host Antiviral State by Intercellular Communications

PubMed Central

Assil, Sonia; Webster, Brian; Dreux, Marlène

2015-01-01

Viruses usually induce a profound remodeling of host cells, including the usurpation of host machinery to support their replication and production of virions to invade new cells. Nonetheless, recognition of viruses by the host often triggers innate immune signaling, preventing viral spread and modulating the function of immune cells. It conventionally occurs through production of antiviral factors and cytokines by infected cells. Virtually all viruses have evolved mechanisms to blunt such responses. Importantly, it is becoming increasingly recognized that infected cells also transmit signals to regulate innate immunity in uninfected neighboring cells. These alternative pathways are notably mediated by vesicular secretion of various virus- and host-derived products (miRNAs, RNAs, and proteins) and non-infectious viral particles. In this review, we focus on these newly-described modes of cell-to-cell communications and their impact on neighboring cell functions. The reception of these signals can have anti- and pro-viral impacts, as well as more complex effects in the host such as oncogenesis and inflammation. Therefore, these “broadcasting” functions, which might be tuned by an arms race involving selective evolution driven by either the host or the virus, constitute novel and original regulations of viral infection, either highly localized or systemic. PMID:26295405

Molecular engineering and measurements to test hypothesized mechanisms in single molecule conductance switching.

PubMed

Moore, Amanda M; Dameron, Arrelaine A; Mantooth, Brent A; Smith, Rachel K; Fuchs, Daniel J; Ciszek, Jacob W; Maya, Francisco; Yao, Yuxing; Tour, James M; Weiss, Paul S

2006-02-15

Six customized phenylene-ethynylene-based oligomers have been studied for their electronic properties using scanning tunneling microscopy to test hypothesized mechanisms of stochastic conductance switching. Previously suggested mechanisms include functional group reduction, functional group rotation, backbone ring rotation, neighboring molecule interactions, bond fluctuations, and hybridization changes. Here, we test these hypotheses experimentally by varying the molecular designs of the switches; the ability of the molecules to switch via each hypothetical mechanism is selectively engineered into or out of each molecule. We conclude that hybridization changes at the molecule-surface interface are responsible for the switching we observe.

Identifying influential neighbors in animal flocking

PubMed Central

Jiang, Li; Giuggioli, Luca; Escobedo, Ramón; Sire, Clément; Han, Zhangang

2017-01-01

Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors. PMID:29161269

nth-Nearest-neighbor distribution functions of an interacting fluid from the pair correlation function: a hierarchical approach.

PubMed

Bhattacharjee, Biplab

2003-04-01

The paper presents a general formalism for the nth-nearest-neighbor distribution (NND) of identical interacting particles in a fluid confined in a nu-dimensional space. The nth-NND functions, W(n,r) (for n=1,2,3, em leader) in a fluid are obtained hierarchically in terms of the pair correlation function and W(n-1,r) alone. The radial distribution function (RDF) profiles obtained from the molecular dynamics (MD) simulation of Lennard-Jones (LJ) fluid is used to illustrate the results. It is demonstrated that the collective structural information contained in the maxima and minima of the RDF profiles being resolved in terms of individual NND functions may provide more insights about the microscopic neighborhood structure around a reference particle in a fluid. Representative comparison between the results obtained from the formalism and the MD simulation data shows good agreement. Apart from the quantities such as nth-NND functions and nth-nearest-neighbor distances, the average neighbor population number is defined. These quantities are evaluated for the LJ model system and interesting density dependence of the microscopic neighborhood shell structures are discussed in terms of them. The relevance of the NND functions in various phenomena is also pointed out.

nth-nearest-neighbor distribution functions of an interacting fluid from the pair correlation function: A hierarchical approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, Biplab

2003-04-01

The paper presents a general formalism for the nth-nearest-neighbor distribution (NND) of identical interacting particles in a fluid confined in a ν-dimensional space. The nth-NND functions, W(n,r¯) (for n=1,2,3,…) in a fluid are obtained hierarchically in terms of the pair correlation function and W(n-1,r¯) alone. The radial distribution function (RDF) profiles obtained from the molecular dynamics (MD) simulation of Lennard-Jones (LJ) fluid is used to illustrate the results. It is demonstrated that the collective structural information contained in the maxima and minima of the RDF profiles being resolved in terms of individual NND functions may provide more insights about the microscopic neighborhood structure around a reference particle in a fluid. Representative comparison between the results obtained from the formalism and the MD simulation data shows good agreement. Apart from the quantities such as nth-NND functions and nth-nearest-neighbor distances, the average neighbor population number is defined. These quantities are evaluated for the LJ model system and interesting density dependence of the microscopic neighborhood shell structures are discussed in terms of them. The relevance of the NND functions in various phenomena is also pointed out.

Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection.

PubMed

Zhu, Xiaofeng; Li, Xuelong; Zhang, Shichao; Ju, Chunhua; Wu, Xindong

2017-06-01

In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate their new representations, by proposing a novel joint graph sparse coding (JGSC) model. In JGSC, we first formulate its objective function by simultaneously taking subspace learning and joint sparse regression into account, then, design a new optimization solution to solve the resulting objective function, and further prove the convergence of the proposed solution. Furthermore, we extend JGSC to a robust JGSC (RJGSC) via replacing the least square loss function with a robust loss function, for achieving the same goals and also avoiding the impact of outliers. Finally, experimental results on real data sets showed that both JGSC and RJGSC outperformed the state-of-the-art algorithms in terms of k -nearest neighbor classification performance.

Preferential selection based on degree difference in the spatial prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Huang, Changwei; Dai, Qionglin; Cheng, Hongyan; Li, Haihong

2017-10-01

Strategy evolution in spatial evolutionary games is generally implemented through imitation processes between individuals. In most previous studies, it is assumed that individuals pick up one of their neighbors randomly to learn from. However, by considering the heterogeneity of individuals' influence in the real society, preferential selection is more realistic. Here, we introduce a preferential selection mechanism based on degree difference into spatial prisoner's dilemma games on Erdös-Rényi networks and Barabási-Albert scale-free networks and investigate the effects of the preferential selection on cooperation. The results show that, when the individuals prefer to choose the neighbors who have small degree difference with themselves to imitate, cooperation is hurt by the preferential selection. In contrast, when the individuals prefer to choose those large degree difference neighbors to learn from, there exists optimal preference strength resulting in the maximal cooperation level no matter what the network structure is. In addition, we investigate the robustness of the results against variations of the noise, the average degree and the size of network in the model, and find that the qualitative features of the results are unchanged.

Reasoning about Complex Networks: A Logic Programming Approach

DTIC Science & Technology

2013-01-01

of influence exerted on a node by its neighbors is specified by an influence function , whose precise effects will be described later on when we...discuss the semantics. As a result, a rule consists of four major parts: (i) an influence function , (ii) neighbor criteria, (iii) target criteria, and (iv...Definition 2.6 ( Influence Function ) An influence function is a function ifl : N×N→ [0, 1]× [0, 1] that satisfies the following two axioms: 1. ifl

Evidence for cultural differences between neighboring chimpanzee communities.

PubMed

Luncz, Lydia V; Mundry, Roger; Boesch, Christophe

2012-05-22

The majority of evidence for cultural behavior in animals has come from comparisons between populations separated by large geographical distances that often inhabit different environments. The difficulty of excluding ecological and genetic variation as potential explanations for observed behaviors has led some researchers to challenge the idea of animal culture. Chimpanzees (Pan troglodytes verus) in the Taï National Park, Côte d'Ivoire, crack Coula edulis nuts using stone and wooden hammers and tree root anvils. In this study, we compare for the first time hammer selection for nut cracking across three neighboring chimpanzee communities that live in the same forest habitat, which reduces the likelihood of ecological variation. Furthermore, the study communities experience frequent dispersal of females at maturity, which eliminates significant genetic variation. We compared key ecological factors, such as hammer availability and nut hardness, between the three neighboring communities and found striking differences in group-specific hammer selection among communities despite similar ecological conditions. Differences were found in the selection of hammer material and hammer size in response to changes in nut resistance over time. Our findings highlight the subtleties of cultural differences in wild chimpanzees and illustrate how cultural knowledge is able to shape behavior, creating differences among neighboring social groups. Copyright © 2012 Elsevier Ltd. All rights reserved.

A 10-Year Follow-Up Study of Social Ties and Functional Health among the Old: The AGES Project

PubMed Central

Murata, Chiyoe; Saito, Tami; Tsuji, Taishi; Saito, Masashige

2017-01-01

In Asian nations, family ties are considered important. However, it is not clear what happens among older people with no such ties. To investigate the association, we used longitudinal data from the Aichi Gerontological Evaluation Study (AGES) project. Functionally independent older people at baseline (N = 14,088) in 10 municipalities were followed from 2003 to 2013. Social ties were assessed by asking about their social support exchange with family, relatives, friends, or neighbors. Cox proportional hazard models were employed to investigate the association between social ties and the onset of functional disability adjusting for age, health status, and living arrangement. We found that social ties with co-residing family members, and those with friends or neighbors, independently protected functional health with hazard ratios of 0.81 and 0.85 among men. Among women, ties with friend or neighbors had a stronger effect on health compared to their male counterparts with a hazard ratio of 0.89. The fact that social ties with friends or neighbors are associated with a lower risk of functional decline, independent of family support, serves to underscore the importance of promoting social ties, especially among those lacking family ties. PMID:28671627

Misregistration in Adaptive Optics Systems

DTIC Science & Technology

2009-03-01

introduces a new factor called the influence function , or the amount of slope that is introduced in neighboring subapertures by pushing one actuator...nearest neighbor is unity. The actuator influence function Akl, is the phase caused by poking an individual actuator. It is assumed that Akl = 1 at the...The square bracket indicates actua- tor indices, and the round brackets are subaperture indices. 28 influence function is given by A(x, y

Local biotic adaptation of trees and shrubs to plant neighbors

USGS Publications Warehouse

Grady, Kevin C.; Wood, Troy E.; Kolb, Thomas E.; Hersch-Green, Erika; Shuster, Stephen M.; Gehring, Catherine A.; Hart, Stephen C.; Allan, Gerard J.; Whitham, Thomas G.

2017-01-01

Natural selection as a result of plant–plant interactions can lead to local biotic adaptation. This may occur where species frequently interact and compete intensely for resources limiting growth, survival, and reproduction. Selection is demonstrated by comparing a genotype interacting with con- or hetero-specific sympatric neighbor genotypes with a shared site-level history (derived from the same source location), to the same genotype interacting with foreign neighbor genotypes (from different sources). Better genotype performance in sympatric than allopatric neighborhoods provides evidence of local biotic adaptation. This pattern might be explained by selection to avoid competition by shifting resource niches (differentiation) or by interactions benefitting one or more members (facilitation). We tested for local biotic adaptation among two riparian trees, Populus fremontii and Salix gooddingii, and the shrub Salix exigua by transplanting replicated genotypes from multiple source locations to a 17 000 tree common garden with sympatric and allopatric treatments along the Colorado River in California. Three major patterns were observed: 1) across species, 62 of 88 genotypes grew faster with sympatric neighbors than allopatric neighbors; 2) these growth rates, on an individual tree basis, were 44, 15 and 33% higher in sympatric than allopatric treatments for P. fremontii, S. exigua and S. gooddingii, respectively, and; 3) survivorship was higher in sympatric treatments for P. fremontiiand S. exigua. These results support the view that fitness of foundation species supporting diverse communities and dominating ecosystem processes is determined by adaptive interactions among multiple plant species with the outcome that performance depends on the genetic identity of plant neighbors. The occurrence of evolution in a plant-community context for trees and shrubs builds on ecological evolutionary research that has demonstrated co-evolution among herbaceous taxa, and evolution of native species during exotic plants invasion, and taken together, refutes the concept that plant communities are always random associations.

Distinct Effects of Lexical and Semantic Competition during Picture Naming in Younger Adults, Older Adults, and People with Aphasia

PubMed Central

Britt, Allison E.; Ferrara, Casey; Mirman, Daniel

2016-01-01

Producing a word requires selecting among a set of similar alternatives. When many semantically related items become activated, the difficulty of the selection process is increased. Experiment 1 tested naming of items with either multiple synonymous labels (“Alternate Names,” e.g., gift/present) or closely semantically related but non-equivalent responses (“Near Semantic Neighbors,” e.g., jam/jelly). Picture naming was fastest and most accurate for pictures with only one label (“High Name Agreement”), slower and less accurate in the Alternate Names condition, and slowest and least accurate in the Near Semantic Neighbors condition. These results suggest that selection mechanisms in picture naming operate at two distinct levels of processing: selecting between similar but non-equivalent names requires two selection processes (semantic and lexical), whereas selecting among equivalent names only requires one selection at the lexical level. Experiment 2 examined how these selection mechanisms are affected by normal aging and found that older adults had significantly more difficulty in the Near Semantic Neighbors condition, but not in the Alternate Names condition. This suggests that aging affects semantic processing and selection more strongly than it affects lexical selection. Experiment 3 examined the role of the left inferior frontal gyrus (LIFG) in these selection processes by testing individuals with aphasia secondary to stroke lesions that either affected the LIFG or spared it. Surprisingly, there was no interaction between condition and lesion group: the presence of LIFG damage was not associated with substantively worse naming performance for pictures with multiple acceptable labels. These results are not consistent with a simple view of LIFG as the locus of lexical selection and suggest a more nuanced view of the neural basis of lexical and semantic selection. PMID:27458393

A Parallel Ghosting Algorithm for The Flexible Distributed Mesh Database

DOE PAGES

Mubarak, Misbah; Seol, Seegyoung; Lu, Qiukai; ...

2013-01-01

Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in amore » 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can create n number of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.« less

Distribution of Steps with Finite-Range Interactions: Analytic Approximations and Numerical Results

NASA Astrophysics Data System (ADS)

GonzáLez, Diego Luis; Jaramillo, Diego Felipe; TéLlez, Gabriel; Einstein, T. L.

2013-03-01

While most Monte Carlo simulations assume only nearest-neighbor steps interact elastically, most analytic frameworks (especially the generalized Wigner distribution) posit that each step elastically repels all others. In addition to the elastic repulsions, we allow for possible surface-state-mediated interactions. We investigate analytically and numerically how next-nearest neighbor (NNN) interactions and, more generally, interactions out to q'th nearest neighbor alter the form of the terrace-width distribution and of pair correlation functions (i.e. the sum over n'th neighbor distribution functions, which we investigated recently.[2] For physically plausible interactions, we find modest changes when NNN interactions are included and generally negligible changes when more distant interactions are allowed. We discuss methods for extracting from simulated experimental data the characteristic scale-setting terms in assumed potential forms.

Generating a Simulated Fluid Flow over a Surface Using Anisotropic Diffusion

NASA Technical Reports Server (NTRS)

Rodriguez, David L. (Inventor); Sturdza, Peter (Inventor)

2016-01-01

A fluid-flow simulation over a computer-generated surface is generated using a diffusion technique. The surface is comprised of a surface mesh of polygons. A boundary-layer fluid property is obtained for a subset of the polygons of the surface mesh. A gradient vector is determined for a selected polygon, the selected polygon belonging to the surface mesh but not one of the subset of polygons. A maximum and minimum diffusion rate is determined along directions determined using the gradient vector corresponding to the selected polygon. A diffusion-path vector is defined between a point in the selected polygon and a neighboring point in a neighboring polygon. An updated fluid property is determined for the selected polygon using a variable diffusion rate, the variable diffusion rate based on the minimum diffusion rate, maximum diffusion rate, and the gradient vector.

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

Formulation/preparation of functionalized nanoparticles for in vivo targeted drug delivery.

PubMed

Gu, Frank; Langer, Robert; Farokhzad, Omid C

2009-01-01

Targeted cancer therapy allows the delivery of therapeutic agents to cancer cells without incurring undesirable side effects on the neighboring healthy tissues. Over the past decade, there has been an increasing interest in the development of advanced cancer therapeutics using targeted nanoparticles. Here we describe the preparation of drug-encapsulated nanoparticles formulated with biocompatible and biodegradable poly(D: ,L: -lactic-co-glycolic acid)-block-poly(ethylene glycol) (PLGA-b-PEG) copolymer and surface functionalized with the A10 2-fluoropyrimidine ribonucleic acid aptamers that recognize the extracellular domain of prostate-specific membrane antigen (PSMA), a well-characterized antigen expressed on the surface of prostate cancer cells. We show that the self-assembled nanoparticles can selectively bind to PSMA-targeted prostate cancer cells in vitro and in vivo. This formulation method may contribute to the development of highly selective and effective cancer therapeutic and diagnostic devices.

Estimating forest attribute parameters for small areas using nearest neighbors techniques

Treesearch

Ronald E. McRoberts

2012-01-01

Nearest neighbors techniques have become extremely popular, particularly for use with forest inventory data. With these techniques, a population unit prediction is calculated as a linear combination of observations for a selected number of population units in a sample that are most similar, or nearest, in a space of ancillary variables to the population unit requiring...

Minimum Expected Risk Estimation for Near-neighbor Classification

DTIC Science & Technology

2006-04-01

We consider the problems of class probability estimation and classification when using near-neighbor classifiers, such as k-nearest neighbors ( kNN ...estimate for weighted kNN classifiers with different prior information, for a broad class of risk functions. Theory and simulations show how significant...the difference is compared to the standard maximum likelihood weighted kNN estimates. Comparisons are made with uniform weights, symmetric weights

Spatial correlations between browsing on balsam fir by white-tailed deer and the nutritional value of neighboring winter forage.

PubMed

Champagne, Emilie; Moore, Ben D; Côté, Steeve D; Tremblay, Jean-Pierre

2018-03-01

Associational effects, that is, the influence of neighboring plants on herbivory suffered by a plant, are an outcome of forage selection. Although forage selection is a hierarchical process, few studies have investigated associational effects at multiple spatial scales. Because the nutritional quality of plants can be spatially structured, it might differently influence associational effects across multiple scales. Our objective was to determine the radius of influence of neighbor density and nutritional quality on balsam fir ( Abies balsamea ) herbivory by white-tailed deer ( Odocoileus virginianus ) in winter. We quantified browsing rates on fir and the density and quality of neighboring trees in a series of 10-year-old cutovers on Anticosti Island (Canada). We used cross-correlations to investigate relationships between browsing rates and the density and nutritional quality of neighboring trees at distances up to 1,000 m. Balsam fir and white spruce ( Picea glauca ) fiber content and dry matter in vitro true digestibility were correlated with fir browsing rate at the finest extra-patch scale (across distance of up to 50 m) and between cutover areas (300-400 m). These correlations suggest associational effects, that is, low nutritional quality of neighbors reduces the likelihood of fir herbivory (associational defense). Our results may indicate associational effects mediated by intraspecific variation in plant quality and suggest that these effects could occur at scales from tens to hundreds of meters. Understanding associational effects could inform strategies for restoration or conservation; for example, planting of fir among existing natural regeneration could be concentrated in areas of low nutritional quality.

Complement-Related Regulates Autophagy in Neighboring Cells.

PubMed

Lin, Lin; Rodrigues, Frederico S L M; Kary, Christina; Contet, Alicia; Logan, Mary; Baxter, Richard H G; Wood, Will; Baehrecke, Eric H

2017-06-29

Autophagy degrades cytoplasmic components and is important for development and human health. Although autophagy is known to be influenced by systemic intercellular signals, the proteins that control autophagy are largely thought to function within individual cells. Here, we report that Drosophila macroglobulin complement-related (Mcr), a complement ortholog, plays an essential role during developmental cell death and inflammation by influencing autophagy in neighboring cells. This function of Mcr involves the immune receptor Draper, suggesting a relationship between autophagy and the control of inflammation. Interestingly, Mcr function in epithelial cells is required for macrophage autophagy and migration to epithelial wounds, a Draper-dependent process. This study reveals, unexpectedly, that complement-related from one cell regulates autophagy in neighboring cells via an ancient immune signaling program. Copyright © 2017 Elsevier Inc. All rights reserved.

Extending the accuracy of the SNAP interatomic potential form

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

Wood, Mitchell A.; Thompson, Aidan P.

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

Extending the accuracy of the SNAP interatomic potential form

DOE PAGES

Wood, Mitchell A.; Thompson, Aidan P.

2018-03-28

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

The structure of ribosome-lankacidin complex reveals ribosomal sites for synergistic antibiotics

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

Auerbach, Tamar; Mermershtain, Inbal; Davidovich, Chen

2010-04-26

Crystallographic analysis revealed that the 17-member polyketide antibiotic lankacidin produced by Streptomyces rochei binds at the peptidyl transferase center of the eubacterial large ribosomal subunit. Biochemical and functional studies verified this finding and showed interference with peptide bond formation. Chemical probing indicated that the macrolide lankamycin, a second antibiotic produced by the same species, binds at a neighboring site, at the ribosome exit tunnel. These two antibiotics can bind to the ribosome simultaneously and display synergy in inhibiting bacterial growth. The binding site of lankacidin and lankamycin partially overlap with the binding site of another pair of synergistic antibiotics, themore » streptogramins. Thus, at least two pairs of structurally dissimilar compounds have been selected in the course of evolution to act synergistically by targeting neighboring sites in the ribosome. These results underscore the importance of the corresponding ribosomal sites for development of clinically relevant synergistic antibiotics and demonstrate the utility of structural analysis for providing new directions for drug discovery.« less

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

PubMed

Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms

PubMed Central

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; Yin, Hang; Crowley, Michael F.; Bomble, Yannick J.

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions. PMID:26741367

Improving RNA nearest neighbor parameters for helices by going beyond the two-state model.

PubMed

Spasic, Aleksandar; Berger, Kyle D; Chen, Jonathan L; Seetin, Matthew G; Turner, Douglas H; Mathews, David H

2018-06-01

RNA folding free energy change nearest neighbor parameters are widely used to predict folding stabilities of secondary structures. They were determined by linear regression to datasets of optical melting experiments on small model systems. Traditionally, the optical melting experiments are analyzed assuming a two-state model, i.e. a structure is either complete or denatured. Experimental evidence, however, shows that structures exist in an ensemble of conformations. Partition functions calculated with existing nearest neighbor parameters predict that secondary structures can be partially denatured, which also directly conflicts with the two-state model. Here, a new approach for determining RNA nearest neighbor parameters is presented. Available optical melting data for 34 Watson-Crick helices were fit directly to a partition function model that allows an ensemble of conformations. Fitting parameters were the enthalpy and entropy changes for helix initiation, terminal AU pairs, stacks of Watson-Crick pairs and disordered internal loops. The resulting set of nearest neighbor parameters shows a 38.5% improvement in the sum of residuals in fitting the experimental melting curves compared to the current literature set.

Human Impairment from Living near Confined Animal (Hog) Feeding Operations

PubMed Central

Kilburn, Kaye H.

2012-01-01

Problem. To determine whether neighbors around manure lagoons and massive hog confinement buildings who complained of offensive odors and symptoms had impaired brain and lung functions. Method. We compared near hog manure neighbors of lagoons to people living beyond 3 kilometers in Ohio and to unexposed people controls in a nearby state for neurophysiological, cognitive, recall and memory functions, and pulmonary performance. Results. The 25 exposed subjects averaged 4.3 neurobehavioral abnormalities, significantly different from 2.5 for local controls and 2.3 for Tennessee controls. Exposed subjects mean forced vital capacity and expiratory volume in 1 sec were reduced significantly compared to local and regional controls. Conclusions. Near neighbors of hog enclosures and manure lagoon gases had impaired neurobehavioral functions and pulmonary functions and these effects extended to nearby people thought to be controls. Hydrogen sulfide must be abated because people living near lagoons cannot avoid rotten egg gas. PMID:22496706

The Reconstruction Problem Revisited

NASA Technical Reports Server (NTRS)

Suresh, Ambaby

1999-01-01

The role of reconstruction in avoiding oscillations in upwind schemes is reexamined, with the aim of providing simple, concise proofs. In one dimension, it is shown that if the reconstruction is any arbitrary function bounded by neighboring cell averages and increasing within a cell for increasing data, the resulting scheme is monotonicity preserving, even though the reconstructed function may have overshoots and undershoots at the cell edges and is in general not a monotone function. In the special case of linear reconstruction, it is shown that merely bounding the reconstruction between neighboring cell averages is sufficient to obtain a monotonicity preservinc,y scheme. In two dimensions, it is shown that some ID TVD limiters applied in each direction result in schemes that are not positivity preserving, i.e. do not give positive updates when the data are positive. A simple proof is given to show that if the reconstruction inside the cell is bounded by the neighboring cell averages (including corner neighbors), then the scheme is positivity preserving. A new limiter that enforces this condition but is not as dissipative as the Minmod limiter is also presented.

Signal interactions and interference in insect choruses: singing and listening in the social environment.

PubMed

Greenfield, Michael D

2015-01-01

Acoustic insects usually sing amidst conspecifics, thereby creating a social environment-the chorus-in which individuals communicate, find mates, and avoid predation. A temporal structure may arise in a chorus because of competitive and cooperative factors that favor certain signal interactions between neighbors. This temporal structure can generate significant acoustic interference among singers that pose problems for communication, mate finding, and predator detection. Acoustic insects can reduce interference by means of selective attention to only their nearest neighbors and by alternating calls with neighbors. Alternatively, they may synchronize, allowing them to preserve call rhythm and also to listen for predators during the silent intervals between calls. Moreover, males singing in choruses may benefit from reduced per capita predation risk as well as enhanced vigilance. They may also enjoy greater per capita attractiveness to females, particularly in the case of synchronous choruses. In many cases, however, the overall temporal structure of the chorus is only an emergent property of simple, pairwise interactions between neighbors. Nonetheless, the chorus that emerges can impose significant selection pressure on the singing of those individual males. Thus, feedback loops may occur and potentially influence traits at both individual and group levels in a chorus.

Generating a Simulated Fluid Flow Over an Aircraft Surface Using Anisotropic Diffusion

NASA Technical Reports Server (NTRS)

Rodriguez, David L. (Inventor); Sturdza, Peter (Inventor)

2013-01-01

A fluid-flow simulation over a computer-generated aircraft surface is generated using a diffusion technique. The surface is comprised of a surface mesh of polygons. A boundary-layer fluid property is obtained for a subset of the polygons of the surface mesh. A pressure-gradient vector is determined for a selected polygon, the selected polygon belonging to the surface mesh but not one of the subset of polygons. A maximum and minimum diffusion rate is determined along directions determined using a pressure gradient vector corresponding to the selected polygon. A diffusion-path vector is defined between a point in the selected polygon and a neighboring point in a neighboring polygon. An updated fluid property is determined for the selected polygon using a variable diffusion rate, the variable diffusion rate based on the minimum diffusion rate, maximum diffusion rate, and angular difference between the diffusion-path vector and the pressure-gradient vector.

A traveling salesman approach for predicting protein functions.

PubMed

Johnson, Olin; Liu, Jing

2006-10-12

Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm 1 on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems.

A traveling salesman approach for predicting protein functions

PubMed Central

Johnson, Olin; Liu, Jing

2006-01-01

Background Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Results Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm [1] on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Conclusion Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems. PMID:17147783

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

PubMed Central

Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

2009-01-01

Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

Functionally dissimilar neighbors accelerate litter decomposition in two grass species.

PubMed

Barbe, Lou; Jung, Vincent; Prinzing, Andreas; Bittebiere, Anne-Kristel; Butenschoen, Olaf; Mony, Cendrine

2017-05-01

Plant litter decomposition is a key regulator of nutrient recycling. In a given environment, decomposition of litter from a focal species depends on its litter quality and on the efficiency of local decomposers. Both may be strongly modified by functional traits of neighboring species, but the consequences for decomposition of litter from the focal species remain unknown. We tested whether decomposition of a focal plant's litter is influenced by the functional-trait dissimilarity to the neighboring plants. We cultivated two grass species (Brachypodium pinnatum and Elytrigia repens) in experimental mesocosms with functionally similar and dissimilar neighborhoods, and reciprocally transplanted litter. For both species, litter quality increased in functionally dissimilar neighborhoods, partly as a result of changes in functional traits involved in plant-plant interactions. Furthermore, functional dissimilarity increased overall decomposer efficiency in one species, probably via complementarity effects. Our results suggest a novel mechanism of biodiversity effects on ecosystem functioning in grasslands: interspecific functional diversity within plant communities can enhance intraspecific contributions to litter decomposition. Thus, plant species might better perform in diverse communities by benefiting from higher remineralization rates of their own litter. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

A Discovery Process for Initializing Ad Hoc Underwater Acoustic Networks

DTIC Science & Technology

2008-12-01

the ping utility packet is set to global address 0, its function becomes a broadcast ping and it elicits echoes from all neighboring nodes within...destination. At the Seaweb server, a global neighbor table and a global routing table are maintained to support network configurability. 2. Cellular...aggregates the received peer discovery data in a global neighbor table and ultimately decides how routing to each branch node should be configured

Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Liu, Yuanming; Huang, Changwei; Dai, Qionglin

2018-06-01

Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

Unique Thermal Stability of Unnatural Hydrophobic Ds Bases in Double-Stranded DNAs.

PubMed

Kimoto, Michiko; Hirao, Ichiro

2017-10-20

Genetic alphabet expansion technology, the introduction of unnatural bases or base pairs into replicable DNA, has rapidly advanced as a new synthetic biology area. A hydrophobic unnatural base pair between 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds) and 2-nitro-4-propynylpyrrole (Px) exhibited high fidelity as a third base pair in PCR. SELEX methods using the Ds-Px pair enabled high-affinity DNA aptamer generation, and introducing a few Ds bases into DNA aptamers extremely augmented their affinities and selectivities to target proteins. Here, to further scrutinize the functions of this highly hydrophobic Ds base, the thermal stabilities of double-stranded DNAs (dsDNA) containing a noncognate Ds-Ds or G-Ds pair were examined. The thermal stability of the Ds-Ds self-pair was as high as that of the natural G-C pair, and apart from the generally higher stability of the G-C pair than that of the A-T pair, most of the 5'-pyrimidine-Ds-purine-3' sequences, such as CDsA and TDsA, exhibited higher stability than the 5'-purine-Ds-pyrimidine-3' sequences, such as GDsC and ADsC, in dsDNAs. This trait enabled the GC-content-independent control of the thermal stability of the designed dsDNA fragments. The melting temperatures of dsDNA fragments containing the Ds-Ds pair can be predicted from the nearest-neighbor parameters including the Ds base. In addition, the noncognate G-Ds pair can efficiently distinguish its neighboring cognate natural base pairs from noncognate pairs. We demonstrated that real-time PCR using primers containing Ds accurately detected a single-nucleotide mismatch in target DNAs. These unique properties of the Ds base that affect the stabilities of the neighboring base pairs could impart new functions to DNA molecules and technologies.

An Efficient Next Hop Selection Algorithm for Multi-Hop Body Area Networks

PubMed Central

Ayatollahitafti, Vahid; Ngadi, Md Asri; Mohamad Sharif, Johan bin; Abdullahi, Mohammed

2016-01-01

Body Area Networks (BANs) consist of various sensors which gather patient’s vital signs and deliver them to doctors. One of the most significant challenges faced, is the design of an energy-efficient next hop selection algorithm to satisfy Quality of Service (QoS) requirements for different healthcare applications. In this paper, a novel efficient next hop selection algorithm is proposed in multi-hop BANs. This algorithm uses the minimum hop count and a link cost function jointly in each node to choose the best next hop node. The link cost function includes the residual energy, free buffer size, and the link reliability of the neighboring nodes, which is used to balance the energy consumption and to satisfy QoS requirements in terms of end to end delay and reliability. Extensive simulation experiments were performed to evaluate the efficiency of the proposed algorithm using the NS-2 simulator. Simulation results show that our proposed algorithm provides significant improvement in terms of energy consumption, number of packets forwarded, end to end delay and packet delivery ratio compared to the existing routing protocol. PMID:26771586

Efficient protein structure search using indexing methods

PubMed Central

2013-01-01

Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively. PMID:23691543

Efficient protein structure search using indexing methods.

PubMed

Kim, Sungchul; Sael, Lee; Yu, Hwanjo

2013-01-01

Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles

PubMed Central

Azulay, Aharon; Zaslaver, Alon

2016-01-01

A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available. PMID:27606684

Gas Sorption and Storage Properties of Calixarenes

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

Patil, Rahul S.; Banerjee, Debasis; Atwood, Jerry L.

2016-12-01

Calixarenes, a class of organic macrocyclic molecules have shown interesting gas sorption properties towards industrially important gases such as carbon di-oxide, hydrogen, methane and acetylene. These macrocycles are involved in weak van der Waals interaction to form multidimensional supramolecular frameworks. The gas-diffusion and subsequent sorption occurs due to a cooperative behavior between neighboring macrocycles. Furthermore, the flexibility at the upper rim functional group also plays a key role in the overall gas uptake of calixarene. In this book chapter, we give a brief account of interaction and diffusion of gases in calixarene and selected derivatives.

Learning with imperfectly labeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

Greedy Gossip With Eavesdropping

NASA Astrophysics Data System (ADS)

Ustebay, Deniz; Oreshkin, Boris N.; Coates, Mark J.; Rabbat, Michael G.

2010-07-01

This paper presents greedy gossip with eavesdropping (GGE), a novel randomized gossip algorithm for distributed computation of the average consensus problem. In gossip algorithms, nodes in the network randomly communicate with their neighbors and exchange information iteratively. The algorithms are simple and decentralized, making them attractive for wireless network applications. In general, gossip algorithms are robust to unreliable wireless conditions and time varying network topologies. In this paper we introduce GGE and demonstrate that greedy updates lead to rapid convergence. We do not require nodes to have any location information. Instead, greedy updates are made possible by exploiting the broadcast nature of wireless communications. During the operation of GGE, when a node decides to gossip, instead of choosing one of its neighbors at random, it makes a greedy selection, choosing the node which has the value most different from its own. In order to make this selection, nodes need to know their neighbors' values. Therefore, we assume that all transmissions are wireless broadcasts and nodes keep track of their neighbors' values by eavesdropping on their communications. We show that the convergence of GGE is guaranteed for connected network topologies. We also study the rates of convergence and illustrate, through theoretical bounds and numerical simulations, that GGE consistently outperforms randomized gossip and performs comparably to geographic gossip on moderate-sized random geometric graph topologies.

Heat perturbation spreading in the Fermi-Pasta-Ulam-β system with next-nearest-neighbor coupling: Competition between phonon dispersion and nonlinearity

NASA Astrophysics Data System (ADS)

Xiong, Daxing

2017-06-01

We employ the heat perturbation correlation function to study thermal transport in the one-dimensional Fermi-Pasta-Ulam-β lattice with both nearest-neighbor and next-nearest-neighbor couplings. We find that such a system bears a peculiar phonon dispersion relation, and thus there exists a competition between phonon dispersion and nonlinearity that can strongly affect the heat correlation function's shape and scaling property. Specifically, for small and large anharmoncities, the scaling laws are ballistic and superdiffusive types, respectively, which are in good agreement with the recent theoretical predictions; whereas in the intermediate range of the nonlinearity, we observe an unusual multiscaling property characterized by a nonmonotonic delocalization process of the central peak of the heat correlation function. To understand these multiscaling laws, we also examine the momentum perturbation correlation function and find a transition process with the same turning point of the anharmonicity as that shown in the heat correlation function. This suggests coupling between the momentum transport and the heat transport, in agreement with the theoretical arguments of mode cascade theory.

Digital Parallel Processor Array for Optimum Path Planning

NASA Technical Reports Server (NTRS)

Kremeny, Sabrina E. (Inventor); Fossum, Eric R. (Inventor); Nixon, Robert H. (Inventor)

1996-01-01

The invention computes the optimum path across a terrain or topology represented by an array of parallel processor cells interconnected between neighboring cells by links extending along different directions to the neighboring cells. Such an array is preferably implemented as a high-speed integrated circuit. The computation of the optimum path is accomplished by, in each cell, receiving stimulus signals from neighboring cells along corresponding directions, determining and storing the identity of a direction along which the first stimulus signal is received, broadcasting a subsequent stimulus signal to the neighboring cells after a predetermined delay time, whereby stimulus signals propagate throughout the array from a starting one of the cells. After propagation of the stimulus signal throughout the array, a master processor traces back from a selected destination cell to the starting cell along an optimum path of the cells in accordance with the identity of the directions stored in each of the cells.

Beyond pairwise strategy updating in the prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Wang, Xiaofeng; Perc, Matjaž; Liu, Yongkui; Chen, Xiaojie; Wang, Long

2012-10-01

In spatial games players typically alter their strategy by imitating the most successful or one randomly selected neighbor. Since a single neighbor is taken as reference, the information stemming from other neighbors is neglected, which begets the consideration of alternative, possibly more realistic approaches. Here we show that strategy changes inspired not only by the performance of individual neighbors but rather by entire neighborhoods introduce a qualitatively different evolutionary dynamics that is able to support the stable existence of very small cooperative clusters. This leads to phase diagrams that differ significantly from those obtained by means of pairwise strategy updating. In particular, the survivability of cooperators is possible even by high temptations to defect and over a much wider uncertainty range. We support the simulation results by means of pair approximations and analysis of spatial patterns, which jointly highlight the importance of local information for the resolution of social dilemmas.

Practice makes proficient: pigeons (Columba livia) learn efficient routes on full-circuit navigational traveling salesperson problems.

PubMed

Baron, Danielle M; Ramirez, Alejandro J; Bulitko, Vadim; Madan, Christopher R; Greiner, Ariel; Hurd, Peter L; Spetch, Marcia L

2015-01-01

Visiting multiple locations and returning to the start via the shortest route, referred to as the traveling salesman (or salesperson) problem (TSP), is a valuable skill for both humans and non-humans. In the current study, pigeons were trained with increasing set sizes of up to six goals, with each set size presented in three distinct configurations, until consistency in route selection emerged. After training at each set size, the pigeons were tested with two novel configurations. All pigeons acquired routes that were significantly more efficient (i.e., shorter in length) than expected by chance selection of the goals. On average, the pigeons also selected routes that were more efficient than expected based on a local nearest-neighbor strategy and were as efficient as the average route generated by a crossing-avoidance strategy. Analysis of the routes taken indicated that they conformed to both a nearest-neighbor and a crossing-avoidance strategy significantly more often than expected by chance. Both the time taken to visit all goals and the actual distance traveled decreased from the first to the last trials of training in each set size. On the first trial with novel configurations, average efficiency was higher than chance, but was not higher than expected from a nearest-neighbor or crossing-avoidance strategy. These results indicate that pigeons can learn to select efficient routes on a TSP problem.

Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

NASA Astrophysics Data System (ADS)

Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

2014-03-01

A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

A comparison of 12 algorithms for matching on the propensity score.

PubMed

Austin, Peter C

2014-03-15

Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy nearest neighbor matching without replacement within specified caliper widths. For each of the latter two algorithms, we examined four different sub-algorithms defined by the order in which treated subjects were selected for matching to an untreated subject: lowest to highest propensity score, highest to lowest propensity score, best match first, and random order. We also examined matching with replacement. We found that (i) nearest neighbor matching induced the same balance in baseline covariates as did optimal matching; (ii) when at least some of the covariates were continuous, caliper matching tended to induce balance on baseline covariates that was at least as good as the other algorithms; (iii) caliper matching tended to result in estimates of treatment effect with less bias compared with optimal and nearest neighbor matching; (iv) optimal and nearest neighbor matching resulted in estimates of treatment effect with negligibly less variability than did caliper matching; (v) caliper matching had amongst the best performance when assessed using mean squared error; (vi) the order in which treated subjects were selected for matching had at most a modest effect on estimation; and (vii) matching with replacement did not have superior performance compared with caliper matching without replacement. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

A comparison of 12 algorithms for matching on the propensity score

PubMed Central

Austin, Peter C

2014-01-01

Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy nearest neighbor matching without replacement within specified caliper widths. For each of the latter two algorithms, we examined four different sub-algorithms defined by the order in which treated subjects were selected for matching to an untreated subject: lowest to highest propensity score, highest to lowest propensity score, best match first, and random order. We also examined matching with replacement. We found that (i) nearest neighbor matching induced the same balance in baseline covariates as did optimal matching; (ii) when at least some of the covariates were continuous, caliper matching tended to induce balance on baseline covariates that was at least as good as the other algorithms; (iii) caliper matching tended to result in estimates of treatment effect with less bias compared with optimal and nearest neighbor matching; (iv) optimal and nearest neighbor matching resulted in estimates of treatment effect with negligibly less variability than did caliper matching; (v) caliper matching had amongst the best performance when assessed using mean squared error; (vi) the order in which treated subjects were selected for matching had at most a modest effect on estimation; and (vii) matching with replacement did not have superior performance compared with caliper matching without replacement. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24123228

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

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

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

DOE PAGES

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; ...

2016-01-07

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

Collective Behaviors of Mobile Robots Beyond the Nearest Neighbor Rules With Switching Topology.

PubMed

Ning, Boda; Han, Qing-Long; Zuo, Zongyu; Jin, Jiong; Zheng, Jinchuan

2018-05-01

This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

The time course of spoken word learning and recognition: studies with artificial lexicons.

PubMed

Magnuson, James S; Tanenhaus, Michael K; Aslin, Richard N; Dahan, Delphine

2003-06-01

The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations.

Reduction in Predator Defense in the Presence of Neighbors in a Colonial Fish

PubMed Central

Schädelin, Franziska C.; Fischer, Stefan; Wagner, Richard H.

2012-01-01

Predation pressure has long been considered a leading explanation of colonies, where close neighbors may reduce predation via dilution, alarming or group predator attacks. Attacking predators may be costly in terms of energy and survival, leading to the question of how neighbors contribute to predator deterrence in relationship to each other. Two hypotheses explaining the relative efforts made by neighbors are byproduct-mutualism, which occurs when breeders inadvertently attack predators by defending their nests, and reciprocity, which occurs when breeders deliberately exchange predator defense efforts with neighbors. Most studies investigating group nest defense have been performed with birds. However, colonial fish may constitute a more practical model system for an experimental approach because of the greater ability of researchers to manipulate their environment. We investigated in the colonial fish, Neolamprologus caudopunctatus, whether prospecting pairs preferred to breed near conspecifics or solitarily, and how breeders invested in anti-predator defense in relation to neighbors. In a simple choice test, prospecting pairs selected breeding sites close to neighbors versus a solitary site. Predators were then sequentially presented to the newly established test pairs, the previously established stimulus pairs or in between the two pairs. Test pairs attacked the predator eight times more frequently when they were presented on their non-neighbor side compared to between the two breeding sites, where stimulus pairs maintained high attack rates. Thus, by joining an established pair, test pairs were able to reduce their anti-predator efforts near neighbors, at no apparent cost to the stimulus pairs. These findings are unlikely to be explained by reciprocity or byproduct-mutualism. Our results instead suggest a commensal relationship in which new pairs exploit the high anti-predator efforts of established pairs, which invest similarly with or without neighbors. Further studies are needed to determine the scope of commensalism as an anti-predator strategy in colonial animals. PMID:22615741

Unconventional quantum antiferromagnetism with a fourfold symmetry breaking in a spin-1/2 Ising-Heisenberg pentagonal chain

NASA Astrophysics Data System (ADS)

Karľová, Katarína; Strečka, Jozef; Lyra, Marcelo L.

2018-03-01

The spin-1/2 Ising-Heisenberg pentagonal chain is investigated with use of the star-triangle transformation, which establishes a rigorous mapping equivalence with the effective spin-1/2 Ising zigzag ladder. The investigated model has a rich ground-state phase diagram including two spectacular quantum antiferromagnetic ground states with a fourfold broken symmetry. It is demonstrated that these long-period quantum ground states arise due to a competition between the effective next-nearest-neighbor and nearest-neighbor interactions of the corresponding spin-1/2 Ising zigzag ladder. The concurrence is used to quantify the bipartite entanglement between the nearest-neighbor Heisenberg spin pairs, which are quantum-mechanically entangled in two quantum ground states with or without spontaneously broken symmetry. The pair correlation functions between the nearest-neighbor Heisenberg spins as well as the next-nearest-neighbor and nearest-neighbor Ising spins were investigated with the aim to bring insight into how a relevant short-range order manifests itself at low enough temperatures. It is shown that the specific heat displays temperature dependencies with either one or two separate round maxima.

Control of DNA-Functionalized Nanoparticle Assembly

NASA Astrophysics Data System (ADS)

Olvera de La Cruz, Monica

Directed crystallization of a large variety of nanoparticles, including proteins, via DNA hybridization kinetics has led to unique materials with a broad range of crystal symmetries. The nanoparticles are functionalized with DNA chains that link neighboring functionalized units. The shape of the nanoparticle, the DNA length, the sequence of the hybridizing DNA linker and the grafting density determine the crystal symmetries and lattice spacing. By carefully selecting these parameters one can, in principle, achieve all the symmetries found for both atomic and colloidal crystals of asymmetric shapes as well as new symmetries, and drive transitions between them. A scale-accurate coarse-grained model with explicit DNA chains provides the design parameters, including degree of hybridization, to achieve specific crystal structures. The model also provides surface energy values to determine the shape of defect-free single crystals with macroscopic anisotropic properties, as well as the parameters to develop colloidal models that reproduce both the shape of single crystals and their growth kinetics.

Analysis of miRNA expression profile based on SVM algorithm

NASA Astrophysics Data System (ADS)

Ting-ting, Dai; Chang-ji, Shan; Yan-shou, Dong; Yi-duo, Bian

2018-05-01

Based on mirna expression spectrum data set, a new data mining algorithm - tSVM - KNN (t statistic with support vector machine - k nearest neighbor) is proposed. the idea of the algorithm is: firstly, the feature selection of the data set is carried out by the unified measurement method; Secondly, SVM - KNN algorithm, which combines support vector machine (SVM) and k - nearest neighbor (k - nearest neighbor) is used as classifier. Simulation results show that SVM - KNN algorithm has better classification ability than SVM and KNN alone. Tsvm - KNN algorithm only needs 5 mirnas to obtain 96.08 % classification accuracy in terms of the number of mirna " tags" and recognition accuracy. compared with similar algorithms, tsvm - KNN algorithm has obvious advantages.

Belowground neighbor perception in Arabidopsis thaliana studied by transcriptome analysis: roots of Hieracium pilosella cause biotic stress

PubMed Central

Schmid, Christoph; Bauer, Sibylle; Müller, Benedikt; Bartelheimer, Maik

2013-01-01

Root-root interactions are much more sophisticated than previously thought, yet the mechanisms of belowground neighbor perception remain largely obscure. Genome-wide transcriptome analyses allow detailed insight into plant reactions to environmental cues. A root interaction trial was set up to explore both morphological and whole genome transcriptional responses in roots of Arabidopsis thaliana in the presence or absence of an inferior competitor, Hieracium pilosella. Neighbor perception was indicated by Arabidopsis roots predominantly growing away from the neighbor (segregation), while solitary plants placed more roots toward the middle of the pot. Total biomass remained unaffected. Database comparisons in transcriptome analysis revealed considerable similarity between Arabidopsis root reactions to neighbors and reactions to pathogens. Detailed analyses of the functional category “biotic stress” using MapMan tools found the sub-category “pathogenesis-related proteins” highly significantly induced. A comparison to a study on intraspecific competition brought forward a core of genes consistently involved in reactions to neighbor roots. We conclude that beyond resource depletion roots perceive neighboring roots or their associated microorganisms by a relatively uniform mechanism that involves the strong induction of pathogenesis-related proteins. In an ecological context the findings reveal that belowground neighbor detection may occur independently of resource depletion, allowing for a time advantage for the root to prepare for potential interactions. PMID:23967000

Error minimizing algorithms for nearest eighbor classifiers

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

Porter, Reid B; Hush, Don; Zimmer, G. Beate

2011-01-03

Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. Wemore » use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.« less

Fault-Tolerant, Real-Time, Multi-Core Computer System

NASA Technical Reports Server (NTRS)

Gostelow, Kim P.

2012-01-01

A document discusses a fault-tolerant, self-aware, low-power, multi-core computer for space missions with thousands of simple cores, achieving speed through concurrency. The proposed machine decides how to achieve concurrency in real time, rather than depending on programmers. The driving features of the system are simple hardware that is modular in the extreme, with no shared memory, and software with significant runtime reorganizing capability. The document describes a mechanism for moving ongoing computations and data that is based on a functional model of execution. Because there is no shared memory, the processor connects to its neighbors through a high-speed data link. Messages are sent to a neighbor switch, which in turn forwards that message on to its neighbor until reaching the intended destination. Except for the neighbor connections, processors are isolated and independent of each other. The processors on the periphery also connect chip-to-chip, thus building up a large processor net. There is no particular topology to the larger net, as a function at each processor allows it to forward a message in the correct direction. Some chip-to-chip connections are not necessarily nearest neighbors, providing short cuts for some of the longer physical distances. The peripheral processors also provide the connections to sensors, actuators, radios, science instruments, and other devices with which the computer system interacts.

Fast Demand Forecast of Electric Vehicle Charging Stations for Cell Phone Application

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

Majidpour, Mostafa; Qiu, Charlie; Chung, Ching-Yen

This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, kNearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for themore » cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.« less

Lexical precision in skilled readers: Individual differences in masked neighbor priming.

PubMed

Andrews, Sally; Hersch, Jolyn

2010-05-01

Two experiments investigated the relationship between masked form priming and individual differences in reading and spelling proficiency among university students. Experiment 1 assessed neighbor priming for 4-letter word targets from high- and low-density neighborhoods in 97 university students. The overall results replicated previous evidence of facilitatory neighborhood priming only for low-neighborhood words. However, analyses including measures of reading and spelling proficiency as covariates revealed that better spellers showed inhibitory priming for high-neighborhood words, while poorer spellers showed facilitatory priming. Experiment 2, with 123 participants, replicated the finding of stronger inhibitory neighbor priming in better spellers using 5-letter words and distinguished facilitatory and inhibitory components of priming by comparing neighbor primes with ambiguous and unambiguous partial-word primes (e.g., crow#, cr#wd, crown CROWD). The results indicate that spelling ability is selectively associated with inhibitory effects of lexical competition. The implications for theories of visual word recognition and the lexical quality hypothesis of reading skill are discussed.

Selenium hyperaccumulators facilitate selenium-tolerant neighbors via phytoenrichment and reduced herbivory.

PubMed

El Mehdawi, Ali F; Quinn, Colin F; Pilon-Smits, Elizabeth A H

2011-09-13

Soil surrounding selenium (Se) hyperaccumulator plants was shown earlier to be enriched in Se, impairing the growth of Se-sensitive plant species. Because Se levels in neighbors of hyperaccumulators were higher and Se has been shown to protect plants from herbivory, we investigate here the potential facilitating effect of Se hyperaccumulators on Se-tolerant neighboring species in the field. We measured growth and herbivory of Artemisia ludoviciana and Symphyotrichum ericoides as a function of their Se concentration and proximity to hyperaccumulators Astragalus bisulcatus and Stanleya pinnata. When growing next to hyperaccumulators, A. ludoviciana and S. ericoides contained 10- to 20-fold higher Se levels (800-2,000 mg kg(-1) DW) than when growing next to nonaccumulators. The roots of both species were predominantly (70%-90%) directed toward hyperaccumulator neighbors, not toward other neighbors. Moreover, neighbors of hyperaccumulators were 2-fold bigger, showed 2-fold less herbivory damage, and harbored 3- to 4-fold fewer arthropods. When used in laboratory choice and nonchoice grasshopper herbivory experiments, Se-rich neighbors of hyperaccumulators experienced less herbivory and caused higher grasshopper Se accumulation (10-fold) and mortality (4-fold). Enhanced soil Se levels around hyperaccumulators can facilitate growth of Se-tolerant plant species through reduced herbivory and enhanced growth. This study is the first to show facilitation via enrichment with a nonessential element. It is interesting that Se enrichment of hyperaccumulator neighbors may affect competition in two ways, by reducing growth of Se-sensitive neighbors while facilitating Se-tolerant neighbors. Via these competitive and facilitating effects, Se hyperaccumulators may affect plant community composition and, consequently, higher trophic levels. Copyright © 2011 Elsevier Ltd. All rights reserved.

From Flexible and Stretchable Meta-Atom to Metamaterial: A Wearable Microwave Meta-Skin with Tunable Frequency Selective and Cloaking Effects

PubMed Central

Yang, Siming; Liu, Peng; Yang, Mingda; Wang, Qiugu; Song, Jiming; Dong, Liang

2016-01-01

This paper reports a flexible and stretchable metamaterial-based “skin” or meta-skin with tunable frequency selective and cloaking effects in microwave frequency regime. The meta-skin is composed of an array of liquid metallic split ring resonators (SRRs) embedded in a stretchable elastomer. When stretched, the meta-skin performs as a tunable frequency selective surface with a wide resonance frequency tuning range. When wrapped around a curved dielectric material, the meta-skin functions as a flexible “cloaking” surface to significantly suppress scattering from the surface of the dielectric material along different directions. We studied frequency responses of multilayer meta-skins to stretching in a planar direction and to changing the spacing between neighboring layers in vertical direction. We also investigated scattering suppression effect of the meta-skin coated on a finite-length dielectric rod in free space. This meta-skin technology will benefit many electromagnetic applications, such as frequency tuning, shielding, and scattering suppression. PMID:26902969

Toward literature-based feature selection for diagnostic classification: a meta-analysis of resting-state fMRI in depression.

PubMed

Sundermann, Benedikt; Olde Lütke Beverborg, Mona; Pfleiderer, Bettina

2014-01-01

Information derived from functional magnetic resonance imaging (fMRI) during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD). Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD, primarily to serve as feature selection for multivariate pattern analysis techniques (MVPA). Thirty two studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components including the precuneus and neighboring posterior cingulate cortices associated with self-referential processing and the subgenual anterior cingulate and neighboring medial frontal cortices) with lateral prefrontal areas related to externally-directed cognition. Other areas of hyperactivity/hyperconnectivity include the left lateral parietal cortex, right hippocampus and right cerebellum whereas hypoactivity/hypoconnectivity was observed mainly in the left temporal cortex, the insula, precuneus, superior frontal gyrus, lentiform nucleus and thalamus. Results are made available in two different data formats to be used as spatial hypotheses in future studies, particularly for diagnostic classification by MVPA.

A decentralized mechanism for improving the functional robustness of distribution networks.

PubMed

Shi, Benyun; Liu, Jiming

2012-10-01

Most real-world distribution systems can be modeled as distribution networks, where a commodity can flow from source nodes to sink nodes through junction nodes. One of the fundamental characteristics of distribution networks is the functional robustness, which reflects the ability of maintaining its function in the face of internal or external disruptions. In view of the fact that most distribution networks do not have any centralized control mechanisms, we consider the problem of how to improve the functional robustness in a decentralized way. To achieve this goal, we study two important problems: 1) how to formally measure the functional robustness, and 2) how to improve the functional robustness of a network based on the local interaction of its nodes. First, we derive a utility function in terms of network entropy to characterize the functional robustness of a distribution network. Second, we propose a decentralized network pricing mechanism, where each node need only communicate with its distribution neighbors by sending a "price" signal to its upstream neighbors and receiving "price" signals from its downstream neighbors. By doing so, each node can determine its outflows by maximizing its own payoff function. Our mathematical analysis shows that the decentralized pricing mechanism can produce results equivalent to those of an ideal centralized maximization with complete information. Finally, to demonstrate the properties of our mechanism, we carry out a case study on the U.S. natural gas distribution network. The results validate the convergence and effectiveness of our mechanism when comparing it with an existing algorithm.

Asymmetric homotypic interactions of the atypical cadherin Flamingo mediate intercellular polarity signaling

PubMed Central

Chen, Wei-Shen; Antic, Dragana; Matis, Maja; Logan, Catriona Y.; Povelones, Michael; Anderson, Graham; Nusse, Roel; Axelrod, Jeffrey D.

2008-01-01

Acquisition of planar cell polarity (PCP) in epithelia involves intercellular communication, during which cells align their polarity with that of their neighbors. The transmembrane proteins Frizzled (Fz) and Van Gogh (Vang) are essential components of the intercellular communication mechanism, as loss of either strongly perturbs the polarity of neighboring cells. How Fz and Vang communicate polarity information between neighboring cells is poorly understood. The atypical cadherin, Flamingo (Fmi), is implicated in this process, yet whether Fmi acts permissively as a scaffold, or instructively as a signal is unclear. Here, we provide evidence that Fmi functions instructively to mediate Fz-Vang intercellular signal relay, recruiting Fz and Vang to opposite sides of cell boundaries. We propose that two functional forms of Fmi, one of which is induced by and physically interacts with Fz, form cadherin homodimers that signal bidirectionally and asymmetrically, instructing unequal responses in adjacent cell membranes to establish molecular asymmetry. PMID:18555784

C-glycosylation reactions of sulfur-substituted glycosyl donors: evidence against the role of neighboring-group participation.

PubMed

Beaver, Matthew G; Billings, Susan B; Woerpel, K A

2008-02-13

Nucleophilic substitution reactions of C-4 sulfur-substituted tetrahydropyran acetals revealed that neighboring-group participation does not control product formation. Spectroscopic evidence for the formation of an intermediate sulfonium ion is provided, as are data from nucleophilic substitution reactions demonstrating that products are formed from oxocarbenium ion intermediates. The selectivity was not sensitive to solvent or to which Lewis acid was employed. The identity of the heteroatom at the C-4 position also did not significantly impact diastereoselectivity. Consequently, neighboring-group participation was not responsible for the formation of either the major or the minor products. These studies implicate a Curtin-Hammett kinetic scenario in which the formation of a low-energy intermediate does not necessitate its involvement in the product-forming pathway.

Evolution of coalitionary killing.

PubMed

Wrangham, R W

1999-01-01

Warfare has traditionally been considered unique to humans. It has, therefore, often been explained as deriving from features that are unique to humans, such as the possession of weapons or the adoption of a patriarchal ideology. Mounting evidence suggests, however, that coalitional killing of adults in neighboring groups also occurs regularly in other species, including wolves and chimpanzees. This implies that selection can favor components of intergroup aggression important to human warfare, including lethal raiding. Here I present the principal adaptive hypothesis for explaining the species distribution of intergroup coalitional killing. This is the "imbalance-of-power hypothesis," which suggests that coalitional killing is the expression of a drive for dominance over neighbors. Two conditions are proposed to be both necessary and sufficient to account for coalitional killing of neighbors: (1) a state of intergroup hostility; (2) sufficient imbalances of power between parties that one party can attack the other with impunity. Under these conditions, it is suggested, selection favors the tendency to hunt and kill rivals when the costs are sufficiently low. The imbalance-of-power hypothesis has been criticized on a variety of empirical and theoretical grounds which are discussed. To be further tested, studies of the proximate determinants of aggression are needed. However, current evidence supports the hypothesis that selection has favored a hunt-and-kill propensity in chimpanzees and humans, and that coalitional killing has a long history in the evolution of both species.

Streamflow variability and classification using false nearest neighbor method

NASA Astrophysics Data System (ADS)

Vignesh, R.; Jothiprakash, V.; Sivakumar, B.

2015-12-01

Understanding regional streamflow dynamics and patterns continues to be a challenging problem. The present study introduces the false nearest neighbor (FNN) algorithm, a nonlinear dynamic-based method, to examine the spatial variability of streamflow over a region. The FNN method is a dimensionality-based approach, where the dimension of the time series represents its variability. The method uses phase space reconstruction and nearest neighbor concepts, and identifies false neighbors in the reconstructed phase space. The FNN method is applied to monthly streamflow data monitored over a period of 53 years (1950-2002) in an extensive network of 639 stations in the contiguous United States (US). Since selection of delay time in phase space reconstruction may influence the FNN outcomes, analysis is carried out for five different delay time values: monthly, seasonal, and annual separation of data as well as delay time values obtained using autocorrelation function (ACF) and average mutual information (AMI) methods. The FNN dimensions for the 639 streamflow series are generally identified to range from 4 to 12 (with very few exceptional cases), indicating a wide range of variability in the dynamics of streamflow across the contiguous US. However, the FNN dimensions for a majority of the streamflow series are found to be low (less than or equal to 6), suggesting low level of complexity in streamflow dynamics in most of the individual stations and over many sub-regions. The FNN dimension estimates also reveal that streamflow dynamics in the western parts of the US (including far west, northwestern, and southwestern parts) generally exhibit much greater variability compared to that in the eastern parts of the US (including far east, northeastern, and southeastern parts), although there are also differences among 'pockets' within these regions. These results are useful for identification of appropriate model complexity at individual stations, patterns across regions and sub-regions, interpolation and extrapolation of data, and catchment classification. An attempt is also made to relate the FNN dimensions with catchment characteristics and streamflow statistical properties.

Sequencing Needs for Viral Diagnostics

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

Gardner, S N; Lam, M; Mulakken, N J

2004-01-26

We built a system to guide decisions regarding the amount of genomic sequencing required to develop diagnostic DNA signatures, which are short sequences that are sufficient to uniquely identify a viral species. We used our existing DNA diagnostic signature prediction pipeline, which selects regions of a target species genome that are conserved among strains of the target (for reliability, to prevent false negatives) and unique relative to other species (for specificity, to avoid false positives). We performed simulations, based on existing sequence data, to assess the number of genome sequences of a target species and of close phylogenetic relatives (''nearmore » neighbors'') that are required to predict diagnostic signature regions that are conserved among strains of the target species and unique relative to other bacterial and viral species. For DNA viruses such as variola (smallpox), three target genomes provide sufficient guidance for selecting species-wide signatures. Three near neighbor genomes are critical for species specificity. In contrast, most RNA viruses require four target genomes and no near neighbor genomes, since lack of conservation among strains is more limiting than uniqueness. SARS and Ebola Zaire are exceptional, as additional target genomes currently do not improve predictions, but near neighbor sequences are urgently needed. Our results also indicate that double stranded DNA viruses are more conserved among strains than are RNA viruses, since in most cases there was at least one conserved signature candidate for the DNA viruses and zero conserved signature candidates for the RNA viruses.« less

Genomic Signatures of Speciation in Sympatric and Allopatric Hawaiian Picture-Winged Drosophila

PubMed Central

Kang, Lin; Settlage, Robert; McMahon, Wyatt; Michalak, Katarzyna; Tae, Hongseok; Garner, Harold R.; Stacy, Elizabeth A.; Price, Donald K.; Michalak, Pawel

2016-01-01

The Hawaiian archipelago provides a natural arena for understanding adaptive radiation and speciation. The Hawaiian Drosophila are one of the most diverse endemic groups in Hawaiì with up to 1,000 species. We sequenced and analyzed entire genomes of recently diverged species of Hawaiian picture-winged Drosophila, Drosophila silvestris and Drosophila heteroneura from Hawaiì Island, in comparison with Drosophila planitibia, their sister species from Maui, a neighboring island where a common ancestor of all three had likely occurred. Genome-wide single nucleotide polymorphism patterns suggest the more recent origin of D. silvestris and D. heteroneura, as well as a pervasive influence of positive selection on divergence of the three species, with the signatures of positive selection more prominent in sympatry than allopatry. Positively selected genes were significantly enriched for functional terms related to sensory detection and mating, suggesting that sexual selection played an important role in speciation of these species. In particular, sequence variation in Olfactory receptor and Gustatory receptor genes seems to play a major role in adaptive radiation in Hawaiian pictured-winged Drosophila. PMID:27189993

Nearest neighbors by neighborhood counting.

PubMed

Wang, Hui

2006-06-01

Finding nearest neighbors is a general idea that underlies many artificial intelligence tasks, including machine learning, data mining, natural language understanding, and information retrieval. This idea is explicitly used in the k-nearest neighbors algorithm (kNN), a popular classification method. In this paper, this idea is adopted in the development of a general methodology, neighborhood counting, for devising similarity functions. We turn our focus from neighbors to neighborhoods, a region in the data space covering the data point in question. To measure the similarity between two data points, we consider all neighborhoods that cover both data points. We propose to use the number of such neighborhoods as a measure of similarity. Neighborhood can be defined for different types of data in different ways. Here, we consider one definition of neighborhood for multivariate data and derive a formula for such similarity, called neighborhood counting measure or NCM. NCM was tested experimentally in the framework of kNN. Experiments show that NCM is generally comparable to VDM and its variants, the state-of-the-art distance functions for multivariate data, and, at the same time, is consistently better for relatively large k values. Additionally, NCM consistently outperforms HEOM (a mixture of Euclidean and Hamming distances), the "standard" and most widely used distance function for multivariate data. NCM has a computational complexity in the same order as the standard Euclidean distance function and NCM is task independent and works for numerical and categorical data in a conceptually uniform way. The neighborhood counting methodology is proven sound for multivariate data experimentally. We hope it will work for other types of data.

A Milieu Molecule for TGF-β Required for Microglia Function in the Nervous System.

PubMed

Qin, Yan; Garrison, Brian S; Ma, Wenjiang; Wang, Rui; Jiang, Aiping; Li, Jing; Mistry, Meeta; Bronson, Roderick T; Santoro, Daria; Franco, Charlotte; Robinton, Daisy A; Stevens, Beth; Rossi, Derrick J; Lu, Chafen; Springer, Timothy A

2018-06-12

Extracellular proTGF-β is covalently linked to "milieu" molecules in the matrix or on cell surfaces and is latent until TGF-β is released by integrins. Here, we show that LRRC33 on the surface of microglia functions as a milieu molecule and enables highly localized, integrin-αVβ8-dependent TGF-β activation. Lrrc33 -/- mice lack CNS vascular abnormalities associated with deficiency in TGF-β-activating integrins but have microglia with a reactive phenotype and after 2 months develop ascending paraparesis with loss of myelinated axons and death by 5 months. Whole bone marrow transplantation results in selective repopulation of Lrrc33 -/- brains with WT microglia and halts disease progression. The phenotypes of WT and Lrrc33 -/- microglia in the same brain suggest that there is little spreading of TGF-β activated from one microglial cell to neighboring microglia. Our results suggest that interactions between integrin-bearing cells and cells bearing milieu molecule-associated TGF-β provide localized and selective activation of TGF-β. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Chatterjee, Anupam; Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076; Higham, Jonathan

A range of methods are presented to calculate a solute’s hydration shell from computer simulations of dilute solutions of monatomic ions and noble gas atoms. The methods are designed to be parameter-free and instantaneous so as to make them more general, accurate, and consequently applicable to disordered systems. One method is a modified nearest-neighbor method, another considers solute-water Lennard-Jones overlap followed by hydrogen-bond rearrangement, while three methods compare various combinations of water-solute and water-water forces. The methods are tested on a series of monatomic ions and solutes and compared with the values from cutoffs in the radial distribution function, themore » nearest-neighbor distribution functions, and the strongest-acceptor hydrogen bond definition for anions. The Lennard-Jones overlap method and one of the force-comparison methods are found to give a hydration shell for cations which is in reasonable agreement with that using a cutoff in the radial distribution function. Further modifications would be required, though, to make them capture the neighboring water molecules of noble-gas solutes if these weakly interacting molecules are considered to constitute the hydration shell.« less

Community detection using preference networks

NASA Astrophysics Data System (ADS)

Tasgin, Mursel; Bingol, Haluk O.

2018-04-01

Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph

USGS Publications Warehouse

Eaton, Mitchell J.; Hughes, Phillip T.; Hines, James E.; Nichols, James D.

2014-01-01

Metapopulation ecology is a field that is richer in theory than in empirical results. Many existing empirical studies use an incidence function approach based on spatial patterns and key assumptions about extinction and colonization rates. Here we recast these assumptions as hypotheses to be tested using 18 years of historic detection survey data combined with four years of data from a new monitoring program for the Lower Keys marsh rabbit. We developed a new model to estimate probabilities of local extinction and colonization in the presence of nondetection, while accounting for estimated occupancy levels of neighboring patches. We used model selection to identify important drivers of population turnover and estimate the effective neighborhood size for this system. Several key relationships related to patch size and isolation that are often assumed in metapopulation models were supported: patch size was negatively related to the probability of extinction and positively related to colonization, and estimated occupancy of neighboring patches was positively related to colonization and negatively related to extinction probabilities. This latter relationship suggested the existence of rescue effects. In our study system, we inferred that coastal patches experienced higher probabilities of extinction and colonization than interior patches. Interior patches exhibited higher occupancy probabilities and may serve as refugia, permitting colonization of coastal patches following disturbances such as hurricanes and storm surges. Our modeling approach should be useful for incorporating neighbor occupancy into future metapopulation analyses and in dealing with other historic occupancy surveys that may not include the recommended levels of sampling replication.

Finger vein identification using fuzzy-based k-nearest centroid neighbor classifier

NASA Astrophysics Data System (ADS)

Rosdi, Bakhtiar Affendi; Jaafar, Haryati; Ramli, Dzati Athiar

2015-02-01

In this paper, a new approach for personal identification using finger vein image is presented. Finger vein is an emerging type of biometrics that attracts attention of researchers in biometrics area. As compared to other biometric traits such as face, fingerprint and iris, finger vein is more secured and hard to counterfeit since the features are inside the human body. So far, most of the researchers focus on how to extract robust features from the captured vein images. Not much research was conducted on the classification of the extracted features. In this paper, a new classifier called fuzzy-based k-nearest centroid neighbor (FkNCN) is applied to classify the finger vein image. The proposed FkNCN employs a surrounding rule to obtain the k-nearest centroid neighbors based on the spatial distributions of the training images and their distance to the test image. Then, the fuzzy membership function is utilized to assign the test image to the class which is frequently represented by the k-nearest centroid neighbors. Experimental evaluation using our own database which was collected from 492 fingers shows that the proposed FkNCN has better performance than the k-nearest neighbor, k-nearest-centroid neighbor and fuzzy-based-k-nearest neighbor classifiers. This shows that the proposed classifier is able to identify the finger vein image effectively.

Effect of interjunction coupling on superconducting current and charge correlations in intrinsic Josephson junctions

NASA Astrophysics Data System (ADS)

Shukrinov, Yu. M.; Hamdipour, M.; Kolahchi, M. R.

2009-07-01

Charge formations on superconducting layers and creation of the longitudinal plasma wave in the stack of intrinsic Josephson junctions change crucially the superconducting current through the stack. Investigation of the correlations of superconducting currents in neighboring Josephson junctions and the charge correlations in neighboring superconducting layers allows us to predict the additional features in the current-voltage characteristics. The charge autocorrelation functions clearly demonstrate the difference between harmonic and chaotic behavior in the breakpoint region. Use of the correlation functions gives us a powerful method for the analysis of the current-voltage characteristics of coupled Josephson junctions.

Neighbor-directed histidine N(τ) alkylation. A route to imidazolium-containing phosphopeptide macrocycles

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

Qian, Wen-Jian; Park, Jung-Eun; Grant, Robert

2015-07-07

Our recently discovered, selective, on-resin route to N(τ)-alkylated imidazolium-containing histidine residues affords new strategies for peptide mimetic design. In this, we demonstrate the use of this chemistry to prepare a series of macrocyclic phosphopeptides, in which imidazolium groups serve as ring-forming junctions. These cationic moieties subsequently serve to charge-mask the phosphoamino acid group that directed their formation. Furthermore, neighbor-directed histidine N(τ)-alkylation opens the door to new families of phosphopeptidomimetics for use in a range of chemical biology contexts.

Progress on the autophagic regulators and receptors in plants.

PubMed

Zeng, Xiao-wei; Liu, Cui-cui; Han, Ning; Bian, Hong-wu; Zhu, Mu-yuan

2016-07-20

Autophagy is an evolutionarily highly conserved catabolic pathway among eukaryotic cells that protects the organisms against environmental stress. Normally, autophagy is mainly involved with autophagy-related proteins(ATGs) and autophagic regulators including a series of cytoplasmic proteins and small molecules. Besides, the selective autophagy, which targets damaged organalles or protein aggregates, is mediated by the additional receptors to help the ATGs recognize different substrates. In this review, we summarize recent advances in autophagic regulators like ROS(Reactive oxygen species), TOR(Target of rapamycin) and receptors like NBR1(Neighbor of BRCA1 gene protein), RPN10(Regulatory particle non-ATPase 10) as well as their functional mechanisms mainly in Arabidopsis thaliana.

Velocity correlations and spatial dependencies between neighbors in a unidirectional flow of pedestrians

NASA Astrophysics Data System (ADS)

Porzycki, Jakub; WÄ s, Jarosław; Hedayatifar, Leila; Hassanibesheli, Forough; Kułakowski, Krzysztof

2017-08-01

The aim of the paper is an analysis of self-organization patterns observed in the unidirectional flow of pedestrians. On the basis of experimental data from Zhang et al. [J. Zhang et al., J. Stat. Mech. (2011) P06004, 10.1088/1742-5468/2011/06/P06004], we analyze the mutual positions and velocity correlations between pedestrians when walking along a corridor. The angular and spatial dependencies of the mutual positions reveal a spatial structure that remains stable during the crowd motion. This structure differs depending on the value of n , for the consecutive n th -nearest-neighbor position set. The preferred position for the first-nearest neighbor is on the side of the pedestrian, while for further neighbors, this preference shifts to the axis of movement. The velocity correlations vary with the angle formed by the pair of neighboring pedestrians and the direction of motion and with the time delay between pedestrians' movements. The delay dependence of the correlations shows characteristic oscillations, produced by the velocity oscillations when striding; however, a filtering of the main frequency of individual striding out reduces the oscillations only partially. We conclude that pedestrians select their path directions so as to evade the necessity of continuously adjusting their speed to their neighbors'. They try to keep a given distance, but follow the person in front of them, as well as accepting and observing pedestrians on their sides. Additionally, we show an empirical example that illustrates the shape of a pedestrian's personal space during movement.

Neighboring trees affect ectomycorrhizal fungal community composition in a woodland-forest ecotone.

PubMed

Hubert, Nathaniel A; Gehring, Catherine A

2008-09-01

Ectomycorrhizal fungi (EMF) are frequently species rich and functionally diverse; yet, our knowledge of the environmental factors that influence local EMF diversity and species composition remains poor. In particular, little is known about the influence of neighboring plants on EMF community structure. We tested the hypothesis that the EMF of plants with heterospecific neighbors would differ in species richness and community composition from the EMF of plants with conspecific neighbors. We conducted our study at the ecotone between pinyon (Pinus edulis)-juniper (Juniperus monosperma) woodland and ponderosa pine (Pinus ponderosa) forest in northern Arizona, USA where the dominant trees formed associations with either EMF (P. edulis and P. ponderosa) or arbuscular mycorrhizal fungi (AMF; J. monosperma). We also compared the EMF communities of pinyon and ponderosa pines where their rhizospheres overlapped. The EMF community composition, but not species richness of pinyon pines was significantly influenced by neighboring AM juniper, but not by neighboring EM ponderosa pine. Ponderosa pine EMF communities were different in species composition when growing in association with pinyon pine than when growing in association with a conspecific. The EMF communities of pinyon and ponderosa pines were similar where their rhizospheres overlapped consisting of primarily the same species in similar relative abundance. Our findings suggest that neighboring tree species identity shaped EMF community structure, but that these effects were specific to host-neighbor combinations. The overlap in community composition between pinyon pine and ponderosa pine suggests that these tree species may serve as reservoirs of EMF inoculum for one another.

Response Properties of Neighboring Neurons in the Auditory Midbrain for Pure-Tone Stimulation: A Tetrode Study

PubMed Central

Seshagiri, Chandran V.; Delgutte, Bertrand

2007-01-01

The complex anatomical structure of the central nucleus of the inferior colliculus (ICC), the principal auditory nucleus in the midbrain, may provide the basis for functional organization of auditory information. To investigate this organization, we used tetrodes to record from neighboring neurons in the ICC of anesthetized cats and studied the similarity and difference among the responses of these neurons to pure-tone stimuli using widely used physiological characterizations. Consistent with the tonotopic arrangement of neurons in the ICC and reports of a threshold map, we found a high degree of correlation in the best frequencies (BFs) of neighboring neurons, which were mostly <3 kHz in our sample, and the pure-tone thresholds among neighboring neurons. However, width of frequency tuning, shapes of the frequency response areas, and temporal discharge patterns showed little or no correlation among neighboring neurons. Because the BF and threshold are measured at levels near the threshold and the characteristic frequency (CF), neighboring neurons may receive similar primary inputs tuned to their CF; however, at higher levels, additional inputs from other frequency channels may be recruited, introducing greater variability in the responses. There was also no correlation among neighboring neurons' sensitivity to interaural time differences (ITD) measured with binaural beats. However, the characteristic phases (CPs) of neighboring neurons revealed a significant correlation. Because the CP is related to the neural mechanisms generating the ITD sensitivity, this result is consistent with segregation of inputs to the ICC from the lateral and medial superior olives. PMID:17671101

Response properties of neighboring neurons in the auditory midbrain for pure-tone stimulation: a tetrode study.

PubMed

Seshagiri, Chandran V; Delgutte, Bertrand

2007-10-01

The complex anatomical structure of the central nucleus of the inferior colliculus (ICC), the principal auditory nucleus in the midbrain, may provide the basis for functional organization of auditory information. To investigate this organization, we used tetrodes to record from neighboring neurons in the ICC of anesthetized cats and studied the similarity and difference among the responses of these neurons to pure-tone stimuli using widely used physiological characterizations. Consistent with the tonotopic arrangement of neurons in the ICC and reports of a threshold map, we found a high degree of correlation in the best frequencies (BFs) of neighboring neurons, which were mostly <3 kHz in our sample, and the pure-tone thresholds among neighboring neurons. However, width of frequency tuning, shapes of the frequency response areas, and temporal discharge patterns showed little or no correlation among neighboring neurons. Because the BF and threshold are measured at levels near the threshold and the characteristic frequency (CF), neighboring neurons may receive similar primary inputs tuned to their CF; however, at higher levels, additional inputs from other frequency channels may be recruited, introducing greater variability in the responses. There was also no correlation among neighboring neurons' sensitivity to interaural time differences (ITD) measured with binaural beats. However, the characteristic phases (CPs) of neighboring neurons revealed a significant correlation. Because the CP is related to the neural mechanisms generating the ITD sensitivity, this result is consistent with segregation of inputs to the ICC from the lateral and medial superior olives.

Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

NASA Astrophysics Data System (ADS)

Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

2017-11-01

K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

Comparisons of topological properties in autism for the brain network construction methods

NASA Astrophysics Data System (ADS)

Lee, Min-Hee; Kim, Dong Youn; Lee, Sang Hyeon; Kim, Jin Uk; Chung, Moo K.

2015-03-01

Structural brain networks can be constructed from the white matter fiber tractography of diffusion tensor imaging (DTI), and the structural characteristics of the brain can be analyzed from its networks. When brain networks are constructed by the parcellation method, their network structures change according to the parcellation scale selection and arbitrary thresholding. To overcome these issues, we modified the Ɛ -neighbor construction method proposed by Chung et al. (2011). The purpose of this study was to construct brain networks for 14 control subjects and 16 subjects with autism using both the parcellation and the Ɛ-neighbor construction method and to compare their topological properties between two methods. As the number of nodes increased, connectedness decreased in the parcellation method. However in the Ɛ-neighbor construction method, connectedness remained at a high level even with the rising number of nodes. In addition, statistical analysis for the parcellation method showed significant difference only in the path length. However, statistical analysis for the Ɛ-neighbor construction method showed significant difference with the path length, the degree and the density.

Serving by local consensus in the public service location game.

PubMed

Sun, Yi-Fan; Zhou, Hai-Jun

2016-09-02

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems.

Serving by local consensus in the public service location game

PubMed Central

Sun, Yi-Fan; Zhou, Hai-Jun

2016-01-01

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems. PMID:27586793

Serving by local consensus in the public service location game

NASA Astrophysics Data System (ADS)

Sun, Yi-Fan; Zhou, Hai-Jun

2016-09-01

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems.

Effective Feature Selection for Classification of Promoter Sequences.

PubMed

K, Kouser; P G, Lavanya; Rangarajan, Lalitha; K, Acharya Kshitish

2016-01-01

Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM) features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine), KNN (K Nearest Neighbor) and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method) but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

Dynamics of transit times and StorAge Selection functions in four forested catchments from stable isotope data

NASA Astrophysics Data System (ADS)

Rodriguez, Nicolas B.; McGuire, Kevin J.; Klaus, Julian

2017-04-01

Transit time distributions, residence time distributions and StorAge Selection functions are fundamental integrated descriptors of water storage, mixing, and release in catchments. In this contribution, we determined these time-variant functions in four neighboring forested catchments in H.J. Andrews Experimental Forest, Oregon, USA by employing a two year time series of 18O in precipitation and discharge. Previous studies in these catchments assumed stationary, exponentially distributed transit times, and complete mixing/random sampling to explore the influence of various catchment properties on the mean transit time. Here we relaxed such assumptions to relate transit time dynamics and the variability of StoreAge Selection functions to catchment characteristics, catchment storage, and meteorological forcing seasonality. Conceptual models of the catchments, consisting of two reservoirs combined in series-parallel, were calibrated to discharge and stable isotope tracer data. We assumed randomly sampled/fully mixed conditions for each reservoir, which resulted in an incompletely mixed system overall. Based on the results we solved the Master Equation, which describes the dynamics of water ages in storage and in catchment outflows Consistent between all catchments, we found that transit times were generally shorter during wet periods, indicating the contribution of shallow storage (soil, saprolite) to discharge. During extended dry periods, transit times increased significantly indicating the contribution of deeper storage (bedrock) to discharge. Our work indicated that the strong seasonality of precipitation impacted transit times by leading to a dynamic selection of stored water ages, whereas catchment size was not a control on transit times. In general this work showed the usefulness of using time-variant transit times with conceptual models and confirmed the existence of the catchment age mixing behaviors emerging from other similar studies.

Hash Bit Selection for Nearest Neighbor Search.

PubMed

Xianglong Liu; Junfeng He; Shih-Fu Chang

2017-11-01

To overcome the barrier of storage and computation when dealing with gigantic-scale data sets, compact hashing has been studied extensively to approximate the nearest neighbor search. Despite the recent advances, critical design issues remain open in how to select the right features, hashing algorithms, and/or parameter settings. In this paper, we address these by posing an optimal hash bit selection problem, in which an optimal subset of hash bits are selected from a pool of candidate bits generated by different features, algorithms, or parameters. Inspired by the optimization criteria used in existing hashing algorithms, we adopt the bit reliability and their complementarity as the selection criteria that can be carefully tailored for hashing performance in different tasks. Then, the bit selection solution is discovered by finding the best tradeoff between search accuracy and time using a modified dynamic programming method. To further reduce the computational complexity, we employ the pairwise relationship among hash bits to approximate the high-order independence property, and formulate it as an efficient quadratic programming method that is theoretically equivalent to the normalized dominant set problem in a vertex- and edge-weighted graph. Extensive large-scale experiments have been conducted under several important application scenarios of hash techniques, where our bit selection framework can achieve superior performance over both the naive selection methods and the state-of-the-art hashing algorithms, with significant accuracy gains ranging from 10% to 50%, relatively.

Most Undirected Random Graphs Are Amplifiers of Selection for Birth-Death Dynamics, but Suppressors of Selection for Death-Birth Dynamics.

PubMed

Hindersin, Laura; Traulsen, Arne

2015-11-01

We analyze evolutionary dynamics on graphs, where the nodes represent individuals of a population. The links of a node describe which other individuals can be displaced by the offspring of the individual on that node. Amplifiers of selection are graphs for which the fixation probability is increased for advantageous mutants and decreased for disadvantageous mutants. A few examples of such amplifiers have been developed, but so far it is unclear how many such structures exist and how to construct them. Here, we show that almost any undirected random graph is an amplifier of selection for Birth-death updating, where an individual is selected to reproduce with probability proportional to its fitness and one of its neighbors is replaced by that offspring at random. If we instead focus on death-Birth updating, in which a random individual is removed and its neighbors compete for the empty spot, then the same ensemble of graphs consists of almost only suppressors of selection for which the fixation probability is decreased for advantageous mutants and increased for disadvantageous mutants. Thus, the impact of population structure on evolutionary dynamics is a subtle issue that will depend on seemingly minor details of the underlying evolutionary process.

BET Bromodomain Inhibition Releases the Mediator Complex from Select cis-Regulatory Elements.

PubMed

Bhagwat, Anand S; Roe, Jae-Seok; Mok, Beverly Y L; Hohmann, Anja F; Shi, Junwei; Vakoc, Christopher R

2016-04-19

The bromodomain and extraterminal (BET) protein BRD4 can physically interact with the Mediator complex, but the relevance of this association to the therapeutic effects of BET inhibitors in cancer is unclear. Here, we show that BET inhibition causes a rapid release of Mediator from a subset of cis-regulatory elements in the genome of acute myeloid leukemia (AML) cells. These sites of Mediator eviction were highly correlated with transcriptional suppression of neighboring genes, which are enriched for targets of the transcription factor MYB and for functions related to leukemogenesis. A shRNA screen of Mediator in AML cells identified the MED12, MED13, MED23, and MED24 subunits as performing a similar regulatory function to BRD4 in this context, including a shared role in sustaining a block in myeloid maturation. These findings suggest that the interaction between BRD4 and Mediator has functional importance for gene-specific transcriptional activation and for AML maintenance. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses

PubMed Central

Kringel, D; Ultsch, A; Zimmermann, M; Jansen, J-P; Ilias, W; Freynhagen, R; Griessinger, N; Kopf, A; Stein, C; Doehring, A; Resch, E; Lötsch, J

2017-01-01

Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces ‘big data’ exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics. PMID:27139154

Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses.

PubMed

Kringel, D; Ultsch, A; Zimmermann, M; Jansen, J-P; Ilias, W; Freynhagen, R; Griessinger, N; Kopf, A; Stein, C; Doehring, A; Resch, E; Lötsch, J

2017-10-01

Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces 'big data' exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics.

A quasi-dense matching approach and its calibration application with Internet photos.

PubMed

Wan, Yanli; Miao, Zhenjiang; Wu, Q M Jonathan; Wang, Xifu; Tang, Zhen; Wang, Zhifei

2015-03-01

This paper proposes a quasi-dense matching approach to the automatic acquisition of camera parameters, which is required for recovering 3-D information from 2-D images. An affine transformation-based optimization model and a new matching cost function are used to acquire quasi-dense correspondences with high accuracy in each pair of views. These correspondences can be effectively detected and tracked at the sub-pixel level in multiviews with our neighboring view selection strategy. A two-layer iteration algorithm is proposed to optimize 3-D quasi-dense points and camera parameters. In the inner layer, different optimization strategies based on local photometric consistency and a global objective function are employed to optimize the 3-D quasi-dense points and camera parameters, respectively. In the outer layer, quasi-dense correspondences are resampled to guide a new estimation and optimization process of the camera parameters. We demonstrate the effectiveness of our algorithm with several experiments.

Hydrogen abstraction from deoxyribose by a neighboring 3'-uracil peroxyl radical.

PubMed

Schyman, Patric; Eriksson, Leif A; Laaksonen, Aatto

2009-05-07

Theoretical examination of the reactivity of the uracil-5-peroxyl radical when abstracting a hydrogen atom from a neighboring 5'-deoxyribose in 5'-ApU-5-peroxyl-3' has been performed using density functional theory with the MPWB1K functional. Halogenated uracils are often used as radiosensitizers in DNA since the reactive uracil-5-yl radical is formed upon radiation and is known to create strand break and alkali-labile sites. Under aerobic conditions, such as in the cell, it has been proposed that the uracil-5-peroxyl radical is formed and would be the damaging agent. Our results show low reactivity for the uracil-5-peroxyl radical, determined by calculating the activation and reaction energies for the plausible hydrogen abstraction sites C1', C2', and C3' of the neighboring 5'-deoxyribose. These findings support the hypothesis that hydrogen abstraction primarily occurs by the uracil-5-yl radical, also under aerobic conditions, prior to formation of the peroxyl radical.

Nanoscale lamellar photoconductor hybrids and methods of making same

DOEpatents

Stupp, Samuel I; Goldberger, Josh; Sofos, Marina

2013-02-05

An article of manufacture and methods of making same. In one embodiment, the article of manufacture has a plurality of zinc oxide layers substantially in parallel, wherein each zinc oxide layer has a thickness d.sub.1, and a plurality of organic molecule layers substantially in parallel, wherein each organic molecule layer has a thickness d.sub.2 and a plurality of molecules with a functional group that is bindable to zinc ions, wherein for every pair of neighboring zinc oxide layers, one of the plurality of organic molecule layers is positioned in between the pair of neighboring zinc oxide layers to allow the functional groups of the plurality of organic molecules to bind to zinc ions in the neighboring zinc oxide layers to form a lamellar hybrid structure with a geometric periodicity d.sub.1+d.sub.2, and wherein d.sub.1 and d.sub.2 satisfy the relationship of d.sub.1.ltoreq.d.sub.2.ltoreq.3d.sub.1.

Impacts of leguminous shrub encroachment on neighboring grasses include transfer of fixed nitrogen.

PubMed

Zhang, Hai-Yang; Yu, Qiang; Lü, Xiao-Tao; Trumbore, Susan E; Yang, Jun-Jie; Han, Xing-Guo

2016-04-01

Shrub encroachment induced by global change and human disturbance strongly affects ecosystem structure and function. In this study, we explore the degree to which invading leguminous shrubs affected neighboring grasses, including via the transfer of fixed nitrogen (N). We measured N concentrations and natural abundance (15)N of shoot tissues from three dominant grasses from different plant functional groups across seven distances along a local transect (up to 500 cm) to the leguminous shrub, Caragana microphylla. C. microphylla did transfer fixed N to neighboring grasses, but the amount and distance of N transferred were strongly species-specific. Shoot N concentrations decreased significantly with distance from C. microphylla, for a rhizomatous grass, Leymus chinensis, and a bunchgrass, Achnatherum sibiricum. However, N concentrations of another bunchgrass, Stipa grandis, were higher only directly underneath the shrub canopy. Shoot δ(15)N values of L. chinensis were enriched up to 500 cm from the shrub, but for S. grandis were enriched only below the shrub canopy. In contrast, δ(15)N of A. sibiricum did not change along the 500-cm transect. Our results indicated the rhizomatous grass transferred fixed N over long distances while bunchgrasses did not. The presence of C. microphylla increased the shoot biomass of L. chinensis but decreased that of S. grandis and A. sibiricum. These findings highlight the potential role of nutrient-acquisition strategies of neighboring grasses in moderating the interspecific variation of fixed N transfer from the leguminous shrub. Overall, leguminous shrubs have either positive or negative effects on the neighboring grasses and dramatically affect plant community composition and structure.

X-ray K-edge absorption spectra of Fe minerals and model compounds: II. EXAFS

NASA Astrophysics Data System (ADS)

Waychunas, Glenn A.; Brown, Gordon E.; Apted, Michael J.

1986-01-01

K-edge extended X-ray absorption fine structure (EXAFS) spectra of Fe in varying environments in a suite of well-characterized silicate and oxide minerals were collected using synchrotron radiation and analyzed using single scattering approximation theory to yield nearest neighbor Fe-O distances and coordination numbers. The partial inverse character of synthetic hercynite spinal was verified in this way. Comparison of the results from all samples with structural data from X-ray diffraction crystal structure refinements indicates that EXAFS-derived first neighbor distances are generally accurate to ±0.02 Å using only theoretically generated phase information, and may be improved over this if similar model compounds are used to determine EXAFS phase functions. Coordination numbers are accurate to ±20 percent and can be similarly improved using model compound EXAFS amplitude information. However, in particular cases the EXAFS-derived distances may be shortened, and the coordination number reduced, by the effects of static and thermal disorder or by partial overlap of the longer Fe-O first neighbor distances with second neighbor distances in the EXAFS structure function. In the former case the total information available in the EXAFS is limited by the disorder, while in the latter case more accurate results can in principle be obtained by multiple neighbor EXAFS analysis. The EXAFS and XANES spectra of Fe in Nain, Labrador osumulite and Lakeview, Oregon plagioclase are also analyzed as an example of the application of X-ray absorption spectroscopy to metal ion site occupation determination in minerals.

Ground-state ordering of the J1-J2 model on the simple cubic and body-centered cubic lattices

NASA Astrophysics Data System (ADS)

Farnell, D. J. J.; Götze, O.; Richter, J.

2016-06-01

The J1-J2 Heisenberg model is a "canonical" model in the field of quantum magnetism in order to study the interplay between frustration and quantum fluctuations as well as quantum phase transitions driven by frustration. Here we apply the coupled cluster method (CCM) to study the spin-half J1-J2 model with antiferromagnetic nearest-neighbor bonds J1>0 and next-nearest-neighbor bonds J2>0 for the simple cubic (sc) and body-centered cubic (bcc) lattices. In particular, we wish to study the ground-state ordering of these systems as a function of the frustration parameter p =z2J2/z1J1 , where z1 (z2) is the number of nearest (next-nearest) neighbors. We wish to determine the positions of the phase transitions using the CCM and we aim to resolve the nature of the phase transition points. We consider the ground-state energy, order parameters, spin-spin correlation functions, as well as the spin stiffness in order to determine the ground-state phase diagrams of these models. We find a direct first-order phase transition at a value of p =0.528 from a state of nearest-neighbor Néel order to next-nearest-neighbor Néel order for the bcc lattice. For the sc lattice the situation is more subtle. CCM results for the energy, the order parameter, the spin-spin correlation functions, and the spin stiffness indicate that there is no direct first-order transition between ground-state phases with magnetic long-range order, rather it is more likely that two phases with antiferromagnetic long range are separated by a narrow region of a spin-liquid-like quantum phase around p =0.55 . Thus the strong frustration present in the J1-J2 Heisenberg model on the sc lattice may open a window for an unconventional quantum ground state in this three-dimensional spin model.

Thermodynamic functions of hydration of hydrocarbons at 298.15 K and 0.1 MPa

NASA Astrophysics Data System (ADS)

Plyasunov, Andrey V.; Shock, Everett L.

2000-02-01

An extensive compilation of experimental data yielding the infinite dilution partial molar Gibbs energy of hydration Δ hGO, enthalpy of hydration Δ hHO, heat capacity of hydration Δ hCpO, and volume V2O, at the reference temperature and pressure, 298.15 K and 0.1 MPa, is presented for hydrocarbons (excluding polyaromatic compounds) and monohydric alcohols. These results are used in a least-squares procedure to determine the numerical values of the corresponding properties of the selected functional groups. The simple first order group contribution method, which in general ignores nearest-neighbors and steric hindrance effects, was chosen to represent the compiled data. Following the precedent established by Cabani et al. (1981), the following groups are considered: CH 3, CH 2, CH, C for saturated hydrocarbons; c-CH 2, c-CH, c-C for cyclic saturated hydrocarbons; CH ar, C ar for aromatic hydrocarbons (containing the benzene ring); C=C, C≡C for double and triple bonds in linear hydrocarbons, respectively; c-C=C for the double bond in cyclic hydrocarbons; H for a hydrogen atom attached to the double bond (both in linear and cyclic hydrocarbons) or triple bond; and OH for the hydroxyl functional group. In addition it was found necessary to include the "pseudo"-group I(C-C) to account for the specific interactions of the neighboring hydrocarbon groups attached to the benzene or cyclic ring (in the latter case only for cis-isomers). Results of this study, the numerical values of the group contributions, will allow in most cases reasonably accurate estimations of Δ hGO, Δ hHO, Δ hCpO, and V2O at 298.15 K, 0.1 MPa for many hydrocarbons involved in geochemical and environmental processes.

MUFFINN: cancer gene discovery via network analysis of somatic mutation data.

PubMed

Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk

2016-06-23

A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.

Heterogeneity and nearest-neighbor coupling can explain small-worldness and wave properties in pancreatic islets

NASA Astrophysics Data System (ADS)

Cappon, Giacomo; Pedersen, Morten Gram

2016-05-01

Many multicellular systems consist of coupled cells that work as a syncytium. The pancreatic islet of Langerhans is a well-studied example of such a microorgan. The islets are responsible for secretion of glucose-regulating hormones, mainly glucagon and insulin, which are released in distinct pulses. In order to observe pulsatile insulin secretion from the β-cells within the islets, the cellular responses must be synchronized. It is now well established that gap junctions provide the electrical nearest-neighbor coupling that allows excitation waves to spread across islets to synchronize the β-cell population. Surprisingly, functional coupling analysis of calcium responses in β-cells shows small-world properties, i.e., a high degree of local coupling with a few long-range "short-cut" connections that reduce the average path-length greatly. Here, we investigate how such long-range functional coupling can appear as a result of heterogeneity, nearest-neighbor coupling, and wave propagation. Heterogeneity is also able to explain a set of experimentally observed synchronization and wave properties without introducing all-or-none cell coupling and percolation theory. Our theoretical results highlight how local biological coupling can give rise to functional small-world properties via heterogeneity and wave propagation.

Social aggregation in pea aphids: experiment and random walk modeling.

PubMed

Nilsen, Christa; Paige, John; Warner, Olivia; Mayhew, Benjamin; Sutley, Ryan; Lam, Matthew; Bernoff, Andrew J; Topaz, Chad M

2013-01-01

From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid's nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control.

Matrix light and pixel light: optical system architecture and requirements to the light source

NASA Astrophysics Data System (ADS)

Spinger, Benno; Timinger, Andreas L.

2015-09-01

Modern Automotive headlamps enable improved functionality for more driving comfort and safety. Matrix or Pixel light headlamps are not restricted to either pure low beam functionality or pure high beam. Light in direction of oncoming traffic is selectively switched of, potential hazard can be marked via an isolated beam and the illumination on the road can even follow a bend. The optical architectures that enable these advanced functionalities are diverse. Electromechanical shutters and lens units moved by electric motors were the first ways to realize these systems. Switching multiple LED light sources is a more elegant and mechanically robust solution. While many basic functionalities can already be realized with a limited number of LEDs, an increasing number of pixels will lead to more driving comfort and better visibility. The required optical system needs not only to generate a desired beam distribution with a high angular dynamic, but also needs to guarantee minimal stray light and cross talk between the different pixels. The direct projection of the LED array via a lens is a simple but not very efficient optical system. We discuss different optical elements for pre-collimating the light with minimal cross talk and improved contrast between neighboring pixels. Depending on the selected optical system, we derive the basic light source requirements: luminance, surface area, contrast, flux and color homogeneity.

Creating peer groups for assessing and comparing nursing home performance.

PubMed

Byrne, Margaret M; Daw, Christina; Pietz, Ken; Reis, Brian; Petersen, Laura A

2013-11-01

Publicly reported performance data for hospitals and nursing homes are becoming ubiquitous. For such comparisons to be fair, facilities must be compared with their peers. To adapt a previously published methodology for developing hospital peer groupings so that it is applicable to nursing homes and to explore the characteristics of "nearest-neighbor" peer groupings. Analysis of Department of Veterans Affairs administrative databases and nursing home facility characteristics. The nearest-neighbor methodology for developing peer groupings involves calculating the Euclidean distance between facilities based on facility characteristics. We describe our steps in selection of facility characteristics, describe the characteristics of nearest-neighbor peer groups, and compare them with peer groups derived through classical cluster analysis. The facility characteristics most pertinent to nursing home groupings were found to be different from those that were most relevant for hospitals. Unlike classical cluster groups, nearest neighbor groups are not mutually exclusive, and the nearest-neighbor methodology resulted in nursing home peer groupings that were substantially less diffuse than nursing home peer groups created using traditional cluster analysis. It is essential that healthcare policy makers and administrators have a means of fairly grouping facilities for the purposes of quality, cost, or efficiency comparisons. In this research, we show that a previously published methodology can be successfully applied to a nursing home setting. The same approach could be applied in other clinical settings such as primary care.

Numerical Simulation of the Diffusion Processes in Nanoelectrode Arrays Using an Axial Neighbor Symmetry Approximation.

PubMed

Peinetti, Ana Sol; Gilardoni, Rodrigo S; Mizrahi, Martín; Requejo, Felix G; González, Graciela A; Battaglini, Fernando

2016-06-07

Nanoelectrode arrays have introduced a complete new battery of devices with fascinating electrocatalytic, sensitivity, and selectivity properties. To understand and predict the electrochemical response of these arrays, a theoretical framework is needed. Cyclic voltammetry is a well-fitted experimental technique to understand the undergoing diffusion and kinetics processes. Previous works describing microelectrode arrays have exploited the interelectrode distance to simulate its behavior as the summation of individual electrodes. This approach becomes limited when the size of the electrodes decreases to the nanometer scale due to their strong radial effect with the consequent overlapping of the diffusional fields. In this work, we present a computational model able to simulate the electrochemical behavior of arrays working either as the summation of individual electrodes or being affected by the overlapping of the diffusional fields without previous considerations. Our computational model relays in dividing a regular electrode array in cells. In each of them, there is a central electrode surrounded by neighbor electrodes; these neighbor electrodes are transformed in a ring maintaining the same active electrode area than the summation of the closest neighbor electrodes. Using this axial neighbor symmetry approximation, the problem acquires a cylindrical symmetry, being applicable to any diffusion pattern. The model is validated against micro- and nanoelectrode arrays showing its ability to predict their behavior and therefore to be used as a designing tool.

Weighted Parzen Windows for Pattern Classification

DTIC Science & Technology

1994-05-01

Nearest-Neighbor Rule The k-Nearest-Neighbor ( kNN ) technique is nonparametric, assuming nothing about the distribution of the data. Stated succinctly...probabilities P(wj I x) from samples." Raudys and Jain [20:255] advance this interpretation by pointing out that the kNN technique can be viewed as the...34Parzen window classifier with a hyper- rectangular window function." As with the Parzen-window technique, the kNN classifier is more accurate as the

On the role of heat and mass transfer into laser processability during selective laser melting AlSi12 alloy based on a randomly packed powder-bed

NASA Astrophysics Data System (ADS)

Wang, Lianfeng; Yan, Biao; Guo, Lijie; Gu, Dongdong

2018-04-01

A newly transient mesoscopic model with a randomly packed powder-bed has been proposed to investigate the heat and mass transfer and laser process quality between neighboring tracks during selective laser melting (SLM) AlSi12 alloy by finite volume method (FVM), considering the solid/liquid phase transition, variable temperature-dependent properties and interfacial force. The results apparently revealed that both the operating temperature and resultant cooling rate were obviously elevated by increasing the laser power. Accordingly, the resultant viscosity of liquid significantly reduced under a large laser power and was characterized with a large velocity, which was prone to result in a more intensive convection within pool. In this case, the sufficient heat and mass transfer occurred at the interface between the previously fabricated tracks and currently building track, revealing a strongly sufficient spreading between the neighboring tracks and a resultant high-quality surface without obvious porosity. By contrast, the surface quality of SLM-processed components with a relatively low laser power notably weakened due to the limited and insufficient heat and mass transfer at the interface of neighboring tracks. Furthermore, the experimental surface morphologies of the top surface were correspondingly acquired and were in full accordance to the calculated results via simulation.

Structures of human ADAR2 bound to dsRNA reveal base-flipping mechanism and basis for site selectivity

DOE PAGES

Matthews, Melissa M.; Thomas, Justin M.; Zheng, Yuxuan; ...

2016-04-11

Adenosine deaminases acting on RNA (ADARs) are editing enzymes that convert adenosine to inosine in duplex RNA, a modification reaction with wide-ranging consequences in RNA function. Understanding of the ADAR reaction mechanism, the origin of editing-site selectivity, and the effect of mutations is limited by the lack of high-resolution structural data for complexes of ADARs bound to substrate RNAs. In this paper, we describe four crystal structures of the human ADAR2 deaminase domain bound to RNA duplexes bearing a mimic of the deamination reaction intermediate. These structures, together with structure-guided mutagenesis and RNA-modification experiments, explain the basis of the ADARmore » deaminase domain's dsRNA specificity, its base-flipping mechanism, and its nearest-neighbor preferences. In addition, we identified an ADAR2-specific RNA-binding loop near the enzyme active site, thus rationalizing differences in selectivity observed between different ADARs. In conclusion, our results provide a structural framework for understanding the effects of ADAR mutations associated with human disease.« less

Overexpression of neurofilament H disrupts normal cell structure and function

NASA Technical Reports Server (NTRS)

Szebenyi, Gyorgyi; Smith, George M.; Li, Ping; Brady, Scott T.

2002-01-01

Studying exogenously expressed tagged proteins in live cells has become a standard technique for evaluating protein distribution and function. Typically, expression levels of experimentally introduced proteins are not regulated, and high levels are often preferred to facilitate detection. However, overexpression of many proteins leads to mislocalization and pathologies. Therefore, for normative studies, moderate levels of expression may be more suitable. To understand better the dynamics of intermediate filament formation, transport, and stability in a healthy, living cell, we inserted neurofilament heavy chain (NFH)-green fluorescent protein (GFP) fusion constructs in adenoviral vectors with tetracycline (tet)-regulated promoters. This system allows for turning on or off the synthesis of NFH-GFP at a selected time, for a defined period, in a dose-dependent manner. We used this inducible system for live cell imaging of changes in filament structure and cell shape, motility, and transport associated with increasing NFH-GFP expression. Cells with low to intermediate levels of NFH-GFP were structurally and functionally similar to neighboring, nonexpressing cells. In contrast, overexpression led to pathological alterations in both filament organization and cell function. Copyright 2002 Wiley-Liss, Inc.

Genomic Signatures of Speciation in Sympatric and Allopatric Hawaiian Picture-Winged Drosophila.

PubMed

Kang, Lin; Settlage, Robert; McMahon, Wyatt; Michalak, Katarzyna; Tae, Hongseok; Garner, Harold R; Stacy, Elizabeth A; Price, Donald K; Michalak, Pawel

2016-05-30

The Hawaiian archipelago provides a natural arena for understanding adaptive radiation and speciation. The Hawaiian Drosophila are one of the most diverse endemic groups in Hawaiì with up to 1,000 species. We sequenced and analyzed entire genomes of recently diverged species of Hawaiian picture-winged Drosophila, Drosophila silvestris and Drosophila heteroneura from Hawaiì Island, in comparison with Drosophila planitibia, their sister species from Maui, a neighboring island where a common ancestor of all three had likely occurred. Genome-wide single nucleotide polymorphism patterns suggest the more recent origin of D. silvestris and D. heteroneura, as well as a pervasive influence of positive selection on divergence of the three species, with the signatures of positive selection more prominent in sympatry than allopatry. Positively selected genes were significantly enriched for functional terms related to sensory detection and mating, suggesting that sexual selection played an important role in speciation of these species. In particular, sequence variation in Olfactory receptor and Gustatory receptor genes seems to play a major role in adaptive radiation in Hawaiian pictured-winged Drosophila. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Exact density functional theory for ideal polymer fluids with nearest neighbor bonding constraints.

PubMed

Woodward, Clifford E; Forsman, Jan

2008-08-07

We present a new density functional theory of ideal polymer fluids, assuming nearest-neighbor bonding constraints. The free energy functional is expressed in terms of end site densities of chain segments and thus has a simpler mathematical structure than previously used expressions using multipoint distributions. This work is based on a formalism proposed by Tripathi and Chapman [Phys. Rev. Lett. 94, 087801 (2005)]. Those authors obtain an approximate free energy functional for ideal polymers in terms of monomer site densities. Calculations on both repulsive and attractive surfaces show that their theory is reasonably accurate in some cases, but does differ significantly from the exact result for longer polymers with attractive surfaces. We suggest that segment end site densities, rather than monomer site densities, are the preferred choice of "site functions" for expressing the free energy functional of polymer fluids. We illustrate the application of our theory to derive an expression for the free energy of an ideal fluid of infinitely long polymers.

The effects of herbivory on neighbor interactions along a coastal marsh gradient

USGS Publications Warehouse

Taylor, K.L.; Grace, J.B.; Marx, B.D.

1997-01-01

Many current theories of community function are based on the assumption that disturbances such as herbivory act to reduce the importance of neighbor interactions among plants. In this study, we examined the effects of herbivory (primarily by nutria, Myocastor coy-pus) on neighbor interactions between three dominant grasses in three coastal marsh communities, fresh, oligohaline, and mesohaline. The grasses studied were Panicum virgatum, Spartina patens, and Spartina alterniflora, which are dominant species in the fresh, oligohaline, and mesohaline marshes, respectively. Additive mixtures and monocultures of transplants were used in conjunction with exclosure fences to determine the impact of herbivory on neighbor interactions in the different marsh types. Herbivory had a strong effect on all three species and was important in all three marshes. In the absence of herbivores, the impact of neighbors was significant for two of the species (Panicum virgatum and Spartina patens) and varied considerably between environments, with competition intensifying for Panicum virgatum and decreasing for Spartina patens with increasing salinity. Indications of positive neighbor effects (mutualisms) were observed for both of these species, though in contrasting habitats and to differing degrees. In the presence of herbivores, however, competitive and positive effects were eliminated. Overall, then, it was observed that in this case, intense herbivory was able to override other biotic interactions such as competition and mutualism, which were not detectable in the presence of herbivores.

The Effects of Sample Selection Bias on Racial Differences in Child Abuse Reporting.

ERIC Educational Resources Information Center

Ards, Sheila; Chung, Chanjin; Myers, Samuel L., Jr.

1998-01-01

Data from the National Incidence Study (NIS) of Child Abuse and Neglect suggest no racial difference in child maltreatment, although there are more black children within the child welfare population. This study found selection bias in the NIS design caused by the exclusion of family, friends, and neighbors that resulted in differences in NIS cases…

Path Diversity Improved Opportunistic Routing for Underwater Sensor Networks

PubMed Central

Wang, Haiyan; He, Ke

2018-01-01

The packets carried along a pre-defined route in underwater sensor networks are very vulnerble. Node mobility or intermittent channel availability easily leads to unreachable routing. Opportunistic routing has been proven to be a promising paradigm to design routing protocols for underwater sensor networks. It takes advantage of the broadcast nature of the wireless medium to combat packet losses and selects potential paths on the fly. Finding an appropriate forwarding candidate set is a key issue in opportunistic routing. Many existing solutions ignore the impact of candidates location distribution on packet forwarding. In this paper, a path diversity improved candidate selection strategy is applied in opportunistic routing to improve packet forwarding efficiency. It not only maximizes the packet forwarding advancements but also takes the candidate’s location distribution into account. Based on this strategy, we propose two effective routing protocols: position improved candidates selection (PICS) and position random candidates selection (PRCS). PICS employs two-hop neighbor information to make routing decisions. PRCS only uses one-hop neighbor information. Simulation results show that both PICS and PRCS can significantly improve network performance when compared with the previous solutions, in terms of packet delivery ratio, average energy consumption and end-to-end delay. PMID:29690621

Path Diversity Improved Opportunistic Routing for Underwater Sensor Networks.

PubMed

Bai, Weigang; Wang, Haiyan; He, Ke; Zhao, Ruiqin

2018-04-23

The packets carried along a pre-defined route in underwater sensor networks are very vulnerble. Node mobility or intermittent channel availability easily leads to unreachable routing. Opportunistic routing has been proven to be a promising paradigm to design routing protocols for underwater sensor networks. It takes advantage of the broadcast nature of the wireless medium to combat packet losses and selects potential paths on the fly. Finding an appropriate forwarding candidate set is a key issue in opportunistic routing. Many existing solutions ignore the impact of candidates location distribution on packet forwarding. In this paper, a path diversity improved candidate selection strategy is applied in opportunistic routing to improve packet forwarding efficiency. It not only maximizes the packet forwarding advancements but also takes the candidate’s location distribution into account. Based on this strategy, we propose two effective routing protocols: position improved candidates selection (PICS) and position random candidates selection (PRCS). PICS employs two-hop neighbor information to make routing decisions. PRCS only uses one-hop neighbor information. Simulation results show that both PICS and PRCS can significantly improve network performance when compared with the previous solutions, in terms of packet delivery ratio, average energy consumption and end-to-end delay.

Integrating instance selection, instance weighting, and feature weighting for nearest neighbor classifiers by coevolutionary algorithms.

PubMed

Derrac, Joaquín; Triguero, Isaac; Garcia, Salvador; Herrera, Francisco

2012-10-01

Cooperative coevolution is a successful trend of evolutionary computation which allows us to define partitions of the domain of a given problem, or to integrate several related techniques into one, by the use of evolutionary algorithms. It is possible to apply it to the development of advanced classification methods, which integrate several machine learning techniques into a single proposal. A novel approach integrating instance selection, instance weighting, and feature weighting into the framework of a coevolutionary model is presented in this paper. We compare it with a wide range of evolutionary and nonevolutionary related methods, in order to show the benefits of the employment of coevolution to apply the techniques considered simultaneously. The results obtained, contrasted through nonparametric statistical tests, show that our proposal outperforms other methods in the comparison, thus becoming a suitable tool in the task of enhancing the nearest neighbor classifier.

Lessons from the canine Oxtr gene: populations, variants and functional aspects.

PubMed

Bence, M; Marx, P; Szantai, E; Kubinyi, E; Ronai, Z; Banlaki, Z

2017-04-01

Oxytocin receptor (OXTR) acts as a key behavioral modulator of the central nervous system, affecting social behavior, stress, affiliation and cognitive functions. Variants of the Oxtr gene are known to influence behavior both in animals and humans; however, canine Oxtr polymorphisms are less characterized in terms of possible relevance to function, selection criteria in breeding and domestication. In this report, we provide a detailed characterization of common variants of the canine Oxtr gene. In particular (1) novel polymorphisms were identified by direct sequencing of wolf and dog samples, (2) allelic distributions and pairwise linkage disequilibrium patterns of several canine populations were compared, (3) neighbor joining (NJ) tree based on common single nucleotide polymorphisms (SNPs) was constructed, (4) mRNA expression features were assessed, (5) a novel splice variant was detected and (6) in vitro functional assays were performed. Results indicate marked differences regarding Oxtr variations between purebred dogs of different breeds, free-ranging dog populations, wolf subspecies and golden jackals. This, together with existence of explicitly dog-specific alleles and data obtained from the NJ tree implies that Oxtr could indeed have been a target gene during domestication and selection for human preferred aspects of temperament and social behavior. This assumption is further supported by the present observations on gene expression patterns within the brain and luciferase reporter experiments, providing a molecular level link between certain canine Oxtr polymorphisms and differences in nervous system function and behavior. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Influence of the number of topologically interacting neighbors on swarm dynamics

PubMed Central

Shang, Yilun; Bouffanais, Roland

2014-01-01

Recent empirical and theoretical works on collective behaviors based on a topological interaction are beginning to offer some explanations as for the physical reasons behind the selection of a particular number of nearest neighbors locally affecting each individual's dynamics. Recently, flocking starlings have been shown to topologically interact with a very specific number of neighbors, between six to eight, while metric-free interactions were found to govern human crowd dynamics. Here, we use network- and graph-theoretic approaches combined with a dynamical model of locally interacting self-propelled particles to study how the consensus reaching process and its dynamics are influenced by the number k of topological neighbors. Specifically, we prove exactly that, in the absence of noise, consensus is always attained with a speed to consensus strictly increasing with k. The analysis of both speed and time to consensus reveals that, irrespective of the swarm size, a value of k ~ 10 speeds up the rate of convergence to consensus to levels close to the one of the optimal all-to-all interaction signaling. Furthermore, this effect is found to be more pronounced in the presence of environmental noise. PMID:24567077

If You Don't Have Valence, Ask Your Neighbor: Evaluation of Neutral Words as a Function of Affective Semantic Associates

PubMed Central

Kuhlmann, Michael; Hofmann, Markus J.; Jacobs, Arthur M.

2017-01-01

How do humans perform difficult forced-choice evaluations, e.g., of words that have been previously rated as being neutral? Here we tested the hypothesis that in this case, the valence of semantic associates is of significant influence. From corpus based co-occurrence statistics as a measure of association strength we computed individual neighborhoods for single neutral words comprised of the 10 words with the largest association strength. We then selected neutral words according to the valence of the associated words included in the neighborhoods, which were either mostly positive, mostly negative, mostly neutral or mixed positive and negative, and tested them using a valence decision task (VDT). The data showed that the valence of semantic neighbors can predict valence judgments to neutral words. However, all but the positive neighborhood items revealed a high tendency to elicit negative responses. For the positive and negative neighborhood categories responses congruent with the neighborhood's valence were faster than incongruent responses. We interpret this effect as a semantic network process that supports the evaluation of neutral words by assessing the valence of the associative semantic neighborhood. In this perspective, valence is considered a semantic super-feature, at least partially represented in associative activation patterns of semantic networks. PMID:28348538

Distinct regions of right temporo-parietal junction are selective for theory of mind and exogenous attention.

PubMed

Scholz, Jonathan; Triantafyllou, Christina; Whitfield-Gabrieli, Susan; Brown, Emery N; Saxe, Rebecca

2009-01-01

In functional magnetic resonance imaging (fMRI) studies, a cortical region in the right temporo-parietal junction (RTPJ) is recruited when participants read stories about people's thoughts ('Theory of Mind'). Both fMRI and lesion studies suggest that a region near the RTPJ is associated with attentional reorienting in response to an unexpected stimulus. Do Theory of Mind and attentional reorienting recruit a single population of neurons, or are there two neighboring but distinct neural populations in the RTPJ? One recent study compared these activations, and found evidence consistent with a single common region. However, the apparent overlap may have been due to the low resolution of the previous technique. We tested this hypothesis using a high-resolution protocol, within-subjects analyses, and more powerful statistical methods. Strict conjunction analyses revealed that the area of overlap was small and on the periphery of each activation. In addition, a bootstrap analysis identified a reliable 6-10 mm spatial displacement between the peak activations of the two tasks; the same magnitude and direction of displacement was observed in within-subjects comparisons. In all, these results suggest that there are neighboring but distinct regions within the RTPJ implicated in Theory of Mind and orienting attention.

If You Don't Have Valence, Ask Your Neighbor: Evaluation of Neutral Words as a Function of Affective Semantic Associates.

PubMed

Kuhlmann, Michael; Hofmann, Markus J; Jacobs, Arthur M

2017-01-01

How do humans perform difficult forced-choice evaluations, e.g., of words that have been previously rated as being neutral? Here we tested the hypothesis that in this case, the valence of semantic associates is of significant influence. From corpus based co-occurrence statistics as a measure of association strength we computed individual neighborhoods for single neutral words comprised of the 10 words with the largest association strength. We then selected neutral words according to the valence of the associated words included in the neighborhoods, which were either mostly positive, mostly negative, mostly neutral or mixed positive and negative, and tested them using a valence decision task (VDT). The data showed that the valence of semantic neighbors can predict valence judgments to neutral words. However, all but the positive neighborhood items revealed a high tendency to elicit negative responses. For the positive and negative neighborhood categories responses congruent with the neighborhood's valence were faster than incongruent responses. We interpret this effect as a semantic network process that supports the evaluation of neutral words by assessing the valence of the associative semantic neighborhood. In this perspective, valence is considered a semantic super-feature, at least partially represented in associative activation patterns of semantic networks.

MMDB: Entrez’s 3D-structure database

PubMed Central

Wang, Yanli; Anderson, John B.; Chen, Jie; Geer, Lewis Y.; He, Siqian; Hurwitz, David I.; Liebert, Cynthia A.; Madej, Thomas; Marchler, Gabriele H.; Marchler-Bauer, Aron; Panchenko, Anna R.; Shoemaker, Benjamin A.; Song, James S.; Thiessen, Paul A.; Yamashita, Roxanne A.; Bryant, Stephen H.

2002-01-01

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez’s 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez’s search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez’s Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure. PMID:11752307

Pericytes of the neurovascular unit: Key functions and signaling pathways

PubMed Central

Sweeney, Melanie D.; Ayyadurai, Shiva; Zlokovic, Berislav V.

2017-01-01

Pericytes are vascular mural cells embedded in the basement membrane of blood microvessels. They extend their processes along capillaries, pre-capillary arterioles, and post-capillary venules. The central nervous system (CNS) pericytes are uniquely positioned within the neurovascular unit between endothelial cells, astrocytes, and neurons. They integrate, coordinate, and process signals from their neighboring cells to generate diverse functional responses that are critical for CNS functions in health and disease including regulation of the blood-brain barrier permeability, angiogenesis, clearance of toxic metabolites, capillary hemodynamic responses, neuroinflammation, and stem cell activity. Here, we examine the key signaling pathways between pericytes and their neighboring endothelial cells, astrocytes, and neurons that control neurovascular functions. We also review the role of pericytes in different CNS disorders including rare monogenic diseases and complex neurological disorders such as Alzheimer's disease and brain tumors. Finally, we discuss directions for future studies. PMID:27227366

The probability of misassociation between neighboring targets

NASA Astrophysics Data System (ADS)

Areta, Javier A.; Bar-Shalom, Yaakov; Rothrock, Ronald

2008-04-01

This paper presents procedures to calculate the probability that the measurement originating from an extraneous target will be (mis)associated with a target of interest for the cases of Nearest Neighbor and Global association. It is shown that these misassociation probabilities depend, under certain assumptions, on a particular - covariance weighted - norm of the difference between the targets' predicted measurements. For the Nearest Neighbor association, the exact solution, obtained for the case of equal innovation covariances, is based on a noncentral chi-square distribution. An approximate solution is also presented for the case of unequal innovation covariances. For the Global case an approximation is presented for the case of "similar" innovation covariances. In the general case of unequal innovation covariances where this approximation fails, an exact method based on the inversion of the characteristic function is presented. The theoretical results, confirmed by Monte Carlo simulations, quantify the benefit of Global vs. Nearest Neighbor association. These results are applied to problems of single sensor as well as centralized fusion architecture multiple sensor tracking.

An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images.

PubMed

Feng, Yuan; Dong, Fenglin; Xia, Xiaolong; Hu, Chun-Hong; Fan, Qianmin; Hu, Yanle; Gao, Mingyuan; Mutic, Sasa

2017-07-01

Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images. To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM. Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints. Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the potential application of the method in breast tumor CAD and other US-guided procedures. © 2017 American Association of Physicists in Medicine.

Breaking the polar-nonpolar division in solvation free energy prediction.

PubMed

Wang, Bao; Wang, Chengzhang; Wu, Kedi; Wei, Guo-Wei

2018-02-05

Implicit solvent models divide solvation free energies into polar and nonpolar additive contributions, whereas polar and nonpolar interactions are inseparable and nonadditive. We present a feature functional theory (FFT) framework to break this ad hoc division. The essential ideas of FFT are as follows: (i) representability assumption: there exists a microscopic feature vector that can uniquely characterize and distinguish one molecule from another; (ii) feature-function relationship assumption: the macroscopic features, including solvation free energy, of a molecule is a functional of microscopic feature vectors; and (iii) similarity assumption: molecules with similar microscopic features have similar macroscopic properties, such as solvation free energies. Based on these assumptions, solvation free energy prediction is carried out in the following protocol. First, we construct a molecular microscopic feature vector that is efficient in characterizing the solvation process using quantum mechanics and Poisson-Boltzmann theory. Microscopic feature vectors are combined with macroscopic features, that is, physical observable, to form extended feature vectors. Additionally, we partition a solvation dataset into queries according to molecular compositions. Moreover, for each target molecule, we adopt a machine learning algorithm for its nearest neighbor search, based on the selected microscopic feature vectors. Finally, from the extended feature vectors of obtained nearest neighbors, we construct a functional of solvation free energy, which is employed to predict the solvation free energy of the target molecule. The proposed FFT model has been extensively validated via a large dataset of 668 molecules. The leave-one-out test gives an optimal root-mean-square error (RMSE) of 1.05 kcal/mol. FFT predictions of SAMPL0, SAMPL1, SAMPL2, SAMPL3, and SAMPL4 challenge sets deliver the RMSEs of 0.61, 1.86, 1.64, 0.86, and 1.14 kcal/mol, respectively. Using a test set of 94 molecules and its associated training set, the present approach was carefully compared with a classic solvation model based on weighted solvent accessible surface area. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Comprehensive Biothreat Cluster Identification by PCR/Electrospray-Ionization Mass Spectrometry

PubMed Central

Sampath, Rangarajan; Mulholland, Niveen; Blyn, Lawrence B.; Massire, Christian; Whitehouse, Chris A.; Waybright, Nicole; Harter, Courtney; Bogan, Joseph; Miranda, Mary Sue; Smith, David; Baldwin, Carson; Wolcott, Mark; Norwood, David; Kreft, Rachael; Frinder, Mark; Lovari, Robert; Yasuda, Irene; Matthews, Heather; Toleno, Donna; Housley, Roberta; Duncan, David; Li, Feng; Warren, Robin; Eshoo, Mark W.; Hall, Thomas A.; Hofstadler, Steven A.; Ecker, David J.

2012-01-01

Technology for comprehensive identification of biothreats in environmental and clinical specimens is needed to protect citizens in the case of a biological attack. This is a challenge because there are dozens of bacterial and viral species that might be used in a biological attack and many have closely related near-neighbor organisms that are harmless. The biothreat agent, along with its near neighbors, can be thought of as a biothreat cluster or a biocluster for short. The ability to comprehensively detect the important biothreat clusters with resolution sufficient to distinguish the near neighbors with an extremely low false positive rate is required. A technological solution to this problem can be achieved by coupling biothreat group-specific PCR with electrospray ionization mass spectrometry (PCR/ESI-MS). The biothreat assay described here detects ten bacterial and four viral biothreat clusters on the NIAID priority pathogen and HHS/USDA select agent lists. Detection of each of the biothreat clusters was validated by analysis of a broad collection of biothreat organisms and near neighbors prepared by spiking biothreat nucleic acids into nucleic acids extracted from filtered environmental air. Analytical experiments were carried out to determine breadth of coverage, limits of detection, linearity, sensitivity, and specificity. Further, the assay breadth was demonstrated by testing a diverse collection of organisms from each biothreat cluster. The biothreat assay as configured was able to detect all the target organism clusters and did not misidentify any of the near-neighbor organisms as threats. Coupling biothreat cluster-specific PCR to electrospray ionization mass spectrometry simultaneously provides the breadth of coverage, discrimination of near neighbors, and an extremely low false positive rate due to the requirement that an amplicon with a precise base composition of a biothreat agent be detected by mass spectrometry. PMID:22768032

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

Matthews, Melissa M.; Thomas, Justin M.; Zheng, Yuxuan

Adenosine deaminases acting on RNA (ADARs) are editing enzymes that convert adenosine to inosine in duplex RNA, a modification reaction with wide-ranging consequences in RNA function. Understanding of the ADAR reaction mechanism, the origin of editing-site selectivity, and the effect of mutations is limited by the lack of high-resolution structural data for complexes of ADARs bound to substrate RNAs. In this paper, we describe four crystal structures of the human ADAR2 deaminase domain bound to RNA duplexes bearing a mimic of the deamination reaction intermediate. These structures, together with structure-guided mutagenesis and RNA-modification experiments, explain the basis of the ADARmore » deaminase domain's dsRNA specificity, its base-flipping mechanism, and its nearest-neighbor preferences. In addition, we identified an ADAR2-specific RNA-binding loop near the enzyme active site, thus rationalizing differences in selectivity observed between different ADARs. In conclusion, our results provide a structural framework for understanding the effects of ADAR mutations associated with human disease.« less

Structure and Dynamics of Zr6O8 Metal-Organic Framework Node Surfaces Probed with Ethanol Dehydration as a Catalytic Test Reaction.

PubMed

Yang, Dong; Ortuño, Manuel A; Bernales, Varinia; Cramer, Christopher J; Gagliardi, Laura; Gates, Bruce C

2018-03-14

Some metal-organic frameworks (MOFs) incorporate nodes that are metal oxide clusters such as Zr 6 O 8 . Vacancies on the node surfaces, accidental or by design, act as catalytic sites. Here, we report elucidation of the chemistry of Zr 6 O 8 nodes in the MOFs UiO-66 and UiO-67 having used infrared and nuclear magnetic resonance spectroscopies to determine the ligands on the node surfaces originating from the solvents and modifiers used in the syntheses and having elucidated the catalytic properties of the nodes for ethanol dehydration, which takes place selectively to make diethyl ether but not ethylene at 473-523 K. Density functional theory calculations show that the key to the selective catalysis is the breaking of node-linker bonds (or the accidental adjacency of open/defect sites) that allows catalytically fruitful bonding of the reactant ethanol to neighboring sites on the nodes, facilitating the bimolecular ether formation through an S N 2 mechanism.

Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection.

PubMed

Steinrueck, Magdalena; Guet, Călin C

2017-07-25

How the organization of genes on a chromosome shapes adaptation is essential for understanding evolutionary paths. Here, we investigate how adaptation to rapidly increasing levels of antibiotic depends on the chromosomal neighborhood of a drug-resistance gene inserted at different positions of the Escherichia coli chromosome. Using a dual-fluorescence reporter that allows us to distinguish gene amplifications from other up-mutations, we track in real-time adaptive changes in expression of the drug-resistance gene. We find that the relative contribution of several mutation types differs systematically between loci due to properties of neighboring genes: essentiality, expression, orientation, termination, and presence of duplicates. These properties determine rate and fitness effects of gene amplification, deletions, and mutations compromising transcriptional termination. Thus, the adaptive potential of a gene under selection is a system-property with a complex genetic basis that is specific for each chromosomal locus, and it can be inferred from detailed functional and genomic data.

Determination of the Optimal Chromosomal Location(s) for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach.

PubMed

Frimodt-Møller, Jakob; Charbon, Godefroid; Krogfelt, Karen A; Løbner-Olesen, Anders

2017-09-11

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In bacteria, the impact of the genetic context on the function of a genetic element can be difficult to assess. Several mechanisms, including topological effects, transcriptional interference from neighboring genes, and/or replication-associated gene dosage, may affect the function of a given genetic element. Here, we describe a method that permits the random integration of a DNA element into the chromosome of Escherichia coli and select the most favorable locations using a simple growth competition experiment. The method takes advantage of a well-described transposon-based system of random insertion, coupled with a selection of the fittest clone(s) by growth advantage, a procedure that is easily adjustable to experimental needs. The nature of the fittest clone(s) can be determined by whole-genome sequencing on a complex multi-clonal population or by easy gene walking for the rapid identification of selected clones. Here, the non-coding DNA region DARS2, which controls the initiation of chromosome replication in E. coli, was used as an example. The function of DARS2 is known to be affected by replication-associated gene dosage; the closer DARS2 gets to the origin of DNA replication, the more active it becomes. DARS2 was randomly inserted into the chromosome of a DARS2-deleted strain. The resultant clones containing individual insertions were pooled and competed against one another for hundreds of generations. Finally, the fittest clones were characterized and found to contain DARS2 inserted in close proximity to the original DARS2 location.

The advantages of the surface Laplacian in brain-computer interface research.

PubMed

McFarland, Dennis J

2015-09-01

Brain-computer interface (BCI) systems frequently use signal processing methods, such as spatial filtering, to enhance performance. The surface Laplacian can reduce spatial noise and aid in identification of sources. In BCI research, these two functions of the surface Laplacian correspond to prediction accuracy and signal orthogonality. In the present study, an off-line analysis of data from a sensorimotor rhythm-based BCI task dissociated these functions of the surface Laplacian by comparing nearest-neighbor and next-nearest neighbor Laplacian algorithms. The nearest-neighbor Laplacian produced signals that were more orthogonal while the next-nearest Laplacian produced signals that resulted in better accuracy. Both prediction and signal identification are important for BCI research. Better prediction of user's intent produces increased speed and accuracy of communication and control. Signal identification is important for ruling out the possibility of control by artifacts. Identifying the nature of the control signal is relevant both to understanding exactly what is being studied and in terms of usability for individuals with limited motor control. Copyright © 2014 Elsevier B.V. All rights reserved.

A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations

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

Osei-Kuffuor, Daniel; Fattebert, Jean-Luc

2014-01-01

Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N 3) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix,more » based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.« less

Cholinergic Neurons in the Basal Forebrain Promote Wakefulness by Actions on Neighboring Non-Cholinergic Neurons: An Opto-Dialysis Study.

PubMed

Zant, Janneke C; Kim, Tae; Prokai, Laszlo; Szarka, Szabolcs; McNally, James; McKenna, James T; Shukla, Charu; Yang, Chun; Kalinchuk, Anna V; McCarley, Robert W; Brown, Ritchie E; Basheer, Radhika

2016-02-10

Understanding the control of sleep-wake states by the basal forebrain (BF) poses a challenge due to the intermingled presence of cholinergic, GABAergic, and glutamatergic neurons. All three BF neuronal subtypes project to the cortex and are implicated in cortical arousal and sleep-wake control. Thus, nonspecific stimulation or inhibition studies do not reveal the roles of these different neuronal types. Recent studies using optogenetics have shown that "selective" stimulation of BF cholinergic neurons increases transitions between NREM sleep and wakefulness, implicating cholinergic projections to cortex in wake promotion. However, the interpretation of these optogenetic experiments is complicated by interactions that may occur within the BF. For instance, a recent in vitro study from our group found that cholinergic neurons strongly excite neighboring GABAergic neurons, including the subset of cortically projecting neurons, which contain the calcium-binding protein, parvalbumin (PV) (Yang et al., 2014). Thus, the wake-promoting effect of "selective" optogenetic stimulation of BF cholinergic neurons could be mediated by local excitation of GABA/PV or other non-cholinergic BF neurons. In this study, using a newly designed opto-dialysis probe to couple selective optical stimulation with simultaneous in vivo microdialysis, we demonstrated that optical stimulation of cholinergic neurons locally increased acetylcholine levels and increased wakefulness in mice. Surprisingly, the enhanced wakefulness caused by cholinergic stimulation was abolished by simultaneous reverse microdialysis of cholinergic receptor antagonists into BF. Thus, our data suggest that the wake-promoting effect of cholinergic stimulation requires local release of acetylcholine in the basal forebrain and activation of cortically projecting, non-cholinergic neurons, including the GABAergic/PV neurons. Optogenetics is a revolutionary tool to assess the roles of particular groups of neurons in behavioral functions, such as control of sleep and wakefulness. However, the interpretation of optogenetic experiments requires knowledge of the effects of stimulation on local neurotransmitter levels and effects on neighboring neurons. Here, using a novel "opto-dialysis" probe to couple optogenetics and in vivo microdialysis, we report that optical stimulation of basal forebrain (BF) cholinergic neurons in mice increases local acetylcholine levels and wakefulness. Reverse microdialysis of cholinergic antagonists within BF prevents the wake-promoting effect. This important result challenges the prevailing dictum that BF cholinergic projections to cortex directly control wakefulness and illustrates the utility of "opto-dialysis" for dissecting the complex brain circuitry underlying behavior. Copyright © 2016 the authors 0270-6474/16/362058-11$15.00/0.

Focal exposure of limited lung volumes to high-dose irradiation down-regulated organ development-related functions and up-regulated the immune response in mouse pulmonary tissues.

PubMed

Kim, Bu-Yeo; Jin, Hee; Lee, Yoon-Jin; Kang, Ga-Young; Cho, Jaeho; Lee, Yun-Sil

2016-01-27

Despite the emergence of stereotactic body radiotherapy (SBRT) for treatment of medically inoperable early-stage non-small-cell lung cancer patients, the molecular effects of focal exposure of limited lung volumes to high-dose radiation have not been fully characterized. This study was designed to identify molecular changes induced by focal high-dose irradiation using a mouse model of SBRT. Central areas of the mouse left lung were focally-irradiated (3 mm in diameter) with a single high-dose of radiation (90 Gy). Temporal changes in gene expression in the irradiated and non-irradiated neighboring lung regions were analyzed by microarray. For comparison, the long-term effect (12 months) of 20 Gy radiation on a diffuse region of lung was also measured. The majority of genes were down-regulated in the focally-irradiated lung areas at 2 to 3 weeks after irradiation. This pattern of gene expression was clearly different than gene expression in the diffuse region of lungs exposed to low-dose radiation. Ontological and pathway analyses indicated these down-regulated genes were mainly associated with organ development. Although the number was small, genes that were up-regulated after focal irradiation were associated with immune-related functions. The temporal patterns of gene expression and the associated biological functions were also similar in non-irradiated neighboring lung regions, although statistical significance was greatly reduced when compared with those from focally-irradiated areas of the lung. From network analysis of temporally regulated genes, we identified inter-related modules associated with diverse functions, including organ development and the immune response, in both the focally-irradiated regions and non-irradiated neighboring lung regions. Focal exposure of lung tissue to high-dose radiation induced expression of genes associated with organ development and the immune response. This pattern of gene expression was also observed in non-irradiated neighboring areas of lung tissue, indicating a global lung response to focal high-dose irradiation.

Phase transition and monopole densities in a nearest neighbor two-dimensional spin ice model

NASA Astrophysics Data System (ADS)

Morais, C. W.; de Freitas, D. N.; Mota, A. L.; Bastone, E. C.

2017-12-01

In this work, we show that, due to the alternating orientation of the spins in the ground state of the artificial square spin ice, the influence of a set of spins at a certain distance of a reference spin decreases faster than the expected result for the long range dipolar interaction, justifying the use of the nearest neighbor two-dimensional square spin ice model as an effective model. Using an extension of the model presented in Y. L. Xie et al., Sci. Rep. 5, 15875 (2015), considering the influence of the eight nearest neighbors of each spin on the lattice, we analyze the thermodynamics of the model and study the dependence of monopoles and string densities as a function of the temperature.

Orientation selectivity based structure for texture classification

NASA Astrophysics Data System (ADS)

Wu, Jinjian; Lin, Weisi; Shi, Guangming; Zhang, Yazhong; Lu, Liu

2014-10-01

Local structure, e.g., local binary pattern (LBP), is widely used in texture classification. However, LBP is too sensitive to disturbance. In this paper, we introduce a novel structure for texture classification. Researches on cognitive neuroscience indicate that the primary visual cortex presents remarkable orientation selectivity for visual information extraction. Inspired by this, we investigate the orientation similarities among neighbor pixels, and propose an orientation selectivity based pattern for local structure description. Experimental results on texture classification demonstrate that the proposed structure descriptor is quite robust to disturbance.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

Activity of the hypoxia-activated pro-drug TH-302 in hypoxic and perivascular regions of solid tumors and its potential to enhance therapeutic effects of chemotherapy.

PubMed

Saggar, Jasdeep K; Tannock, Ian F

2014-06-01

Many chemotherapy drugs have poor therapeutic activity in regions distant from tumor blood vessels because of poor tissue penetration and low cytotoxic activity against slowly-proliferating cells. The hypoxia-activated pro-drug TH-302 may have selective toxicity for hypoxic and neighboring cells in tumors. Here we characterize the spatial distribution and ability of TH-302 to selectively target hypoxic regions and complement the effect of doxorubicin and docetaxel by modifying biomarker distribution. Athymic nude mice bearing human breast MCF-7 or prostate PC-3 tumors were treated with doxorubicin or docetaxel respectively and TH-302 alone or in combination. Biomarkers of drug effect including γH2aX (a marker of DNA damage), cleaved caspase-3 or -6 (markers of apoptosis) and reduction in Ki-67 (a marker of cell proliferation) were quantified in tumor sections in relation to functional blood vessels (recognized by DiOC7) and hypoxia (recognized by EF5) using immunohistochemistry. γH2aX expression at 10 min and cleaved caspase-3 or -6 at 24 hr after doxorubicin or docetaxel decreased with increasing distance from tumor blood vessels, with minimal expression in hypoxic regions; maximum reduction in Ki67 levels was observed in regions closest to vasculature at 24 hr. TH-302 induced maximal cell damage in hypoxic and neighboring regions, but was also active in tumor regions closer to blood vessels. TH-302 given 4 hr before doxorubicin or docetaxel increased DNA damage and apoptosis throughout the tumor compared to chemotherapy alone. When given with doxorubicin or docetaxel, TH-302 complements and enhances anticancer effects in both perivascular and hypoxic regions but also increases toxicity. © 2013 UICC.

Dissection of a single rat muscle-tendon complex changes joint moments exerted by neighboring muscles: implications for invasive surgical interventions.

PubMed

Maas, Huub; Baan, Guus C; Huijing, Peter A

2013-01-01

The aim of this paper is to investigate mechanical functioning of a single skeletal muscle, active within a group of (previously) synergistic muscles. For this purpose, we assessed wrist angle-active moment characteristics exerted by a group of wrist flexion muscles in the rat for three conditions: (i) after resection of the upper arm skin; (ii) after subsequent distal tenotomy of flexor carpi ulnaris muscle (FCU); and (iii) after subsequent freeing of FCU distal tendon and muscle belly from surrounding tissues (MT dissection). Measurements were performed for a control group and for an experimental group after recovery (5 weeks) from tendon transfer of FCU to extensor carpi radialis (ECR) insertion. To assess if FCU tenotomy and MT dissection affects FCU contributions to wrist moments exclusively or also those of neighboring wrist flexion muscles, these data were compared to wrist angle-moment characteristics of selectively activated FCU. FCU tenotomy and MT dissection decreased wrist moments of the control group at all wrist angles tested, including also angles for which no or minimal wrist moments were measured when activating FCU exclusively. For the tendon transfer group, wrist flexion moment increased after FCU tenotomy, but to a greater extent than can be expected based on wrist extension moments exerted by selectively excited transferred FCU. We conclude that dissection of a single muscle in any surgical treatment does not only affect mechanical characteristics of the target muscle, but also those of other muscles within the same compartment. Our results demonstrate also that even after agonistic-to-antagonistic tendon transfer, mechanical interactions with previously synergistic muscles do remain present.

Missing value imputation in DNA microarrays based on conjugate gradient method.

PubMed

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

PubChem3D: Shape compatibility filtering using molecular shape quadrupoles

PubMed Central

2011-01-01

Background PubChem provides a 3-D neighboring relationship, which involves finding the maximal shape overlap between two static compound 3-D conformations, a computationally intensive step. It is highly desirable to avoid this overlap computation, especially if it can be determined with certainty that a conformer pair cannot meet the criteria to be a 3-D neighbor. As such, PubChem employs a series of pre-filters, based on the concept of volume, to remove approximately 65% of all conformer neighbor pairs prior to shape overlap optimization. Given that molecular volume, a somewhat vague concept, is rather effective, it leads one to wonder: can the existing PubChem 3-D neighboring relationship, which consists of billions of shape similar conformer pairs from tens of millions of unique small molecules, be used to identify additional shape descriptor relationships? Or, put more specifically, can one place an upper bound on shape similarity using other "fuzzy" shape-like concepts like length, width, and height? Results Using a basis set of 4.18 billion 3-D neighbor pairs identified from single conformer per compound neighboring of 17.1 million molecules, shape descriptors were computed for all conformers. These steric shape descriptors included several forms of molecular volume and shape quadrupoles, which essentially embody the length, width, and height of a conformer. For a given 3-D neighbor conformer pair, the volume and each quadrupole component (Qx, Qy, and Qz) were binned and their frequency of occurrence was examined. Per molecular volume type, this effectively produced three different maps, one per quadrupole component (Qx, Qy, and Qz), of allowed values for the similarity metric, shape Tanimoto (ST) ≥ 0.8. The efficiency of these relationships (in terms of true positive, true negative, false positive and false negative) as a function of ST threshold was determined in a test run of 13.2 billion conformer pairs not previously considered by the 3-D neighbor set. At an ST ≥ 0.8, a filtering efficiency of 40.4% of true negatives was achieved with only 32 false negatives out of 24 million true positives, when applying the separate Qx, Qy, and Qz maps in a series (Qxyz). This efficiency increased linearly as a function of ST threshold in the range 0.8-0.99. The Qx filter was consistently the most efficient followed by Qy and then by Qz. Use of a monopole volume showed the best overall performance, followed by the self-overlap volume and then by the analytic volume. Application of the monopole-based Qxyz filter in a "real world" test of 3-D neighboring of 4,218 chemicals of biomedical interest against 26.1 million molecules in PubChem reduced the total CPU cost of neighboring by between 24-38% and, if used as the initial filter, removed from consideration 48.3% of all conformer pairs at almost negligible computational overhead. Conclusion Basic shape descriptors, such as those embodied by size, length, width, and height, can be highly effective in identifying shape incompatible compound conformer pairs. When performing a 3-D search using a shape similarity cut-off, computation can be avoided by identifying conformer pairs that cannot meet the result criteria. Applying this methodology as a filter for PubChem 3-D neighboring computation, an improvement of 31% was realized, increasing the average conformer pair throughput from 154,000 to 202,000 per second per CPU core. PMID:21774809

Spatial distribution of nuclei in progressive nucleation: Modeling and application

NASA Astrophysics Data System (ADS)

Tomellini, Massimo

2018-04-01

Phase transformations ruled by non-simultaneous nucleation and growth do not lead to random distribution of nuclei. Since nucleation is only allowed in the untransformed portion of space, positions of nuclei are correlated. In this article an analytical approach is presented for computing pair-correlation function of nuclei in progressive nucleation. This quantity is further employed for characterizing the spatial distribution of nuclei through the nearest neighbor distribution function. The modeling is developed for nucleation in 2D space with power growth law and it is applied to describe electrochemical nucleation where correlation effects are significant. Comparison with both computer simulations and experimental data lends support to the model which gives insights into the transition from Poissonian to correlated nearest neighbor probability density.

Interacting steps with finite-range interactions: Analytical approximation and numerical results

NASA Astrophysics Data System (ADS)

Jaramillo, Diego Felipe; Téllez, Gabriel; González, Diego Luis; Einstein, T. L.

2013-05-01

We calculate an analytical expression for the terrace-width distribution P(s) for an interacting step system with nearest- and next-nearest-neighbor interactions. Our model is derived by mapping the step system onto a statistically equivalent one-dimensional system of classical particles. The validity of the model is tested with several numerical simulations and experimental results. We explore the effect of the range of interactions q on the functional form of the terrace-width distribution and pair correlation functions. For physically plausible interactions, we find modest changes when next-nearest neighbor interactions are included and generally negligible changes when more distant interactions are allowed. We discuss methods for extracting from simulated experimental data the characteristic scale-setting terms in assumed potential forms.

X-ray absorption spectroscopy study on SiC-side interface structure of SiO2–SiC formed by thermal oxidation in dry oxygen

NASA Astrophysics Data System (ADS)

Isomura, Noritake; Kosaka, Satoru; Kataoka, Keita; Watanabe, Yukihiko; Kimoto, Yasuji

2018-06-01

Extended X-ray absorption fine structure (EXAFS) spectroscopy is demonstrated to measure the fine atomic structure of SiO2–SiC interfaces. The SiC-side of the interface can be measured by fabricating thin SiO2 films and using SiC-selective EXAFS measurements. Fourier transforms of the oscillations of the EXAFS spectra correspond to radial-structure functions and reveal a new peak of the first nearest neighbor of Si for m-face SiC, which does not appear in measurements of the Si-face. This finding suggests that the m-face interface could include a structure with shorter Si–C distances. Numerical calculations provide additional support for this finding.

Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Bouk, Safdar H.; Sasase, Iwao

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

Percolation of localized attack on isolated and interdependent random networks

NASA Astrophysics Data System (ADS)

Shao, Shuai; Huang, Xuqing; Stanley, H. Eugene; Havlin, Shlomo

2014-03-01

Percolation properties of isolated and interdependent random networks have been investigated extensively. The focus of these studies has been on random attacks where each node in network is attacked with the same probability or targeted attack where each node is attacked with a probability being a function of its centrality, such as degree. Here we discuss a new type of realistic attacks which we call a localized attack where a group of neighboring nodes in the networks are attacked. We attack a randomly chosen node, its neighbors, and its neighbor of neighbors and so on, until removing a fraction (1 - p) of the network. This type of attack reflects damages due to localized disasters, such as earthquakes, floods and war zones in real-world networks. We study, both analytically and by simulations the impact of localized attack on percolation properties of random networks with arbitrary degree distributions and discuss in detail random regular (RR) networks, Erdős-Rényi (ER) networks and scale-free (SF) networks. We extend and generalize our theoretical and simulation results of single isolated networks to networks formed of interdependent networks.

Large margin nearest neighbor classifiers.

PubMed

Domeniconi, Carlotta; Gunopulos, Dimitrios; Peng, Jing

2005-07-01

The nearest neighbor technique is a simple and appealing approach to addressing classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with a finite number of examples due to the curse of dimensionality. Severe bias can be introduced under these conditions when using the nearest neighbor rule. The employment of a locally adaptive metric becomes crucial in order to keep class conditional probabilities close to uniform, thereby minimizing the bias of estimates. We propose a technique that computes a locally flexible metric by means of support vector machines (SVMs). The decision function constructed by SVMs is used to determine the most discriminant direction in a neighborhood around the query. Such a direction provides a local feature weighting scheme. We formally show that our method increases the margin in the weighted space where classification takes place. Moreover, our method has the important advantage of online computational efficiency over competing locally adaptive techniques for nearest neighbor classification. We demonstrate the efficacy of our method using both real and simulated data.

Ab initio calculation of atomic interactions on Al(110): implications for epitaxial growth

NASA Astrophysics Data System (ADS)

Fichthorn, Kristen; Tiwary, Yogesh

2007-03-01

Using first-principles calculations based on density-functional theory, we resolved atomic interactions between adsorbed Al atoms on Al(110). Relevant pair and trio interactions were quantified. We find that pair interactions extend to the third in-channel and second cross-channel neighbor on the anisotropic (110) surface. Beyond these distances, pair interactions are negligible. The nearest-neighbor interaction in the in-channel direction is attractive, but nearest-neighbor cross-channel interaction is repulsive. While nearest-neighbor, cross-channel repulsion does not support the experimental observation of 3D hut formation in Al/Al(110) homoepitaxial growth [1], we find that trio interactions can be significant and attractive and they support cross-channel bonding. The pair and trio interactions have direct and indirect components. We have quantified the electronic and elastic components of the indirect, substrate-mediated interactions. We also probe the influence of these interactions on the energy barriers for adatom hopping. [1] F. Buatier de Mongeot, W. Zhu, A. Molle, R. Buzio, C. Boragno, U. Valbusa, E. Wang, and Z. Zhang, Phys. Rev. Lett. 91, 016102 (2003).

Spillover-mediated feedforward-inhibition functionally segregates interneuron activity

PubMed Central

Coddington, Luke T.; Rudolph, Stephanie; Lune, Patrick Vande; Overstreet-Wadiche, Linda; Wadiche, Jacques I.

2013-01-01

Summary Neurotransmitter spillover represents a form of neural transmission not restricted to morphologically defined synaptic connections. Communication between climbing fibers (CFs) and molecular layer interneurons (MLIs) in the cerebellum is mediated exclusively by glutamate spillover. Here, we show how CF stimulation functionally segregates MLIs based on their location relative to glutamate release. Excitation of MLIs that reside within the domain of spillover diffusion coordinates inhibition of MLIs outside the diffusion limit. CF excitation of MLIs is dependent on extrasynaptic NMDA receptors that enhance the spatial and temporal spread of CF signaling. Activity mediated by functionally segregated MLIs converges onto neighboring Purkinje cells (PCs) to generate a long-lasting biphasic change in inhibition. These data demonstrate how glutamate release from single CFs modulates excitability of neighboring PCs, thus expanding the influence of CFs on cerebellar cortical activity in a manner not predicted by anatomical connectivity. PMID:23707614

Radial basis function neural networks in non-destructive determination of compound aspirin tablets on NIR spectroscopy.

PubMed

Dou, Ying; Mi, Hong; Zhao, Lingzhi; Ren, Yuqiu; Ren, Yulin

2006-09-01

The application of the second most popular artificial neural networks (ANNs), namely, the radial basis function (RBF) networks, has been developed for quantitative analysis of drugs during the last decade. In this paper, the two components (aspirin and phenacetin) were simultaneously determined in compound aspirin tablets by using near-infrared (NIR) spectroscopy and RBF networks. The total database was randomly divided into a training set (50) and a testing set (17). Different preprocessing methods (standard normal variate (SNV), multiplicative scatter correction (MSC), first-derivative and second-derivative) were applied to two sets of NIR spectra of compound aspirin tablets with different concentrations of two active components and compared each other. After that, the performance of RBF learning algorithm adopted the nearest neighbor clustering algorithm (NNCA) and the criterion for selection used a cross-validation technique. Results show that using RBF networks to quantificationally analyze tablets is reliable, and the best RBF model was obtained by first-derivative spectra.

Retrieving Coherent Receiver Function Images with Dense Arrays

NASA Astrophysics Data System (ADS)

Zhong, M.; Zhan, Z.

2016-12-01

Receiver functions highlight converted phases (e.g., Ps, PpPs, sP) and have been widely used to study seismic interfaces. With a dense array, receiver functions (RFs) at multiple stations form a RF image that can provide more robust/detailed constraints. However, due to noise in data, non-uniqueness of deconvolution, and local structures that cannot be detected across neighboring stations, traditional RF images are often noisy and hard to interpret. Previous attempts to enhance coherence by stacking RFs from multiple events or post-filtering the RF images have not produced satisfactory improvements. Here, we propose a new method to retrieve coherent RF images with dense arrays. We take advantage of the waveform coherency at neighboring stations and invert for a small number of coherent arrivals for their RFs. The new RF images contain only the coherent arrivals required to fit data well. Synthetic tests and preliminary applications on real data demonstrate that the new RF images are easier to interpret and improve our ability to infer Earth structures using receiver functions.

Directional filtering for block recovery using wavelet features

NASA Astrophysics Data System (ADS)

Hyun, Seung H.; Eom, Il K.; Kim, Yoo S.

2005-07-01

When images compressed with block-based compression techniques are transmitted over a noisy channel, unexpected block losses occur. Conventional methods that do not consider edge directions can cause blocked blurring artifacts. In this paper, we present a post-processing-based block recovery scheme using Haar wavelet features. The adaptive selection of neighboring blocks is performed based on the energy of wavelet subbands (EWS) and difference between DC values (DDC). The lost blocks are recovered by linear interpolation in the spatial domain using selected blocks. The method using only EWS performs well for horizontal and vertical edges, but not as well for diagonal edges. Conversely, only using DDC performs well for diagonal edges with the exception of line- or roof-type edge profiles. Therefore, we combine EWS and DDC for better results. The proposed directional recovery method is effective for the strong edge because exploit the varying neighboring blocks adaptively according to the edges and the directional information in the image. The proposed method outperforms the previous methods that used only fixed blocks.

A new scalable modular data acquisition system for SPECT (PET)

NASA Astrophysics Data System (ADS)

Stenstrom, P.; Rillbert, A.; Bergquist, M.; Habte, F.; Bohm, C.; Larsson, S. A.

1998-06-01

Describes a modular decentralized data acquisition system that continuously samples shaped PMT pulses from a SPECT detector. The pulse waveform data are used by signal processors to accurately reconstruct amplitude and time for each scintillation event. Data acquisition for a PMT channel is triggered in two alternative ways, either when its own signal exceeds a selected digital threshold, or when it receives a trigger pulse from one of its neighboring PMTs. The triggered region is restricted to seven, thirteen or nineteen neighboring PMT channels. Each acquisition module supports three PMT channels and connects to all other modules and a reconstruction computer via Firewire to cover the 72 channels in the Stockholm University/Karolinska Hospital cylindrical SPECT camera.

Collective motion in animal groups from a neurobiological perspective: the adaptive benefits of dynamic sensory loads and selective attention.

PubMed

Lemasson, B H; Anderson, J J; Goodwin, R A

2009-12-21

We explore mechanisms associated with collective animal motion by drawing on the neurobiological bases of sensory information processing and decision-making. The model uses simplified retinal processes to translate neighbor movement patterns into information through spatial signal integration and threshold responses. The structure provides a mechanism by which individuals can vary their sets of influential neighbors, a measure of an individual's sensory load. Sensory loads are correlated with group order and density, and we discuss their adaptive values in an ecological context. The model also provides a mechanism by which group members can identify, and rapidly respond to, novel visual stimuli.

Thyroid hormones and thyroid disease in relation to perchlorate dose and residence near a superfund site.

PubMed

Gold, Ellen B; Blount, Benjamin C; O'Neill Rasor, Marianne; Lee, Jennifer S; Alwis, Udeni; Srivastav, Anup; Kim, Kyoungmi

2013-07-01

Perchlorate is a widely occurring contaminant, which can competitively inhibit iodide uptake and thus thyroid hormone production. The health effects of chronic low dose perchlorate exposure are largely unknown. In a community-based study, we compared thyroid function and disease in women with differing likelihoods of prior and current perchlorate exposure. Residential blocks were randomly selected from areas: (1) with potential perchlorate exposure via drinking water; (2) with potential exposure to environmental contaminants; and (3) neighboring but without such exposures. Eligibility included having lived in the area for ≥6 months and aged 20-50 years during 1988-1996 (during documented drinking water well contamination). We interviewed 814 women and collected blood samples (assayed for thyroid stimulating hormone and free thyroxine) from 431 interviewed women. Daily urine samples were assayed for perchlorate and iodide for 178 premenopausal women with blood samples. We performed multivariable regression analyses comparing thyroid function and disease by residential area and by urinary perchlorate dose adjusted for urinary iodide levels. Residential location and current perchlorate dose were not associated with thyroid function or disease. No persistent effect of perchlorate on thyroid function or disease was found several years after contaminated wells were capped.

Secure and Fair Cluster Head Selection Protocol for Enhancing Security in Mobile Ad Hoc Networks

PubMed Central

Paramasivan, B.; Kaliappan, M.

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP. PMID:25143986

Secure and fair cluster head selection protocol for enhancing security in mobile ad hoc networks.

PubMed

Paramasivan, B; Kaliappan, M

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP.

The nearest neighbor and the bayes error rates.

PubMed

Loizou, G; Maybank, S J

1987-02-01

The (k, l) nearest neighbor method of pattern classification is compared to the Bayes method. If the two acceptance rates are equal then the asymptotic error rates satisfy the inequalities Ek,l + 1 ¿ E*(¿) ¿ Ek,l dE*(¿), where d is a function of k, l, and the number of pattern classes, and ¿ is the reject threshold for the Bayes method. An explicit expression for d is given which is optimal in the sense that for some probability distributions Ek,l and dE* (¿) are equal.

Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Nearest-neighbor guided evaluation of data reliability and its applications.

PubMed

Boongoen, Tossapon; Shen, Qiang

2010-12-01

The intuition of data reliability has recently been incorporated into the main stream of research on ordered weighted averaging (OWA) operators. Instead of relying on human-guided variables, the aggregation behavior is determined in accordance with the underlying characteristics of the data being aggregated. Data-oriented operators such as the dependent OWA (DOWA) utilize centralized data structures to generate reliable weights, however. Despite their simplicity, the approach taken by these operators neglects entirely any local data structure that represents a strong agreement or consensus. To address this issue, the cluster-based OWA (Clus-DOWA) operator has been proposed. It employs a cluster-based reliability measure that is effective to differentiate the accountability of different input arguments. Yet, its actual application is constrained by the high computational requirement. This paper presents a more efficient nearest-neighbor-based reliability assessment for which an expensive clustering process is not required. The proposed measure can be perceived as a stress function, from which the OWA weights and associated decision-support explanations can be generated. To illustrate the potential of this measure, it is applied to both the problem of information aggregation for alias detection and the problem of unsupervised feature selection (in which unreliable features are excluded from an actual learning process). Experimental results demonstrate that these techniques usually outperform their conventional state-of-the-art counterparts.

Hydrogel-based three-dimensional cell culture for organ-on-a-chip applications.

PubMed

Lee, Seung Hwan; Shim, Kyu Young; Kim, Bumsang; Sung, Jong Hwan

2017-05-01

Recent studies have reported that three-dimensionally cultured cells have more physiologically relevant functions than two-dimensionally cultured cells. Cells are three-dimensionally surrounded by the extracellular matrix (ECM) in complex in vivo microenvironments and interact with the ECM and neighboring cells. Therefore, replicating the ECM environment is key to the successful cell culture models. Various natural and synthetic hydrogels have been used to mimic ECM environments based on their physical, chemical, and biological characteristics, such as biocompatibility, biodegradability, and biochemical functional groups. Because of these characteristics, hydrogels have been combined with microtechnologies and used in organ-on-a-chip applications to more closely recapitulate the in vivo microenvironment. Therefore, appropriate hydrogels should be selected depending on the cell types and applications. The porosity of the selected hydrogel should be controlled to facilitate the movement of nutrients and oxygen. In this review, we describe various types of hydrogels, external stimulation-based gelation of hydrogels, and control of their porosity. Then, we introduce applications of hydrogels for organ-on-a-chip. Last, we also discuss the challenges of hydrogel-based three-dimensional cell culture techniques and propose future directions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:580-589, 2017. © 2017 American Institute of Chemical Engineers.

Alpha-beta coordination method for collective search

DOEpatents

Goldsmith, Steven Y.

2002-01-01

The present invention comprises a decentralized coordination strategy called alpha-beta coordination. The alpha-beta coordination strategy is a family of collective search methods that allow teams of communicating agents to implicitly coordinate their search activities through a division of labor based on self-selected roles and self-determined status. An agent can play one of two complementary roles. An agent in the alpha role is motivated to improve its status by exploring new regions of the search space. An agent in the beta role is also motivated to improve its status, but is conservative and tends to remain aggregated with other agents until alpha agents have clearly identified and communicated better regions of the search space. An agent can select its role dynamically based on its current status value relative to the status values of neighboring team members. Status can be determined by a function of the agent's sensor readings, and can generally be a measurement of source intensity at the agent's current location. An agent's decision cycle can comprise three sequential decision rules: (1) selection of a current role based on the evaluation of the current status data, (2) selection of a specific subset of the current data, and (3) determination of the next heading using the selected data. Variations of the decision rules produce different versions of alpha and beta behaviors that lead to different collective behavior properties.

Spatially selective formation of hydrocarbon, fluorocarbon, and hydroxyl-terminated monolayers on a microelectrode array.

PubMed

Cook, Kevin M; Nissley, Daniel A; Ferguson, Gregory S

2013-06-11

A protection-deprotection strategy, using gold oxide as a passivating layer, was used to direct the self-assembly of monolayers (SAMs) selectively at individual gold microelectrodes in an array. This approach allowed the formation of hydroxyl-terminated monolayers, without side reactions, in addition to hydrocarbon and fluorocarbon SAMs. Fluorescence microscopy was used to visualize selective dewetting of hydrophobic monolayers by an aqueous dye solution, and spatially resolved X-ray photoelectron spectroscopy was used to demonstrate a lack of cross-contamination on neighboring microelectrodes in the array.

Comparison of Control Group Generating Methods.

PubMed

Szekér, Szabolcs; Fogarassy, György; Vathy-Fogarassy, Ágnes

2017-01-01

Retrospective studies suffer from drawbacks such as selection bias. As the selection of the control group has a significant impact on the evaluation of the results, it is very important to find the proper method to generate the most appropriate control group. In this paper we suggest two nearest neighbors based control group selection methods that aim to achieve good matching between the individuals of case and control groups. The effectiveness of the proposed methods is evaluated by runtime and accuracy tests and the results are compared to the classical stratified sampling method.

Western Juniper Field Guide: Asking the Right Questions to Select Appropriate Management Actions

USDA-ARS?s Scientific Manuscript database

The rapid expansion of western juniper into neighboring plant communities during the past 130 years has been linked to increased soil erosion; reduced forage production; altered wildlife habitat; changes in plant community composition, structure, and biodiversity. Impacts of post-settlement woodland...

A Bootstrap Procedure of Propensity Score Estimation

ERIC Educational Resources Information Center

Bai, Haiyan

2013-01-01

Propensity score estimation plays a fundamental role in propensity score matching for reducing group selection bias in observational data. To increase the accuracy of propensity score estimation, the author developed a bootstrap propensity score. The commonly used propensity score matching methods: nearest neighbor matching, caliper matching, and…

Tradition over trend: Neighboring chimpanzee communities maintain differences in cultural behavior despite frequent immigration of adult females.

PubMed

Luncz, Lydia V; Boesch, Christophe

2014-07-01

The notion of animal culture has been well established mainly through research aiming at uncovering differences between populations. In chimpanzees (Pan troglodytes verus), cultural diversity has even been found in neighboring communities, where differences were observed despite frequent immigration of individuals. Female chimpanzees transfer at the onset of sexual maturity at an age, when the behavioral repertoire is fully formed. With immigrating females, behavioral variety enters the group. Little is known about the diversity and the longevity of cultural traits within a community. This study is building on previous findings of differences in hammer selection when nut cracking between neighboring communities despite similar ecological conditions. We now further investigated the diversity and maintenance of cultural traits within one chimpanzee community and were able to show high levels of uniformity in group-specific behavior. Fidelity to the behavior pattern did not vary between dispersing females and philopatric males. Furthermore, group-specific tool selection remained similar over a period of 25 years. Additionally, we present a study case on how one newly immigrant female progressively behaved more similar to her new group, suggesting that the high level of similarity in behavior is actively adopted by group members possibly even when originally expressing the behavior in another form. Taken together, our data support a cultural transmission process in adult chimpanzees, which leads to persisting cultural behavior of one community over time. © 2014 Wiley Periodicals, Inc.

Understanding the Cu-Zn brass alloys using a short-range-order cluster model: significance of specific compositions of industrial alloys

PubMed Central

Hong, H. L.; Wang, Q.; Dong, C.; Liaw, Peter K.

2014-01-01

Metallic alloys show complex chemistries that are not yet understood so far. It has been widely accepted that behind the composition selection lies a short-range-order mechanism for solid solutions. The present paper addresses this fundamental question by examining the face-centered-cubic Cu-Zn α-brasses. A new structural approach, the cluster-plus-glue-atom model, is introduced, which suits specifically for the description of short-range-order structures in disordered systems. Two types of formulas are pointed out, [Zn-Cu12]Zn1~6 and [Zn-Cu12](Zn,Cu)6, which explain the α-brasses listed in the American Society for Testing and Materials (ASTM) specifications. In these formulas, the bracketed parts represent the 1st-neighbor cluster, and each cluster is matched with one to six 2nd-neighbor Zn atoms or with six mixed (Zn,Cu) atoms. Such a cluster-based formulism describes the 1st- and 2nd-neighbor local atomic units where the solute and solvent interactions are ideally satisfied. The Cu-Ni industrial alloys are also explained, thus proving the universality of the cluster-formula approach in understanding the alloy selections. The revelation of the composition formulas for the Cu-(Zn,Ni) industrial alloys points to the common existence of simple composition rules behind seemingly complex chemistries of industrial alloys, thus offering a fundamental and practical method towards composition interpretations of all kinds of alloys. PMID:25399835

Understanding the Cu-Zn brass alloys using a short-range-order cluster model: Significance of specific compositions of industrial alloys

DOE PAGES

Hong, H. L.; Wang, Q.; Dong, C.; ...

2014-11-17

Metallic alloys show complex chemistries that are not yet understood so far. It has been widely accepted that behind the composition selection lies a short-range-order mechanism for solid solutions. The present paper addresses this fundamental question by examining the face-centered-cubic Cu-Zn α-brasses. A new structural approach, the cluster-plus-glue-atom model, is introduced, which suits specifically for the description of short-range-order structures in disordered systems. Two types of formulas are pointed out, [Zn-Cu 12]Zn 1~6 and [Zn-Cu 12](Zn,Cu) 6, which explain the α-brasses listed in the American Society for Testing and Materials (ASTM) specifications. In these formulas, the bracketed parts represent themore » 1 st-neighbor cluster, and each cluster is matched with one to six 2 nd-neighbor Zn atoms or with six mixed (Zn,Cu) atoms. Such a cluster-based formulism describes the 1 st- and 2 nd-neighbor local atomic units where the solute and solvent interactions are ideally satisfied. The Cu-Ni industrial alloys are also explained, thus proving the universality of the cluster-formula approach in understanding the alloy selections. As a result, the revelation of the composition formulas for the Cu-(Zn,Ni) industrial alloys points to the common existence of simple composition rules behind seemingly complex chemistries of industrial alloys, thus offering a fundamental and practical method towards composition interpretations of all kinds of alloys.« less

Kinship and familiarity mitigate costs of social conflict between Seychelles warbler neighbors

PubMed Central

Fairfield, Eleanor A.; Komdeur, Jan; Spurgin, Lewis G.; Richardson, David S.

2017-01-01

Because virtually all organisms compete with others in their social environment, mechanisms that reduce conflict between interacting individuals are crucial for the evolution of stable families, groups, and societies. Here, we tested whether costs of social conflict over territorial space between Seychelles warblers (Acrocephalus sechellensis) are mitigated by kin-selected (genetic relatedness) or mutualistic (social familiarity) mechanisms. By measuring longitudinal changes in individuals’ body mass and telomere length, we demonstrated that the fitness costs of territoriality are driven by a complex interplay between relatedness, familiarity, local density, and sex. Physical fights were less common at territory boundaries shared between related or familiar males. In line with this, male territory owners gained mass when living next to related or familiar males and also showed less telomere attrition when living next to male kin. Importantly, these relationships were strongest in high-density areas of the population. Males also had more rapid telomere attrition when living next to unfamiliar male neighbors, but mainly when relatedness to those neighbors was also low. In contrast, neither kinship nor familiarity was linked to body mass or telomere loss in female territory owners. Our results indicate that resolving conflict over territorial space through kin-selected or mutualistic pathways can reduce both immediate energetic costs and permanent somatic damage, thus providing an important mechanism to explain fine-scale population structure and cooperation between different social units across a broad range of taxa. PMID:29073100

General formulation of long-range degree correlations in complex networks

NASA Astrophysics Data System (ADS)

Fujiki, Yuka; Takaguchi, Taro; Yakubo, Kousuke

2018-06-01

We provide a general framework for analyzing degree correlations between nodes separated by more than one step (i.e., beyond nearest neighbors) in complex networks. One joint and four conditional probability distributions are introduced to fully describe long-range degree correlations with respect to degrees k and k' of two nodes and shortest path length l between them. We present general relations among these probability distributions and clarify the relevance to nearest-neighbor degree correlations. Unlike nearest-neighbor correlations, some of these probability distributions are meaningful only in finite-size networks. Furthermore, as a baseline to determine the existence of intrinsic long-range degree correlations in a network other than inevitable correlations caused by the finite-size effect, the functional forms of these probability distributions for random networks are analytically evaluated within a mean-field approximation. The utility of our argument is demonstrated by applying it to real-world networks.

Geographical traceability of Marsdenia tenacissima by Fourier transform infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Li, Chao; Yang, Sheng-Chao; Guo, Qiao-Sheng; Zheng, Kai-Yan; Wang, Ping-Li; Meng, Zhen-Gui

2016-01-01

A combination of Fourier transform infrared spectroscopy with chemometrics tools provided an approach for studying Marsdenia tenacissima according to its geographical origin. A total of 128 M. tenacissima samples from four provinces in China were analyzed with FTIR spectroscopy. Six pattern recognition methods were used to construct the discrimination models: support vector machine-genetic algorithms, support vector machine-particle swarm optimization, K-nearest neighbors, radial basis function neural network, random forest and support vector machine-grid search. Experimental results showed that K-nearest neighbors was superior to other mathematical algorithms after data were preprocessed with wavelet de-noising, with a discrimination rate of 100% in both the training and prediction sets. This study demonstrated that FTIR spectroscopy coupled with K-nearest neighbors could be successfully applied to determine the geographical origins of M. tenacissima samples, thereby providing reliable authentication in a rapid, cheap and noninvasive way.

Prospects of second generation artificial intelligence tools in calibration of chemical sensors.

PubMed

Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala

2005-05-01

Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.

Species richness and traits predict overyielding in stem growth in an early-successional tree diversity experiment.

PubMed

Grossman, Jake J; Cavender-Bares, Jeannine; Hobbie, Sarah E; Reich, Peter B; Montgomery, Rebecca A

2017-10-01

Over the last two decades, empirical work has established that higher biodiversity can lead to greater primary productivity; however, the importance of different aspects of biodiversity in contributing to such relationships is rarely elucidated. We assessed the relative importance of species richness, phylogenetic diversity, functional diversity, and identity of neighbors for stem growth 3 yr after seedling establishment in a tree diversity experiment in eastern Minnesota. Generally, we found that community-weighted means of key functional traits (including mycorrhizal association, leaf nitrogen and calcium, and waterlogging tolerance) as well as species richness were strong, independent predictors of stem biomass growth. More phylogenetically diverse communities did not consistently produce more biomass than expected, and the trait values or diversity of individual functional traits better predicted biomass production than did a multidimensional functional diversity metric. Furthermore, functional traits and species richness best predicted growth at the whole-plot level (12 m 2 ), whereas neighborhood composition best predicted growth at the focal tree level (0.25 m 2 ). The observed effects of biodiversity on growth appear strongly driven by positive complementary effects rather than by species-specific selection effects, suggesting that synergistic species' interactions rather than the influence of a few important species may drive overyielding. © 2017 by the Ecological Society of America.

Differential morphological, cytological and biochemical responses of two rice cultivars to coumarin

USDA-ARS?s Scientific Manuscript database

Plants are often exposed to allelochemicals in the environment produced by neighboring plants. Coumarin is a common allelochemical produced by many higher plants. Two cultivars (susceptible BS-2000 and less susceptible BR-41) of rice (Oryza sativa L.) were selected to compare their differential root...

Sediment transport-storage functions for alluvial reservoirs

Treesearch

Thomas E. Lisle; Michael Church

2000-01-01

In a drainage network, sediment is routed through a linked series of channel/valley segments (alluvial reservoirs) that are distinguished from their neighbors by their capacity to store and transport sediment.

Vector dissimilarity and clustering.

PubMed

Lefkovitch, L P

1991-04-01

Based on the description of objects by m attributes, an m-element vector dissimilarity function is defined that, unlike scalar functions, retains the distinction among attributes. This function, which satisfies the conditions for a metric, allows the definition of betweenness, which can then be used for clustering. Applications to the subset-generation phase of conditional clustering and to nearest-neighbor-type algorithms are described.

Attractor reconstruction for non-linear systems: a methodological note

USGS Publications Warehouse

Nichols, J.M.; Nichols, J.D.

2001-01-01

Attractor reconstruction is an important step in the process of making predictions for non-linear time-series and in the computation of certain invariant quantities used to characterize the dynamics of such series. The utility of computed predictions and invariant quantities is dependent on the accuracy of attractor reconstruction, which in turn is determined by the methods used in the reconstruction process. This paper suggests methods by which the delay and embedding dimension may be selected for a typical delay coordinate reconstruction. A comparison is drawn between the use of the autocorrelation function and mutual information in quantifying the delay. In addition, a false nearest neighbor (FNN) approach is used in minimizing the number of delay vectors needed. Results highlight the need for an accurate reconstruction in the computation of the Lyapunov spectrum and in prediction algorithms.

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1990-01-01

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

Symmetry and electronic structure of noble-metal nanoparticles and the role of relativity.

PubMed

Häkkinen, Hannu; Moseler, Michael; Kostko, Oleg; Morgner, Nina; Hoffmann, Margarita Astruc; von Issendorff, Bernd

2004-08-27

We present high resolution UV-photoelectron spectra of cold mass selected Cun-, Agn-, and Aun- with n=53-58. The observed electron density of states is not the expected simple electron shell structure, but is strongly influenced by electron-lattice interactions. Only Cu55- and Ag55- exhibit highly degenerate states. This is a direct consequence of their icosahedral symmetry, as is confirmed by density functional theory calculations. Neighboring sizes exhibit perturbed electronic structures, as they are formed by removal or addition of atoms to the icosahedron and therefore have lower symmetries. Gold clusters in the same size range show completely different spectra with almost no degeneracy, which indicates that they have structures of much lower symmetry. This behavior is related to strong relativistic bonding effects in gold, as demonstrated by ab initio calculations for Au55-.

Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

PubMed

Suratanee, Apichat; Plaimas, Kitiporn

2017-01-01

The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.

Comparative statics of games between relatives.

PubMed

Milchtaich, Igal

2006-03-01

According to Hamilton's theory of kin selection, species tend to evolve behavior such that each organism appears to be attempting to maximize its inclusive fitness. In particular, two neighbors are likely to help each other if the cost of doing so is less than the benefit multiplied by r, their coefficient of relatedness. Since the latter is less than unity, mutual altruism benefits both neighbors. However, is it theoretically possible that acting so as to maximize the inclusive, rather than personal, fitness may harm both parties. This may occur in strategic symmetric pairwise interactions (more specifically, nxn games), in which the outcome depends on both sides' actions. In this case, the equilibrium outcome may be less favorable to the interactants' personal fitness than if each of them acted so as to maximize the latter. This paper shows, however, that such negative effect of relatedness on fitness is incompatible with evolutionary stability. If the symmetric equilibrium strategies are evolutionarily stable, a higher coefficient of relatedness can only entail higher personal fitness for the two neighbors. This suggests that negative comparative statics as above are not likely to occur in nature.

The Nature of Bonding in Bulk Tellurium Composed of One-Dimensional Helical Chains.

PubMed

Yi, Seho; Zhu, Zhili; Cai, Xiaolin; Jia, Yu; Cho, Jun-Hyung

2018-05-07

Bulk tellurium (Te) is composed of one-dimensional (1D) helical chains which have been considered to be coupled by van der Waals (vdW) interactions. However, on the basis of first-principles density functional theory calculations, we here propose a different bonding nature between neighboring chains: i.e., helical chains made of normal covalent bonds are connected together by coordinate covalent bonds. It is revealed that the lone pairs of electrons of Te atoms participate in forming coordinate covalent bonds between neighboring chains, where each Te atom behaves as both an electron donor to neighboring chains and an electron acceptor from neighboring chains. This ligand-metal-like bonding nature in bulk Te results in the same order of bulk moduli along the directions parallel and perpendicular to the chains, contrasting with the large anisotropy of bulk moduli in vdW crystals. We further find that the electron effective masses parallel and perpendicular to the chains are almost the same as each other, consistent with the observed nearly isotropic electrical resistivity. It is thus demonstrated that the normal/coordinate covalent bonds parallel/perpendicular to the chains in bulk Te lead to a minor anisotropy in structural and transport properties.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Interconnection arrangement of routers of processor boards in array of cabinets supporting secure physical partition

DOEpatents

Tomkins, James L [Albuquerque, NM; Camp, William J [Albuquerque, NM

2007-07-17

A multiple processor computing apparatus includes a physical interconnect structure that is flexibly configurable to support selective segregation of classified and unclassified users. The physical interconnect structure includes routers in service or compute processor boards distributed in an array of cabinets connected in series on each board and to respective routers in neighboring row cabinet boards with the routers in series connection coupled to routers in series connection in respective neighboring column cabinet boards. The array can include disconnect cabinets or respective routers in all boards in each cabinet connected in a toroid. The computing apparatus can include an emulator which permits applications from the same job to be launched on processors that use different operating systems.

Moving to Mars: There and Back Again. Stress and the Psychology and Culture of Crew and Astronaut

NASA Astrophysics Data System (ADS)

Bishop, Sheryl L.

2010-10-01

The journey to explore our red neighbor will entail the application of all our terrestrial lessons learned and of some we have yet to discover. A Mars mission represents the extreme in terms of both distance and uncharted environment. The selection, monitoring and support of Mars bound crews will challenge existing technology and knowledge. The human, at the center, represents the greatest strength and the greatest weakness for a Mars mission. Human response to confined and isolated environments has been shown to be characterized by serious stressors and a Mars mission will represent the most extreme of such environments. The impact of such stressors on coping, performance, motivation, behavior, cognitive functioning and psychological well-being must be taken into account. The extraordinary duration of the mission poses special challenges in planning for mission support since very different needs may be driven by particular phases of the mission. Selection, monitoring and! support will similarly be significantly affected by anticipating potential differential characteristics and needs across the travel phases to and from Mars and the period on the planet's surface.

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B.

PubMed

Hu, Wei; Lagarias, J Clark

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. © 2017 American Society of Plant Biologists. All Rights Reserved.

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B1[OPEN

PubMed Central

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. PMID:27881727

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field

PubMed Central

Shore, Joel D.; Thurston, George M.

2018-01-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (pH-pK,W) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of pH-pK and W, and 1/W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of 74 lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (pH-pK,W) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions. PMID:26764648

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field.

PubMed

Shore, Joel D; Thurston, George M

2015-12-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (pH-pK,W) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of pH-pK and W, and 1/W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of √74 lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (pH-pK,W) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions.

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field

NASA Astrophysics Data System (ADS)

Shore, Joel D.; Thurston, George M.

2015-12-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (p H-p K ,W ) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of p H-p K and W , and 1 /W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of √{74 } lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (p H-p K ,W ) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions.

Truncated Calogero-Sutherland models

NASA Astrophysics Data System (ADS)

Pittman, S. M.; Beau, M.; Olshanii, M.; del Campo, A.

2017-05-01

A one-dimensional quantum many-body system consisting of particles confined in a harmonic potential and subject to finite-range two-body and three-body inverse-square interactions is introduced. The range of the interactions is set by truncation beyond a number of neighbors and can be tuned to interpolate between the Calogero-Sutherland model and a system with nearest and next-nearest neighbors interactions discussed by Jain and Khare. The model also includes the Tonks-Girardeau gas describing impenetrable bosons as well as an extension with truncated interactions. While the ground state wave function takes a truncated Bijl-Jastrow form, collective modes of the system are found in terms of multivariable symmetric polynomials. We numerically compute the density profile, one-body reduced density matrix, and momentum distribution of the ground state as a function of the range r and the interaction strength.

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

PubMed

Zhao, Meng; Ding, Baocang

2015-03-01

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Accurate modeling of defects in graphene transport calculations

NASA Astrophysics Data System (ADS)

Linhart, Lukas; Burgdörfer, Joachim; Libisch, Florian

2018-01-01

We present an approach for embedding defect structures modeled by density functional theory into large-scale tight-binding simulations. We extract local tight-binding parameters for the vicinity of the defect site using Wannier functions. In the transition region between the bulk lattice and the defect the tight-binding parameters are continuously adjusted to approach the bulk limit far away from the defect. This embedding approach allows for an accurate high-level treatment of the defect orbitals using as many as ten nearest neighbors while keeping a small number of nearest neighbors in the bulk to render the overall computational cost reasonable. As an example of our approach, we consider an extended graphene lattice decorated with Stone-Wales defects, flower defects, double vacancies, or silicon substitutes. We predict distinct scattering patterns mirroring the defect symmetries and magnitude that should be experimentally accessible.

Density Functional Study of Stacking Structures and Electronic Behaviors of AnE-PV Copolymer.

PubMed

Dong, Chuan-Ding; Beenken, Wichard J D

2016-10-10

In this work, we report an in-depth investigation on the π-stacking and interdigitating structures of poly(p-anthracene-ethynylene)-alt-poly(p-phenylene-vinylene) copolymer with octyl and ethyl-hexyl side chains and the resulting electronic band structures using density functional theory calculations. We found that in the π-stacking direction, the preferred stacking structure, determined by the steric effect of the branched ethyl-hexyl side chains, is featured by the anthracene-ethynylene units stacking on the phenylene-vinylene units of the neighboring chains and vice versa. This stacking structure, combined with the interdigitating structure where the branched side chains of the laterally neighboring chains are isolated, defines the energetically favorable structure of the ordered copolymer phase, which provides a good compromise between light absorption and charge-carrier transport.

Embedded-atom-method interatomic potentials from lattice inversion.

PubMed

Yuan, Xiao-Jian; Chen, Nan-Xian; Shen, Jiang; Hu, Wangyu

2010-09-22

The present work develops a physically reliable procedure for building the embedded-atom-method (EAM) interatomic potentials for the metals with fcc, bcc and hcp structures. This is mainly based on Chen-Möbius lattice inversion (Chen et al 1997 Phys. Rev. E 55 R5) and first-principles calculations. Following Baskes (Baskes et al 2007 Phys. Rev. B 75 094113), this new version of the EAM eliminates all of the prior arbitrary choices in the determination of the atomic electron density and pair potential functions. Parameterizing the universal form deduced from the calculations within the density-functional scheme for homogeneous electron gas as the embedding function, the new-type EAM potentials for Cu, Fe and Ti metals have successfully been constructed by considering interatomic interactions up to the fifth neighbor, the third neighbor and the seventh neighbor, respectively. The predictions of elastic constants, structural energy difference, vacancy formation energy and migration energy, activation energy of vacancy diffusion, latent heat of melting and relative volume change on melting all satisfactorily agree with the experimental results available or first-principles calculations. The predicted surface energies for low-index crystal faces and the melting point are in agreement with the experimental data to the same extent as those calculated by other EAM-type potentials such as the FBD-EAM, 2NN MEAM and MS-EAM. In addition, the order among the predicted low-index surface energies is also consistent with the experimental information.

High density diffusion-free nanowell arrays.

PubMed

Takulapalli, Bharath R; Qiu, Ji; Magee, D Mitchell; Kahn, Peter; Brunner, Al; Barker, Kristi; Means, Steven; Miersch, Shane; Bian, Xiaofang; Mendoza, Alex; Festa, Fernanda; Syal, Karan; Park, Jin G; LaBaer, Joshua; Wiktor, Peter

2012-08-03

Proteomics aspires to elucidate the functions of all proteins. Protein microarrays provide an important step by enabling high-throughput studies of displayed proteins. However, many functional assays of proteins include untethered intermediates or products, which could frustrate the use of planar arrays at very high densities because of diffusion to neighboring features. The nucleic acid programmable protein array (NAPPA) is a robust in situ synthesis method for producing functional proteins just-in-time, which includes steps with diffusible intermediates. We determined that diffusion of expressed proteins led to cross-binding at neighboring spots at very high densities with reduced interspot spacing. To address this limitation, we have developed an innovative platform using photolithographically etched discrete silicon nanowells and used NAPPA as a test case. This arrested protein diffusion and cross-binding. We present confined high density protein expression and display, as well as functional protein-protein interactions, in 8000 nanowell arrays. This is the highest density of individual proteins in nanovessels demonstrated on a single slide. We further present proof of principle results on ultrahigh density protein arrays capable of up to 24000 nanowells on a single slide.

An Improvement To The k-Nearest Neighbor Classifier For ECG Database

NASA Astrophysics Data System (ADS)

Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

2018-03-01

The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

Spatially weighted mutual information image registration for image guided radiation therapy.

PubMed

Park, Samuel B; Rhee, Frank C; Monroe, James I; Sohn, Jason W

2010-09-01

To develop a new metric for image registration that incorporates the (sub)pixelwise differential importance along spatial location and to demonstrate its application for image guided radiation therapy (IGRT). It is well known that rigid-body image registration with mutual information is dependent on the size and location of the image subset on which the alignment analysis is based [the designated region of interest (ROI)]. Therefore, careful review and manual adjustments of the resulting registration are frequently necessary. Although there were some investigations of weighted mutual information (WMI), these efforts could not apply the differential importance to a particular spatial location since WMI only applies the weight to the joint histogram space. The authors developed the spatially weighted mutual information (SWMI) metric by incorporating an adaptable weight function with spatial localization into mutual information. SWMI enables the user to apply the selected transform to medically "important" areas such as tumors and critical structures, so SWMI is neither dominated by, nor neglects the neighboring structures. Since SWMI can be utilized with any weight function form, the authors presented two examples of weight functions for IGRT application: A Gaussian-shaped weight function (GW) applied to a user-defined location and a structures-of-interest (SOI) based weight function. An image registration example using a synthesized 2D image is presented to illustrate the efficacy of SWMI. The convergence and feasibility of the registration method as applied to clinical imaging is illustrated by fusing a prostate treatment planning CT with a clinical cone beam CT (CBCT) image set acquired for patient alignment. Forty-one trials are run to test the speed of convergence. The authors also applied SWMI registration using two types of weight functions to two head and neck cases and a prostate case with clinically acquired CBCT/ MVCT image sets. The SWMI registration with a Gaussian weight function (SWMI-GW) was tested between two different imaging modalities: CT and MRI image sets. SWMI-GW converges 10% faster than registration using mutual information with an ROI. SWMI-GW as well as SWMI with SOI-based weight function (SWMI-SOI) shows better compensation of the target organ's deformation and neighboring critical organs' deformation. SWMI-GW was also used to successfully fuse MRI and CT images. Rigid-body image registration using our SWMI-GW and SWMI-SOI as cost functions can achieve better registration results in (a) designated image region(s) as well as faster convergence. With the theoretical foundation established, we believe SWMI could be extended to larger clinical testing.

Indirect Gas Species Monitoring Using Tunable Diode Lasers

DOEpatents

Von Drasek, William A.; Saucedo, Victor M.

2005-02-22

A method for indirect gas species monitoring based on measurements of selected gas species is disclosed. In situ absorption measurements of combustion species are used for process control and optimization. The gas species accessible by near or mid-IR techniques are limited to species that absorb in this spectral region. The absorption strength is selected to be strong enough for the required sensitivity and is selected to be isolated from neighboring absorption transitions. By coupling the gas measurement with a software sensor gas, species not accessible from the near or mid-IR absorption measurement can be predicted.

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm

PubMed Central

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request. PMID:26955638

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

NASA Astrophysics Data System (ADS)

Chao, LIANG; Ling-yao, JIA; Dong-cheng, SHI

2017-01-01

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.

Selection of Inhibitor-Resistant Viral Potassium Channels Identifies a Selectivity Filter Site that Affects Barium and Amantadine Block

PubMed Central

Fujiwara, Yuichiro; Arrigoni, Cristina; Domigan, Courtney; Ferrara, Giuseppina; Pantoja, Carlos; Thiel, Gerhard; Moroni, Anna; Minor, Daniel L.

2009-01-01

Background Understanding the interactions between ion channels and blockers remains an important goal that has implications for delineating the basic mechanisms of ion channel function and for the discovery and development of ion channel directed drugs. Methodology/Principal Findings We used genetic selection methods to probe the interaction of two ion channel blockers, barium and amantadine, with the miniature viral potassium channel Kcv. Selection for Kcv mutants that were resistant to either blocker identified a mutant bearing multiple changes that was resistant to both. Implementation of a PCR shuffling and backcrossing procedure uncovered that the blocker resistance could be attributed to a single change, T63S, at a position that is likely to form the binding site for the inner ion in the selectivity filter (site 4). A combination of electrophysiological and biochemical assays revealed a distinct difference in the ability of the mutant channel to interact with the blockers. Studies of the analogous mutation in the mammalian inward rectifier Kir2.1 show that the T→S mutation affects barium block as well as the stability of the conductive state. Comparison of the effects of similar barium resistant mutations in Kcv and Kir2.1 shows that neighboring amino acids in the Kcv selectivity filter affect blocker binding. Conclusions/Significance The data support the idea that permeant ions have an integral role in stabilizing potassium channel structure, suggest that both barium and amantadine act at a similar site, and demonstrate how genetic selections can be used to map blocker binding sites and reveal mechanistic features. PMID:19834614

Complete Genome Sequences for 59 Burkholderia Isolates, Both Pathogenic and Near Neighbor

DOE PAGES

Johnson, Shannon L.; Bishop-Lilly, Kimberly A.; Ladner, Jason T.; ...

2015-04-30

The genus Burkholderia encompasses both pathogenic (including Burkholderia mallei and Burkholderia pseudomallei, U.S. Centers for Disease Control and Prevention Category B listed), and nonpathogenic Gram-negative bacilli. Presented in this document are full genome sequences for a panel of 59 Burkholderia strains, selected to aid in detection assay development.

Structure-based Design of Cdk4/6-Specific Inhibitors

DTIC Science & Technology

2005-10-01

were selected to facilitate interactions with residues in neighboring repeats. Moreover,buried hydrophilic residues were mutated to hydrophobic res- Fio ... Russo , A. A., Tong, L., Lee, J.-O., Jeffrey, P. D., and Pavletich, N. P. (1998) tion, although we do not yet have structures for the p18"NK4c Nature 395

Magnetic state selected by magnetic dipole interaction in the kagome antiferromagnet NaBa2Mn3F11

NASA Astrophysics Data System (ADS)

Hayashida, Shohei; Ishikawa, Hajime; Okamoto, Yoshihiko; Okubo, Tsuyoshi; Hiroi, Zenji; Avdeev, Maxim; Manuel, Pascal; Hagihala, Masato; Soda, Minoru; Masuda, Takatsugu

2018-02-01

We haved studied the ground state of the classical kagome antiferromagnet NaBa2Mn3F11 . Strong magnetic Bragg peaks observed for d spacings shorter than 6.0 Å were indexed by the propagation vector of k0=(0 ,0 ,0 ) . Additional peaks with weak intensities in the d -spacing range above 8.0 Å were indexed by the incommensurate vector of k1=[0.3209 (2 ) ,0.3209 (2 ) ,0 ] and k2=[0.3338 (4 ) ,0.3338 (4 ) ,0 ] . Magnetic structure analysis unveils a 120∘ structure with the tail-chase geometry having k0 modulated by the incommensurate vector. A classical calculation of the Heisenberg kagome antiferromagnet with antiferromagnetic second-neighbor interaction, for which the ground state a k0120∘ degenerated structure, reveals that the magnetic dipole-dipole (MDD) interaction including up to the fourth neighbor terms selects the tail-chase structure. The observed modulation of the tail-chase structure is attributed to a small perturbation such as the long-range MDD interaction or the interlayer interaction.

Individual Differences in the Alignment of Structural and Functional Markers of the V5/MT Complex in Primates

PubMed Central

Large, I.; Bridge, H.; Ahmed, B.; Clare, S.; Kolasinski, J.; Lam, W. W.; Miller, K. L.; Dyrby, T. B.; Parker, A. J.; Smith, J. E. T.; Daubney, G.; Sallet, J.; Bell, A. H.; Krug, K.

2016-01-01

Extrastriate visual area V5/MT in primates is defined both structurally by myeloarchitecture and functionally by distinct responses to visual motion. Myelination is directly identifiable from postmortem histology but also indirectly by image contrast with structural magnetic resonance imaging (sMRI). First, we compared the identification of V5/MT using both sMRI and histology in Rhesus macaques. A section-by-section comparison of histological slices with in vivo and postmortem sMRI for the same block of cortical tissue showed precise correspondence in localizing heavy myelination for V5/MT and neighboring MST. Thus, sMRI in macaques accurately locates histologically defined myelin within areas known to be motion selective. Second, we investigated the functionally homologous human motion complex (hMT+) using high-resolution in vivo imaging. Humans showed considerable intersubject variability in hMT+ location, when defined with myelin-weighted sMRI signals to reveal structure. When comparing sMRI markers to functional MRI in response to moving stimuli, a region of high myelin signal was generally located within the hMT+ complex. However, there were considerable differences in the alignment of structural and functional markers between individuals. Our results suggest that variation in area identification for hMT+ based on structural and functional markers reflects individual differences in human regional brain architecture. PMID:27371764

New evidence for a multi-functional role of herbivore-induced plant volatiles in defense against herbivores.

PubMed

Rodriguez-Saona, Cesar R; Frost, Christopher J

2010-01-01

A diverse, often species-specific, array of herbivore-induced plant volatiles (HIPVs) are commonly emitted from plants after herbivore attack. Although research in the last 3 decades indicates a multi-functional role of these HIPVs, the evolutionary rationale underpinning HIPV emissions remains an open question. Many studies have documented that HIPVs can attract natural enemies, and some studies indicate that neighboring plants may eavesdrop their undamaged neighbors and induce or prime their own defenses prior to herbivore attack. Both of these ecological roles for HIPVs are risky strategies for the emitting plant. In a recent paper, we reported that most branches within a blueberry bush share limited vascular connectivity, which restricts the systemic movement of internal signals. Blueberry branches circumvent this limitation by responding to HIPVs emitted from neighboring branches of the same plant: exposure to HIPVs increases levels of defensive signaling hormones, changes their defensive status, and makes undamaged branches more resistant to herbivores. Similar findings have been reported recently for sagebrush, poplar and lima beans, where intra-plant communication played a role in activating or priming defenses against herbivores. Thus, there is increasing evidence that intra-plant communication occurs in a wide range of taxonomically unrelated plant species. While the degree to which this phenomenon increases a plant's fitness remains to be determined in most cases, we here argue that within-plant signaling provides more adaptive benefit for HIPV emissions than does between-plant signaling or attraction of predators. That is, the emission of HIPVs might have evolved primarily to protect undamaged parts of the plant against potential enemies, and neighboring plants and predators of herbivores later co-opted such HIPV signals for their own benefit.

Dipole-dipole resonance line shapes in a cold Rydberg gas

NASA Astrophysics Data System (ADS)

Richards, B. G.; Jones, R. R.

2016-04-01

We have explored the dipole-dipole mediated, resonant energy transfer reaction, 32 p3 /2+32 p3 /2→32 s +33 s , in an ensemble of cold 85Rb Rydberg atoms. Stark tuning is employed to measure the population transfer probability as a function of the total electronic energy difference between the initial and final atom-pair states over a range of Rydberg densities, 2 ×108≤ρ ≤3 ×109 cm-3. The observed line shapes provide information on the role of beyond nearest-neighbor interactions, the range of Rydberg atom separations, and the electric field inhomogeneity in the sample. The widths of the resonance line shapes increase approximately linearly with the Rydberg density and are only a factor of 2 larger than expected for two-body, nearest-neighbor interactions alone. These results are in agreement with the prediction [B. Sun and F. Robicheaux, Phys. Rev. A 78, 040701(R) (2008), 10.1103/PhysRevA.78.040701] that beyond nearest-neighbor exchange interactions should not influence the population transfer process to the degree once thought. At low densities, Gaussian rather than Lorentzian line shapes are observed due to electric field inhomogeneities, allowing us to set an upper limit for the field variation across the Rydberg sample. At higher densities, non-Lorentzian, cusplike line shapes characterized by sharp central peaks and broad wings reflect the random distribution of interatomic distances within the magneto-optical trap (MOT). These line shapes are well reproduced by an analytic expression derived from a nearest-neighbor interaction model and may serve as a useful fingerprint for characterizing the position correlation function for atoms within the MOT.

Effective model with strong Kitaev interactions for α -RuCl3

NASA Astrophysics Data System (ADS)

Suzuki, Takafumi; Suga, Sei-ichiro

2018-04-01

We use an exact numerical diagonalization method to calculate the dynamical spin structure factors of three ab initio models and one ab initio guided model for a honeycomb-lattice magnet α -RuCl3 . We also use thermal pure quantum states to calculate the temperature dependence of the heat capacity, the nearest-neighbor spin-spin correlation function, and the static spin structure factor. From the results obtained from these four effective models, we find that, even when the magnetic order is stabilized at low temperature, the intensity at the Γ point in the dynamical spin structure factors increases with increasing nearest-neighbor spin correlation. In addition, we find that the four models fail to explain heat-capacity measurements whereas two of the four models succeed in explaining inelastic-neutron-scattering experiments. In the four models, when temperature decreases, the heat capacity shows a prominent peak at a high temperature where the nearest-neighbor spin-spin correlation function increases. However, the peak temperature in heat capacity is too low in comparison with that observed experimentally. To address these discrepancies, we propose an effective model that includes strong ferromagnetic Kitaev coupling, and we show that this model quantitatively reproduces both inelastic-neutron-scattering experiments and heat-capacity measurements. To further examine the adequacy of the proposed model, we calculate the field dependence of the polarized terahertz spectra, which reproduces the experimental results: the spin-gapped excitation survives up to an onset field where the magnetic order disappears and the response in the high-field region is almost linear. Based on these numerical results, we argue that the low-energy magnetic excitation in α -RuCl3 is mainly characterized by interactions such as off-diagonal interactions and weak Heisenberg interactions between nearest-neighbor pairs, rather than by the strong Kitaev interactions.

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

Bacterial genomes lacking long-range correlations may not be modeled by low-order Markov chains: the role of mixing statistics and frame shift of neighboring genes.

PubMed

Cocho, Germinal; Miramontes, Pedro; Mansilla, Ricardo; Li, Wentian

2014-12-01

We examine the relationship between exponential correlation functions and Markov models in a bacterial genome in detail. Despite the well known fact that Markov models generate sequences with correlation function that decays exponentially, simply constructed Markov models based on nearest-neighbor dimer (first-order), trimer (second-order), up to hexamer (fifth-order), and treating the DNA sequence as being homogeneous all fail to predict the value of exponential decay rate. Even reading-frame-specific Markov models (both first- and fifth-order) could not explain the fact that the exponential decay is very slow. Starting with the in-phase coding-DNA-sequence (CDS), we investigated correlation within a fixed-codon-position subsequence, and in artificially constructed sequences by packing CDSs with out-of-phase spacers, as well as altering CDS length distribution by imposing an upper limit. From these targeted analyses, we conclude that the correlation in the bacterial genomic sequence is mainly due to a mixing of heterogeneous statistics at different codon positions, and the decay of correlation is due to the possible out-of-phase between neighboring CDSs. There are also small contributions to the correlation from bases at the same codon position, as well as by non-coding sequences. These show that the seemingly simple exponential correlation functions in bacterial genome hide a complexity in correlation structure which is not suitable for a modeling by Markov chain in a homogeneous sequence. Other results include: use of the (absolute value) second largest eigenvalue to represent the 16 correlation functions and the prediction of a 10-11 base periodicity from the hexamer frequencies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors

PubMed Central

Guo, Maozu; Guo, Yahong; Li, Jinbao; Ding, Jian; Liu, Yong; Dai, Qiguo; Li, Jin; Teng, Zhixia; Huang, Yufei

2013-01-01

Background The identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies. Methodology/Principal Findings It is known that miRNAs with similar functions are often associated with similar diseases and vice versa. Therefore, the functional similarity of two miRNAs has been successfully estimated by measuring the semantic similarity of their associated diseases. To effectively predict disease miRNAs, we calculated the functional similarity by incorporating the information content of disease terms and phenotype similarity between diseases. Furthermore, the members of miRNA family or cluster are assigned higher weight since they are more probably associated with similar diseases. A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates. Conclusions The superior performance of HDMP can be attributed to the accurate measurement of miRNA functional similarity, the weight assignment based on miRNA family or cluster, and the effective prediction based on weighted k most similar neighbors. The online prediction and analysis tool is freely available at http://nclab.hit.edu.cn/hdmpred. PMID:23950912

The distance function effect on k-nearest neighbor classification for medical datasets.

PubMed

Hu, Li-Yu; Huang, Min-Wei; Ke, Shih-Wen; Tsai, Chih-Fong

2016-01-01

K-nearest neighbor (k-NN) classification is conventional non-parametric classifier, which has been used as the baseline classifier in many pattern classification problems. It is based on measuring the distances between the test data and each of the training data to decide the final classification output. Since the Euclidean distance function is the most widely used distance metric in k-NN, no study examines the classification performance of k-NN by different distance functions, especially for various medical domain problems. Therefore, the aim of this paper is to investigate whether the distance function can affect the k-NN performance over different medical datasets. Our experiments are based on three different types of medical datasets containing categorical, numerical, and mixed types of data and four different distance functions including Euclidean, cosine, Chi square, and Minkowsky are used during k-NN classification individually. The experimental results show that using the Chi square distance function is the best choice for the three different types of datasets. However, using the cosine and Euclidean (and Minkowsky) distance function perform the worst over the mixed type of datasets. In this paper, we demonstrate that the chosen distance function can affect the classification accuracy of the k-NN classifier. For the medical domain datasets including the categorical, numerical, and mixed types of data, K-NN based on the Chi square distance function performs the best.

Individual species affect plant traits structure in their surroundings: evidence of functional mechanisms of assembly.

PubMed

Chacón-Labella, Julia; de la Cruz, Marcelino; Pescador, David S; Escudero, Adrián

2016-04-01

Evaluating community assembly through the use of functional traits is a promising tool for testing predictions arising from Niche and Coexistence theories. Although interactions among neighboring species and their inter-specific differences are known drivers of coexistence with a strong spatial signal, assessing the role of individual species on the functional structure of the community at different spatial scales remains a challenge. Here, we ask whether individual species exert a measurable effect on the spatial organization of different functional traits in local assemblages. We first propose and compute two functions that describe different aspects of functional trait organization around individual species at multiple scales: individual weighted mean area relationship and individual functional diversity area relationship. Secondly, we develop a conceptual model on the relationship and simultaneous variation of these two metrics, providing five alternative scenarios in response to the ability of some target species to modify its neighbor environment and the possible assembly mechanisms involved. Our results show that some species influence the spatial structure of specific functional traits, but their effects were always restricted to the finest spatial scales. In the basis of our conceptual model, the observed patterns point to two main mechanisms driving the functional structure of the community at the fine scale, "biotic" filtering meditated by individual species and resource partitioning driven by indirect facilitation rather than by competitive mechanisms.

Is plant evolutionary history impacting recruitment of diazotrophs and nifH expression in the rhizosphere?

PubMed

Bouffaud, Marie-Lara; Renoud, Sébastien; Moënne-Loccoz, Yvan; Muller, Daniel

2016-02-23

Plant evolutionary history influences the taxonomic composition of the root-associated bacterial community, but whether it can also modulate its functioning is unknown. Here, we tested the hypothesis that crop diversification is a significant factor determining the ecology of the functional group of nitrogen-fixing bacteria the rhizosphere of Poaceae. A greenhouse experiment was carried out using a range of Poaceae, i.e. four Zea mays varieties (from two genetic groups) and teosinte (representing maize's ancestor), sorghum (from the same Panicoideae subfamily), and wheat (from neighboring Pooideae subfamily), as well as the dicot tomato as external reference. Diazotroph rhizosphere community was characterized at 21 days in terms of size (quantitative PCR of nifH genes), composition (T-RFLP and partial sequencing of nifH alleles) and functioning (quantitative RT-PCR, T-RFLP and partial sequencing of nifH transcripts). Plant species and varieties had a significant effect on diazotroph community size and the number of nifH transcripts per root system. Contrarily to expectations, however, there was no relation between Poaceae evolutionary history and the size, diversity or expression of the rhizosphere diazotroph community. These results suggest a constant selection of this functional group through evolution for optimization of nitrogen fixation in the rhizosphere.

Is plant evolutionary history impacting recruitment of diazotrophs and nifH expression in the rhizosphere?

PubMed Central

Bouffaud, Marie-Lara; Renoud, Sébastien; Moënne-Loccoz, Yvan; Muller, Daniel

2016-01-01

Plant evolutionary history influences the taxonomic composition of the root-associated bacterial community, but whether it can also modulate its functioning is unknown. Here, we tested the hypothesis that crop diversification is a significant factor determining the ecology of the functional group of nitrogen-fixing bacteria the rhizosphere of Poaceae. A greenhouse experiment was carried out using a range of Poaceae, i.e. four Zea mays varieties (from two genetic groups) and teosinte (representing maize’s ancestor), sorghum (from the same Panicoideae subfamily), and wheat (from neighboring Pooideae subfamily), as well as the dicot tomato as external reference. Diazotroph rhizosphere community was characterized at 21 days in terms of size (quantitative PCR of nifH genes), composition (T-RFLP and partial sequencing of nifH alleles) and functioning (quantitative RT-PCR, T-RFLP and partial sequencing of nifH transcripts). Plant species and varieties had a significant effect on diazotroph community size and the number of nifH transcripts per root system. Contrarily to expectations, however, there was no relation between Poaceae evolutionary history and the size, diversity or expression of the rhizosphere diazotroph community. These results suggest a constant selection of this functional group through evolution for optimization of nitrogen fixation in the rhizosphere. PMID:26902960

Selecting a restoration technique to minimize OCR error.

PubMed

Cannon, M; Fugate, M; Hush, D R; Scovel, C

2003-01-01

This paper introduces a learning problem related to the task of converting printed documents to ASCII text files. The goal of the learning procedure is to produce a function that maps documents to restoration techniques in such a way that on average the restored documents have minimum optical character recognition error. We derive a general form for the optimal function and use it to motivate the development of a nonparametric method based on nearest neighbors. We also develop a direct method of solution based on empirical error minimization for which we prove a finite sample bound on estimation error that is independent of distribution. We show that this empirical error minimization problem is an extension of the empirical optimization problem for traditional M-class classification with general loss function and prove computational hardness for this problem. We then derive a simple iterative algorithm called generalized multiclass ratchet (GMR) and prove that it produces an optimal function asymptotically (with probability 1). To obtain the GMR algorithm we introduce a new data map that extends Kesler's construction for the multiclass problem and then apply an algorithm called Ratchet to this mapped data, where Ratchet is a modification of the Pocket algorithm . Finally, we apply these methods to a collection of documents and report on the experimental results.

Thyroid Hormones and Thyroid Disease in Relation to Perchlorate Dose and Residence Near a Superfund Site

PubMed Central

Gold, Ellen B.; Blount, Benjamin C.; Rasor, Marianne O’Neill; Lee, Jennifer S.; Alwis, Udeni; Srivastav, Anup; Kim, Kyoungmi

2013-01-01

Background Perchlorate is a widely occurring contaminant, which can competitively inhibit iodide uptake and thus thyroid hormone production. The health effects of chronic low dose perchlorate exposure are largely unknown. Objectives In a community-based study, we compared thyroid function and disease in women with differing likelihoods of prior and current perchlorate exposure. Methods Residential blocks were randomly selected from areas: 1) with potential perchlorate exposure via drinking water; 2) with potential exposure to environmental contaminants; and 3) neighboring but without such exposures. Eligibility included having lived in the area for ≥6 months and aged 20–50 years during 1988–1996 (during documented drinking water well contamination). We interviewed 814 women and collected blood samples (assayed for thyroid stimulating hormone [TSH] and free thyroxine [fT4]) from 431 interviewed women. Daily urine samples were assayed for perchlorate and iodide for 178 premenopausal women with blood samples. We performed multivariable regression analyses comparing thyroid function and disease by residential area and by urinary perchlorate dose adjusted for urinary iodide levels. Results Residential location and current perchlorate dose were not associated with thyroid function or disease. Conclusions No persistent effect of perchlorate on thyroid function or disease was found several years after contaminated wells were capped. PMID:22968349

The nearest neighbor and next nearest neighbor effects on the thermodynamic and kinetic properties of RNA base pair

NASA Astrophysics Data System (ADS)

Wang, Yujie; Wang, Zhen; Wang, Yanli; Liu, Taigang; Zhang, Wenbing

2018-01-01

The thermodynamic and kinetic parameters of an RNA base pair with different nearest and next nearest neighbors were obtained through long-time molecular dynamics simulation of the opening-closing switch process of the base pair near its melting temperature. The results indicate that thermodynamic parameters of GC base pair are dependent on the nearest neighbor base pair, and the next nearest neighbor base pair has little effect, which validated the nearest-neighbor model. The closing and opening rates of the GC base pair also showed nearest neighbor dependences. At certain temperature, the closing and opening rates of the GC pair with nearest neighbor AU is larger than that with the nearest neighbor GC, and the next nearest neighbor plays little role. The free energy landscape of the GC base pair with the nearest neighbor GC is rougher than that with nearest neighbor AU.

Selection of sleeping trees in pileated gibbons (Hylobates pileatus).

PubMed

Phoonjampa, Rungnapa; Koenig, Andreas; Borries, Carola; Gale, George A; Savini, Tommaso

2010-06-01

Selection and use patterns of sleeping sites in nonhuman primates are suggested to have multiple functions, such as predation avoidance, but they might be further affected by range defense as well as foraging constraints or other factors. Here, we investigate sleeping tree selection by the male and female members of one group of pileated gibbons (Hylobates pileatus) at Khao Ang Rue Nai Wildlife Sanctuary, Thailand. Data were collected on 113 nights, between September 2006 and January 2009, yielding data on 201 sleeping tree choices (107 by the female and 94 by the male) and on the characteristics of 71 individual sleeping trees. Each sleeping tree and all trees > or =40 cm diameter at breast height (DBH) in the home range were assessed (height, DBH, canopy structure, liana load) and mapped using a GPS. The gibbons preferentially selected tall (mean=38.5 m), emergent trees without lianas. The majority of the sleeping trees (53.5%) were used only once and consecutive reuse was rare (9.5%). Sleeping trees were closer to the last feeding tree of the evening than to the first feeding tree in the morning, and sleeping trees were located in the overlap areas with neighbors less often than expected based on time spent in these areas. These results suggest avoidance of predators as the main factor influencing sleeping tree selection in pileated gibbons. However, other non-mutually exclusive factors may be involved as well. (c) 2010 Wiley-Liss, Inc.

Evolution of the pygmy phenotype: evidence of positive selection fro genome-wide scans in African, Asian, and Melanesian pygmies.

PubMed

Migliano, Andrea Bamberg; Romero, Irene Gallego; Metspalu, Mait; Leavesley, Matthew; Pagani, Luca; Antao, Tiago; Huang, Da-Wei; Sherman, Brad T; Siddle, Katharine; Scholes, Clarissa; Hudjashov, Georgi; Kaitokai, Elton; Babalu, Avis; Belatti, Maggie; Cagan, Alex; Hopkinshaw, Byrony; Shaw, Colin; Nelis, Mari; Metspalu, Ene; Mägi, Reedik; Lempicki, Richard A; Villems, Richard; Lahr, Marta Mirazon; Kivisild, Toomas

2013-01-01

Human pygmy populations inhabit different regions of the world, from Africa to Melanesia. In Asia, short-statured populations are often referred to as "negritos." Their short stature has been interpreted as a consequence of thermoregulatory, nutritional, and/or locomotory adaptations to life in tropical forests. A more recent hypothesis proposes that their stature is the outcome of a life history trade-off in high-mortality environments, where early reproduction is favored and, consequently, early sexual maturation and early growth cessation have coevolved. Some serological evidence of deficiencies in the growth hormone/insulin-like growth factor axis have been previously associated with pygmies' short stature. Using genome-wide single-nucleotide polymorphism genotype data, we first tested whether different negrito groups living in the Philippines and Papua New Guinea are closely related and then investigated genomic signals of recent positive selection in African, Asian, and Papuan pygmy populations. We found that negritos in the Philippines and Papua New Guinea are genetically more similar to their nonpygmy neighbors than to one another and have experienced positive selection at different genes. These results indicate that geographically distant pygmy groups are likely to have evolved their short stature independently. We also found that selection on common height variants is unlikely to explain their short stature and that different genes associated with growth, thyroid function, and sexual development are under selection in different pygmy groups. Copyright © 2013 Wayne State University Press, Detroit, Michigan 48201-1309.

Feature weight estimation for gene selection: a local hyperlinear learning approach

PubMed Central

2014-01-01

Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071

Spatial clustering of pixels of a multispectral image

DOEpatents

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

Neighboring Optimal Aircraft Guidance in a General Wind Environment

NASA Technical Reports Server (NTRS)

Jardin, Matthew R. (Inventor)

2003-01-01

Method and system for determining an optimal route for an aircraft moving between first and second waypoints in a general wind environment. A selected first wind environment is analyzed for which a nominal solution can be determined. A second wind environment is then incorporated; and a neighboring optimal control (NOC) analysis is performed to estimate an optimal route for the second wind environment. In particular examples with flight distances of 2500 and 6000 nautical miles in the presence of constant or piecewise linearly varying winds, the difference in flight time between a nominal solution and an optimal solution is 3.4 to 5 percent. Constant or variable winds and aircraft speeds can be used. Updated second wind environment information can be provided and used to obtain an updated optimal route.

Automated diagnosis of epilepsy using CWT, HOS and texture parameters.

PubMed

Acharya, U Rajendra; Yanti, Ratna; Zheng, Jia Wei; Krishnan, M Muthu Rama; Tan, Jen Hong; Martis, Roshan Joy; Lim, Choo Min

2013-06-01

Epilepsy is a chronic brain disorder which manifests as recurrent seizures. Electroencephalogram (EEG) signals are generally analyzed to study the characteristics of epileptic seizures. In this work, we propose a method for the automated classification of EEG signals into normal, interictal and ictal classes using Continuous Wavelet Transform (CWT), Higher Order Spectra (HOS) and textures. First the CWT plot was obtained for the EEG signals and then the HOS and texture features were extracted from these plots. Then the statistically significant features were fed to four classifiers namely Decision Tree (DT), K-Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) to select the best classifier. We observed that the SVM classifier with Radial Basis Function (RBF) kernel function yielded the best results with an average accuracy of 96%, average sensitivity of 96.9% and average specificity of 97% for 23.6 s duration of EEG data. Our proposed technique can be used as an automatic seizure monitoring software. It can also assist the doctors to cross check the efficacy of their prescribed drugs.

Selective autophagy limits cauliflower mosaic virus infection by NBR1-mediated targeting of viral capsid protein and particles

PubMed Central

Hafrén, Anders; Macia, Jean-Luc; Love, Andrew J.; Milner, Joel J.; Drucker, Martin; Hofius, Daniel

2017-01-01

Autophagy plays a paramount role in mammalian antiviral immunity including direct targeting of viruses and their individual components, and many viruses have evolved measures to antagonize or even exploit autophagy mechanisms for the benefit of infection. In plants, however, the functions of autophagy in host immunity and viral pathogenesis are poorly understood. In this study, we have identified both anti- and proviral roles of autophagy in the compatible interaction of cauliflower mosaic virus (CaMV), a double-stranded DNA pararetrovirus, with the model plant Arabidopsis thaliana. We show that the autophagy cargo receptor NEIGHBOR OF BRCA1 (NBR1) targets nonassembled and virus particle-forming capsid proteins to mediate their autophagy-dependent degradation, thereby restricting the establishment of CaMV infection. Intriguingly, the CaMV-induced virus factory inclusions seem to protect against autophagic destruction by sequestering capsid proteins and coordinating particle assembly and storage. In addition, we found that virus-triggered autophagy prevents extensive senescence and tissue death of infected plants in a largely NBR1-independent manner. This survival function significantly extends the timespan of virus production, thereby increasing the chances for virus particle acquisition by aphid vectors and CaMV transmission. Together, our results provide evidence for the integration of selective autophagy into plant immunity against viruses and reveal potential viral strategies to evade and adapt autophagic processes for successful pathogenesis. PMID:28223514

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.

PubMed

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-03-07

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

Liquid li structure and dynamics: A comparison between OFDFT and second nearest-neighbor embedded-atom method

DOE PAGES

Chen, Mohan; Vella, Joseph R.; Panagiotopoulos, Athanassios Z.; ...

2015-04-08

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital-free (OF) first-principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest-neighbor embedded-atom method potential. The properties we studied include the dynamic structure factor, the self-diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Our simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can accessmore » a broader temperature range and longer time scales. The combination of first-principles and classical simulations is a powerful tool for studying properties of liquid lithium.« less

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

A study of the diffusional behavior of a two-phase metal matrix composite exposed to a high temperature environment

NASA Technical Reports Server (NTRS)

Tenney, D. R.

1974-01-01

The progress of diffusion-controlled filament-matrix interaction in a metal matrix composite where the filaments and matrix comprise a two-phase binary alloy system was studied by mathematically modeling compositional changes resulting from prolonged elevated temperature exposure. The analysis treats a finite, diffusion-controlled, two-phase moving-interface problem by means of a variable-grid finite-difference technique. The Ni-W system was selected as an example system. Modeling was carried out for the 1000 to 1200 C temperature range for unidirectional composites containing from 6 to 40 volume percent tungsten filaments in a Ni matrix. The results are displayed to show both the change in filament diameter and matrix composition as a function of exposure time. Compositional profiles produced between first and second nearest neighbor filaments were calculated by superposition of finite-difference solutions of the diffusion equations.

Activation of VTA GABA neurons disrupts reward consumption

PubMed Central

van Zessen, Ruud; Phillips, Jana L.; Budygin, Evgeny A.; Stuber, Garret D.

2012-01-01

The activity of Ventral Tegmental Area (VTA) dopamine (DA) neurons promotes behavioral responses to rewards and environmental stimuli that predict them. VTA GABA inputs synapse directly onto DA neurons and may regulate DA neuronal activity to alter reward-related behaviors, however, the functional consequences of selective activation of VTA GABA neurons remains unknown. Here, we show that in vivo optogenetic activation of VTA GABA neurons disrupts reward consummatory behavior, but not conditioned anticipatory behavior in response to reward-predictive cues. In addition, direct activation of VTA GABA projections to the nucleus accumbens (NAc) resulted in detectable GABA release, but did not alter reward consumption. Furthermore, optogenetic stimulation of VTA GABA neurons directly suppressed the activity and excitability of neighboring DA neurons, as well as the release of DA in the NAc, suggesting that the dynamic interplay between VTA DA and GABA neurons can control the initiation and termination of reward-related behaviors. PMID:22445345

Managing the complexity of communication: regulation of gap junctions by post-translational modification

PubMed Central

Axelsen, Lene N.; Calloe, Kirstine; Holstein-Rathlou, Niels-Henrik; Nielsen, Morten S.

2013-01-01

Gap junctions are comprised of connexins that form cell-to-cell channels which couple neighboring cells to accommodate the exchange of information. The need for communication does, however, change over time and therefore must be tightly controlled. Although the regulation of connexin protein expression by transcription and translation is of great importance, the trafficking, channel activity and degradation are also under tight control. The function of connexins can be regulated by several post translational modifications, which affect numerous parameters; including number of channels, open probability, single channel conductance or selectivity. The most extensively investigated post translational modifications are phosphorylations, which have been documented in all mammalian connexins. Besides phosphorylations, some connexins are known to be ubiquitinated, SUMOylated, nitrosylated, hydroxylated, acetylated, methylated, and γ-carboxyglutamated. The aim of the present review is to summarize our current knowledge of post translational regulation of the connexin family of proteins. PMID:24155720

Norrin/Frizzled4 signaling in retinal vascular development and blood brain barrier plasticity.

PubMed

Wang, Yanshu; Rattner, Amir; Zhou, Yulian; Williams, John; Smallwood, Philip M; Nathans, Jeremy

2012-12-07

Norrin/Frizzled4 (Fz4) signaling activates the canonical Wnt pathway to control retinal vascular development. Using genetically engineered mice, we show that precocious Norrin production leads to premature retinal vascular invasion and delayed Norrin production leads to characteristic defects in intraretinal vascular architecture. In genetic mosaics, wild-type endothelial cells (ECs) instruct neighboring Fz4(-/-) ECs to produce an architecturally normal mosaic vasculature, a cell nonautonomous effect. However, over the ensuing weeks, Fz4(-/-) ECs are selectively eliminated from the mosaic vasculature, implying the existence of a quality control program that targets defective ECs. In the adult retina and cerebellum, gain or loss of Norrin/Fz4 signaling results in a cell-autonomous gain or loss, respectively, of blood retina barrier and blood brain barrier function, indicating an ongoing requirement for Frizzled signaling in barrier maintenance and substantial plasticity in mature CNS vascular structure. Copyright © 2012 Elsevier Inc. All rights reserved.

Structures, stability and electronic properties of bimetallic Cun-1Sc and Cun-2Sc2 (n = 2-7) clusters

NASA Astrophysics Data System (ADS)

Li, Zhi; Zhao, Zhen; Zhou, Zhonghao; Wang, Qi

2018-02-01

To investigate the interface between the main phases of Cu-Sc alloys, the structures, stability and electronic properties of bimetallic Cun-1Sc and Cun-2Sc2 (n = 2-7) clusters are systematically calculated by the GGA-PW91 functional. The results reveal that the structures of Cun-1Sc and Cun-2Sc2 (n = 2-7) clusters inherited those of pure Cun (n = 2-7) clusters and they maintained higher symmetry. Cu5Sc cluster possesses more stable than its neighbors while Cu2Sc2 cluster is less stable than its neighbors by binding energy. Cu5Sc cluster possesses the highest kinetic stability of Cun-1Sc clusters and CuSc2, Cu3Sc2 and Cu5Sc2 clusters possess higher kinetic stability than their neighbors by HOMO-LUMO gap. NBO analysis reveals that Cu-Sc atoms have less pd orbital hybridization in the Sc doping Cun (n = 2-7) clusters.

Effects of environmental cadmium and lead exposure on adults neighboring a discharge: Evidences of adverse health effects.

PubMed

Cabral, Mathilde; Toure, Aminata; Garçon, Guillaume; Diop, Cheikh; Bouhsina, Saâd; Dewaele, Dorothée; Cazier, Fabrice; Courcot, Dominique; Tall-Dia, Anta; Shirali, Pirouz; Diouf, Amadou; Fall, Mamadou; Verdin, Anthony

2015-11-01

The purpose of the study was to determine Pb and Cd concentrations in humans and to assess the effect of co-exposure to these metals on biomarkers of oxidative stress and nephrotoxicity. Blood and urine levels of Pb and Cd, oxidative stress and urinary renal biomarkers were measured in 77 subjects neighboring a discharge and 52 in the control site. Exposed subjects showed significantly higher levels of lead and cadmium in blood and urine than the controls. Excessive production of reactive oxygen species induced by these metals in exposed subjects conducted to a decrease in antioxidant defense system (GPx, Selenium, GSH) and an increase in lipid peroxidation (MDA). Moreover, changes in markers of nephrotoxicity (high urinary concentrations of total protein, RBP and CC16, as well as GSTα and LDH increased activities) suggested the occurrence of discrete and early signs of impaired renal function for the discharge neighboring population. Copyright © 2015 Elsevier Ltd. All rights reserved.

RNA-Seq Mouse Brain Regions Expression Data Analysis: Focus on ApoE Functional Network

PubMed

Babenko, Vladimir N; Smagin, Dmitry A; Kudryavtseva, Natalia N

2017-09-13

ApoE expression status was proved to be a highly specific marker of energy metabolism rate in the brain. Along with its neighbor, Translocase of Outer Mitochondrial Membrane 40 kDa (TOMM40) which is involved in mitochondrial metabolism, the corresponding genomic region constitutes the neuroenergetic hotspot. Using RNA-Seq data from a murine model of chronic stress a significant positive expression coordination of seven neighboring genes in ApoE locus in five brain regions was observed. ApoE maintains one of the highest absolute expression values genome-wide, implying that ApoE can be the driver of the neighboring gene expression alteration observed under stressful loads. Notably, we revealed the highly statistically significant increase of ApoE expression in the hypothalamus of chronically aggressive (FDR < 0.007) and defeated (FDR < 0.001) mice compared to the control. Correlation analysis revealed a close association of ApoE and proopiomelanocortin (Pomc) gene expression profiles implying the putative neuroendocrine stress response background of ApoE expression elevation therein.

Nearest-neighbor Kitaev exchange blocked by charge order in electron-doped α -RuCl3

NASA Astrophysics Data System (ADS)

Koitzsch, A.; Habenicht, C.; Müller, E.; Knupfer, M.; Büchner, B.; Kretschmer, S.; Richter, M.; van den Brink, J.; Börrnert, F.; Nowak, D.; Isaeva, A.; Doert, Th.

2017-10-01

A quantum spin liquid might be realized in α -RuCl3 , a honeycomb-lattice magnetic material with substantial spin-orbit coupling. Moreover, α -RuCl3 is a Mott insulator, which implies the possibility that novel exotic phases occur upon doping. Here, we study the electronic structure of this material when intercalated with potassium by photoemission spectroscopy, electron energy loss spectroscopy, and density functional theory calculations. We obtain a stable stoichiometry at K0.5RuCl3 . This gives rise to a peculiar charge disproportionation into formally Ru2 + (4 d6 ) and Ru3 + (4 d5 ). Every Ru 4 d5 site with one hole in the t2 g shell is surrounded by nearest neighbors of 4 d6 character, where the t2 g level is full and magnetically inert. Thus, each type of Ru site forms a triangular lattice, and nearest-neighbor interactions of the original honeycomb are blocked.

Collective coherence in nearest neighbor coupled metamaterials: A metasurface ruler equation

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

Xu, Ningning; Zhang, Weili, E-mail: weili.zhang@okstate.edu; Singh, Ranjan, E-mail: ranjans@ntu.edu.sg

The collective coherent interactions in a meta-atom lattice are the key to myriad applications and functionalities offered by metasurfaces. We demonstrate a collective coherent response of the nearest neighbor coupled split-ring resonators whose resonance shift decays exponentially in the strong near-field coupled regime. This occurs due to the dominant magnetic coupling between the nearest neighbors which leads to the decay of the electromagnetic near fields. Based on the size scaling behavior of the different periodicity metasurfaces, we identified a collective coherent metasurface ruler equation. From the coherent behavior, we also show that the near-field coupling in a metasurface lattice existsmore » even when the periodicity exceeds the resonator size. The identification of a universal coherence in metasurfaces and their scaling behavior would enable the design of novel metadevices whose spectral tuning response based on near-field effects could be calibrated across microwave, terahertz, infrared, and the optical parts of the electromagnetic spectrum.« less

Kinetic Models for Topological Nearest-Neighbor Interactions

NASA Astrophysics Data System (ADS)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Ground-state entropy of the potts antiferromagnet with next-nearest-neighbor spin-spin couplings on strips of the square lattice

PubMed

Chang; Shrock

2000-10-01

We present exact calculations of the zero-temperature partition function (chromatic polynomial) and W(q), the exponent of the ground-state entropy, for the q-state Potts antiferromagnet with next-nearest-neighbor spin-spin couplings on square lattice strips, of width L(y)=3 and L(y)=4 vertices and arbitrarily great length Lx vertices, with both free and periodic boundary conditions. The resultant values of W for a range of physical q values are compared with each other and with the values for the full two-dimensional lattice. These results give insight into the effect of such nonnearest-neighbor couplings on the ground-state entropy. We show that the q=2 (Ising) and q=4 Potts antiferromagnets have zero-temperature critical points on the Lx-->infinity limits of the strips that we study. With the generalization of q from Z+ to C, we determine the analytic structure of W(q) in the q plane for the various cases.

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

ZEA-TDMA: design and system level implementation of a TDMA protocol for anonymous wireless networks

NASA Astrophysics Data System (ADS)

Banerjee, Debasmit; Dong, Bo; Biswas, Subir

2013-05-01

Wireless sensor network used in military applications may be deployed in hostile environments, where privacy and security is of primary concern. This can lead to the formation of a trust-based sub-network among mutually-trusting nodes. However, designing a TDMA MAC protocol is very challenging in situations where such multiple sub-networks coexist, since TDMA protocols require node identity information for slot assignments. This paper introduces a novel distributed TDMA MAC protocol, ZEA-TDMA (Zero Exposure Anonymous TDMA), for anonymous wireless networks. ZEA-TDMA achieves slot allocation with strict anonymity constraints, i.e. without nodes having to exchange any identity revealing information. By using just the relative time of arrival of packets and a novel technique of wireless collision-detection and resolution for fixed packetsizes, ZEA-TDMA is able to achieve MAC slot-allocation which is described as follows. Initially, a newly joined node listens to its one-hop neighborhood channel usage and creates a slot allocation table based on its own relative time, and finally, selects a slot that is collision free within its one-hop neighborhood. The selected slot can however cause hidden collisions with a two-hop neighbor of the node. These collisions are resolved by a common neighbor of the colliding nodes, which first detects the collision, and then resolve them using an interrupt packet. ZEA-TDMA provides the following features: a) it is a TDMA protocol ideally suited for highly secure or strictly anonymous environments b) it can be used in heterogeneous environments where devices use different packet structures c) it does not require network time-synchronization, and d) it is insensitive to channel errors. We have implemented ZEA-TDMA on the MICA2 hardware platform running TinyOS and evaluated the protocol functionality and performance on a MICA2 test-bed.

Jagged–Delta asymmetry in Notch signaling can give rise to a Sender/Receiver hybrid phenotype

PubMed Central

Boareto, Marcelo; Jolly, Mohit Kumar; Lu, Mingyang; Onuchic, José N.; Clementi, Cecilia; Ben-Jacob, Eshel

2015-01-01

Notch signaling pathway mediates cell-fate determination during embryonic development, wound healing, and tumorigenesis. This pathway is activated when the ligand Delta or the ligand Jagged of one cell interacts with the Notch receptor of its neighboring cell, releasing the Notch Intracellular Domain (NICD) that activates many downstream target genes. NICD affects ligand production asymmetrically––it represses Delta, but activates Jagged. Although the dynamical role of Notch–Jagged signaling remains elusive, it is widely recognized that Notch–Delta signaling behaves as an intercellular toggle switch, giving rise to two distinct fates that neighboring cells adopt––Sender (high ligand, low receptor) and Receiver (low ligand, high receptor). Here, we devise a specific theoretical framework that incorporates both Delta and Jagged in Notch signaling circuit to explore the functional role of Jagged in cell-fate determination. We find that the asymmetric effect of NICD renders the circuit to behave as a three-way switch, giving rise to an additional state––a hybrid Sender/Receiver (medium ligand, medium receptor). This phenotype allows neighboring cells to both send and receive signals, thereby attaining similar fates. We also show that due to the asymmetric effect of the glycosyltransferase Fringe, different outcomes are generated depending on which ligand is dominant: Delta-mediated signaling drives neighboring cells to have an opposite fate; Jagged-mediated signaling drives the cell to maintain a similar fate to that of its neighbor. We elucidate the role of Jagged in cell-fate determination and discuss its possible implications in understanding tumor–stroma cross-talk, which frequently entails Notch–Jagged communication. PMID:25605936

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

Creating Profiles from User Network Behavior

DTIC Science & Technology

2013-09-01

We varied the m-estimate in Naïve Bayes, m for pruning in Learning Tree, and how many k nearest neighbors to select from in KNN, before settling on the...N. Taft, “The cubicle vs. the coffee shop: behavioral modes in enterprise end-users,” in Proc. of the 9th Int. Conf. on Passive and Active Network

The Support System of the Hispanic Elderly and the Use of Formal Social Services.

ERIC Educational Resources Information Center

Starrett, Richard A.; And Others

The study examined the role played by informal (i.e., family, kin, neighbors, friends) and quasiformal (i.e., church-sponsored) support systems in predicting, enhancing, or inhibiting use of social services by Hispanic elderly. Thirty-seven variables and data selected from a 1979-1980 15-state survey of 1,805 noninstitutionalized Hispanic…

The coupling effects of kinematics and flexibility on the Lagrangian dynamic formulation of open chain deformable links

NASA Technical Reports Server (NTRS)

Changizi, Koorosh

1989-01-01

A nonlinear Lagrangian formulation for the spatial kinematic and dynamic analysis of open chain deformable links consisting of cylindrical joints that connect pairs of flexible links is developed. The special cases of revolute or prismatic joint can also be obtained from the kinematic equations. The kinematic equations are described using a 4x4 matrix method. The configuration of each deformable link in the open loop kinematic chain is identified using a coupled set of relative joint variables, constant geometric parameters, and elastic coordinates. The elastic coordinates define the link deformation with respect to a selected joint coordinate system that is consistent with the kinematic constraints on the boundary of the deformable link. These coordinates can be introduced using approximation techniques such as Rayleigh-Ritz method, finite element technique or any other desired approach. The large relative motion between two neighboring links are defined by a set of joint coordinates which describes the large relative translational and rotational motion between two neighboring joint coordinate systems. The origin of these coordinate systems are rigidly attached to the neighboring links at the joint definition points along the axis of motion.

Reducing Sweeping Frequencies in Microwave NDT Employing Machine Learning Feature Selection

PubMed Central

Moomen, Abdelniser; Ali, Abdulbaset; Ramahi, Omar M.

2016-01-01

Nondestructive Testing (NDT) assessment of materials’ health condition is useful for classifying healthy from unhealthy structures or detecting flaws in metallic or dielectric structures. Performing structural health testing for coated/uncoated metallic or dielectric materials with the same testing equipment requires a testing method that can work on metallics and dielectrics such as microwave testing. Reducing complexity and expenses associated with current diagnostic practices of microwave NDT of structural health requires an effective and intelligent approach based on feature selection and classification techniques of machine learning. Current microwave NDT methods in general based on measuring variation in the S-matrix over the entire operating frequency ranges of the sensors. For instance, assessing the health of metallic structures using a microwave sensor depends on the reflection or/and transmission coefficient measurements as a function of the sweeping frequencies of the operating band. The aim of this work is reducing sweeping frequencies using machine learning feature selection techniques. By treating sweeping frequencies as features, the number of top important features can be identified, then only the most influential features (frequencies) are considered when building the microwave NDT equipment. The proposed method of reducing sweeping frequencies was validated experimentally using a waveguide sensor and a metallic plate with different cracks. Among the investigated feature selection techniques are information gain, gain ratio, relief, chi-squared. The effectiveness of the selected features were validated through performance evaluations of various classification models; namely, Nearest Neighbor, Neural Networks, Random Forest, and Support Vector Machine. Results showed good crack classification accuracy rates after employing feature selection algorithms. PMID:27104533

Functional Interactions between Newborn and Mature Neurons Leading to Integration into Established Neuronal Circuits.

PubMed

Boulanger-Weill, Jonathan; Candat, Virginie; Jouary, Adrien; Romano, Sebastián A; Pérez-Schuster, Verónica; Sumbre, Germán

2017-06-19

From development up to adulthood, the vertebrate brain is continuously supplied with newborn neurons that integrate into established mature circuits. However, how this process is coordinated during development remains unclear. Using two-photon imaging, GCaMP5 transgenic zebrafish larvae, and sparse electroporation in the larva's optic tectum, we monitored spontaneous and induced activity of large neuronal populations containing newborn and functionally mature neurons. We observed that the maturation of newborn neurons is a 4-day process. Initially, newborn neurons showed undeveloped dendritic arbors, no neurotransmitter identity, and were unresponsive to visual stimulation, although they displayed spontaneous calcium transients. Later on, newborn-labeled neurons began to respond to visual stimuli but in a very variable manner. At the end of the maturation period, newborn-labeled neurons exhibited visual tuning curves (spatial receptive fields and direction selectivity) and spontaneous correlated activity with neighboring functionally mature neurons. At this developmental stage, newborn-labeled neurons presented complex dendritic arbors and neurotransmitter identity (excitatory or inhibitory). Removal of retinal inputs significantly perturbed the integration of newborn neurons into the functionally mature tectal network. Our results provide a comprehensive description of the maturation of newborn neurons during development and shed light on potential mechanisms underlying their integration into a functionally mature neuronal circuit. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Isolation and functional assessment of cutaneous stem cells.

PubMed

Doucet, Yanne S; Owens, David M

2015-01-01

The epidermis and associated appendages of the skin represent a multi-lineage tissue that is maintained by perpetual rounds of renewal. During homeostasis, turnover of epidermal lineages is achieved by input from regionalized keratinocytes stem or progenitor populations with little overlap from neighboring niches. Over the last decade, molecular markers selectively expressed by a number of these stem or progenitor pools have been identified, allowing for the isolation and functional assessment of stem cells and genetic lineage tracing analysis within intact skin. These advancements have led to many fundamental observations about epidermal stem cell function such as the identification of their progeny, their role in maintenance of skin homeostasis, or their contribution to wound healing. In this chapter, we provide a methodology to identify and isolate epidermal stem cells and to assess their functional role in their respective niche. Furthermore, recent evidence has shown that the microenvironment also plays a crucial role in stem cell function. Indeed, epidermal cells are under the influence of surrounding fibroblasts, adipocytes, and sensory neurons that provide extrinsic signals and mechanical cues to the niche and contribute to skin morphogenesis and homeostasis. A better understanding of these microenvironmental cues will help engineer in vitro experimental models with more relevance to in vivo skin biology. New approaches to address and study these environmental cues in vitro will also be addressed.

The afterlife of interspecific indirect genetic effects: genotype interactions alter litter quality with consequences for decomposition and nutrient dynamics.

PubMed

Genung, Mark A; Bailey, Joseph K; Schweitzer, Jennifer A

2013-01-01

Aboveground-belowground linkages are recognized as divers of community dynamics and ecosystem processes, but the impacts of plant-neighbor interactions on these linkages are virtually unknown. Plant-neighbor interactions are a type of interspecific indirect genetic effect (IIGE) if the focal plant's phenotype is altered by the expression of genes in a neighboring heterospecific plant, and IIGEs could persist after plant senescence to affect ecosystem processes. This perspective can provide insight into how plant-neighbor interactions affect evolution, as IIGEs are capable of altering species interactions and community composition over time. Utilizing genotypes of Solidago altissima and Solidago gigantea, we experimentally tested whether IIGEs that had affected living focal plants would affect litter decomposition rate, as well as nitrogen (N) and phosphorous (P) dynamics after the focal plant senesced. We found that species interactions affected N release and genotype interactions affected P immobilization. From a previous study we knew that neighbor genotype influenced patterns of biomass allocation for focal plants. Here we extend those previous results to show that these changes in biomass allocation altered litter quality, that then altered rates of decomposition and nutrient cycling. Our results provide insights into above- and belowground linkages by showing that, through their effects on plant litter quality (e.g., litter lignin:N), IIGEs can have afterlife effects, tying plant-neighbor interactions to ecosystem processes. This holistic approach advances our understanding of decomposition and nutrient cycling by showing that evolutionary processes (i.e., IIGEs) can influence ecosystem functioning after plant senescence. Because plant traits are determined by the combined effects of genetic and environmental influences, and because these traits are known to affect decomposition and nutrient cycling, we suggest that ecosystem processes can be described as gene-less products of genetic interactions among the species comprising ecological communities.

The Afterlife of Interspecific Indirect Genetic Effects: Genotype Interactions Alter Litter Quality with Consequences for Decomposition and Nutrient Dynamics

PubMed Central

Genung, Mark A.; Bailey, Joseph K.; Schweitzer, Jennifer A.

2013-01-01

Aboveground-belowground linkages are recognized as divers of community dynamics and ecosystem processes, but the impacts of plant-neighbor interactions on these linkages are virtually unknown. Plant-neighbor interactions are a type of interspecific indirect genetic effect (IIGE) if the focal plant’s phenotype is altered by the expression of genes in a neighboring heterospecific plant, and IIGEs could persist after plant senescence to affect ecosystem processes. This perspective can provide insight into how plant-neighbor interactions affect evolution, as IIGEs are capable of altering species interactions and community composition over time. Utilizing genotypes of Solidago altissima and Solidago gigantea, we experimentally tested whether IIGEs that had affected living focal plants would affect litter decomposition rate, as well as nitrogen (N) and phosphorous (P) dynamics after the focal plant senesced. We found that species interactions affected N release and genotype interactions affected P immobilization. From a previous study we knew that neighbor genotype influenced patterns of biomass allocation for focal plants. Here we extend those previous results to show that these changes in biomass allocation altered litter quality, that then altered rates of decomposition and nutrient cycling. Our results provide insights into above- and belowground linkages by showing that, through their effects on plant litter quality (e.g., litter lignin:N), IIGEs can have afterlife effects, tying plant-neighbor interactions to ecosystem processes. This holistic approach advances our understanding of decomposition and nutrient cycling by showing that evolutionary processes (i.e., IIGEs) can influence ecosystem functioning after plant senescence. Because plant traits are determined by the combined effects of genetic and environmental influences, and because these traits are known to affect decomposition and nutrient cycling, we suggest that ecosystem processes can be described as gene-less products of genetic interactions among the species comprising ecological communities. PMID:23349735

Swedish Folk High Schools ("Folkhögskolor"): Past and Present. A Look from the Polish Perspective

ERIC Educational Resources Information Center

Maliszewski, Tomasz

2014-01-01

The article presents an outline of the history of Folk High Schools in Sweden. The analysis includes mainly social and political determinants of their functioning in Poland's northern neighbor. The main trends of the evolution of social functions of these institutions has also been presented in the article encompassing 145 years of their…

High Density Diffusion-Free Nanowell Arrays

PubMed Central

Takulapalli, Bharath R; Qiu, Ji; Magee, D. Mitchell; Kahn, Peter; Brunner, Al; Barker, Kristi; Means, Steven; Miersch, Shane; Bian, Xiaofang; Mendoza, Alex; Festa, Fernanda; Syal, Karan; Park, Jin; LaBaer, Joshua; Wiktor, Peter

2012-01-01

Proteomics aspires to elucidate the functions of all proteins. Protein microarrays provide an important step by enabling high-throughput studies of displayed proteins. However, many functional assays of proteins include untethered intermediates or products, which could frustrate the use of planar arrays at very high densities because of diffusion to neighboring features. The nucleic acid programmable protein array (NAPPA), is a robust, in situ synthesis method for producing functional proteins just-in-time, which includes steps with diffusible intermediates. We determined that diffusion of expressed proteins led to cross-binding at neighboring spots at very high densities with reduced inter-spot spacing. To address this limitation, we have developed an innovative platform using photolithographically-etched discrete silicon nanowells and used NAPPA as a test case. This arrested protein diffusion and cross-binding. We present confined high density protein expression and display, as well as functional protein-protein interactions, in 8,000 nanowell arrays. This is the highest density of individual proteins in nano-vessels demonstrated on a single slide. We further present proof of principle results on ultra-high density protein arrays capable of up to 24,000 nanowells on a single slide. PMID:22742968

A density functional approach to ferrogels

NASA Astrophysics Data System (ADS)

Cremer, P.; Heinen, M.; Menzel, A. M.; Löwen, H.

2017-07-01

Ferrogels consist of magnetic colloidal particles embedded in an elastic polymer matrix. As a consequence, their structural and rheological properties are governed by a competition between magnetic particle-particle interactions and mechanical matrix elasticity. Typically, the particles are permanently fixed within the matrix, which makes them distinguishable by their positions. Over time, particle neighbors do not change due to the fixation by the matrix. Here we present a classical density functional approach for such ferrogels. We map the elastic matrix-induced interactions between neighboring colloidal particles distinguishable by their positions onto effective pairwise interactions between indistinguishable particles similar to a ‘pairwise pseudopotential’. Using Monte-Carlo computer simulations, we demonstrate for one-dimensional dipole-spring models of ferrogels that this mapping is justified. We then use the pseudopotential as an input into classical density functional theory of inhomogeneous fluids and predict the bulk elastic modulus of the ferrogel under various conditions. In addition, we propose the use of an ‘external pseudopotential’ when one switches from the viewpoint of a one-dimensional dipole-spring object to a one-dimensional chain embedded in an infinitely extended bulk matrix. Our mapping approach paves the way to describe various inhomogeneous situations of ferrogels using classical density functional concepts of inhomogeneous fluids.

Studying the hopping parameters of half-Heusler NaAuS using maximally localized Wannier function

NASA Astrophysics Data System (ADS)

Sihi, Antik; Lal, Sohan; Pandey, Sudhir K.

2018-04-01

Here, the electronic behavior of half-Heusler NaAuS is studied using PBEsol exchange correlation functional by plotting the band structure curve. These bands are reproduced using maximally localized Wannier function using WANNIER90. Tight-binding bands are nicely matched with density functional theory bands. By fitting the tight-binding model, hopping parameter for NaAuS is obtained by including Na 2s, 2p, Au 6s, 5p, 5d and S 3s, 3p orbitals within the energy interval of -5 to 16 eV around the Fermi level. In present study, hopping integrals for NaAuS are computed for the first primitive unit cell atoms as well as the first nearest neighbor primitive unit cell. The most dominating hopping integrals are found for Na (3s) - S (3s), Na (2px) - S (2px), Au (6s) - S (3px), Au (6s) - S (3py) and Au (6s) - S (3pz) orbitals. The hopping integrals for the first nearest neighbor primitive unit cell are also discussed in this manuscript. In future, these hopping integrals are very important to find the topological invariant for NaAuS compound.

Local structure of ion pair interaction in lapatinib amorphous dispersions characterized by synchrotron x-ray diffraction and pair distribution function analysis

DOE PAGES

de Araujo, Gabriel L. B.; Benmore, Chris J.; Byrn, Stephen R.

2017-04-11

For many years, the idea of analyzing atom-atom contacts in amorphous drug-polymer systems has been of major interest, because this method has always had the potential to differentiate between amorphous systems with domains and amorphous systems which are molecular mixtures. In this study, local structure of ionic and noninonic interactions were studied by High-Energy X-ray Diffraction and Pair Distribution Function (PDF) analysis in amorphous solid dispersions of lapatinib in hypromellose phthalate (HPMCP) and hypromellose (HPMC-E3). The strategy of extracting lapatinib intermolecular drug interactions from the total PDF x-ray pattern was successfully applied allowing the detection of distinct nearest neighbor contactsmore » for the HPMC-E3 rich preparations showing that lapatinib molecules do not cluster in the same way as observed in HPMC-P, where ionic interactions are present. Orientational correlations up to nearest neighbor molecules at about 4.3 Å were observed for polymer rich samples; both observations showed strong correlation to the stability of the systems. Lasty, the superior physical stability of 1:3 LP:HPMCP was consistent with the absence of significant intermolecular interactions in (ΔD inter LP(r)) in the range of 3.0 to 6.0 Å, which are attributed to C-C, C-N and C-O nearest neighbor contacts present in drug-drug interactions.« less

Local structure of ion pair interaction in lapatinib amorphous dispersions characterized by synchrotron x-ray diffraction and pair distribution function analysis

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

de Araujo, Gabriel L. B.; Benmore, Chris J.; Byrn, Stephen R.

For many years, the idea of analyzing atom-atom contacts in amorphous drug-polymer systems has been of major interest, because this method has always had the potential to differentiate between amorphous systems with domains and amorphous systems which are molecular mixtures. In this study, local structure of ionic and noninonic interactions were studied by High-Energy X-ray Diffraction and Pair Distribution Function (PDF) analysis in amorphous solid dispersions of lapatinib in hypromellose phthalate (HPMCP) and hypromellose (HPMC-E3). The strategy of extracting lapatinib intermolecular drug interactions from the total PDF x-ray pattern was successfully applied allowing the detection of distinct nearest neighbor contactsmore » for the HPMC-E3 rich preparations showing that lapatinib molecules do not cluster in the same way as observed in HPMC-P, where ionic interactions are present. Orientational correlations up to nearest neighbor molecules at about 4.3 Å were observed for polymer rich samples; both observations showed strong correlation to the stability of the systems. Lasty, the superior physical stability of 1:3 LP:HPMCP was consistent with the absence of significant intermolecular interactions in (ΔD inter LP(r)) in the range of 3.0 to 6.0 Å, which are attributed to C-C, C-N and C-O nearest neighbor contacts present in drug-drug interactions.« less

Risk of Social Isolation among Older Patients: What Factors Affect the Availability of Family, Friends, and Neighbors upon Hospitalization?

PubMed

Ha, Jung-Hwa; Hougham, Gavin W; Meltzer, David O

2018-03-02

To examine the prevalence of social isolation among older patients admitted to a hospital, and the effects of sociodemographic and health-related factors on the availability of their family, friends, and neighbor networks. Analyses are based on interviews with a sample of 2,449 older patients admitted to an urban academic medical center in the United States. A nine-item version of Lubben's Social Network Scale was developed and used to assess the availability of different social networks. About 47% of the sample was at risk of social isolation. The oldest old and non-White older adults showed greater risk. The availability of family networks was associated with age, sex, marital status, and prior hospitalization; friend networks with age, race, education, prior hospitalization, and functional limitations; neighbor networks with race, education, marital status, and functional limitations. The risk of social isolation and the availability of social support for hospitalized older adults varies by both patient and network characteristics. Health professionals should attend to this risk and the factors associated with such risk. By assessing the availability of various types and frequency of support among older patients, health professionals can better identify those who may need additional support after discharge. Such information should be used in discharge planning to help prevent unnecessary complications and potential readmission.

Local Structure of Ion Pair Interaction in Lapatinib Amorphous Dispersions characterized by Synchrotron X-Ray diffraction and Pair Distribution Function Analysis

NASA Astrophysics Data System (ADS)

de Araujo, Gabriel L. B.; Benmore, Chris J.; Byrn, Stephen R.

2017-04-01

For many years, the idea of analyzing atom-atom contacts in amorphous drug-polymer systems has been of major interest, because this method has always had the potential to differentiate between amorphous systems with domains and amorphous systems which are molecular mixtures. In this study, local structure of ionic and noninonic interactions were studied by High-Energy X-ray Diffraction and Pair Distribution Function (PDF) analysis in amorphous solid dispersions of lapatinib in hypromellose phthalate (HPMCP) and hypromellose (HPMC-E3). The strategy of extracting lapatinib intermolecular drug interactions from the total PDF x-ray pattern was successfully applied allowing the detection of distinct nearest neighbor contacts for the HPMC-E3 rich preparations showing that lapatinib molecules do not cluster in the same way as observed in HPMC-P, where ionic interactions are present. Orientational correlations up to nearest neighbor molecules at about 4.3 Å were observed for polymer rich samples; both observations showed strong correlation to the stability of the systems. Finally, the superior physical stability of 1:3 LP:HPMCP was consistent with the absence of significant intermolecular interactions in (Δ) in the range of 3.0 to 6.0 Å, which are attributed to C-C, C-N and C-O nearest neighbor contacts present in drug-drug interactions.

EPA Region 1 - Valley Depth in Meters

EPA Pesticide Factsheets

Raster of the Depth in meters of EPA-delimited Valleys in Region 1.Valleys (areas that are lower than their neighbors) were extracted from a Digital Elevation Model (USGS, 30m) by finding the local average elevation, subtracting the actual elevation from the average, and selecting areas where the actual elevation was below the average. The landscape was sampled at seven scales (circles of 1, 2, 4, 7, 11, 16, and 22 km radius) to take into account the diversity of valley shapes and sizes. Areas selected in at least four scales were designated as valleys.

Nearest neighbor density ratio estimation for large-scale applications in astronomy

NASA Astrophysics Data System (ADS)

Kremer, J.; Gieseke, F.; Steenstrup Pedersen, K.; Igel, C.

2015-09-01

In astronomical applications of machine learning, the distribution of objects used for building a model is often different from the distribution of the objects the model is later applied to. This is known as sample selection bias, which is a major challenge for statistical inference as one can no longer assume that the labeled training data are representative. To address this issue, one can re-weight the labeled training patterns to match the distribution of unlabeled data that are available already in the training phase. There are many examples in practice where this strategy yielded good results, but estimating the weights reliably from a finite sample is challenging. We consider an efficient nearest neighbor density ratio estimator that can exploit large samples to increase the accuracy of the weight estimates. To solve the problem of choosing the right neighborhood size, we propose to use cross-validation on a model selection criterion that is unbiased under covariate shift. The resulting algorithm is our method of choice for density ratio estimation when the feature space dimensionality is small and sample sizes are large. The approach is simple and, because of the model selection, robust. We empirically find that it is on a par with established kernel-based methods on relatively small regression benchmark datasets. However, when applied to large-scale photometric redshift estimation, our approach outperforms the state-of-the-art.

Constructing a logical, regular axis topology from an irregular topology

DOEpatents

Faraj, Daniel A.

2014-07-22

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

Constructing a logical, regular axis topology from an irregular topology

DOEpatents

Faraj, Daniel A.

2014-07-01

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

Raman scattering mediated by neighboring molecules

NASA Astrophysics Data System (ADS)

Williams, Mathew D.; Bradshaw, David S.; Andrews, David L.

2016-05-01

Raman scattering is most commonly associated with a change in vibrational state within individual molecules, the corresponding frequency shift in the scattered light affording a key way of identifying material structures. In theories where both matter and light are treated quantum mechanically, the fundamental scattering process is represented as the concurrent annihilation of a photon from one radiation mode and creation of another in a different mode. Developing this quantum electrodynamical formulation, the focus of the present work is on the spectroscopic consequences of electrodynamic coupling between neighboring molecules or other kinds of optical center. To encompass these nanoscale interactions, through which the molecular states evolve under the dual influence of the input light and local fields, this work identifies and determines two major mechanisms for each of which different selection rules apply. The constituent optical centers are considered to be chemically different and held in a fixed orientation with respect to each other, either as two components of a larger molecule or a molecular assembly that can undergo free rotation in a fluid medium or as parts of a larger, solid material. The two centers are considered to be separated beyond wavefunction overlap but close enough together to fall within an optical near-field limit, which leads to high inverse power dependences on their local separation. In this investigation, individual centers undergo a Stokes transition, whilst each neighbor of a different species remains in its original electronic and vibrational state. Analogous principles are applicable for the anti-Stokes case. The analysis concludes by considering the experimental consequences of applying this spectroscopic interpretation to fluid media; explicitly, the selection rules and the impact of pressure on the radiant intensity of this process.

Behavior of Collective Cooperation Yielded by Two Update Rules in Social Dilemmas: Combining Fermi and Moran Rules

NASA Astrophysics Data System (ADS)

Xia, Cheng-Yi; Wang, Lei; Wang, Juan; Wang, Jin-Song

2012-09-01

We combine the Fermi and Moran update rules in the spatial prisoner's dilemma and snowdrift games to investigate the behavior of collective cooperation among agents on the regular lattice. Large-scale simulations indicate that, compared to the model with only one update rule, the cooperation behavior exhibits the richer phenomena, and the role of update dynamics should be paid more attention in the evolutionary game theory. Meanwhile, we also observe that the introduction of Moran rule, which needs to consider all neighbor's information, can markedly promote the aggregate cooperation level, that is, randomly selecting the neighbor proportional to its payoff to imitate will facilitate the cooperation among agents. Current results will contribute to further understand the cooperation dynamics and evolutionary behaviors within many biological, economic and social systems.

Escherichia coli infection induces distinct local and systemic transcriptome responses in the mammary gland.

PubMed

Mitterhuemer, Simone; Petzl, Wolfram; Krebs, Stefan; Mehne, Daniel; Klanner, Andrea; Wolf, Eckhard; Zerbe, Holm; Blum, Helmut

2010-02-25

Coliform bacteria are the most common etiologic agents in severe mastitis of cows. Escherichia coli infections are mostly restricted to a single udder quarter whereas neighboring quarters stay clinically inapparent, implicating the presence of a systemic defense reaction. To address its underlying mechanism, we performed a transcriptome study of mammary tissue from udder quarters inoculated with E. coli (6 h and 24 h post infection), from neighboring quarters of the same animals, and from untreated control animals. After 6 h 13 probe sets of differentially expressed genes (DEG) were detected in infected quarters versus control animals. Eighteen hours later 2154 and 476 DEG were found in infected and in neighboring quarters vs. control animals. Cluster analysis revealed DEG found only in infected quarters (local response) and DEG detected in both infected and neighboring quarters (systemic response). The first group includes genes mainly involved in immune response and inflammation, while the systemic reaction comprises antigen processing and presentation, cytokines, protein degradation and apoptosis. Enhanced expression of antimicrobial genes (S100A8, S100A9, S100A12, CXCL2, GNLY), acute phase genes (LBP, SAA3, CP, BF, C6, C4BPA, IF), and indicators of oxidative stress (GPX3, MT1A, MT2A, SOD2) point to an active defense reaction in infected and neighboring healthy quarters. Its early onset is indicated by increased transcription of NFIL3 at 6 h. NFIL3 is a predicted regulator of many genes of the systemic response at 24 h. The significance of our transcriptome study was evidenced by some recent findings with candidate gene based approaches. The discovery and holistic analysis of an extensive systemic reaction in the mammary gland significantly expands the knowledge of host-pathogen interactions in mastitis which may be relevant for the development of novel therapies and for genetic selection towards mastitis resistance.

Studies on DNA-binding selectivity of WRKY transcription factors lend structural clues into WRKY-domain function.

PubMed

Ciolkowski, Ingo; Wanke, Dierk; Birkenbihl, Rainer P; Somssich, Imre E

2008-09-01

WRKY transcription factors have been shown to play a major role in regulating, both positively and negatively, the plant defense transcriptome. Nearly all studied WRKY factors appear to have a stereotypic binding preference to one DNA element termed the W-box. How specificity for certain promoters is accomplished therefore remains completely unknown. In this study, we tested five distinct Arabidopsis WRKY transcription factor subfamily members for their DNA binding selectivity towards variants of the W-box embedded in neighboring DNA sequences. These studies revealed for the first time differences in their binding site preferences, which are partly dependent on additional adjacent DNA sequences outside of the TTGACY-core motif. A consensus WRKY binding site derived from these studies was used for in silico analysis to identify potential target genes within the Arabidopsis genome. Furthermore, we show that even subtle amino acid substitutions within the DNA binding region of AtWRKY11 strongly impinge on its binding activity. Additionally, all five factors were found localized exclusively to the plant cell nucleus and to be capable of trans-activating expression of a reporter gene construct in vivo.

Cooperative deformations of periodically patterned hydrogels.

PubMed

Wang, Zhi Jian; Zhu, Chao Nan; Hong, Wei; Wu, Zi Liang; Zheng, Qiang

2017-09-01

Nature has shown elegant paradigms of smart deformation, which inspired biomimetic systems with controllable bending, folding, and twisting that are significant for the development of soft electronics and actuators. Complex deformations are usually realized by additively incorporating typical structures in selective domains with little interaction. We demonstrate the cooperative deformations of periodically patterned hydrogel sheets, in which neighboring domains mutually interact and cooperatively deform. Nonswelling disc gels are periodically positioned in a high-swelling gel. During the swelling process, the compartmentalized high-swelling gel alternately bends upward or downward to relieve the in-plane compression, but the overall integrated structure remains flat. The synergy between the elastic mismatch and the geometric periodicity selects the outcome pattern. Both experiment and modeling show that various types of cooperative deformation can be achieved by tuning the pattern geometry and gel properties. Different responsive polymers can also be patterned in one composite gel. Under stimulation, reversible transformations between different cooperative deformations are realized. The principle of cooperative deformation should be applicable to other materials, and the patterns can be miniaturized to the micrometer- or nanometer-scale level, providing the morphing materials with advanced functionalities for applications in various fields.

A hybrid fault diagnosis method based on second generation wavelet de-noising and local mean decomposition for rotating machinery.

PubMed

Liu, Zhiwen; He, Zhengjia; Guo, Wei; Tang, Zhangchun

2016-03-01

In order to extract fault features of large-scale power equipment from strong background noise, a hybrid fault diagnosis method based on the second generation wavelet de-noising (SGWD) and the local mean decomposition (LMD) is proposed in this paper. In this method, a de-noising algorithm of second generation wavelet transform (SGWT) using neighboring coefficients was employed as the pretreatment to remove noise in rotating machinery vibration signals by virtue of its good effect in enhancing the signal-noise ratio (SNR). Then, the LMD method is used to decompose the de-noised signals into several product functions (PFs). The PF corresponding to the faulty feature signal is selected according to the correlation coefficients criterion. Finally, the frequency spectrum is analyzed by applying the FFT to the selected PF. The proposed method is applied to analyze the vibration signals collected from an experimental gearbox and a real locomotive rolling bearing. The results demonstrate that the proposed method has better performances such as high SNR and fast convergence speed than the normal LMD method. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Meaningful Education for Returning-to-School Students in a Comprehensive Upper Secondary School in Iceland

ERIC Educational Resources Information Center

Jóhannesson, Ingólfur Ásgeir; Bjarnadóttir, Valgerður S.

2016-01-01

Dropout from upper secondary education in Iceland is higher than in the neighboring countries, but varied options to re-enter school have also been on offer. This article focuses on how students, who had returned to a selected upper secondary school after having quit in one or more other schools, benefited from an innovative pedagogical approach…

An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

ERIC Educational Resources Information Center

Pankau, Brian L.

2009-01-01

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

Non-parametric analysis of LANDSAT maps using neural nets and parallel computers

NASA Technical Reports Server (NTRS)

Salu, Yehuda; Tilton, James

1991-01-01

Nearest neighbor approaches and a new neural network, the Binary Diamond, are used for the classification of images of ground pixels obtained by LANDSAT satellite. The performances are evaluated by comparing classifications of a scene in the vicinity of Washington DC. The problem of optimal selection of categories is addressed as a step in the classification process.

Neighbor-Directed Histidine N (s)–Alkylation: A Route to Imidazolium-Containing Phosphopeptide Macrocycles-Biopolymers | Center for Cancer Research

Cancer.gov

Our recently discovered, selective, on-resin route to N(s)-alkylated imidazolium-containing histidine residues affords new strategies for peptide mimetic design. In this, we demonstrate the use of this chemistry to prepare a series of macrocyclic phosphopeptides, in which imidazolium groups serve as ring-forming junctions. Interestingly, these cationic moieties subsequently

Culture rather than genes provides greater scope for the evolution of large-scale human prosociality

PubMed Central

Bell, Adrian V.; Richerson, Peter J.; McElreath, Richard

2009-01-01

Whether competition among large groups played an important role in human social evolution is dependent on how variation, whether cultural or genetic, is maintained between groups. Comparisons between genetic and cultural differentiation between neighboring groups show how natural selection on large groups is more plausible on cultural rather than genetic variation. PMID:19822753

Tentative guides for the selection of plus trees and superior stands in Douglas-fir.

Treesearch

Leo A. Isaac

1955-01-01

Interest among foresters in forest tree improvement has increased rapidly in recent years. Geneticists have learned that some individual trees greatly excel their neighbors in desirable characteristics, and that some entire stands are superior to other stands of the same species in a general locality. They have learned that many of the desirable tree characteristics...

Hyperspectral Image Classification via Kernel Sparse Representation

DTIC Science & Technology

2013-01-01

classification algorithms. Moreover, the spatial coherency across neighboring pixels is also incorporated through a kernelized joint sparsity model , where...joint sparsity model , where all of the pixels within a small neighborhood are jointly represented in the feature space by selecting a few common training...hyperspectral imagery, joint spar- sity model , kernel methods, sparse representation. I. INTRODUCTION HYPERSPECTRAL imaging sensors capture images

Language Non-Selective Activation of Orthography during Spoken Word Processing in Hindi-English Sequential Bilinguals: An Eye Tracking Visual World Study

ERIC Educational Resources Information Center

Mishra, Ramesh Kumar; Singh, Niharika

2014-01-01

Previous psycholinguistic studies have shown that bilinguals activate lexical items of both the languages during auditory and visual word processing. In this study we examined if Hindi-English bilinguals activate the orthographic forms of phonological neighbors of translation equivalents of the non target language while listening to words either…

How School Choice Is Framed by Parental Preferences and Family Characteristics: A Study of Western Area, Sierra Leone

ERIC Educational Resources Information Center

Dixon, Pauline; Humble, Steve

2017-01-01

This research set out to investigate how, in a post-conflict area, parental preferences and household characteristics affect school choice for their children. A multinomial logit is used to model the relationship between education preferences and the selection of schools for 954 households in Freetown and neighboring districts, Western Area,…

Text Classification for Intelligent Portfolio Management

DTIC Science & Technology

2002-05-01

years including nearest neighbor classification [15], naive Bayes with EM (Ex- pectation Maximization) [11] [13], Winnow with active learning [10... Active Learning and Expectation Maximization (EM). In particular, active learning is used to actively select documents for labeling, then EM assigns...generalization with active learning . Machine Learning, 15(2):201–221, 1994. [3] I. Dagan and P. Engelson. Committee-based sampling for training

Shade avoidance components and pathways in adult plants revealed by phenotypic profiling.

PubMed

Nozue, Kazunari; Tat, An V; Kumar Devisetty, Upendra; Robinson, Matthew; Mumbach, Maxwell R; Ichihashi, Yasunori; Lekkala, Saradadevi; Maloof, Julin N

2015-04-01

Shade from neighboring plants limits light for photosynthesis; as a consequence, plants have a variety of strategies to avoid canopy shade and compete with their neighbors for light. Collectively the response to foliar shade is called the shade avoidance syndrome (SAS). The SAS includes elongation of a variety of organs, acceleration of flowering time, and additional physiological responses, which are seen throughout the plant life cycle. However, current mechanistic knowledge is mainly limited to shade-induced elongation of seedlings. Here we use phenotypic profiling of seedling, leaf, and flowering time traits to untangle complex SAS networks. We used over-representation analysis (ORA) of shade-responsive genes, combined with previous annotation, to logically select 59 known and candidate novel mutants for phenotyping. Our analysis reveals shared and separate pathways for each shade avoidance response. In particular, auxin pathway components were required for shade avoidance responses in hypocotyl, petiole, and flowering time, whereas jasmonic acid pathway components were only required for petiole and flowering time responses. Our phenotypic profiling allowed discovery of seventeen novel shade avoidance mutants. Our results demonstrate that logical selection of mutants increased success of phenotypic profiling to dissect complex traits and discover novel components.

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

PubMed Central

Villa-Parra, Ana Cecilia; Bastos-Filho, Teodiano; López-Delis, Alberto; Frizera-Neto, Anselmo; Krishnan, Sridhar

2017-01-01

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. PMID:29186848

Numerical and experimental investigation into the subsequent thermal cycling during selective laser melting of multi-layer 316L stainless steel

NASA Astrophysics Data System (ADS)

Liu, Yang; Zhang, Jian; Pang, Zhicong

2018-01-01

Subsequent thermal cycling (STC), as the unique thermal behavior during the multi-layer manufacturing process of selective laser melting (SLM), brings about unique microstructure of the as-produced parts. A multi-layer finite element (FE) model was proposed to study the STC along with a contrast experiment. The FE simulational results show that as layer increases, the maximum temperature, dimensions and liquid lifetime of the molten pool increase, while the heating and cooling rates decrease. The maximum temperature point shifts into the molten pool, and central of molten pool shifts backward. The neighborly underlying layer can be remelted thoroughly when laser irradiates a powder layer, thus forming an excellent bonding between neighbor layers. The contrast experimental results between the single-layer and triple-layer samples show that grains in of latter become coarsen and tabular along the height direction compared with those of the former. Moreover, this effect become more serious in 2nd and 1st layers in the triple-layer sample. All the above illustrate that the STC has an significant influence on the thermal behavior during SLM process, and thus affects the microstructure of SLMed parts.

Kalman/Map filtering-aided fast normalized cross correlation-based Wi-Fi fingerprinting location sensing.

PubMed

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-11-13

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

PubMed Central

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-01-01

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results. PMID:24233027

A discrete wavelet based feature extraction and hybrid classification technique for microarray data analysis.

PubMed

Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan

2014-01-01

Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

Helminths and human ancestral immune ecology: What is the evidence for high helminth loads among foragers?

PubMed

London, Douglas; Hruschka, Daniel

2014-01-01

Recent theories of human immune ecology have invoked high helminth loads as an important selection factor among early humans. However, few studies have assessed this assumption among extant human foragers. We review the current evidence for high helminth loads in documented forager populations and present new data from members of a Kawymeno Waorani forager group in Amazonian Ecuador (n = 16) compared with neighboring Kichwa subsistence farmers (n = 63). Stool samples indicated a near absence of helminths among the Kawymeno foraging group (6.25% with Ascaris lumbricoides and 0% with Ancylostoma duodenale or Trichuris trichiura). In contrast neighboring, isolated Kichwa subsistence farmers in a similar ecosystem had abundant helminth infestations (76.1% with Ascaris lumbricoides, 11.1% with Ancylostoma duodenale, and 1.5% with Trichuris trichiura). The presence of helminths among the Waorani and Kichwa was triangulated across multiple data sources, including presence in stool samples, medical exams, and 3 years of participant observation. These findings, coupled with the modern forager literature, raise questions as to whether helminths were prevalent enough in Paleolithic humans to be a unique evolutionary selective force in human physiology. Copyright © 2014 Wiley Periodicals, Inc.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

Germination phenology determines the propensity for facilitation and competition.

PubMed

Leverett, Lindsay D

2017-09-01

A single plant can interact both positively and negatively with its neighbors through the processes of facilitation and competition, respectively. Much of the variation in the balance of facilitation and competition that individuals experience can be explained by the degree of physical stress and the sizes or ages of plants during the interaction. Germination phenology partly controls both of these factors, but its role in defining the facilitation-competition balance has not been explicitly considered. I performed an experiment in a population of the winter annual Arabidopsis thaliana (Brassicaceae) to test whether germinating during physically stressful periods leads to facilitation while germinating during periods that promote growth and reproduction leads to competition. I manipulated germination and neighbor presence across two years in order to quantify the effects of the local plant community on survival, fecundity, and total fitness as a function of germination phenology. Neighbors increased survival when germination occurred under conditions that were unsuitable for survival, but they reduced fecundity in germinants that were otherwise the most fecund. Later germination was associated with facilitation in the first year but competition in the second year. These episodes of facilitation and competition opposed each other, leading to no net effect of neighbors when averaged over all cohorts. These results indicate that variation in germination timing can explain some of the variation in the facilitation-competition balance in plant communities. © 2017 by the Ecological Society of America.

A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-01-01

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power. PMID:24608008

Misregistration in Adaptive Optics Systems

DTIC Science & Technology

2009-06-01

which is constructcd on one thin reflectivc sheet that is attached to the actuators. This coupling of actuators introduces an influence function between...neighboring actuators. The actuator influence function Akl, is the phase caused hy poking an individual actuator. It is assumed that Akl = I at...the location (k, l). The influence function is given by { 0, A(x,y) = I-lxi, 1 -1111 , if Ixl > 1 or Iyl > 1, if Iyl :5 lxi, if Ixl :5 Iyl. (4) Using

Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency

DTIC Science & Technology

2010-01-01

sgn(Y )C log n, o.w, (45b) where sgn is the sign function and C > 0 is a constant. Consider the functionals H ′2, φ ′ 2 by replacing Yn with Zn in H2...Gaussian signal processing, and has held visiting faculty positions at INP , Toulouse. He is currently with the US Army Research Laboratory where his work

White matter structural connectivity is associated with sensorimotor function in stroke survivors☆

PubMed Central

Kalinosky, Benjamin T.; Schindler-Ivens, Sheila; Schmit, Brian D.

2013-01-01

Purpose Diffusion tensor imaging (DTI) provides functionally relevant information about white matter structure. Local anatomical connectivity information combined with fractional anisotropy (FA) and mean diffusivity (MD) may predict functional outcomes in stroke survivors. Imaging methods for predicting functional outcomes in stroke survivors are not well established. This work uses DTI to objectively assess the effects of a stroke lesion on white matter structure and sensorimotor function. Methods A voxel-based approach is introduced to assess a stroke lesion's global impact on motor function. Anatomical T1-weighted and diffusion tensor images of the brain were acquired for nineteen subjects (10 post-stroke and 9 age-matched controls). A manually selected volume of interest was used to alleviate the effects of stroke lesions on image registration. Images from all subjects were registered to the images of the control subject that was anatomically closest to Talairach space. Each subject's transformed image was uniformly seeded for DTI tractography. Each seed was inversely transformed into the individual subject space, where DTI tractography was conducted and then the results were transformed back to the reference space. A voxel-wise connectivity matrix was constructed from the fibers, which was then used to calculate the number of directly and indirectly connected neighbors of each voxel. A novel voxel-wise indirect structural connectivity (VISC) index was computed as the average number of direct connections to a voxel's indirect neighbors. Voxel-based analyses (VBA) were performed to compare VISC, FA, and MD for the detection of lesion-induced changes in sensorimotor function. For each voxel, a t-value was computed from the differences between each stroke brain and the 9 controls. A series of linear regressions was performed between Fugl-Meyer (FM) assessment scores of sensorimotor impairment and each DTI metric's log number of voxels that differed from the control group. Results Correlation between the logarithm of the number of significant voxels in the ipsilesional hemisphere and total Fugl-Meyer score was moderate for MD (R2 = 0.512), and greater for VISC (R2 = 0.796) and FA (R2 = 0.674). The slopes of FA (p = 0.0036), VISC (p = 0.0005), and MD (p = 0.0199) versus the total FM score were significant. However, these correlations were driven by the upper extremity motor component of the FM score (VISC: R2 = 0.879) with little influence of the lower extremity motor component (FA: R2 = 0.177). Conclusion The results suggest that a voxel-wise metric based on DTI tractography can predict upper extremity sensorimotor function of stroke survivors, and that supraspinal intraconnectivity may have a less dominant role in lower extremity function. PMID:24179827

Tuning Gas Adsorption Properties of Zeolite-like Supramolecular Assemblies with gis Topology via Functionalization of Isoreticular Metal-Organic Squares.

PubMed

Wang, Shuang; Belmabkhout, Youssef; Cairns, Amy J; Li, Guanghua; Huo, Qisheng; Liu, Yunling; Eddaoudi, Mohamed

2017-10-04

A strategy based on metal-ligand directed assembly of metal-organic squares (MOSs), built-up from four-membered ring (4MR) secondary building units (SBUs), has been employed for the design and construction of isoreticular zeolite-like supramolecular assemblies (ZSAs). Four porous Co-based ZSAs having the same underlying gis topology, but differing only with respect to the capping and bridging linkers, were successfully isolated and fully characterized. In this series, each MOS in ZSA-3-ZSA-6 possess an ideal square geometry and is connected to four neighboring MOS via a total of 16 hydrogen bonds to give a 3-periodic porous network.To systematically assess the effect of the pore system (size and functionality) on the gas adsorption properties, we evaluated the MOSs for their affinity for different probe molecules such as CO 2 and light hydrocarbons. ZSA-3-ZSA-6 showed high thermal stability (up to 300 °C) and was proven highly porous as evidenced by gas adsorption studies. Notably, alkyl-functionalized MOSs were found to offer potential for selective separation of CO 2 , C 3 H 6 , and C 3 H 8 from CH 4 and H 2 containing gas stream, such as natural gas and refinery-off gases.

An autoregressive model-based particle filtering algorithms for extraction of respiratory rates as high as 90 breaths per minute from pulse oximeter.

PubMed

Lee, Jinseok; Chon, Ki H

2010-09-01

We present particle filtering (PF) algorithms for an accurate respiratory rate extraction from pulse oximeter recordings over a broad range: 12-90 breaths/min. These methods are based on an autoregressive (AR) model, where the aim is to find the pole angle with the highest magnitude as it corresponds to the respiratory rate. However, when SNR is low, the pole angle with the highest magnitude may not always lead to accurate estimation of the respiratory rate. To circumvent this limitation, we propose a probabilistic approach, using a sequential Monte Carlo method, named PF, which is combined with the optimal parameter search (OPS) criterion for an accurate AR model-based respiratory rate extraction. The PF technique has been widely adopted in many tracking applications, especially for nonlinear and/or non-Gaussian problems. We examine the performances of five different likelihood functions of the PF algorithm: the strongest neighbor, nearest neighbor (NN), weighted nearest neighbor (WNN), probability data association (PDA), and weighted probability data association (WPDA). The performance of these five combined OPS-PF algorithms was measured against a solely OPS-based AR algorithm for respiratory rate extraction from pulse oximeter recordings. The pulse oximeter data were collected from 33 healthy subjects with breathing rates ranging from 12 to 90 breaths/ min. It was found that significant improvement in accuracy can be achieved by employing particle filters, and that the combined OPS-PF employing either the NN or WNN likelihood function achieved the best results for all respiratory rates considered in this paper. The main advantage of the combined OPS-PF with either the NN or WNN likelihood function is that for the first time, respiratory rates as high as 90 breaths/min can be accurately extracted from pulse oximeter recordings.

A parasitic nematode releases cytokinin that controls cell division and orchestrates feeding site formation in host plants.

PubMed

Siddique, Shahid; Radakovic, Zoran S; De La Torre, Carola M; Chronis, Demosthenis; Novák, Ondřej; Ramireddy, Eswarayya; Holbein, Julia; Matera, Christiane; Hütten, Marion; Gutbrod, Philipp; Anjam, Muhammad Shahzad; Rozanska, Elzbieta; Habash, Samer; Elashry, Abdelnaser; Sobczak, Miroslaw; Kakimoto, Tatsuo; Strnad, Miroslav; Schmülling, Thomas; Mitchum, Melissa G; Grundler, Florian M W

2015-10-13

Sedentary plant-parasitic cyst nematodes are biotrophs that cause significant losses in agriculture. Parasitism is based on modifications of host root cells that lead to the formation of a hypermetabolic feeding site (a syncytium) from which nematodes withdraw nutrients. The host cell cycle is activated in an initial cell selected by the nematode for feeding, followed by activation of neighboring cells and subsequent expansion of feeding site through fusion of hundreds of cells. It is generally assumed that nematodes manipulate production and signaling of the plant hormone cytokinin to activate cell division. In fact, nematodes have been shown to produce cytokinin in vitro; however, whether the hormone is secreted into host plants and plays a role in parasitism remained unknown. Here, we analyzed the spatiotemporal activation of cytokinin signaling during interaction between the cyst nematode, Heterodera schachtii, and Arabidopsis using cytokinin-responsive promoter:reporter lines. Our results showed that cytokinin signaling is activated not only in the syncytium but also in neighboring cells to be incorporated into syncytium. An analysis of nematode infection on mutants that are deficient in cytokinin or cytokinin signaling revealed a significant decrease in susceptibility of these plants to nematodes. Further, we identified a cytokinin-synthesizing isopentenyltransferase gene in H. schachtii and show that silencing of this gene in nematodes leads to a significant decrease in virulence due to a reduced expansion of feeding sites. Our findings demonstrate the ability of a plant-parasitic nematode to synthesize a functional plant hormone to manipulate the host system and establish a long-term parasitic interaction.

Neighboring and Urbanism: Commonality versus Friendship.

ERIC Educational Resources Information Center

Silverman, Carol J.

1986-01-01

Examines a dimension of neighboring that need not assume friendship as the role model. When the model assumes only a sense of connectedness as defining neighboring, then the residential correlation, shown in many studies between urbanism and neighboring, disappears. Theories of neighboring, study variables, methods, and analysis are discussed.…

Testing spatial theories of plant coexistence: no consistent differences in intra- and interspecific interaction distances.

PubMed

Vogt, Deborah R; Murrell, David J; Stoll, Peter

2010-01-01

Plants stand still and interact with their immediate neighbors. Theory has shown that the distances over which these interactions occur may have important consequences for population and community dynamics. In particular, if intraspecific competition occurs over longer distances than interspecific competition (heteromyopia), coexistence can be promoted. We examined how intraspecific and interspecific competition scales with neighbor distance in a target-neighbor greenhouse competition experiment. Individuals from co-occurring forbs from calcareous grasslands were grown in isolation and with single conspecific or heterospecific neighbors at distances of 5, 10, or 15 cm (Plantago lanceolata vs. Plantago media and Hieracium pilosella vs. Prunella grandiflora). Neighbor effects were strong and declined with distance. Interaction distances varied greatly within and between species, but we found no evidence for heteromyopia. Instead, neighbor identity effects were mostly explained by relative size differences between target and neighbor. We found a complex interaction between final neighbor size and identity such that neighbor identity may become important only as the neighbor becomes very large compared with the target individual. Our results suggest that species-specific size differences between neighboring individuals determine both the strength of competitive interactions and the distance over which these interactions occur.

Rattler behavior in As skutterudites and oxy-skutterudites

NASA Astrophysics Data System (ADS)

Bridges, Frank; Car, Brad; Hoffman-Stapleton, Mikaela; Keiber, Trevor; Sutton, Logan; Maple, M. Brian

2014-03-01

We report EXAFS measurements for the series CeX4As12 (X = Fe, Ru, Os) and NdCu3Ru4O12 as a function of temperature for most elements in the structure. In each case the rare earth atom is a ``rattler'' atom, with a low Einstein temperature while the skutterudite cage structure is relatively stiff. From temperature dependencies of the correlated Debye model for the cage atoms, one can estimate the effective spring constant for various atom pairs. We also find for the oxy-skutterudites that the planar CuO4 sub-structure is very stiff, and likely vibrates as a rigid unit. We compare the behavior of the As-skutterudites with other skutterudites and with the oxy-skutterudites, and discuss in terms of the rigid cage model. The second neighbor pair Ce-X for the As-skutterudites is softer than expected while for the oxy-skutterudites the second neighbor Nd-Ru pair is stiffer than the nearest neighbor Nd-O pair. Models are need to explore this behavior. Support: NSF DMR1005568.

Dielectric Properties of Poly(ethylene oxide) from Molecular Dynamics Simulations

NASA Technical Reports Server (NTRS)

Smith, Grant D.

1994-01-01

The order, conformations and dynamics of poly(oxyethylene) (POE) melts have been investigated through molecular dynamics simulations. The potential energy functions were determined from detailed ab initio electronic structure calculations of the conformational energies of the model molecules 1,2-dimethoxyethane (DME) and diethylether. The x-ray structure factor for POE from simulation will be compared to experiment. In terms of conformation, simulations reveal that chains are extended in the melt relative to isolated chains due to the presence of strong intermolecular O...H interactions, which occur at the expense of intramolecular O...H interactions. Conformational dynamics about the C-C bond were found to be significantly faster than in polymethylene, while conformational dynamics about the C-O bond even faster than the C-C dynamics. The faster local dynamics in POE relative to polymethylene is consistent with C-13 NMR spin-lattice relaxation experiments. Conformational transitions showed significant second-neighbor correlation, as was found for polymethylene. This correlation of transitions with C-C neighbors was found to be reduced relative to C-O neighbors. Dielectric relaxation from simulation will also be compared with experiment.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

PubMed

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

PubMed Central

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-01-01

Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN. PMID:19558694

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs

PubMed Central

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-01-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network. PMID:28763014

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

PubMed

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Rational selection of training and test sets for the development of validated QSAR models

NASA Astrophysics Data System (ADS)

Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

2003-02-01

Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

32 CFR 256.4 - Policy.

Code of Federal Regulations, 2010 CFR

2010-07-01

... installations and neighboring civilian communities by means of a compatible land use planning and control.... In all instances the primary objective will be to identify planning areas and reasonable land use guidelines which will be recommended to appropriate agencies who are in control of the planning functions for...

32 CFR 256.4 - Policy.

Code of Federal Regulations, 2011 CFR

2011-07-01

... installations and neighboring civilian communities by means of a compatible land use planning and control.... In all instances the primary objective will be to identify planning areas and reasonable land use guidelines which will be recommended to appropriate agencies who are in control of the planning functions for...

Cohesive Relations for Surface Atoms in the Iron-Technetium Binary System

DOE PAGES

Taylor, Christopher D.

2011-01-01

Iron-technetium alloys are of relevance to the development of waste forms for disposition of radioactive technetium-99 obtained from spent nuclear fuel. Corrosion of candidate waste forms is a function of the local cohesive energy () of surface atoms. A theoretical model for calculating is developed. Density functional theory was used to construct a modified embedded atom (MEAM) potential for iron-technetium. Materials properties determined for the iron-technetium system were in good agreement with the literature. To explore the relationship between local structure and corrosion, MEAM simulations were performed on representative iron-technetium alloys and intermetallics. Technetium-rich phases have lower , suggesting thatmore » these phases will be more noble than iron-rich ones. Quantitative estimates of based on numbers of nearest neighbors alone can lead to errors up to 0.5 eV. Consequently, atomistic corrosion simulations for alloy systems should utilize physics-based models that consider not only neighbor counts, but also local compositions and atomic arrangements.« less

Effect of the next-nearest-neighbor hopping on the charge collective modes in the paramagnetic phase of the Hubbard model

NASA Astrophysics Data System (ADS)

Dao, Vu Hung; Frésard, Raymond

2017-10-01

The charge dynamical response function of the t-t'-U Hubbard model is investigated on the square lattice in the thermodynamical limit. The correlation function is calculated from Gaussian fluctuations around the paramagnetic saddle-point within the Kotliar and Ruckenstein slave-boson representation. The next-nearest-neighbor hopping only slightly affects the renormalization of the quasiparticle mass. In contrast a negative t'/t notably decreases (increases) their velocity, and hence the zero-sound velocity, at positive (negative) doping. For low (high) density n ≲ 0.5 (n ≳ 1.5) we find that it enhances (reduces) the damping of the zero-sound mode. Furthermore it softens (hardens) the upper-Hubbard-band collective mode at positive (negative) doping. It is also shown that our results differ markedly from the random-phase approximation in the strong-coupling limit, even at high doping, while they compare favorably with existing quantum Monte Carlo numerical simulations.

Investigation of electronic transport through a ladder-like graphene nanoribbon including random distributed impurities

NASA Astrophysics Data System (ADS)

Esmaili, Esmat; Mardaani, Mohammad; Rabani, Hassan

2018-01-01

The electronic transport of a ladder-like graphene nanoribbon which the on-site or hopping energies of a small part of it can be random is modeled by using the Green's function technique within the nearest neighbor tight-binding approach. We employ a unitary transformation in order to convert the Hamiltonian of the nanoribbon to the Hamiltonian of a tight-binding ladder-like network. In this case, the disturbed part of the system includes the second neighbor hopping interactions. While, the converted Hamiltonian of each ideal part is equivalent to the Hamiltonian of two periodic on-site chains. Therefore, we can insert the self-energies of the alternative on-site tight-binding chains to the inverse of the Green's function matrix of the ladder-like part. In this viewpoint, the conductance is constructed from two trans and cis contributions. The results show that increasing the disorder strength causes the increase and decrease of the conductance of the trans and cis contributions, respectively.

Digital system for structural dynamics simulation

NASA Technical Reports Server (NTRS)

Krauter, A. I.; Lagace, L. J.; Wojnar, M. K.; Glor, C.

1982-01-01

State-of-the-art digital hardware and software for the simulation of complex structural dynamic interactions, such as those which occur in rotating structures (engine systems). System were incorporated in a designed to use an array of processors in which the computation for each physical subelement or functional subsystem would be assigned to a single specific processor in the simulator. These node processors are microprogrammed bit-slice microcomputers which function autonomously and can communicate with each other and a central control minicomputer over parallel digital lines. Inter-processor nearest neighbor communications busses pass the constants which represent physical constraints and boundary conditions. The node processors are connected to the six nearest neighbor node processors to simulate the actual physical interface of real substructures. Computer generated finite element mesh and force models can be developed with the aid of the central control minicomputer. The control computer also oversees the animation of a graphics display system, disk-based mass storage along with the individual processing elements.

Comprehensive thermodynamic analysis of 3′ double-nucleotide overhangs neighboring Watson–Crick terminal base pairs

PubMed Central

O'Toole, Amanda S.; Miller, Stacy; Haines, Nathan; Zink, M. Coleen; Serra, Martin J.

2006-01-01

Thermodynamic parameters are reported for duplex formation of 48 self-complementary RNA duplexes containing Watson–Crick terminal base pairs (GC, AU and UA) with all 16 possible 3′ double-nucleotide overhangs; mimicking the structures of short interfering RNAs (siRNA) and microRNAs (miRNA). Based on nearest-neighbor analysis, the addition of a second dangling nucleotide to a single 3′ dangling nucleotide increases stability of duplex formation up to 0.8 kcal/mol in a sequence dependent manner. Results from this study in conjunction with data from a previous study [A. S. O'Toole, S. Miller and M. J. Serra (2005) RNA, 11, 512.] allows for the development of a refined nearest-neighbor model to predict the influence of 3′ double-nucleotide overhangs on the stability of duplex formation. The model improves the prediction of free energy and melting temperature when tested against five oligomers with various core duplex sequences. Phylogenetic analysis of naturally occurring miRNAs was performed to support our results. Selection of the effector miR strand of the mature miRNA duplex appears to be dependent upon the identity of the 3′ double-nucleotide overhang. Thermodynamic parameters for 3′ single terminal overhangs adjacent to a UA pair are also presented. PMID:16820533

Two symmetry-breaking mechanisms for the development of orientation selectivity in a neural system

NASA Astrophysics Data System (ADS)

Cho, Myoung Won; Chun, Min Young

2015-11-01

Orientation selectivity is a remarkable feature of the neurons located in the primary visual cortex. Provided that the visual neurons acquire orientation selectivity through activity-dependent Hebbian learning, the development process could be understood as a kind of symmetry-breaking phenomenon in the view of physics. This paper examines the key mechanisms of the orientation selectivity development process. Be found that at least two different mechanisms, which lead to the development of orientation selectivity by breaking the radial symmetry in receptive fields. The first is a simultaneous symmetry-breaking mechanism occurring based on the competition between neighboring neurons, and the second is a spontaneous one occurring based on the nonlinearity in interactions. Only the second mechanism leads to the formation of a columnar pattern whose characteristics is in accord with those observed in an animal experiment.

Structural Transitions in Densifying Networks

NASA Astrophysics Data System (ADS)

Lambiotte, R.; Krapivsky, P. L.; Bhat, U.; Redner, S.

2016-11-01

We introduce a minimal generative model for densifying networks in which a new node attaches to a randomly selected target node and also to each of its neighbors with probability p . The networks that emerge from this copying mechanism are sparse for p <1/2 and dense (average degree increasing with number of nodes N ) for p ≥1/2 . The behavior in the dense regime is especially rich; for example, individual network realizations that are built by copying are disparate and not self-averaging. Further, there is an infinite sequence of structural anomalies at p =2/3 , 3/4 , 4/5 , etc., where the N dependences of the number of triangles (3-cliques), 4-cliques, undergo phase transitions. When linking to second neighbors of the target can occur, the probability that the resulting graph is complete—all nodes are connected—is nonzero as N →∞ .

Infrared small target detection based on multiscale center-surround contrast measure

NASA Astrophysics Data System (ADS)

Fu, Hao; Long, Yunli; Zhu, Ran; An, Wei

2018-04-01

Infrared(IR) small target detection plays a critical role in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained to the clutter environment. According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for infrared small target detection called multiscale centersurround contrast measure (MCSCM). First, to determine the maximum neighboring window size, an entropy-based window selection technique is used. Then, we construct a novel multiscale center-surround contrast measure to calculate the saliency map. Compared with the original image, the MCSCM map has less background clutters and noise residual. Subsequently, a simple threshold is used to segment the target. Experimental results show our method achieves better performance.

The NRL Program on Electroactive Polymers.

DTIC Science & Technology

1980-09-15

cell of a point in an aggregate involves selecting the smallest cell formed by planes perpendicularly bisecting all the point to neighbor vectors . Such...plane perpendicular to the interatomic vector is located nearer the smaller atom by bisecting the distance between the sur- faces of spheres whose...density waves (and consequent novel excitations such as solitons (6)). The physical structure as well as the chemical bonding of such polymeric

The Rhetoric of the Norwegian Constitution Day: A Topos Analysis of Young Norwegian Students' May 17 Speeches, 2011 and 2012

ERIC Educational Resources Information Center

Tønnesson, Johan Laurits; Sivesind, Kirsten

2016-01-01

National Day, or Constitution Day, in Norway, May 17, is often referred to as Children's Day. On this day, thousands of young Norwegian students march in parades and participate in celebrations in schoolyards and similar meeting places. Some students are selected to give speeches, performed in front of family members, neighbors, classmates, and…

Information Assurance in Sensor Networks

DTIC Science & Technology

2009-09-15

minority class instance and a randomly selected neighbor. Expanding on the SMOTE framework, the Borderline -SMOTE algorithm [15] locates those minority...instances form a Tomek link then they either both reside on the borderline of the two classes or one of them is attributed to noise; therefore, by...the synthetic dataset to testify the effectiveness of our proposed algorithm. Despite the popularity of STAGGER [76] and the SEA [77] synthetic

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

Revising traditional theory on the link between plant body size and fitness under competition: evidence from old-field vegetation

PubMed Central

Tracey, Amanda J; Aarssen, Lonnie W

2014-01-01

The selection consequences of competition in plants have been traditionally interpreted based on a “size-advantage” hypothesis – that is, under intense crowding/competition from neighbors, natural selection generally favors capacity for a relatively large plant body size. However, this conflicts with abundant data, showing that resident species body size distributions are usually strongly right-skewed at virtually all scales within vegetation. Using surveys within sample plots and a neighbor-removal experiment, we tested: (1) whether resident species that have a larger maximum potential body size (MAX) generally have more successful local individual recruitment, and thus greater local abundance/density (as predicted by the traditional size-advantage hypothesis); and (2) whether there is a general between-species trade-off relationship between MAX and capacity to produce offspring when body size is severely suppressed by crowding/competition – that is, whether resident species with a larger MAX generally also need to reach a larger minimum reproductive threshold size (MIN) before they can reproduce at all. The results showed that MIN had a positive relationship with MAX across resident species, and local density – as well as local density of just reproductive individuals – was generally greater for species with smaller MIN (and hence smaller MAX). In addition, the cleared neighborhoods of larger target species (which had relatively large MIN) generally had – in the following growing season – a lower ratio of conspecific recruitment within these neighborhoods relative to recruitment of other (i.e., smaller) species (which had generally smaller MIN). These data are consistent with an alternative hypothesis based on a ‘reproductive-economy-advantage’ – that is, superior fitness under competition in plants generally requires not larger potential body size, but rather superior capacity to recruit offspring that are in turn capable of producing grand-offspring – and hence transmitting genes to future generations – despite intense and persistent (cross-generational) crowding/competition from near neighbors. Selection for the latter is expected to favor relatively small minimum reproductive threshold size and hence – as a tradeoff – relatively small (not large) potential body size. PMID:24772274

Vegetation analysis for arid lands geobotany

NASA Technical Reports Server (NTRS)

Barbour, M. G.; Ustin, S. L.

1985-01-01

Three primary study sites were selected for measurement of plant phenological properties and spectral analysis. The sites selected represented typical sagebrush, creosote bush, and saltbush communities in Owens Valley, CA. Community composition was studied at these three sites plus five burned sites. Ten 50 m transects at each locality were measured for percent cover (over 10 cm) by a given species. On each transect two point quarter and five nearest neighbor analyses were conducted. These data provided percent cover, cover by area, plant size, tendency for association, and recolonization patterns after a disturbance. Plots representing percentage plant cover for six sites are included.

Coreceptors and Their Ligands in Epithelial γδ T Cell Biology

PubMed Central

Witherden, Deborah A.; Johnson, Margarete D.; Havran, Wendy L.

2018-01-01

Epithelial tissues line the body providing a protective barrier from the external environment. Maintenance of these epithelial barrier tissues critically relies on the presence of a functional resident T cell population. In some tissues, the resident T cell population is exclusively comprised of γδ T cells, while in others γδ T cells are found together with αβ T cells and other lymphocyte populations. Epithelial-resident γδ T cells function not only in the maintenance of the epithelium, but are also central to the repair process following damage from environmental and pathogenic insults. Key to their function is the crosstalk between γδ T cells and neighboring epithelial cells. This crosstalk relies on multiple receptor–ligand interactions through both the T cell receptor and accessory molecules leading to temporal and spatial regulation of cytokine, chemokine, growth factor, and extracellular matrix protein production. As antigens that activate epithelial γδ T cells are largely unknown and many classical costimulatory molecules and coreceptors are not used by these cells, efforts have focused on identification of novel coreceptors and ligands that mediate pivotal interactions between γδ T cells and their neighbors. In this review, we discuss recent advances in the understanding of functions for these coreceptors and their ligands in epithelial maintenance and repair processes. PMID:29686687

The basic tilted helix bundle domain of the prolyl isomerase FKBP25 is a novel double-stranded RNA binding module

PubMed Central

Dilworth, David; Bonnafous, Pierre; Edoo, Amiirah Bibi; Bourbigot, Sarah; Pesek-Jardim, Francy; Gudavicius, Geoff; Serpa, Jason J.; Petrotchenko, Evgeniy V.; Borchers, Christoph H.

2017-01-01

Abstract Prolyl isomerases are defined by a catalytic domain that facilitates the cis–trans interconversion of proline residues. In most cases, additional domains in these enzymes add important biological function, including recruitment to a set of protein substrates. Here, we report that the N-terminal basic tilted helix bundle (BTHB) domain of the human prolyl isomerase FKBP25 confers specific binding to double-stranded RNA (dsRNA). This binding is selective over DNA as well as single-stranded oligonucleotides. We find that FKBP25 RNA-association is required for its nucleolar localization and for the vast majority of its protein interactions, including those with 60S pre-ribosome and early ribosome biogenesis factors. An independent mobility of the BTHB and FKBP catalytic domains supports a model by which the N-terminus of FKBP25 is anchored to regions of dsRNA, whereas the FKBP domain is free to interact with neighboring proteins. Apart from the identification of the BTHB as a new dsRNA-binding module, this domain adds to the growing list of auxiliary functions used by prolyl isomerases to define their primary cellular targets. PMID:29036638

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Transferable tight-binding model for strained group IV and III-V materials and heterostructures

NASA Astrophysics Data System (ADS)

Tan, Yaohua; Povolotskyi, Michael; Kubis, Tillmann; Boykin, Timothy B.; Klimeck, Gerhard

2016-07-01

It is critical to capture the effect due to strain and material interface for device level transistor modeling. We introduce a transferable s p3d5s* tight-binding model with nearest-neighbor interactions for arbitrarily strained group IV and III-V materials. The tight-binding model is parametrized with respect to hybrid functional (HSE06) calculations for varieties of strained systems. The tight-binding calculations of ultrasmall superlattices formed by group IV and group III-V materials show good agreement with the corresponding HSE06 calculations. The application of the tight-binding model to superlattices demonstrates that the transferable tight-binding model with nearest-neighbor interactions can be obtained for group IV and III-V materials.

Spread of Epidemic on Complex Networks Under Voluntary Vaccination Mechanism

NASA Astrophysics Data System (ADS)

Xue, Shengjun; Ruan, Feng; Yin, Chuanyang; Zhang, Haifeng; Wang, Binghong

Under the assumption that the decision of vaccination is a voluntary behavior, in this paper, we use two forms of risk functions to characterize how susceptible individuals estimate the perceived risk of infection. One is uniform case, where each susceptible individual estimates the perceived risk of infection only based on the density of infection at each time step, so the risk function is only a function of the density of infection; another is preferential case, where each susceptible individual estimates the perceived risk of infection not only based on the density of infection but only related to its own activities/immediate neighbors (in network terminology, the activity or the number of immediate neighbors is the degree of node), so the risk function is a function of the density of infection and the degree of individuals. By investigating two different ways of estimating the risk of infection for susceptible individuals on complex network, we find that, for the preferential case, the spread of epidemic can be effectively controlled; yet, for the uniform case, voluntary vaccination mechanism is almost invalid in controlling the spread of epidemic on networks. Furthermore, given the temporality of some vaccines, the waves of epidemic for two cases are also different. Therefore, our work insight that the way of estimating the perceived risk of infection determines the decision on vaccination options, and then determines the success or failure of control strategy.

Electronic spectrum of trilayer graphene

NASA Astrophysics Data System (ADS)

Kumar, S.; Ajay

2014-08-01

Present work deals with the analysis of the single particle electronic spectral function in trilayer (ABC-, ABA- and AAA-stacked) graphene. Tight binding Hamiltonian containing intralayer nearest-neighbor and next-nearest neighbor hopping along-with the interlayer coupling parameter within two triangular sub-lattice approach for trilayer graphene has been employed. The expression of single particle spectral functions A(kw) is obtained within mean-field Green's function equations of motion approach. Spectral function at Γ, M and K points of the Brillouin zone has been numerically computed. It is pointed out that the nature of electronic states at different points of Brillouin zone is found to be influenced by stacking order and Coulomb interactions. At Γ and M points, a trilayer splitting is predicted while at K point a bilayer splitting effect is observed due to crossing of two bands (at K point). Interlayer coupling ( t_{ bot } ) is found to be responsible for the splitting of quasi-particle peaks at each point of Brillouin zone. The influence of t_{ bot } in trilayer graphene is prominent for AAA-stacking compared to ABC- and ABA-stacking. On the other hand, onsite Coulomb interaction reduces the trilayer splitting effect into bilayer splitting at Γ and M points of Brillouin zone and bilayer splitting into single peak spectral function at K point with a shifting of the peak away from Fermi level.

Random ensemble learning for EEG classification.

PubMed

Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid

2018-01-01

Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.

Speed of evolution on graphs

NASA Astrophysics Data System (ADS)

Sui, Xiukai; Wu, Bin; Wang, Long

2015-12-01

The likelihood that a mutant fixates in the wild population, i.e., fixation probability, has been intensively studied in evolutionary game theory, where individuals' fitness is frequency dependent. However, it is of limited interest when it takes long to take over. Thus the speed of evolution becomes an important issue. In general, it is still unclear how fixation times are affected by the population structure, although the fixation times have already been addressed in the well-mixed populations. Here we theoretically address this issue by pair approximation and diffusion approximation on regular graphs. It is shown (i) that under neutral selection, both unconditional and conditional fixation time are shortened by increasing the number of neighbors; (ii) that under weak selection, for the simplified prisoner's dilemma game, if benefit-to-cost ratio exceeds the degree of the graph, then the unconditional fixation time of a single cooperator is slower than that in the neutral case; and (iii) that under weak selection, for the conditional fixation time, limited neighbor size dilutes the counterintuitive stochastic slowdown which was found in well-mixed populations. Interestingly, we find that all of our results can be interpreted as that in the well-mixed population with a transformed payoff matrix. This interpretation is also valid for both death-birth and birth-death processes on graphs. This interpretation bridges the fixation time in the structured population and that in the well-mixed population. Thus it opens the avenue to investigate the challenging fixation time in structured populations by the known results in well-mixed populations.

Crosstalk between reticular adherens junctions and platelet endothelial cell adhesion molecule-1 regulates endothelial barrier function.

PubMed

Fernández-Martín, Laura; Marcos-Ramiro, Beatriz; Bigarella, Carolina L; Graupera, Mariona; Cain, Robert J; Reglero-Real, Natalia; Jiménez, Anaïs; Cernuda-Morollón, Eva; Correas, Isabel; Cox, Susan; Ridley, Anne J; Millán, Jaime

2012-08-01

Endothelial cells provide a barrier between the blood and tissues, which is reduced during inflammation to allow selective passage of molecules and cells. Adherens junctions (AJ) play a central role in regulating this barrier. We aim to investigate the role of a distinctive 3-dimensional reticular network of AJ found in the endothelium. In endothelial AJ, vascular endothelial-cadherin recruits the cytoplasmic proteins β-catenin and p120-catenin. β-catenin binds to α-catenin, which links AJ to actin filaments. AJ are usually described as linear structures along the actin-rich intercellular contacts. Here, we show that these AJ components can also be organized in reticular domains that contain low levels of actin. Reticular AJ are localized in areas where neighboring cells overlap and encompass the cell adhesion receptor platelet endothelial cell adhesion molecule-1 (PECAM-1). Superresolution microscopy revealed that PECAM-1 forms discrete structures distinct from and distributed along AJ, within the voids of reticular domains. Inflammatory tumor necrosis factor-α increases permeability by mechanisms that are independent of actomyosin-mediated tension and remain incompletely understood. Reticular AJ, but not actin-rich linear AJ, were disorganized by tumor necrosis factor-α. This correlated with PECAM-1 dispersal from cell borders. PECAM-1 inhibition with blocking antibodies or small interfering RNA specifically disrupted reticular AJ, leaving linear AJ intact. This disruption recapitulated typical tumor necrosis factor-α-induced alterations of barrier function, including increased β-catenin phosphorylation, without altering the actomyosin cytoskeleton. We propose that reticular AJ act coordinately with PECAM-1 to maintain endothelial barrier function in regions of low actomyosin-mediated tension. Selective disruption of reticular AJ contributes to permeability increase in response to tumor necrosis factor-α.

Maximal Neighbor Similarity Reveals Real Communities in Networks

PubMed Central

Žalik, Krista Rizman

2015-01-01

An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pairs of nodes and their maximal similar neighbors we find real communities. We show that the overall advantage of the proposed algorithm compared to the other community detection algorithms is its simple nature, low computational cost and its very high accuracy in detection communities of different sizes also in networks with blurred modularity structure consisting of poorly separated communities. All communities identified by the proposed method for facebook network and E-Coli transcriptional regulatory network have strong structural and functional coherence. PMID:26680448

Trend of hepatocellular carcinoma incidence after Bayesian correction for misclassified data in Iranian provinces.

PubMed

Hajizadeh, Nastaran; Baghestani, Ahmad Reza; Pourhoseingholi, Mohamad Amin; Ashtari, Sara; Fazeli, Zeinab; Vahedi, Mohsen; Zali, Mohammad Reza

2017-05-28

To study the trend of hepatocellular carcinoma incidence after correcting the misclassification in registering cancer incidence across Iranian provinces in cancer registry data. Incidence data of hepatocellular carcinoma were extracted from Iranian annual of national cancer registration reports 2004 to 2008. A Bayesian method was implemented to estimate the rate of misclassification in registering cancer incidence in neighboring province. A beta prior is considered for misclassification parameter. Each time two neighboring provinces were selected to be entered in the Bayesian model based on their expected coverage of cancer cases which is reported by medical university of the province. It is assumed that some cancer cases from a province that has an expected coverage of cancer cases lower than 100% are registered in their neighboring facilitate province with more than 100% expected coverage. There is an increase in the rate of hepatocellular carcinoma in Iran. Among total of 30 provinces of Iran, 21 provinces were selected to be entered to the Bayesian model for correcting the existed misclassification. Provinces with more medical facilities of Iran are Tehran (capital of the country), Razavi Khorasan in north-east of Iran, East Azerbaijan in north-west of the country, Isfahan in central part and near to Tehran, Khozestan and Fars in south and Mazandaran in north of the Iran, had an expected coverage more than their expectation. Those provinces had significantly higher rates of hepatocellular carcinoma than their neighboring provinces. In years 2004 to 2008, it was estimated to be on average 34% misclassification between North Khorasan province and Razavi Khorasan, 43% between South Khorasan province and Razavi Khorasan, 47% between Sistan and balochestan province and Razavi Khorasan, 23% between West Azerbaijan province and East Azerbaijan province, 25% between Ardebil province and East Azerbaijan province, 41% between Hormozgan province and Fars province, 22% betweenChaharmahal and bakhtyari province and Isfahan province, 22% between Kogiloye and boyerahmad province and Isfahan, 22% between Golestan province and Mazandaran province, 43% between Bushehr province and Khozestan province, 41% between Ilam province and Khuzestan province, 42% between Qazvin province and Tehran province, 44% between Markazi province and Tehran, and 30% between Qom province and Tehran. Accounting and correcting the regional misclassification is necessary for identifying high risk areas and planning for reducing the cancer incidence.

Ultracold fermions in a one-dimensional bipartite optical lattice: Metal-insulator transitions driven by shaking

NASA Astrophysics Data System (ADS)

Di Liberto, M.; Malpetti, D.; Japaridze, G. I.; Morais Smith, C.

2014-08-01

We theoretically investigate the behavior of a system of fermionic atoms loaded in a bipartite one-dimensional optical lattice that is under the action of an external time-periodic driving force. By using Floquet theory, an effective model is derived. The bare hopping coefficients are renormalized by zeroth-order Bessel functions of the first kind with different arguments for the nearest-neighbor and next-nearest-neighbor hopping. The insulating behavior characterizing the system at half filling in the absence of driving is dynamically suppressed, and for particular values of the driving parameter the system becomes either a standard metal or an unconventional metal with four Fermi points. The existence of the four-Fermi-point metal relies on the fact that, as a consequence of the shaking procedure, the next-nearest-neighbor hopping coefficients become significant compared to the nearest-neighbor ones. We use the bosonization technique to investigate the effect of on-site Hubbard interactions on the four-Fermi-point metal-insulator phase transition. Attractive interactions are expected to enlarge the regime of parameters where the unconventional metallic phase arises, whereas repulsive interactions reduce it. This metallic phase is known to be a Luther-Emery liquid (spin-gapped metal) for both repulsive and attractive interactions, contrary to the usual Hubbard model, which exhibits a Mott-insulator phase for repulsive interactions. Ultracold fermions in driven one-dimensional bipartite optical lattices provide an interesting platform for the realization of this long-studied four-Fermi-point unconventional metal.

Band nesting, massive Dirac fermions, and valley Landé and Zeeman effects in transition metal dichalcogenides: A tight-binding model

NASA Astrophysics Data System (ADS)

Bieniek, Maciej; Korkusiński, Marek; Szulakowska, Ludmiła; Potasz, Paweł; Ozfidan, Isil; Hawrylak, Paweł

2018-02-01

We present here the minimal tight-binding model for a single layer of transition metal dichalcogenides (TMDCs) MX 2(M , metal; X , chalcogen) which illuminates the physics and captures band nesting, massive Dirac fermions, and valley Landé and Zeeman magnetic field effects. TMDCs share the hexagonal lattice with graphene but their electronic bands require much more complex atomic orbitals. Using symmetry arguments, a minimal basis consisting of three metal d orbitals and three chalcogen dimer p orbitals is constructed. The tunneling matrix elements between nearest-neighbor metal and chalcogen orbitals are explicitly derived at K ,-K , and Γ points of the Brillouin zone. The nearest-neighbor tunneling matrix elements connect specific metal and sulfur orbitals yielding an effective 6 ×6 Hamiltonian giving correct composition of metal and chalcogen orbitals but not the direct gap at K points. The direct gap at K , correct masses, and conduction band minima at Q points responsible for band nesting are obtained by inclusion of next-neighbor Mo-Mo tunneling. The parameters of the next-nearest-neighbor model are successfully fitted to MX 2(M =Mo ; X =S ) density functional ab initio calculations of the highest valence and lowest conduction band dispersion along K -Γ line in the Brillouin zone. The effective two-band massive Dirac Hamiltonian for MoS2, Landé g factors, and valley Zeeman splitting are obtained.

Neuroscience Reveals that Boredom Hurts

ERIC Educational Resources Information Center

Willis, Judy

2014-01-01

The student who appears lazy, intentionally oppositional, or who seems to willfully ignore admonitions to pay attention, apply more effort, or to stop talking to his neighbor or texting may not be making voluntary choices. These students' brains may be responding to the stress of sustained or frequent boredom. Functional neuroimaging and…

The Origins of Order: Self-Organization and Selection in Evolution

NASA Astrophysics Data System (ADS)

Kauffman, Stuart A.

The following sections are included: * Introduction * Fitness Landscapes in Sequence Space * The NK Model of Rugged Fitness Landscapes * The NK Model of Random Epistatic Interactions * The Rank Order Statistics on K = N - 1 Random Landscapes * The number of local optima is very large * The expected fraction of fitter 1-mutant neighbors dwindles by 1/2 on each improvement step * Walks to local optima are short and vary as a logarithmic function of N * The expected time to reach an optimum is proportional to the dimensionality of the space * The ratio of accepted to tried mutations scales as lnN/N * Any genotype can only climb to a small fraction of the local optima * A small fraction of the genotypes can climb to any one optimum * Conflicting constraints cause a "complexity catastrophe": as complexity increase accessible adaptive peaks fall toward the mean fitness * The "Tunable" NK Family of Correlated Landscapes * Other Combinatorial Optimization Problems and Their Landscapes * Summary * References

Structural basis for subtype-specific inhibition of the P2X7 receptor

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

Karasawa, Akira; Kawate, Toshimitsu

The P2X7 receptor is a non-selective cation channel activated by extracellular adenosine triphosphate (ATP). Chronic activation of P2X7 underlies many health problems such as pathologic pain, yet we lack effective antagonists due to poorly understood mechanisms of inhibition. Here we present crystal structures of a mammalian P2X7 receptor complexed with five structurally-unrelated antagonists. Unexpectedly, these drugs all bind to an allosteric site distinct from the ATP-binding pocket in a groove formed between two neighboring subunits. This novel drug-binding pocket accommodates a diversity of small molecules mainly through hydrophobic interactions. Functional assays propose that these compounds allosterically prevent narrowing of themore » drug-binding pocket and the turret-like architecture during channel opening, which is consistent with a site of action distal to the ATP-binding pocket. These novel mechanistic insights will facilitate the development of P2X7-specific drugs for treating human diseases.« less

A Model for Displacements Between Parallel Plates That Shows Change of Type from Hyperbolic to Elliptic

NASA Astrophysics Data System (ADS)

Shariati, Maryam; Yortsos, Yannis; Talon, Laurent; Martin, Jerome; Rakotomalala, Nicole; Salin, Dominique

2003-11-01

We consider miscible displacement between parallel plates, where the viscosity is a function of the concentration. By selecting a piece-wise representation, the problem can be considered as ``three-phase'' flow. Assuming a lubrication-type approximation, the mathematical description is in terms of two quasi-linear hyperbolic equations. When the mobility of the middle phase is smaller than its neighbors, the system is genuinely hyperbolic and can be solved analytically. However, when it is larger, an elliptic region develops. This change-of-type behavior is for the first time proved here based on sound physical principles. Numerical solutions with a small diffusion are presented. Good agreement is obtained outside the elliptic region, but not inside, where the numerical results show unstable behavior. We conjecture that for the solution of the real problem in the mixed-type case, the full higher-dimensionality problem must be considered inside the elliptic region, in which the lubrication (parallel-flow) approximation is no longer appropriate. This is discussed in a companion presentation.

Frustrated spin-1/2 Ising antiferromagnet on a square lattice in a transverse field

NASA Astrophysics Data System (ADS)

Bobák, A.; Jurčišinová, E.; Jurčišin, M.; Žukovič, M.

2018-02-01

We investigate the phase transitions and tricritical behaviors of the frustrated Ising antiferromagnet with first- (J1<0 ) and second- (J2<0 ) nearest-neighbor interactions in a transverse field Ω on the square lattice using an effective-field theory with correlations based on a single-spin approximation. We have proposed a functional for the free energy to obtain the phase diagram in the T -R (R =J2/|J1| ) or T -Ω planes. It is shown that due to the transverse field the phase transition between ordered and disordered phases changes in the tricritical point (TCP) from the second order to the first order. The longitudinal and transverse magnetizations are also studied for selected values of R and Ω . In particular, the variation of TCP at the ground state in the three-dimensional space is constructed. For some special cases, values of the critical temperature and the critical transverse field have been determined analytically.

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2012-01-01

This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.

The domestic participation in birth assistance in the mid-twentieth century

PubMed Central

Díaz, Elena Andina; González, José Siles

2016-01-01

Abstract Objective: to describe how the progressive creation of the Social Security (providing widespread health care) affected the birth assistance in Spain from the 1940s to the 1970s in a rural area. Method: historical ethnography. Twenty-seven people who lived at that time were selected and interviewed guided by a semistructured script. Based on their testimonies, a chart was built with the functional elements involved in birth assistance in this region. Results: three agents performed such care: traditional midwives, women of the family/neighbors and health workers. Conclusion: although birth assistance had been transferred to the hands of the health workers from the forties in this region, women in labor continued to count on the domestic resources until the early seventies, when births were compulsorily transferred to hospitals. This research brings to light the names and recognizes the work performed by these female characters of the popular sphere, who helped women in labor of that community to give birth, for at least three decades. PMID:27463108

Cell-to-cell movement of plastids in plants.

PubMed

Thyssen, Gregory; Svab, Zora; Maliga, Pal

2012-02-14

Our objective was to test whether or not plastids and mitochondria, the two DNA-containing organelles, move between cells in plants. As our experimental approach, we grafted two different species of tobacco, Nicotiana tabacum and Nicotiana sylvestris. Grafting triggers formation of new cell-to-cell contacts, creating an opportunity to detect cell-to-cell organelle movement between the genetically distinct plants. We initiated tissue culture from sliced graft junctions and selected for clonal lines in which gentamycin resistance encoded in the N. tabacum nucleus was combined with spectinomycin resistance encoded in N. sylvestris plastids. Here, we present evidence for cell-to-cell movement of the entire 161-kb plastid genome in these plants, most likely in intact plastids. We also found that the related mitochondria were absent, suggesting independent movement of the two DNA-containing organelles. Acquisition of plastids from neighboring cells provides a mechanism by which cells may be repopulated with functioning organelles. Our finding supports the universality of intercellular organelle trafficking and may enable development of future biotechnological applications.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

NASA Astrophysics Data System (ADS)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks

PubMed Central

Jiang, Peng; Xu, Yiming; Liu, Jun

2017-01-01

For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime. PMID:28106837

A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks.

PubMed

Jiang, Peng; Xu, Yiming; Liu, Jun

2017-01-19

For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes' being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network's best service quality and lifetime.

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

Giraldo, L. Ocampo; Bolotnikov, A. E.; Camarda, G. S.

For this study, we evaluated the X-Y position resolution achievable in 3D pixelated detectors by processing the signal waveforms readout from neighboring pixels. In these measurements we used a focused light beam, down to 10 μm, generated by a ~1 mW pulsed laser (650 nm) to carry out raster scans over selected 3×3 pixel areas, while recording the charge signals from the 9 pixels and the cathode using two synchronized digital oscilloscopes.

The Information Processing Role of the Informal and Quasi-Formal Support Systems among the Hispanic Elderly: Implications for the Delivery of Formal Social Services.

ERIC Educational Resources Information Center

Starrett, Richard A.; And Others

The study examined relationships among factors influencing utilization of social services by Hispanic elderly, particularly factors categorized as: (1) informal, such as support groups of family, kin, neighbors, friends, and (2) quasi-formal, such as church groups. Thirty-seven variables and data selected from a 1979-80 15-state survey of 1,805…

Future of the Rural Elderly. Hearing before the Select Committee on Aging, House of Representatives, One Hundredth Congress, Second Session (Pittsburg, Kansas, June 13, 1988).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Select Committee on Aging.

This document contains testimony of witnesses in a field hearing on the future of the rural elderly. The opening statement by Representative Bob Whittaker (Kansas) notes that the aging of America creates a more difficult time for the rural elderly than their urban neighbors. Distance and low population density magnify the difficulties of…

Adult and Child Semantic Neighbors of the Kroll and Potter (1984) Nonobjects

PubMed Central

Storkel, Holly L.; Adlof, Suzanne M.

2008-01-01

Purpose The purpose was to determine the number of semantic neighbors, namely semantic set size, for 88 nonobjects (Kroll & Potter, 1984) and determine how semantic set size related to other measures and age. Method Data were collected from 82 adults and 92 preschool children in a discrete association task. The nonobjects were presented via computer, and participants reported the first word that came to mind that was meaningfully related to the nonobject. Words reported by two or more participants were considered semantic neighbors. The strength of each neighbor was computed as the proportion of participants who reported the neighbor. Results Results showed that semantic set size was not significantly correlated with objectlikeness ratings or object decision reaction times from Kroll and Potter (1984). However, semantic set size was significantly negatively correlated with the strength of the strongest neighbor(s). In terms of age effects, adult and child semantic set sizes were significantly positively correlated and the majority of numeric differences were on the order of 0–3 neighbors. Comparison of actual neighbors showed greater discrepancies; however, this varied by neighbor strength. Conclusions Semantic set size can be determined for nonobjects. Specific guidelines are suggested for using these nonobjects in future research. PMID:19252127

Continuity and Change in Relationships with Neighbors: Implications for Psychological Well-being in Middle and Later Life

PubMed Central

Reyes, Laurent

2015-01-01

Objectives. There is growing enthusiasm for community initiatives that aim to strengthen neighbor relationships to promote well-being in later life. Nevertheless, few studies have examined the extent to which relationships with neighbors are associated with better psychological well-being among midlife and older adults. Methods. We used data from 1,071 noninstitutionalized, English-speaking adults, aged 40–70 years, who participated in both waves of the 1995–2005 National Survey of Midlife Development in the United States. Lagged dependent regression models were estimated to examine associations between changes in two dimensions of neighbor relationships (contact and perceived support) and psychological well-being. Results. Few associations were found between relationships with neighbors and negative or positive affect. In contrast, having continuously low levels of contact with neighbors, or losing contact with neighbors over the 10-year study period, was associated with declining levels of eudaimonic well-being. Associations between contact and this aspect of well-being were explained, in part, by less perceived support from neighbors. Discussion. Results suggest that continuity and change in relationships with neighbors is especially important for more developmental aspects of psychological well-being. Implications for future research on the meaning of neighbor relationships and aging in community are discussed. PMID:25106785

Assortative and dissortative priorities for game interaction and strategy adaptation significantly bolster network reciprocity in the prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-05-01

In 2 × 2 prisoner’s dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. Here we show that combining the process for selecting a gaming partner with the process for selecting an adaptation partner significantly enhances cooperation, even though such selection processes require additional costs to collect further information concerning which neighbor should be chosen. Based on elaborate investigations of the dynamics generated by our model, we find that high levels of cooperation result from two kinds of behavior: cooperators tend to interact with cooperators to prevent being exploited by defectors and defectors tend to choose cooperators to exploit despite the possibility that some defectors convert to cooperators.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

PubMed

Sadeh, Sadra; Rotter, Stefan

2015-01-01

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity.

Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons: Effect of Single Neuron Properties and Network Dynamics

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2015-01-01

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity. PMID:25569445

Neutral evolution of proteins: The superfunnel in sequence space and its relation to mutational robustness

NASA Astrophysics Data System (ADS)

Noirel, Josselin; Simonson, Thomas

2008-11-01

Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate μ and the population size N, the biological population can evolve purely randomly (μN ≪1) or it can evolve in such a way as to select for sequences of higher mutational robustness (μN ≫1). The stringency of the selection depends not only on the product μN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular modeling.

Neutral evolution of proteins: The superfunnel in sequence space and its relation to mutational robustness.

PubMed

Noirel, Josselin; Simonson, Thomas

2008-11-14

Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate mu and the population size N, the biological population can evolve purely randomly (muN<1) or it can evolve in such a way as to select for sequences of higher mutational robustness (muN>1). The stringency of the selection depends not only on the product muN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular modeling.

Automated corresponding point candidate selection for image registration using wavelet transformation neurla network with rotation invariant inputs and context information about neighboring candidates

NASA Astrophysics Data System (ADS)

Okumura, Hiroshi; Suezaki, Masashi; Sueyasu, Hideki; Arai, Kohei

2003-03-01

An automated method that can select corresponding point candidates is developed. This method has the following three features: 1) employment of the RIN-net for corresponding point candidate selection; 2) employment of multi resolution analysis with Haar wavelet transformation for improvement of selection accuracy and noise tolerance; 3) employment of context information about corresponding point candidates for screening of selected candidates. Here, the 'RIN-net' means the back-propagation trained feed-forward 3-layer artificial neural network that feeds rotation invariants as input data. In our system, pseudo Zernike moments are employed as the rotation invariants. The RIN-net has N x N pixels field of view (FOV). Some experiments are conducted to evaluate corresponding point candidate selection capability of the proposed method by using various kinds of remotely sensed images. The experimental results show the proposed method achieves fewer training patterns, less training time, and higher selection accuracy than conventional method.

Genetic and phenotypic differentiation of an Andean intermediate altitude population

PubMed Central

Eichstaedt, Christina A; Antão, Tiago; Cardona, Alexia; Pagani, Luca; Kivisild, Toomas; Mormina, Maru

2015-01-01

Highland populations living permanently under hypobaric hypoxia have been subject of extensive research because of the relevance of their physiological adaptations for the understanding of human health and disease. In this context, what is considered high altitude is a matter of interpretation and while the adaptive processes at high altitude (above 3000 m) are well documented, the effects of moderate altitude (below 3000 m) on the phenotype are less well established. In this study, we compare physiological and anthropometric characteristics as well as genetic variations in two Andean populations: the Calchaquíes (2300 m) and neighboring Collas (3500 m). We compare their phenotype and genotype to the sea-level Wichí population. We measured physiological (heart rate, oxygen saturation, respiration rate, and lung function) as well as anthropometric traits (height, sitting height, weight, forearm, and tibia length). We conducted genome-wide genotyping on a subset of the sample (n = 74) and performed various scans for positive selection. At the phenotypic level (n = 179), increased lung capacity stood out in both Andean groups, whereas a growth reduction in distal limbs was only observed at high altitude. At the genome level, Calchaquíes revealed strong signals around PRKG1, suggesting that the nitric oxide pathway may be a target of selection. PRKG1 was highlighted by one of four selection tests among the top five genes using the population branch statistic. Selection tests results of Collas were reported previously. Overall, our study shows that some phenotypic and genetic differentiation occurs at intermediate altitude in response to moderate lifelong selection pressures. PMID:25948820

The sound of enemies and friends in the neighborhood.

PubMed

Pecher, Diane; Boot, Inge; van Dantzig, Saskia; Madden, Carol J; Huber, David E; Zeelenberg, René

2011-01-01

Previous studies (e.g., Pecher, Zeelenberg, & Wagenmakers, 2005) found that semantic classification performance is better for target words with orthographic neighbors that are mostly from the same semantic class (e.g., living) compared to target words with orthographic neighbors that are mostly from the opposite semantic class (e.g., nonliving). In the present study we investigated the contribution of phonology to orthographic neighborhood effects by comparing effects of phonologically congruent orthographic neighbors (book-hook) to phonologically incongruent orthographic neighbors (sand-wand). The prior presentation of a semantically congruent word produced larger effects on subsequent animacy decisions when the previously presented word was a phonologically congruent neighbor than when it was a phonologically incongruent neighbor. In a second experiment, performance differences between target words with versus without semantically congruent orthographic neighbors were larger if the orthographic neighbors were also phonologically congruent. These results support models of visual word recognition that assume an important role for phonology in cascaded access to meaning.

The response of the soil microbial food web to extreme rainfall under different plant systems

NASA Astrophysics Data System (ADS)

Sun, Feng; Pan, Kaiwen; Tariq, Akash; Zhang, Lin; Sun, Xiaoming; Li, Zilong; Wang, Sizhong; Xiong, Qinli; Song, Dagang; Olatunji, Olusanya Abiodun

2016-11-01

An agroforestry experiment was conducted that involved four planting systems: monoculture of the focal species Zanthoxylum bungeanum and mixed cultures of Z. bungeanum and Capsicum annuum, Z. bungeanum and Medicago sativa and Z. bungeanum and Glycine max. Soil microbial food web (microorganisms and nematodes) was investigated under manipulated extreme rainfall in the four planting systems to assess whether presence of neighbor species alleviated the magnitude of extreme rainfall on nutrient uptake of the focal species by increasing the stability of soil food web. Our results indicate that in the focal species and G. max mixed culture, leaf nitrogen contents of the focal species were higher than in the monoculture and in the other mixed cultures under extreme rainfall. This result was mainly due to the significant increase under extreme rainfall of G. max species root biomass, resulting in enhanced microbial resistance and subsequent net nitrogen mineralization rate and leaf nitrogen uptake for the focal species. Differences in functional traits of neighbors had additive effects and led to a marked divergence of soil food-web resistance and nutrient uptake of the focal species. Climate change can indirectly alleviate focal species via its influence on their neighbors.

The response of the soil microbial food web to extreme rainfall under different plant systems

PubMed Central

Sun, Feng; Pan, Kaiwen; Tariq, Akash; Zhang, Lin; Sun, Xiaoming; Li, Zilong; Wang, Sizhong; Xiong, Qinli; Song, Dagang; Olatunji, Olusanya Abiodun

2016-01-01

An agroforestry experiment was conducted that involved four planting systems: monoculture of the focal species Zanthoxylum bungeanum and mixed cultures of Z. bungeanum and Capsicum annuum, Z. bungeanum and Medicago sativa and Z. bungeanum and Glycine max. Soil microbial food web (microorganisms and nematodes) was investigated under manipulated extreme rainfall in the four planting systems to assess whether presence of neighbor species alleviated the magnitude of extreme rainfall on nutrient uptake of the focal species by increasing the stability of soil food web. Our results indicate that in the focal species and G. max mixed culture, leaf nitrogen contents of the focal species were higher than in the monoculture and in the other mixed cultures under extreme rainfall. This result was mainly due to the significant increase under extreme rainfall of G. max species root biomass, resulting in enhanced microbial resistance and subsequent net nitrogen mineralization rate and leaf nitrogen uptake for the focal species. Differences in functional traits of neighbors had additive effects and led to a marked divergence of soil food-web resistance and nutrient uptake of the focal species. Climate change can indirectly alleviate focal species via its influence on their neighbors. PMID:27874081

Energy management of three-dimensional minimum-time intercept. [for aircraft flight optimization

NASA Technical Reports Server (NTRS)

Kelley, H. J.; Cliff, E. M.; Visser, H. G.

1985-01-01

A real-time computer algorithm to control and optimize aircraft flight profiles is described and applied to a three-dimensional minimum-time intercept mission. The proposed scheme has roots in two well known techniques: singular perturbations and neighboring-optimal guidance. Use of singular-perturbation ideas is made in terms of the assumed trajectory-family structure. A heading/energy family of prestored point-mass-model state-Euler solutions is used as the baseline in this scheme. The next step is to generate a near-optimal guidance law that will transfer the aircraft to the vicinity of this reference family. The control commands fed to the autopilot (bank angle and load factor) consist of the reference controls plus correction terms which are linear combinations of the altitude and path-angle deviations from reference values, weighted by a set of precalculated gains. In this respect the proposed scheme resembles neighboring-optimal guidance. However, in contrast to the neighboring-optimal guidance scheme, the reference control and state variables as well as the feedback gains are stored as functions of energy and heading in the present approach. Some numerical results comparing open-loop optimal and approximate feedback solutions are presented.

Disentangling neighbors and extended range density oscillations in monatomic amorphous semiconductors.

PubMed

Roorda, S; Martin, C; Droui, M; Chicoine, M; Kazimirov, A; Kycia, S

2012-06-22

High energy x-ray diffraction measurements of pure amorphous Ge were made and its radial distribution function (RDF) was determined at high resolution, revealing new information on the atomic structure of amorphous semiconductors. Fine structure in the second peak in the RDF provides evidence that a fraction of third neighbors are closer than some second neighbors; taking this into account leads to a narrow distribution of tetrahedral bond angles, (8.5 ± 0.1)°. A small peak which appears near 5 Å upon thermal annealing shows that some ordering in the dihedral bond-angle distribution takes place during structural relaxation. Extended range order is detected (in both a-Ge and a-Si) which persists to beyond 20 Å, and both the periodicity and its decay length increase upon thermal annealing. Previously, the effect of structural relaxation was only detected at intermediate range, involving reduced tetrahedral bond-angle distortions. These results enhance our understanding of the atomic order in continuous random networks and place significantly more stringent requirements on computer models intending to describe these networks, or their alternatives which attempt to describe the structure in terms of an arrangement of paracrystals.

Seeing Is Not Feeling: Posterior Parietal But Not Somatosensory Cortex Engagement During Touch Observation

PubMed Central

Baker, Chris I.

2015-01-01

Observing touch has been reported to elicit activation in human primary and secondary somatosensory cortices and is suggested to underlie our ability to interpret other's behavior and potentially empathy. However, despite these reports, there are a large number of inconsistencies in terms of the precise topography of activation, the extent of hemispheric lateralization, and what aspects of the stimulus are necessary to drive responses. To address these issues, we investigated the localization and functional properties of regions responsive to observed touch in a large group of participants (n = 40). Surprisingly, even with a lenient contrast of hand brushing versus brushing alone, we did not find any selective activation for observed touch in the hand regions of somatosensory cortex but rather in superior and inferior portions of neighboring posterior parietal cortex, predominantly in the left hemisphere. These regions in the posterior parietal cortex required the presence of both brush and hand to elicit strong responses and showed some selectivity for the form of the object or agent of touch. Furthermore, the inferior parietal region showed nonspecific tactile and motor responses, suggesting some similarity to area PFG in the monkey. Collectively, our findings challenge the automatic engagement of somatosensory cortex when observing touch, suggest mislocalization in previous studies, and instead highlight the role of posterior parietal cortex. PMID:25632124

Recent Advances in the Separation of Rare Earth Elements Using Mesoporous Hybrid Materials.

PubMed

Hu, Yimu; Florek, Justyna; Larivière, Dominic; Fontaine, Frédéric-Georges; Kleitz, Freddy

2018-05-27

Over the past decades, the need for rare earth elements (REEs) has increased substantially, mostly because these elements are used as valuable additives in advanced technologies. However, the difference in ionic radius between neighboring REEs is small, which renders an efficient sized-based separation extremely challenging. Among different types of extraction methods, solid-phase extraction (SPE) is a promising candidate, featuring high enrichment factor, rapid adsorption kinetics, reduced solvent consumption and minimized waste generation. The great challenge remains yet to develop highly efficient and selective adsorbents for this process. In this regard, ordered mesoporous materials (OMMs) possess high specific surface area, tunable pore size, large pore volume, as well as stable and interconnected frameworks with active pore surfaces for functionalization. Such features meet the requirements for enhanced adsorbents, not only providing huge reactional interface and large surface capable of accommodating guest species, but also enabling the possibility of ion-specific binding for enrichment and separation purposes. This short personal account summarizes some of the recent advances in the use of porous hybrid materials as selective sorbents for REE separation and purification, with particular attention devoted to ordered mesoporous silica and carbon-based sorbents. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca).

PubMed

Zheng, Yang; Cai, Jing; Li, JianWen; Li, Bo; Lin, Runmao; Tian, Feng; Wang, XiaoLing; Wang, Jun

2010-01-01

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

Secreting and sensing the same molecule allows cells to achieve versatile social behaviors

PubMed Central

Youk, Hyun; Lim, Wendell A.

2014-01-01

Cells that secrete and sense the same signaling molecule are ubiquitous. To uncover the functional capabilities of the core ‘secrete-and-sense’ circuit motif shared by these cells, we engineered yeast to secrete and sense the mating pheromone. Perturbing each circuit element revealed parameters that control the degree to which the cell communicated with itself versus with its neighbors. This tunable interplay of self- and neighbor-communication enables cells to span a diverse repertoire of cellular behaviors. These include a cell being asocial by responding only to itself, social through quorum sensing and an isogenic population of cells splitting into social and asocial subpopulations. A mathematical model explained these behaviors. The versatility of the secrete-and-sense circuit motif may explain its recurrence across species. PMID:24503857

Calculation of the fast ion tail distribution for a spherically symmetric hot spot

NASA Astrophysics Data System (ADS)

McDevitt, C. J.; Tang, X.-Z.; Guo, Z.; Berk, H. L.

2014-10-01

The fast ion tail for a spherically symmetric hot spot is computed via the solution of a simplified Fokker-Planck collision operator. Emphasis is placed on describing the energy scaling of the fast ion distribution function in the hot spot as well as the surrounding cold plasma throughout a broad range of collisionalities and temperatures. It is found that while the fast ion tail inside the hot spot is significantly depleted, leading to a reduction of the fusion yield in this region, a surplus of fast ions is observed in the neighboring cold plasma region. The presence of this surplus of fast ions in the neighboring cold region is shown to result in a partial recovery of the fusion yield lost in the hot spot.

In-Plane Structure of Underpotentially Deposited Copper on Gold (111) Determined by Surface EXAFS (Extended X-Ray Absorption Fine Structure).

DTIC Science & Technology

1988-01-28

EXAFS is the inverse transform of the two peaks in the RSF using a filtering a12 function to isolate the range between I and 4A. Both the frequency...backscattering of different neighbors. This inverse transform contains only one frequency and its envelope of intensity is the backscattering amplitude function...and the inverse transform of the RSF using a fourier filter between 1 and 4A (Solid line). Insert: Radial Structure Function (RSF) analyzed between

On the Asymptotic Behavior of the Kernel Function in the Generalized Langevin Equation: A One-Dimensional Lattice Model

NASA Astrophysics Data System (ADS)

Chu, Weiqi; Li, Xiantao

2018-01-01

We present some estimates for the memory kernel function in the generalized Langevin equation, derived using the Mori-Zwanzig formalism from a one-dimensional lattice model, in which the particles interactions are through nearest and second nearest neighbors. The kernel function can be explicitly expressed in a matrix form. The analysis focuses on the decay properties, both spatially and temporally, revealing a power-law behavior in both cases. The dependence on the level of coarse-graining is also studied.

Localized electron transfer rates and microelectrode-based enrichment of microbial communities within a phototrophic microbial mat.

PubMed

Babauta, Jerome T; Atci, Erhan; Ha, Phuc T; Lindemann, Stephen R; Ewing, Timothy; Call, Douglas R; Fredrickson, James K; Beyenal, Haluk

2014-01-01

Phototrophic microbial mats frequently exhibit sharp, light-dependent redox gradients that regulate microbial respiration on specific electron acceptors as a function of depth. In this work, a benthic phototrophic microbial mat from Hot Lake, a hypersaline, epsomitic lake located near Oroville in north-central Washington, was used to develop a microscale electrochemical method to study local electron transfer processes within the mat. To characterize the physicochemical variables influencing electron transfer, we initially quantified redox potential, pH, and dissolved oxygen gradients by depth in the mat under photic and aphotic conditions. We further demonstrated that power output of a mat fuel cell was light-dependent. To study local electron transfer processes, we deployed a microscale electrode (microelectrode) with tip size ~20 μm. To enrich a subset of microorganisms capable of interacting with the microelectrode, we anodically polarized the microelectrode at depth in the mat. Subsequently, to characterize the microelectrode-associated community and compare it to the neighboring mat community, we performed amplicon sequencing of the V1-V3 region of the 16S gene. Differences in Bray-Curtis beta diversity, illustrated by large changes in relative abundance at the phylum level, suggested successful enrichment of specific mat community members on the microelectrode surface. The microelectrode-associated community exhibited substantially reduced alpha diversity and elevated relative abundances of Prosthecochloris, Loktanella, Catellibacterium, other unclassified members of Rhodobacteraceae, Thiomicrospira, and Limnobacter, compared with the community at an equivalent depth in the mat. Our results suggest that local electron transfer to an anodically polarized microelectrode selected for a specific microbial population, with substantially more abundance and diversity of sulfur-oxidizing phylotypes compared with the neighboring mat community.

Localized electron transfer rates and microelectrode-based enrichment of microbial communities within a phototrophic microbial mat

PubMed Central

Babauta, Jerome T.; Atci, Erhan; Ha, Phuc T.; Lindemann, Stephen R.; Ewing, Timothy; Call, Douglas R.; Fredrickson, James K.; Beyenal, Haluk

2014-01-01

Phototrophic microbial mats frequently exhibit sharp, light-dependent redox gradients that regulate microbial respiration on specific electron acceptors as a function of depth. In this work, a benthic phototrophic microbial mat from Hot Lake, a hypersaline, epsomitic lake located near Oroville in north-central Washington, was used to develop a microscale electrochemical method to study local electron transfer processes within the mat. To characterize the physicochemical variables influencing electron transfer, we initially quantified redox potential, pH, and dissolved oxygen gradients by depth in the mat under photic and aphotic conditions. We further demonstrated that power output of a mat fuel cell was light-dependent. To study local electron transfer processes, we deployed a microscale electrode (microelectrode) with tip size ~20 μm. To enrich a subset of microorganisms capable of interacting with the microelectrode, we anodically polarized the microelectrode at depth in the mat. Subsequently, to characterize the microelectrode-associated community and compare it to the neighboring mat community, we performed amplicon sequencing of the V1–V3 region of the 16S gene. Differences in Bray-Curtis beta diversity, illustrated by large changes in relative abundance at the phylum level, suggested successful enrichment of specific mat community members on the microelectrode surface. The microelectrode-associated community exhibited substantially reduced alpha diversity and elevated relative abundances of Prosthecochloris, Loktanella, Catellibacterium, other unclassified members of Rhodobacteraceae, Thiomicrospira, and Limnobacter, compared with the community at an equivalent depth in the mat. Our results suggest that local electron transfer to an anodically polarized microelectrode selected for a specific microbial population, with substantially more abundance and diversity of sulfur-oxidizing phylotypes compared with the neighboring mat community. PMID:24478768

Localized electron transfer rates and microelectrode-based enrichment of microbial communities within a phototrophic microbial mat

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

Babauta, Jerome T.; Atci, Erhan; Ha, Phuc T.

2014-01-01

Phototrophic microbial mats frequently exhibit sharp, light-dependent redox gradients that regulate microbial respiration on specific electron acceptors as a function of depth. In this work, a benthic phototrophic microbial mat from Hot Lake, a hypersaline, epsomitic lake located near Oroville in north-central Washington, was used to develop a microscale electrochemical method to study local electron transfer processes within the mat. To characterize the physicochemical variables influencing electron transfer, we initially quantified redox potential, pH, and dissolved oxygen gradients by depth in the mat under photic and aphotic conditions. We further demonstrated that power output of a mat fuel cell wasmore » light-dependent. To study local electron transfer processes, we deployed a microscale electrode (microelectrode) with tip size ~20 μm. To enrich a subset of microorganisms capable of interacting with the microelectrode, we anodically polarized the microelectrode at depth in the mat. Subsequently, to characterize the microelectrode- associated community and compare it to the neighboring mat community, we performed amplicon sequencing of the V1-V3 region of the 16S gene. Differences in Bray-Curtis beta diversity, illustrated by large changes in relative abundance at the phylum level, suggested successful enrichment of specific mat community members on the microelectrode surface. The microelectrode-associated community exhibited substantially reduced alpha diversity and elevated relative abundances of Prosthecochloris, Loktanella, Catellibacterium, other unclassified members of Rhodobacteraceae, Thiomicrospira, and Limnobacter, compared with the community at an equivalent depth in the mat. Our results suggest that local electron transfer to an anodically polarized microelectrode selected for a specific microbial population, with substantially more abundance and diversity of sulfur-oxidizing phylotypes compared with the neighboring mat community.« less

[Classification of Children with Attention-Deficit/Hyperactivity Disorder and Typically Developing Children Based on Electroencephalogram Principal Component Analysis and k-Nearest Neighbor].

PubMed

Yang, Jiaojiao; Guo, Qian; Li, Wenjie; Wang, Suhong; Zou, Ling

2016-04-01

This paper aims to assist the individual clinical diagnosis of children with attention-deficit/hyperactivity disorder using electroencephalogram signal detection method.Firstly,in our experiments,we obtained and studied the electroencephalogram signals from fourteen attention-deficit/hyperactivity disorder children and sixteen typically developing children during the classic interference control task of Simon-spatial Stroop,and we completed electroencephalogram data preprocessing including filtering,segmentation,removal of artifacts and so on.Secondly,we selected the subset electroencephalogram electrodes using principal component analysis(PCA)method,and we collected the common channels of the optimal electrodes which occurrence rates were more than 90%in each kind of stimulation.We then extracted the latency(200~450ms)mean amplitude features of the common electrodes.Finally,we used the k-nearest neighbor(KNN)classifier based on Euclidean distance and the support vector machine(SVM)classifier based on radial basis kernel function to classify.From the experiment,at the same kind of interference control task,the attention-deficit/hyperactivity disorder children showed lower correct response rates and longer reaction time.The N2 emerged in prefrontal cortex while P2 presented in the inferior parietal area when all kinds of stimuli demonstrated.Meanwhile,the children with attention-deficit/hyperactivity disorder exhibited markedly reduced N2 and P2amplitude compared to typically developing children.KNN resulted in better classification accuracy than SVM classifier,and the best classification rate was 89.29%in StI task.The results showed that the electroencephalogram signals were different in the brain regions of prefrontal cortex and inferior parietal cortex between attention-deficit/hyperactivity disorder and typically developing children during the interference control task,which provided a scientific basis for the clinical diagnosis of attention-deficit/hyperactivity disorder individuals.

Inhibition of 5-HT neuron activity and induction of depressive-like behavior by high-frequency stimulation of the subthalamic nucleus.

PubMed

Temel, Yasin; Boothman, Laura J; Blokland, Arjan; Magill, Peter J; Steinbusch, Harry W M; Visser-Vandewalle, Veerle; Sharp, Trevor

2007-10-23

Bilateral, high-frequency stimulation (HFS) of the subthalamic nucleus (STN) is the surgical therapy of choice for movement disability in advanced Parkinson's disease (PD), but this procedure evokes debilitating psychiatric effects, including depressed mood, of unknown neural origin. Here, we report the unexpected finding that HFS of the STN inhibits midbrain 5-hydroxytryptamine (5-HT) neurons to evoke depression-related behavioral changes. We found that bilateral HFS of the STN consistently inhibited (40-50%) the firing rate of 5-HT neurons in the dorsal raphe nucleus of the rat, but not neighboring non-5-HT neurons. This effect was apparent at clinically relevant stimulation parameters (> or =100 Hz, > or =30 microA), was not elicited by HFS of either neighboring or remote structures to the STN, and was still present in rat models of PD. We also found that bilateral HFS of the STN evoked clear-cut, depressive-like behavior in a widely used experimental paradigm of depression (forced swim test), and this effect was also observed in a PD model. Importantly, the depressive-like behavior elicited by HFS of the STN was reversed by a selective 5-HT-enhancing antidepressant, thereby linking the behavioral change to decreased 5-HT neuronal activity. Overall, these findings link reduced 5-HT function to the psychiatric effects of HFS of the STN observed in PD patients and provide a rational basis for their clinical management. More generally, the powerful interaction between the STN and 5-HT system uncovered here offers insights into the high level of comorbidity of basal ganglia disease and mood disorder.

Tobacco smoking in urban neighborhoods: exploring social capital as a protective factor in Santiago, Chile.

PubMed

Sapag, Jaime C; Poblete, Fernando C; Eicher, Caitlin; Aracena, Marcela; Caneo, Constanza; Vera, Gloria; Martínez, Mayra; Hoyos, Rodrigo; Villarroel, Luis; Bradford, Elizabeth

2010-09-01

Research examining the relationship between social capital and health in Latin America has been limited. The aim of this study is to evaluate the association between social capital and tobacco use in four low-income neighborhoods in Santiago, Chile. A multistage probability sample was used to select households in 4 of the 10 poorest neighborhoods in the district of Puente Alto, in Santiago, Chile. A cross-sectional survey of 781 participants (81.2% response rate for households) included sociodemographic variables, questions pertaining to neighborhood social capital, and questions pertaining to tobacco. Main analyses were carried out at the individual level by performing a multiple logistic regression of individual tobacco use on individual perceptions of community social capital. The prevalence of smoking was 43.9% of the surveyed population. A five-factor structure for social capital was identified, including "perceived trust in neighbors," "perceived trust in organizations," "reciprocity within the neighborhood," "neighborhood integration," and "social participation." An inverse relationship between trust in neighbors and tobacco smoking was statistically significantly with an adjusted odds ratio of 0.95 (95% CI: 0.91-0.99). Trust in neighbors was also significantly inversely associated with the number of cigarettes smoked. Tobacco control remains a significant challenge in global health, requiring innovative strategies that address changing social contexts as well as the changing epidemiological profile of developing regions.

Evolutionary game theory and criticality

NASA Astrophysics Data System (ADS)

Mahmoodi, Korosh; Grigolini, Paolo

2017-01-01

We study a regular two-dimensional network of individuals playing the Prisonner’s Dilemma game with their neighbors, assigning to each individual the adoption of two different criteria to make a choice between cooperation and defection. For a fraction q  <  1 of her time the individual makes her choice by imitating those done by the nearest neighbors, with no payoff consideration. For a fraction ε =1-q the choice between cooperation and defection of an individual depends on the payoff difference between the most successful neighbor and her payoff. When q  =  1 for a special value of the imitation strength K, denoted as K c, the model of social pressure generates criticality. When q  =  0 a large incentive to cheat yields the extinction of cooperation and a modest one leads to the survival of cooperation. We show that for K={{K}\\text{c}} the adoption of a very small value of ɛ exerts a bias in favor of either cooperation or defection, as a form of criticality-induced intelligence, which leads the system to select either the cooperation or the defection branch, when K>{{K}\\text{c}} . Intermediate values of ɛ annihilated criticality-induced cognition and, as consequence, may favor defection choice even in the case when a wise payoff consideration is expected to yield the emergence of cooperation.

Second-Nearest-Neighbor Effects upon N NMR Shieldings in Models for Solid Si 3N 4and C 3N 4

NASA Astrophysics Data System (ADS)

Tossell, J. A.

1997-07-01

NMR shifts are generally determined mainly by the nearest-neighbor environment of an atom, with fairly small changes in the shift arising from differences in the second-nearest-neighbor environment. Previous calculations on the (SiH3)3N molecule used as a model for the local environment of N in crystalline α- and β-Si3N4gave N NMR shieldings much larger than those measured in the solids and gave the wrong order for the shifts of the inequivalent N sites (e.g., N1 and N2 in β-Si3N4). We have now calculated the N NMR shieldings in larger molecular models for the N2 site of β-Si3N4and have found that the N2 shielding is greatly reduced when additional N1 atoms (second-nearest-neighbors to the central N2) are included. The calculated N2 shieldings (using the GIAO method with the 6-31G* basis set and 6-31G* SCF optimized geometries) are 288.1, 244.7, and 206.0 ppm for the molecules (SiH3)3N, Si6N5H15, and Si9N9H21(central N2), respectively, while the experimental shielding of N2 in β-Si3N4is about 155 ppm. Second-nearest-neighbor effects of only slightly smaller magnitude are calculated for the analog C molecules. At the same time, the effects of molecule size upon Si NMR shieldings and N electric field gradients are small. The local geometries at the N2-like Ns in C6N5H15and C9N9H21are calculated to be planar, consistent with the planar local geometry recently calculated for N in crystalline C3N4using density functional theory.

Integrin Engagement by the Helical RGD Motif of the Helicobacter pylori CagL Protein Is Regulated by pH-induced Displacement of a Neighboring Helix*

PubMed Central

Bonsor, Daniel A.; Pham, Kieu T.; Beadenkopf, Robert; Diederichs, Kay; Haas, Rainer; Beckett, Dorothy; Fischer, Wolfgang; Sundberg, Eric J.

2015-01-01

Arginine-aspartate-glycine (RGD) motifs are recognized by integrins to bridge cells to one another and the extracellular matrix. RGD motifs typically reside in exposed loop conformations. X-ray crystal structures of the Helicobacter pylori protein CagL revealed that RGD motifs can also exist in helical regions of proteins. Interactions between CagL and host gastric epithelial cell via integrins are required for the translocation of the bacterial oncoprotein CagA. Here, we have investigated the molecular basis of the CagL-host cell interactions using structural, biophysical, and functional analyses. We solved an x-ray crystal structure of CagL that revealed conformational changes induced by low pH not present in previous structures. Using analytical ultracentrifugation, we found that pH-induced conformational changes in CagL occur in solution and not just in the crystalline environment. By designing numerous CagL mutants based on all available crystal structures, we probed the functional roles of CagL conformational changes on cell surface integrin engagement. Together, our data indicate that the helical RGD motif in CagL is buried by a neighboring helix at low pH to inhibit CagL binding to integrin, whereas at neutral pH the neighboring helix is displaced to allow integrin access to the CagL RGD motif. This novel molecular mechanism of regulating integrin-RGD motif interactions by changes in the chemical environment provides new insight to H. pylori-mediated oncogenesis. PMID:25837254

Near-Neighbor Algorithms for Processing Bearing Data

DTIC Science & Technology

1989-05-10

neighbor algorithms need not be universally more cost -effective than brute force methods. While the data access time of near-neighbor techniques scales with...the number of objects N better than brute force, the cost of setting up the data structure could scale worse than (Continues) 20...for the near neighbors NN2 1 (i). Depending on the particular NN algorithm, the cost of accessing near neighbors for each ai E S1 scales as either N

Coevolution of strategy-selection time scale and cooperation in spatial prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Rong, Zhihai; Wu, Zhi-Xi; Chen, Guanrong

2013-06-01

In this paper, we investigate a networked prisoner's dilemma game where individuals' strategy-selection time scale evolves based on their historical learning information. We show that the more times the current strategy of an individual is learnt by his neighbors, the longer time he will stick on the successful behavior by adaptively adjusting the lifetime of the adopted strategy. Through characterizing the extent of success of the individuals with normalized payoffs, we show that properly using the learned information can form a positive feedback mechanism between cooperative behavior and its lifetime, which can boost cooperation on square lattices and scale-free networks.

Watch Out for Your Neighbor: Climbing onto Shrubs Is Related to Risk of Cannibalism in the Scorpion Buthus cf. occitanus

PubMed Central

Urbano-Tenorio, Fernando

2016-01-01

The distribution and behavior of foraging animals usually imply a balance between resource availability and predation risk. In some predators such as scorpions, cannibalism constitutes an important mortality factor determining their ecology and behavior. Climbing on vegetation by scorpions has been related both to prey availability and to predation (cannibalism) risk. We tested different hypotheses proposed to explain climbing on vegetation by scorpions. We analyzed shrub climbing in Buthus cf. occitanus with regard to the following: a) better suitability of prey size for scorpions foraging on shrubs than on the ground, b) selection of shrub species with higher prey load, c) seasonal variations in prey availability on shrubs, and d) whether or not cannibalism risk on the ground increases the frequency of shrub climbing. Prey availability on shrubs was compared by estimating prey abundance in sticky traps placed in shrubs. A prey sample from shrubs was measured to compare prey size. Scorpions were sampled in six plots (50 m x 10 m) to estimate the proportion of individuals climbing on shrubs. Size difference and distance between individuals and their closest scorpion neighbor were measured to assess cannibalism risk. The results showed that mean prey size was two-fold larger on the ground. Selection of particular shrub species was not related to prey availability. Seasonal variations in the number of scorpions on shrubs were related to the number of active scorpions, but not with fluctuations in prey availability. Size differences between a scorpion and its nearest neighbor were positively related with a higher probability for a scorpion to climb onto a shrub when at a disadvantage, but distance was not significantly related. These results do not support hypotheses explaining shrub climbing based on resource availability. By contrast, our results provide evidence that shrub climbing is related to cannibalism risk. PMID:27655347

Watch Out for Your Neighbor: Climbing onto Shrubs Is Related to Risk of Cannibalism in the Scorpion Buthus cf. occitanus.

PubMed

Sánchez-Piñero, Francisco; Urbano-Tenorio, Fernando

The distribution and behavior of foraging animals usually imply a balance between resource availability and predation risk. In some predators such as scorpions, cannibalism constitutes an important mortality factor determining their ecology and behavior. Climbing on vegetation by scorpions has been related both to prey availability and to predation (cannibalism) risk. We tested different hypotheses proposed to explain climbing on vegetation by scorpions. We analyzed shrub climbing in Buthus cf. occitanus with regard to the following: a) better suitability of prey size for scorpions foraging on shrubs than on the ground, b) selection of shrub species with higher prey load, c) seasonal variations in prey availability on shrubs, and d) whether or not cannibalism risk on the ground increases the frequency of shrub climbing. Prey availability on shrubs was compared by estimating prey abundance in sticky traps placed in shrubs. A prey sample from shrubs was measured to compare prey size. Scorpions were sampled in six plots (50 m x 10 m) to estimate the proportion of individuals climbing on shrubs. Size difference and distance between individuals and their closest scorpion neighbor were measured to assess cannibalism risk. The results showed that mean prey size was two-fold larger on the ground. Selection of particular shrub species was not related to prey availability. Seasonal variations in the number of scorpions on shrubs were related to the number of active scorpions, but not with fluctuations in prey availability. Size differences between a scorpion and its nearest neighbor were positively related with a higher probability for a scorpion to climb onto a shrub when at a disadvantage, but distance was not significantly related. These results do not support hypotheses explaining shrub climbing based on resource availability. By contrast, our results provide evidence that shrub climbing is related to cannibalism risk.

A Novel Hybrid Classification Model of Genetic Algorithms, Modified k-Nearest Neighbor and Developed Backpropagation Neural Network

PubMed Central

Salari, Nader; Shohaimi, Shamarina; Najafi, Farid; Nallappan, Meenakshii; Karishnarajah, Isthrinayagy

2014-01-01

Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models. PMID:25419659

Assessing hypotheses about nesting site occupancy dynamics

USGS Publications Warehouse

Bled, Florent; Royle, J. Andrew; Cam, Emmanuelle

2011-01-01

Hypotheses about habitat selection developed in the evolutionary ecology framework assume that individuals, under some conditions, select breeding habitat based on expected fitness in different habitat. The relationship between habitat quality and fitness may be reflected by breeding success of individuals, which may in turn be used to assess habitat quality. Habitat quality may also be assessed via local density: if high-quality sites are preferentially used, high density may reflect high-quality habitat. Here we assessed whether site occupancy dynamics vary with site surrogates for habitat quality. We modeled nest site use probability in a seabird subcolony (the Black-legged Kittiwake, Rissa tridactyla) over a 20-year period. We estimated site persistence (an occupied site remains occupied from time t to t + 1) and colonization through two subprocesses: first colonization (site creation at the timescale of the study) and recolonization (a site is colonized again after being deserted). Our model explicitly incorporated site-specific and neighboring breeding success and conspecific density in the neighborhood. Our results provided evidence that reproductively "successful'' sites have a higher persistence probability than "unsuccessful'' ones. Analyses of site fidelity in marked birds and of survival probability showed that high site persistence predominantly reflects site fidelity, not immediate colonization by new owners after emigration or death of previous owners. There is a negative quadratic relationship between local density and persistence probability. First colonization probability decreases with density, whereas recolonization probability is constant. This highlights the importance of distinguishing initial colonization and recolonization to understand site occupancy. All dynamics varied positively with neighboring breeding success. We found evidence of a positive interaction between site-specific and neighboring breeding success. We addressed local population dynamics using a site occupancy approach integrating hypotheses developed in behavioral ecology to account for individual decisions. This allows development of models of population and metapopulation dynamics that explicitly incorporate ecological and evolutionary processes.

Diagnostic tools for nearest neighbors techniques when used with satellite imagery

Treesearch

Ronald E. McRoberts

2009-01-01

Nearest neighbors techniques are non-parametric approaches to multivariate prediction that are useful for predicting both continuous and categorical forest attribute variables. Although some assumptions underlying nearest neighbor techniques are common to other prediction techniques such as regression, other assumptions are unique to nearest neighbor techniques....

An epidemic model of rumor diffusion in online social networks

NASA Astrophysics Data System (ADS)

Cheng, Jun-Jun; Liu, Yun; Shen, Bo; Yuan, Wei-Guo

2013-01-01

So far, in some standard rumor spreading models, the transition probability from ignorants to spreaders is always treated as a constant. However, from a practical perspective, the case that individual whether or not be infected by the neighbor spreader greatly depends on the trustiness of ties between them. In order to solve this problem, we introduce a stochastic epidemic model of the rumor diffusion, in which the infectious probability is defined as a function of the strength of ties. Moreover, we investigate numerically the behavior of the model on a real scale-free social site with the exponent γ = 2.2. We verify that the strength of ties plays a critical role in the rumor diffusion process. Specially, selecting weak ties preferentially cannot make rumor spread faster and wider, but the efficiency of diffusion will be greatly affected after removing them. Another significant finding is that the maximum number of spreaders max( S) is very sensitive to the immune probability μ and the decay probability v. We show that a smaller μ or v leads to a larger spreading of the rumor, and their relationships can be described as the function ln(max( S)) = Av + B, in which the intercept B and the slope A can be fitted perfectly as power-law functions of μ. Our findings may offer some useful insights, helping guide the application in practice and reduce the damage brought by the rumor.

Numerical Modeling of Ion Dynamics in a Carbon Nanotube Field-Ionized Thruster

DTIC Science & Technology

2011-12-01

30  Figure 13.  Equipotential plot, Ez as a function of z and r, Jreq=300 kA/m2, space charge off... Equipotential plots, Ez as a function of z and r, Jreq=300 kA/m2, space charge on. Plots are taken at time intervals of 0.05 ns...on the accelerating grids; under-perveance results in crossover, overlap of neighboring beamlets, and impingement on downstream surfaces . Optimum

Penalized weighted least-squares approach for low-dose x-ray computed tomography

NASA Astrophysics Data System (ADS)

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-03-01

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Karhunen-Loeve (KL) transform can be used to de-correlate the signal among the neighboring views. In each KL component, a penalized weighted least-squares (PWLS) objective function can be constructed and optimal sinogram can be estimated by minimizing the objective function, followed by filtered backprojection (FBP) for CT image reconstruction. In this work, we compared the KL-PWLS method with an iterative image reconstruction algorithm, which uses the Gauss-Seidel iterative calculation to minimize the PWLS objective function in image domain. We also compared the KL-PWLS with an iterative sinogram smoothing algorithm, which uses the iterated conditional mode calculation to minimize the PWLS objective function in sinogram space, followed by FBP for image reconstruction. Phantom experiments show a comparable performance of these three PWLS methods in suppressing the noise-induced artifacts and preserving resolution in reconstructed images. Computer simulation concurs with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS noise reduction may have the advantage in computation for low-dose CT imaging, especially for dynamic high-resolution studies.

A Model for Determining Information Diffusion in a Family Planning Program

ERIC Educational Resources Information Center

Jackson, Audrey R.

1972-01-01

Knowledge of the existence of birth control clinics is seen as a function of proximity to clinics, friendliness of neighborhood, and propensity to discuss birth control with neighbors. A conceptual model is developed to illustrate variables contributing to the diffusion of birth control information in a public health family planning program.…

Sediment transport-storage relations for degrading, gravel bed channels

Treesearch

Thomas E. Lisle; Michael Church

2002-01-01

In a drainage network,sediment is transferred through a series of channel/valley segments (natural sediment storage reservoirs) that are distinguished from their neighbors by their particular capacity to store and transport sediment. We propose that the sediment transport capacity of each reservoir is a unique positive function of storage volume, which influences...

Predicting protein submitochondrial locations using a K-Nearest neighbor method based on the Bit-Score weighted euclidean distance

USDA-ARS?s Scientific Manuscript database

Mitochondria are essential subcellular organelles found in eukaryotic cells. Knowing information on a protein’s subcellular or sub subcellular location provides in-depth insights about the microenvironment where it interacts with other molecules and is crucial for inferring the protein’s function. T...

Cultural and Biological Adaptations to Deprivation: The Northern Ojibwa Case.

ERIC Educational Resources Information Center

Bishop, Charles A.

After the fur trade reached the Ojibwa during the early 17th Century, tribe structure and function rapidly changed. The intensity of social life increased as the Ojibwa and neighboring tribes gathered to exchange fur pelts for European items. Trade became so important that intertribal hostilities arose and an almost unrestrictive slaughter of…

Metastability of Reversible Random Walks in Potential Fields

NASA Astrophysics Data System (ADS)

Landim, C.; Misturini, R.; Tsunoda, K.

2015-09-01

Let be an open and bounded subset of , and let be a twice continuously differentiable function. Denote by the discretization of , , and denote by the continuous-time, nearest-neighbor, random walk on which jumps from to at rate . We examine in this article the metastable behavior of among the wells of the potential F.

DNA Origami Patterned Colloids for Programmed Design and Chirality

NASA Astrophysics Data System (ADS)

Ben Zion, Matan Yah; He, Xiaojin; Maass, Corinna; Sha, Ruojie; Seeman, Ned; Chaikin, Paul

Micron size colloidal particles are scientifically important as model systems for equilibrium and active systems in physics, chemistry and biology and for technologies ranging from catalysis to photonics. The past decade has seen development of new particles with directional patches, lock and key reactions and specific recognition that guide assembly of structures such as complex crystalline arrays. What remains lacking is the ability to self-assemble structures of arbitrary shape with specific chirality, placement and orientation of neighbors. Here we demonstrate the adaptation of DNA origami nanotechnology to the micron colloidal scale with designed control of neighbor type, placement and dihedral angle. We use DNA origami belts with programmed flexibility, and functionality to pattern colloidal surfaces and bind particles to specific sites at specific angles and make uniquely right handed or left handed structures. The hybrid DNA origami colloid technology should allow the synthesis of designed functional structural and active materials. This work was supported as part of the Center for Bio-Inspired Energy Science, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0000989.

Electronic structure and magnetic anisotropy of Sm2Fe17Nx

NASA Astrophysics Data System (ADS)

Akai, Hisazumi; Ogura, Masako

2014-03-01

Electronic structure and magnetic properties of Sm2Fe17Nx are studies on the basis of the first-principles electronic structure calculation in the framework of the density functional theory within the local density and coherent potential approximations. The magnetic anisotropy of the system as a function of nitrogen concentration x is discussed by taking account not only of the crystal field effects but also of the effects of the f-electron transfer from Sm to the neighboring sites. Also discussed is the magnetic transition temperature that is estimated by mapping the system into a Heisenberg model. The results show the crystalline magnetic anisotropy changes its direction from in-plane to uniaxial ones as x increases. It takes the maximum value near x ~ 2 . 8 and then decreases slightly towards x = 3 . The mechanism for these behaviors is discussed in the light of the results of detailed calculations on the bonding properties between Sm and its neighboring N. This work was partly supported by Elements Strategy Initiative Center for Magnetic Materials Project, the Ministry of Education, Culture, Sports, Science and Technology, Japan.

Self-calibrated correlation imaging with k-space variant correlation functions.

PubMed

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

CortiQ-based Real-Time Functional Mapping for Epilepsy Surgery.

PubMed

Kapeller, Christoph; Korostenskaja, Milena; Prueckl, Robert; Chen, Po-Ching; Lee, Ki Heyeong; Westerveld, Michael; Salinas, Christine M; Cook, Jane C; Baumgartner, James E; Guger, Christoph

2015-06-01

To evaluate the use of the cortiQ-based mapping system (g.tec medication engineering GmbH, Austria) for real-time functional mapping (RTFM) and to compare it to results from electrical cortical stimulation mapping (ESM) and functional magnetic resonance imaging (fMRI). Electrocorticographic activity was recorded in 3 male patients with intractable epilepsy by using cortiQ mapping system and analyzed in real time. Activation related to motor, sensory, and receptive language tasks was determined by evaluating the power of the high gamma frequency band (60-170 Hz). The sensitivity and specificity of RTFM were tested against ESM and fMRI results. "Next-neighbor" approach demonstrated [sensitivity/specificity %] (1) RTFM against ESM: 100.00/79.70 for hand motor; 100.00/73.87 for hand sensory; -/87 for language (it was not identified by the ESM); (2) RTFM against fMRI: 100.00/84.4 for hand motor; 66.70/85.35 for hand sensory; and 87.85/77.70 for language. The results of the quantitative "next-neighbor" RTFM evaluation were concordant to those from ESM and fMRI. The RTFM correlates well with localization of hand motor function provided by ESM and fMRI, which may offer added localization in the operating room and guidance for extraoperative ESM mapping. Real-time functional mapping correlates with fMRI language activation when ESM findings are negative. It has fewer limitations than ESM and greater flexibility in activation paradigms and measuring responses.

Annual Threat Assessment of the Intelligence Community for the Senate Select Committee on Intelligence

DTIC Science & Technology

2009-02-12

industries—so-called beggar-thy-neighbor policies such as competitive currency devaluations , import tariffs, and/or export subsidies—risk unleashing a...in domestic and foreign spending or to devalue the Venezuelan currency and draw down government hard currency reserves to avoid a major economic...early as late 2009. The IMF , which recently released its revised forecast for 2009 projecting an anemic 0.5 percent increase in the global economy

Predicting missing links in complex networks based on common neighbors and distance

PubMed Central

Yang, Jinxuan; Zhang, Xiao-Dong

2016-01-01

The algorithms based on common neighbors metric to predict missing links in complex networks are very popular, but most of these algorithms do not account for missing links between nodes with no common neighbors. It is not accurate enough to reconstruct networks by using these methods in some cases especially when between nodes have less common neighbors. We proposed in this paper a new algorithm based on common neighbors and distance to improve accuracy of link prediction. Our proposed algorithm makes remarkable effect in predicting the missing links between nodes with no common neighbors and performs better than most existing currently used methods for a variety of real-world networks without increasing complexity. PMID:27905526

Control of Electronic Structures and Phonon Dynamics in Quantum Dot Superlattices by Manipulation of Interior Nanospace.

PubMed

Chang, I-Ya; Kim, DaeGwi; Hyeon-Deuk, Kim

2016-07-20

Quantum dot (QD) superlattices, periodically ordered array structures of QDs, are expected to provide novel photo-optical functions due to their resonant couplings between adjacent QDs. Here, we computationally demonstrated that electronic structures and phonon dynamics of a QD superlattice can be effectively and selectively controlled by manipulating its interior nanospace, where quantum resonance between neighboring QDs appears, rather than by changing component QD size, shape, compositions, etc. A simple H-passivated Si QD was examined to constitute one-, two-, and three-dimensional QD superlattices, and thermally fluctuating band energies and phonon modes were simulated by finite-temperature ab initio molecular dynamics (MD) simulations. The QD superlattice exhibited a decrease in the band gap energy enhanced by thermal modulations and also exhibited selective extraction of charge carriers out of the component QD, indicating its advantage as a promising platform for implementation in solar cells. Our dynamical phonon analyses based on the ab initio MD simulations revealed that THz-frequency phonon modes were created by an inter-QD crystalline lattice formed in the QD superlattice, which can contribute to low energy thermoelectric conversion and will be useful for direct observation of the dimension-dependent superlattice. Further, we found that crystalline and ligand-originated phonon modes inside each component QD can be independently controlled by asymmetry of the superlattice and by restriction of the interior nanospace, respectively. Taking into account the thermal effects at the finite temperature, we proposed guiding principles for designing efficient and space-saving QD superlattices to develop functional photovoltaic and thermoelectric devices.

Evaluation of different classification methods for the diagnosis of schizophrenia based on functional near-infrared spectroscopy.

PubMed

Li, Zhaohua; Wang, Yuduo; Quan, Wenxiang; Wu, Tongning; Lv, Bin

2015-02-15

Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population. In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods. We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier. This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals. Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Post-mortem ecosystem engineering by oysters creates habitat for a rare marsh plant.

PubMed

Guo, Hongyu; Pennings, Steven C

2012-11-01

Oysters are ecosystem engineers in marine ecosystems, but the functions of oyster shell deposits in intertidal salt marshes are not well understood. The annual plant Suaeda linearis is associated with oyster shell deposits in Georgia salt marshes. We hypothesized that oyster shell deposits promoted the distribution of Suaeda linearis by engineering soil conditions unfavorable to dominant salt marsh plants of the region (the shrub Borrichia frutescens, the rush Juncus roemerianus, and the grass Spartina alterniflora). We tested this hypothesis using common garden pot experiments and field transplant experiments. Suaeda linearis thrived in Borrichia frutescens stands in the absence of neighbors, but was suppressed by Borrichia frutescens in the with-neighbor treatment, suggesting that Suaeda linearis was excluded from Borrichia frutescens stands by interspecific competition. Suaeda linearis plants all died in Juncus roemerianus and Spartina alterniflora stands, regardless of neighbor treatments, indicating that Suaeda linearis is excluded from these habitats by physical stress (likely water-logging). In contrast, Borrichia frutescens, Juncus roemerianus, and Spartina alterniflora all performed poorly in Suaeda linearis stands regardless of neighbor treatments, probably due to physical stresses such as low soil water content and low organic matter content. Thus, oyster shell deposits play an important ecosystem engineering role in influencing salt marsh plant communities by providing a unique niche for Suaeda linearis, which otherwise would be rare or absent in salt marshes in the southeastern US. Since the success of Suaeda linearis is linked to the success of oysters, efforts to protect and restore oyster reefs may also benefit salt marsh plant communities.

Ising lattices with +/-J second-nearest-neighbor interactions

NASA Astrophysics Data System (ADS)

Ramírez-Pastor, A. J.; Nieto, F.; Vogel, E. E.

1997-06-01

Second-nearest-neighbor interactions are added to the usual nearest-neighbor Ising Hamiltonian for square lattices in different ways. The starting point is a square lattice where half the nearest-neighbor interactions are ferromagnetic and the other half of the bonds are antiferromagnetic. Then, second-nearest-neighbor interactions can also be assigned randomly or in a variety of causal manners determined by the nearest-neighbor interactions. In the present paper we consider three causal and three random ways of assigning second-nearest-neighbor exchange interactions. Several ground-state properties are then calculated for each of these lattices:energy per bond ɛg, site correlation parameter pg, maximal magnetization μg, and fraction of unfrustrated bonds hg. A set of 500 samples is considered for each size N (number of spins) and array (way of distributing the N spins). The properties of the original lattices with only nearest-neighbor interactions are already known, which allows realizing the effect of the additional interactions. We also include cubic lattices to discuss the distinction between coordination number and dimensionality. Comparison with results for triangular and honeycomb lattices is done at specific points.

Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

PubMed Central

2013-01-01

Background The learning active subnetworks problem involves finding subnetworks of a bio-molecular network that are active in a particular condition. Many approaches integrate observation data (e.g., gene expression) with the network topology to find candidate subnetworks. Increasingly, pathway databases contain additional annotation information that can be mined to improve prediction accuracy, e.g., interaction mechanism (e.g., transcription, microRNA, cleavage) annotations. We introduce a mechanism-based approach to active subnetwork recovery which exploits such annotations. We suggest that neighboring interactions in a network tend to be co-activated in a way that depends on the “correlation” of their mechanism annotations. e.g., neighboring phosphorylation and de-phosphorylation interactions may be more likely to be co-activated than neighboring phosphorylation and covalent bonding interactions. Results Our method iteratively learns the mechanism correlations and finds the most likely active subnetwork. We use a probabilistic graphical model with a Markov Random Field component which creates dependencies between the states (active or non-active) of neighboring interactions, that incorporates a mechanism-based component to the function. We apply a heuristic-based EM-based algorithm suitable for the problem. We validated our method’s performance using simulated data in networks downloaded from GeneGO against the same approach without the mechanism-based component, and two other existing methods. We validated our methods performance in correctly recovering (1) the true interaction states, and (2) global network properties of the original network against these other methods. We applied our method to networks generated from time-course gene expression studies in angiogenesis and lung organogenesis and validated the findings from a biological perspective against current literature. Conclusions The advantage of our mechanism-based approach is best seen in networks composed of connected regions with a large number of interactions annotated with a subset of mechanisms, e.g., a regulatory region of transcription interactions, or a cleavage cascade region. When applied to real datasets, our method recovered novel and biologically meaningful putative interactions, e.g., interactions from an integrin signaling pathway using the angiogenesis dataset, and a group of regulatory microRNA interactions in an organogenesis network. PMID:23432934

The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support

PubMed Central

Malof, Jordan M.; Mazurowski, Maciej A.; Tourassi, Georgia D.

2013-01-01

Case selection is a useful approach for increasing the efficiency and performance of case-based classifiers. Multiple techniques have been designed to perform case selection. This paper empirically investigates how class imbalance in the available set of training cases can impact the performance of the resulting classifier as well as properties of the selected set. In this study, the experiments are performed using a dataset for the problem of detecting breast masses in screening mammograms. The classification problem was binary and we used a k-nearest neighbor classifier. The classifier’s performance was evaluated using the Receiver Operating Characteristic (ROC) area under the curve (AUC) measure. The experimental results indicate that although class imbalance reduces the performance of the derived classifier and the effectiveness of selection at improving overall classifier performance, case selection can still be beneficial, regardless of the level of class imbalance. PMID:21820273

Comparing supervised learning methods for classifying sex, age, context and individual Mudi dogs from barking.

PubMed

Larrañaga, Ana; Bielza, Concha; Pongrácz, Péter; Faragó, Tamás; Bálint, Anna; Larrañaga, Pedro

2015-03-01

Barking is perhaps the most characteristic form of vocalization in dogs; however, very little is known about its role in the intraspecific communication of this species. Besides the obvious need for ethological research, both in the field and in the laboratory, the possible information content of barks can also be explored by computerized acoustic analyses. This study compares four different supervised learning methods (naive Bayes, classification trees, [Formula: see text]-nearest neighbors and logistic regression) combined with three strategies for selecting variables (all variables, filter and wrapper feature subset selections) to classify Mudi dogs by sex, age, context and individual from their barks. The classification accuracy of the models obtained was estimated by means of [Formula: see text]-fold cross-validation. Percentages of correct classifications were 85.13 % for determining sex, 80.25 % for predicting age (recodified as young, adult and old), 55.50 % for classifying contexts (seven situations) and 67.63 % for recognizing individuals (8 dogs), so the results are encouraging. The best-performing method was [Formula: see text]-nearest neighbors following a wrapper feature selection approach. The results for classifying contexts and recognizing individual dogs were better with this method than they were for other approaches reported in the specialized literature. This is the first time that the sex and age of domestic dogs have been predicted with the help of sound analysis. This study shows that dog barks carry ample information regarding the caller's indexical features. Our computerized analysis provides indirect proof that barks may serve as an important source of information for dogs as well.

Integrated Solvent Design for CO 2 Capture and Viscosity Tuning

DOE PAGES

Cantu, David C.; Malhotra, Deepika; Koech, Phillip K.; ...

2017-08-18

We present novel design strategies for reduced viscosity single-component, water-lean CO 2 capture organic solvent systems. Through molecular simulation, we identify the main molecular-level descriptor that influences bulk solvent viscosity. Upon loading, a zwitterionic structure forms with a small activation energy of ca 16 kJ/mol and a small stabilization of ca 6 kJ/mol. Viscosity increases exponentially with CO 2 loading due to hydrogen-bonding between neighboring Zwitterions. We find that molecular structures that promote internal hydrogen bonding (within the same molecule) and suppress interactions with neighboring molecules have low viscosities. In addition, tuning the acid/base properties leads to a shift ofmore » the equilibrium toward a non-charged (acid) form that further reduces the viscosity. Here, based on the above structural criteria, a reduced order model is also presented that allows for the quick screening of large compound libraries and down selection of promising candidates for synthesis and testing.« less

Application of different markers and data-analysis tools to the examination of biodiversity can lead to different results: a case study with Starmerella bacillaris (synonym Candida zemplinina) strains.

PubMed

Csoma, Hajnalka; Ács-Szabó, Lajos; Papp, László Attila; Sipiczki, Matthias

2018-08-01

Starmerella bacillaris (Candida zemplinina) is a genetically heterogeneous species. In this work, the diversity of 41 strains of various origins is examined and compared by the analysis of the length polymorphism of nuclear microsatellites and the RFLP of mitochondrial genomes. The band patterns are analysed with UPGMA, neighbor joining, neighbor net, minimum spanning tree and non-metric MDS algorithms. The results and their comparison to previous analyses demonstrate that different markers and different clustering methods can result in very different groupings of the same strains. The observed differences between the topologies of the dendrograms also indicate that the positions of the strains do not necessarily reflect their real genetic relationships and origins. The possibilities that the differences might be partially due to different sensitivity of the markers to environmental factors (selection pressure) and partially to the different grouping criteria of the algorithms are also discussed.

Killing wolves to prevent predation on livestock may protect one farm but harm neighbors.

PubMed

Santiago-Avila, Francisco J; Cornman, Ari M; Treves, Adrian

2018-01-01

Large carnivores, such as gray wolves, Canis lupus, are difficult to protect in mixed-use landscapes because some people perceive them as dangerous and because they sometimes threaten human property and safety. Governments may respond by killing carnivores in an effort to prevent repeated conflicts or threats, although the functional effectiveness of lethal methods has long been questioned. We evaluated two methods of government intervention following independent events of verified wolf predation on domestic animals (depredation) in the Upper Peninsula of Michigan, USA between 1998-2014, at three spatial scales. We evaluated two intervention methods using log-rank tests and conditional Cox recurrent event, gap time models based on retrospective analyses of the following quasi-experimental treatments: (1) selective killing of wolves by trapping near sites of verified depredation, and (2) advice to owners and haphazard use of non-lethal methods without wolf-killing. The government did not randomly assign treatments and used a pseudo-control (no removal of wolves was not a true control), but the federal permission to intervene lethally was granted and rescinded independent of events on the ground. Hazard ratios suggest lethal intervention was associated with an insignificant 27% lower risk of recurrence of events at trapping sites, but offset by an insignificant 22% increase in risk of recurrence at sites up to 5.42 km distant in the same year, compared to the non-lethal treatment. Our results do not support the hypothesis that Michigan's use of lethal intervention after wolf depredations was effective for reducing the future risk of recurrence in the vicinities of trapping sites. Examining only the sites of intervention is incomplete because neighbors near trapping sites may suffer the recurrence of depredations. We propose two new hypotheses for perceived effectiveness of lethal methods: (a) killing predators may be perceived as effective because of the benefits to a small minority of farmers, and (b) if neighbors experience side-effects of lethal intervention such as displaced depredations, they may perceive the problem growing and then demand more lethal intervention rather than detecting problems spreading from the first trapping site. Ethical wildlife management guided by the "best scientific and commercial data available" would suggest suspending the standard method of trapping wolves in favor of non-lethal methods (livestock guarding dogs or fladry) that have been proven effective in preventing livestock losses in Michigan and elsewhere.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space.

PubMed

Jin, Xian; Awale, Mahendra; Zasso, Michaël; Kostro, Daniel; Patiny, Luc; Reymond, Jean-Louis

2015-10-23

The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.cheminfo.org/pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB. ᅟ

Performance analysis of microcomputer based differential protection of UHV lines under selective phase switching

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

Bhatti, A.A.

1990-04-01

This paper examines the effects of primary and secondary fault quantities as well s of mutual couplings of neighboring circuits on the sensitivity of operation and threshold settings of a microcomputer based differential protection of UHV lines under selective phase switching. Microcomputer based selective phase switching allows the disconnection of minimum number of phases involved in a fault and requires the autoreclosing of these phases immediately after the extinction of secondary arc. During a primary fault a heavy current contribution to the healthy phases tends to cause an unwanted tripping. Faulty phases physically disconnected constitute an isolated fault which beingmore » coupled to the system affects the current and voltage levels of the healthy phases still retained in the system and may cause an unwanted tripping. The microcomputer based differential protection, appears to have poor performance when applied to uncompensated lines employing selective pole switching.« less

Na⁺ and K⁺ ion selectivity by size-controlled biomimetic graphene nanopores.

PubMed

Kang, Yu; Zhang, Zhisen; Shi, Hui; Zhang, Junqiao; Liang, Lijun; Wang, Qi; Ågren, Hans; Tu, Yaoquan

2014-09-21

Because biological ionic channels play a key role in cellular transport phenomena, they have attracted extensive research interest for the design of biomimetic nanopores with high permeability and selectivity in a variety of technical applications. Inspired by the structure of K(+) channel proteins, we designed a series of oxygen doped graphene nanopores of different sizes by molecular dynamics simulations to discriminate between K(+) and Na(+) channel transport. The results from free energy calculations indicate that the ion selectivity of such biomimetic graphene nanopores can be simply controlled by the size of the nanopore; compared to K(+), the smaller radius of Na(+) leads to a significantly higher free energy barrier in the nanopore of a certain size. Our results suggest that graphene nanopores with a distance of about 3.9 Å between two neighboring oxygen atoms could constitute a promising candidate to obtain excellent ion selectivity for Na(+) and K(+) ions.

Mechanism for subgap optical conductivity in honeycomb Kitaev materials

NASA Astrophysics Data System (ADS)

Bolens, Adrien; Katsura, Hosho; Ogata, Masao; Miyashita, Seiji

2018-04-01

Motivated by recent terahertz absorption measurements in α -RuCl3 , we develop a theory for the electromagnetic absorption of materials described by the Kitaev model on the honeycomb lattice. We derive a mechanism for the polarization operator at second order in the nearest-neighbor hopping Hamiltonian. Using the exact results of the Kitaev honeycomb model, we then calculate the polarization dynamical correlation function corresponding to electric dipole transitions in addition to the spin dynamical correlation function corresponding to magnetic dipole transitions.

Flocking of the Motsch-Tadmor Model with a Cut-Off Interaction Function

NASA Astrophysics Data System (ADS)

Jin, Chunyin

2018-04-01

In this paper, we study the flocking behavior of the Motsch-Tadmor model with a cut-off interaction function. Our analysis shows that connectedness is important for flocking of this kind of model. Fortunately, we get a sufficient condition imposed only on the model parameters and initial data to guarantee the connectedness of the neighbor graph associated with the system. Then we present a theoretical analysis for flocking, and show that the system achieves consensus at an exponential rate.

Effect of the collective motions of molecules inside a condensed phase on fluctuations in the density of small bodies

NASA Astrophysics Data System (ADS)

Tovbin, Yu. K.

2017-11-01

An approach to calculating the effects of fluctuations in density that considers the collective motions of molecules in small condensed phases (e.g., droplets, microcrystals, adsorption at microcrystal faces) is proposed. Statistical sums of the vibrational, rotational, and translational motions of molecules are of a collective character expressed in the dependences of these statistical sums on the local configurations of neighboring molecules. This changes their individual contributions to the free energy and modifies fluctuations in density in the inner homogeneous regions of small bodies. Interactions between nearest neighbors are considered in a quasi-chemical approximation that reflects the effects of short-range direct correlations. Expressions for isotherms relating the densities of mixture components to the chemical potentials in a thermostat are obtained, along with equations for pair distribution functions.

Realization of the axial next-nearest-neighbor Ising model in U 3 Al 2 Ge 3

DOE PAGES

Fobes, David M.; Lin, Shi-Zeng; Ghimire, Nirmal J.; ...

2017-11-09

Inmore » this paper, we report small-angle neutron scattering (SANS) measurements and theoretical modeling of U 3 Al 2 Ge 3 . Analysis of the SANS data reveals a phase transition to sinusoidally modulated magnetic order at T N = 63 K to be second order and a first-order phase transition to ferromagnetic order at T c = 48 K. Within the sinusoidally modulated magnetic phase (T c < T < T N), we uncover a dramatic change, by a factor of 3, in the ordering wave vector as a function of temperature. Finally, these observations all indicate that U 3 Al 2 Ge 3 is a close realization of the three-dimensional axial next-nearest-neighbor Ising model, a prototypical framework for describing commensurate to incommensurate phase transitions in frustrated magnets.« less

Realization of the axial next-nearest-neighbor Ising model in U 3 Al 2 Ge 3

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

Fobes, David M.; Lin, Shi-Zeng; Ghimire, Nirmal J.

Inmore » this paper, we report small-angle neutron scattering (SANS) measurements and theoretical modeling of U 3 Al 2 Ge 3 . Analysis of the SANS data reveals a phase transition to sinusoidally modulated magnetic order at T N = 63 K to be second order and a first-order phase transition to ferromagnetic order at T c = 48 K. Within the sinusoidally modulated magnetic phase (T c < T < T N), we uncover a dramatic change, by a factor of 3, in the ordering wave vector as a function of temperature. Finally, these observations all indicate that U 3 Al 2 Ge 3 is a close realization of the three-dimensional axial next-nearest-neighbor Ising model, a prototypical framework for describing commensurate to incommensurate phase transitions in frustrated magnets.« less

EPR investigation of the trivalent chromium complexes in SrTiO3

NASA Astrophysics Data System (ADS)

Azamat, D. V.; Dejneka, A.; Lančok, J.; Jastrabik, L.; Trepakov, V. A.; Bryknar, Z.; Neverova, E. V.; Badalyan, A. G.

2014-02-01

The trivalent chromium centers were investigated by means of electron paramagnetic resonance (EPR) in SrTiO3 single crystals grown using the Verneuil technique. It was shown that the charge compensation of the Cr3+-VO dominant centers in octahedral environment is due to the remote oxygen vacancy located on the axial axis of the center. In order to provide insight into spin-phonon relaxation processes the studies of axial distortion of Cr3+-VO centers have been performed as function of temperature. The analysis of the trigonal Cr3+ centers found in SrTiO3 indicates the presence of the nearest-neighbor strontium vacancy. The next-nearest-neighbor exchange-coupled pairs of Cr3+ in SrTiO3 has been analyzed from the angular variation of the total electron spin of S=2 resonance lines.

Modulational Instability and Quantum Discrete Breather States of Cold Bosonic Atoms in a Zig-Zag Optical Lattice

NASA Astrophysics Data System (ADS)

Chang, Xia; Xie, Jiayu; Wu, Tianle; Tang, Bing

2018-07-01

A theoretical study on modulational instability and quantum discrete breather states in a system of cold bosonic atoms in zig-zag optical lattices is presented in this work. The time-dependent Hartree approximation is employed to deal with the multiple body problem. By means of a linear stability analysis, we analytically study the modulational instability, and estimate existence conditions of the bright stationary localized solutions for different values of the second-neighbor hopping constant. On the other hand, we get analytical bright stationary localized solutions, and analyze the influence of the second-neighbor hopping on their existence conditions. The predictions of the modulational instability analysis are shown to be reliable. Using these stationary localized single-boson wave functions, the quantum breather states corresponding to the system with different types of nonlinearities are constructed.

On the structural context and identification of enzyme catalytic residues.

PubMed

Chien, Yu-Tung; Huang, Shao-Wei

2013-01-01

Enzymes play important roles in most of the biological processes. Although only a small fraction of residues are directly involved in catalytic reactions, these catalytic residues are the most crucial parts in enzymes. The study of the fundamental and unique features of catalytic residues benefits the understanding of enzyme functions and catalytic mechanisms. In this work, we analyze the structural context of catalytic residues based on theoretical and experimental structure flexibility. The results show that catalytic residues have distinct structural features and context. Their neighboring residues, whether sequence or structure neighbors within specific range, are usually structurally more rigid than those of noncatalytic residues. The structural context feature is combined with support vector machine to identify catalytic residues from enzyme structure. The prediction results are better or comparable to those of recent structure-based prediction methods.

Ties that bind: implications of social support for rural, partnered African American women's health functioning.

PubMed

Black, Angela R; Cook, Jennifer L; Murry, Velma McBride; Cutrona, Carolyn E

2005-01-01

Ecological theory was used to explore the pathways through which intimate relationship quality influenced health functioning among rural, partnered African American women. Structural equation modeling was used to analyze data from 349 women in Georgia and Iowa. Women's intimate relationship quality was positively associated with their psychological and physical health functioning. Support from community residents moderated this link, which was strongest for women who felt most connected with their neighbors and for women who believed their neighborhood to have a sense of communal responsibility. Future research should identify other factors salient to health functioning among members of this population.

Frog sound identification using extended k-nearest neighbor classifier

NASA Astrophysics Data System (ADS)

Mukahar, Nordiana; Affendi Rosdi, Bakhtiar; Athiar Ramli, Dzati; Jaafar, Haryati

2017-09-01

Frog sound identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed to evaluate the accuracy of frog sound identification. This paper presents a frog sound identification with Extended k-Nearest Neighbor (EKNN) classifier. The EKNN classifier integrates the nearest neighbors and mutual sharing of neighborhood concepts, with the aims of improving the classification performance. It makes a prediction based on who are the nearest neighbors of the testing sample and who consider the testing sample as their nearest neighbors. In order to evaluate the classification performance in frog sound identification, the EKNN classifier is compared with competing classifier, k -Nearest Neighbor (KNN), Fuzzy k -Nearest Neighbor (FKNN) k - General Nearest Neighbor (KGNN)and Mutual k -Nearest Neighbor (MKNN) on the recorded sounds of 15 frog species obtained in Malaysia forest. The recorded sounds have been segmented using Short Time Energy and Short Time Average Zero Crossing Rate (STE+STAZCR), sinusoidal modeling (SM), manual and the combination of Energy (E) and Zero Crossing Rate (ZCR) (E+ZCR) while the features are extracted by Mel Frequency Cepstrum Coefficient (MFCC). The experimental results have shown that the EKNCN classifier exhibits the best performance in terms of accuracy compared to the competing classifiers, KNN, FKNN, GKNN and MKNN for all cases.

Partner switching promotes cooperation among myopic agents on a geographical plane

NASA Astrophysics Data System (ADS)

Li, Yixiao; Min, Yong; Zhu, Xiaodong; Cao, Jie

2013-02-01

We study the coupling dynamics between the evolution of cooperation and the evolution of partnership network on a geographical plane. While agents play networked prisoner’s dilemma games, they can dynamically adjust their partnerships based on local information about reputation. We incorporate geographical features into the process of the agent’s partner switching and investigate the corresponding effects. At each time step of the coevolution, a random agent can either update his strategy by imitation or adjust his partnership by switching from the lowest reputation partner to the highest reputation one among his neighbors. We differentiate two types of neighbors: geographical neighbors (i.e., the set of agents who are close to the focal agent in terms of geographical distance) and connectivity neighbors (i.e., the set of agents who are close to the focal agent in the partnership network in terms of geodesic distance). We find that switching to either geographical neighbors or connectivity neighbors enhances cooperation greatly in a wide parameter range. Cooperation can be favored in a much stricter condition when agents switch to connectivity neighbors more frequently. However, an increasing tendency of reconnecting to geographical neighbors shortens the geographical distance between a pair of partners on average. When agents consider the cost of geographical distance in adjusting the partnership, they are prone to reconnect to geographical neighbors.

Adaptive local linear regression with application to printer color management.

PubMed

Gupta, Maya R; Garcia, Eric K; Chin, Erika

2008-06-01

Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

Link prediction measures considering different neighbors’ effects and application in social networks

NASA Astrophysics Data System (ADS)

Luo, Peng; Wu, Chong; Li, Yongli

Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

Loss of MeCP2 From Forebrain Excitatory Neurons Leads to Cortical Hyperexcitation and Seizures

PubMed Central

Zhang, Wen; Peterson, Matthew; Beyer, Barbara; Frankel, Wayne N.

2014-01-01

Mutations of MECP2 cause Rett syndrome (RTT), a neurodevelopmental disorder leading to loss of motor and cognitive functions, impaired social interactions, and seizure at young ages. Defects of neuronal circuit development and function are thought to be responsible for the symptoms of RTT. The majority of RTT patients show recurrent seizures, indicating that neuronal hyperexcitation is a common feature of RTT. However, mechanisms underlying hyperexcitation in RTT are poorly understood. Here we show that deletion of Mecp2 from cortical excitatory neurons but not forebrain inhibitory neurons in the mouse leads to spontaneous seizures. Selective deletion of Mecp2 from excitatory but not inhibitory neurons in the forebrain reduces GABAergic transmission in layer 5 pyramidal neurons in the prefrontal and somatosensory cortices. Loss of MeCP2 from cortical excitatory neurons reduces the number of GABAergic synapses in the cortex, and enhances the excitability of layer 5 pyramidal neurons. Using single-cell deletion of Mecp2 in layer 2/3 pyramidal neurons, we show that GABAergic transmission is reduced in neurons without MeCP2, but is normal in neighboring neurons with MeCP2. Together, these results suggest that MeCP2 in cortical excitatory neurons plays a critical role in the regulation of GABAergic transmission and cortical excitability. PMID:24523563

Self-optimizing charge-transfer energy phenomena in metallosupramolecular complexes by dynamic constitutional self-sorting.

PubMed

Legrand, Yves-Marie; van der Lee, Arie; Barboiu, Mihail

2007-11-12

In this paper we report an extended series of 2,6-(iminoarene)pyridine-type ZnII complexes [(Lii)2Zn]II, which were surveyed for their ability to self-exchange both their ligands and their aromatic arms and to form different homoduplex and heteroduplex complexes in solution. The self-sorting of heteroduplex complexes is likely to be the result of geometric constraints. Whereas the imine-exchange process occurs quantitatively in 1:1 mixtures of [(Lii)2Zn]II complexes, the octahedral coordination process around the metal ion defines spatial-frustrated exchanges that involve the selective formation of heterocomplexes of two, by two different substituents; the bulkiest ones (pyrene in principle) specifically interact with the pseudoterpyridine core, sterically hindering the least bulky ones, which are intermolecularly stacked with similar ligands of neighboring molecules. Such a self-sorting process defined by the specific self-constitution of the ligands exchanging their aromatic substituents is self-optimized by a specific control over their spatial orientation around a metal center within the complex. They ultimately show an improved charge-transfer energy function by virtue of the dynamic amplification of self-optimized heteroduplex architectures. These systems therefore illustrate the convergence of the combinatorial self-sorting of the dynamic combinatorial libraries (DCLs) strategy and the constitutional self-optimized function.

Metabolic labeling enables selective photocrosslinking of O-GlcNAc-modified proteins to their binding partners

PubMed Central

Yu, Seok-Ho; Boyce, Michael; Wands, Amberlyn M.; Bond, Michelle R.; Bertozzi, Carolyn R.; Kohler, Jennifer J.

2012-01-01

O-linked β-N-acetylglucosamine (O-GlcNAc) is a reversible posttranslational modification found on hundreds of nuclear and cytoplasmic proteins in higher eukaryotes. Despite its ubiquity and essentiality in mammals, functional roles for the O-GlcNAc modification remain poorly defined. Here we develop a combined genetic and chemical approach that enables introduction of the diazirine photocrosslinker onto the O-GlcNAc modification in cells. We engineered mammalian cells to produce diazirine-modified O-GlcNAc by expressing a mutant form of UDP-GlcNAc pyrophosphorylase and subsequently culturing these cells with a cell-permeable, diazirine-modified form of GlcNAc-1-phosphate. Irradiation of cells with UV light activated the crosslinker, resulting in formation of covalent bonds between O-GlcNAc-modified proteins and neighboring molecules, which could be identified by mass spectrometry. We used this method to identify interaction partners for the O-GlcNAc-modified FG-repeat nucleoporins. We observed crosslinking between FG-repeat nucleoporins and nuclear transport factors, suggesting that O-GlcNAc residues are intimately associated with essential recognition events in nuclear transport. Further, we propose that the method reported here could find widespread use in investigating the functional consequences of O-GlcNAcylation. PMID:22411826

Science Literacy in School and Home Contexts: Kindergarteners' Science Achievement and Motivation

ERIC Educational Resources Information Center

Mantzicopoulos, Panayota; Patrick, Helen; Samarapungavan, Ala

2013-01-01

We examined science learning and motivation outcomes as a function of children's participation in the classroom and classroom-plus-home components of the Scientific Literacy Project (SLP). The sample was comprised of kindergarten children in 4 low income, neighboring schools. Children in Schools 1 and 2 (n = 120) participated in the SLP science…

ECOWAS and Lome,

DTIC Science & Technology

1980-01-01

purpose of exporting cash crops but which generally did not cross colonial frontiers, and preferential trading systems and banking arrange- ments which...divide through cooperation in specific functional organisations--the Cocoa Producers Alliance (founded 1962), the African Groundnut Council (1964), the...arrangements essentially allowed EEC exports privileged access to Associates’ markets vis-a-vis the exports of all other countries, including the neighboring

Organizational Effectiveness through Assessing Institutional Outcomes: Measuring the Transfer Function at CCTC.

ERIC Educational Resources Information Center

Mohammadi, John; Danek, Kim

This study assesses the academic performance of Capital Community-Technical College (CCTC) students who transferred to senior institutions in Connecticut and neighboring states between the academic years of 1993-94 and 1996-97. It was designed to address the students' experience at CCTC as compared to the students' experiences at their senior…

Herd-level risk factors for bovine tuberculosis in French cattle herds.

PubMed

Marsot, Maud; Béral, Marina; Scoizec, Axelle; Mathevon, Yoann; Durand, Benoit; Courcoul, Aurélie

2016-09-01

Although officially free of bovine tuberculosis (bTB), France has been experiencing a slight increase in the incidence and geographical spread of the infection. Eradication of bTB requires determining the infection risk factors. Although several studies identifying bTB risk factors have been conducted in the United Kingdom and Spain, no information is currently available regarding bTB risk factors in French cattle. The objective of this work was thus to study the factors associated with the risk of bTB in cattle herds in three French administrative divisions (départements of Ardennes, Côte d'Or and Dordogne). A case-control study was conducted to compare herds having experienced a bTB outbreak between 2012 and early 2014 with randomly selected control herds of the three study départements. A questionnaire of farming practices, inter-herd contacts (e.g. at pasture or via vehicles or materials), and the presence of other domestic species was carried out in the selected herds. Data on other variables of interest included animal movements between farms and potential contacts between cattle and wildlife (e.g. badger and wild boar abundances) were also collected. Multivariable logistic regression and multimodel inference methods were used to assess risk factors related to bTB. A total of 216 herds (72 cases and 144 controls) were analyzed. The two main risk factors were the presence of a recent neighboring outbreak, being defined as a neighboring herd at pasture reported as infected in the past two years (odds ratio (OR)=3.6; population attributable fraction (PAF)=30.7%) and the presence of a farm building for cattle housing or for feed storage located at more than 300-m from inhabited areas (OR=2.3; PAF=27.6%). Another risk factor was related to sharing water points at pasture with a recent neighboring outbreak. Results illustrated the multifactorial nature of bTB dynamics. The risk factors related to recently infected neighboring herds could be attributable to between-herd contacts at pasture and/or to exposure to a common source of infection (environment or wildlife). Moreover, the use of remote farm buildings by wildlife may also play a role in the bTB spread in the French départements studied. The identification of the main risk factors help better understand bTB dynamics and are useful for implementing appropriate and targeted surveillance, biosecurity and control measures in France. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of Image Analysis for Characterization of Spatial Arrangements of Features in Microstructure

NASA Technical Reports Server (NTRS)

Louis, Pascal; Gokhale, Arun M.

1995-01-01

A number of microstructural processes are sensitive to the spatial arrangements of features in microstructure. However, very little attention has been given in the past to the experimental measurements of the descriptors of microstructural distance distributions due to the lack of practically feasible methods. We present a digital image analysis procedure to estimate the micro-structural distance distributions. The application of the technique is demonstrated via estimation of K function, radial distribution function, and nearest-neighbor distribution function of hollow spherical carbon particulates in a polymer matrix composite, observed in a metallographic section.

Toward a generalized theory of epidemic awareness in social networks

NASA Astrophysics Data System (ADS)

Wu, Qingchu; Zhu, Wenfang

We discuss the dynamics of a susceptible-infected-susceptible (SIS) model with local awareness in networks. Individual awareness to the infectious disease is characterized by a general function of epidemic information in its neighborhood. We build a high-accuracy approximate equation governing the spreading dynamics and derive an approximate epidemic threshold above which the epidemic spreads over the whole network. Our results extend the previous work and show that the epidemic threshold is dependent on the awareness function in terms of one infectious neighbor. Interestingly, when a pow-law awareness function is chosen, the epidemic threshold can emerge in infinite networks.

Frustrated quantum magnetism in the Kondo lattice on the zigzag ladder

NASA Astrophysics Data System (ADS)

Peschke, Matthias; Rausch, Roman; Potthoff, Michael

2018-03-01

The interplay between the Kondo effect, indirect magnetic interaction, and geometrical frustration is studied in the Kondo lattice on the one-dimensional zigzag ladder. Using the density-matrix renormalization group, the ground-state and various short- and long-range spin- and density-correlation functions are calculated for the model at half filling as a function of the antiferromagnetic Kondo interaction down to J =0.3 t , where t is the nearest-neighbor hopping on the zigzag ladder. Geometrical frustration is shown to lead to at least two critical points: Starting from the strong-J limit, where almost local Kondo screening dominates and where the system is a nonmagnetic Kondo insulator, antiferromagnetic correlations between nearest-neighbor and next-nearest-neighbor local spins become stronger and stronger, until at Jcdim≈0.89 t frustration is alleviated by a spontaneous breaking of translational symmetry and a corresponding transition to a dimerized state. This is characterized by antiferromagnetic correlations along the legs and by alternating antiferro- and ferromagnetic correlations on the rungs of the ladder. A mechanism of partial Kondo screening that has been suggested for the Kondo lattice on the two-dimensional triangular lattice is not realized in the one-dimensional case. Furthermore, within the symmetry-broken dimerized state, there is a magnetic transition to a 90∘ quantum spin spiral with quasi-long-range order at Jcmag≈0.84 t . The quantum-critical point is characterized by a closure of the spin gap (with decreasing J ) and a divergence of the spin-correlation length and of the spin-structure factor S (q ) at wave vector q =π /2 . This is opposed to the model on the one-dimensional bipartite chain, which is known to have a finite spin gap for all J >0 at half filling.

Qualitative assessment of ultra-fast non-Grotthuss proton dynamics in S1 excited state of liquid H2O from ab initio time-dependent density functional theory★

NASA Astrophysics Data System (ADS)

Ziaei, Vafa; Bredow, Thomas

2017-11-01

We study qualitatively ultra-fast proton transfer (PT) in the first singlet (S1) state of liquid water (absorption onset) through excited-state dynamics by means of time-dependent density functional theory and ab initio Born-Oppenheimer molecular dynamics. We find that after the initial excitation, a PT occurs in S1 in form of a rapid jump to a neighboring water molecule, on which the proton either may rest for a relatively long period of time (as a consequence of possible defect in the hydrogen bond network) followed by back and forth hops to its neighboring water molecule or from which it further moves to the next water molecule accompanied by back and forth movements. In this way, the proton may become delocalized over a long water wire branch, followed again by back and forth jumps or short localization on a water molecule for some femtoseconds. As a result, the mechanism of PT in S1 is in most cases highly non-Grotthuss-like, delayed and discrete. Furthermore, upon PT an excess charge is ejected to the solvent trap, the so-called solvated electron. The spatial extent of the ejected solvated electron is mainly localized within one solvent shell with overlappings on the nearest neighbor water molecules and delocalizing (diffuse) tails extending beyond the first solvent sphere. During the entire ultra-short excited-state dynamics the remaining OH radical from the initially excited water molecule exhibits an extremely low mobility and is non-reactive. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjb/e2017-80329-7.

A Spatio-Temporal Model of Phenotypic Evolution in the Atlantic Silverside (Menidia menidia) and Its Implications for Size-Selective Fishing in a Warmer World

NASA Astrophysics Data System (ADS)

Sbrocco, E. J.

2016-02-01

A pervasive phenotypic pattern observed across marine fishes is that vertebral number increases with latitude. Jordan's Rule, as it is known, holds true both within and across species, and like other ecogeographic principles (e.g., Bergmann's Rule), it is presumed to be an adaptive response to latitudinal gradients in temperature. As such, future ocean warming is expected to impact not only the geographic range limits of marine fishes that conform to Jordan's Rule, but also their phenotype, with warmer waters selecting for fish with fewer vertebrae at any given latitude. Here I present a model of phenotypic evolution over space and time for the Atlantic silverside (Menidia menidia), a common marine fish found in coastal waters along the western North Atlantic. This species has long served as a model organism for the study of fisheries-induced selection and exhibits numerous latitudinal clines in phenotypic and life-history traits, including vertebral number. Common garden experiments have shown that vertebral number is genetically determined in this species, but correlative models of observed vertebral counts and climate reveal that SST is the single strongest predictor of phenotype, even after accounting for gene flow. This result indicates that natural selection is responsible for maintaining vertebral clines in the silverside, and allows for the prediction of phenotypic responses to ocean warming. By integrating genetic estimates of population connectivity, species distribution models, and statistical models, I find that by the end of the 21st century, ocean warming will select for silversides with up to 8% fewer vertebrae. Mid-Atlantic populations are the most mal-adapted for future conditions, but may be rescued by migration from small-phenotype southern neighbors or by directional selection. Despite smaller temperature anomalies, the strongest impacts of warming will be felt at both northern and southern edges of the distribution, where genetic rescue from neighboring populations is not predicted to occur and in situ directional selection is less likely due to low phenotypic variation. This study has important implications for marine fisheries, since climate-induced phenotypic evolution may compound issues that already exist as a result of size-selective harvest of large, fast-growing fish.

Segregation and trapping of oxygen vacancies near the SrTiO 3Σ3 (112) [110] tilt grain boundary

DOE PAGES

Liu, Bin; Cooper, Valentino R.; Zhang, Yanwen; ...

2015-03-21

In nanocrystalline materials, structural discontinuities at grain boundaries (GBs) and the segregation of point defects to these GBs play a key role in defining the structural stability of a material, as well as its macroscopic electrical/mechanical properties. In this study, the segregation of oxygen vacancies near the Σ3 (1 1 2) [¯110] tilt GB in SrTiO 3 is explored using density functional theory. We find that oxygen vacancies segregate toward the GB, preferring to reside within the next nearest-neighbor layer. This oxygen vacancy segregation is found to be crucial for stabilizing this tilt GB. Furthermore, we find that the migrationmore » barriers of oxygen vacancies diffusing toward the first nearest-neighbor layer of the GB are low, while those away from this layer are very high. Furthermore, the segregation and trapping of the oxygen vacancies in the first nearest-neighbor layer of GBs are attributed to the large local distortions, which can now accommodate the preferred sixfold coordination of Ti. These results suggest that the electronic, transport, and capacitive properties of SrTiO 3 can be engineered through the control of GB structure and grain size or layer thickness.« less

Simulating ensembles of source water quality using a K-nearest neighbor resampling approach.

PubMed

Towler, Erin; Rajagopalan, Balaji; Seidel, Chad; Summers, R Scott

2009-03-01

Climatological, geological, and water management factors can cause significant variability in surface water quality. As drinking water quality standards become more stringent, the ability to quantify the variability of source water quality becomes more important for decision-making and planning in water treatment for regulatory compliance. However, paucity of long-term water quality data makes it challenging to apply traditional simulation techniques. To overcome this limitation, we have developed and applied a robust nonparametric K-nearest neighbor (K-nn) bootstrap approach utilizing the United States Environmental Protection Agency's Information Collection Rule (ICR) data. In this technique, first an appropriate "feature vector" is formed from the best available explanatory variables. The nearest neighbors to the feature vector are identified from the ICR data and are resampled using a weight function. Repetition of this results in water quality ensembles, and consequently the distribution and the quantification of the variability. The main strengths of the approach are its flexibility, simplicity, and the ability to use a large amount of spatial data with limited temporal extent to provide water quality ensembles for any given location. We demonstrate this approach by applying it to simulate monthly ensembles of total organic carbon for two utilities in the U.S. with very different watersheds and to alkalinity and bromide at two other U.S. utilities.

Complex Consequences of Herbivory and Interplant Cues in Three Annual Plants

PubMed Central

Pearse, Ian S.; Porensky, Lauren M.; Yang, Louie H.; Stanton, Maureen L.; Karban, Richard; Bhattacharyya, Lisa; Cox, Rosa; Dove, Karin; Higgins, August; Kamoroff, Corrina; Kirk, Travis; Knight, Christopher; Koch, Rebecca; Parker, Corwin; Rollins, Hilary; Tanner, Kelsey

2012-01-01

Information exchange (or signaling) between plants following herbivore damage has recently been shown to affect plant responses to herbivory in relatively simple natural systems. In a large, manipulative field study using three annual plant species (Achyrachaena mollis, Lupinus nanus, and Sinapis arvensis), we tested whether experimental damage to a neighboring conspecific affected a plant's lifetime fitness and interactions with herbivores. By manipulating relatedness between plants, we assessed whether genetic relatedness of neighboring individuals influenced the outcome of having a damaged neighbor. Additionally, in laboratory feeding assays, we assessed whether damage to a neighboring plant specifically affected palatability to a generalist herbivore and, for S. arvensis, a specialist herbivore. Our study suggested a high level of contingency in the outcomes of plant signaling. For example, in the field, damaging a neighbor resulted in greater herbivory to A. mollis, but only when the damaged neighbor was a close relative. Similarly, in laboratory trials, the palatability of S. arvensis to a generalist herbivore increased after the plant was exposed to a damaged neighbor, while palatability to a specialist herbivore decreased. Across all species, damage to a neighbor resulted in decreased lifetime fitness, but only if neighbors were closely related. These results suggest that the outcomes of plant signaling within multi-species neighborhoods may be far more context-specific than has been previously shown. In particular, our study shows that herbivore interactions and signaling between plants are contingent on the genetic relationship between neighboring plants. Many factors affect the outcomes of plant signaling, and studies that clarify these factors will be necessary in order to assess the role of plant information exchange about herbivory in natural systems. PMID:22675439

Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists.

PubMed

Bonet, Isis; Franco-Montero, Pedro; Rivero, Virginia; Teijeira, Marta; Borges, Fernanda; Uriarte, Eugenio; Morales Helguera, Aliuska

2013-12-23

A(2B) adenosine receptor antagonists may be beneficial in treating diseases like asthma, diabetes, diabetic retinopathy, and certain cancers. This has stimulated research for the development of potent ligands for this subtype, based on quantitative structure-affinity relationships. In this work, a new ensemble machine learning algorithm is proposed for classification and prediction of the ligand-binding affinity of A(2B) adenosine receptor antagonists. This algorithm is based on the training of different classifier models with multiple training sets (composed of the same compounds but represented by diverse features). The k-nearest neighbor, decision trees, neural networks, and support vector machines were used as single classifiers. To select the base classifiers for combining into the ensemble, several diversity measures were employed. The final multiclassifier prediction results were computed from the output obtained by using a combination of selected base classifiers output, by utilizing different mathematical functions including the following: majority vote, maximum and average probability. In this work, 10-fold cross- and external validation were used. The strategy led to the following results: i) the single classifiers, together with previous features selections, resulted in good overall accuracy, ii) a comparison between single classifiers, and their combinations in the multiclassifier model, showed that using our ensemble gave a better performance than the single classifier model, and iii) our multiclassifier model performed better than the most widely used multiclassifier models in the literature. The results and statistical analysis demonstrated the supremacy of our multiclassifier approach for predicting the affinity of A(2B) adenosine receptor antagonists, and it can be used to develop other QSAR models.

Estimating the Turn-around Radii of Six Isolated Galaxy Groups in the Local Universe

NASA Astrophysics Data System (ADS)

Lee, Jounghun

2018-03-01

Estimates of the turn-around radii of six isolated galaxy groups in the nearby universe are presented. From the Tenth Data Release of the Sloan Digital Sky Survey, we first select those isolated galaxy groups at redshifts z ≤ 0.05 in the mass range [0.3–1] × {10}14 {h}-1 {M}ȯ whose nearest-neighbor groups are located at distances larger than 15 times their virial radii. Then, we search for a gravitationally interacting web-like structure around each isolated group, which appears as an inclined streak pattern in the anisotropic spatial distribution of the neighboring field galaxies. Out of 59 isolated groups, only seven are found to possess such web-like structures in their neighbor zones, but one of them turns out to be NGC 5353/4, whose turn-around radius was already measured in a previous work and was thus excluded from our analysis. Applying the Turn-around Radius Estimator algorithm devised by Lee et al. to the identified web-like structures of the remaining six target groups, we determine their turn-around radii and show that three out of the six targets have larger turn-around radii than the spherical bound limit predicted by Planck cosmology. We discuss possible sources of the apparent violations of the three groups, including the underestimated spherical bound limit due to the approximation of the turn-around mass by the virial mass.

Availability and costs of single cigarettes in Guatemala.

PubMed

de Ojeda, Ana; Barnoya, Joaquin; Thrasher, James F

2013-01-01

Single-cigarette sales have been associated with increased cigarette accessibility to less educated, lower-income populations, and minors; lower immediate cost, and increased smoking cues. Since 1997, Guatemalan Law bans the sale of single cigarettes and packs with fewer than 20 cigarettes. In 2005, Guatemala ratified the World Health Organization Framework Convention on Tobacco Control (WHO FCTC); it is therefore obliged to "prohibit sale of cigarettes individually or in small packets." Blocks were numbered and randomly selected in Guatemala City and 3 neighboring towns. All stores in each block were surveyed. Single-cigarette and fewer than 20-cigarette pack sales were assessed by observation and purchase attempts. Cigarette brands and manufacturers (Philip Morris, PM or British American Tobacco, BAT) were also recorded. Percentages and means were used to describe data. Analyses were done using STATA 11.0. Of 398 stores and street vendors surveyed, 75.6% (301) sold cigarettes. Of these, 91% (275) sold single cigarettes and none sold fewer than 20-cigarette packs. Only informal economic sectors sold singles. There was no difference on sales between Guatemala City and neighboring towns and by store type. Buying 20 single cigarettes was US$ 0.83 more expensive than buying a 20-cigarette pack. The most prevalent brands were Rubios (PM), Marlboro (PM), Payasos (BAT), and After Hours (BAT). Single-cigarettes sales are highly prevalent among informal economic sectors in Guatemala City and its neighboring towns. Our data should prove useful to advocate for FCTC Article 16 enforcement in Guatemala.

An operando Raman study of molecular structure and reactivity of molybdenum(VI) oxide supported on anatase for the oxidative dehydrogenation of ethane.

PubMed

Tsilomelekis, George; Boghosian, Soghomon

2012-02-21

Supported molybdenum oxide catalysts on TiO(2) (anatase) with surface densities in the range of 1.8-17.0 Mo per nm(2) were studied at temperatures of 410-480 °C for unraveling the configuration and molecular structure of the deposited (MoO(x))(n) species and examining their behavior for the ethane oxidative dehydrogenation (ODH). In situ Raman and in situ FTIR spectra under oxidizing conditions combined with (18)O/(16)O isotope exchange studies provide the first sound evidence for mono-oxo configuration for the deposited (MoO(x))(n) species on anatase. Isolated O=Mo(-O-)(3) tetra-coordinated species in C(3v)-like symmetry prevail at all surface coverages with a low presence of associated (polymeric) species (probably penta-coordinated) evidenced at high coverages, below the approximate monolayer of 6 Mo per nm(2). A mechanistic scenario for (18)O/(16)O isotope exchange and next-nearest-neighbor vibrational isotope effect is proposed at the molecular level to account for the pertinent spectral observations. Catalytic measurements for ethane ODH with simultaneous monitoring of operando Raman spectra were performed. The selectivity to ethylene increases with increasing surface density up to the monolayer coverage, where primary steps of ethane activation follow selective reaction pathways leading to ∼100% C(2)H(4) selectivity. The operando Raman spectra and a quantitative exploitation of the relative normalized Mo=O band intensities for surface densities of 1.8-5.9 Mo per nm(2) and various residence times show that the terminal Mo=O sites are involved in non-selective reaction turnovers. Reaction routes follow primarily non-selective pathways at low coverage and selective pathways at high coverage. Trends in the initial rates of ethane consumption (apparent reactivity per Mo) as a function of Mo surface density are discussed on the basis of several factors.

Rumor has it...: relay communication of stress cues in plants.

PubMed

Falik, Omer; Mordoch, Yonat; Quansah, Lydia; Fait, Aaron; Novoplansky, Ariel

2011-01-01

Recent evidence demonstrates that plants are able not only to perceive and adaptively respond to external information but also to anticipate forthcoming hazards and stresses. Here, we tested the hypothesis that unstressed plants are able to respond to stress cues emitted from their abiotically-stressed neighbors and in turn induce stress responses in additional unstressed plants located further away from the stressed plants. Pisum sativum plants were subjected to drought while neighboring rows of five unstressed plants on both sides, with which they could exchange different cue combinations. On one side, the stressed plant and its unstressed neighbors did not share their rooting volumes (UNSHARED) and thus were limited to shoot communication. On its other side, the stressed plant shared one of its rooting volumes with its nearest unstressed neighbor and all plants shared their rooting volumes with their immediate neighbors (SHARED), allowing both root and shoot communication. Fifteen minutes following drought induction, significant stomatal closure was observed in both the stressed plants and their nearest unstressed SHARED neighbors, and within one hour, all SHARED neighbors closed their stomata. Stomatal closure was not observed in the UNSHARED neighbors. The results demonstrate that unstressed plants are able to perceive and respond to stress cues emitted by the roots of their drought-stressed neighbors and, via 'relay cuing', elicit stress responses in further unstressed plants. Further work is underway to study the underlying mechanisms of this new mode of plant communication and its possible adaptive implications for the anticipation of forthcoming abiotic stresses by plants.

Substituent Effects on the Self-Assembly/Coassembly and Hydrogelation of Phenylalanine Derivatives.

PubMed

Liyanage, Wathsala; Nilsson, Bradley L

2016-01-26

Supramolecular hydrogels derived from the self-assembly of organic molecules have been exploited for applications ranging from drug delivery to tissue engineering. The relationship between the structure of the assembly motif and the emergent properties of the resulting materials is often poorly understood, impeding rational approaches for the creation of next-generation materials. Aromatic π-π interactions play a significant role in the self-assembly of many supramolecular hydrogelators, but the exact nature of these interactions lacks definition. Conventional models that describe π-π interactions rely on quadrupolar electrostatic interactions between neighboring aryl groups in the π-system. However, recent experimental and computational studies reveal the potential importance of local dipolar interactions between elements of neighboring aromatic rings in stabilizing π-π interactions. Herein, we examine the nature of π-π interactions in the self- and coassembly of Fmoc-Phe-derived hydrogelators by systematically varying the electron-donating or electron-withdrawing nature of the side chain benzyl substituents and correlating these effects to the emergent assembly and gelation properties of the systems. These studies indicate a significant role for stabilizing dipolar interactions between neighboring benzyl groups in the assembled materials. Additional evidence for specific dipolar interactions is provided by high-resolution crystal structures obtained from dynamic transition of gel fibrils to crystals for several of the self-assembled/coassembled Fmoc-Phe derivatives. In addition to electronic effects, steric properties also have a significant effect on the interaction between neighboring benzyl groups in these assembled systems. These findings provide significant insight into the structure-function relationship for Fmoc-Phe-derived hydrogelators and give cues for the design of next-generation materials with desired emergent properties.

Odontoblasts as sensory receptors: transient receptor potential channels, pannexin-1, and ionotropic ATP receptors mediate intercellular odontoblast-neuron signal transduction.

PubMed

Shibukawa, Yoshiyuki; Sato, Masaki; Kimura, Maki; Sobhan, Ubaidus; Shimada, Miyuki; Nishiyama, Akihiro; Kawaguchi, Aya; Soya, Manabu; Kuroda, Hidetaka; Katakura, Akira; Ichinohe, Tatsuya; Tazaki, Masakazu

2015-04-01

Various stimuli induce pain when applied to the surface of exposed dentin. However, the mechanisms underlying dentinal pain remain unclear. We investigated intercellular signal transduction between odontoblasts and trigeminal ganglion (TG) neurons following direct mechanical stimulation of odontoblasts. Mechanical stimulation of single odontoblasts increased the intracellular free calcium concentration ([Ca(2+)]i) by activating the mechanosensitive-transient receptor potential (TRP) channels TRPV1, TRPV2, TRPV4, and TRPA1, but not TRPM8 channels. In cocultures of odontoblasts and TG neurons, increases in [Ca(2+)]i were observed not only in mechanically stimulated odontoblasts, but also in neighboring odontoblasts and TG neurons. These increases in [Ca(2+)]i were abolished in the absence of extracellular Ca(2+) and in the presence of mechanosensitive TRP channel antagonists. A pannexin-1 (ATP-permeable channel) inhibitor and ATP-degrading enzyme abolished the increases in [Ca(2+)]i in neighboring odontoblasts and TG neurons, but not in the stimulated odontoblasts. G-protein-coupled P2Y nucleotide receptor antagonists also inhibited the increases in [Ca(2+)]i. An ionotropic ATP (P2X3) receptor antagonist inhibited the increase in [Ca(2+)]i in neighboring TG neurons, but not in stimulated or neighboring odontoblasts. During mechanical stimulation of single odontoblasts, a connexin-43 blocker did not have any effects on the [Ca(2+)]i responses observed in any of the cells. These results indicate that ATP, released from mechanically stimulated odontoblasts via pannexin-1 in response to TRP channel activation, transmits a signal to P2X3 receptors on TG neurons. We suggest that odontoblasts are sensory receptor cells and that ATP released from odontoblasts functions as a neurotransmitter in the sensory transduction sequence for dentinal pain.

NASA Alternative Orion Small Cell Battery Design Support

NASA Technical Reports Server (NTRS)

Haynes, Chuck

2016-01-01

The NASA Orion Crew Module Reference Design was produced to address large scale thermal runaway (TR) hazard with specific safety controls for the Orion Spacecraft. The design presented provides the description of a full scale battery design reference for implementation as a drop in replacement to meet all spacecraft energy requirements with compatible 120 Vdc electrical and mechanical interface using small cell technology (18650) packaging. The 32V SuperBrick incorporates unique support features and an electrical bus bar arrangement that allows cells negative can insertion into heat sink that is compressively coupled to the battery enclosure to promote good thermal management. The housing design also provides an internal flame suppression "filter tray" and positive venting path internal to the enclosure to allow hot effluent ejecta to escape in the event of single cell TR. Virtual cells (14P Banks) that are supported to provide cell spacing with interstitial materials to prevent side can failures that can produce cell to cell TR propagation. These features were successfully test in four separate TR run with the full scale DTA1 test article in February 2016. Successfully Completed Test Objectives - Four separate TR test runs with Full-Scale DTA1 housing with Two SuperBricks, Two SuperBrick Emulators All Tests resulted in "clean" gas with less than 6 C rise at Battery vent All Tests resulted in less than 2 C temperature rise on cold-plate outlet All Tests resulted in less than 6 psi pressure rise in the battery housing Test Run 1 -One neighbor cell TR, highest remaining neighbor 139 C. Ejecta shorted to bus caused prolonged additional heating, One shorted cell did experience TR after 12 minutes, remaining cells had adequate thermal margin Test Run 2 - No cell to cell propagation, highest neighbor cell 112 C; Test Run 3 - No cell to cell propagation, highest neighbor cell 96 C; Test Run 4 - No cell to cell propagation, highest neighbor cell 101 C; Primary TR testing and analysis were completed and reviewed for endorsement by NASA Engineering and Safety Center team members. All Key Test Objectives were met and the small cell design alternative was demonstrated and selected to be a feasible drop in replacement for the MPCV Orion CM Battery for EM2 mission.

Generative Models for Similarity-based Classification

DTIC Science & Technology

2007-01-01

NC), local nearest centroid (local NC), k-nearest neighbors ( kNN ), and condensed nearest neighbors (CNN) are all similarity-based classifiers which...vector machine to the k nearest neighbors of the test sample [80]. The SVM- KNN method was developed to address the robustness and dimensionality...concerns that afflict nearest neighbors and SVMs. Similarly to the nearest-means classifier, the SVM- KNN is a hybrid local and global classifier developed

Relationship between neighbor number and vibrational spectra in disordered colloidal clusters with attractive interactions

NASA Astrophysics Data System (ADS)

Yunker, Peter J.; Zhang, Zexin; Gratale, Matthew; Chen, Ke; Yodh, A. G.

2013-03-01

We study connections between vibrational spectra and average nearest neighbor number in disordered clusters of colloidal particles with attractive interactions. Measurements of displacement covariances between particles in each cluster permit calculation of the stiffness matrix, which contains effective spring constants linking pairs of particles. From the cluster stiffness matrix, we derive vibrational properties of corresponding "shadow" glassy clusters, with the same geometric configuration and interactions as the "source" cluster but without damping. Here, we investigate the stiffness matrix to elucidate the origin of the correlations between the median frequency of cluster vibrational modes and average number of nearest neighbors in the cluster. We find that the mean confining stiffness of particles in a cluster, i.e., the ensemble-averaged sum of nearest neighbor spring constants, correlates strongly with average nearest neighbor number, and even more strongly with median frequency. Further, we find that the average oscillation frequency of an individual particle is set by the total stiffness of its nearest neighbor bonds; this average frequency increases as the square root of the nearest neighbor bond stiffness, in a manner similar to the simple harmonic oscillator.