ACTION RECOGNITION USING SALIENT NEIGHBORING HISTOGRAMS

DEFF Research Database (Denmark)

Ren, Huamin; Moeslund, Thomas B.

2013-01-01

Combining spatio-temporal interest points with Bag-of-Words models achieves state-of-the-art performance in action recognition. However, existing methods based on “bag-ofwords” models either are too local to capture the variance in space/time or fail to solve the ambiguity problem in spatial...... and temporal dimensions. Instead, we propose a salient vocabulary construction algorithm to select visual words from a global point of view, and form compact descriptors to represent discriminative histograms in the neighborhoods. Those salient neighboring histograms are then trained to model different actions...

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

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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.

Beyond formal groups: neighboring acts and watershed protection in Appalachia

Directory of Open Access Journals (Sweden)

Heather Lukacs

2016-09-01

Full Text Available This paper explores how watershed organizations in Appalachia have persisted in addressing water quality issues in areas with a history of coal mining. We identified two watershed groups that have taken responsibility for restoring local creeks that were previously highly degraded and sporadically managed. These watershed groups represent cases of self-organized commons governance in resource-rich, economically poor Appalachian communities. We describe the extent and characteristics of links between watershed group volunteers and watershed residents who are not group members. Through surveys, participant observation, and key-informant consultation, we found that neighbors – group members as well as non-group-members – supported the group's function through informal neighboring acts. Past research has shown that local commons governance institutions benefit from being nested in supportive external structures. We found that the persistence and success of community watershed organizations depends on the informal participation of local residents, affirming the necessity of looking beyond formal, organized groups to understand the resources, expertise, and information needed to address complex water pollution at the watershed level. Our findings augment the concept of nestedness in commons governance to include that of a formal organization acting as a neighbor that exchanges informal neighboring acts with local residents. In this way, we extend the concept of neighboring to include interactions between individuals and a group operating in the same geographic area.

Reduction in predator defense in the presence of neighbors in a colonial fish.

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Franziska C Schädelin

Full Text Available 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

Recrafting the neighbor-joining method

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Pedersen Christian NS

2006-01-01

Full Text Available Abstract Background The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Θ(n3 algorithm upon which all existing implementations are based. Results In this paper we present techniques for speeding up the canonical neighbor-joining method. Our algorithms construct the same phylogenetic trees as the canonical neighbor-joining method. The best-case running time of our algorithms are O(n2 but the worst-case remains O(n3. We empirically evaluate the performance of our algoritms on distance matrices obtained from the Pfam collection of alignments. The experiments indicate that the running time of our algorithms evolve as Θ(n2 on the examined instance collection. We also compare the running time with that of the QuickTree tool, a widely used efficient implementation of the canonical neighbor-joining method. Conclusion The experiments show that our algorithms also yield a significant speed-up, already for medium sized instances.

Novel qsar combination forecast model for insect repellent coupling support vector regression and k-nearest-neighbor

International Nuclear Information System (INIS)

Wang, L.F.; Bai, L.Y.

2013-01-01

To improve the precision of quantitative structure-activity relationship (QSAR) modeling for aromatic carboxylic acid derivatives insect repellent, a novel nonlinear combination forecast model was proposed integrating support vector regression (SVR) and K-nearest neighbor (KNN): Firstly, search optimal kernel function and nonlinearly select molecular descriptors by the rule of minimum MSE value using SVR. Secondly, illuminate the effects of all descriptors on biological activity by multi-round enforcement resistance-selection. Thirdly, construct the sub-models with predicted values of different KNN. Then, get the optimal kernel and corresponding retained sub-models through subtle selection. Finally, make prediction with leave-one-out (LOO) method in the basis of reserved sub-models. Compared with previous widely used models, our work shows significant improvement in modeling performance, which demonstrates the superiority of the present combination forecast model. (author)

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

Science.gov (United States)

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.

Model of directed lines for square ice with second-neighbor and third-neighbor interactions

Science.gov (United States)

Kirov, Mikhail V.

2018-02-01

The investigation of the properties of nanoconfined systems is one of the most rapidly developing scientific fields. Recently it has been established that water monolayer between two graphene sheets forms square ice. Because of the energetic disadvantage, in the structure of the square ice there are no longitudinally arranged molecules. The result is that the structure is formed by unidirectional straight-lines of hydrogen bonds only. A simple but accurate discrete model of square ice with second-neighbor and third-neighbor interactions is proposed. According to this model, the ground state includes all configurations which do not contain three neighboring unidirectional chains of hydrogen bonds. Each triplet increases the energy by the same value. This new model differs from an analogous model with long-range interactions where in the ground state all neighboring chains are antiparallel. The new model is suitable for the corresponding system of point electric (and magnetic) dipoles on the square lattice. It allows separately estimating the different contributions to the total binding energy and helps to understand the properties of infinite monolayers and finite nanostructures. Calculations of the binding energy for square ice and for point dipole system are performed using the packages TINKER and LAMMPS.

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

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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.

Raman scattering mediated by neighboring molecules

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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.

Raman scattering mediated by neighboring molecules

Energy Technology Data Exchange (ETDEWEB)

Williams, Mathew D.; Bradshaw, David S.; Andrews, David L., E-mail: david.andrews@physics.org [School of Chemistry, University of East Anglia, Norwich NR4 7TJ (United Kingdom)

2016-05-07

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.

Haldane to Dimer Phase Transition in the Spin-1 Haldane System with Bond-Alternating Nearest-Neighbor and Uniform Next-Nearest-Neighbor Exchange Interactions

OpenAIRE

Takashi, Tonegawa; Makoto, Kaburagi; Takeshi, Nakao; Department of Physics, Faculty of Science, Kobe University; Faculty of Cross-Cultural Studies, Kobe University; Department of Physics, Faculty of Science, Kobe University

1995-01-01

The Haldane to dimer phase transition is studied in the spin-1 Haldane system with bond-alternating nearest-neighbor and uniform next-nearest-neighbor exchange interactions, where both interactions are antiferromagnetic and thus compete with each other. By using a method of exact diagonalization, the ground-state phase diagram on the ratio of the next-nearest-neighbor interaction constant to the nearest-neighbor one versus the bond-alternation parameter of the nearest-neighbor interactions is...

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

Science.gov (United States)

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 EOperon-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.

Estimating forest attribute parameters for small areas using nearest neighbors techniques

Science.gov (United States)

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...

Kinetic Models for Topological Nearest-Neighbor Interactions

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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.

Recrafting the Neighbor-Joining Method

DEFF Research Database (Denmark)

Mailund; Brodal, Gerth Stølting; Fagerberg, Rolf

2006-01-01

Background: The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Θ(n3) algorithm upon which all existing implementations are based. Methods: In this paper we present techniques for speeding...... up the canonical neighbor-joining method. Our algorithms construct the same phylogenetic trees as the canonical neighbor-joining method. The best-case running time of our algorithms are O(n2) but the worst-case remains O(n3). We empirically evaluate the performance of our algoritms on distance...... matrices obtained from the Pfam collection of alignments. Results: The experiments indicate that the running time of our algorithms evolve as Θ(n2) on the examined instance collection. We also compare the running time with that of the QuickTree tool, a widely used efficient implementation of the canonical...

Frog sound identification using extended k-nearest neighbor classifier

Science.gov (United States)

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.

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

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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.

Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms

Directory of Open Access Journals (Sweden)

Shengyun Liang

2015-11-01

Full Text Available The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers participated in functional movement tests, including walking and sit-to-stand (STS. A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN, pseudo nearest neighbor (PNN, local mean pseudo nearest neighbor (LMPNN classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population.

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

Science.gov (United States)

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%.

Mixed random walks with a trap in scale-free networks including nearest-neighbor and next-nearest-neighbor jumps

Science.gov (United States)

Zhang, Zhongzhi; Dong, Yuze; Sheng, Yibin

2015-10-01

Random walks including non-nearest-neighbor jumps appear in many real situations such as the diffusion of adatoms and have found numerous applications including PageRank search algorithm; however, related theoretical results are much less for this dynamical process. In this paper, we present a study of mixed random walks in a family of fractal scale-free networks, where both nearest-neighbor and next-nearest-neighbor jumps are included. We focus on trapping problem in the network family, which is a particular case of random walks with a perfect trap fixed at the central high-degree node. We derive analytical expressions for the average trapping time (ATT), a quantitative indicator measuring the efficiency of the trapping process, by using two different methods, the results of which are consistent with each other. Furthermore, we analytically determine all the eigenvalues and their multiplicities for the fundamental matrix characterizing the dynamical process. Our results show that although next-nearest-neighbor jumps have no effect on the leading scaling of the trapping efficiency, they can strongly affect the prefactor of ATT, providing insight into better understanding of random-walk process in complex systems.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

Science.gov (United States)

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Lectures on the nearest neighbor method

CERN Document Server

Biau, Gérard

2015-01-01

This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).   .

Dimensional testing for reverse k-nearest neighbor search

DEFF Research Database (Denmark)

Casanova, Guillaume; Englmeier, Elias; Houle, Michael E.

2017-01-01

Given a query object q, reverse k-nearest neighbor (RkNN) search aims to locate those objects of the database that have q among their k-nearest neighbors. In this paper, we propose an approximation method for solving RkNN queries, where the pruning operations and termination tests are guided...... by a characterization of the intrinsic dimensionality of the data. The method can accommodate any index structure supporting incremental (forward) nearest-neighbor search for the generation and verification of candidates, while avoiding impractically-high preprocessing costs. We also provide experimental evidence...

Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

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E. Parvinnia

2014-01-01

Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

Supplier selection using different metric functions

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Omosigho S.E.

2015-01-01

Full Text Available Supplier selection is an important component of supply chain management in today’s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution. Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

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

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Christoph eSchmid

2013-08-01

Full Text Available 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 towards 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.

The nearest neighbor and the bayes error rates.

Science.gov (United States)

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.

Electronic transport of molecular nanowires by considering of electron hopping energy between the second neighbors

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H Rabani

2015-07-01

Full Text Available In this paper, we study the electronic conductance of molecular nanowires by considering the electron hopping between the first and second neighbors with the help Green’s function method at the tight-binding approach. We investigate three types of structures including linear uniform and periodic chains as well as poly(p-phenylene molecule which are embedded between two semi-infinite metallic leads. The results show that in the second neighbor approximation, the resonance, anti-resonance and Fano phenomena occur in the conductance spectra of these structures. Moreover, a new gap is observed at edge of the lead energy band wich its width depends on the value of the electron hopping energy between the second neighbors. In the systems including intrinsic gap, this hopping energy shifts the gap in the energy spectra.

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

Science.gov (United States)

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.

Performance modeling of neighbor discovery in proactive routing protocols

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Andres Medina

2011-07-01

Full Text Available It is well known that neighbor discovery is a critical component of proactive routing protocols in wireless ad hoc networks. However there is no formal study on the performance of proposed neighbor discovery mechanisms. This paper provides a detailed model of key performance metrics of neighbor discovery algorithms, such as node degree and the distribution of the distance to symmetric neighbors. The model accounts for the dynamics of neighbor discovery as well as node density, mobility, radio and interference. The paper demonstrates a method for applying these models to the evaluation of global network metrics. In particular, it describes a model of network connectivity. Validation of the models shows that the degree estimate agrees, within 5% error, with simulations for the considered scenarios. The work presented in this paper serves as a basis for the performance evaluation of remaining performance metrics of routing protocols, vital for large scale deployment of ad hoc networks.

Dynamical correlation functions of the S=1/2 nearest-neighbor and Haldane-Shastry Heisenberg antiferromagnetic chains in zero and applied fields

DEFF Research Database (Denmark)

Lefmann, K.; Rischel, C.

1996-01-01

We present a numerical diagonalization study of two one-dimensional S=1/2 antiferromagnetic Heisenberg chains, having nearest-neighbor and Haldane-Shastry (1/r(2)) interactions, respectively. We have obtained the T=0 dynamical correlation function, S-alpha alpha(q,omega), for chains of length N=8......-28. We have studied S-zz(q,omega) for the Heisenberg chain in zero field, and from finite-size scaling we have obtained a limiting behavior that for large omega deviates from the conjecture proposed earlier by Muller ct al. For both chains we describe the behavior of S-zz(q,omega) and S...

A dumbed-down approach to unite Fermilab, its neighbors

CERN Multimedia

Constable, B

2004-01-01

"...Fermilab is reaching out to its suburban neighbors...With the nation on orange alert, Fermilab scientists no longer can sit on the front porch and invite neighbors in for coffee and quasars" (1 page).

Selective functionalization of carbon nanotubes

Science.gov (United States)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H. (Inventor); Smalley, Richard E. (Inventor)

2009-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Marjan Radi

2014-01-01

Full Text Available 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.

Neighbors United for Health

Science.gov (United States)

Westhoff, Wayne W.; Corvin, Jaime; Virella, Irmarie

2009-01-01

Modeled upon the ecclesiastic community group concept of Latin America to unite and strengthen the bond between the Church and neighborhoods, a community-based organization created Vecinos Unidos por la Salud (Neighbors United for Health) to bring health messages into urban Latino neighborhoods. The model is based on five tenants, and incorporates…

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

Science.gov (United States)

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).

Pollinator-mediated interactions in experimental arrays vary with neighbor identity.

Science.gov (United States)

Ha, Melissa K; Ivey, Christopher T

2017-02-01

Local ecological conditions influence the impact of species interactions on evolution and community structure. We investigated whether pollinator-mediated interactions between coflowering plants vary with plant density, coflowering neighbor identity, and flowering season. We conducted a field experiment in which flowering time and floral neighborhood were manipulated in a factorial design. Early- and late-flowering Clarkia unguiculata plants were placed into arrays with C. biloba neighbors, noncongeneric neighbors, additional conspecific plants, or no additional plants as a density control. We compared whole-plant pollen limitation of seed set, pollinator behavior, and pollen deposition among treatments. Interactions mediated by shared pollinators depended on the identity of the neighbor and possibly changed through time, although flowering-season comparisons were compromised by low early-season plant survival. Interactions with conspecific neighbors were likely competitive late in the season. Interactions with C. biloba appeared to involve facilitation or neutral interactions. Interactions with noncongeners were more consistently competitive. The community composition of pollinators varied among treatment combinations. Pollinator-mediated interactions involved competition and likely facilitation, depending on coflowering neighbor. Experimental manipulation helped to reveal context-dependent variation in indirect biotic interactions. © 2017 Botanical Society of America.

The clinic as a good corporate neighbor.

Science.gov (United States)

Sass, Hans-Martin

2013-02-01

Clinics today specialize in health repair services similar to car repair shops; procedures and prices are standardized, regulated, and inflexibly uniform. Clinics of the future have to become Health Care Centers in order to be more respected and more effective corporate neighbors in offering outreach services in health education and preventive health care. The traditional concept of care for health is much broader than repair management and includes the promotion of lay health competence and responsibility in healthy social and natural environments. The corporate profile and ethics of the clinic as a good and competitive local neighbor will have to focus on [a] better personalized care, [b] education and services in preventive care, [c] direct or web-based information and advice for general, seasonal, or age related health risks, and on developing and improving trustworthy character traits of the clinic as a corporate person and a good neighbor.

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

Science.gov (United States)

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.

Diagnostic tools for nearest neighbors techniques when used with satellite imagery

Science.gov (United States)

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....

Unwanted Behaviors and Nuisance Behaviors Among Neighbors in a Belgian Community Sample.

Science.gov (United States)

Michaux, Emilie; Groenen, Anne; Uzieblo, Katarzyna

2015-06-30

Unwanted behaviors between (ex-)intimates have been extensively studied, while those behaviors within other contexts such as neighbors have received much less scientific consideration. Research indicates that residents are likely to encounter problem behaviors from their neighbors. Besides the lack of clarity in the conceptualization of problem behaviors among neighbors, little is known on which types of behaviors characterize neighbor problems. In this study, the occurrence of two types of problem behaviors encountered by neighbors was explored within a Belgian community sample: unwanted behaviors such as threats and neighbor nuisance issues such as noise nuisance. By clearly distinguishing those two types of behaviors, this study aimed at contributing to the conceptualization of neighbor problems. Next, the coping strategies used to deal with the neighbor problems were investigated. Our results indicated that unwanted behaviors were more frequently encountered by residents compared with nuisance problems. Four out of 10 respondents reported both unwanted pursuit behavior and nuisance problems. It was especially unlikely to encounter nuisance problems in isolation of unwanted pursuit behaviors. While different coping styles (avoiding the neighbor, confronting the neighbor, and enlisting help from others) were equally used by the stalked participants, none of them was perceived as being more effective in reducing the stalking behaviors. Strikingly, despite being aware of specialized help services such as community mediation services, only a very small subgroup enlisted this kind of professional help. © The Author(s) 2015.

Who's your neighbor? Acoustic cues to individual identity in red squirrel Tamiasciurus hudsonicus rattle calls

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Shannon M. DIGWEED, Drew RENDALL, Teana IMBEAU

2012-10-01

Full Text Available North American red squirrels Tamiasciurus hudsonicus often produce a loud territorial rattle call when conspecifics enter or invade a territory. Previous playback experiments suggest that the territorial rattle call may indicate an invader's identity as squirrels responded more intensely to calls played from strangers than to calls played from neighbors. This dear-enemy effect is well known in a variety of bird and mammal species and functions to reduce aggressive interactions between known neighbors. However, although previous experiments on red squirrels suggest some form of individual differentiation and thus recognition, detailed acoustic analysis of potential acoustic cues in rattle calls have not been conducted. If calls function to aid in conspecific identification in order to mitigate aggressive territorial interactions, we would expect that individual recognition cues would be acoustically represented. Our work provides a detailed analysis of acoustic cues to identity within rattle calls. A total of 225 calls across 32 individual squirrels from Sheep River Provincial Park, Kananaskis, AB, Canada, were analyzed with discriminant function analysis for potential acoustic cues to individual identity. Initial analysis of all individuals revealed a reliable acoustic differentiation across individuals. A more detailed analysis of clusters of neighboring squirrels was performed and results again indicated a statistically significant likelihood that calls were assigned correctly to specific squirrels (55%-75% correctly assigned; in other words squirrels have distinct voices that should allow for individual identification and discrimination by conspecifics [Current Zoology 58 (5: 758–764, 2012].

Neighbor Rupture Degree of Some Middle Graphs

Directory of Open Access Journals (Sweden)

Gökşen BACAK-TURAN

2017-12-01

Full Text Available Networks have an important place in our daily lives. Internet networks, electricity networks, water networks, transportation networks, social networks and biological networks are some of the networks we run into every aspects of our lives. A network consists of centers connected by links. A network is represented when centers and connections modelled by vertices and edges, respectively. In consequence of the failure of some centers or connection lines, measurement of the resistance of the network until the communication interrupted is called vulnerability of the network. In this study, neighbor rupture degree which is a parameter that explores the vulnerability values of the resulting graphs due to the failure of some centers of a communication network and its neighboring centers becoming nonfunctional were applied to some middle graphs and neighbor rupture degree of the $M(C_{n},$ $M(P_{n},$ $M(K_{1,n},$ $M(W_{n},$ $M(P_{n}\\times K_{2}$ and $M(C_{n}\\times K_{2}$ have been found.

Rational Density Functional Selection Using Game Theory.

Science.gov (United States)

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

Secure Nearest Neighbor Query on Crowd-Sensing Data

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Ke Cheng

2016-09-01

Full Text Available Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.

Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas

International Nuclear Information System (INIS)

Hu, Menglong; Wang, Juan; Kong, Lingcong; An, Kang; Bi, Tao; Guo, Baohong; Dong, Enzeng

2015-01-01

Highlights: •A novel fitness evaluation method integrating environmental information is presented. •The introduction of neighbors’ payoff favors the promotion of cooperation in the PDG. •The role of direct neighbors becomes much more prominent. •In the SDG, the cooperative behavior is also improved by this new mechanism. -- Abstract: We propose an improved fitness evaluation method to investigate the evolution of cooperation in the spatial social dilemmas. In our model, a focal player’s fitness is calculated as the linear combination of his own payoff, the average payoffs of direct and indirect neighbors in which two independent selection parameters (α and β) are used to control the proportion of various payoff contribution to the current fitness. Then, the fitness-based strategy update rule is still Fermi-like, and asynchronous update is adopted here. A large plethora of numerical simulations are performed to validate the behaviors of the current model, and the results unambiguously demonstrate that the cooperation level is greatly enhanced by introducing the payoffs from the surrounding players. In particular, the influence of direct neighbors become more evident when compared with indirect neighbors since the correlation between focal players and their direct neighbors is much closer. Current outcomes are significant for us to further illustrate the origin and emergence of cooperation within a wide variety of natural and man-made systems

Co-Expression of Neighboring Genes in the Zebrafish (Danio rerio Genome

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Daryi Wang

2009-08-01

Full Text Available Neighboring genes in the eukaryotic genome have a tendency to express concurrently, and the proximity of two adjacent genes is often considered a possible explanation for their co-expression behavior. However, the actual contribution of the physical distance between two genes to their co-expression behavior has yet to be defined. To further investigate this issue, we studied the co-expression of neighboring genes in zebrafish, which has a compact genome and has experienced a whole genome duplication event. Our analysis shows that the proportion of highly co-expressed neighboring pairs (Pearson’s correlation coefficient R>0.7 is low (0.24% ~ 0.67%; however, it is still significantly higher than that of random pairs. In particular, the statistical result implies that the co-expression tendency of neighboring pairs is negatively correlated with their physical distance. Our findings therefore suggest that physical distance may play an important role in the co-expression of neighboring genes. Possible mechanisms related to the neighboring genes’ co-expression are also discussed.

Introduction to machine learning: k-nearest neighbors.

Science.gov (United States)

Zhang, Zhongheng

2016-06-01

Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The article introduces some basic ideas underlying the kNN algorithm, and then focuses on how to perform kNN modeling with R. The dataset should be prepared before running the knn() function in R. After prediction of outcome with kNN algorithm, the diagnostic performance of the model should be checked. Average accuracy is the mostly widely used statistic to reflect the kNN algorithm. Factors such as k value, distance calculation and choice of appropriate predictors all have significant impact on the model performance.

New Sliding Puzzle with Neighbors Swap Motion

OpenAIRE

Prihardono, Ariyanto; Kawagoe, Kenichi

2015-01-01

The sliding puzzles (15-puzzle, 8-puzzle, 5-puzzle) are known to have 2 kind of puz-zle: solvable puzzle and unsolvable puzzle. In this thesis, we make a new puzzle with only 1 kind of it, solvable puzzle. This new puzzle is made by adopting sliding puzzle with several additional rules from M13 puzzle; the puzzle that is formed form The Mathieu group M13. This puzzle has a movement that called a neighbors swap motion, a rule of movement that enables every neighboring points to swap. This extr...

The role of orthography in the semantic activation of neighbors.

Science.gov (United States)

Hino, Yasushi; Lupker, Stephen J; Taylor, Tamsen E

2012-09-01

There is now considerable evidence that a letter string can activate semantic information appropriate to its orthographic neighbors (e.g., Forster & Hector's, 2002, TURPLE effect). This phenomenon is the focus of the present research. Using Japanese words, we examined whether semantic activation of neighbors is driven directly by orthographic similarity alone or whether there is also a role for phonological similarity. In Experiment 1, using a relatedness judgment task in which a Kanji word-Katakana word pair was presented on each trial, an inhibitory effect was observed when the initial Kanji word was related to an orthographic and phonological neighbor of the Katakana word target but not when the initial Kanji word was related to a phonological but not orthographic neighbor of the Katakana word target. This result suggests that phonology plays little, if any, role in the activation of neighbors' semantics when reading familiar words. In Experiment 2, the targets were transcribed into Hiragana, a script they are typically not written in, requiring readers to engage in phonological coding. In that experiment, inhibitory effects were observed in both conditions. This result indicates that phonologically mediated semantic activation of neighbors will emerge when phonological processing is necessary in order to understand a written word (e.g., when that word is transcribed into an unfamiliar script). PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

Science.gov (United States)

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 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.

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

Directory of Open Access Journals (Sweden)

Nisrine Jrad

2009-01-01

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.

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.

Directory of Open Access Journals (Sweden)

Brett A McKinney

Full Text Available 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

Color and neighbor edge directional difference feature for image retrieval

Institute of Scientific and Technical Information of China (English)

Chaobing Huang; Shengsheng Yu; Jingli Zhou; Hongwei Lu

2005-01-01

@@ A novel image feature termed neighbor edge directional difference unit histogram is proposed, in which the neighbor edge directional difference unit is defined and computed for every pixel in the image, and is used to generate the neighbor edge directional difference unit histogram. This histogram and color histogram are used as feature indexes to retrieve color image. The feature is invariant to image scaling and translation and has more powerful descriptive for the natural color images. Experimental results show that the feature can achieve better retrieval performance than other color-spatial features.

Neighboring Genes Show Correlated Evolution in Gene Expression

Science.gov (United States)

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

Science.gov (United States)

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

The Islands Approach to Nearest Neighbor Querying in Spatial Networks

DEFF Research Database (Denmark)

Huang, Xuegang; Jensen, Christian Søndergaard; Saltenis, Simonas

2005-01-01

, and versatile approach to k nearest neighbor computation that obviates the need for using several k nearest neighbor approaches for supporting a single service scenario. The experimental comparison with the existing techniques uses real-world road network data and considers both I/O and CPU performance...

Handling Neighbor Discovery and Rendezvous Consistency with Weighted Quorum-Based Approach.

Science.gov (United States)

Own, Chung-Ming; Meng, Zhaopeng; Liu, Kehan

2015-09-03

Neighbor discovery and the power of sensors play an important role in the formation of Wireless Sensor Networks (WSNs) and mobile networks. Many asynchronous protocols based on wake-up time scheduling have been proposed to enable neighbor discovery among neighboring nodes for the energy saving, especially in the difficulty of clock synchronization. However, existing researches are divided two parts with the neighbor-discovery methods, one is the quorum-based protocols and the other is co-primality based protocols. Their distinction is on the arrangements of time slots, the former uses the quorums in the matrix, the latter adopts the numerical analysis. In our study, we propose the weighted heuristic quorum system (WQS), which is based on the quorum algorithm to eliminate redundant paths of active slots. We demonstrate the specification of our system: fewer active slots are required, the referring rate is balanced, and remaining power is considered particularly when a device maintains rendezvous with discovered neighbors. The evaluation results showed that our proposed method can effectively reschedule the active slots and save the computing time of the network system.

Handling Neighbor Discovery and Rendezvous Consistency with Weighted Quorum-Based Approach

Directory of Open Access Journals (Sweden)

Chung-Ming Own

2015-09-01

Full Text Available Neighbor discovery and the power of sensors play an important role in the formation of Wireless Sensor Networks (WSNs and mobile networks. Many asynchronous protocols based on wake-up time scheduling have been proposed to enable neighbor discovery among neighboring nodes for the energy saving, especially in the difficulty of clock synchronization. However, existing researches are divided two parts with the neighbor-discovery methods, one is the quorum-based protocols and the other is co-primality based protocols. Their distinction is on the arrangements of time slots, the former uses the quorums in the matrix, the latter adopts the numerical analysis. In our study, we propose the weighted heuristic quorum system (WQS, which is based on the quorum algorithm to eliminate redundant paths of active slots. We demonstrate the specification of our system: fewer active slots are required, the referring rate is balanced, and remaining power is considered particularly when a device maintains rendezvous with discovered neighbors. The evaluation results showed that our proposed method can effectively reschedule the active slots and save the computing time of the network system.

Accelerating distributed average consensus by exploring the information of second-order neighbors

Energy Technology Data Exchange (ETDEWEB)

Yuan Deming [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Xu Shengyuan, E-mail: syxu02@yahoo.com.c [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Zhao Huanyu [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)

2010-05-17

The problem of accelerating distributed average consensus by using the information of second-order neighbors in both the discrete- and continuous-time cases is addressed in this Letter. In both two cases, when the information of second-order neighbors is used in each iteration, the network will converge with a speed faster than the algorithm only using the information of first-order neighbors. Moreover, the problem of using partial information of second-order neighbors is considered, and the edges are not chosen randomly from second-order neighbors. In the continuous-time case, the edges are chosen by solving a convex optimization problem which is formed by using the convex relaxation method. In the discrete-time case, for small network the edges are chosen optimally via the brute force method. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed algorithm.

On Competitiveness of Nearest-Neighbor-Based Music Classification: A Methodological Critique

DEFF Research Database (Denmark)

Pálmason, Haukur; Jónsson, Björn Thór; Amsaleg, Laurent

2017-01-01

The traditional role of nearest-neighbor classification in music classification research is that of a straw man opponent for the learning approach of the hour. Recent work in high-dimensional indexing has shown that approximate nearest-neighbor algorithms are extremely scalable, yielding results...... of reasonable quality from billions of high-dimensional features. With such efficient large-scale classifiers, the traditional music classification methodology of aggregating and compressing the audio features is incorrect; instead the approximate nearest-neighbor classifier should be given an extensive data...... collection to work with. We present a case study, using a well-known MIR classification benchmark with well-known music features, which shows that a simple nearest-neighbor classifier performs very competitively when given ample data. In this position paper, we therefore argue that nearest...

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

Energy Technology Data Exchange (ETDEWEB)

Qian, Wen-Jian [National Cancer Inst., Frederick, MD (United States); Park, Jung-Eun [National Cancer Inst., Bethesda, MD (United States); Grant, Robert [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Lai, Christopher C. [National Cancer Inst., Frederick, MD (United States); Kelley, James A. [National Cancer Inst., Frederick, MD (United States); Yaffe, Michael B. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Lee, Kyung S. [National Cancer Inst., Bethesda, MD (United States); Burke, Terrence R. [National Cancer Inst., Frederick, MD (United States)

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.

Neighboring Optimal Aircraft Guidance in a General Wind Environment

Science.gov (United States)

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.

Plant neighbor identity influences plant biochemistry and physiology related to defense.

Science.gov (United States)

Broz, Amanda K; Broeckling, Corey D; De-la-Peña, Clelia; Lewis, Matthew R; Greene, Erick; Callaway, Ragan M; Sumner, Lloyd W; Vivanco, Jorge M

2010-06-17

Chemical and biological processes dictate an individual organism's ability to recognize and respond to other organisms. A small but growing body of evidence suggests that plants may be capable of recognizing and responding to neighboring plants in a species specific fashion. Here we tested whether or not individuals of the invasive exotic weed, Centaurea maculosa, would modulate their defensive strategy in response to different plant neighbors. In the greenhouse, C. maculosa individuals were paired with either conspecific (C. maculosa) or heterospecific (Festuca idahoensis) plant neighbors and elicited with the plant defense signaling molecule methyl jasmonate to mimic insect herbivory. We found that elicited C. maculosa plants grown with conspecific neighbors exhibited increased levels of total phenolics, whereas those grown with heterospecific neighbors allocated more resources towards growth. To further investigate these results in the field, we conducted a metabolomics analysis to explore chemical differences between individuals of C. maculosa growing in naturally occurring conspecific and heterospecific field stands. Similar to the greenhouse results, C. maculosa individuals accumulated higher levels of defense-related secondary metabolites and lower levels of primary metabolites when growing in conspecific versus heterospecific field stands. Leaf herbivory was similar in both stand types; however, a separate field study positively correlated specialist herbivore load with higher densities of C. maculosa conspecifics. Our results suggest that an individual C. maculosa plant can change its defensive strategy based on the identity of its plant neighbors. This is likely to have important consequences for individual and community success.

Dimensionality reduction with unsupervised nearest neighbors

CERN Document Server

Kramer, Oliver

2013-01-01

This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustr...

Does a pear growl? Interference from semantic properties of orthographic neighbors.

Science.gov (United States)

Pecher, Diane; de Rooij, Jimmy; Zeelenberg, René

2009-07-01

In this study, we investigated whether semantic properties of a word's orthographic neighbors are activated during visual word recognition. In two experiments, words were presented with a property that was not true for the word itself. We manipulated whether the property was true for an orthographic neighbor of the word. Our results showed that rejection of the property was slower and less accurate when the property was true for a neighbor than when the property was not true for a neighbor. These findings indicate that semantic information is activated before orthographic processing is finished. The present results are problematic for the links model (Forster, 2006; Forster & Hector, 2002) that was recently proposed in order to bring form-first models of visual word recognition into line with previously reported findings (Forster & Hector, 2002; Pecher, Zeelenberg, & Wagenmakers, 2005; Rodd, 2004).

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

Science.gov (United States)

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.

Fluorination of some highly functionalized cycloalkanes: chemoselectivity and substrate dependence.

Science.gov (United States)

Remete, Attila Márió; Nonn, Melinda; Fustero, Santos; Haukka, Matti; Fülöp, Ferenc; Kiss, Loránd

2017-01-01

A study exploring the chemical behavior of some dihydroxylated β-amino ester stereo- and regioisomers, derived from unsaturated cyclic β-amino acids is described. The nucleophilic fluorinations involving hydroxy-fluorine exchange of some highly functionalized alicyclic diol derivatives have been carried out in view of selective fluorination, investigating substrate dependence, neighboring group assistance and chemodifferentiation.

Optimal Bandwidth Selection for Kernel Density Functionals Estimation

Directory of Open Access Journals (Sweden)

Su Chen

2015-01-01

Full Text Available The choice of bandwidth is crucial to the kernel density estimation (KDE and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade. It has been known that scale and location parameters are proportional to density functionals ∫γ(xf2(xdx with appropriate choice of γ(x and furthermore equality of scale and location tests can be transformed to comparisons of the density functionals among populations. ∫γ(xf2(xdx can be estimated nonparametrically via kernel density functionals estimation (KDFE. However, the optimal bandwidth selection for KDFE of ∫γ(xf2(xdx has not been examined. We propose a method to select the optimal bandwidth for the KDFE. The idea underlying this method is to search for the optimal bandwidth by minimizing the mean square error (MSE of the KDFE. Two main practical bandwidth selection techniques for the KDFE of ∫γ(xf2(xdx are provided: Normal scale bandwidth selection (namely, “Rule of Thumb” and direct plug-in bandwidth selection. Simulation studies display that our proposed bandwidth selection methods are superior to existing density estimation bandwidth selection methods in estimating density functionals.

Detect thy neighbor: Identity recognition at the root level in plants

NARCIS (Netherlands)

Chen, B.J.W.; During, H.J.; Anten, N.P.R.

2012-01-01

Some plant species increase root allocation at the expense of reproduction in the presence of non-self and non-kin neighbors, indicating the capacity of neighbor-identityrecognition at the rootlevel. Yet in spite of the potential consequences of rootidentityrecognition for the relationship between

When natural selection gives gene function the cold shoulder.

Science.gov (United States)

Cutter, Asher D; Jovelin, Richard

2015-11-01

It is tempting to invoke organismal selection as perpetually optimizing the function of any given gene. However, natural selection can drive genic functional change without improvement of biochemical activity, even to the extinction of gene activity. Detrimental mutations can creep in owing to linkage with other selectively favored loci. Selection can promote functional degradation, irrespective of genetic drift, when adaptation occurs by loss of gene function. Even stabilizing selection on a trait can lead to divergence of the underlying molecular constituents. Selfish genetic elements can also proliferate independent of any functional benefits to the host genome. Here we review the logic and evidence for these diverse processes acting in genome evolution. This collection of distinct evolutionary phenomena - while operating through easily understandable mechanisms - all contribute to the seemingly counterintuitive notion that maintenance or improvement of a gene's biochemical function sometimes do not determine its evolutionary fate. © 2015 WILEY Periodicals, Inc.

Plant neighbor identity influences plant biochemistry and physiology related to defense

Directory of Open Access Journals (Sweden)

Callaway Ragan M

2010-06-01

Full Text Available Abstract Background Chemical and biological processes dictate an individual organism's ability to recognize and respond to other organisms. A small but growing body of evidence suggests that plants may be capable of recognizing and responding to neighboring plants in a species specific fashion. Here we tested whether or not individuals of the invasive exotic weed, Centaurea maculosa, would modulate their defensive strategy in response to different plant neighbors. Results In the greenhouse, C. maculosa individuals were paired with either conspecific (C. maculosa or heterospecific (Festuca idahoensis plant neighbors and elicited with the plant defense signaling molecule methyl jasmonate to mimic insect herbivory. We found that elicited C. maculosa plants grown with conspecific neighbors exhibited increased levels of total phenolics, whereas those grown with heterospecific neighbors allocated more resources towards growth. To further investigate these results in the field, we conducted a metabolomics analysis to explore chemical differences between individuals of C. maculosa growing in naturally occurring conspecific and heterospecific field stands. Similar to the greenhouse results, C. maculosa individuals accumulated higher levels of defense-related secondary metabolites and lower levels of primary metabolites when growing in conspecific versus heterospecific field stands. Leaf herbivory was similar in both stand types; however, a separate field study positively correlated specialist herbivore load with higher densities of C. maculosa conspecifics. Conclusions Our results suggest that an individual C. maculosa plant can change its defensive strategy based on the identity of its plant neighbors. This is likely to have important consequences for individual and community success.

Disentangling neighbors and extended range density oscillations in monatomic amorphous semiconductors.

Science.gov (United States)

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.

A multilevel-skin neighbor list algorithm for molecular dynamics simulation

Science.gov (United States)

Zhang, Chenglong; Zhao, Mingcan; Hou, Chaofeng; Ge, Wei

2018-01-01

Searching of the interaction pairs and organization of the interaction processes are important steps in molecular dynamics (MD) algorithms and are critical to the overall efficiency of the simulation. Neighbor lists are widely used for these steps, where thicker skin can reduce the frequency of list updating but is discounted by more computation in distance check for the particle pairs. In this paper, we propose a new neighbor-list-based algorithm with a precisely designed multilevel skin which can reduce unnecessary computation on inter-particle distances. The performance advantages over traditional methods are then analyzed against the main simulation parameters on Intel CPUs and MICs (many integrated cores), and are clearly demonstrated. The algorithm can be generalized for various discrete simulations using neighbor lists.

Effects of second neighbor interactions on skyrmion lattices in chiral magnets

International Nuclear Information System (INIS)

Oliveira, E A S; Silva, R L; Silva, R C; Pereira, A R

2017-01-01

In this paper we investigate the influences of the second neighbor interactions on a skyrmion lattice in two-dimensional chiral magnets. Such a system contains the exchange and the Dzyaloshinskii–Moriya for the spin interactions and therefore, we analyse three situations: firstly, the second neighbor interaction is present only in the exchange coupling; secondly, it is present only in the Dzyaloshinskii–Moriya coupling. Finally, the second neighbor interactions are present in both exchange and Dzyaloshinskii–Moriya couplings. We show that such effects cause important modifications to the helical and skyrmion phases when an external magnetic field is applied. (paper)

Improving Fraudster Detection in Online Auctions by Using Neighbor-Driven Attributes

Directory of Open Access Journals (Sweden)

Jun-Lin Lin

2015-12-01

Full Text Available Online auction websites use a simple reputation system to help their users to evaluate the trustworthiness of sellers and buyers. However, to improve their reputation in the reputation system, fraudulent users can easily deceive the reputation system by creating fake transactions. This inflated-reputation fraud poses a major problem for online auction websites because it can lead legitimate users into scams. Numerous approaches have been proposed in the literature to address this problem, most of which involve using social network analysis (SNA to derive critical features (e.g., k-core, center weight, and neighbor diversity for distinguishing fraudsters from legitimate users. This paper discusses the limitations of these SNA features and proposes a class of SNA features referred to as neighbor-driven attributes (NDAs. The NDAs of users are calculated from the features of their neighbors. Because fraudsters require collusive neighbors to provide them with positive ratings in the reputation system, using NDAs can be helpful for detecting fraudsters. Although the idea of NDAs is not entirely new, experimental results on a real-world dataset showed that using NDAs improves classification accuracy compared with state-of-the-art methods that use the k-core, center weight, and neighbor diversity.

Fluorination of some highly functionalized cycloalkanes: chemoselectivity and substrate dependence

Directory of Open Access Journals (Sweden)

Attila Márió Remete

2017-11-01

Full Text Available A study exploring the chemical behavior of some dihydroxylated β-amino ester stereo- and regioisomers, derived from unsaturated cyclic β-amino acids is described. The nucleophilic fluorinations involving hydroxy–fluorine exchange of some highly functionalized alicyclic diol derivatives have been carried out in view of selective fluorination, investigating substrate dependence, neighboring group assistance and chemodifferentiation.

The distribution of the number of node neighbors in random hypergraphs

International Nuclear Information System (INIS)

López, Eduardo

2013-01-01

Hypergraphs, the generalization of graphs in which edges become conglomerates of r nodes called hyperedges of rank r ⩾ 2, are excellent models to study systems with interactions that are beyond the pairwise level. For hypergraphs, the node degree ℓ (number of hyperedges connected to a node) and the number of neighbors k of a node differ from each other in contrast to the case of graphs, where counting the number of edges is equivalent to counting the number of neighbors. In this paper, I calculate the distribution of the number of node neighbors in random hypergraphs in which hyperedges of uniform rank r have a homogeneous (equal for all hyperedges) probability p to appear. This distribution is equivalent to the degree distribution of ensembles of graphs created as projections of hypergraph or bipartite network ensembles, where the projection connects any two nodes in the projected graph when they are also connected in the hypergraph or bipartite network. The calculation is non-trivial due to the possibility that neighbor nodes belong simultaneously to multiple hyperedges (node overlaps). From the exact results, the traditional asymptotic approximation to the distribution in the sparse regime (small p) where overlaps are ignored is rederived and improved; the approximation exhibits Poisson-like behavior accompanied by strong fluctuations modulated by power-law decays in the system size N with decay exponents equal to the minimum number of overlapping nodes possible for a given number of neighbors. It is shown that the dense limit cannot be explained if overlaps are ignored, and the correct asymptotic distribution is provided. The neighbor distribution requires the calculation of a new combinatorial coefficient Q r−1 (k, ℓ), which counts the number of distinct labeled hypergraphs of k nodes, ℓ hyperedges of rank r − 1, and where every node is connected to at least one hyperedge. Some identities of Q r−1 (k, ℓ) are derived and applied to the

Selective functionalization of patterned glass surfaces

NARCIS (Netherlands)

Ploetz, E.; Visser, B.; Slingenbergh, W.; Evers, K.; Martinez-Martinez, D.; Pei, Y. T.; Feringa, B. L.; De Hosson, J. Th. M.; Cordes, T.; van Dorp, W. F.

2014-01-01

Tailored writing and specific positioning of molecules on nanostructures is a key step for creating functional materials and nano-optical devices, or interfaces for synthetic machines in various applications. We present a novel approach for the selective functionalization of patterned glass surfaces

Implementation of the k -Neighbors Technique in a recommender algorithm for a purchasing system using NFC and Android

Directory of Open Access Journals (Sweden)

Oscar Arley Riveros

2017-01-01

Full Text Available Introduction: This paper aims to present the design of a mobile application involving NFC technology and a collaborative recommendation algorithm under the K-neighbors technique, allowing to observe personalized suggestions for each client. Objective: Design and develop a mobile application, using NFC technologies and K-Neighbors Technique in a recommendation algorithm, for a Procurement System. Methodology: The process followed for the design and development of the application focuses on: • Review of the state of the art in mobile shopping systems. • State-of-the-art construction in the use of NFC technology and AI techniques for recommending systems focused on K-Neighbors Algorithms • Proposed system design • Parameterization and implementation of the K-Neighbors Technique and integration of NFC Technology • Proposed System Implementation and Testing. Results: Among the results obtained are detailed: • Mobile application that integrates Android, NFC Technologies and a Technique of Algorithm Recommendation • Parameterization of the K-Neighbors Technique, to be used within the recommended algorithm. • Implementation of functional requirements that allow the generation of personalized recommendations for purchase to the user, user ratings Conclusions: The k-neighbors technique in a recommendation algorithm allows the client to provide a series of recommendations with a level of security, since this algorithm performs calculations taking into account multiple parameters and contrasts the results obtained for other users, finding the articles with a Greater degree of similarity with the customer profile. This algorithm starts from a sample of similar, complementary and other unrelated products, applying its respective formulation, we obtain that the recommendation is made only with the complementary products that obtained higher qualification; Making a big difference with most recommending systems on the market, which are limited to

Marbled Murrelets Select Distinctive Nest Trees within Old-Growth Forest Patches

Directory of Open Access Journals (Sweden)

Michael P. Silvergieter

2011-12-01

Full Text Available The coastal old-growth forests of North America's Pacific Coast are renowned both for their commercial and ecological value. This study adds to growing evidence that selective harvesting of the largest trees may have a disproportionate ecological impact. Marbled Murrelets (Brachyramphus marmoratus, a threatened species, nest almost exclusively in these old-growth forests. Detailed knowledge of nesting habitat selection provides guidance for habitat management and conservation. Habitat selection for this species has been studied at a variety of scales using ground and remote methods. However, because Marbled Murrelet nesting activity is limited to a single mossy platform on a single tree, we investigated nest tree selection within old-growth forest patches, using a set of 59 forest patches containing active nests. Nest trees were usually distinctive compared with neighboring trees in the surrounding 25 m radius patch. They averaged 15 to 20% taller than neighboring trees depending on region, had significantly larger stem diameters, more potential nesting platforms, and more moss. They had the most extreme values of height and width about three times as often as expected by chance. An analysis of moss platform use as a function of number of platforms per platform tree suggests that murrelets select individual platforms, rather than platform trees per se. Nonetheless, highly selective logging practices that remove high-value trees from stands may also remove trees most likely to be selected by nesting murrelets.

Incidence and Prevalence of Tuberculosis in Iran and Neighboring Countries

Directory of Open Access Journals (Sweden)

Arezoo Tavakoli

2017-07-01

Full Text Available Background Tuberculosis is one of the major public health concerns in many countries, however the available and effective treatment is known. Tuberculosis typically determined with socio-economic problems such as war, malnutrition and HIV prevalence. In Iran, many progresses are carried to control tuberculosis but, different factors such as immigration from neighboring countries are affective to tuberculosis infection. Objectives In this paper, the incidence and prevalence of tuberculosis is evaluated in different regions of Iran and neighboring countries. Methods The data are collected from different and valid sources such as Scopus, Pubmed and also many reports from world health organization (WHO and center of disease control and prevention (CDC for a period of 25 years (1990 - 2015 evaluated for Iran and neighboring countries. Results This study as a descriptive- analytical research is conducted cross- sectional among Iran and neighboring countries since 1990. The information is obtained from exact and valid informative data from web of sciences. The east and west border countries of Iran which are faced with war and immigration in Afghanistan, Pakistan and Iraq are source of tuberculosis infection that effect on tuberculosis prevalence in Iran. The data were analyzed by SPSS 22 and Excel 2013. Conclusions The incidence of tuberculosis in Iran has been decreased because of many controlling actions such as BCG vaccination, electronic reporting system for tuberculosis and free access to tuberculosis medication. Some of Iran neighboring countries such as Tajikistan and Pakistan have the highest incidence of tuberculosis which known as a challenge for tuberculosis control in Iran while Saudi Arabia and Turkey have the lowest incidence.

Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks.

Science.gov (United States)

Han, Yongkoo; Park, Kisung; Hong, Jihye; Ulamin, Noor; Lee, Young-Koo

2015-07-27

The κ-Nearest Neighbors ( κNN) query is an important spatial query in mobile sensor networks. In this work we extend κNN to include a distance constraint, calling it a l-distant κ-nearest-neighbors (l-κNN) query, which finds the κ sensor nodes nearest to a query point that are also at or greater distance from each other. The query results indicate the objects nearest to the area of interest that are scattered from each other by at least distance l. The l-κNN query can be used in most κNN applications for the case of well distributed query results. To process an l-κNN query, we must discover all sets of κNN sensor nodes and then find all pairs of sensor nodes in each set that are separated by at least a distance l. Given the limited battery and computing power of sensor nodes, this l-κNN query processing is problematically expensive in terms of energy consumption. In this paper, we propose a greedy approach for l-κNN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose all sides are l. By selecting κ sensor nodes from the other subspaces near the query point, we guarantee accurate query results for l-κNN. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the κNN query in terms of energy efficiency, query latency, and accuracy.

Neighbor Detection Induces Organ-Specific Transcriptomes, Revealing Patterns Underlying Hypocotyl-Specific Growth.

Science.gov (United States)

Kohnen, Markus V; Schmid-Siegert, Emanuel; Trevisan, Martine; Petrolati, Laure Allenbach; Sénéchal, Fabien; Müller-Moulé, Patricia; Maloof, Julin; Xenarios, Ioannis; Fankhauser, Christian

2016-12-01

In response to neighbor proximity, plants increase the growth of specific organs (e.g., hypocotyls) to enhance access to sunlight. Shade enhances the activity of Phytochrome Interacting Factors (PIFs) by releasing these bHLH transcription factors from phytochrome B-mediated inhibition. PIFs promote elongation by inducing auxin production in cotyledons. In order to elucidate spatiotemporal aspects of the neighbor proximity response, we separately analyzed gene expression patterns in the major light-sensing organ (cotyledons) and in rapidly elongating hypocotyls of Arabidopsis thaliana PIFs initiate transcriptional reprogramming in both organs within 15 min, comprising regulated expression of several early auxin response genes. This suggests that hypocotyl growth is elicited by both local and distal auxin signals. We show that cotyledon-derived auxin is both necessary and sufficient to initiate hypocotyl growth, but we also provide evidence for the functional importance of the local PIF-induced response. With time, the transcriptional response diverges increasingly between organs. We identify genes whose differential expression may underlie organ-specific elongation. Finally, we uncover a growth promotion gene expression signature shared between different developmentally regulated growth processes and responses to the environment in different organs. © 2016 American Society of Plant Biologists. All rights reserved.

Specific Protein Markers for Stem Cell Cross-Talk with Neighboring Cells in the Environment

OpenAIRE

Park, Kyung Soo; Shin, Seung Won; Choi, Jeong-Woo; Um, Soong Ho

2013-01-01

A stem cell interacts with the neighboring cells in its environment. To maintain a living organism’s metabolism, either cell-cell or cell-environment interactions may be significant. Usually, these cells communicate with each other through biological signaling by interactive behaviors of primary proteins or complementary chemicals. The signaling intermediates offer the stem cell’s functionality on its metabolism. With the rapid advent of omics technologies, various specific markers by which s...

Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors

DEFF Research Database (Denmark)

Pan, Rong; Xu, Guandong; Dolog, Peter

2012-01-01

Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors...... in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result...... demonstrates that our approach could considerably improve the performance of recommendations....

Nearest Neighbor Search in the Metric Space of a Complex Network for Community Detection

Directory of Open Access Journals (Sweden)

Suman Saha

2016-03-01

Full Text Available The objective of this article is to bridge the gap between two important research directions: (1 nearest neighbor search, which is a fundamental computational tool for large data analysis; and (2 complex network analysis, which deals with large real graphs but is generally studied via graph theoretic analysis or spectral analysis. In this article, we have studied the nearest neighbor search problem in a complex network by the development of a suitable notion of nearness. The computation of efficient nearest neighbor search among the nodes of a complex network using the metric tree and locality sensitive hashing (LSH are also studied and experimented. For evaluation of the proposed nearest neighbor search in a complex network, we applied it to a network community detection problem. Experiments are performed to verify the usefulness of nearness measures for the complex networks, the role of metric tree and LSH to compute fast and approximate node nearness and the the efficiency of community detection using nearest neighbor search. We observed that nearest neighbor between network nodes is a very efficient tool to explore better the community structure of the real networks. Several efficient approximation schemes are very useful for large networks, which hardly made any degradation of results, whereas they save lot of computational times, and nearest neighbor based community detection approach is very competitive in terms of efficiency and time.

Working with Family, Friend, and Neighbor Caregivers: Lessons from Four Diverse Communities

Science.gov (United States)

Powell, Douglas R.

2011-01-01

This article is excerpted from "Who's Watching the Babies? Improving the Quality of Family, Friend, and Neighbor Care" by Douglas R. Powell ("ZERO TO THREE," 2008). The article explores questions about program development and implementation strategies for supporting Family, Friend, and Neighbor (FFN) caregivers: How do programs and their host…

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

Science.gov (United States)

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.

The Application of Determining Students’ Graduation Status of STMIK Palangkaraya Using K-Nearest Neighbors Method

Science.gov (United States)

Rusdiana, Lili; Marfuah

2017-12-01

K-Nearest Neighbors method is one of methods used for classification which calculate a value to find out the closest in distance. It is used to group a set of data such as students’ graduation status that are got from the amount of course credits taken by them, the grade point average (AVG), and the mini-thesis grade. The study is conducted to know the results of using K-Nearest Neighbors method on the application of determining students’ graduation status, so it can be analyzed from the method used, the data, and the application constructed. The aim of this study is to find out the application results by using K-Nearest Neighbors concept to determine students’ graduation status using the data of STMIK Palangkaraya students. The development of the software used Extreme Programming, since it was appropriate and precise for this study which was to quickly finish the project. The application was created using Microsoft Office Excel 2007 for the training data and Matlab 7 to implement the application. The result of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5%. It could determine the predicate graduation of 94 data used from the initial data before the processing as many as 136 data which the maximal training data was 50data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study. The results of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5% could determine the predicate graduation which is the maximal training data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study.

Modeling the effect of neighboring grains on twin growth in HCP polycrystals

Science.gov (United States)

Kumar, M. Arul; Beyerlein, I. J.; Lebensohn, R. A.; Tomé, C. N.

2017-09-01

In this paper, we study the dependence of neighboring grain orientation on the local stress state around a deformation twin in a hexagonal close packed (HCP) crystal and its effects on the resistance against twin thickening. We use a recently developed, full-field elasto-visco-plastic formulation based on fast Fourier transforms that account for the twinning shear transformation imposed by the twin lamella. The study is applied to Mg, Zr and Ti, since these HCP metals tend to deform by activation of different types of slip modes. The analysis shows that the local stress along the twin boundary are strongly controlled by the relative orientation of the easiest deformation modes in the neighboring grain with respect to the twin lamella in the parent grain. A geometric expression that captures this parent-neighbor relationship is proposed and incorporated into a larger scale, mean-field visco-plastic self-consistent model to simulate the role of neighboring grain orientation on twin thickening. We demonstrate that the approach improves the prediction of twin area fraction distribution when compared with experimental observations.

The selection function of the RAVE survey

NARCIS (Netherlands)

Wojno, Jennifer; Kordopatis, Georges; Piffl, Tilmann; Binney, James; Steinmetz, Matthias; Matijevič, Gal; Bland-Hawthorn, Joss; Sharma, Sanjib; McMillan, Paul; Watson, Fred; Reid, Warren; Kunder, Andrea; Enke, Harry; Grebel, Eva K.; Seabroke, George; Wyse, Rosemary F. G.; Zwitter, Tomaž; Bienaymé, Olivier; Freeman, Kenneth C.; Gibson, Brad K.; Gilmore, Gerry; Helmi, Amina; Munari, Ulisse; Navarro, Julio F.; Parker, Quentin A.; Siebert, Arnaud

2017-01-01

We characterize the selection function of RAdial Velocity Experiment (RAVE) using 2 Micron All Sky Survey (2MASS) as our underlying population, which we assume represents all stars that could have potentially been observed. We evaluate the completeness fraction as a function of position, magnitude

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

Science.gov (United States)

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.

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

National Research Council Canada - National Science Library

Han, Euihong; Karypis, George; Kumar, Vipin

1999-01-01

.... The authors present a nearest neighbor classification scheme for text categorization in which the importance of discriminating words is learned using mutual information and weight adjustment techniques...

Third nearest neighbor parameterized tight binding model for graphene nano-ribbons

Directory of Open Access Journals (Sweden)

Van-Truong Tran

2017-07-01

Full Text Available The existing tight binding models can very well reproduce the ab initio band structure of a 2D graphene sheet. For graphene nano-ribbons (GNRs, the current sets of tight binding parameters can successfully describe the semi-conducting behavior of all armchair GNRs. However, they are still failing in reproducing accurately the slope of the bands that is directly associated with the group velocity and the effective mass of electrons. In this work, both density functional theory and tight binding calculations were performed and a new set of tight binding parameters up to the third nearest neighbors including overlap terms is introduced. The results obtained with this model offer excellent agreement with the predictions of the density functional theory in most cases of ribbon structures, even in the high-energy region. Moreover, this set can induce electron-hole asymmetry as manifested in results from density functional theory. Relevant outcomes are also achieved for armchair ribbons of various widths as well as for zigzag structures, thus opening a route for multi-scale atomistic simulation of large systems that cannot be considered using density functional theory.

SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

Science.gov (United States)

Shams, Bita; Haratizadeh, Saman

2016-09-01

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

Do alcohol compliance checks decrease underage sales at neighboring establishments?

Science.gov (United States)

Erickson, Darin J; Smolenski, Derek J; Toomey, Traci L; Carlin, Bradley P; Wagenaar, Alexander C

2013-11-01

Underage alcohol compliance checks conducted by law enforcement agencies can reduce the likelihood of illegal alcohol sales at checked alcohol establishments, and theory suggests that an alcohol establishment that is checked may warn nearby establishments that compliance checks are being conducted in the area. In this study, we examined whether the effects of compliance checks diffuse to neighboring establishments. We used data from the Complying with the Minimum Drinking Age trial, which included more than 2,000 compliance checks conducted at more than 900 alcohol establishments. The primary outcome was the sale of alcohol to a pseudo-underage buyer without the need for age identification. A multilevel logistic regression was used to model the effect of a compliance check at each establishment as well as the effect of compliance checks at neighboring establishments within 500 m (stratified into four equal-radius concentric rings), after buyer, license, establishment, and community-level variables were controlled for. We observed a decrease in the likelihood of establishments selling alcohol to underage youth after they had been checked by law enforcement, but these effects quickly decayed over time. Establishments that had a close neighbor (within 125 m) checked in the past 90 days were also less likely to sell alcohol to young-appearing buyers. The spatial effect of compliance checks on other establishments decayed rapidly with increasing distance. Results confirm the hypothesis that the effects of police compliance checks do spill over to neighboring establishments. These findings have implications for the development of an optimal schedule of police compliance checks.

Nearest unlike neighbor (NUN): an aid to decision confidence estimation

Science.gov (United States)

Dasarathy, Belur V.

1995-09-01

The concept of nearest unlike neighbor (NUN), proposed and explored previously in the design of nearest neighbor (NN) based decision systems, is further exploited in this study to develop a measure of confidence in the decisions made by NN-based decision systems. This measure of confidence, on the basis of comparison with a user-defined threshold, may be used to determine the acceptability of the decision provided by the NN-based decision system. The concepts, associated methodology, and some illustrative numerical examples using the now classical Iris data to bring out the ease of implementation and effectiveness of the proposed innovations are presented.

Adaptive behavior of neighboring neurons during adaptation-induced plasticity of orientation tuning in V1

Directory of Open Access Journals (Sweden)

Shumikhina Svetlana

2009-12-01

Full Text Available Abstract Background Sensory neurons display transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation. In adult cat primary visual cortex, orientation-selective neurons shift their preferred orientation after being adapted to a non-preferred orientation. The direction of those shifts, towards (attractive or away (repulsive from the adapter depends mostly on adaptation duration. How the adaptive behavior of a neuron is related to that of its neighbors remains unclear. Results Here we show that in most cases (75%, cells shift their preferred orientation in the same direction as their neighbors. We also found that cells shifting preferred orientation differently from their neighbors (25% display three interesting properties: (i larger variance of absolute shift amplitude, (ii wider tuning bandwidth and (iii larger range of preferred orientations among the cluster of cells. Several response properties of V1 neurons depend on their location within the cortical orientation map. Our results suggest that recording sites with both attractive and repulsive shifts following adaptation may be located in close proximity to iso-orientation domain boundaries or pinwheel centers. Indeed, those regions have a more diverse orientation distribution of local inputs that could account for the three properties above. On the other hand, sites with all cells shifting their preferred orientation in the same direction could be located within iso-orientation domains. Conclusions Our results suggest that the direction and amplitude of orientation preference shifts in V1 depend on location within the orientation map. This anisotropy of adaptation-induced plasticity, comparable to that of the visual cortex itself, could have important implications for our understanding of visual adaptation at the psychophysical level.

Parallel selection on TRPV6 in human populations.

Science.gov (United States)

Hughes, David A; Tang, Kun; Strotmann, Rainer; Schöneberg, Torsten; Prenen, Jean; Nilius, Bernd; Stoneking, Mark

2008-02-27

We identified and examined a candidate gene for local directional selection in Europeans, TRPV6, and conclude that selection has acted on standing genetic variation at this locus, creating parallel soft sweep events in humans. A novel modification of the extended haplotype homozygosity (EHH) test was utilized, which compares EHH for a single allele across populations, to investigate the signature of selection at TRPV6 and neighboring linked loci in published data sets for Europeans, Asians and African-Americans, as well as in newly-obtained sequence data for additional populations. We find that all non-African populations carry a signature of selection on the same haplotype at the TRPV6 locus. The selective footprints, however, are significantly differentiated between non-African populations and estimated to be younger than an ancestral population of non-Africans. The possibility of a single selection event occurring in an ancestral population of non-Africans was tested by simulations and rejected. The putatively-selected TRPV6 haplotype contains three candidate sites for functional differences, namely derived non-synonymous substitutions C157R, M378V and M681T. Potential functional differences between the ancestral and derived TRPV6 proteins were investigated by cloning the ancestral and derived forms, transfecting cell lines, and carrying out electrophysiology experiments via patch clamp analysis. No statistically-significant differences in biophysical channel function were found, although one property of the protein, namely Ca(2+) dependent inactivation, may show functionally relevant differences between the ancestral and derived forms. Although the reason for selection on this locus remains elusive, this is the first demonstration of a widespread parallel selection event acting on standing genetic variation in humans, and highlights the utility of between population EHH statistics.

Parallel selection on TRPV6 in human populations.

Directory of Open Access Journals (Sweden)

David A Hughes

Full Text Available We identified and examined a candidate gene for local directional selection in Europeans, TRPV6, and conclude that selection has acted on standing genetic variation at this locus, creating parallel soft sweep events in humans. A novel modification of the extended haplotype homozygosity (EHH test was utilized, which compares EHH for a single allele across populations, to investigate the signature of selection at TRPV6 and neighboring linked loci in published data sets for Europeans, Asians and African-Americans, as well as in newly-obtained sequence data for additional populations. We find that all non-African populations carry a signature of selection on the same haplotype at the TRPV6 locus. The selective footprints, however, are significantly differentiated between non-African populations and estimated to be younger than an ancestral population of non-Africans. The possibility of a single selection event occurring in an ancestral population of non-Africans was tested by simulations and rejected. The putatively-selected TRPV6 haplotype contains three candidate sites for functional differences, namely derived non-synonymous substitutions C157R, M378V and M681T. Potential functional differences between the ancestral and derived TRPV6 proteins were investigated by cloning the ancestral and derived forms, transfecting cell lines, and carrying out electrophysiology experiments via patch clamp analysis. No statistically-significant differences in biophysical channel function were found, although one property of the protein, namely Ca(2+ dependent inactivation, may show functionally relevant differences between the ancestral and derived forms. Although the reason for selection on this locus remains elusive, this is the first demonstration of a widespread parallel selection event acting on standing genetic variation in humans, and highlights the utility of between population EHH statistics.

[Galaxy/quasar classification based on nearest neighbor method].

Science.gov (United States)

Li, Xiang-Ru; Lu, Yu; Zhou, Jian-Ming; Wang, Yong-Jun

2011-09-01

With the wide application of high-quality CCD in celestial spectrum imagery and the implementation of many large sky survey programs (e. g., Sloan Digital Sky Survey (SDSS), Two-degree-Field Galaxy Redshift Survey (2dF), Spectroscopic Survey Telescope (SST), Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) program and Large Synoptic Survey Telescope (LSST) program, etc.), celestial observational data are coming into the world like torrential rain. Therefore, to utilize them effectively and fully, research on automated processing methods for celestial data is imperative. In the present work, we investigated how to recognizing galaxies and quasars from spectra based on nearest neighbor method. Galaxies and quasars are extragalactic objects, they are far away from earth, and their spectra are usually contaminated by various noise. Therefore, it is a typical problem to recognize these two types of spectra in automatic spectra classification. Furthermore, the utilized method, nearest neighbor, is one of the most typical, classic, mature algorithms in pattern recognition and data mining, and often is used as a benchmark in developing novel algorithm. For applicability in practice, it is shown that the recognition ratio of nearest neighbor method (NN) is comparable to the best results reported in the literature based on more complicated methods, and the superiority of NN is that this method does not need to be trained, which is useful in incremental learning and parallel computation in mass spectral data processing. In conclusion, the results in this work are helpful for studying galaxies and quasars spectra classification.

Prototype Generation Using Multiobjective Particle Swarm Optimization for Nearest Neighbor Classification.

Science.gov (United States)

Hu, Weiwei; Tan, Ying

2016-12-01

The nearest neighbor (NN) classifier suffers from high time complexity when classifying a test instance since the need of searching the whole training set. Prototype generation is a widely used approach to reduce the classification time, which generates a small set of prototypes to classify a test instance instead of using the whole training set. In this paper, particle swarm optimization is applied to prototype generation and two novel methods for improving the classification performance are presented: 1) a fitness function named error rank and 2) the multiobjective (MO) optimization strategy. Error rank is proposed to enhance the generation ability of the NN classifier, which takes the ranks of misclassified instances into consideration when designing the fitness function. The MO optimization strategy pursues the performance on multiple subsets of data simultaneously, in order to keep the classifier from overfitting the training set. Experimental results over 31 UCI data sets and 59 additional data sets show that the proposed algorithm outperforms nearly 30 existing prototype generation algorithms.

Plant Clonal Integration Mediates the Horizontal Redistribution of Soil Resources, Benefiting Neighboring Plants.

Science.gov (United States)

Ye, Xue-Hua; Zhang, Ya-Lin; Liu, Zhi-Lan; Gao, Shu-Qin; Song, Yao-Bin; Liu, Feng-Hong; Dong, Ming

2016-01-01

Resources such as water taken up by plants can be released into soils through hydraulic redistribution and can also be translocated by clonal integration within a plant clonal network. We hypothesized that the resources from one (donor) microsite could be translocated within a clonal network, released into different (recipient) microsites and subsequently used by neighbor plants in the recipient microsite. To test these hypotheses, we conducted two experiments in which connected and disconnected ramet pairs of Potentilla anserina were grown under both homogeneous and heterogeneous water regimes, with seedlings of Artemisia ordosica as neighbors. The isotopes [(15)N] and deuterium were used to trace the translocation of nitrogen and water, respectively, within the clonal network. The water and nitrogen taken up by P. anserina ramets in the donor microsite were translocated into the connected ramets in the recipient microsites. Most notably, portions of the translocated water and nitrogen were released into the recipient microsite and were used by the neighboring A. ordosica, which increased growth of the neighboring A. ordosica significantly. Therefore, our hypotheses were supported, and plant clonal integration mediated the horizontal hydraulic redistribution of resources, thus benefiting neighboring plants. Such a plant clonal integration-mediated resource redistribution in horizontal space may have substantial effects on the interspecific relations and composition of the community and consequently on ecosystem processes.

Adaptive neighbor connection for PRMs: A natural fit for heterogeneous environments and parallelism

KAUST Repository

Ekenna, Chinwe

2013-11-01

Probabilistic Roadmap Methods (PRMs) are widely used motion planning methods that sample robot configurations (nodes) and connect them to form a graph (roadmap) containing feasible trajectories. Many PRM variants propose different strategies for each of the steps and choosing among them is problem dependent. Planning in heterogeneous environments and/or on parallel machines necessitates dividing the problem into regions where these choices have to be made for each one. Hand-selecting the best method for each region becomes infeasible. In particular, there are many ways to select connection candidates, and choosing the appropriate strategy is input dependent. In this paper, we present a general connection framework that adaptively selects a neighbor finding strategy from a candidate set of options. Our framework learns which strategy to use by examining their success rates and costs. It frees the user of the burden of selecting the best strategy and allows the selection to change over time. We perform experiments on rigid bodies of varying geometry and articulated linkages up to 37 degrees of freedom. Our results show that strategy performance is indeed problem/region dependent, and our adaptive method harnesses their strengths. Over all problems studied, our method differs the least from manual selection of the best method, and if one were to manually select a single method across all problems, the performance can be quite poor. Our method is able to adapt to changing sampling density and learns different strategies for each region when the problem is partitioned for parallelism. © 2013 IEEE.

Adaptive neighbor connection for PRMs: A natural fit for heterogeneous environments and parallelism

KAUST Repository

Ekenna, Chinwe; Jacobs, Sam Ade; Thomas, Shawna; Amato, Nancy M.

2013-01-01

Probabilistic Roadmap Methods (PRMs) are widely used motion planning methods that sample robot configurations (nodes) and connect them to form a graph (roadmap) containing feasible trajectories. Many PRM variants propose different strategies for each of the steps and choosing among them is problem dependent. Planning in heterogeneous environments and/or on parallel machines necessitates dividing the problem into regions where these choices have to be made for each one. Hand-selecting the best method for each region becomes infeasible. In particular, there are many ways to select connection candidates, and choosing the appropriate strategy is input dependent. In this paper, we present a general connection framework that adaptively selects a neighbor finding strategy from a candidate set of options. Our framework learns which strategy to use by examining their success rates and costs. It frees the user of the burden of selecting the best strategy and allows the selection to change over time. We perform experiments on rigid bodies of varying geometry and articulated linkages up to 37 degrees of freedom. Our results show that strategy performance is indeed problem/region dependent, and our adaptive method harnesses their strengths. Over all problems studied, our method differs the least from manual selection of the best method, and if one were to manually select a single method across all problems, the performance can be quite poor. Our method is able to adapt to changing sampling density and learns different strategies for each region when the problem is partitioned for parallelism. © 2013 IEEE.

Neighbor Discovery Algorithm in Wireless Local Area Networks Using Multi-beam Directional Antennas

Science.gov (United States)

Wang, Jin; Peng, Wei; Liu, Song

2017-10-01

Neighbor discovery is an important step for Wireless Local Area Networks (WLAN) and the use of multi-beam directional antennas can greatly improve the network performance. However, most neighbor discovery algorithms in WLAN, based on multi-beam directional antennas, can only work effectively in synchronous system but not in asynchro-nous system. And collisions at AP remain a bottleneck for neighbor discovery. In this paper, we propose two asynchrono-us neighbor discovery algorithms: asynchronous hierarchical scanning (AHS) and asynchronous directional scanning (ADS) algorithm. Both of them are based on three-way handshaking mechanism. AHS and ADS reduce collisions at AP to have a good performance in a hierarchical way and directional way respectively. In the end, the performance of the AHS and ADS are tested on OMNeT++. Moreover, it is analyzed that different application scenarios and the factors how to affect the performance of these algorithms. The simulation results show that AHS is suitable for the densely populated scenes around AP while ADS is suitable for that most of the neighborhood nodes are far from AP.

Using K-Nearest Neighbor in Optical Character Recognition

Directory of Open Access Journals (Sweden)

Veronica Ong

2016-03-01

Full Text Available The growth in computer vision technology has aided society with various kinds of tasks. One of these tasks is the ability of recognizing text contained in an image, or usually referred to as Optical Character Recognition (OCR. There are many kinds of algorithms that can be implemented into an OCR. The K-Nearest Neighbor is one such algorithm. This research aims to find out the process behind the OCR mechanism by using K-Nearest Neighbor algorithm; one of the most influential machine learning algorithms. It also aims to find out how precise the algorithm is in an OCR program. To do that, a simple OCR program to classify alphabets of capital letters is made to produce and compare real results. The result of this research yielded a maximum of 76.9% accuracy with 200 training samples per alphabet. A set of reasons are also given as to why the program is able to reach said level of accuracy.

Selective Functionalization of Arbitrary Nanowires

Science.gov (United States)

2006-11-02

3-mercaptopropyl)- trimethoxysilane (MPTMS). The wires were grown electrochemically in anodic aluminum oxide ( AAO ) templates. Selective deposition...In the past, templates composed of polycarbonate track-etched membranes or anodic aluminum oxide materials have been used for the construction of...modifier MPTMS was used to function- alize the AAO template because it can form covalent bonds with silanes and metal oxide surfaces21 and because of

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

Science.gov (United States)

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

Detection of Burkholderia pseudomallei O-antigen serotypes in near-neighbor species

Directory of Open Access Journals (Sweden)

Stone Joshua K

2012-11-01

Full Text Available Abstract Background Burkholderia pseudomallei is the etiological agent of melioidosis and a CDC category B select agent with no available effective vaccine. Previous immunizations in mice have utilized the lipopolysaccharide (LPS as a potential vaccine target because it is known as one of the most important antigenic epitopes in B. pseudomallei. Complicating this strategy are the four different B. pseudomallei LPS O-antigen types: A, B, B2, and rough. Sero-crossreactivity is common among O-antigens of Burkholderia species. Here, we identified the presence of multiple B. pseudomallei O-antigen types and sero-crossreactivity in its near-neighbor species. Results PCR screening of O-antigen biosynthesis genes, phenotypic characterization using SDS-PAGE, and immunoblot analysis showed that majority of B. mallei and B. thailandensis strains contained the typical O-antigen type A. In contrast, most of B. ubonensis and B. thailandensis-like strains expressed the atypical O-antigen types B and B2, respectively. Most B. oklahomensis strains expressed a distinct and non-seroreactive O-antigen type, except strain E0147 which expressed O-antigen type A. O-antigen type B2 was also detected in B. thailandensis 82172, B. ubonensis MSMB108, and Burkholderia sp. MSMB175. Interestingly, B. thailandensis-like MSMB43 contained a novel serotype B positive O-antigen. Conclusions This study expands the number of species which express B. pseudomallei O-antigen types. Further work is required to elucidate the full structures and how closely these are to the B. pseudomallei O-antigens, which will ultimately determine the efficacy of the near-neighbor B serotypes for vaccine development.

Reduction of Conflicts in Mining Development Using "Good Neighbor Agreements"

Science.gov (United States)

Masaitis, A.

2013-05-01

New environmental and social challenges for the mining industry in both developed and developing countries show the obvious need to implement "responsible" mining practices that include improved community involvement. Good Neighbor Agreements (GNA's) are a relatively new mechanism for improving communication and trust between a mining company and the community. The focus of a GNA will be to provide a written and enforceable agreement, negotiated between the concerned public and the respective mining company to respond to concerns from the public, and also provide a mechanism for conflict resolution, when there is mutual benefit to maintain a working relationship. Development of GNA's, a recently evolving process that promotes environmentally sound relationships between mines and the surrounding communities. Modify and apply the resulting GNA formulas to the developing countries and countries with transitional economies. This is particularly important for countries that have poorly functioning regulatory systems that cannot guarantee a healthy and safe environment for the communities. The fundamental questions addressed by this research. 1. This is a three-year research project started in August 2012 at the University of Nevada, Reno (UNR) to develop a Good Neighbor Agreements standards as well as to investigate the details of mine development. 2. Identify spheres of possible cooperation between mining companies, government organizations, and the Non-Governmental Organizations (NGO's). Use this cooperation to develop international standards for the GNA, to promote exchange of environmental information, and exchange of successful environmental, health, and safety practices between mining operations from different countries. Discussion: The Good Neighbor Agreement currently evolving will address the following: 1. Provide an economically viable mechanism for developing a partnership between mining operations and the local communities that will increase mining industry

Enhancing Web Service Selection by User Preferences of Non-Functional Features

OpenAIRE

Badr , Youakim; Abraham , Ajith; Biennier , Frédérique; Grosan , Crina

2008-01-01

International audience; Selection of an appropriate Web service for a particular task has become a difficult challenge due to the increasing number of Web services offering similar functionalities. The functional properties describe what the service can do and the nonfunctional properties depict how the service can do it. Non-functional properties involving qualitative or quantitative features have become essential criteria to enhance the selection process of services making the selection pro...

Methods for selective functionalization and separation of carbon nanotubes

Science.gov (United States)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

2011-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Historical harvests reduce neighboring old-growth basal area across a forest landscape.

Science.gov (United States)

Bell, David M; Spies, Thomas A; Pabst, Robert

2017-07-01

While advances in remote sensing have made stand, landscape, and regional assessments of the direct impacts of disturbance on forests quite common, the edge influence of timber harvesting on the structure of neighboring unharvested forests has not been examined extensively. In this study, we examine the impact of historical timber harvests on basal area patterns of neighboring old-growth forests to assess the magnitude and scale of harvest edge influence in a forest landscape of western Oregon, USA. We used lidar data and forest plot measurements to construct 30-m resolution live tree basal area maps in lower and middle elevation mature and old-growth forests. We assessed how edge influence on total, upper canopy, and lower canopy basal area varied across this forest landscape as a function of harvest characteristics (i.e., harvest size and age) and topographic conditions in the unharvested area. Upper canopy, lower canopy, and total basal area increased with distance from harvest edge and elevation. Forests within 75 m of harvest edges (20% of unharvested forests) had 4% to 6% less live tree basal area compared with forest interiors. An interaction between distance from harvest edge and elevation indicated that elevation altered edge influence in this landscape. We observed a positive edge influence at low elevations (800 m). Surprisingly, we found no or weak effects of harvest age (13-60 yr) and harvest area (0.2-110 ha) on surrounding unharvested forest basal area, implying that edge influence was relatively insensitive to the scale of disturbance and multi-decadal recovery processes. Our study indicates that the edge influence of past clearcutting on the structure of neighboring uncut old-growth forests is widespread and persistent. These indirect and diffuse legacies of historical timber harvests complicate forest management decision-making in old-growth forest landscapes by broadening the traditional view of stand boundaries. Furthermore, the consequences

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

Science.gov (United States)

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.

Near Neighbor Distribution in Sets of Fractal Nature

Czech Academy of Sciences Publication Activity Database

Jiřina, Marcel

2013-01-01

Roč. 5, č. 1 (2013), s. 159-166 ISSN 2150-7988 R&D Projects: GA MŠk(CZ) LG12020 Institutional support: RVO:67985807 Keywords : nearest neighbor * fractal set * multifractal * Erlang distribution Subject RIV: BB - Applied Statistics, Operational Research http://www.mirlabs.org/ijcisim/regular_papers_2013/Paper91.pdf

A Novel Preferential Diffusion Recommendation Algorithm Based on User’s Nearest Neighbors

Directory of Open Access Journals (Sweden)

Fuguo Zhang

2017-01-01

Full Text Available Recommender system is a very efficient way to deal with the problem of information overload for online users. In recent years, network based recommendation algorithms have demonstrated much better performance than the standard collaborative filtering methods. However, most of network based algorithms do not give a high enough weight to the influence of the target user’s nearest neighbors in the resource diffusion process, while a user or an object with high degree will obtain larger influence in the standard mass diffusion algorithm. In this paper, we propose a novel preferential diffusion recommendation algorithm considering the significance of the target user’s nearest neighbors and evaluate it in the three real-world data sets: MovieLens 100k, MovieLens 1M, and Epinions. Experiments results demonstrate that the novel preferential diffusion recommendation algorithm based on user’s nearest neighbors can significantly improve the recommendation accuracy and diversity.

Sequential nearest-neighbor effects on computed {sup 13}C{sup {alpha}} chemical shifts

Energy Technology Data Exchange (ETDEWEB)

Vila, Jorge A. [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States); Serrano, Pedro; Wuethrich, Kurt [The Scripps Research Institute, Department of Molecular Biology (United States); Scheraga, Harold A., E-mail: has5@cornell.ed [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States)

2010-09-15

To evaluate sequential nearest-neighbor effects on quantum-chemical calculations of {sup 13}C{sup {alpha}} chemical shifts, we selected the structure of the nucleic acid binding (NAB) protein from the SARS coronavirus determined by NMR in solution (PDB id 2K87). NAB is a 116-residue {alpha}/{beta} protein, which contains 9 prolines and has 50% of its residues located in loops and turns. Overall, the results presented here show that sizeable nearest-neighbor effects are seen only for residues preceding proline, where Pro introduces an overestimation, on average, of 1.73 ppm in the computed {sup 13}C{sup {alpha}} chemical shifts. A new ensemble of 20 conformers representing the NMR structure of the NAB, which was calculated with an input containing backbone torsion angle constraints derived from the theoretical {sup 13}C{sup {alpha}} chemical shifts as supplementary data to the NOE distance constraints, exhibits very similar topology and comparable agreement with the NOE constraints as the published NMR structure. However, the two structures differ in the patterns of differences between observed and computed {sup 13}C{sup {alpha}} chemical shifts, {Delta}{sub ca,i}, for the individual residues along the sequence. This indicates that the {Delta}{sub ca,i} -values for the NAB protein are primarily a consequence of the limited sampling by the bundles of 20 conformers used, as in common practice, to represent the two NMR structures, rather than of local flaws in the structures.

Neighbor discovery in multi-hop wireless networks: evaluation and dimensioning with interferences considerations

Directory of Open Access Journals (Sweden)

Elyes Ben Hamida

2008-04-01

Full Text Available In this paper, we study the impact of collisions and interferences on a neighbor discovery process in the context of multi-hop wireless networks. We consider three models in which interferences and collisions are handled in very different ways. From an ideal channel where simultaneous transmissions do not interfere, we derive an alternate channel where simultaneous transmissions are considered two-by-two under the form of collisions, to finally reach a more realistic channel where simultaneous transmissions are handled under the form of shot-noise interferences. In these models, we analytically compute the link probability success between two neighbors as well as the expected number of nodes that correctly receive a Hello packet. Using this analysis, we show that if the neighbor discovery process is asymptotically equivalent in the three models, it offers very different behaviors locally in time. In particular, the scalability of the process is not the same depending on the way interferences are handled. Finally, we apply our results to the dimensioning of a Hello protocol parameters. We propose a method to adapt the protocol parameters to meet application constraints on the neighbor discovery process and to minimize the protocol energy consumption.

Forest structure of Mediterranean yew (Taxus baccata L. populations and neighbor effects on juvenile yew performance in the NE Iberian Peninsula

Directory of Open Access Journals (Sweden)

Pere Casals

2015-12-01

Full Text Available Aim of study: In the Mediterranean region, yew (Taxus baccata L. usually grows with other tree species in mixed forests. Yew recruitment and juvenile growth may depend on the structure of the forest and the net balance between competition for soil water and nutrients with neighbors and facilitation that these neighbors exert by protecting the plants from direct sun exposure. This study aims, at a regional scale, to analyze the structure of forests containing yew, and, on an individual level, to analyze the effect of the surrounding vegetation structure on the performance of yew juveniles.Area of study: The structural typologies of yew populations were defined based on field inventories conducted in 55 plots distributed in 14 localities in the North-Eastern (NE Iberian Peninsula, covering a wide range of yew distribution in the area. In a second step, an analysis of neighboring species' effects on juveniles was conducted based on the data from 103 plots centered in yew juveniles in five localities.Main Results: A cluster analysis classified the inventoried stands into four forest structural types: two multi-stratified forests with scattered yew and two yew groves. Multiple regression modeling showed that the δ13C measured in last year's leaves positively relates to the basal area of conifer neighbors, but negatively with the cover of the yew crown by other trees.Research highlights: At a stand-level, the density of recruits and juveniles (625 ± 104 recruits ha-1, 259 ± 55 juveniles ha-1 in mixed forests was found to be higher than that on yew dominant stands (181 ± 88 recruits ha-1 and 57 ± 88 juveniles ha-1. At an individual-level, the water stress (estimated from leaf δ13C of yew juveniles seems alleviated by the crown cover by neighbors while it increases with the basal area of conifers. Yew conservation should focus on selective felling for the reduction of basal area of neighbors surrounding the target tree, but avoid affecting the

Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

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Mu Zhou

2014-01-01

Full Text Available This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs in logarithmic received signal strength (RSS varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future.

Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

Science.gov (United States)

Tian, Zengshan; Xu, Kunjie; Yu, Xiang

2014-01-01

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. PMID:24683349

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

Directory of Open Access Journals (Sweden)

Junhui He

2018-01-01

Full Text Available Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.

Grain price spikes and beggar-thy-neighbor policy responses

DEFF Research Database (Denmark)

Boysen, Ole; Jensen, Hans Grinsted

on the agenda of various international policy fora, including the annual meetings of G20 countries in recent years. For that reason, recent studies have attempted to quantify the extent to which such policy actions contributed to the rise in food prices. A study by Jensen & Anderson (2014) uses the global AGE...... model GTAP and the corresponding database to quantify the global policy actions contributions to the raise in food prices by modeling the changes in distortions to agricultural incentives in the period 2006 to 2008. We link the results from this global model into a national AGE model, highlighting how...... global "Beggar-thy-Neighbor Policy Responses" impacted on poor households in Uganda. More specifically we examine the following research questions: What were the Ugandan economy-wide and poverty impacts of the price spikes? What was the impact of other countries "Beggar-thy-Neighbor Policy Responses...

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-09-20

Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

Herbivores modify selection on plant functional traits in a temperate rainforest understory.

Science.gov (United States)

Salgado-Luarte, Cristian; Gianoli, Ernesto

2012-08-01

There is limited evidence regarding the adaptive value of plant functional traits in contrasting light environments. It has been suggested that changes in these traits in response to light availability can increase herbivore susceptibility. We tested the adaptive value of plant functional traits linked with carbon gain in contrasting light environments and also evaluated whether herbivores can modify selection on these traits in each light environment. In a temperate rainforest, we examined phenotypic selection on functional traits in seedlings of the pioneer tree Aristotelia chilensis growing in sun (canopy gap) and shade (forest understory) and subjected to either natural herbivory or herbivore exclusion. We found differential selection on functional traits depending on light environment. In sun, there was positive directional selection on photosynthetic rate and relative growth rate (RGR), indicating that selection favors competitive ability in a high-resource environment. Seedlings with high specific leaf area (SLA) and intermediate RGR were selected in shade, suggesting that light capture and conservative resource use are favored in the understory. Herbivores reduced the strength of positive directional selection acting on SLA in shade. We provide the first demonstration that natural herbivory rates can change the strength of selection on plant ecophysiological traits, that is, attributes whose main function is resource uptake. Research addressing the evolution of shade tolerance should incorporate the selective role of herbivores.

The Influence of Neighbor Effect and Urbanization Toward Organ Donation in Thailand.

Science.gov (United States)

Wongboonsin, Kua; Jindahra, Pavitra; Teerakapibal, Surat

2018-03-01

Toward population wellness, an extreme scarcity of organ supply is proven to be an enormous hindrance. Preferences toward organ donation are vital to raise the organ donation rate. Notably, the area people live in can address the social influence on individual preference toward organ donation. This article studies the impact of the neighbor effect on organ donation decisions, addressing the social influence of urbanization on preferences. How neighborhood-specific variables, population density, and socioeconomic status drive the neighbor effect is investigated. The pursuit of organ donor traits is to be answered. The study uses organ donation interview survey data and neighborhood-specific data from Thailand to estimate a series of logistic regression models. Individuals residing in urban areas exhibit a greater likelihood to sign the donor card than those in rural areas. The neighborhood socioeconomic status is the key driver. An individual is more willing to be an organ donor when having neighbors with higher socioeconomic statuses. Results also reveal positive influences of males and education on the organ donation rate. This article documents the "neighbor effect" on the organ donation decision via living area type, offering an alternative exposition in raising the organ donation rate. In shifting the society norm toward organ donation consent, policy-makers should acknowledge the benefit of urbanization on organ donation decision derived from resourceful urban areas. Moreover, raising education levels does improve not only citizens' well-being but also their tendency to exhibit an altruistic act toward others.

Spatially Selective Functionalization of Conducting Polymers by "Electroclick" Chemistry

DEFF Research Database (Denmark)

Hansen, Thomas Steen; Daugaard, Anders Egede; Hvilsted, Søren

2009-01-01

Conducting polymer microelectrodes can electrochemically generate the catalyst required for their own functionalization by "click chemistry" with high spatial resolution. Interdigitated microelectrodes prepared from an azide-containing conducting polymer are selectively functionalized in sequence...

K-Nearest Neighbor Intervals Based AP Clustering Algorithm for Large Incomplete Data

Directory of Open Access Journals (Sweden)

Cheng Lu

2015-01-01

Full Text Available The Affinity Propagation (AP algorithm is an effective algorithm for clustering analysis, but it can not be directly applicable to the case of incomplete data. In view of the prevalence of missing data and the uncertainty of missing attributes, we put forward a modified AP clustering algorithm based on K-nearest neighbor intervals (KNNI for incomplete data. Based on an Improved Partial Data Strategy, the proposed algorithm estimates the KNNI representation of missing attributes by using the attribute distribution information of the available data. The similarity function can be changed by dealing with the interval data. Then the improved AP algorithm can be applicable to the case of incomplete data. Experiments on several UCI datasets show that the proposed algorithm achieves impressive clustering results.

The influence of neighbors' family size preference on progression to high parity births in rural Nepal.

Science.gov (United States)

Jennings, Elyse A; Barber, Jennifer S

2013-03-01

Large families can have a negative impact on the health and well-being of women, children, and their communities. Seventy-three percent of the individuals in our rural Nepalese sample report that two children is their ideal number, yet about half of the married women continue childbearing after their second child. Using longitudinal data from the Chitwan Valley Family Study, we explore the influence of women's and neighbors' family size preferences on women's progression to high parity births, comparing this influence across two cohorts. We find that neighbors' family size preferences influence women's fertility, that older cohorts of women are more influenced by their neighbors' preferences than are younger cohorts of women, and that the influence of neighbors' preferences is independent of women's own preferences. © 2013 The Population Council, Inc.

A bayesian hierarchical model for classification with selection of functional predictors.

Science.gov (United States)

Zhu, Hongxiao; Vannucci, Marina; Cox, Dennis D

2010-06-01

In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis-Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.

Anodic selective functionalization of cyclic amine derivatives

OpenAIRE

Onomura, Osamu

2012-01-01

Anodic reactions are desirable methods from the viewpoint of Green Chemistry, since no toxic oxidants are necessary for the oxidation of organic molecules. This review introduces usefulness of anodic oxidation and successive reaction for selective functionalization of cyclic amine derivatives.

Clustered K nearest neighbor algorithm for daily inflow forecasting

NARCIS (Netherlands)

Akbari, M.; Van Overloop, P.J.A.T.M.; Afshar, A.

2010-01-01

Instance based learning (IBL) algorithms are a common choice among data driven algorithms for inflow forecasting. They are based on the similarity principle and prediction is made by the finite number of similar neighbors. In this sense, the similarity of a query instance is estimated according to

Contrasting demographic histories of the neighboring bonobo and chimpanzee

DEFF Research Database (Denmark)

Hvilsom, Christina; Carlsen, Frands; Heller, Rasmus

2014-01-01

of the neighboring bonobo remained constant. The changes in population size are likely linked to changes in habitat area due to climate oscillations during the late Pleistocene. Furthermore, the timing of population expansion for the rainforest-adapted chimpanzee is concurrent with the expansion of the savanna...

Descriptive Topology in Selected Topics of Functional Analysis

CERN Document Server

Kakol, J; Pellicer, Manuel Lopez

2011-01-01

"Descriptive Topology in Selected Topics of Functional Analysis" is a collection of recent developments in the field of descriptive topology, specifically focused on the classes of infinite-dimensional topological vector spaces that appear in functional analysis. Such spaces include Frechet spaces, (LF)-spaces and their duals, and the space of continuous real-valued functions C(X) on a completely regular Hausdorff space X, to name a few. These vector spaces appear in functional analysis in distribution theory, differential equations, complex analysis, and various other analytical set

Air Pollution from Livestock Farms Is Associated with Airway Obstruction in Neighboring Residents.

Science.gov (United States)

Borlée, Floor; Yzermans, C Joris; Aalders, Bernadette; Rooijackers, Jos; Krop, Esmeralda; Maassen, Catharina B M; Schellevis, François; Brunekreef, Bert; Heederik, Dick; Smit, Lidwien A M

2017-11-01

Livestock farm emissions may not only affect respiratory health of farmers but also of neighboring residents. To explore associations between spatial and temporal variation in pollutant emissions from livestock farms and lung function in a general, nonfarming, rural population in the Netherlands. We conducted a cross-sectional study in 2,308 adults (age, 20-72 yr). A pulmonary function test was performed measuring prebronchodilator and post-bronchodilator FEV 1 , FVC, FEV 1 /FVC, and maximum mid-expiratory flow (MMEF). Spatial exposure was assessed as (1) number of farms within 500 m and 1,000 m of the home, (2) distance to the nearest farm, and (3) modeled annual average fine dust emissions from farms within 500 m and 1,000 m of the home address. Temporal exposure was assessed as week-average ambient particulate matter livestock farms within a 1,000-m buffer from the home address and MMEF, which was more pronounced in participants without atopy. No associations were found with other spatial exposure variables. Week-average particulate matter livestock air pollution emissions are associated with lung function deficits in nonfarming residents.

Neighbor-dependent Ramachandran probability distributions of amino acids developed from a hierarchical Dirichlet process model.

Directory of Open Access Journals (Sweden)

Daniel Ting

2010-04-01

Full Text Available Distributions of the backbone dihedral angles of proteins have been studied for over 40 years. While many statistical analyses have been presented, only a handful of probability densities are publicly available for use in structure validation and structure prediction methods. The available distributions differ in a number of important ways, which determine their usefulness for various purposes. These include: 1 input data size and criteria for structure inclusion (resolution, R-factor, etc.; 2 filtering of suspect conformations and outliers using B-factors or other features; 3 secondary structure of input data (e.g., whether helix and sheet are included; whether beta turns are included; 4 the method used for determining probability densities ranging from simple histograms to modern nonparametric density estimation; and 5 whether they include nearest neighbor effects on the distribution of conformations in different regions of the Ramachandran map. In this work, Ramachandran probability distributions are presented for residues in protein loops from a high-resolution data set with filtering based on calculated electron densities. Distributions for all 20 amino acids (with cis and trans proline treated separately have been determined, as well as 420 left-neighbor and 420 right-neighbor dependent distributions. The neighbor-independent and neighbor-dependent probability densities have been accurately estimated using Bayesian nonparametric statistical analysis based on the Dirichlet process. In particular, we used hierarchical Dirichlet process priors, which allow sharing of information between densities for a particular residue type and different neighbor residue types. The resulting distributions are tested in a loop modeling benchmark with the program Rosetta, and are shown to improve protein loop conformation prediction significantly. The distributions are available at http://dunbrack.fccc.edu/hdp.

Identification of influential users by neighbors in online social networks

Science.gov (United States)

Sheikhahmadi, Amir; Nematbakhsh, Mohammad Ali; Zareie, Ahmad

2017-11-01

Identification and ranking of influential users in social networks for the sake of news spreading and advertising has recently become an attractive field of research. Given the large number of users in social networks and also the various relations that exist among them, providing an effective method to identify influential users has been gradually considered as an essential factor. In most of the already-provided methods, those users who are located in an appropriate structural position of the network are regarded as influential users. These methods do not usually pay attention to the interactions among users, and also consider those relations as being binary in nature. This paper, therefore, proposes a new method to identify influential users in a social network by considering those interactions that exist among the users. Since users tend to act within the frame of communities, the network is initially divided into different communities. Then the amount of interaction among users is used as a parameter to set the weight of relations existing within the network. Afterward, by determining the neighbors' role for each user, a two-level method is proposed for both detecting users' influence and also ranking them. Simulation and experimental results on twitter data shows that those users who are selected by the proposed method, comparing to other existing ones, are distributed in a more appropriate distance. Moreover, the proposed method outperforms the other ones in terms of both the influential speed and capacity of the users it selects.

Phase Transition and Critical Values of a Nearest-Neighbor System with Uncountable Local State Space on Cayley Trees

International Nuclear Information System (INIS)

Jahnel, Benedikt; Külske, Christof; Botirov, Golibjon I.

2014-01-01

We consider a ferromagnetic nearest-neighbor model on a Cayley tree of degree k ⩾ 2 with uncountable local state space [0,1] where the energy function depends on a parameter θ ∊[0, 1). We show that for 0 ⩽ θ ⩽ 5 3 k the model has a unique translation-invariant Gibbs measure. If 5 3 k < θ < 1 , there is a phase transition, in particular there are three translation-invariant Gibbs measures

Quality and efficiency in high dimensional Nearest neighbor search

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2009-01-01

Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.

Use of Behavior and Influence Functions for Relay Selection in Cooperative Communications

DEFF Research Database (Denmark)

Craciunescu, Razvan; Mihovska, Albena Dimitrova; Prasad, Ramjee

2015-01-01

This paper uses a novel set of functions to model the relay selection process in a scenario of cooperative wireless communications. We define a utility function that reflects the behavior and influence that a selected relay may have on the quality of the link to be established for the forwarding...... of data. The utility function takes into account also the strategies of other players. To this end, we define a relay selection game and a supporting Nash Equilibrium (NE) algorithm for the choice of a relay during communication. The successful selection of a relay is evaluated by simulations in terms...

Functional mining of transporters using synthetic selections

DEFF Research Database (Denmark)

Genee, Hans Jasper; Bali, Anne Pihl; Petersen, Søren Dalsgård

2016-01-01

transporters, PnuT, which is widely distributed across multiple bacterial phyla. We demonstrate that with modular replacement of the biosensor, we could expand our method to xanthine and identify xanthine permeases from gut and soil metagenomes. Our results demonstrate how synthetic-biology approaches can......-responsive biosensor systems that enable selective growth of cells only if they encode a ligand-specific importer. We developed such a synthetic selection system for thiamine pyrophosphate and mined soil and gut metagenomes for thiamine-uptake functions. We identified several members of a novel class of thiamine...

Symmetric Link Key Management for Secure Neighbor Discovery in a Decentralized Wireless Sensor Network

Science.gov (United States)

2017-09-01

KEY MANAGEMENT FOR SECURE NEIGHBOR DISCOVERY IN A DECENTRALIZED WIRELESS SENSOR NETWORK by Kelvin T. Chew September 2017 Thesis Advisor...and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT...DATE September 2017 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE SYMMETRIC LINK KEY MANAGEMENT FOR SECURE NEIGHBOR

Chaotic synchronization of nearest-neighbor diffusive coupling Hindmarsh-Rose neural networks in noisy environments

International Nuclear Information System (INIS)

Fang Xiaoling; Yu Hongjie; Jiang Zonglai

2009-01-01

The chaotic synchronization of Hindmarsh-Rose neural networks linked by a nonlinear coupling function is discussed. The HR neural networks with nearest-neighbor diffusive coupling form are treated as numerical examples. By the construction of a special nonlinear-coupled term, the chaotic system is coupled symmetrically. For three and four neurons network, a certain region of coupling strength corresponding to full synchronization is given, and the effect of network structure and noise position are analyzed. For five and more neurons network, the full synchronization is very difficult to realize. All the results have been proved by the calculation of the maximum conditional Lyapunov exponent.

ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms

DEFF Research Database (Denmark)

Aumüller, Martin; Bernhardsson, Erik; Faithfull, Alexander

2017-01-01

This paper describes ANN-Benchmarks, a tool for evaluating the performance of in-memory approximate nearest neighbor algorithms. It provides a standard interface for measuring the performance and quality achieved by nearest neighbor algorithms on different standard data sets. It supports several...... visualise these as images, Open image in new window plots, and websites with interactive plots. ANN-Benchmarks aims to provide a constantly updated overview of the current state of the art of k-NN algorithms. In the short term, this overview allows users to choose the correct k-NN algorithm and parameters...... for their similarity search task; in the longer term, algorithm designers will be able to use this overview to test and refine automatic parameter tuning. The paper gives an overview of the system, evaluates the results of the benchmark, and points out directions for future work. Interestingly, very different...

Functional Assessment-Based Intervention for Selective Mutism

Science.gov (United States)

Kern, Lee; Starosta, Kristin M.; Bambara, Linda M.; Cook, Clayton R.; Gresham, Frank R.

2007-01-01

The process of functional assessment has emerged as an essential component for intervention development. Applications across divergent types of problem behavior, however, remain limited. This study evaluated the applicability of this promising approach to students with selective mutism. Two middle school students served as participants. The…

What Will the Neighbors Think? Building Large-Scale Science Projects Around the World

International Nuclear Information System (INIS)

Jones, Craig; Mrotzek, Christian; Toge, Nobu; Sarno, Doug

2007-01-01

Public participation is an essential ingredient for turning the International Linear Collider into a reality. Wherever the proposed particle accelerator is sited in the world, its neighbors -- in any country -- will have something to say about hosting a 35-kilometer-long collider in their backyards. When it comes to building large-scale physics projects, almost every laboratory has a story to tell. Three case studies from Japan, Germany and the US will be presented to examine how community relations are handled in different parts of the world. How do particle physics laboratories interact with their local communities? How do neighbors react to building large-scale projects in each region? How can the lessons learned from past experiences help in building the next big project? These and other questions will be discussed to engage the audience in an active dialogue about how a large-scale project like the ILC can be a good neighbor.

Optimizing Neighbor Discovery for Ad hoc Networks based on the Bluetooth PAN Profile

DEFF Research Database (Denmark)

Kuijpers, Gerben; Nielsen, Thomas Toftegaard; Prasad, Ramjee

2002-01-01

IP layer neighbor discovery mechanisms rely highly on broadcast/multicast capabilities of the underlying link layer. The Bluetooth personal area network (PAN) profile has no native link layer broadcast/multicast capabilities and can only emulate this by repeatedly unicast link layer frames....... This paper introduces a neighbor discovery mechanism that utilizes the resources in the Bluetooth PAN profile more efficient. The performance of the new mechanism is investigated using a IPv6 network simulator and compared with emulated broadcasting. It is shown that the signaling overhead can...

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

Directory of Open Access Journals (Sweden)

Eun-Seok Cho

2017-10-01

Full Text Available Face routing has been adopted in wireless sensor networks (WSNs where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency.

A Markov chain Monte Carlo Expectation Maximization Algorithm for Statistical Analysis of DNA Sequence Evolution with Neighbor-Dependent Substitution Rates

DEFF Research Database (Denmark)

Hobolth, Asger

2008-01-01

The evolution of DNA sequences can be described by discrete state continuous time Markov processes on a phylogenetic tree. We consider neighbor-dependent evolutionary models where the instantaneous rate of substitution at a site depends on the states of the neighboring sites. Neighbor...

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

Science.gov (United States)

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.

75 FR 62412 - Notice of Proposed Information Collection: Comment Request; HUD-Owned Real Estate-Good Neighbor...

Science.gov (United States)

2010-10-08

... DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT [Docket No. FR-5380-N-36] Notice of Proposed Information Collection: Comment Request; HUD- Owned Real Estate-Good Neighbor Next Door Program AGENCY: Office... information: Title of Proposal: HUD-Owned Real Estate-Good Neighbor Next Door Program. OMB Control Number, if...

Selecting the Number of Principal Components in Functional Data

KAUST Repository

Li, Yehua

2013-12-01

Functional principal component analysis (FPCA) has become the most widely used dimension reduction tool for functional data analysis. We consider functional data measured at random, subject-specific time points, contaminated with measurement error, allowing for both sparse and dense functional data, and propose novel information criteria to select the number of principal component in such data. We propose a Bayesian information criterion based on marginal modeling that can consistently select the number of principal components for both sparse and dense functional data. For dense functional data, we also develop an Akaike information criterion based on the expected Kullback-Leibler information under a Gaussian assumption. In connecting with the time series literature, we also consider a class of information criteria proposed for factor analysis of multivariate time series and show that they are still consistent for dense functional data, if a prescribed undersmoothing scheme is undertaken in the FPCA algorithm. We perform intensive simulation studies and show that the proposed information criteria vastly outperform existing methods for this type of data. Surprisingly, our empirical evidence shows that our information criteria proposed for dense functional data also perform well for sparse functional data. An empirical example using colon carcinogenesis data is also provided to illustrate the results. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Local and neighboring patch conditions alter sex-specific movement in banana weevils.

Science.gov (United States)

Carval, Dominique; Perrin, Benjamin; Duyck, Pierre-François; Tixier, Philippe

2015-12-01

Understanding the mechanisms underlying the movements and spread of a species over time and space is a major concern of ecology. Here, we assessed the effects of an individual's sex and the density and sex ratio of conspecifics in the local and neighboring environment on the movement probability of the banana weevil, Cosmopolites sordidus. In a "two patches" experiment, we used radiofrequency identification tags to study the C. sordidus movement response to patch conditions. We showed that local and neighboring densities of conspecifics affect the movement rates of individuals but that the density-dependent effect can be either positive or negative depending on the relative densities of conspecifics in local and neighboring patches. We demonstrated that sex ratio also influences the movement of C. sordidus, that is, the weevil exhibits nonfixed sex-biased movement strategies. Sex-biased movement may be the consequence of intrasexual competition for resources (i.e., oviposition sites) in females and for mates in males. We also detected a high individual variability in the propensity to move. Finally, we discuss the role of demographic stochasticity, sex-biased movement, and individual heterogeneity in movement on the colonization process.

Impact of Training Bolivian Farmers on Integrated Pest Management and Diffusion of Knowledge to Neighboring Farmers.

Science.gov (United States)

Jørs, Erik; Konradsen, Flemming; Huici, Omar; Morant, Rafael C; Volk, Julie; Lander, Flemming

2016-01-01

Teaching farmers integrated pest management (IPM) in farmer field schools (FFS) has led to reduced pesticide use and safer handling. This article evaluates the long-term impact of training farmers on IPM and the diffusion of knowledge from trained farmers to neighboring farmers, a subject of importance to justify training costs and to promote a healthy and sustainable agriculture. Training on IPM of farmers took place from 2002 to 2004 in their villages in La Paz County, Bolivia, whereas dissemination of knowledge from trained farmer to neighboring farmer took place until 2009. To evaluate the impact of the intervention, self-reported knowledge and practice on pesticide handling and IPM among trained farmers (n = 23) and their neighboring farmers (n = 47) were analyzed in a follow-up study and compared in a cross-sectional analysis with a control group of farmers (n = 138) introduced in 2009. Variables were analyzed using χ2 test and analysis of variance (ANOVA). Trained farmers improved and performed significantly better in all tested variables than their neighboring farmers, although the latter also improved their performance from 2002 to 2009. Including a control group showed an increasing trend in all variables, with the control farmers having the poorest performance and trained farmers the best. The same was seen in an aggregated variable where trained farmers had a mean score of 16.55 (95% confidence interval [CI]: 15.45-17.65), neighboring farmers a mean score of 11.97 (95% CI: 10.56-13.38), and control farmers a mean score of 9.18 (95% CI: 8.55-9.80). Controlling for age and living altitude did not change these results. Trained farmers and their neighboring farmers improved and maintained knowledge and practice on IPM and pesticide handling. Diffusion of knowledge from trained farmers might explain the better performance of the neighboring farmers compared with the control farmers. Dissemination of knowledge can contribute to justify the cost and convince

Cryptosporidiosis in Saudi Arabia and neighboring countries

International Nuclear Information System (INIS)

Areeshi, Mohammed Y.; Hart, C.A.; Beeching, N.J.

2007-01-01

Cryptosporidium is a coccidian protozoan parasite of the intestinal tract that causes severe and sometimes fatal watery diarrhea in immunocompromised patients and self-limiting but prolonged diarrheal disease in immunocompetent individuals. It exists naturally in animals and can be zoonotic. Although cryptosporidiosis is a significant cause of diarrheal disease in both developing and developed countries, it is more prevalent in developing countries and in tropical environments. We examined the epidemiology and disease burden of Cryptosporidium in Saudi Arabia and neighboring countries by reviewing 23 published studies of Cryptosporidium and etiology of diarrhea in between 1986 and 2006. The prevalence of Cryptosporidium infection in human's ranged from 1% to 37% with a median of 4%, while in animals it was for different species of animals and geographic locations of the studies. Most cases of cryptosporidiosis occurred among children less than 7 years of age and particularly in the first two years of life. The seasonality of Cryptosporidium varied depending on the geographic locations of the studies but it generally most prevalent in the rainy season. The most commonly identified species was Cryptosporidium parvum while C.hominis was detected only in one study from Kuwait. The cumulative experience from Saudi Arabia and four neighboring countries (Kuwait, Oman, Jordan and Iraq) suggest that Cryptosporidium is an important cause of diarrhea in human and cattle. However, the findings of this review also demonstrate the limitations of the available data regarding Cryptosporidium species and strains in circulation in these countries. (author)

Effect of Floquet engineering on the p-wave superconductor with second-neighbor couplings

Science.gov (United States)

Li, X. P.; Li, C. F.; Wang, L. C.; Zhou, L.

2018-06-01

The influence of the Floquet engineering on a particular one-dimensional p-wave superconductor, Kitaev model, with second-neighbor couplings is investigated in this paper. The effective Hamiltonians in the rotated reference frames have been obtained, and the convergent regions of the approximated Hamiltonian as well as the topological phase diagrams have been analyzed and discussed. We show that by modulating the external driving field amplitude, frequency as well as the second-neighbor hopping amplitude, the rich phase diagrams and transitions between different topological phases can be obtained.

Short-lived long non-coding RNAs as surrogate indicators for chemical exposure and LINC00152 and MALAT1 modulate their neighboring genes.

Directory of Open Access Journals (Sweden)

Hidenori Tani

Full Text Available Whole transcriptome analyses have revealed a large number of novel long non-coding RNAs (lncRNAs. Although accumulating evidence demonstrates that lncRNAs play important roles in regulating gene expression, the detailed mechanisms of action of most lncRNAs remain unclear. We previously reported that a novel class of lncRNAs with a short half-life (t1/2 < 4 h in HeLa cells, termed short-lived non-coding transcripts (SLiTs, are closely associated with physiological and pathological functions. In this study, we focused on 26 SLiTs and nuclear-enriched abundant lncRNA, MALAT1(t1/2 of 7.6 h in HeLa cells in neural stem cells (NSCs derived from human induced pluripotent stem cells, and identified four SLiTs (TUG1, GAS5, FAM222-AS1, and SNHG15 that were affected by the following typical chemical stresses (oxidative stress, heavy metal stress and protein synthesis stress. We also found the expression levels of LINC00152 (t1/2 of 2.1 h in NSCs, MALAT1 (t1/2 of 1.8 h in NSCs, and their neighboring genes were elevated proportionally to the chemical doses. Moreover, we confirmed that the overexpression of LINC00152 or MALAT1 upregulated the expressions of their neighboring genes even in the absence of chemical stress. These results reveal that LINC00152 and MALAT1 modulate their neighboring genes, and thus provide a deeper understanding of the functions of lncRNAs.

Phosphate functionalized graphene oxide for selective preconcentration of Pu(IV)

International Nuclear Information System (INIS)

Chappa, Shankararao; Pandey, Ashok K.

2015-01-01

Selective preconcentration of the target ions is a subject of continuous research due to the fact that functional groups are selective to a group of ions/species, and not to a specific ion. Various strategies being explored to make functional group selective to a target ion are based on chemical architecture of functional groups, co-assembly of ligand molecules, synergistic combination of two ligands, formation of size selective cavity, and imprinting using ions as template. Graphene oxide (GO) can be used for removal of radionuclides from aqueous solution having acidity in pH range. As such, GO cannot be used as a sorbent for metal ions from solution having high acidity. GO has epoxy and carboxylic groups that can be used for anchoring functional groups. In the present work, ethylene glycol methacrylate phosphate (EGMP) has been anchored on GO that act as chemical platform. Typically, GO was dispersed in ethanol by sonication for 15 min. In this solution, the EGMP was added and equilibrated for overnight in a shaker at room temp. After equilibrated, GO at the rate EGMP was separated by centrifuge and washed 4-5 times with methanol, EGMP was anchored via C-O-P bonds as confirmed by XPS studies. The sorption studies were carried out using 233 U and 238,239,240 Pu at 3 M HNO 3 using 15 mg of GO at the rate EGMP

Parallel selection on TRPV6 in human populations

OpenAIRE

Hughes, David A; Tang, Kun; Strotmann, Rainer; Schöneberg, Torsten; Prenen, Jean; Nilius, Bernd; Stoneking, Mark

2008-01-01

We identified and examined a candidate gene for local directional selection in Europeans, TRPV6, and conclude that selection has acted on standing genetic variation at this locus, creating parallel soft sweep events in humans. A novel modification of the extended haplotype homozygosity (EHH) test was utilized, which compares EHH for a single allele across populations, to investigate the signature of selection at TRPV6 and neighboring linked loci in published data sets for Europeans, Asians an...

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

Science.gov (United States)

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Social dilemma alleviated by sharing the gains with immediate neighbors

Science.gov (United States)

Wu, Zhi-Xi; Yang, Han-Xin

2014-01-01

We study the evolution of cooperation in the evolutionary spatial prisoner's dilemma game (PDG) and snowdrift game (SG), within which a fraction α of the payoffs of each player gained from direct game interactions is shared equally by the immediate neighbors. The magnitude of the parameter α therefore characterizes the degree of the relatedness among the neighboring players. By means of extensive Monte Carlo simulations as well as an extended mean-field approximation method, we trace the frequency of cooperation in the stationary state. We find that plugging into relatedness can significantly promote the evolution of cooperation in the context of both studied games. Unexpectedly, cooperation can be more readily established in the spatial PDG than that in the spatial SG, given that the degree of relatedness and the cost-to-benefit ratio of mutual cooperation are properly formulated. The relevance of our model with the stakeholder theory is also briefly discussed.

Allotment gardening and health: a comparative survey among allotment gardeners and their neighbors without an allotment.

Science.gov (United States)

van den Berg, Agnes E; van Winsum-Westra, Marijke; de Vries, Sjerp; van Dillen, Sonja M E

2010-11-23

The potential contribution of allotment gardens to a healthy and active life-style is increasingly recognized, especially for elderly populations. However, few studies have empirically examined beneficial effects of allotment gardening. In the present study the health, well-being and physical activity of older and younger allotment gardeners was compared to that of controls without an allotment. A survey was conducted among 121 members of 12 allotment sites in the Netherlands and a control group of 63 respondents without an allotment garden living next to the home addresses of allotment gardeners. The survey included five self-reported health measures (perceived general health, acute health complaints, physical constraints, chronic illnesses, and consultations with GP), four self-reported well-being measures (stress, life satisfaction, loneliness, and social contacts with friends) and one measure assessing self-reported levels of physical activity in summer. Respondents were divided into a younger and older group at the median of 62 years which equals the average retirement age in the Netherlands. After adjusting for income, education level, gender, stressful life events, physical activity in winter, and access to a garden at home as covariates, both younger and older allotment gardeners reported higher levels of physical activity during the summer than neighbors in corresponding age categories. The impacts of allotment gardening on health and well-being were moderated by age. Allotment gardeners of 62 years and older scored significantly or marginally better on all measures of health and well-being than neighbors in the same age category. Health and well-being of younger allotment gardeners did not differ from younger neighbors. The greater health and well-being benefits of allotment gardening for older gardeners may be related to the finding that older allotment gardeners were more oriented towards gardening and being active, and less towards passive relaxation

Multilevel Selection Theory and the Evolutionary Functions of Transposable Elements.

Science.gov (United States)

Brunet, Tyler D P; Doolittle, W Ford

2015-08-06

One of several issues at play in the renewed debate over "junk DNA" is the organizational level at which genomic features might be seen as selected, and thus to exhibit function, as etiologically defined. The intuition frequently expressed by molecular geneticists that junk DNA is functional because it serves to "speed evolution" or as an "evolutionary repository" could be recast as a claim about selection between species (or clades) rather than within them, but this is not often done. Here, we review general arguments for the importance of selection at levels above that of organisms in evolution, and develop them further for a common genomic feature: the carriage of transposable elements (TEs). In many species, not least our own, TEs comprise a large fraction of all nuclear DNA, and whether they individually or collectively contribute to fitness--or are instead junk--is a subject of ongoing contestation. Even if TEs generally owe their origin to selfish selection at the lowest level (that of genomes), their prevalence in extant organisms and the prevalence of extant organisms bearing them must also respond to selection within species (on organismal fitness) and between species (on rates of speciation and extinction). At an even higher level, the persistence of clades may be affected (positively or negatively) by TE carriage. If indeed TEs speed evolution, it is at these higher levels of selection that such a function might best be attributed to them as a class. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Multi-strategy based quantum cost reduction of linear nearest-neighbor quantum circuit

Science.gov (United States)

Tan, Ying-ying; Cheng, Xue-yun; Guan, Zhi-jin; Liu, Yang; Ma, Haiying

2018-03-01

With the development of reversible and quantum computing, study of reversible and quantum circuits has also developed rapidly. Due to physical constraints, most quantum circuits require quantum gates to interact on adjacent quantum bits. However, many existing quantum circuits nearest-neighbor have large quantum cost. Therefore, how to effectively reduce quantum cost is becoming a popular research topic. In this paper, we proposed multiple optimization strategies to reduce the quantum cost of the circuit, that is, we reduce quantum cost from MCT gates decomposition, nearest neighbor and circuit simplification, respectively. The experimental results show that the proposed strategies can effectively reduce the quantum cost, and the maximum optimization rate is 30.61% compared to the corresponding results.

A Markov chain Monte Carlo Expectation Maximization Algorithm for Statistical Analysis of DNA Sequence Evolution with Neighbor-Dependent Substitution Rates

DEFF Research Database (Denmark)

Hobolth, Asger

2008-01-01

-dimensional integrals required in the EM algorithm are estimated using MCMC sampling. The MCMC sampler requires simulation of sample paths from a continuous time Markov process, conditional on the beginning and ending states and the paths of the neighboring sites. An exact path sampling algorithm is developed......The evolution of DNA sequences can be described by discrete state continuous time Markov processes on a phylogenetic tree. We consider neighbor-dependent evolutionary models where the instantaneous rate of substitution at a site depends on the states of the neighboring sites. Neighbor......-dependent substitution models are analytically intractable and must be analyzed using either approximate or simulation-based methods. We describe statistical inference of neighbor-dependent models using a Markov chain Monte Carlo expectation maximization (MCMC-EM) algorithm. In the MCMC-EM algorithm, the high...

Thermodynamic systematics of oxides of americium, curium, and neighboring elements

International Nuclear Information System (INIS)

Morss, L.R.

1984-01-01

Recently-obtained calorimetric data on the sesquioxides and dioxides of americium and curium are summarized. These data are combined with other properties of the actinide elements to elucidate the stability relationships among these oxides and to predict the behavior of neighboring actinide oxides. 45 references, 4 figures, 5 tables

The patient-centered medical home neighbor: A primary care physician's view.

Science.gov (United States)

Sinsky, Christine A

2011-01-04

The American College of Physicians' position paper on the patient-centered medical home neighbor (PCMH-N) extends the work of the patient-centered medical home (PCMH) as a means of improving the delivery of health care. Recognizing that the PCMH does not exist in isolation, the PCMH-N concept outlines expectations for comanagement, communication, and care coordination and broadens responsibility for safe, effective, and efficient care beyond primary care to include physicians of all specialties. As such, it is a fitting follow-up to the PCMH and moves further down the road toward improved care for complex patients. Yet, there is more work to be done. Truly transforming the U.S. health care system around personalized medical homes embedded in highly functional medical neighborhoods will require better staffing models; more robust electronic information tools; aligned incentives for quality and efficiency within payment and regulatory policies; and a culture of greater engagement of patients, their families, and communities.

Sequence correction of random coil chemical shifts: correlation between neighbor correction factors and changes in the Ramachandran distribution

DEFF Research Database (Denmark)

Kjærgaard, Magnus; Poulsen, Flemming Martin

2011-01-01

Random coil chemical shifts are necessary for secondary chemical shift analysis, which is the main NMR method for identification of secondary structure in proteins. One of the largest challenges in the determination of random coil chemical shifts is accounting for the effect of neighboring residues....... The contributions from the neighboring residues are typically removed by using neighbor correction factors determined based on each residue's effect on glycine chemical shifts. Due to its unusual conformational freedom, glycine may be particularly unrepresentative for the remaining residue types. In this study, we...... in the conformational ensemble are an important source of neighbor effects in disordered proteins. Glutamine derived random coil chemical shifts and correction factors modestly improve our ability to predict (13)C chemical shifts of intrinsically disordered proteins compared to existing datasets, and may thus improve...

Sistem Rekomendasi Pada E-Commerce Menggunakan K-Nearest Neighbor

Directory of Open Access Journals (Sweden)

Chandra Saha Dewa Prasetya

2017-09-01

The growing number of product information available on the internet brings challenges to both customer and online businesses in the e-commerce environment. Customer often have difficulty when looking for products on the internet because of the number of products sold on the internet. In addition, online businessman often experience difficulties because they has much data about products, customers and transactions, thus causing online businessman have difficulty to promote the right product to a particular customer target. A recommendation system was developed to address those problem with various methods such as Collaborative Filtering, ContentBased, and Hybrid. Collaborative filtering method uses customer’s rating data, content based using product content such as title or description, and hybrid using both as the basis of the recommendation. In this research, the k-nearest neighbor algorithm is used to determine the top-n product recommendations for each buyer. The result of this research method Content Based outperforms other methods because the sparse data, that is the condition where the number of rating given by the customers is relatively little compared the number of products available in e-commerce. Keywords: recomendation system, k-nearest neighbor, collaborative filtering, content based.

Crimean-Congo hemorrhagic fever in Iran and neighboring countries

DEFF Research Database (Denmark)

Chinikar, S; Ghiasi, Seyed Mojtaba; Hewson, R

2010-01-01

Crimean-Congo hemorrhagic fever (CCHF) is a zoonotic viral disease that is asymptomatic in infected livestock, but a serious threat to humans. Human infections begin with nonspecific febrile symptoms, but progress to a serious hemorrhagic syndrome with a case fatality rate of 2-50%. Although the ...... in Iran and neighboring countries and provide evidence of over 5000 confirmed cases of CCHF in a single period/season....

The surprising power of neighborly advice.

Science.gov (United States)

Gilbert, Daniel T; Killingsworth, Matthew A; Eyre, Rebecca N; Wilson, Timothy D

2009-03-20

Two experiments revealed that (i) people can more accurately predict their affective reactions to a future event when they know how a neighbor in their social network reacted to the event than when they know about the event itself and (ii) people do not believe this. Undergraduates made more accurate predictions about their affective reactions to a 5-minute speed date (n = 25) and to a peer evaluation (n = 88) when they knew only how another undergraduate had reacted to these events than when they had information about the events themselves. Both participants and independent judges mistakenly believed that predictions based on information about the event would be more accurate than predictions based on information about how another person had reacted to it.

The impact of vacant, tax-delinquent, and foreclosed property on sales prices of neighboring homes

OpenAIRE

Stephan Whitaker; Thomas J. Fitzpatrick

2012-01-01

In this empirical analysis, we estimate the impact of vacancy, neglect associated with property-tax delinquency, and foreclosures on the value of neighboring homes using parcel-level observations. Numerous studies have estimated the impact of foreclosures on neighboring properties, and these papers theorize that the foreclosure impact works partially through creating vacant and neglected homes. To our knowledge, this is only the second attempt to estimate the impact of vacancy itself and the ...

An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem

Directory of Open Access Journals (Sweden)

Jing Bian

2016-01-01

Full Text Available In the era of big data, feature selection is an essential process in machine learning. Although the class imbalance problem has recently attracted a great deal of attention, little effort has been undertaken to develop feature selection techniques. In addition, most applications involving feature selection focus on classification accuracy but not cost, although costs are important. To cope with imbalance problems, we developed a cost-sensitive feature selection algorithm that adds the cost-based evaluation function of a filter feature selection using a chaos genetic algorithm, referred to as CSFSG. The evaluation function considers both feature-acquiring costs (test costs and misclassification costs in the field of network security, thereby weakening the influence of many instances from the majority of classes in large-scale datasets. The CSFSG algorithm reduces the total cost of feature selection and trades off both factors. The behavior of the CSFSG algorithm is tested on a large-scale dataset of network security, using two kinds of classifiers: C4.5 and k-nearest neighbor (KNN. The results of the experimental research show that the approach is efficient and able to effectively improve classification accuracy and to decrease classification time. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Resampling nucleotide sequences with closest-neighbor trimming and its comparison to other methods.

Directory of Open Access Journals (Sweden)

Kouki Yonezawa

Full Text Available A large number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore, it is important to study resampling methods to reduce the sampling bias. A novel algorithm-called the closest-neighbor trimming method-that resamples a given number of sequences from a large nucleotide sequence dataset was proposed. The performance of the proposed algorithm was compared with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses. We compared the closest-neighbor trimming method with the naive hierarchical clustering algorithm and [Formula: see text]-medoids clustering algorithm. Genetic information accumulated in public databases contains sampling bias. The closest-neighbor trimming method can thin out densely sampled sequences from a given dataset. Since nucleotide sequences are among the most widely used materials for life sciences, we anticipate that our algorithm to various datasets will result in reducing sampling bias.

A ROBUST CLUSTER HEAD SELECTION BASED ON NEIGHBORHOOD CONTRIBUTION AND AVERAGE MINIMUM POWER FOR MANETs

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S.Balaji

2015-06-01

Full Text Available Mobile Adhoc network is an instantaneous wireless network that is dynamic in nature. It supports single hop and multihop communication. In this infrastructure less network, clustering is a significant model to maintain the topology of the network. The clustering process includes different phases like cluster formation, cluster head selection, cluster maintenance. Choosing cluster head is important as the stability of the network depends on well-organized and resourceful cluster head. When the node has increased number of neighbors it can act as a link between the neighbor nodes which in further reduces the number of hops in multihop communication. Promisingly the node with more number of neighbors should also be available with enough energy to provide stability in the network. Hence these aspects demand the focus. In weight based cluster head selection, closeness and average minimum power required is considered for purging the ineligible nodes. The optimal set of nodes selected after purging will compete to become cluster head. The node with maximum weight selected as cluster head. Mathematical formulation is developed to show the proposed method provides optimum result. It is also suggested that weight factor in calculating the node weight should give precise importance to energy and node stability.

The neighbor enclosed area tracking algorithm and its application to cyclone merger in the midlatitudes

Science.gov (United States)

Inatsu, Masaru; Amada, Shotarou; Satake, Yuya

2010-05-01

The neighbor enclosed area tracking (NEAT) algorithm is proposed as an alternative method to conventional point-to-point cyclone tracking approaches. Most automated Lagrangian tracking algorithms contain three procedures: cyclone identification, cyclone tracking, and quantification of cyclone intensity and activity. The cyclone identification was simply based on a comparison of neighboring grid points; cyclone tracking mainly employed a near-neighbor point search to neighbor-time cyclone-center datasets; and cyclone intensity and activity are mainly quantified as cyclone track density, and other accompanying products such as genesis and lysis densities, mean lifetime, average moving vector, and mean growth rate can also be obtained in the final procedure. But a crucial problem in the above technique is its requirement of some complicated connecting conditions for near-neighbor tracking. To overcome the problem, NEAT completes cyclone identification and cyclone tracking in a single process of equivalent labeling for spatiotemporally connected domains, i.e., if two spatially enclosed areas in a neighboring time frame overlap, they should be connected. NEAT enables us to count the genesis and tracks of individual cyclones as the conventional tracking. Moreover, NEAT has the ability to produce fruitful information on cyclone mergers and separations, cyclone shape, and material transport by individual eddies (the latter two features will be reported elsewhere). There are many possible applications of NEAT to meteorology and oceanography, but now we focus on the situation, well-known by Japanese synopticians, that two cyclones pass respectively over the north and south of Japan and then they frequently merge and are rapidly deepened in the western Pacific. For the case, the southern cyclones tend to be stimulated just above the sea surface temperature front to the north of oceanic western boundary currents, while the northern cyclones, moving eastward along the polar

Stuttering Attitudes among Turkish Family Generations and Neighbors from Representative Samples

Science.gov (United States)

Ozdemir, R. Sertan; St. Louis, Kenneth O.; Topbas, Seyhun

2011-01-01

Purpose: Attitudes toward stuttering, measured by the "Public Opinion Survey of Human Attributes-Stuttering" ("POSHA-S"), are compared among (a) two different representative samples; (b) family generations (children, parents, and either grandparents or uncles and aunts) and neighbors; (c) children, parents, grandparents/adult…

Therapeutic potential of functional selectivity in the treatment of heart failure

DEFF Research Database (Denmark)

Christensen, Gitte Lund; Aplin, Mark; Hansen, Jakob Lerche

2010-01-01

Adrenergic and angiotensin receptors are prominent targets in pharmacological alleviation of cardiac remodeling and heart failure, but their use is associated with cardiodepressant side effects. Recent advances in our understanding of seven transmembrane receptor signaling show that it is possible...... to design ligands with "functional selectivity," acting as agonists on certain signaling pathways while antagonizing others. This represents a major pharmaceutical opportunity to separate desired from adverse effects governed by the same receptor. Accordingly, functionally selective ligands are currently...

The Patient-Centered Medical Home Neighbor: A Critical Concept for a Redesigned Healthcare Delivery System

Science.gov (United States)

2011-01-25

Sharing Knowledge: Achieving Breakthrough Performance 2010 Military Health System Conference The Patient -Centered Medical Home Neighbor: A Critical...DATE 25 JAN 2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE The Patient -Centered Medical Home Neighbor: A...Conference What is the Patient -Centered Medical Home?  …a vision of health care as it should be  …a framework for organizing systems of care at both the

Single cell transcriptomics of neighboring hyphae of Aspergillus niger

Science.gov (United States)

2011-01-01

Single cell profiling was performed to assess differences in RNA accumulation in neighboring hyphae of the fungus Aspergillus niger. A protocol was developed to isolate and amplify RNA from single hyphae or parts thereof. Microarray analysis resulted in a present call for 4 to 7% of the A. niger genes, of which 12% showed heterogeneous RNA levels. These genes belonged to a wide range of gene categories. PMID:21816052

Preimage Selective Trapdoor Function: How to Repair an Easy Problem

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Baocang Wang

2014-01-01

Full Text Available Public key cryptosystems are constructed by embedding a trapdoor into a one-way function. So, the one-wayness and the trapdoorness are vital to public key cryptography. In this paper, we propose a novel public key cryptographic primitive called preimage selective trapdoor function. This scenario allows to use exponentially many preimage to hide a plaintext even if the underlying function is not one-way. The compact knapsack problem is used to construct a probabilistic public key cryptosystem, the underlying encryption function of which is proven to be preimage selective trapdoor one-way functions under some linearization attack models. The constructive method can guarantee the noninjectivity of the underlying encryption function and the unique decipherability for ciphertexts simultaneously. It is heuristically argued that the security of the proposal cannot be compromised by a polynomial-time adversary even if the compact knapsack is easy to solve. We failed to provide any provable security results about the proposal; however, heuristic illustrations show that the proposal is secure against some known attacks including brute force attacks, linearization attacks, and key-recovery attacks. The proposal turns out to have acceptable key sizes and performs efficiently and hence is practical.

Perceptual inequality between two neighboring time intervals defined by sound markers: correspondence between neurophysiological and psychological data

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Takako eMitsudo

2014-09-01

Full Text Available Brain activity related to time estimation processes in humans was analyzed using a perceptual phenomenon called auditory temporal assimilation. In a typical stimulus condition, two neighboring time intervals (T1 and T2 in this order are perceived as equal even when the physical lengths of these time intervals are considerably different. Our previous event-related potential (ERP study demonstrated that a slow negative component (SNCt appears in the right-frontal brain area (around the F8 electrode after T2, which is associated with judgment of the equality/inequality of T1 and T2. In the present study, we conducted two ERP experiments to further confirm the robustness of the SNCt. The stimulus patterns consisted of two neighboring time intervals marked by three successive tone bursts. Thirteen participants only listened to the patterns in the first session, and judged the equality/inequality of T1 and T2 in the next session. Behavioral data showed typical temporal assimilation. The ERP data revealed that three components (N1; contingent negative variation, CNV; and SNCt emerged related to the temporal judgment. The N1 appeared in the central area, and its peak latencies corresponded to the physical timing of each marker onset. The CNV component appeared in the frontal area during T2 presentation, and its amplitude increased as a function of T1. The SNCt appeared in the right-frontal area after the presentation of T1 and T2, and its magnitude was larger for the temporal patterns causing perceptual inequality. The SNCt was also correlated with the perceptual equality/inequality of the same stimulus pattern, and continued up to about 400 ms after the end of T2. These results suggest that the SNCt can be a signature of equality/inequality judgment, which derives from the comparison of the two neighboring time intervals.

Membrane proteins bind lipids selectively to modulate their structure and function.

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Laganowsky, Arthur; Reading, Eamonn; Allison, Timothy M; Ulmschneider, Martin B; Degiacomi, Matteo T; Baldwin, Andrew J; Robinson, Carol V

2014-06-05

Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar experiments identify AmtB as being highly selective for phosphatidylglycerol, prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane

Automatic selection of resting-state networks with functional magnetic resonance imaging

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Silvia Francesca eStorti

2013-05-01

Full Text Available Functional magnetic resonance imaging (fMRI during a resting-state condition can reveal the co-activation of specific brain regions in distributed networks, called resting-state networks, which are selected by independent component analysis (ICA of the fMRI data. One of the major difficulties with component analysis is the automatic selection of the ICA features related to brain activity. In this study we describe a method designed to automatically select networks of potential functional relevance, specifically, those regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. To do this, image analysis was based on probabilistic ICA as implemented in FSL software. After decomposition, the optimal number of components was selected by applying a novel algorithm which takes into account, for each component, Pearson's median coefficient of skewness of the spatial maps generated by FSL, followed by clustering, segmentation, and spectral analysis. To evaluate the performance of the approach, we investigated the resting-state networks in 25 subjects. For each subject, three resting-state scans were obtained with a Siemens Allegra 3 T scanner (NYU data set. Comparison of the visually and the automatically identified neuronal networks showed that the algorithm had high accuracy (first scan: 95%, second scan: 95%, third scan: 93% and precision (90%, 90%, 84%. The reproducibility of the networks for visual and automatic selection was very close: it was highly consistent in each subject for the default-mode network (≥ 92% and the occipital network, which includes the medial visual cortical areas (≥ 94%, and consistent for the attention network (≥ 80%, the right and/or left lateralized frontoparietal attention networks, and the temporal-motor network (≥ 80%. The automatic selection method may be used to detect neural networks and reduce subjectivity in ICA

First-generation Students’ Underperformance at University: The Impact of the Function of Selection

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Mickaël eJury

2015-05-01

Full Text Available According to recent research, university not only has the role to educate and train students, it also has the role to select the best students. We argue that this function of selection disadvantages first-generation students, in comparison with continuing-generation students. Thus, the mere activation of the function of selection should be sufficient to produce achievement differences between first-generation and continuing-generation students in a novel academic task. Furthermore, we propose that when the function of selection is salient, first-generation students would be more vigilant to a cue that may confirm their inferiority, which should explain their underperformance. In the present experiment, participants were asked to complete an arithmetic modular task under two conditions, which either made the function of selection salient or reduced its importance. Participants’ vigilance to a threatening cue (i.e., their performance relative to others was measured through an eye-tracking technique. The results confirmed that first-generation students performed more poorly compared to continuing-generation students only when the function of selection was salient while no differences appeared in the no-selection condition. Regarding vigilance, the results did not confirm our hypothesis; thus, mediation path could not be tested. However, results indicated that at a high level of initial performance, first-generation students looked more often at the threatening cue. In others words, these students seemed more concerned about whether they were performing more poorly than others compared to their continuing-generation counterparts. Some methodological issues are discussed, notably regarding the measure of vigilance.

Effect of electrode design on crosstalk between neighboring organic field-effect transistors based on one single crystal

Science.gov (United States)

Li, Mengjie; Tang, Qingxin; Tong, Yanhong; Zhao, Xiaoli; Zhou, Shujun; Liu, Yichun

2018-03-01

The design of high-integration organic circuits must be such that the interference between neighboring devices is eliminated. Here, rubrene crystals were used to study the effect of the electrode design on crosstalk between neighboring organic field-effect transistors (OFETs). Results show that a decreased source/drain interval and gate electrode width can decrease the diffraction distance of the current, and therefore can weaken the crosstalk. In addition, the inherent low carrier concentration in organic semiconductors can create a high-resistance barrier at the space between gate electrodes of neighboring devices, limiting or even eliminating the crosstalk as a result of the gate electrode width being smaller than the source/drain electrode width.

Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

Science.gov (United States)

Nababan, A. A.; Sitompul, O. S.; Tulus

2018-04-01

K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

Learn good from bad: Effects of good and bad neighbors in spatial prisoners' dilemma games

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Lu, Peng

2015-10-01

Cooperation is vital for the human society and this study focuses on how to promote cooperation. In our stratification model, there exist three classes: two minorities are elites who are prone to cooperate and scoundrels who are born to defect; one majority is the class of common people. Agents of these three classes interact with each other on a square lattice. Commons' cooperation and its factors are investigated. Contradicting our common sense, it indicates that elites play a negative role while scoundrels play a positive one in promoting commons' cooperation. Besides, effects of good and bad neighbors vary with temptation. When the temptation is smaller the positive effect is able to overcome the negative effect, but the later prevails when the temptation is larger. It concludes that common people are more prone to cooperate in harsh environment with bad neighbors, and a better environment with good neighbors merely leads to laziness and free riding of commons.

Cell membrane disruption stimulates cAMP and Ca2+ signaling to potentiate cell membrane resealing in neighboring cells

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Tatsuru Togo

2017-12-01

Full Text Available Disruption of cellular plasma membranes is a common event in many animal tissues, and the membranes are usually rapidly resealed. Moreover, repeated membrane disruptions within a single cell reseal faster than the initial wound in a protein kinase A (PKA- and protein kinase C (PKC-dependent manner. In addition to wounded cells, recent studies have demonstrated that wounding of Madin-Darby canine kidney (MDCK cells potentiates membrane resealing in neighboring cells in the short-term by purinergic signaling, and in the long-term by nitric oxide/protein kinase G signaling. In the present study, real-time imaging showed that cell membrane disruption stimulated cAMP synthesis and Ca2+ mobilization from intracellular stores by purinergic signaling in neighboring MDCK cells. Furthermore, inhibition of PKA and PKC suppressed the ATP-mediated short-term potentiation of membrane resealing in neighboring cells. These results suggest that cell membrane disruption stimulates PKA and PKC via purinergic signaling to potentiate cell membrane resealing in neighboring MDCK cells.

Neuroendocrine prostate cancer (NEPCa) increased the neighboring PCa chemo-resistance via altering the PTHrP/p38/Hsp27/androgen receptor (AR)/p21 signals

Science.gov (United States)

Cui, Yun; Sun, Yin; Hu, Shuai; Luo, Jie; Li, Lei; Li, Xin; Yeh, Shuyuan; Jin, Jie; Chang, Chawnshang

2016-01-01

Prostatic neuroendocrine cells (NE) are an integral part of prostate cancer (PCa) that are associated with PCa progression. As the current androgen-deprivation therapy (ADT) with anti-androgens may promote the neuroendocrine PCa (NEPCa) development, and few therapies can effectively suppress NEPCa, understanding the impact of NEPCa on PCa progression may help us to develop better therapies to battle PCa. Here we found NEPCa cells could increase the docetaxel-resistance of their neighboring PCa cells. Mechanism dissection revealed that through secretion of PTHrP, NEPCa cells could alter the p38/MAPK/Hsp27 signals in their neighboring PCa cells that resulted in increased androgen receptor (AR) activity via promoting AR nuclear translocation. The consequences of increased AR function might then increase docetaxel-resistance via increasing p21 expression. In vivo xenograft mice experiments also confirmed NEPCa could increase the docetaxel-resistance of neighboring PCa, and targeting this newly identified PTHrP/p38/Hsp27/AR/p21 signaling pathway with either p38 inhibitor (SB203580) or sh-PTHrP may result in improving/restoring the docetaxel sensitivity to better suppress PCa. PMID:27375022

Fast Most Similar Neighbor (MSN) classifiers for Mixed Data

OpenAIRE

Hernández Rodríguez, Selene

2010-01-01

The k nearest neighbor (k-NN) classifier has been extensively used in Pattern Recognition because of its simplicity and its good performance. However, in large datasets applications, the exhaustive k-NN classifier becomes impractical. Therefore, many fast k-NN classifiers have been developed; most of them rely on metric properties (usually the triangle inequality) to reduce the number of prototype comparisons. Hence, the existing fast k-NN classifiers are applicable only when the comparison f...

Antiferromagnetic geometric frustration under the influence of the next-nearest-neighbor interaction. An exactly solvable model

Science.gov (United States)

Jurčišinová, E.; Jurčišin, M.

2018-02-01

The influence of the next-nearest-neighbor interaction on the properties of the geometrically frustrated antiferromagnetic systems is investigated in the framework of the exactly solvable antiferromagnetic spin- 1 / 2 Ising model in the external magnetic field on the square-kagome recursive lattice, where the next-nearest-neighbor interaction is supposed between sites within each elementary square of the lattice. The thermodynamic properties of the model are investigated in detail and it is shown that the competition between the nearest-neighbor antiferromagnetic interaction and the next-nearest-neighbor ferromagnetic interaction changes properties of the single-point ground states but does not change the frustrated character of the basic model. On the other hand, the presence of the antiferromagnetic next-nearest-neighbor interaction leads to the enhancement of the frustration effects with the formation of additional plateau and single-point ground states at low temperatures. Exact expressions for magnetizations and residual entropies of all ground states of the model are found. It is shown that the model exhibits various ground states with the same value of magnetization but different macroscopic degeneracies as well as the ground states with different values of magnetization but the same value of the residual entropy. The specific heat capacity is investigated and it is shown that the model exhibits the Schottky-type anomaly behavior in the vicinity of each single-point ground state value of the magnetic field. The formation of the field-induced double-peak structure of the specific heat capacity at low temperatures is demonstrated and it is shown that its very existence is directly related to the presence of highly macroscopically degenerated single-point ground states in the model.

Association of food access and neighbor relationships with diet and underweight among community-dwelling older Japanese.

Science.gov (United States)

Nakamura, Hideko; Nakamura, Mieko; Okada, Eisaku; Ojima, Toshiyuki; Kondo, Katsunori

2017-11-01

Food access is important for maintaining dietary variety, which predicts underweight. The aim of this study was to examine the association of food access and neighbor relationships with eating and underweight. We analyzed cross-sectional data from 102,869 Japanese individuals aged 65 years or older. The perceived availability of food was assessed using the presence or absence of food stores within 1 km of the home. Level of relationships with neighbors was also assessed. The odds ratios (ORs) and 95% confidence intervals (CIs) for infrequent food intake and underweight were determined using logistic regression analysis. The proportion of men and women having low access to food was 25-30%. Having low food access (OR 1.18; 95% CI, 1.12-1.25 for men and OR 1.26; 95% CI, 1.19-1.33 for women) and a low level of relationship with neighbors (OR 1.38; 95% CI, 1.31-1.45 for men and OR 1.57; 95% CI, 1.48-1.67 for women) was associated with infrequent intake of fruits and vegetables in both sexes. Association between low food access and infrequent intake of fruits and vegetables was higher among men with low levels of neighbor relationship (OR 1.34; 95% CI, 1.23-1.46) than among men with high levels of relationship (OR 1.10; 95% CI, 1.03-1.18). Low perceived availability of food is a risk factor for low dietary variety among older people. Furthermore, high levels of relationship with neighbors may relieve the harmful effect of low food access. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

The selection function of the LAMOST Spectroscopic Survey of the Galactic Anti-centre

Science.gov (United States)

Chen, B.-Q.; Liu, X.-W.; Yuan, H.-B.; Xiang, M.-S.; Huang, Y.; Wang, C.; Zhang, H.-W.; Tian, Z.-J.

2018-05-01

We present a detailed analysis of the selection function of the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC). LSS-GAC was designed to obtain low-resolution optical spectra for a sample of more than 3 million stars in the Galactic anti-centre. The second release of value-added catalogues of the LSS-GAC (LSS-GAC DR2) contains stellar parameters, including radial velocity, atmospheric parameters, elemental abundances, and absolute magnitudes deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC between 2011 and 2014. For many studies using this data base, such as those investigating the chemodynamical structure of the Milky Way, a detailed understanding of the selection function of the survey is indispensable. In this paper, we describe how the selection function of the LSS-GAC can be evaluated to sufficient detail and provide selection function corrections for all spectroscopic measurements with reliable parameters released in LSS-GAC DR2. The results, to be released as new entries in the LSS-GAC value-added catalogues, can be used to correct the selection effects of the catalogue for scientific studies of various purposes.

Allotment gardening and health: a comparative survey among allotment gardeners and their neighbors without an allotment

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van Winsum-Westra Marijke

2010-11-01

Full Text Available Abstract Background The potential contribution of allotment gardens to a healthy and active life-style is increasingly recognized, especially for elderly populations. However, few studies have empirically examined beneficial effects of allotment gardening. In the present study the health, well-being and physical activity of older and younger allotment gardeners was compared to that of controls without an allotment. Methods A survey was conducted among 121 members of 12 allotment sites in the Netherlands and a control group of 63 respondents without an allotment garden living next to the home addresses of allotment gardeners. The survey included five self-reported health measures (perceived general health, acute health complaints, physical constraints, chronic illnesses, and consultations with GP, four self-reported well-being measures (stress, life satisfaction, loneliness, and social contacts with friends and one measure assessing self-reported levels of physical activity in summer. Respondents were divided into a younger and older group at the median of 62 years which equals the average retirement age in the Netherlands. Results After adjusting for income, education level, gender, stressful life events, physical activity in winter, and access to a garden at home as covariates, both younger and older allotment gardeners reported higher levels of physical activity during the summer than neighbors in corresponding age categories. The impacts of allotment gardening on health and well-being were moderated by age. Allotment gardeners of 62 years and older scored significantly or marginally better on all measures of health and well-being than neighbors in the same age category. Health and well-being of younger allotment gardeners did not differ from younger neighbors. The greater health and well-being benefits of allotment gardening for older gardeners may be related to the finding that older allotment gardeners were more oriented towards gardening

Effective Feature Selection for Classification of Promoter Sequences.

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Kouser K

Full Text Available 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.

Selective androgen receptor modulators as function promoting therapies.

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Bhasin, Shalender; Jasuja, Ravi

2009-05-01

The past decade has witnessed an unprecedented discovery effort to develop selective androgen receptor modulators (SARMs) that improve physical function and bone health without adversely affecting the prostate and cardiovascular outcomes. This review describes the historical evolution, the rationale for SARM development, and the mechanisms of testosterone action and SARM selectivity. Although steroidal SARMs have been around since the 1940s, a number of nonsteroidal SARMs that do not serve as substrates for CYP19 aromatase or 5alpha-reductase, act as full agonists in muscle and bone and as partial agonists in prostate are in development. The differing interactions of steroidal and nonsteroidal compounds with androgen receptor (AR) contribute to their unique pharmacologic actions. Ligand binding induces specific conformational changes in the ligand-binding domain, which could modulate surface topology and protein-protein interactions between AR and coregulators, resulting in tissue-specific gene regulation. Preclinical studies have demonstrated the ability of SARMs to increase muscle and bone mass in preclinical rodent models with varying degree of prostate sparing. Phase I trials of SARMs in humans have reported modest increments in fat-free mass. SARMs hold promise as a new class of function promoting anabolic therapies for a number of clinical indications, including functional limitations associated with aging and chronic disease, frailty, cancer cachexia, and osteoporosis.

Elliptic Painlevé equations from next-nearest-neighbor translations on the E_8^{(1)} lattice

Science.gov (United States)

Joshi, Nalini; Nakazono, Nobutaka

2017-07-01

The well known elliptic discrete Painlevé equation of Sakai is constructed by a standard translation on the E_8(1) lattice, given by nearest neighbor vectors. In this paper, we give a new elliptic discrete Painlevé equation obtained by translations along next-nearest-neighbor vectors. This equation is a generic (8-parameter) version of a 2-parameter elliptic difference equation found by reduction from Adler’s partial difference equation, the so-called Q4 equation. We also provide a projective reduction of the well known equation of Sakai.

The quasar luminosity function from a variability-selected sample

Science.gov (United States)

Hawkins, M. R. S.; Veron, P.

1993-01-01

A sample of quasars is selected from a 10-yr sequence of 30 UK Schmidt plates. Luminosity functions are derived in several redshift intervals, which in each case show a featureless power-law rise towards low luminosities. There is no sign of the 'break' found in the recent UVX sample of Boyle et al. It is suggested that reasons for the disagreement are connected with biases in the selection of the UVX sample. The question of the nature of quasar evolution appears to be still unresolved.

Knowledgeable Neighbors: a mobile clinic model for disease prevention and screening in underserved communities.

Science.gov (United States)

Hill, Caterina; Zurakowski, David; Bennet, Jennifer; Walker-White, Rainelle; Osman, Jamie L; Quarles, Aaron; Oriol, Nancy

2012-03-01

The Family Van mobile health clinic uses a "Knowledgeable Neighbor" model to deliver cost-effective screening and prevention activities in underserved neighborhoods in Boston, MA. We have described the Knowledgeable Neighbor model and used operational data collected from 2006 to 2009 to evaluate the service. The Family Van successfully reached mainly minority low-income men and women. Of the clients screened, 60% had previously undetected elevated blood pressure, 14% had previously undetected elevated blood glucose, and 38% had previously undetected elevated total cholesterol. This represents an important model for reaching underserved communities to deliver proven cost-effective prevention activities, both to help control health care costs and to reduce health disparities.

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

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

Science.gov (United States)

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.

Neighboring Structure Visualization on a Grid-based Layout.

Science.gov (United States)

Marcou, G; Horvath, D; Varnek, A

2017-10-01

Here, we describe an algorithm to visualize chemical structures on a grid-based layout in such a way that similar structures are neighboring. It is based on structure reordering with the help of the Hilbert Schmidt Independence Criterion, representing an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator. The method can be applied to any layout of bi- or three-dimensional shape. The approach is demonstrated on a set of dopamine D5 ligands visualized on squared, disk and spherical layouts. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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.

Tricriticality in the q-neighbor Ising model on a partially duplex clique.

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Chmiel, Anna; Sienkiewicz, Julian; Sznajd-Weron, Katarzyna

2017-12-01

We analyze a modified kinetic Ising model, a so-called q-neighbor Ising model, with Metropolis dynamics [Phys. Rev. E 92, 052105 (2015)PLEEE81539-375510.1103/PhysRevE.92.052105] on a duplex clique and a partially duplex clique. In the q-neighbor Ising model each spin interacts only with q spins randomly chosen from its whole neighborhood. In the case of a duplex clique the change of a spin is allowed only if both levels simultaneously induce this change. Due to the mean-field-like nature of the model we are able to derive the analytic form of transition probabilities and solve the corresponding master equation. The existence of the second level changes dramatically the character of the phase transition. In the case of the monoplex clique, the q-neighbor Ising model exhibits a continuous phase transition for q=3, discontinuous phase transition for q≥4, and for q=1 and q=2 the phase transition is not observed. On the other hand, in the case of the duplex clique continuous phase transitions are observed for all values of q, even for q=1 and q=2. Subsequently we introduce a partially duplex clique, parametrized by r∈[0,1], which allows us to tune the network from monoplex (r=0) to duplex (r=1). Such a generalized topology, in which a fraction r of all nodes appear on both levels, allows us to obtain the critical value of r=r^{*}(q) at which a tricriticality (switch from continuous to discontinuous phase transition) appears.

Spacer for enhancing selectivity of functionalized polymer towards Pu(IV)

International Nuclear Information System (INIS)

Chavan, Vivek; Pandey, A.K.; Goswami, A.

2012-01-01

To address problems in selective and fast preconcentration of Pu(IV) at ultratrace concentration from the multicomponents aqueous media and low level nuclear waste, a new functionalized polymer sorbent was developed

Observing Literacy Practices in Neighbor Institutions

DEFF Research Database (Denmark)

Reusch, Charlotte

’procedures on language and literacy. Based on this material, we developed an observation scheme and a guide for preschool teachers to follow, inspired by an action learning concept.During fall 2015, a pilot project is carried out. Preschool teachers from one institution visit a neighbor institution one by one during...... work hours, in order to observe and register how language and literacy events look like there. Afterwards, they share their registrations at a team meeting, and discuss and decide which procedures to test in their own institution. Thus, they form a professional learning network. In the pilot project......The Danish National Centre for Reading and a municipality in southern Denmark cooperate to develop a program to improve preschool children’s early literacy skills. The project aims to support preschool teachers’ ability to create a rich literacy environment for children age 3‒6. Recent research...

Long-term effect of September 11 on the political behavior of victims’ families and neighbors

Science.gov (United States)

Hersh, Eitan D.

2013-01-01

This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims’ families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become—and have stayed—significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis. PMID:24324145

Long-term effect of September 11 on the political behavior of victims' families and neighbors.

Science.gov (United States)

Hersh, Eitan D

2013-12-24

This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims' families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become--and have stayed--significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis.

Applying an efficient K-nearest neighbor search to forest attribute imputation

Science.gov (United States)

Andrew O. Finley; Ronald E. McRoberts; Alan R. Ek

2006-01-01

This paper explores the utility of an efficient nearest neighbor (NN) search algorithm for applications in multi-source kNN forest attribute imputation. The search algorithm reduces the number of distance calculations between a given target vector and each reference vector, thereby, decreasing the time needed to discover the NN subset. Results of five trials show gains...

Holographic memories with encryption-selectable function

Science.gov (United States)

Su, Wei-Chia; Lee, Xuan-Hao

2006-03-01

Volume holographic storage has received increasing attention owing to its potential high storage capacity and access rate. In the meanwhile, encrypted holographic memory using random phase encoding technique is attractive for an optical community due to growing demand for protection of information. In this paper, encryption-selectable holographic storage algorithms in LiNbO 3 using angular multiplexing are proposed and demonstrated. Encryption-selectable holographic memory is an advance concept of security storage for content protection. It offers more flexibility to encrypt the data or not optionally during the recording processes. In our system design, the function of encryption and non-encryption storage is switched by a random phase pattern and a uniform phase pattern. Based on a 90-degree geometry, the input patterns including the encryption and non-encryption storage are stored via angular multiplexing with reference plane waves at different incident angles. Image is encrypted optionally by sliding the ground glass into one of the recording waves or removing it away in each exposure. The ground glass is a key for encryption. Besides, it is also an important key available for authorized user to decrypt the encrypted information.

River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

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H. Sanikhani

2016-02-01

Full Text Available Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1 methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE methodology for an application to runoff prediction, (2 methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3 methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models

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

Science.gov (United States)

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

Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

Institute of Scientific and Technical Information of China (English)

LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming

2004-01-01

Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.

Positive selection in the chromosome 16 VKORC1 genomic region has contributed to the variability of anticoagulant response in humans.

Directory of Open Access Journals (Sweden)

Blandine Patillon

Full Text Available VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2 is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK. This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8, and PRSS8 with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect.

Mountain tourism development in Serbia and neighboring countries

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Krunić Nikola

2010-01-01

Full Text Available Mountain areas with their surroundings are important parts of tourism regions with potentials for all-season tourism development and complementary activities. Development possibilities are based on size of high mountain territory, nature protection regimes, infrastructural equipment, provided conditions for leisure and recreation as well as involvement of local population in processes of development and protection. This paper analyses the key aspects of tourism development, winter tourism in high-mountain areas of Serbia and some neighboring countries (Slovakia, Romania, Bulgaria, and Greece. Common determinants of cohesion between nature protection and mountain tourism development, national development policies, applied models and concepts and importance of trans-border cooperation are indicated.

An interactive cooperation model for neighboring virtual power plants

International Nuclear Information System (INIS)

Shabanzadeh, Morteza; Sheikh-El-Eslami, Mohammad-Kazem; Haghifam, Mahmoud-Reza

2017-01-01

Highlights: •The trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. •A portfolio of inter-regional contracts is considered to model this cooperation scheme. •A novel mathematical formulation for possible inadvertent transactions is provided. •A two-stage stochastic programming approach is applied to characterize the uncertainty. •Two efficient risk measures, SSD and CVaR, are implemented in the VPP decision-making problem. -- Abstract: Future distribution systems will accommodate an increasing share of distributed energy resources (DERs). Facing with this new reality, virtual power plants (VPPs) play a key role to aggregate DERs with the aim of facilitating their involvement in wholesale electricity markets. In this paper, the trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. Toward this aim, a portfolio of inter-regional contracts is considered to model this cooperation and maximize the energy trade opportunities of the VPP within a medium-term horizon. To hedge against profit variability caused by market price uncertainties, two efficient risk management approaches are also implemented in the VPP decision-making problem based on the concepts of conditional value at risk (CVaR) and second-order stochastic dominance constraints (SSD). The resulting models are formulated as mixed-integer linear programming (MILP) problems that can be solved using off-the-shelf software packages. The efficiency of the proposed risk-hedging models is analyzed through a detailed case study, and thereby relevant conclusions are drawn.

Selective individual primary cell capture using locally bio-functionalized micropores.

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Jie Liu

Full Text Available BACKGROUND: Solid-state micropores have been widely employed for 6 decades to recognize and size flowing unlabeled cells. However, the resistive-pulse technique presents limitations when the cells to be differentiated have overlapping dimension ranges such as B and T lymphocytes. An alternative approach would be to specifically capture cells by solid-state micropores. Here, the inner wall of 15-µm pores made in 10 µm-thick silicon membranes was covered with antibodies specific to cell surface proteins of B or T lymphocytes. The selective trapping of individual unlabeled cells in a bio-functionalized micropore makes them recognizable just using optical microscopy. METHODOLOGY/PRINCIPAL FINDINGS: We locally deposited oligodeoxynucleotide (ODN and ODN-conjugated antibody probes on the inner wall of the micropores by forming thin films of polypyrrole-ODN copolymers using contactless electro-functionalization. The trapping capabilities of the bio-functionalized micropores were validated using optical microscopy and the resistive-pulse technique by selectively capturing polystyrene microbeads coated with complementary ODN. B or T lymphocytes from a mouse splenocyte suspension were specifically immobilized on micropore walls functionalized with complementary ODN-conjugated antibodies targeting cell surface proteins. CONCLUSIONS/SIGNIFICANCE: The results showed that locally bio-functionalized micropores can isolate target cells from a suspension during their translocation throughout the pore, including among cells of similar dimensions in complex mixtures.

Selective Individual Primary Cell Capture Using Locally Bio-Functionalized Micropores

Science.gov (United States)

Liu, Jie; Bombera, Radoslaw; Leroy, Loïc; Roupioz, Yoann; Baganizi, Dieudonné R.; Marche, Patrice N.; Haguet, Vincent; Mailley, Pascal; Livache, Thierry

2013-01-01

Background Solid-state micropores have been widely employed for 6 decades to recognize and size flowing unlabeled cells. However, the resistive-pulse technique presents limitations when the cells to be differentiated have overlapping dimension ranges such as B and T lymphocytes. An alternative approach would be to specifically capture cells by solid-state micropores. Here, the inner wall of 15-µm pores made in 10 µm-thick silicon membranes was covered with antibodies specific to cell surface proteins of B or T lymphocytes. The selective trapping of individual unlabeled cells in a bio-functionalized micropore makes them recognizable just using optical microscopy. Methodology/Principal Findings We locally deposited oligodeoxynucleotide (ODN) and ODN-conjugated antibody probes on the inner wall of the micropores by forming thin films of polypyrrole-ODN copolymers using contactless electro-functionalization. The trapping capabilities of the bio-functionalized micropores were validated using optical microscopy and the resistive-pulse technique by selectively capturing polystyrene microbeads coated with complementary ODN. B or T lymphocytes from a mouse splenocyte suspension were specifically immobilized on micropore walls functionalized with complementary ODN-conjugated antibodies targeting cell surface proteins. Conclusions/Significance The results showed that locally bio-functionalized micropores can isolate target cells from a suspension during their translocation throughout the pore, including among cells of similar dimensions in complex mixtures. PMID:23469221

Cultural macroevolution on neighbor graphs : vertical and horizontal transmission among Western North American Indian societies.

Science.gov (United States)

Towner, Mary C; Grote, Mark N; Venti, Jay; Borgerhoff Mulder, Monique

2012-09-01

What are the driving forces of cultural macroevolution, the evolution of cultural traits that characterize societies or populations? This question has engaged anthropologists for more than a century, with little consensus regarding the answer. We develop and fit autologistic models, built upon both spatial and linguistic neighbor graphs, for 44 cultural traits of 172 societies in the Western North American Indian (WNAI) database. For each trait, we compare models including or excluding one or both neighbor graphs, and for the majority of traits we find strong evidence in favor of a model which uses both spatial and linguistic neighbors to predict a trait's distribution. Our results run counter to the assertion that cultural trait distributions can be explained largely by the transmission of traits from parent to daughter populations and are thus best analyzed with phylogenies. In contrast, we show that vertical and horizontal transmission pathways can be incorporated in a single model, that both transmission modes may indeed operate on the same trait, and that for most traits in the WNAI database, accounting for only one mode of transmission would result in a loss of information.

Watch Out for Your Neighbor: Climbing onto Shrubs Is Related to Risk of Cannibalism in the Scorpion Buthus cf. occitanus.

Science.gov (United States)

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.

Functionalized membranes for environmental remediation and selective separation

Science.gov (United States)

Xiao, Li

) between UF and RO presents selectivity controlled by both steric and electrostatic repulsions, which are widely used to reject charged species, particularly multivalent ions. In this work, selective permeation of CaCl2 and high sucrose retention are obtained through the modification of nanofiltration membranes with lower charge compared to commercial nanofiltration membrane. The membrane module also shows high stability with constant water permeability in a long-term (two months) test. Extended Nernst-Planck equation were further used to evaluate the experimental results and it fits well. KEY WORDS: Functionalized Membrane, Dechlorination, Responsive, Tunable, Full-scale.

Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2010-01-01

Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii

Understanding Linear Function: A Comparison of Selected Textbooks from England and Shanghai

Science.gov (United States)

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

This study describes a comparison of how worked examples in selected textbooks from England and Shanghai presented possible learning trajectories towards understanding linear function. Six selected English textbooks and one Shanghai compulsory textbook were analysed with regards to the understanding required for pure mathematics knowledge in…

Accounting for animal movement in estimation of resource selection functions: sampling and data analysis.

Science.gov (United States)

Forester, James D; Im, Hae Kyung; Rathouz, Paul J

2009-12-01

Patterns of resource selection by animal populations emerge as a result of the behavior of many individuals. Statistical models that describe these population-level patterns of habitat use can miss important interactions between individual animals and characteristics of their local environment; however, identifying these interactions is difficult. One approach to this problem is to incorporate models of individual movement into resource selection models. To do this, we propose a model for step selection functions (SSF) that is composed of a resource-independent movement kernel and a resource selection function (RSF). We show that standard case-control logistic regression may be used to fit the SSF; however, the sampling scheme used to generate control points (i.e., the definition of availability) must be accommodated. We used three sampling schemes to analyze simulated movement data and found that ignoring sampling and the resource-independent movement kernel yielded biased estimates of selection. The level of bias depended on the method used to generate control locations, the strength of selection, and the spatial scale of the resource map. Using empirical or parametric methods to sample control locations produced biased estimates under stronger selection; however, we show that the addition of a distance function to the analysis substantially reduced that bias. Assuming a uniform availability within a fixed buffer yielded strongly biased selection estimates that could be corrected by including the distance function but remained inefficient relative to the empirical and parametric sampling methods. As a case study, we used location data collected from elk in Yellowstone National Park, USA, to show that selection and bias may be temporally variable. Because under constant selection the amount of bias depends on the scale at which a resource is distributed in the landscape, we suggest that distance always be included as a covariate in SSF analyses. This approach to

Gastronomy Tourism in Several Neighbor Countries of Indonesia: a Brief Review

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Kurniasih Sukenti

2014-04-01

Full Text Available Gastronomy tourism, also called culinary tourism or food tourism, is a kind of tourism that provide attractions based on the culinary aspect owned by a country, region, or area. It is not only offers food and beverages as the main objects in its attractions, but also everything related to food activities ranging from food ingredients, preparation, processing, serving, as well as the cultural and local values. A well-managed culinary tourism will be a supportive program in developing and enhancing the tourism sector in a country. The objective of this paper is to describe the profile of gastronomy tourism in several neighbor countries of Indonesia, i.e. Hongkong, Singapore, Thailand, and Malaysia. This brief review is also discussed the potential of Indonesia gastronomy in supporting government’s tourism program. Basically, Indonesia has more enormous potential asset in managing its cultural heritages in term of culinary than its neighbor countries. A well-managed gastronomy tourism plays not only an important role in enhancing the economic sector, but also contribute in preserving the natural and cultural resources. Keywords: gastronomy tourism, culinary tourism, food tourism.

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

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Aharon Azulay

2016-09-01

Full Text Available 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.

Selective chloroform sensor using thiol functionalized reduced graphene oxide at room temperature

Science.gov (United States)

Midya, Anupam; Mukherjee, Subhrajit; Roy, Shreyasee; Santra, Sumita; Manna, Nilotpal; Ray, Samit K.

2018-02-01

This paper presents a highly selective chloroform sensor using functionalised reduced graphene oxide (RGO) as a sensing layer. Thiol group is covalently attached on the basal plan of RGO film by a simple one-step aryl diazonium chemistry to improve its selectivity. Several spectroscopic techniques like X-ray photoelectron, Raman and Fourier transform infrared spectroscopy confirm successful thiol functionalization of RGO. Finally, the fabricated chemiresistor type sensor is exposed to chloroform in the concentration range 200-800 ppm (parts per million). The sensor shows a 4.3% of response towards 800 ppm chloroform. The selectivity of the sensor is analyzed using various volatile organic compounds as well. The devices show enhanced response and faster recovery attributed to the physiosorption of chloroform onto thiol functionalized graphene making them attractive for 2D materials based sensing applications.

Material selection for Multi-Function Waste Tank Facility tanks

International Nuclear Information System (INIS)

Carlos, W.C.

1994-01-01

This report briefly summarizes the history of the materials selection for the US Department of Energy's high-level waste carbon steel storage tanks. It also provide an evaluation of the materials for the construction of new tanks at the Multi-Function Waste Tank Facility. The evaluation included a materials matrix that summarized the critical design, fabrication, construction, and corrosion resistance requirements; assessed each requirement; and cataloged the advantages and disadvantages of each material. This evaluation is based on the mission of the Multi-Function Waste Tank Facility. On the basis of the compositions of the wastes stored in Hanford waste tanks, it is recommended that tanks for the Multi-Function Waste Tank Facility be constructed of normalized ASME SA 516, Grade 70, carbon steel

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

Science.gov (United States)

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

A Fast Exact k-Nearest Neighbors Algorithm for High Dimensional Search Using k-Means Clustering and Triangle Inequality.

Science.gov (United States)

Wang, Xueyi

2012-02-08

The k-nearest neighbors (k-NN) algorithm is a widely used machine learning method that finds nearest neighbors of a test object in a feature space. We present a new exact k-NN algorithm called kMkNN (k-Means for k-Nearest Neighbors) that uses the k-means clustering and the triangle inequality to accelerate the searching for nearest neighbors in a high dimensional space. The kMkNN algorithm has two stages. In the buildup stage, instead of using complex tree structures such as metric trees, kd-trees, or ball-tree, kMkNN uses a simple k-means clustering method to preprocess the training dataset. In the searching stage, given a query object, kMkNN finds nearest training objects starting from the nearest cluster to the query object and uses the triangle inequality to reduce the distance calculations. Experiments show that the performance of kMkNN is surprisingly good compared to the traditional k-NN algorithm and tree-based k-NN algorithms such as kd-trees and ball-trees. On a collection of 20 datasets with up to 10(6) records and 10(4) dimensions, kMkNN shows a 2-to 80-fold reduction of distance calculations and a 2- to 60-fold speedup over the traditional k-NN algorithm for 16 datasets. Furthermore, kMkNN performs significant better than a kd-tree based k-NN algorithm for all datasets and performs better than a ball-tree based k-NN algorithm for most datasets. The results show that kMkNN is effective for searching nearest neighbors in high dimensional spaces.

Allocating structure to function: the strong links between neuroplasticity and natural selection

Directory of Open Access Journals (Sweden)

Michael L Anderson

2014-01-01

Full Text Available A central question in brain evolution is how species-typical behaviors, and the neural function-structure mappings supporting them, can be acquired and inherited. Advocates of brain modularity, in its different incarnations across scientific subfields, argue that natural selection must target domain-dedicated, separately modifiable neural subsystems, resulting in genetically-specified functional modules. In such modular systems, specification of neuron number and functional connectivity are necessarily linked. Mounting evidence, however, from allometric, developmental, comparative, systems-physiological, neuroimaging and neurological studies suggests that brain elements are used and reused in multiple functional systems. This variable allocation can be seen in short-term neuromodulation, in neuroplasticity over the lifespan and in response to damage. We argue that the same processes are evident in brain evolution. Natural selection must preserve behavioral functions that may co-locate in variable amounts with other functions. In genetics, the uses and problems of pleiotropy, the re-use of genes in multiple networks have been much discussed, but this issue has been sidestepped in neural systems by the invocation of modules. Here we highlight the interaction between evolutionary and developmental mechanisms to produce distributed and overlapping functional architectures in the brain. These adaptive mechanisms must be robust to perturbations that might disrupt critical information processing and action selection, but must also recognize useful new sources of information arising from internal genetic or environmental variability, when those appear. These contrasting properties of robustness and evolvability have been discussed for the basic organization of body plan and fundamental cell physiology. Here we extend them to the evolution and development, evo-devo, of brain structure.

Keeping up With The Neighbors: Nonproliferation and Implementation of UNSCR 1540

Science.gov (United States)

2016-02-15

be respectful of the rule of law and a competitive participatory democracy , yet fail to implement UNSCR 1540, just like its neighbors. Discussion...risk-taking between 1816 and 1992. They found a strong association between conservative governmental decision-making and not only democracies , but...specifically those democracies with highly competitive political systems.46 In addition, Bruce Bueno de Mesquita, et.al. found a significant

Credit scoring analysis using weighted k nearest neighbor

Science.gov (United States)

Mukid, M. A.; Widiharih, T.; Rusgiyono, A.; Prahutama, A.

2018-05-01

Credit scoring is a quatitative method to evaluate the credit risk of loan applications. Both statistical methods and artificial intelligence are often used by credit analysts to help them decide whether the applicants are worthy of credit. These methods aim to predict future behavior in terms of credit risk based on past experience of customers with similar characteristics. This paper reviews the weighted k nearest neighbor (WKNN) method for credit assessment by considering the use of some kernels. We use credit data from a private bank in Indonesia. The result shows that the Gaussian kernel and rectangular kernel have a better performance based on the value of percentage corrected classified whose value is 82.4% respectively.

Selective Androgen Receptor Modulators (SARMs) as Function Promoting Therapies

Science.gov (United States)

Bhasin, Shalender; Jasuja, Ravi

2010-01-01

Purpose of review The last decade has witnessed unprecedented discovery effort to develop selective androgen receptor modulators (SARMs) that improve physical function and bone health without adversely affecting the prostate and cardiovascular outcomes. This review describes the historical evolution, the rationale for SARM development, and the mechanisms of testosterone action and SARM selectivity. Recent Findings While steroidal SARMs have been around since the 1940s, a number of nonsteroidal SARMs that do not serve as substrates for CYP19 aromatase or 5α-reductase, act as full agonists in muscle and bone and as partial agonists in prostate are in development. The differing interactions of steroidal and nonsteroidal compounds with AR contribute to their unique pharmacologic actions. Ligand binding induces specific conformational changes in the ligand binding domain, which could modulate surface topology and protein-protein interactions between AR and coregulators, resulting in tissue-specific gene regulation. Preclinical studies have demonstrated the ability of SARMs to increase muscle and bone mass in preclinical rodent models with varying degree of prostate sparing. Phase I trials of SARMs in humans have reported modest increments in fat-free mass. Summary SARMs hold promise as a new class of function promoting anabolic therapies for a number of clinical indications, including functional limitations associated with aging and chronic disease, frailty, cancer cachexia, and osteoporosis. PMID:19357508

Site-selective three-component reaction for dual-functionalization of peptides

DEFF Research Database (Denmark)

Munch, Henrik Kofoed; Rasmussen, Jakob Ewald; Popa, Gina

2013-01-01

A site-selective dual-functionalization of peptides is presented, involving readily available maleimides as well as N-hydroxylamines. The modification proceeds through a three component 1,3-dipolar cycloaddition, forming a stable product. This was exemplified by the one-pot attachment of two...

Rapid corn and soybean mapping in US Corn Belt and neighboring areas

Science.gov (United States)

Zhong, Liheng; Yu, Le; Li, Xuecao; Hu, Lina; Gong, Peng

2016-11-01

The goal of this study was to promptly map the extent of corn and soybeans early in the growing season. A classification experiment was conducted for the US Corn Belt and neighboring states, which is the most important production area of corn and soybeans in the world. To improve the timeliness of the classification algorithm, training was completely based on reference data and images from other years, circumventing the need to finish reference data collection in the current season. To account for interannual variability in crop development in the cross-year classification scenario, several innovative strategies were used. A random forest classifier was used in all tests, and MODIS surface reflectance products from the years 2008-2014 were used for training and cross-year validation. It is concluded that the fuzzy classification approach is necessary to achieve satisfactory results with R-squared ~0.9 (compared with the USDA Cropland Data Layer). The year of training data is an important factor, and it is recommended to select a year with similar crop phenology as the mapping year. With this phenology-based and cross-year-training method, in 2015 we mapped the cropping proportion of corn and soybeans around mid-August, when the two crops just reached peak growth.

Fusion yield rate recovery by escaping hot-spot fast ions in the neighboring fuel layer

Science.gov (United States)

Tang, Xian-Zhu; McDevitt, C. J.; Guo, Zehua; Berk, H. L.

2014-02-01

Free-streaming loss by fast ions can deplete the tail population in the hot spot of an inertial confinement fusion (ICF) target. Escaping fast ions in the neighboring fuel layer of a cryogenic target can produce a surplus of fast ions locally. In contrast to the Knudsen layer effect that reduces hot-spot fusion reactivity due to tail ion depletion, the inverse Knudsen layer effect increases fusion reactivity in the neighboring fuel layer. In the case of a burning ICF target in the presence of significant hydrodynamic mix which aggravates the Knudsen layer effect, the yield recovery largely compensates for the yield reduction. For mix-dominated sub-ignition targets, the yield reduction is the dominant process.

Development of end-selective functionalized carbon nanotubes for biomedical applications

Science.gov (United States)

Lee, Seung Ho; Kim, Wan Sun; Lee, Ha Rim; Park, Kyu Chang; Lee, Chang Hoon; Park, Hun Kuk; Kim, Kyung Sook

2015-12-01

Carbon nanotube (CNT) is a type of carbon allotrope with excellent physical and electrical properties, including high thermal conductivity, mechanical strength, and thermal stability. Therefore, applications of CNT have been considered for a variety of fields, including biosensors, molecular electronics, X-ray, and fuel cells. However, the application of CNT to biomedicine is limited because this material is cytotoxic and inhomogeneous. In particular, the irregularity in the structural properties of paste or bundle-type CNTs causes an uncontrolled modification in biomolecules. Therefore, using CNT as biosensors to obtain quantitative analyses is difficult. In this study, we developed a new method to perform end-selective functionalization of CNT in order to enable quantitative analysis for biomedical applications. The process was as follows: (1) etching the tip of vertically-aligned CNTs under optimum conditions, (2) oxidation of exposed CNTs, and (3) end-selective linkage of functionalized CNTs with biomolecules (dsDNA).

Aftershock identification problem via the nearest-neighbor analysis for marked point processes

Science.gov (United States)

Gabrielov, A.; Zaliapin, I.; Wong, H.; Keilis-Borok, V.

2007-12-01

The centennial observations on the world seismicity have revealed a wide variety of clustering phenomena that unfold in the space-time-energy domain and provide most reliable information about the earthquake dynamics. However, there is neither a unifying theory nor a convenient statistical apparatus that would naturally account for the different types of seismic clustering. In this talk we present a theoretical framework for nearest-neighbor analysis of marked processes and obtain new results on hierarchical approach to studying seismic clustering introduced by Baiesi and Paczuski (2004). Recall that under this approach one defines an asymmetric distance D in space-time-energy domain such that the nearest-neighbor spanning graph with respect to D becomes a time- oriented tree. We demonstrate how this approach can be used to detect earthquake clustering. We apply our analysis to the observed seismicity of California and synthetic catalogs from ETAS model and show that the earthquake clustering part is statistically different from the homogeneous part. This finding may serve as a basis for an objective aftershock identification procedure.

Carbon-hydrogen defects with a neighboring oxygen atom in n-type Si

Science.gov (United States)

Gwozdz, K.; Stübner, R.; Kolkovsky, Vl.; Weber, J.

2017-07-01

We report on the electrical activation of neutral carbon-oxygen complexes in Si by wet-chemical etching at room temperature. Two deep levels, E65 and E75, are observed by deep level transient spectroscopy in n-type Czochralski Si. The activation enthalpies of E65 and E75 are obtained as EC-0.11 eV (E65) and EC-0.13 eV (E75). The electric field dependence of their emission rates relates both levels to single acceptor states. From the analysis of the depth profiles, we conclude that the levels belong to two different defects, which contain only one hydrogen atom. A configuration is proposed, where the CH1BC defect, with hydrogen in the bond-centered position between neighboring C and Si atoms, is disturbed by interstitial oxygen in the second nearest neighbor position to substitutional carbon. The significant reduction of the CH1BC concentration in samples with high oxygen concentrations limits the use of this defect for the determination of low concentrations of substitutional carbon in Si samples.

Selection of Objective Function For Imbalanced Classification: An Industrial Case Study

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

2017-01-01

In this article we discuss the issue of selecting suitable objective function for Genetic Algorithm to solve an imbalanced classification problem. More precisely, first we discuss the need of specialized objective function to solve a real classification problem from our industrial partner and the...... and then we compare the results of our proposed objective function with commonly used candidates to serve this purpose. Our comparison is based on the analysis of real data collected during the quality control stages of the manufacturing process....

Two Point Correlation Functions for a Periodic Box-Ball System

Directory of Open Access Journals (Sweden)

Jun Mada

2011-03-01

Full Text Available We investigate correlation functions in a periodic box-ball system. For the second and the third nearest neighbor correlation functions, we give explicit formulae obtained by combinatorial methods. A recursion formula for a specific N-point functions is also presented.

Functionally Selective AT(1) Receptor Activation Reduces Ischemia Reperfusion Injury

DEFF Research Database (Denmark)

Hostrup, Anders; Christensen, Gitte Lund; Bentzen, Bo Hjort

2012-01-01

of the physiological functions of AngII. The AT(1)R mediates its effects through both G protein-dependent and independent signaling, which can be separated by functionally selective agonists. In the present study we investigate the effect of AngII and the ß-arrestin biased agonist [SII]AngII on ischemia......]AngII had a protective effect. Together these results demonstrate a cardioprotective effect of simultaneous blockade of G protein signaling and activation of G protein independent signaling through AT(1 )receptors....

The influence of As/III pressure ratio on nitrogen nearest-neighbor environments in as-grown GaInNAs quantum wells

International Nuclear Information System (INIS)

Kudrawiec, R.; Poloczek, P.; Misiewicz, J.; Korpijaervi, V.-M.; Laukkanen, P.; Pakarinen, J.; Dumitrescu, M.; Guina, M.; Pessa, M.

2009-01-01

The energy fine structure, corresponding to different nitrogen nearest-neighbor environments, was observed in contactless electroreflectance (CER) spectra of as-grown GaInNAs quantum wells (QWs) obtained at various As/III pressure ratios. In the spectral range of the fundamental transition, two CER resonances were detected for samples grown at low As pressures whereas only one CER resonance was observed for samples obtained at higher As pressures. This resonance corresponds to the most favorable nitrogen nearest-neighbor environment in terms of the total crystal energy. It means that the nitrogen nearest-neighbor environment in GaInNAs QWs can be controlled in molecular beam epitaxy process by As/III pressure ratio.

Cell-selective metabolic labeling of biomolecules with bioorthogonal functionalities.

Science.gov (United States)

Xie, Ran; Hong, Senlian; Chen, Xing

2013-10-01

Metabolic labeling of biomolecules with bioorthogonal functionalities enables visualization, enrichment, and analysis of the biomolecules of interest in their physiological environments. This versatile strategy has found utility in probing various classes of biomolecules in a broad range of biological processes. On the other hand, metabolic labeling is nonselective with respect to cell type, which imposes limitations for studies performed in complex biological systems. Herein, we review the recent methodological developments aiming to endow metabolic labeling strategies with cell-type selectivity. The cell-selective metabolic labeling strategies have emerged from protein and glycan labeling. We envision that these strategies can be readily extended to labeling of other classes of biomolecules. Copyright © 2013 Elsevier Ltd. All rights reserved.

Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor

OpenAIRE

CHIKH, Mohamed Amine; SAIDI, Meryem; SETTOUTI, Nesma

2012-01-01

The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disea...

On the difference in oscillator strengths of inner shell excitations in noble gases and their alkali neighbors

International Nuclear Information System (INIS)

Amusia, M.Y.; Baltenkov, A.S.; Zhuravleva, G.I.

1995-01-01

It is demonstrated that the oscillator strength of resonant inner-shell excitation in a noble gas atom is considerably smaller than that in its alkali neighbor because in the latter case the effective charge acting upon excited electron is much bigger. With increase of the excitation's principal quantum number the difference between line intensities in noble gases and their alkali neighbors rapidly disappears. The calculations are performed in the Hartree-Fock approximation and with inclusion of rearrangement effects due to inner vacancy creation and its Auger decay. A paper has been submitted for publication

Nearest neighbors EPR superhyperfine interaction in divalent iridium complexes in alkali halide host lattice

International Nuclear Information System (INIS)

Pinhal, N.M.; Vugman, N.V.

1983-01-01

Further splitting of chlorine superhyperfine lines on the EPR spectrum of the [Ir (CN) 4 Cl 2 ] 4 - molecular species in NaCl latice indicates a super-superhyperfine interaction with the nearest neighbors sodium atoms. (Author) [pt

Functional Analysis Of A Selected Airport’s System

Directory of Open Access Journals (Sweden)

Dudek Ewa

2015-11-01

Full Text Available In this paper two selected airport’s systems (Flight Information System and Public Address Voice Annunciation are defined and described. Then they are used to create an integrated unit, with the presentation of its way of functioning and a schematic picture. The author names main purposes of the integration process, serving to counteract negative consequences arising from implementation of the increasing number of systems on transport objects. In the following part of the article functional analysis of the integrated unit is carried out, defining system’s possible states of work and relations between them. Utilization of mathematical apparatus allows to calculate probabilities of system staying in the respective states, as well as system’s time indexes. Presented results are a fundament for the further analysis of this matter.

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

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

Science.gov (United States)

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.

Neighborhood environments and its influence on physical activity in Olomouc and neighboring villages

Directory of Open Access Journals (Sweden)

Michal Kohout

2014-03-01

Full Text Available BACKGROUND: Modern society with development of new technologies greatly facilitates the activities of daily life and thus substantially eliminates human motion. This fact, together with a sedentary behavior is associated with considerable health risks, such as obesity, diabetes mellitus (type II, hypertension etc. A large part of the population is not aware of the negative consequences of physical inactivity, which may cause serious health problems. And this circumstance should be the main motivational factor to change lifestyle, including the environment. AIM: This study examines differences in the structure of physical activity in adults in Olomouc and neighboring villages within 15 km distance around Olomouc. The main objective was to determine how neighborhood environments affect physical activity of selected population groups. METHODS: All respondents were visited in person by authors and asked to participate in a research study using a Czech version of the questionnaire ANEWS. Data collection was carried out in May and June 2012 and data were obtained from 43 respondents aged 24-61 living in Olomouc and neighboring. RESULTS: The results showed that residents of urban areas are more physically active than nonurban residents. In the active area residents with higher walkability were associated with higher physical activity in urban residents, while the rural residents indicated higher physical activity in lower walkability areas. We found a significant difference in energy expenditure among respondents living in areas with higher and lower walkability in favor of the more walkable areas [H (1, 43 = 26.184, p ≤ .000]. CONCLUSIONS: Highest levels of physical activity represent men living in single-family houses and women living in multiple family houses. Participating respondents most frequently engaged in moderate physical activities. They spent more time sitting during work than sitting outside the workplace. Most frequently used

Modifiers of Neighbors' Bystander Intervention in Intimate Partner Violence: A Concept Mapping Study.

Science.gov (United States)

Wee, Sara; Todd, Mary-Justine; Oshiro, Michael; Greene, Emily; Frye, Victoria

2016-03-01

Encouraging bystander intervention in intimate partner violence (IPV) against women is potentially an important method of reducing the prevalence of such violence in urban communities. Most existing research has been conducted on campuses and in relation to sexual violence among teens or young adults. Our understanding of which bystander behaviors are feasible is nascent, and our knowledge of which situational factors influence neighbors' self-reported willingness to intervene is underdeveloped. We conducted a concept mapping study to identify potential bystander intervention behaviors in IPV among neighbors in urban settings; we also assessed whether perceived feasibility and effectiveness of those behaviors varied by situational characteristics. Using data collected from 41 residents of a low-income New York City neighborhood in late 2011, concept mapping was used to create a conceptual map of the 74 behaviors identified by participants. We examined participant differences in mean feasibility (i.e., that the participants "could" or "would" enact a behavior), feasibility given two situational characteristics (if the couple was perceived to have a history of IPV, and if children were believed to be involved or present), and perceived effectiveness of bystander behaviors. Differences across select sociodemographic factors of participants were also analyzed. A 13-cluster solution emerged, with clusters of bystander behaviors grouped into four larger cluster areas: victim focused, parenting/education focused, perpetrator focused, and community involvement focused. Bivariate analyses revealed that participants rated the four cluster areas as more feasible when a child was believed to be involved. Male participants rated intervention as less feasible when the couple was believed to have a history of IPV. Participants who reported a history of IPV victimization rated all four cluster areas as less effective on average, as compared with participants without a history of

Exactly solvable spin-1 Ising–Heisenberg diamond chain with the second-neighbor interaction between nodal spins

International Nuclear Information System (INIS)

Hovhannisyan, V V; Ananikian, N S; Strečka, J

2016-01-01

The spin-1 Ising–Heisenberg diamond chain with the second-neighbor interaction between nodal spins is rigorously solved using the transfer-matrix method. In particular, exact results for the ground state, magnetization process and specific heat are presented and discussed. It is shown that further-neighbor interaction between nodal spins gives rise to three novel ground states with a translationally broken symmetry, but at the same time, does not increases the total number of intermediate plateaus in a zero-temperature magnetization curve compared with the simplified model without this interaction term. The zero-field specific heat displays interesting thermal dependencies with a single- or double-peak structure. (paper)

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Directory of Open Access Journals (Sweden)

Hailun Wang

2017-01-01

Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

Characterization of Angiotensin II Molecular Determinants Involved in AT1 Receptor Functional Selectivity.

Science.gov (United States)

Domazet, Ivana; Holleran, Brian J; Richard, Alexandra; Vandenberghe, Camille; Lavigne, Pierre; Escher, Emanuel; Leduc, Richard; Guillemette, Gaétan

2015-06-01

The octapeptide angiotensin II (AngII) exerts a variety of cardiovascular effects through the activation of the AngII type 1 receptor (AT1), a G protein-coupled receptor. The AT1 receptor engages and activates several signaling pathways, including heterotrimeric G proteins Gq and G12, as well as the extracellular signal-regulated kinases (ERK) 1/2 pathway. Additionally, following stimulation, βarrestin is recruited to the AT1 receptor, leading to receptor desensitization. It is increasingly recognized that specific ligands selectively bind and favor the activation of some signaling pathways over others, a concept termed ligand bias or functional selectivity. A better understanding of the molecular basis of functional selectivity may lead to the development of better therapeutics with fewer adverse effects. In the present study, we developed assays allowing the measurement of six different signaling modalities of the AT1 receptor. Using a series of AngII peptide analogs that were modified in positions 1, 4, and 8, we sought to better characterize the molecular determinants of AngII that underlie functional selectivity of the AT1 receptor in human embryonic kidney 293 cells. The results reveal that position 1 of AngII does not confer functional selectivity, whereas position 4 confers a bias toward ERK signaling over Gq signaling, and position 8 confers a bias toward βarrestin recruitment over ERK activation and Gq signaling. Interestingly, the analogs modified in position 8 were also partial agonists of the protein kinase C (PKC)-dependent ERK pathway via atypical PKC isoforms PKCζ and PKCι. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Variant selection of primary, secondary and tertiary twins in a deformed Mg alloy

International Nuclear Information System (INIS)

Mu, Sijia; Jonas, John J.; Gottstein, Günter

2012-01-01

Samples of magnesium alloy AZ31 were deformed in plane strain compression in a channel die at 100 °C and a strain rate of 5 × 10 −3 s −1 . The initial texture was favorably oriented for extension twinning. At a true strain of ε = −0.11, many primary extension twins were observed to consume their parent grains completely. Furthermore, numerous secondary contraction twins formed within the primary extension twins and some tertiary extension twins grew within the secondary contraction twins. The orientations of the parent grains and all three generations of twins were measured. The twin variants selected during each of the three stages of twinning were determined by electron backscatter diffraction techniques and the absent potential twin variants were also identified. The way in which the selected primary extension twins grow so as to consume the parent grains and contact all the neighboring grains is explained in terms of the accommodation strains imposed on the neighboring grains. The analysis shows that the primary twin selected is not necessarily the variant with the highest Schmid factor but the one that requires the least accommodation work in most of the neighboring grains. The same principle was found to hold for the secondary and tertiary twins. By contrast, potential high Schmid factor twins that required the consumption of appreciable accommodation energy did not form. A Taylor simulation produced similar results and indicates that the accommodation strain concept is consistent with the principle of the minimization of plastic work.

A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets

Science.gov (United States)

Chen, Jianrui; Wang, Hua; Wang, Lina; Liu, Weiwei

2016-04-01

Community detection in social networks has been intensively studied in recent years. In this paper, a novel similarity measurement is defined according to social balance theory for signed networks. Inter-community positive links are found and deleted due to their low similarity. The positive neighbor sets are reconstructed by this method. Then, differential equations are proposed to imitate the constantly changing states of nodes. Each node will update its state based on the difference between its state and average state of its positive neighbors. Nodes in the same community will evolve together with time and nodes in the different communities will evolve far away. Communities are detected ultimately when states of nodes are stable. Experiments on real world and synthetic networks are implemented to verify detection performance. The thorough comparisons demonstrate the presented method is more efficient than two acknowledged better algorithms.

Cluster Head Selection in a Homogeneous Wireless Sensor Network Ensuring Full Connectivity with Minimum Isolated Nodes

Directory of Open Access Journals (Sweden)

Tapan Kumar Jain

2014-01-01

Full Text Available The research work proposes a cluster head selection algorithm for a wireless sensor network. A node can be a cluster head if it is connected to at least one unique neighbor node where the unique neighbor is the one that is not connected to any other node. If there is no connected unique node then the CH is selected on the basis of residual energy and the number of neighbor nodes. With the increase in number of clusters, the processing energy of the network increases; hence, this algorithm proposes minimum number of clusters which further leads to increased network lifetime. The major novel contribution of the proposed work is an algorithm that ensures a completely connected network with minimum number of isolated nodes. An isolated node will remain only if it is not within the transmission range of any other node. With the maximum connectivity, the coverage of the network is automatically maximized. The superiority of the proposed design is verified by simulation results done in MATLAB, where it clearly depicts that the total numbers of rounds before the network dies out are maximum compared to other existing protocols.

77 FR 50504 - Good Neighbor Environmental Board Notification of Public Advisory Committee Teleconference

Science.gov (United States)

2012-08-21

... recommendations to the President and Congress on environmental and infrastructure issues along the U.S. border with Mexico. Purpose of Meeting: The purpose of this teleconference is to discuss the Good Neighbor Environmental Board's Fifteenth Report. The report will focus on water infrastructure issues in the U.S.-Mexico...

77 FR 13599 - Good Neighbor Environmental Board; Notification of Public Advisory Committee Teleconference

Science.gov (United States)

2012-03-07

... recommendations to the President and Congress on environmental and infrastructure issues along the U.S. border with Mexico. Purpose of Meeting: The purpose of this teleconference is to discuss the Good Neighbor Environmental Board's Fifteenth Report. The report will focus on water infrastructure issues in the U.S.-Mexico...

Giant Planets: Good Neighbors for Habitable Worlds?

Science.gov (United States)

Georgakarakos, Nikolaos; Eggl, Siegfried; Dobbs-Dixon, Ian

2018-04-01

The presence of giant planets influences potentially habitable worlds in numerous ways. Massive celestial neighbors can facilitate the formation of planetary cores and modify the influx of asteroids and comets toward Earth analogs later on. Furthermore, giant planets can indirectly change the climate of terrestrial worlds by gravitationally altering their orbits. Investigating 147 well-characterized exoplanetary systems known to date that host a main-sequence star and a giant planet, we show that the presence of “giant neighbors” can reduce a terrestrial planet’s chances to remain habitable, even if both planets have stable orbits. In a small fraction of systems, however, giant planets slightly increase the extent of habitable zones provided that the terrestrial world has a high climate inertia. In providing constraints on where giant planets cease to affect the habitable zone size in a detrimental fashion, we identify prime targets in the search for habitable worlds.

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

Science.gov (United States)

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

2017-07-03

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.

Chaotic Synchronization in Nearest-Neighbor Coupled Networks of 3D CNNs

OpenAIRE

Serrano-Guerrero, H.; Cruz-Hernández, C.; López-Gutiérrez, R.M.; Cardoza-Avendaño, L.; Chávez-Pérez, R.A.

2013-01-01

In this paper, a synchronization of Cellular Neural Networks (CNNs) in nearest-neighbor coupled arrays, is numerically studied. Synchronization of multiple chaotic CNNs is achieved by appealing to complex systems theory. In particular, we consider dynamical networks composed by 3D CNNs, as interconnected nodes, where the interactions in the networks are defined by coupling the first state of each node. Four cases of interest are considered: i) synchronization without chaotic master, ii) maste...

Synthesis and electronic properties of chemically functionalized graphene on metal surfaces

International Nuclear Information System (INIS)

Grüneis, Alexander

2013-01-01

A review on the electronic properties, growth and functionalization of graphene on metals is presented. Starting from the derivation of the electronic properties of an isolated graphene layer using the nearest neighbor tight-binding (TB) approximation for π and σ electrons, the TB model is then extended to third-nearest neighbors and interlayer coupling. The latter is relevant to few-layer graphene and graphite. Next, the conditions under which epitaxial graphene can be obtained by chemical vapor deposition are reviewed with a particular emphasis on the Ni(111) surface. Regarding functionalization, I first discuss the intercalation of monolayer Au into the graphene/Ni(111) interface, which renders graphene quasi-free-standing. The Au intercalated quasi-free-standing graphene is then the basis for chemical functionalization. Functionalization of graphene is classified into covalent, ionic and substitutional functionalization. As archetypical examples for these three possibilities I discuss covalent functionalization by hydrogen, ionic functionalization by alkali metals and substitutional functionalization by nitrogen heteroatoms.

Loving All Your Neighbors: Why Community Colleges Need the Academic Study of Religion

Science.gov (United States)

Maley, Melissa

2013-01-01

This chapter explains how the study of world religions prepares the community college student to become a better citizen, worker, and neighbor. The effective middle between the pitfalls of religious relativism and religious dominance in a world religions classroom is central to this discussion of teaching critical thinking, empathy, and…

Dose distribution in the thyroid and neighboring regions in therapy with 131I

International Nuclear Information System (INIS)

Monteiro, Rommel Barbosa; Bonifacio, Daniel Alexandre Baptista; Sa, Lidia Vasconcellos de

2013-01-01

In this work, simulations were performed with two types of computer simulators: the MIRD phantom and voxel phantom MASH, both of type adult male and in the standing position, coupled to the computational tool GATE (Geant4 Application for Tomographic Emission), to obtain the dose deposited in thyroid and neighboring regions

Instance Selection for Classifier Performance Estimation in Meta Learning

Directory of Open Access Journals (Sweden)

Marcin Blachnik

2017-11-01

Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.

The Lean Reference Collection: Improving Functionality through Selection and Weeding.

Science.gov (United States)

Nolan, Christopher W.

1991-01-01

Discusses references collections in academic libraries and offers guidelines for placing materials in a reference collection that focus on their suitability for true reference functions and the expected frequency of use. Problems with poorly managed collections are discussed, and the importance of selection policies and weeding are emphasized. (37…

A new approach to very short term wind speed prediction using k-nearest neighbor classification

International Nuclear Information System (INIS)

Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

2013-01-01

Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric

Selective Attention, Working Memory, and Executive Function as Potential Independent Sources of Cognitive Dysfunction in Schizophrenia.

Science.gov (United States)

Gold, James M; Robinson, Benjamin; Leonard, Carly J; Hahn, Britta; Chen, Shuo; McMahon, Robert P; Luck, Steven J

2017-11-11

People with schizophrenia demonstrate impairments in selective attention, working memory, and executive function. Given the overlap in these constructs, it is unclear if these represent distinct impairments or different manifestations of one higher-order impairment. To examine this question, we administered tasks from the basic cognitive neuroscience literature to measure visual selective attention, working memory capacity, and executive function in 126 people with schizophrenia and 122 healthy volunteers. Patients demonstrated deficits on all tasks with the exception of selective attention guided by strong bottom-up inputs. Although the measures of top-down control of selective attention, working memory, and executive function were all intercorrelated, several sources of evidence indicate that working memory and executive function are separate sources of variance. Specifically, both working memory and executive function independently contributed to the discrimination of group status and independently accounted for variance in overall general cognitive ability as assessed by the MATRICS battery. These two cognitive functions appear to be separable features of the cognitive impairments observed in schizophrenia. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells

Directory of Open Access Journals (Sweden)

Chao Liu

2018-04-01

Full Text Available The amplitude information (AI of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target’s state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR environment.

Recursive nearest neighbor search in a sparse and multiscale domain for comparing audio signals

DEFF Research Database (Denmark)

Sturm, Bob L.; Daudet, Laurent

2011-01-01

We investigate recursive nearest neighbor search in a sparse domain at the scale of audio signals. Essentially, to approximate the cosine distance between the signals we make pairwise comparisons between the elements of localized sparse models built from large and redundant multiscale dictionaries...

Generation of Cu–In alloy surfaces from CuInO2 as selective catalytic sites for CO2 electroreduction

KAUST Repository

Jedidi, Abdesslem

2015-08-11

The lack of availability of efficient, selective and stable electrocatalysts is a major hindrance for scalable CO2 reduction processes. Herein, we report the generation of Cu–In alloy surfaces for electrochemical reduction of CO2 from mixed metal oxides of CuInO2 as the starting material. The material successfully generates selective active sites to form CO from CO2 electroreduction at mild overpotentials. Density functional theory (DFT) indicates that the site occupation of the inert In occurs more on the specific sites of Cu. In addition, while In atoms do not preferentially adsorb H or CO, Cu atoms, which neighbor the In atoms, alters the preference of their adsorption. This preference for site occupation and altered adsorption may account for the improved selectivity over that observed for Cu metal. This study demonstrates an example of a scalable synthesis method of bimetallic surfaces utilized with the mixed oxide precursor having the diversity of metal choice, which may drastically alter the electrocatalytic performance, as presented herein.

Generation of Cu–In alloy surfaces from CuInO2 as selective catalytic sites for CO2 electroreduction

KAUST Repository

Jedidi, Abdesslem; Rasul, Shahid; Masih, Dilshad; Cavallo, Luigi; Takanabe, Kazuhiro

2015-01-01

The lack of availability of efficient, selective and stable electrocatalysts is a major hindrance for scalable CO2 reduction processes. Herein, we report the generation of Cu–In alloy surfaces for electrochemical reduction of CO2 from mixed metal oxides of CuInO2 as the starting material. The material successfully generates selective active sites to form CO from CO2 electroreduction at mild overpotentials. Density functional theory (DFT) indicates that the site occupation of the inert In occurs more on the specific sites of Cu. In addition, while In atoms do not preferentially adsorb H or CO, Cu atoms, which neighbor the In atoms, alters the preference of their adsorption. This preference for site occupation and altered adsorption may account for the improved selectivity over that observed for Cu metal. This study demonstrates an example of a scalable synthesis method of bimetallic surfaces utilized with the mixed oxide precursor having the diversity of metal choice, which may drastically alter the electrocatalytic performance, as presented herein.

Studying nearest neighbor correlations by atom probe tomography (APT) in metallic glasses as exemplified for Fe40Ni40B20 glassy ribbons

KAUST Repository

Shariq, Ahmed

2012-01-01

A next nearest neighbor evaluation procedure of atom probe tomography data provides distributions of the distances between atoms. The width of these distributions for metallic glasses studied so far is a few Angstrom reflecting the spatial resolution of the analytical technique. However, fitting Gaussian distributions to the distribution of atomic distances yields average distances with statistical uncertainties of 2 to 3 hundredth of an Angstrom. Fe 40Ni40B20 metallic glass ribbons are characterized this way in the as quenched state and for a state heat treated at 350 °C for 1 h revealing a change in the structure on the sub-nanometer scale. By applying the statistical tool of the χ2 test a slight deviation from a random distribution of B-atoms in the as quenched sample is perceived, whereas a pronounced elemental inhomogeneity of boron is detected for the annealed state. In addition, the distance distribution of the first fifteen atomic neighbors is determined by using this algorithm for both annealed and as quenched states. The next neighbor evaluation algorithm evinces a steric periodicity of the atoms when the next neighbor distances are normalized by the first next neighbor distance. A comparison of the nearest neighbor atomic distribution for as quenched and annealed state shows accumulation of Ni and B. Moreover, it also reveals the tendency of Fe and B to move slightly away from each other, an incipient step to Ni rich boride formation. © 2011 Elsevier B.V.

Selectivity control in pd-catalyzed c-h functionalization reactions

OpenAIRE

Flores Gaspar, Areli

2013-01-01

Benzocyclobutenones are an intriguing four-membered ring ketone. In the present thesis, we have developed a new protocol for selectively preparing benzocyclobutenones through intramolecular acylation of aryl bromides via palladium catalyzed C-H bond functionalization reactions based on rac-BINAP ligand. We also found that a subtle modification on the ligand backbone lead to a new catalytic manifold for preparing configurationally-pure styrene derivatives, when using dcpp (bis-dicyclohexylphos...

Measurement of near neighbor separations of surface atoms

International Nuclear Information System (INIS)

Cohen, P.I.

Two techniques are being developed to measure the nearest neighbor distances of atoms at the surfaces of solids. Both measures extended fine structure in the excitation probability of core level electrons which are excited by an incident electron beam. This is an important problem because the structures of most surface systems are as yet unknown, even though the location of surface atoms is the basis for any quantitative understanding of the chemistry and physics of surfaces and interfaces. These methods would allow any laboratory to make in situ determinations of surface structure in conjunction with most other laboratory probes of surfaces. Each of these two techniques has different advantages; further, the combination of the two will increase confidence in the results by reducing systematic error in the data analysis

Radiative energy loss of neighboring subjets arXiv

CERN Document Server

Mehtar-Tani, Yacine

We compute the in-medium energy loss probability distribution of two neighboring subjets at leading order, in the large-$N_c$ approximation. Our result exhibits a gradual onset of color decoherence of the system and accounts for two expected limiting cases. When the angular separation is smaller than the characteristic angle for medium-induced radiation, the two-pronged substructure lose energy coherently as a single color charge, namely that of the parent parton. At large angular separation the two subjets lose energy independently. Our result is a first step towards quantifying effects of energy loss as a result of the fluctuation of the multi-parton jet substructure and therefore goes beyond the standard approach to jet quenching based on single parton energy loss. We briefly discuss applications to jet observables in heavy-ion collisions.

Mapping DNA methylation by transverse current sequencing: Reduction of noise from neighboring nucleotides

Science.gov (United States)

Alvarez, Jose; Massey, Steven; Kalitsov, Alan; Velev, Julian

Nanopore sequencing via transverse current has emerged as a competitive candidate for mapping DNA methylation without needed bisulfite-treatment, fluorescent tag, or PCR amplification. By eliminating the error producing amplification step, long read lengths become feasible, which greatly simplifies the assembly process and reduces the time and the cost inherent in current technologies. However, due to the large error rates of nanopore sequencing, single base resolution has not been reached. A very important source of noise is the intrinsic structural noise in the electric signature of the nucleotide arising from the influence of neighboring nucleotides. In this work we perform calculations of the tunneling current through DNA molecules in nanopores using the non-equilibrium electron transport method within an effective multi-orbital tight-binding model derived from first-principles calculations. We develop a base-calling algorithm accounting for the correlations of the current through neighboring bases, which in principle can reduce the error rate below any desired precision. Using this method we show that we can clearly distinguish DNA methylation and other base modifications based on the reading of the tunneling current.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

Science.gov (United States)

Rivas, Elena; Lang, Raymond; Eddy, Sean R

2012-02-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

Neighboring Hetero-Atom Assistance of Sacrificial Amines to Hydrogen Evolution Using Pt-Loaded TiO2-Photocatalyst

Directory of Open Access Journals (Sweden)

Masahide Yasuda

2014-05-01

Full Text Available Photocatalytic H2 evolution was examined using Pt-loaded TiO2-photocatalyst in the presence of amines as sacrificial agents. In the case of amines with all of the carbon attached to the hetero-atom such as 2-aminoethanol, 1,2-diamonoethane, 2-amino-1,3-propanediol, and 3-amino-1,2-propanediol, they were completely decomposed into CO2 and water to quantitatively evolve H2. On the other hand, the amines with both hetero-atoms and one methyl group at the β-positions (neighboring carbons of amino group such as 2-amino-1-propanol and 1,2-diaminopropane were partially decomposed. Also, the photocatalytic H2 evolution using amines without the hetero-atoms at the β-positions such as ethylamine, propylamine, 1-butylamine, 1,3-diaminopropane, 2-propylamine, and 2-butylamine was inefficient. Thus, it was found that the neighboring hetero-atom strongly assisted the degradation of sacrificial amines. Moreover, rate constants for H2 evolution were compared among amines. In conclusion, the neighboring hetero-atom did not affect the rate constants but enhanced the yield of hydrogen evolution.

Using step and path selection functions for estimating resistance to movement: Pumas as a case study

Science.gov (United States)

Katherine A. Zeller; Kevin McGarigal; Samuel A. Cushman; Paul Beier; T. Winston Vickers; Walter M. Boyce

2015-01-01

GPS telemetry collars and their ability to acquire accurate and consistently frequent locations have increased the use of step selection functions (SSFs) and path selection functions (PathSFs) for studying animal movement and estimating resistance. However, previously published SSFs and PathSFs often do not accommodate multiple scales or multiscale modeling....

Thyroid monitoring for residents of disaster-affected and neighboring areas

International Nuclear Information System (INIS)

Ito, Shigeki

2014-01-01

The devastating environmental contamination caused by the nuclear disaster at the Fukushima Daiichi Nuclear Power Station of The Tokyo Electric Power Company is exposing the residents of the disaster-affected areas to health risks attributable to radiation exposure, and fear of the development of 131 I-induced thyroid cancer, which is a stochastic effect of radiation and is particularly high. As part of the response to nuclear disasters by the government of the municipality where the nuclear power station is located and in operation and by the governments of neighboring municipalities, it is necessary to conduct thyroid monitoring for the purpose of alleviating the fears of residents of the disaster-affected areas as well as those living in the contaminated, even if only slightly, neighboring areas (local residents). This health monitoring needs to be implemented without delay in the case of a disaster along with dissemination of a portable type thyroid monitoring system available at evacuation centers, etc. for assessing thyroid exposure doses. The establishment of a system for developing personnel ready to perform monitoring is also essential. Assessing thyroid exposure doses is indispensable as a means of assuring local residents not only of safety but also of security from the risks of radiation. To date, contamination has not been detected in people, except for residents contaminated by a large amount of iodine, by employing the mobile type of thyroid monitoring system. However, when local residents seeking security desire thyroid monitoring, it is preferable that a portable type simplified thyroid monitoring system be used as a means of ensuring security against radiation. (author)

Mapping change of older forest with nearest-neighbor imputation and Landsat time-series

Science.gov (United States)

Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang. Yang

2012-01-01

The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes...

Penerapan Metode K-nearest Neighbor pada Penentuan Grade Dealer Sepeda Motor

OpenAIRE

Leidiyana, Henny

2017-01-01

The mutually beneficial cooperation is a very important thing for a leasing and dealer. Incentives for marketing is given in order to get consumers as much as possible. But sometimes the surveyor objectivity is lost due to the conspiracy on the field of marketing and surveyors. To overcome this, leasing a variety of ways one of them is doing ranking against the dealer. In this study the application of the k-Nearest Neighbor method and Euclidean distance measurement to determine the grade deal...

Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

Directory of Open Access Journals (Sweden)

Cobaugh Christian W

2004-08-01

Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

Design and Discovery of Functionally Selective Serotonin 2C (5-HT2C) Receptor Agonists.

Science.gov (United States)

Cheng, Jianjun; McCorvy, John D; Giguere, Patrick M; Zhu, Hu; Kenakin, Terry; Roth, Bryan L; Kozikowski, Alan P

2016-11-10

On the basis of the structural similarity of our previous 5-HT 2C agonists with the melatonin receptor agonist tasimelteon and the putative biological cross-talk between serotonergic and melatonergic systems, a series of new (2,3-dihydro)benzofuran-based compounds were designed and synthesized. The compounds were evaluated for their selectivity toward 5-HT 2A , 5-HT 2B , and 5-HT 2C receptors in the calcium flux assay with the ultimate goal to generate selective 5-HT 2C agonists. Selected compounds were studied for their functional selectivity by comparing their transduction efficiency at the G protein signaling pathway versus β-arrestin recruitment. The most functionally selective compound (+)-7e produced weak β-arrestin recruitment and also demonstrated less receptor desensitization compared to serotonin in both calcium flux and phosphoinositide (PI) hydrolysis assays. We report for the first time that selective 5-HT 2C agonists possessing weak β-arrestin recruitment can produce distinct receptor desensitization properties.

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.

Science.gov (United States)

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.

Aesthetic Function Realized in the Selected Modern Chinese Essays by Zhang Peiji

Institute of Scientific and Technical Information of China (English)

罗丹

2014-01-01

The selected modern Chinese essays translated by Zhang Peiji is a masterpiece for Chinese scholars to do translation research. Prof. Zhang not only excels at translating the Chinese works accurately but also conveys the aesthetic value in the translated version. This paper wil analyse the aesthetic function used in Zhang Peiji’s selected modern Chinese essays from five aspects, music value, rhythm value, ful-grownness value, conciseness value and artistic conception value.

Política e cinema na era da Boa Vizinhança (1933-1945 * Policy and cinema at the age of the Good Neighbor (1933-1945

Directory of Open Access Journals (Sweden)

ISAIAS ALBERTIN DE MORAES

2015-03-01

Full Text Available Resumo: O presente artigo apresenta uma análise histórica da Política Externa de Boa Vizinhança para América Latina, particularmente no Brasil, e de sua principal instituição o Office of the coordinator of Inter-American Affairs (OCIAA, destacando sua divisão de cinema, a Motion Picture Division (MPD. Essas instituições são analisadas pelo enfoque teórico dos construtivistas modernistas-linguistas. Assim, o texto busca destacar a importância da construção de uma infraestrutura física, discursiva e humana com habilidade para selecionar, organizar, regular e redistribuir os discursos enunciados pela Política Externa de Boa Vizinhança no setor da indústria cinematográfica.Palavras-chave: Política Externa de Boa Vizinhança; Office of the coordinator of Inter-American Affairs; Motion Picture Division.  Abstract: This paper presents a historical analysis of the Good Neighbor Policy for Latin America, particularly in Brazil, and its main institution the Office of the coordinator of Inter-American Affairs (OCIAA, focusing on its film department, the Motion Picture Division (MPD. These institutions are analyzed by the theoretical approach of modernist linguists constructivists. So this text sought to highlight the importance of building a physical infrastructure, discursive and human with the ability to select, organize, regulate and redistribute the speeches set out by the Good Neighbor Policy in the film industry sector.Keywords: Good Neighbor Policy; Office of the coordinator of Inter-American Affairs; Motion Picture Division.

Functional connectivity of parietal cortex during temporal selective attention.

Science.gov (United States)

Tyler, Sarah C; Dasgupta, Samhita; Agosta, Sara; Battelli, Lorella; Grossman, Emily D

2015-04-01

Perception of natural experiences requires allocation of attention towards features, objects, and events that are moving and changing over time. This allocation of attention is controlled by large-scale brain networks that, when damaged, cause widespread cognitive deficits. In particular, damage to ventral parietal cortex (right lateralized TPJ, STS, supramarginal and angular gyri) is associated with failures to selectively attend to and isolate features embedded within rapidly changing visual sequences (Battelli, Pascual-Leone, & Cavanagh, 2007; Husain, Shapiro, Martin, & Kennard, 1997). In this study, we used fMRI to investigate the neural activity and functional connectivity of intact parietal cortex while typical subjects judged the relative onsets and offsets of rapidly flickering tokens (a phase discrimination task in which right parietal patients are impaired). We found two regions in parietal cortex correlated with task performance: a bilateral posterior TPJ (pTPJ) and an anterior right-lateralized TPJ (R aTPJ). Both regions were deactivated when subjects engaged in the task but showed different patterns of functional connectivity. The bilateral pTPJ was strongly connected to nodes within the default mode network (DMN) and the R aTPJ was connected to the attention network. Accurate phase discriminations were associated with increased functional correlations between sensory cortex (hMT+) and the bilateral pTPJ, whereas accuracy on a control task was associated with yoked activity in the hMT+ and the R aTPJ. We conclude that temporal selective attention is particularly sensitive for revealing information pathways between sensory and core cognitive control networks that, when damaged, can lead to nonspatial attention impairments in right parietal stroke patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Disordering scaling and generalized nearest-neighbor approach in the thermodynamics of Lennard-Jones systems

International Nuclear Information System (INIS)

Vorob'ev, V.S.

2003-01-01

We suggest a concept of multiple disordering scaling of the crystalline state. Such a scaling procedure applied to a crystal leads to the liquid and (in low density limit) gas states. This approach provides an explanation to a high value of configuration (common) entropy of liquefied noble gases, which can be deduced from experimental data. We use the generalized nearest-neighbor approach to calculate free energy and pressure of the Lennard-Jones systems after performing this scaling procedure. These thermodynamic functions depend on one parameter characterizing the disordering only. Condensed states of the system (liquid and solid) correspond to small values of this parameter. When this parameter tends to unity, we get an asymptotically exact equation of state for a gas involving the second virial coefficient. A reasonable choice of the values for the disordering parameter (ranging between zero and unity) allows us to find the lines of coexistence between different phase states in the Lennard-Jones systems, which are in a good agreement with the available experimental data

Selective oxidation of cyclohexene through gold functionalized silica monolith microreactors

Science.gov (United States)

Alotaibi, Mohammed T.; Taylor, Martin J.; Liu, Dan; Beaumont, Simon K.; Kyriakou, Georgios

2016-04-01

Two simple, reproducible methods of preparing evenly distributed Au nanoparticle containing mesoporous silica monoliths are investigated. These Au nanoparticle containing monoliths are subsequently investigated as flow reactors for the selective oxidation of cyclohexene. In the first strategy, the silica monolith was directly impregnated with Au nanoparticles during the formation of the monolith. The second approach was to pre-functionalize the monolith with thiol groups tethered within the silica mesostructure. These can act as evenly distributed anchors for the Au nanoparticles to be incorporated by flowing a Au nanoparticle solution through the thiol functionalized monolith. Both methods led to successfully achieving even distribution of Au nanoparticles along the length of the monolith as demonstrated by ICP-OES. However, the impregnation method led to strong agglomeration of the Au nanoparticles during subsequent heating steps while the thiol anchoring procedure maintained the nanoparticles in the range of 6.8 ± 1.4 nm. Both Au nanoparticle containing monoliths as well as samples with no Au incorporated were tested for the selective oxidation of cyclohexene under constant flow at 30 °C. The Au free materials were found to be catalytically inactive with Au being the minimum necessary requirement for the reaction to proceed. The impregnated Au-containing monolith was found to be less active than the thiol functionalized Au-containing material, attributable to the low metal surface area of the Au nanoparticles. The reaction on the thiol functionalized Au-containing monolith was found to depend strongly on the type of oxidant used: tert-butyl hydroperoxide (TBHP) was more active than H2O2, likely due to the thiol induced hydrophobicity in the monolith.

Moderate-resolution data and gradient nearest neighbor imputation for regional-national risk assessment

Science.gov (United States)

Kenneth B. Jr. Pierce; C. Kenneth Brewer; Janet L. Ohmann

2010-01-01

This study was designed to test the feasibility of combining a method designed to populate pixels with inventory plot data at the 30-m scale with a new national predictor data set. The new national predictor data set was developed by the USDA Forest Service Remote Sensing Applications Center (hereafter RSAC) at the 250-m scale. Gradient Nearest Neighbor (GNN)...

An SDN-Based Authentication Mechanism for Securing Neighbor Discovery Protocol in IPv6

Directory of Open Access Journals (Sweden)

Yiqin Lu

2017-01-01

Full Text Available The Neighbor Discovery Protocol (NDP is one of the main protocols in the Internet Protocol version 6 (IPv6 suite, and it provides many basic functions for the normal operation of IPv6 in a local area network (LAN, such as address autoconfiguration and address resolution. However, it has many vulnerabilities that can be used by malicious nodes to launch attacks, because the NDP messages are easily spoofed without protection. Surrounding this problem, many solutions have been proposed for securing NDP, but these solutions either proposed new protocols that need to be supported by all nodes or built mechanisms that require the cooperation of all nodes, which is inevitable in the traditional distributed networks. Nevertheless, Software-Defined Networking (SDN provides a new perspective to think about protecting NDP. In this paper, we proposed an SDN-based authentication mechanism to verify the identity of NDP packets transmitted in a LAN. Using the centralized control and programmability of SDN, it can effectively prevent the spoofing attacks and other derived attacks based on spoofing. In addition, this mechanism needs no additional protocol supporting or configuration at hosts and routers and does not introduce any dedicated devices.

Local Order in the Unfolded State: Conformational Biases and Nearest Neighbor Interactions

Directory of Open Access Journals (Sweden)

Siobhan Toal

2014-07-01

Full Text Available The discovery of Intrinsically Disordered Proteins, which contain significant levels of disorder yet perform complex biologically functions, as well as unwanted aggregation, has motivated numerous experimental and theoretical studies aimed at describing residue-level conformational ensembles. Multiple lines of evidence gathered over the last 15 years strongly suggest that amino acids residues display unique and restricted conformational preferences in the unfolded state of peptides and proteins, contrary to one of the basic assumptions of the canonical random coil model. To fully understand residue level order/disorder, however, one has to gain a quantitative, experimentally based picture of conformational distributions and to determine the physical basis underlying residue-level conformational biases. Here, we review the experimental, computational and bioinformatic evidence for conformational preferences of amino acid residues in (mostly short peptides that can be utilized as suitable model systems for unfolded states of peptides and proteins. In this context particular attention is paid to the alleged high polyproline II preference of alanine. We discuss how these conformational propensities may be modulated by peptide solvent interactions and so called nearest-neighbor interactions. The relevance of conformational propensities for the protein folding problem and the understanding of IDPs is briefly discussed.

The N400 as a snapshot of interactive processing: evidence from regression analyses of orthographic neighbor and lexical associate effects

Science.gov (United States)

Laszlo, Sarah; Federmeier, Kara D.

2010-01-01

Linking print with meaning tends to be divided into subprocesses, such as recognition of an input's lexical entry and subsequent access of semantics. However, recent results suggest that the set of semantic features activated by an input is broader than implied by a view wherein access serially follows recognition. EEG was collected from participants who viewed items varying in number and frequency of both orthographic neighbors and lexical associates. Regression analysis of single item ERPs replicated past findings, showing that N400 amplitudes are greater for items with more neighbors, and further revealed that N400 amplitudes increase for items with more lexical associates and with higher frequency neighbors or associates. Together, the data suggest that in the N400 time window semantic features of items broadly related to inputs are active, consistent with models in which semantic access takes place in parallel with stimulus recognition. PMID:20624252

Positive selection in octopus haemocyanin indicates functional links to temperature adaptation.

Science.gov (United States)

Oellermann, Michael; Strugnell, Jan M; Lieb, Bernhard; Mark, Felix C

2015-07-05

Octopods have successfully colonised the world's oceans from the tropics to the poles. Yet, successful persistence in these habitats has required adaptations of their advanced physiological apparatus to compensate impaired oxygen supply. Their oxygen transporter haemocyanin plays a major role in cold tolerance and accordingly has undergone functional modifications to sustain oxygen release at sub-zero temperatures. However, it remains unknown how molecular properties evolved to explain the observed functional adaptations. We thus aimed to assess whether natural selection affected molecular and structural properties of haemocyanin that explains temperature adaptation in octopods. Analysis of 239 partial sequences of the haemocyanin functional units (FU) f and g of 28 octopod species of polar, temperate, subtropical and tropical origin revealed natural selection was acting primarily on charge properties of surface residues. Polar octopods contained haemocyanins with higher net surface charge due to decreased glutamic acid content and higher numbers of basic amino acids. Within the analysed partial sequences, positive selection was present at site 2545, positioned between the active copper binding centre and the FU g surface. At this site, methionine was the dominant amino acid in polar octopods and leucine was dominant in tropical octopods. Sites directly involved in oxygen binding or quaternary interactions were highly conserved within the analysed sequence. This study has provided the first insight into molecular and structural mechanisms that have enabled octopods to sustain oxygen supply from polar to tropical conditions. Our findings imply modulation of oxygen binding via charge-charge interaction at the protein surface, which stabilize quaternary interactions among functional units to reduce detrimental effects of high pH on venous oxygen release. Of the observed partial haemocyanin sequence, residue 2545 formed a close link between the FU g surface and the

Anderson localization in one-dimensional quasiperiodic lattice models with nearest- and next-nearest-neighbor hopping

International Nuclear Information System (INIS)

Gong, Longyan; Feng, Yan; Ding, Yougen

2017-01-01

Highlights: • Quasiperiodic lattice models with next-nearest-neighbor hopping are studied. • Shannon information entropies are used to reflect state localization properties. • Phase diagrams are obtained for the inverse bronze and golden means, respectively. • Our studies present a more complete picture than existing works. - Abstract: We explore the reduced relative Shannon information entropies SR for a quasiperiodic lattice model with nearest- and next-nearest-neighbor hopping, where an irrational number is in the mathematical expression of incommensurate on-site potentials. Based on SR, we respectively unveil the phase diagrams for two irrationalities, i.e., the inverse bronze mean and the inverse golden mean. The corresponding phase diagrams include regions of purely localized phase, purely delocalized phase, pure critical phase, and regions with mobility edges. The boundaries of different regions depend on the values of irrational number. These studies present a more complete picture than existing works.

Anderson localization in one-dimensional quasiperiodic lattice models with nearest- and next-nearest-neighbor hopping

Energy Technology Data Exchange (ETDEWEB)

Gong, Longyan, E-mail: lygong@njupt.edu.cn [Information Physics Research Center and Department of Applied Physics, Nanjing University of Posts and Telecommunications, Nanjing, 210003 (China); Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing, 210003 (China); National Laboratory of Solid State Microstructures, Nanjing University, Nanjing 210093 (China); Feng, Yan; Ding, Yougen [Information Physics Research Center and Department of Applied Physics, Nanjing University of Posts and Telecommunications, Nanjing, 210003 (China); Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing, 210003 (China)

2017-02-12

Highlights: • Quasiperiodic lattice models with next-nearest-neighbor hopping are studied. • Shannon information entropies are used to reflect state localization properties. • Phase diagrams are obtained for the inverse bronze and golden means, respectively. • Our studies present a more complete picture than existing works. - Abstract: We explore the reduced relative Shannon information entropies SR for a quasiperiodic lattice model with nearest- and next-nearest-neighbor hopping, where an irrational number is in the mathematical expression of incommensurate on-site potentials. Based on SR, we respectively unveil the phase diagrams for two irrationalities, i.e., the inverse bronze mean and the inverse golden mean. The corresponding phase diagrams include regions of purely localized phase, purely delocalized phase, pure critical phase, and regions with mobility edges. The boundaries of different regions depend on the values of irrational number. These studies present a more complete picture than existing works.

Morphological type correlation between nearest neighbor pairs of galaxies

Science.gov (United States)

Yamagata, Tomohiko

1990-01-01

Although the morphological type of galaxies is one of the most fundamental properties of galaxies, its origin and evolutionary processes, if any, are not yet fully understood. It has been established that the galaxy morphology strongly depends on the environment in which the galaxy resides (e.g., Dressler 1980). Galaxy pairs correspond to the smallest scales of galaxy clustering and may provide important clues to how the environment influences the formation and evolution of galaxies. Several investigators pointed out that there is a tendency for pair galaxies to have similar morphological types (Karachentsev and Karachentseva 1974, Page 1975, Noerdlinger 1979). Here, researchers analyze morphological type correlation for 18,364 nearest neighbor pairs of galaxies identified in the magnetic tape version of the Center for Astrophysics Redshift Catalogue.

The square Ising model with second-neighbor interactions and the Ising chain in a transverse field

International Nuclear Information System (INIS)

Grynberg, M.D.; Tanatar, B.

1991-06-01

We consider the thermal and critical behaviour of the square Ising lattice with frustrated first - and second-neighbor interactions. A low-temperature domain wall analysis including kinks and dislocations shows that there is a close relation between this classical model and the Hamiltonian of an Ising chain in a transverse field provided that the ratio of the next-nearest to nearest-neighbor coupling, is close to 1/2. Due to the field inversion symmetry of the Ising chain Hamiltonian, the thermal properties of the classical system are symmetrical with respect to this coupling ratio. In the neighborhood of this regime critical exponents of the model turn out to belong to the Ising universality class. Our results are compared with previous Monte Carlo simulations. (author). 23 refs, 6 figs

Structure-Guided Screening for Functionally Selective D2 Dopamine Receptor Ligands from a Virtual Chemical Library.

Science.gov (United States)

Männel, Barbara; Jaiteh, Mariama; Zeifman, Alexey; Randakova, Alena; Möller, Dorothee; Hübner, Harald; Gmeiner, Peter; Carlsson, Jens

2017-10-20

Functionally selective ligands stabilize conformations of G protein-coupled receptors (GPCRs) that induce a preference for signaling via a subset of the intracellular pathways activated by the endogenous agonists. The possibility to fine-tune the functional activity of a receptor provides opportunities to develop drugs that selectively signal via pathways associated with a therapeutic effect and avoid those causing side effects. Animal studies have indicated that ligands displaying functional selectivity at the D 2 dopamine receptor (D 2 R) could be safer and more efficacious drugs against neuropsychiatric diseases. In this work, computational design of functionally selective D 2 R ligands was explored using structure-based virtual screening. Molecular docking of known functionally selective ligands to a D 2 R homology model indicated that such compounds were anchored by interactions with the orthosteric site and extended into a common secondary pocket. A tailored virtual library with close to 13 000 compounds bearing 2,3-dichlorophenylpiperazine, a privileged orthosteric scaffold, connected to diverse chemical moieties via a linker was docked to the D 2 R model. Eighteen top-ranked compounds that occupied both the orthosteric and allosteric site were synthesized, leading to the discovery of 16 partial agonists. A majority of the ligands had comparable maximum effects in the G protein and β-arrestin recruitment assays, but a subset displayed preference for a single pathway. In particular, compound 4 stimulated β-arrestin recruitment (EC 50 = 320 nM, E max = 16%) but had no detectable G protein signaling. The use of structure-based screening and virtual libraries to discover GPCR ligands with tailored functional properties will be discussed.

Ion-selective electrodes in organic elemental and functional group analysis: a review

Energy Technology Data Exchange (ETDEWEB)

Selig, W.

1977-11-08

The literature on the use of ion-selective electrodes in organic elemental and functional group analysis is surveyed in some detail. The survey is complete through Chemical Abstracts, Vol. 83 (1975). 40 figures, 52 tables, 236 references.

Ion-selective electrodes in organic elemental and functional group analysis: a review

International Nuclear Information System (INIS)

Selig, W.

1977-01-01

The literature on the use of ion-selective electrodes in organic elemental and functional group analysis is surveyed in some detail. The survey is complete through Chemical Abstracts, Vol. 83 (1975). 40 figures, 52 tables, 236 references

Aripiprazole, A Drug that Displays Partial Agonism and Functional Selectivity.

Science.gov (United States)

Tuplin, Erin W; Holahan, Matthew R

2017-11-14

The treatment of schizophrenia is challenging due to the wide range of symptoms (positive, negative, cognitive) associated with the disease. Typical antipsychotics that antagonize D2 receptors are effective in treating positive symptoms, but extrapyramidal side-effects (EPS) are a common occurrence. Atypical antipsychotics targeting 5-HT2A and D2 receptors are more effective at treating cognitive and negative symptoms compared to typical antipsychotics, but these drugs also result in side-effects such as metabolic syndromes. To identify evidence in the literature that elucidates the pharmacological profile of aripiprazole.s. We searched PubMed for peer reviewed articles on aripiprazole and its clinical efficacy, side-effects, pharmacology, and effects in animal models of schizophrenia symptoms. Aripiprazole is a newer atypical antipsychotic that displays a unique pharmacological profile, including partial D2 agonism and functionally selective properties. Aripiprazole is effective at treating the positive symptoms of schizophrenia and has the potential to treat negative and cognitive symptoms at least as well as other atypical antipsychotics. The drug has a favorable side-effect profile and has a low propensity to result in EPS or metabolic syndromes. Animal models of schizophrenia have been used to determine the efficacy of aripiprazole in symptom management. In these instances, aripiprazole resulted in the reversal of deficits in extinction, pre-pulse inhibition, and social withdrawal. Because aripiprazole requires a greater than 90% occupancy rate at D2 receptors to be clinically active and does not produce EPS, this suggests a functionally selective effect on intracellular signaling pathways. A combination of factors such as dopamine system stabilization via partial agonism, functional selectivity at D2 receptors, and serotonin-dopamine system interaction may contribute to the ability of aripiprazole to successfully manage schizophrenia symptoms. This review

A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

Science.gov (United States)

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

Aiming at efficient data condensation and improving accuracy, this paper presents a hardware-friendly template reduction (TR) method for the nearest neighbor (NN) classifiers by introducing the concept of critical boundary vectors. A hardware system is also implemented to demonstrate the feasibility of using an field-programmable gate array (FPGA) to accelerate the proposed method. Initially, k -means centers are used as substitutes for the entire template set. Then, to enhance the classification performance, critical boundary vectors are selected by a novel learning algorithm, which is completed within a single iteration. Moreover, to remove noisy boundary vectors that can mislead the classification in a generalized manner, a global categorization scheme has been explored and applied to the algorithm. The global characterization automatically categorizes each classification problem and rapidly selects the boundary vectors according to the nature of the problem. Finally, only critical boundary vectors and k -means centers are used as the new template set for classification. Experimental results for 24 data sets show that the proposed algorithm can effectively reduce the number of template vectors for classification with a high learning speed. At the same time, it improves the accuracy by an average of 2.17% compared with the traditional NN classifiers and also shows greater accuracy than seven other TR methods. We have shown the feasibility of using a proof-of-concept FPGA system of 256 64-D vectors to accelerate the proposed method on hardware. At a 50-MHz clock frequency, the proposed system achieves a 3.86 times higher learning speed than on a 3.4-GHz PC, while consuming only 1% of the power of that used by the PC.

Comparing the Selected Transfer Functions and Local Optimization Methods for Neural Network Flood Runoff Forecast

Directory of Open Access Journals (Sweden)

Petr Maca

2014-01-01

Full Text Available The presented paper aims to analyze the influence of the selection of transfer function and training algorithms on neural network flood runoff forecast. Nine of the most significant flood events, caused by the extreme rainfall, were selected from 10 years of measurement on small headwater catchment in the Czech Republic, and flood runoff forecast was investigated using the extensive set of multilayer perceptrons with one hidden layer of neurons. The analyzed artificial neural network models with 11 different activation functions in hidden layer were trained using 7 local optimization algorithms. The results show that the Levenberg-Marquardt algorithm was superior compared to the remaining tested local optimization methods. When comparing the 11 nonlinear transfer functions, used in hidden layer neurons, the RootSig function was superior compared to the rest of analyzed activation functions.

Designing lattice structures with maximal nearest-neighbor entanglement

Energy Technology Data Exchange (ETDEWEB)

Navarro-Munoz, J C; Lopez-Sandoval, R [Instituto Potosino de Investigacion CientIfica y Tecnologica, Camino a la presa San Jose 2055, 78216 San Luis Potosi (Mexico); Garcia, M E [Theoretische Physik, FB 18, Universitaet Kassel and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), Heinrich-Plett-Str.40, 34132 Kassel (Germany)

2009-08-07

In this paper, we study the numerical optimization of nearest-neighbor concurrence of bipartite one- and two-dimensional lattices, as well as non-bipartite two-dimensional lattices. These systems are described in the framework of a tight-binding Hamiltonian while the optimization of concurrence was performed using genetic algorithms. Our results show that the concurrence of the optimized lattice structures is considerably higher than that of non-optimized systems. In the case of one-dimensional chains, the concurrence increases dramatically when the system begins to dimerize, i.e., it undergoes a structural phase transition (Peierls distortion). This result is consistent with the idea that entanglement is maximal or shows a singularity near quantum phase transitions. Moreover, the optimization of concurrence in two-dimensional bipartite and non-bipartite lattices is achieved when the structures break into smaller subsystems, which are arranged in geometrically distinguishable configurations.

Magneto-structural correlations in trinuclear Cu(II) complexes: a density functional study

CERN Document Server

Rodríguez-Forteá, A; Alvarez, S; Centre-De Recera-En-Quimica-Teorica; Alemany, P A; Centre-De Recera-En-Quimica-Teorica

2003-01-01

Density functional theoretical methods have been used to study magneto-structural correlations for linear trinuclear hydroxo-bridged copper(II) complexes. The nearest-neighbor exchange coupling constant shows very similar trends to those found earlier for dinuclear compounds for which the Cu-O-Cu angle and the out of plane displacement of the hydrogen atoms at the bridge are the two key structural factors that determine the nature of their magnetic behavior. Changes in these two parameters can induce variations of over 1000 cm sup - sup 1 in the value of the nearest-neighbor coupling constant. On the contrary, coupling between next-nearest neighbors is found to be practically independent of structural changes with a value for the coupling constant of about -60 cm sup - sup 1. The magnitude calculated for this coupling constant indicates that considering its value to be negligible, as usually done in experimental studies, can lead to considerable errors, especially for compounds in which the nearest-neighbor c...

The Tragedy of Your Upstairs Neighbors: Is the Airbnb Negative Externality Internalized?

OpenAIRE

Horton, John J.

2015-01-01

A commonly expressed concern about the rise of the peer-to-peer rental market Airbnb is that hosts---those renting out their properties---impose costs on their unwitting neighbors. I consider the question of whether apartment building owners will, in a competitive rental market, set a building-specific Airbnb hosting policy that is socially efficient. I find that if tenants can sort across apartments based on the owners policy then the equilibrium fraction of buildings allowing Airbnb listing...

A selective iodide ion sensor electrode based on functionalized ZnO nanotubes.

Science.gov (United States)

Ibupoto, Zafar Hussain; Khun, Kimleang; Willander, Magnus

2013-02-04

In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF) was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10-6 to 1 × 10-1 M) and excellent sensitivity of -62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10-7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.

A Selective Iodide Ion Sensor Electrode Based on Functionalized ZnO Nanotubes

Directory of Open Access Journals (Sweden)

Magnus Willander

2013-02-01

Full Text Available In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10−6 to 1 × 10−1 M and excellent sensitivity of –62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10−7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.

Interacting Effects Induced by Two Neighboring Pits Considering Relative Position Parameters and Pit Depth

Directory of Open Access Journals (Sweden)

Yongfang Huang

2017-04-01

Full Text Available For pre-corroded aluminum alloy 7075-T6, the interacting effects of two neighboring pits on the stress concentration are comprehensively analyzed by considering various relative position parameters (inclination angle θ and dimensionless spacing parameter λ and pit depth (d with the finite element method. According to the severity of the stress concentration, the critical corrosion regions, bearing high susceptibility to fatigue damage, are determined for intersecting and adjacent pits, respectively. A straightforward approach is accordingly proposed to conservatively estimate the combined stress concentration factor induced by two neighboring pits, and a concrete application example is presented. It is found that for intersecting pits, the normalized stress concentration factor Ktnor increases with the increase of θ and λ and always reaches its maximum at θ = 90°, yet for adjacent pits, Ktnor decreases with the increase of λ and the maximum value appears at a slight asymmetric location. The simulations reveal that Ktnor follows a linear and an exponential relationship with the dimensionless depth parameter Rd for intersecting and adjacent cases, respectively.

Data delivery method based on neighbor nodes' information in a mobile ad hoc network.

Science.gov (United States)

Kashihara, Shigeru; Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

2014-01-01

This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

Data Delivery Method Based on Neighbor Nodes’ Information in a Mobile Ad Hoc Network

Directory of Open Access Journals (Sweden)

Shigeru Kashihara

2014-01-01

Full Text Available This paper proposes a data delivery method based on neighbor nodes’ information to achieve reliable communication in a mobile ad hoc network (MANET. In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE, Chachulski et al. (2007, improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

Energy Technology Data Exchange (ETDEWEB)

Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng [Jiangnan University, Wuxi (China)

2014-11-15

The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy.

Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

International Nuclear Information System (INIS)

Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng

2014-01-01

The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

Energy Technology Data Exchange (ETDEWEB)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

International Nuclear Information System (INIS)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features

Effects of selective REM sleep deprivation on prefrontal gamma activity and executive functions.

Science.gov (United States)

Corsi-Cabrera, M; Rosales-Lagarde, A; del Río-Portilla, Y; Sifuentes-Ortega, R; Alcántara-Quintero, B

2015-05-01

Given that the dorsolateral prefrontal cortex is involved in executive functions and is deactivated and decoupled from posterior associative regions during REM sleep, that Gamma temporal coupling involved in information processing is enhanced during REM sleep, and that adult humans spend about 90 min of every 24h in REM sleep, it might be expected that REM sleep deprivation would modify Gamma temporal coupling and have a deteriorating effect on executive functions. We analyzed EEG Gamma activity and temporal coupling during implementation of a rule-guided task before and after REM sleep deprivation and its effect on verbal fluency, flexible thinking and selective attention. After two nights in the laboratory for adaptation, on the third night subjects (n=18) were randomly assigned to either selective REM sleep deprivation effectuated by awakening them at each REM sleep onset or, the same number of NREM sleep awakenings as a control for unspecific effects of sleep interruptions. Implementation of abstract rules to guide behavior required greater activation and synchronization of Gamma activity in the frontopolar regions after REM sleep reduction from 20.6% at baseline to just 3.93% of total sleep time. However, contrary to our hypothesis, both groups showed an overall improvement in executive task performance and no effect on their capacity to sustain selective attention. These results suggest that after one night of selective REM sleep deprivation executive functions can be compensated by increasing frontal activation and they still require the participation of supervisory control by frontopolar regions. Copyright © 2015 Elsevier B.V. All rights reserved.

Hemichannels: new roles in astroglial function

Directory of Open Access Journals (Sweden)

Jimmy eStehberg

2014-06-01

Full Text Available The role of astrocytes in brain function has evolved over the last decade, from support cells to active participants in the neuronal synapse through the release of gliotransmitters. Astrocytes express receptors for most neurotransmitters and respond to them through Ca2+ intracellular oscillations and propagation of intercellular Ca2+ waves. While such waves are able to propagate among neighboring astrocytes through gap junctions, thereby activating several astrocytes simultaneously, they can also trigger the release of gliotransmitters, including glutamate, d-serine, glycine, ATP, adenosine or GABA. There are several mechanisms by which gliotransmitter release occurs, including functional hemichannels. These gliotransmitters can activate neighboring astrocytes and participate in the propagation of intercellular Ca2+ waves, or activate pre- and post-synaptic receptors, including NMDA, AMPA and purinergic receptors. In consequence, hemichannels could play a pivotal role in astrocyte-to-astrocyte communication and astrocyte-to-neuron cross-talk. Recent evidence suggests that astroglial hemichannels are involved in higher brain functions including memory and glucose sensing. The present review will focus on the role of hemichannels in astrocyte-to-astrocyte and astrocyte-to neuron communication and in brain physiology.

Probability distributions for first neighbor distances between resonances that belong to two different families

International Nuclear Information System (INIS)

Difilippo, F.C.

1994-01-01

For a mixture of two families of resonances, we found the probability distribution for the distance, as first neighbors, between resonances that belong to different families. Integration of this distribution gives the probability of accidental overlapping of resonances of one isotope by resonances of the other, provided that the resonances of each isotope belong to a single family. (author)

featsel: A framework for benchmarking of feature selection algorithms and cost functions

OpenAIRE

Marcelo S. Reis; Gustavo Estrela; Carlos Eduardo Ferreira; Junior Barrera

2017-01-01

In this paper, we introduce featsel, a framework for benchmarking of feature selection algorithms and cost functions. This framework allows the user to deal with the search space as a Boolean lattice and has its core coded in C++ for computational efficiency purposes. Moreover, featsel includes Perl scripts to add new algorithms and/or cost functions, generate random instances, plot graphs and organize results into tables. Besides, this framework already comes with dozens of algorithms and co...

Enhanced Approximate Nearest Neighbor via Local Area Focused Search.

Energy Technology Data Exchange (ETDEWEB)

Gonzales, Antonio [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Blazier, Nicholas Paul [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

Approximate Nearest Neighbor (ANN) algorithms are increasingly important in machine learning, data mining, and image processing applications. There is a large family of space- partitioning ANN algorithms, such as randomized KD-Trees, that work well in practice but are limited by an exponential increase in similarity comparisons required to optimize recall. Additionally, they only support a small set of similarity metrics. We present Local Area Fo- cused Search (LAFS), a method that enhances the way queries are performed using an existing ANN index. Instead of a single query, LAFS performs a number of smaller (fewer similarity comparisons) queries and focuses on a local neighborhood which is refined as candidates are identified. We show that our technique improves performance on several well known datasets and is easily extended to general similarity metrics using kernel projection techniques.

Improved Fuzzy K-Nearest Neighbor Using Modified Particle Swarm Optimization

Science.gov (United States)

Jamaluddin; Siringoringo, Rimbun

2017-12-01

Fuzzy k-Nearest Neighbor (FkNN) is one of the most powerful classification methods. The presence of fuzzy concepts in this method successfully improves its performance on almost all classification issues. The main drawbackof FKNN is that it is difficult to determine the parameters. These parameters are the number of neighbors (k) and fuzzy strength (m). Both parameters are very sensitive. This makes it difficult to determine the values of ‘m’ and ‘k’, thus making FKNN difficult to control because no theories or guides can deduce how proper ‘m’ and ‘k’ should be. This study uses Modified Particle Swarm Optimization (MPSO) to determine the best value of ‘k’ and ‘m’. MPSO is focused on the Constriction Factor Method. Constriction Factor Method is an improvement of PSO in order to avoid local circumstances optima. The model proposed in this study was tested on the German Credit Dataset. The test of the data/The data test has been standardized by UCI Machine Learning Repository which is widely applied to classification problems. The application of MPSO to the determination of FKNN parameters is expected to increase the value of classification performance. Based on the experiments that have been done indicating that the model offered in this research results in a better classification performance compared to the Fk-NN model only. The model offered in this study has an accuracy rate of 81%, while. With using Fk-NN model, it has the accuracy of 70%. At the end is done comparison of research model superiority with 2 other classification models;such as Naive Bayes and Decision Tree. This research model has a better performance level, where Naive Bayes has accuracy 75%, and the decision tree model has 70%

Chinese Function Manager of 2006 Partenariat Comments on the Selection Principle for Chinese Enterprises

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

@@ Fang Lei, EU-China Partenariat 2006Function Manager for Chinese Host Companies, worked together with Mr. Richard Morgan, EU Project Expert,Mr. Han Meiqing, Chinese Project Expert in the primary selection of Chinese enterprises.In reply to the strong request of the relevant governmental institutions, CCPIT and enterprises, he gave the following introductions about the details of selection.

Impact parameter and source selected correlation functions with a 4π multidetector

International Nuclear Information System (INIS)

Gourio, D.; Reposeur, T.; Assenard, M.; Germain, M.; Ardouin, D.; Eudes, P.; Lautridou, P.; Laville, J.L.; Lebrun, C.; Metivier, V.

1997-01-01

For the first time in the domain of (light charged) particle interferometry in nuclear physics, a complete study of proton an deuteron correlation functions is presented with both impact parameter and emission source selections. The correlations were determined for the system 129 Xe + nat Sn at 45 and 50 AMeV using the 4π multidetector INDRA at GANIL as an event selector as well as a particle correlator. Very short emission times are found for all the selections indicating possible contributions from a fast and preequilibrium process. (author)

Higher-Order Hierarchical Legendre Basis Functions in Applications

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter

2007-01-01

The higher-order hierarchical Legendre basis functions have been developed for effective solution of integral equations with the method of moments. They are derived from orthogonal Legendre polynomials modified to enforce normal continuity between neighboring mesh elements, while preserving a high...

The effect of near laterally and vertically neighboring quantum dots on the composition of uncapped InxGa1−xAs/GaAs quantum dots

International Nuclear Information System (INIS)

Donglin, Wang; Zhongyuan, Yu; Yumin, Liu; Han, Ye; Pengfei, Lu; Xiaotao, Guo; Long, Zhao; Xia, Xin

2010-01-01

The composition of quantum dots has a direct effect on the optical and electronic properties of quantum-dot-based devices. In this paper, we combine the method of moving asymptotes and finite element tools to compute the composition distribution by minimizing the Gibbs free energy of quantum dots, and use this method to study the effect of near laterally and vertically neighboring quantum dots on the composition distribution. The simulation results indicate that the effect from the laterally neighboring quantum dot is very small, and the vertically neighboring quantum dot can significantly influence the composition by the coupled strain field

Structural and functional imaging: Particularities in children

International Nuclear Information System (INIS)

Chiron, C.; Hertz-Pannier, L.; Chiron, C.; Hertz-Pannier, L.; Chiron, C.; Hertz-Pannier, L.

2008-01-01

Surgery of partial epilepsies in childhood has largely benefited from the recent advances of imaging techniques, which carry a triple goal: (1) to contribute to the localization of the epilepsy onset zone, (2) to detect and delineate an underlying lesion, and (3) to study the spatial relationship between the epileptogenic zone and the neighboring functional cortex, in order to select patients and plan the resection. This noninvasive pre-surgical imaging workup must be compared to clinical and electrical data to estimate the postoperative prognosis, while invasive techniques such as SEEG, cortical stimulations, and IAT often remain indispensable in difficult cases, i.e., in cryptogenic epilepsies. As in adults, advances in MRI allow us to detect more and more subtle underlying lesions, but this requires repeating MR studies during early childhood and using adapted sequence parameters to account for ongoing myelination. Ictal SPECT and PET imaging prove especially useful in planning depth electrode placement when video-EEG is not contributive, when MRI looks normal or shows multiple abnormalities, or in cases of discrepant findings. Multimodal imaging greatly enhances the sensitivity of all of these techniques. Finally, functional MRI of motor and language functions provide noninvasive cortical mapping of essential functions, using age-adapted paradigms, in cooperating children from age five to six and from IQs around 60. (authors)

Structural and functional imaging: Particularities in children

Energy Technology Data Exchange (ETDEWEB)

Chiron, C.; Hertz-Pannier, L. [Hop Necker Enfants Malad, INSERM, Serv Neuropediat, U663, F-75015 Paris (France); Chiron, C.; Hertz-Pannier, L. [UnivParis 05, F-75005 Paris (France); Chiron, C.; Hertz-Pannier, L. [CEA, I2BM, Neurospin, SHFJ, F-91191 Orsay (France)

2008-07-01

Surgery of partial epilepsies in childhood has largely benefited from the recent advances of imaging techniques, which carry a triple goal: (1) to contribute to the localization of the epilepsy onset zone, (2) to detect and delineate an underlying lesion, and (3) to study the spatial relationship between the epileptogenic zone and the neighboring functional cortex, in order to select patients and plan the resection. This noninvasive pre-surgical imaging workup must be compared to clinical and electrical data to estimate the postoperative prognosis, while invasive techniques such as SEEG, cortical stimulations, and IAT often remain indispensable in difficult cases, i.e., in cryptogenic epilepsies. As in adults, advances in MRI allow us to detect more and more subtle underlying lesions, but this requires repeating MR studies during early childhood and using adapted sequence parameters to account for ongoing myelination. Ictal SPECT and PET imaging prove especially useful in planning depth electrode placement when video-EEG is not contributive, when MRI looks normal or shows multiple abnormalities, or in cases of discrepant findings. Multimodal imaging greatly enhances the sensitivity of all of these techniques. Finally, functional MRI of motor and language functions provide noninvasive cortical mapping of essential functions, using age-adapted paradigms, in cooperating children from age five to six and from IQs around 60. (authors)

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

Science.gov (United States)

Chakraborty, Shankar; Prasad, Kanika

2018-06-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

Science.gov (United States)

Chakraborty, Shankar; Prasad, Kanika

2018-01-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

Comparison of feature selection and classification for MALDI-MS data

Directory of Open Access Journals (Sweden)

Yang Mary

2009-07-01

Full Text Available Abstract Introduction In the classification of Mass Spectrometry (MS proteomics data, peak detection, feature selection, and learning classifiers are critical to classification accuracy. To better understand which methods are more accurate when classifying data, some publicly available peak detection algorithms for Matrix assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS data were recently compared; however, the issue of different feature selection methods and different classification models as they relate to classification performance has not been addressed. With the application of intelligent computing, much progress has been made in the development of feature selection methods and learning classifiers for the analysis of high-throughput biological data. The main objective of this paper is to compare the methods of feature selection and different learning classifiers when applied to MALDI-MS data and to provide a subsequent reference for the analysis of MS proteomics data. Results We compared a well-known method of feature selection, Support Vector Machine Recursive Feature Elimination (SVMRFE, and a recently developed method, Gradient based Leave-one-out Gene Selection (GLGS that effectively performs microarray data analysis. We also compared several learning classifiers including K-Nearest Neighbor Classifier (KNNC, Naïve Bayes Classifier (NBC, Nearest Mean Scaled Classifier (NMSC, uncorrelated normal based quadratic Bayes Classifier recorded as UDC, Support Vector Machines, and a distance metric learning for Large Margin Nearest Neighbor classifier (LMNN based on Mahanalobis distance. To compare, we conducted a comprehensive experimental study using three types of MALDI-MS data. Conclusion Regarding feature selection, SVMRFE outperformed GLGS in classification. As for the learning classifiers, when classification models derived from the best training were compared, SVMs performed the best with respect to the expected testing

Spillover-mediated feedforward-inhibition functionally segregates interneuron activity

Science.gov (United States)

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

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

Directory of Open Access Journals (Sweden)

Noor Kamal Al-Qazzaz

2015-11-01

Full Text Available We performed a comparative study to select the efficient mother wavelet (MWT basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM task recorded through electro-encephalography (EEG. Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20, Symlets (sym1–sym20, and Coiflets (coif1–coif5. Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.

Positive Selection or Free to Vary? Assessing the Functional Significance of Sequence Change Using Molecular Dynamics.

Directory of Open Access Journals (Sweden)

Jane R Allison

Full Text Available Evolutionary arms races between pathogens and their hosts may be manifested as selection for rapid evolutionary change of key genes, and are sometimes detectable through sequence-level analyses. In the case of protein-coding genes, such analyses frequently predict that specific codons are under positive selection. However, detecting positive selection can be non-trivial, and false positive predictions are a common concern in such analyses. It is therefore helpful to place such predictions within a structural and functional context. Here, we focus on the p19 protein from tombusviruses. P19 is a homodimer that sequesters siRNAs, thereby preventing the host RNAi machinery from shutting down viral infection. Sequence analysis of the p19 gene is complicated by the fact that it is constrained at the sequence level by overprinting of a viral movement protein gene. Using homology modeling, in silico mutation and molecular dynamics simulations, we assess how non-synonymous changes to two residues involved in forming the dimer interface-one invariant, and one predicted to be under positive selection-impact molecular function. Interestingly, we find that both observed variation and potential variation (where a non-synonymous change to p19 would be synonymous for the overprinted movement protein does not significantly impact protein structure or RNA binding. Consequently, while several methods identify residues at the dimer interface as being under positive selection, MD results suggest they are functionally indistinguishable from a site that is free to vary. Our analyses serve as a caveat to using sequence-level analyses in isolation to detect and assess positive selection, and emphasize the importance of also accounting for how non-synonymous changes impact structure and function.

Best lung function equations for the very elderly selected by survival analysis

DEFF Research Database (Denmark)

Miller, Martin R; Thinggaard, Mikael; Christensen, Kaare

2014-01-01

We evaluated which equations best predicted the lung function of a cohort of nonagenarians based on which best accounted for subsequent survival.In 1998, we measured lung function, grip strength and dementia score (Mini Mental State Examination (MMSE)) in a population-based sample of 2262 Danes...... with a hazard ratio for death of 1, 1.16, 1.32 and 1.60 respectively, compared with equations derived with the inclusion of elderly subjects.We conclude that extrapolating from NHANES III equations to predict lung function in nonagenarians gave better survival predictions from spirometry than when employing...... equations derived using very elderly subjects with possible selection bias. These findings can help inform how future lung function equations for the elderly are derived....

Predicting Audience Location on the Basis of the k-Nearest Neighbor Multilabel Classification

Directory of Open Access Journals (Sweden)

Haitao Wu

2014-01-01

Full Text Available Understanding audience location information in online social networks is important in designing recommendation systems, improving information dissemination, and so on. In this paper, we focus on predicting the location distribution of audiences on YouTube. And we transform this problem to a multilabel classification problem, while we find there exist three problems when the classical k-nearest neighbor based algorithm for multilabel classification (ML-kNN is used to predict location distribution. Firstly, the feature weights are not considered in measuring the similarity degree. Secondly, it consumes considerable computing time in finding similar items by traversing all the training set. Thirdly, the goal of ML-kNN is to find relevant labels for every sample which is different from audience location prediction. To solve these problems, we propose the methods of measuring similarity based on weight, quickly finding similar items, and ranking a specific number of labels. On the basis of these methods and the ML-kNN, the k-nearest neighbor based model for audience location prediction (AL-kNN is proposed for predicting audience location. The experiments based on massive YouTube data show that the proposed model can more accurately predict the location of YouTube video audience than the ML-kNN, MLNB, and Rank-SVM methods.

Who's Watching the Babies? Improving the Quality of Family, Friend, and Neighbor Child Care

Science.gov (United States)

Powell, Douglas R.

2008-01-01

One of the important influences on a child's development is the quality of his or her early care and education experiences. It is estimated that more than 1 million children in the U.S. are cared for while their parents are at work by nonlicensed caregivers who are family, friends, or neighbors - and these caregivers can be difficult to reach…

Maternal immune activation leads to selective functional deficits in offspring parvalbumin interneurons.

Science.gov (United States)

Canetta, S; Bolkan, S; Padilla-Coreano, N; Song, L J; Sahn, R; Harrison, N L; Gordon, J A; Brown, A; Kellendonk, C

2016-07-01

Abnormalities in prefrontal gamma aminobutyric acid (GABA)ergic transmission, particularly in fast-spiking interneurons that express parvalbumin (PV), are hypothesized to contribute to the pathophysiology of multiple psychiatric disorders, including schizophrenia, bipolar disorder, anxiety disorders and depression. While primarily histological abnormalities have been observed in patients and in animal models of psychiatric disease, evidence for abnormalities in functional neurotransmission at the level of specific interneuron populations has been lacking in animal models and is difficult to establish in human patients. Using an animal model of a psychiatric disease risk factor, prenatal maternal immune activation (MIA), we found reduced functional GABAergic transmission in the medial prefrontal cortex (mPFC) of adult MIA offspring. Decreased transmission was selective for interneurons expressing PV, resulted from a decrease in release probability and was not observed in calretinin-expressing neurons. This deficit in PV function in MIA offspring was associated with increased anxiety-like behavior and impairments in attentional set shifting, but did not affect working memory. Furthermore, cell-type specific optogenetic inhibition of mPFC PV interneurons was sufficient to impair attentional set shifting and enhance anxiety levels. Finally, we found that in vivo mPFC gamma oscillations, which are supported by PV interneuron function, were linearly correlated with the degree of anxiety displayed in adult mice, and that this correlation was disrupted in MIA offspring. These results demonstrate a selective functional vulnerability of PV interneurons to MIA, leading to affective and cognitive symptoms that have high relevance for schizophrenia and other psychiatric disorders.

Use of the neighboring orbital model for analysis of electronic coupling in Class III intervalence compounds

International Nuclear Information System (INIS)

Nelsen, Stephen F.; Weaver, Michael N.; Luo Yun; Lockard, Jenny V.; Zink, Jeffrey I.

2006-01-01

Symmetrical charge-delocalized intervalence radical ions should not be described by the traditional two-state model that has been so successful for their localized counterparts. If they lack direct overlap between their charge-bearing units (M), their diabatic orbitals have an equal energy pair of symmetrized M-centered combination orbitals that are symmetric (S) or antisymmetric (A) with respect to a symmetry element at the center of the molecule. The M combination orbitals will mix separately with bridge orbitals of the same symmetry. We call the simplest useful model for this situation the neighboring orbital model, which uses the S and A bridge orbitals of high overlap that lie closest in energy to the M orbital pair, resulting in two two-state models that have a common energy for one pair. This model is developed quantitatively, and examples having 1, 3, 5, and 7 electrons in the neighboring orbitals are illustrated

Chinese Function Manager of 2006 Partenariat Comments on the Selection Principle for Chinese Enterprises

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

　　Fang Lei, EU-China Partenariat 2006Function Manager for Chinese Host Companies, worked together with Mr. Richard Morgan, EU Project Expert,Mr. Han Meiqing, Chinese Project Expert in the primary selection of Chinese enterprises.In reply to the strong request of the relevant governmental institutions, CCPIT and enterprises, he gave the following introductions about the details of selection.……

Behavior change communication activities improve infant and young child nutrition knowledge and practice of neighboring non-participants in a cluster-randomized trial in rural Bangladesh.

Science.gov (United States)

Hoddinott, John; Ahmed, Ishita; Ahmed, Akhter; Roy, Shalini

2017-01-01

To examine the impact on infant and young child nutrition knowledge and practice of mothers who were neighbors of mothers participating in a nutrition Behavior Change Communication (BCC) intervention in rural Bangladesh. We analyzed data from 300 mothers whose neighbor participated in a nutrition BCC intervention and 600 mothers whose neighbor participated in an intervention that did not include BCC. We constructed measures capturing mothers' knowledge of infant and young child nutrition (IYCN) and measures of food consumption by children 6-24m. The effect on these outcomes of exposure to a neighbor receiving a nutrition BCC intervention was estimated using ordinary least squares and probit regressions. The study was registered with ClinicalTrials.gov (Study ID: NCT02237144). Having a neighboring mother participate in a nutrition BCC intervention increased non-participant mothers' IYCN knowledge by 0.17 SD (translating to 0.3 more correct answers). They were 14.1 percentage points more likely to feed their 6-24m children legumes and nuts; 11.6 percentage points more likely to feed these children vitamin A rich fruits and vegetables; and 10.0 percentage points more likely to feed these children eggs. Children of non-participant mothers who had a neighboring mother participate in a nutrition BCC intervention were 13.8 percentage points more likely to meet World Health Organization (WHO) guidelines for minimum diet diversity, 11.9 percentage points more likely to meet WHO guidelines for minimum acceptable diet, and 10.3 percentage points more likely to meet WHO guidelines for minimum meal frequency for children who continue to be breastfed after age 6m. Children aged 0-6m of non-participant mothers who are neighbors of mothers receiving BCC were 7.1 percentage points less likely to have ever consumed water-based liquids. Studies of nutrition BCC that do not account for information spillovers to non-participants may underestimate its benefits in terms of IYCN knowledge

Behavior change communication activities improve infant and young child nutrition knowledge and practice of neighboring non-participants in a cluster-randomized trial in rural Bangladesh.

Directory of Open Access Journals (Sweden)

John Hoddinott

Full Text Available To examine the impact on infant and young child nutrition knowledge and practice of mothers who were neighbors of mothers participating in a nutrition Behavior Change Communication (BCC intervention in rural Bangladesh.We analyzed data from 300 mothers whose neighbor participated in a nutrition BCC intervention and 600 mothers whose neighbor participated in an intervention that did not include BCC. We constructed measures capturing mothers' knowledge of infant and young child nutrition (IYCN and measures of food consumption by children 6-24m. The effect on these outcomes of exposure to a neighbor receiving a nutrition BCC intervention was estimated using ordinary least squares and probit regressions. The study was registered with ClinicalTrials.gov (Study ID: NCT02237144.Having a neighboring mother participate in a nutrition BCC intervention increased non-participant mothers' IYCN knowledge by 0.17 SD (translating to 0.3 more correct answers. They were 14.1 percentage points more likely to feed their 6-24m children legumes and nuts; 11.6 percentage points more likely to feed these children vitamin A rich fruits and vegetables; and 10.0 percentage points more likely to feed these children eggs. Children of non-participant mothers who had a neighboring mother participate in a nutrition BCC intervention were 13.8 percentage points more likely to meet World Health Organization (WHO guidelines for minimum diet diversity, 11.9 percentage points more likely to meet WHO guidelines for minimum acceptable diet, and 10.3 percentage points more likely to meet WHO guidelines for minimum meal frequency for children who continue to be breastfed after age 6m. Children aged 0-6m of non-participant mothers who are neighbors of mothers receiving BCC were 7.1 percentage points less likely to have ever consumed water-based liquids.Studies of nutrition BCC that do not account for information spillovers to non-participants may underestimate its benefits in terms of

Low-spin identical bands in neighboring odd-A and even-even nuclei

International Nuclear Information System (INIS)

Baktash, C.; Winchell, D.F.; Garrett, J.D.; Smith, A.

1992-01-01

A comprehensive study of odd-A rotational bands in normally deformed rare-earth nuclei indicates that a large number of seniority-one configurations (21% for odd-Z nuclei) at low spin have moments of inertia nearly identical to that of the seniority-zero configuration of the neighboring even-even nucleus with one less nucleon. It is difficult to reconcile these results with conventional models of nuclear pair correlation, which predict variations of about 15% in the moments of inertia of configurations differing by one unit in seniority

Contrasting taxonomic and functional responses of a tropical tree community to selective logging

OpenAIRE

Baraloto, C.; Hérault, B.; Paine, C. E. T.; Massot, H.; Blanc, L.; Bonal, D.; Molino, Jean-François; Nicolini, E. A.; Sabatier, Daniel

2012-01-01

1. Considerable debate surrounds the extent to which tropical forests can be managed for resource extraction while conserving biodiversity and ecosystem properties, which depend on functional composition. Here we evaluate the compatibility of these aims by examining the effects of logging on taxonomic and functional diversity and composition in a tropical forest. 2. Twenty years after selective logging, we inventoried 4140 stems regenerating in logging gaps and adjacent undisturbed areas, and...

Functionally graded Nylon-11/silica nanocomposites produced by selective laser sintering

International Nuclear Information System (INIS)

Chung, Haseung; Das, Suman

2008-01-01

Selective laser sintering (SLS), a layered manufacturing-based freeform fabrication approach was explored for constructing three-dimensional structures in functionally graded polymer nanocomposites. Here, we report on the processing and properties of functionally graded polymer nanocomposites of Nylon-11 filled with 0-10% by volume of 15 nm fumed silica nanoparticles. SLS processing parameters for the different compositions were developed by design of experiments (DOE). The densities and micro/nanostructures of the nanocomposites were examined by optical microscopy and transmission electron microscopy (TEM). The tensile and compressive properties for each composition were then tested. These properties exhibit a nonlinear variation as a function of filler volume fraction. Finally, two component designs exhibiting a one-dimensional polymer nanocomposite material gradient were fabricated. The results indicate that particulate-filled functionally graded polymer nanocomposites exhibiting a one-dimensional composition gradient can be successfully processed by SLS to produce three-dimensional components with spatially varying mechanical properties

PolyUbiquitin chain linkage topology selects the functions from the underlying binding landscape.

Directory of Open Access Journals (Sweden)

Yong Wang

2014-07-01

Full Text Available Ubiquitin (Ub can generate versatile molecular signals and lead to different celluar fates. The functional poly-valence of Ub is believed to be resulted from its ability to form distinct polymerized chains with eight linkage types. To provide a full picture of ubiquitin code, we explore the binding landscape of two free Ub monomers and also the functional landscapes of of all eight linkage types by theoretical modeling. Remarkably, we found that most of the compact structures of covalently connected dimeric Ub chains (diUbs pre-exist on the binding landscape. These compact functional states were subsequently validated by corresponding linkage models. This leads to the proposal that the folding architecture of Ub monomer has encoded all functional states into its binding landscape, which is further selected by different topologies of polymeric Ub chains. Moreover, our results revealed that covalent linkage leads to symmetry breaking of interfacial interactions. We further propose that topological constraint not only limits the conformational space for effective switching between functional states, but also selects the local interactions for realizing the corresponding biological function. Therefore, the topological constraint provides a way for breaking the binding symmetry and reaching the functional specificity. The simulation results also provide several predictions that qualitatively and quantitatively consistent with experiments. Importantly, the K48 linkage model successfully predicted intermediate states. The resulting multi-state energy landscape was further employed to reconcile the seemingly contradictory experimental data on the conformational equilibrium of K48-diUb. Our results further suggest that hydrophobic interactions are dominant in the functional landscapes of K6-, K11-, K33- and K48 diUbs, while electrostatic interactions play a more important role in the functional landscapes of K27, K29, K63 and linear linkages.

PolyUbiquitin chain linkage topology selects the functions from the underlying binding landscape.

Science.gov (United States)

Wang, Yong; Tang, Chun; Wang, Erkang; Wang, Jin

2014-07-01

Ubiquitin (Ub) can generate versatile molecular signals and lead to different celluar fates. The functional poly-valence of Ub is believed to be resulted from its ability to form distinct polymerized chains with eight linkage types. To provide a full picture of ubiquitin code, we explore the binding landscape of two free Ub monomers and also the functional landscapes of of all eight linkage types by theoretical modeling. Remarkably, we found that most of the compact structures of covalently connected dimeric Ub chains (diUbs) pre-exist on the binding landscape. These compact functional states were subsequently validated by corresponding linkage models. This leads to the proposal that the folding architecture of Ub monomer has encoded all functional states into its binding landscape, which is further selected by different topologies of polymeric Ub chains. Moreover, our results revealed that covalent linkage leads to symmetry breaking of interfacial interactions. We further propose that topological constraint not only limits the conformational space for effective switching between functional states, but also selects the local interactions for realizing the corresponding biological function. Therefore, the topological constraint provides a way for breaking the binding symmetry and reaching the functional specificity. The simulation results also provide several predictions that qualitatively and quantitatively consistent with experiments. Importantly, the K48 linkage model successfully predicted intermediate states. The resulting multi-state energy landscape was further employed to reconcile the seemingly contradictory experimental data on the conformational equilibrium of K48-diUb. Our results further suggest that hydrophobic interactions are dominant in the functional landscapes of K6-, K11-, K33- and K48 diUbs, while electrostatic interactions play a more important role in the functional landscapes of K27, K29, K63 and linear linkages.

Overexpression of neurofilament H disrupts normal cell structure and function

Science.gov (United States)

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.

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

Science.gov (United States)

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

A γ dose distribution evaluation technique using the k-d tree for nearest neighbor searching

International Nuclear Information System (INIS)

Yuan Jiankui; Chen Weimin

2010-01-01

Purpose: The authors propose an algorithm based on the k-d tree for nearest neighbor searching to improve the γ calculation time for 2D and 3D dose distributions. Methods: The γ calculation method has been widely used for comparisons of dose distributions in clinical treatment plans and quality assurances. By specifying the acceptable dose and distance-to-agreement criteria, the method provides quantitative measurement of the agreement between the reference and evaluation dose distributions. The γ value indicates the acceptability. In regions where γ≤1, the predefined criterion is satisfied and thus the agreement is acceptable; otherwise, the agreement fails. Although the concept of the method is not complicated and a quick naieve implementation is straightforward, an efficient and robust implementation is not trivial. Recent algorithms based on exhaustive searching within a maximum radius, the geometric Euclidean distance, and the table lookup method have been proposed to improve the computational time for multidimensional dose distributions. Motivated by the fact that the least searching time for finding a nearest neighbor can be an O(log N) operation with a k-d tree, where N is the total number of the dose points, the authors propose an algorithm based on the k-d tree for the γ evaluation in this work. Results: In the experiment, the authors found that the average k-d tree construction time per reference point is O(log N), while the nearest neighbor searching time per evaluation point is proportional to O(N 1/k ), where k is between 2 and 3 for two-dimensional and three-dimensional dose distributions, respectively. Conclusions: Comparing with other algorithms such as exhaustive search and sorted list O(N), the k-d tree algorithm for γ evaluation is much more efficient.

Structure of the first- and second-neighbor shells of simulated water: Quantitative relation to translational and orientational order

Science.gov (United States)

Yan, Zhenyu; Buldyrev, Sergey V.; Kumar, Pradeep; Giovambattista, Nicolas; Debenedetti, Pablo G.; Stanley, H. Eugene

2007-11-01

We perform molecular dynamics simulations of water using the five-site transferable interaction potential (TIP5P) model to quantify structural order in both the first shell (defined by four nearest neighbors) and second shell (defined by twelve next-nearest neighbors) of a central water molecule. We find that the anomalous decrease of orientational order upon compression occurs in both shells, but the anomalous decrease of translational order upon compression occurs mainly in the second shell. The decreases of translational order and orientational order upon compression (called the “structural anomaly”) are thus correlated only in the second shell. Our findings quantitatively confirm the qualitative idea that the thermodynamic, structural, and hence dynamic anomalies of water are related to changes upon compression in the second shell.

Low-spin identical bands in neighboring odd-A and even-even nuclei

International Nuclear Information System (INIS)

Baktash, C.; Winchell, D.F.; Garrett, J.D.; Smith, A.

1993-01-01

A comprehensive study of odd-A rotational bands in normally deformed rare-earth nuclei indicates that a large number of seniority-one configurations (21 % for odd-Z nuclei) at low spin have moments of inertia nearly identical to that of the seniority-zero configuration of the neighboring even-even nucleus with one less nucleon. It is difficult to reconcile these results with conventional models of nuclear pair correlation, which predict variations of about 15% in the moments of inertia of configurations differing by one unit in seniority. (orig.)

Social justice in education: how the function of selection in educational institutions predicts support for (non)egalitarian assessment practices.

Science.gov (United States)

Autin, Frédérique; Batruch, Anatolia; Butera, Fabrizio

2015-01-01

Educational institutions are considered a keystone for the establishment of a meritocratic society. They supposedly serve two functions: an educational function that promotes learning for all, and a selection function that sorts individuals into different programs, and ultimately social positions, based on individual merit. We study how the function of selection relates to support for assessment practices known to harm vs. benefit lower status students, through the perceived justice principles underlying these practices. We study two assessment practices: normative assessment-focused on ranking and social comparison, known to hinder the success of lower status students-and formative assessment-focused on learning and improvement, known to benefit lower status students. Normative assessment is usually perceived as relying on an equity principle, with rewards being allocated based on merit and should thus appear as positively associated with the function of selection. Formative assessment is usually perceived as relying on corrective justice that aims to ensure equality of outcomes by considering students' needs, which makes it less suitable for the function of selection. A questionnaire measuring these constructs was administered to university students. Results showed that believing that education is intended to select the best students positively predicts support for normative assessment, through increased perception of its reliance on equity, and negatively predicts support for formative assessment, through reduced perception of its ability to establish corrective justice. This study suggests that the belief in the function of selection as inherent to educational institutions can contribute to the reproduction of social inequalities by preventing change from assessment practices known to disadvantage lower-status student, namely normative assessment, to more favorable practices, namely formative assessment, and by promoting matching beliefs in justice principles.

A holistic method for selecting tidal stream energy hotspots under technical, economic and functional constraints

International Nuclear Information System (INIS)

Vazquez, A.; Iglesias, G.

2016-01-01

Highlights: • A method for selecting the most suitable sites for tidal stream farms was presented. • The selection was based on relevant technical, economic and functional aspects. • As a case study, a model of the Bristol Channel was implemented and validated. - Abstract: Although a number of prospective locations for tidal stream farms have been identified, the development of a unified approach for selecting the optimum site in a region remains a current research topic. The objective of this work is to develop and apply a methodology for determining the most suitable sites for tidal stream farms, i.e. sites whose characteristics maximise power performance, minimise cost and avoid conflicts with competing uses of the marine space. Illustrated through a case study in the Bristol Channel, the method uses a validated hydrodynamics model to identify highly energetic areas and a geospatial Matlab-based program (designed ad hoc) to estimate the energy output that a tidal farm at the site with a given technology would have. This output is then used to obtain the spatial distribution of the levelised cost of energy and, on this basis, to preselect certain areas. Subsequently, potential conflicts with other functions of the marine space (e.g. fishing, shipping) are considered. The result is a selection of areas for tidal stream energy development based on a holistic approach, encompassing the relevant technical, economic and functional aspects. This methodology can lead to a significant improvement in the selection of tidal sites, thereby increasing the possibilities of project acceptance and development.

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

Science.gov (United States)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

A density functional approach to ferrogels

Science.gov (United States)

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.

Impact of Training Bolivian Farmers on Integrated Pest Management and Diffusion of Knowledge to Neighboring Farmers

DEFF Research Database (Denmark)

Jørs, Erik; Konradsen, Flemming; Huici, Omar

2016-01-01

of importance to justify training costs and to promote a healthy and sustainable agriculture. Training on IPM of farmers took place from 2002 to 2004 in their villages in La Paz County, Bolivia, while dissemination of knowledge from trained farmer to neighboring farmer took place until 2009. To evaluate...

Nearest neighbor 3D segmentation with context features

Science.gov (United States)

Hristova, Evelin; Schulz, Heinrich; Brosch, Tom; Heinrich, Mattias P.; Nickisch, Hannes

2018-03-01

Automated and fast multi-label segmentation of medical images is challenging and clinically important. This paper builds upon a supervised machine learning framework that uses training data sets with dense organ annotations and vantage point trees to classify voxels in unseen images based on similarity of binary feature vectors extracted from the data. Without explicit model knowledge, the algorithm is applicable to different modalities and organs, and achieves high accuracy. The method is successfully tested on 70 abdominal CT and 42 pelvic MR images. With respect to ground truth, an average Dice overlap score of 0.76 for the CT segmentation of liver, spleen and kidneys is achieved. The mean score for the MR delineation of bladder, bones, prostate and rectum is 0.65. Additionally, we benchmark several variations of the main components of the method and reduce the computation time by up to 47% without significant loss of accuracy. The segmentation results are - for a nearest neighbor method - surprisingly accurate, robust as well as data and time efficient.

Many Neighbors are not Silent. fMRI Evidence for Global Lexical Activity in Visual Word Recognition.

Directory of Open Access Journals (Sweden)

Mario eBraun

2015-07-01

Full Text Available Many neurocognitive studies investigated the neural correlates of visual word recognition, some of which manipulated the orthographic neighborhood density of words and nonwords believed to influence the activation of orthographically similar representations in a hypothetical mental lexicon. Previous neuroimaging research failed to find evidence for such global lexical activity associated with neighborhood density. Rather, effects were interpreted to reflect semantic or domain general processing. The present fMRI study revealed effects of lexicality, orthographic neighborhood density and a lexicality by orthographic neighborhood density interaction in a silent reading task. For the first time we found greater activity for words and nonwords with a high number of neighbors. We propose that this activity in the dorsomedial prefrontal cortex reflects activation of orthographically similar codes in verbal working memory thus providing evidence for global lexical activity as the basis of the neighborhood density effect. The interaction of lexicality by neighborhood density in the ventromedial prefrontal cortex showed lower activity in response to words with a high number compared to nonwords with a high number of neighbors. In the light of these results the facilitatory effect for words and inhibitory effect for nonwords with many neighbors observed in previous studies can be understood as being due to the operation of a fast-guess mechanism for words and a temporal deadline mechanism for nonwords as predicted by models of visual word recognition. Furthermore, we propose that the lexicality effect with higher activity for words compared to nonwords in inferior parietal and middle temporal cortex reflects the operation of an identification mechanism and based on local lexico-semantic activity.

Synthesis selective transport properties of cleft-type ionophores having two convergent hydroxamic acid functions

International Nuclear Information System (INIS)

Kim, Duck Hee; Choi, Mi Jung; Chang, Suk Kyu

2001-01-01

A series of cleft-type ionophores having two convergent hydroxamic acid functions are prepared and their selective ionophoric properties toward heavy metal and transition metal ions have been investigated. Hydroxamic acids 3 exhibited a prominent selectivity toward heavy metal ions of Hg 2+ and Pb 2+ , and transition metal ions of Cu 2+ over other transition metal and alkaline earth metal ions from slightly acidic source phase (pH 6) to an acidic receiving phase (pH 1). Selective ionophoric properties toward Pb 2+ and Cu 2+ ions over other surveyed metal ions are also confirmed by the FAB-MS measurements

Electrocatalytic Activity and Selectivity - a Density Functional Theory Study

DEFF Research Database (Denmark)

Karamad, Mohammadreza

-catalysts towards two appealing electrochemical reactions: 1)electroreduction of CO2 to hydrocarbons and alcohols, and 2) electrochemical production of hydrogen peroxide, i.e. H2O2, from its elements i.e. H2 and O2. The thesis is divided into three parts: In the first part, electro-catalytic activity of different...... metallic and functionalized graphene catalysts. Secondly, we considered CO2 reduction on RuO2, which has a distinctive catalytic activity and selectivity compared to Cu to get insight into mechanistic pathway of the CO2 reduction. Finally, in the last part, we have taken advantage of the isolated active...

Synthesis and Selective Functionalization of [1,2,4]Triazolo[4,3-a]pyrazines

DEFF Research Database (Denmark)

Demmer, Charles Sylvain; Jorgensen, Morten; Kehler, Jan

2015-01-01

A new tactic for the synthesis and selective functionalization of [1,2,4]triazolo[4,3-a]pyrazines has been developed using an oxidative cyclization as key step. Furthermore, novel strategies for introducing diverse substituents in all positions of the heterocycle were identified....

Social justice in education: how the function of selection in educational institutions predicts support for (non)egalitarian assessment practices

Science.gov (United States)

Autin, Frédérique; Batruch, Anatolia; Butera, Fabrizio

2015-01-01

Educational institutions are considered a keystone for the establishment of a meritocratic society. They supposedly serve two functions: an educational function that promotes learning for all, and a selection function that sorts individuals into different programs, and ultimately social positions, based on individual merit. We study how the function of selection relates to support for assessment practices known to harm vs. benefit lower status students, through the perceived justice principles underlying these practices. We study two assessment practices: normative assessment—focused on ranking and social comparison, known to hinder the success of lower status students—and formative assessment—focused on learning and improvement, known to benefit lower status students. Normative assessment is usually perceived as relying on an equity principle, with rewards being allocated based on merit and should thus appear as positively associated with the function of selection. Formative assessment is usually perceived as relying on corrective justice that aims to ensure equality of outcomes by considering students’ needs, which makes it less suitable for the function of selection. A questionnaire measuring these constructs was administered to university students. Results showed that believing that education is intended to select the best students positively predicts support for normative assessment, through increased perception of its reliance on equity, and negatively predicts support for formative assessment, through reduced perception of its ability to establish corrective justice. This study suggests that the belief in the function of selection as inherent to educational institutions can contribute to the reproduction of social inequalities by preventing change from assessment practices known to disadvantage lower-status student, namely normative assessment, to more favorable practices, namely formative assessment, and by promoting matching beliefs in justice

Diagnosis of diabetes diseases using an Artificial Immune Recognition System2 (AIRS2) with fuzzy K-nearest neighbor.

Science.gov (United States)

Chikh, Mohamed Amine; Saidi, Meryem; Settouti, Nesma

2012-10-01

The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disease dataset used in our work is retrieved from UCI machine learning repository. The performances of the AIRS2 and MAIRS2 are evaluated regarding classification accuracy, sensitivity and specificity values. The highest classification accuracy obtained when applying the AIRS2 and MAIRS2 using 10-fold cross-validation was, respectively 82.69% and 89.10%.

Density functional approach for the magnetism of β-TeVO4

Science.gov (United States)

Saúl, A.; Radtke, G.

2014-03-01

Density functional calculations have been carried out to investigate the microscopic origin of the magnetic properties of β-TeVO4. Two different approaches, based either on a perturbative treatment of the multiorbital Hubbard model in the strongly correlated limit or on the calculation of supercell total energy differences, have been employed to evaluate magnetic couplings in this compound. The picture provided by these two approaches is that of weakly coupled frustrated chains with ferromagnetic nearest-neighbor and antiferromagnetic second-nearest-neighbor couplings. These results, differing substantially from previous reports, should motivate further experimental investigations of the magnetic properties of this compound.

A Quality Function Deployment-Based Model for Cutting Fluid Selection

Directory of Open Access Journals (Sweden)

Kanika Prasad

2016-01-01

Full Text Available Cutting fluid is applied for numerous reasons while machining a workpiece, like increasing tool life, minimizing workpiece thermal deformation, enhancing surface finish, flushing away chips from cutting surface, and so on. Hence, choosing a proper cutting fluid for a specific machining application becomes important for enhanced efficiency and effectiveness of a manufacturing process. Cutting fluid selection is a complex procedure as the decision depends on many complicated interactions, including work material’s machinability, rigorousness of operation, cutting tool material, metallurgical, chemical, and human compatibility, reliability and stability of fluid, and cost. In this paper, a decision making model is developed based on quality function deployment technique with a view to respond to the complex character of cutting fluid selection problem and facilitate judicious selection of cutting fluid from a comprehensive list of available alternatives. In the first example, HD-CUTSOL is recognized as the most suitable cutting fluid for drilling holes in titanium alloy with tungsten carbide tool and in the second example, for performing honing operation on stainless steel alloy with cubic boron nitride tool, CF5 emerges out as the best honing fluid. Implementation of this model would result in cost reduction through decreased manpower requirement, enhanced workforce efficiency, and efficient information exploitation.

Bio-functionalized silver nanoparticles for selective colorimetric sensing of toxic metal ions and antimicrobial studies

Science.gov (United States)

Vinod Kumar, V.; Anbarasan, S.; Christena, Lawrence Rene; SaiSubramanian, Nagarajan; Philip Anthony, Savarimuthu

2014-08-01

Hibiscus Sabdariffa (Gongura) plant extracts (leaves (HL) and stem (HS) were used for the first time in the green synthesis of bio-functionalized silver nanoparticles (AgNPs). The bio-functionality of AgNPs has been successfully utilized for selective colorimetric sensing of potentially health and environmentally hazardous Hg2+, Cd2+ and Pb2+ metal ions at ppm level in aqueous solution. Importantly, clearly distinguishable colour for all three metal ions was observed. The influence of extract preparation condition and pH were also explored on the formation of AgNPs. Both selectivity and sensitivity differed for AgNPs synthesized from different parts of the plant. Direct correlation between the stability of green synthesized AgNPs at different pH and its antibacterial effects has been established. The selective colorimetric sensing of toxic metal ions and antimicrobial effect of green synthesized AgNPs demonstrated the multifunctional applications of green nanotechnology.

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

International Nuclear Information System (INIS)

Thompson, A.P.; Swiler, L.P.; Trott, C.R.; Foiles, S.M.; Tucker, G.J.

2015-01-01

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Energy Technology Data Exchange (ETDEWEB)

Thompson, Aidan P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Multiscale Science Dept.; Swiler, Laura P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Optimization and Uncertainty Quantification Dept.; Trott, Christian R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Scalable Algorithms Dept.; Foiles, Stephen M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Tucker, Garritt J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Drexel Univ., Philadelphia, PA (United States). Dept. of Materials Science and Engineering

2015-03-15

Here, we present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Energy Technology Data Exchange (ETDEWEB)

Thompson, A.P., E-mail: athomps@sandia.gov [Multiscale Science Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Swiler, L.P., E-mail: lpswile@sandia.gov [Optimization and Uncertainty Quantification Department, Sandia National Laboratories, PO Box 5800, MS 1318, Albuquerque, NM 87185 (United States); Trott, C.R., E-mail: crtrott@sandia.gov [Scalable Algorithms Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Foiles, S.M., E-mail: foiles@sandia.gov [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Tucker, G.J., E-mail: gtucker@coe.drexel.edu [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104 (United States)

2015-03-15

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

C-H functionalization: thoroughly tuning ligands at a metal ion, a chemist can greatly enhance catalyst's activity and selectivity.

Science.gov (United States)

Shul'pin, Georgiy B

2013-09-28

This brief essay consists of a few "exciting stories" devoted to relations within a metal-complex catalyst between a metal ion and a coordinated ligand. When, as in the case of a human couple, the rapport of the partners is cordial and a love cements these relations, a chemist finds an ideal married couple, in other words he obtains a catalyst of choice which allows him to functionalize C-H bonds very efficiently and selectively. Examples of such lucky marriages in the catalytic world of ions and ligands are discussed here. Activity of the catalyst is characterized by turnover number (TON) or turnover frequency (TOF) as well as by yield of a target product. Introducing a chelating N,N- or N,O-ligand to the catalyst molecule (this can be an iron or manganese derivative) sharply enhances its activity. However, the activity of vanadium derivatives (with additionally added to the solution pyrazinecarboxylic acid, PCA) as well as of various osmium complexes does not dramatically depend on the nature of ligands surrounding metal ions. Complexes of these metals are very efficient catalysts in oxidations with H2O2. Osmium derivatives are record-holders exhibiting extremely high TONs whereas vanadium complexes are on the second position. Finally, elegant examples of alkane functionalization on the ions of non-transition metals (aluminium, gallium etc.) are described when one ligand within the metal complex (namely, hydroperoxyl ligand HOO(-)) helps other ligand of this complex (H2O2 molecule coordinated to the metal) to disintegrate into two species, generating very reactive hydroxyl radical. Hydrogen peroxide molecule, even ligated to the metal ion, is perfectly stable without the assistance of the neighboring HOO(-) ligand. This ligand can be easily oxidized donating an electron to its partner ligand (H2O2). In an analogous case, when the central ion in the catalyst is a transition metal, this ion changing its oxidation state can donate an electron to the coordinated H2O2

LOPES: Selective control of gait functions during the gait rehabilitation of CVA patients

NARCIS (Netherlands)

Ekkelenkamp, R.; Veneman, J.F.; van der Kooij, Herman

2005-01-01

LOPES aims for an active role of the patient by selective and partial support of gait functions during robotic treadmill training sessions. Virtual model control (VMC) was applied to the robot as an intuitive method for translating current treadmill gait rehabilitation therapy programs into robotic

Humanitarian Cleft Lip/Palate Surgeries in Buddhist Thailand and Neighboring Countries.

Science.gov (United States)

Uemura, Tetsuji; Preeyanont, Piyoros; Udnoon, Sopridee

2015-06-01

This study evaluates surgeries done on patients with cleft lip and/or palate in Thailand and its neighboring countries from 1988 to 2008. This 21-year-long volunteer surgical mission was sponsored by Duang-Kaew Foundation, a volunteer organization. Countries involved, besides Thailand, were Vietnam, Myanmar, Laos, Cambodia, China, Sri Lanka, Bhutan, and India. The same surgical method for primary and secondary repair of lip and/or palate was used throughout: Onizuka method by single surgeon, the second author mainly. We assessed, by way of the patients' medical records including their background, the results of surgeries. The healing rates and complication rates associated with patients for primary and secondary repair of lip and/or palate. The study consisted of a total of 6832 patients: 3120 with cleft lip (CL); 2190 with cleft palate (CP); and 1522 with cleft lip and palate (CLP). Their primary cases were 675 (CL), 799 (CP), and 301 (CLP). All CP operations were done under general anesthesia. Of the CL surgeries, 10% of adult cases were done under local anesthesia. Of all the patients, 78%, or 5329, had one surgery; and 22%, or 1503, had 2 or more surgeries. Good healing was seen in 73.3%, whereas wound infection was noted in 2.0% and healing by second intention was in 1.2% of all cases. It is important that the Onizuka method was the only method used in all the countries throughout the mission period. The method has an advantage over other methods in that its design is simple enough so that even a beginning plastic surgeon can easily master, and operative results are constantly good regardless of who did the operation. The Duang-Kaew Foundation's long-term surgical program helped reduce the number of untreated patients to manageable levels for local health care providers in Thailand and neighboring countries for as long as 21 years.

Tularemia, a re-emerging infectious disease in Iran and neighboring countrie

Science.gov (United States)

Zargar, Afsaneh; Maurin, Max; Mostafavi, Ehsan

2015-01-01

OBJECTIVES: Tularemia is a zoonotic disease transmitted by direct contact with infected animals and through arthropod bites, inhalation of contaminated aerosols, ingestion of contaminated meat or water, and skin contact with any infected material. It is widespread throughout the northern hemisphere, including Iran and its neighbors to the north, northeast, and northwest. METHODS: In this paper, the epidemiology of tularemia as a re-emerging infectious disease in the world with a focus on Iran and the neighboring countries is reviewed. RESULTS: In Iran, positive serological tests were first reported in 1973, in wildlife and domestic livestock in the northwestern and southeastern parts of the country. The first human case was reported in 1980 in the southwest of Iran, and recent studies conducted among at-risk populations in the western, southeastern, and southwestern parts of Iran revealed seroprevalences of 14.4, 6.52, and 6%, respectively. CONCLUSIONS: Several factors may explain the absence of reported tularemia cases in Iran since 1980. Tularemia may be underdiagnosed in Iran because Francisella tularensis subspecies holarctica is likely to be the major etiological agent and usually causes mild to moderately severe disease. Furthermore, tularemia is not a disease extensively studied in the medical educational system in Iran, and empirical therapy may be effective in many cases. Finally, it should be noted that laboratories capable of diagnosing tularemia have only been established in the last few years. Since both recent and older studies have consistently found tularemia antibodies in humans and animals, the surveillance of this disease should receive more attention. In particular, it would be worthwhile for clinical researchers to confirm tularemia cases more often by isolating F. tularensis from infected humans and animals. PMID:25773439

The affects of contrast medium on renal function in selective coronary angiography and intervention

International Nuclear Information System (INIS)

Chen Yueguang; Lv Baojing

2006-01-01

Selective coronary angiography and intervention with injection of contrast medium into the coronary arteries has become very common in dealing with coronary cardiac diseases. The excretion of contrast medium through kidneys may lead to acute renal functional insufficiency, especially for those suffering from chronic nephropathy, diabetes and cardiac functional disorder to form the so called 'contrast medium nephropathy' which is considered as the number second drug induced acute renal functional failure. Although routine preventive measure including low osmotic contrast medium and fine hydrotherapy have been taken, 14% incidences still occur with renal functional damage. The majority could be reversible but the minority needs emergent hemodialysis or even with persistent renal functional damage in a few ones. (authors)

Investment Incentives and Effective Tax Rates in the Philippines; A Comparison With Neighboring Countries

OpenAIRE

Alexander D Klemm; Dennis P Botman; Reza Baqir

2008-01-01

We compare the general tax provisions and investment incentives in the Philippines to six other east-Asian economies-Malaysia, Indonesia, Lao, Vietnam, Cambodia, and Thailand. We calculate effective tax rates and find that general effective tax rates are relatively high in the Philippines, while investment incentives are comparable to those in neighboring countries. Tax holidays are most attractive for very profitable firms, creating redundancy, and for investment in short-lived assets. We al...

False-nearest-neighbors algorithm and noise-corrupted time series

International Nuclear Information System (INIS)

Rhodes, C.; Morari, M.

1997-01-01

The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society

Nearest Neighbor Estimates of Entropy for Multivariate Circular Distributions

Directory of Open Access Journals (Sweden)

Neeraj Misra

2010-05-01

Full Text Available In molecular sciences, the estimation of entropies of molecules is important for the understanding of many chemical and biological processes. Motivated by these applications, we consider the problem of estimating the entropies of circular random vectors and introduce non-parametric estimators based on circular distances between n sample points and their k th nearest neighbors (NN, where k (≤ n – 1 is a fixed positive integer. The proposed NN estimators are based on two different circular distances, and are proven to be asymptotically unbiased and consistent. The performance of one of the circular-distance estimators is investigated and compared with that of the already established Euclidean-distance NN estimator using Monte Carlo samples from an analytic distribution of six circular variables of an exactly known entropy and a large sample of seven internal-rotation angles in the molecule of tartaric acid, obtained by a realistic molecular-dynamics simulation.

A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks

Directory of Open Access Journals (Sweden)

Hyung-Ju Cho

2012-01-01

Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

Directory of Open Access Journals (Sweden)

Weide Li

2017-05-01

Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang

2013-02-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang; Hansen, Charles

2013-01-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

Fixations of the HIV-1 env gene refute neutralism: New evidence for pan-selective evolution

Directory of Open Access Journals (Sweden)

Carlos Y Valenzuela

2010-01-01

Full Text Available We examined 103 nucleotide sequences of the HIV-1 env gene, sampled from 35 countries and tested: I the random (neutral distribution of the number of nucleotide changes; II the proportion of bases at molecular equilibrium; III the neutral expected homogeneity of the distribution of new fxated bases; IV the hypothesis of the neighbor infuence on the mutation rates in a site. The expected random number of fxations per site was estimated by Bose-Einstein statistics, and the expected frequencies of bases by matrices of mutation-fxation rates. The homogeneity of new fxations was analyzed using χ2 and trinomial tests for homogeneity. Fixations of the central base in trinucleotides were used to test the neighbor infuence on base substitutions. Neither the number of fxations nor the frequencies of bases ftted the expected neutral distribution. There was a highly signifcant heterogeneity in the distribution of new fxations, and several sites showed more transversions than transitions, showing that each nucleotide site has its own pattern of change. These three independent results make the neutral theory, the nearly neutral and the neighbor infuence hypotheses untenable and indicate that evolution of env is rather highly selective.

Analysis and optimization with ecological objective function of irreversible single resonance energy selective electron heat engines

International Nuclear Information System (INIS)

Zhou, Junle; Chen, Lingen; Ding, Zemin; Sun, Fengrui

2016-01-01

Ecological performance of a single resonance ESE heat engine with heat leakage is conducted by applying finite time thermodynamics. By introducing Nielsen function and numerical calculations, expressions about power output, efficiency, entropy generation rate and ecological objective function are derived; relationships between ecological objective function and power output, between ecological objective function and efficiency as well as between power output and efficiency are demonstrated; influences of system parameters of heat leakage, boundary energy and resonance width on the optimal performances are investigated in detail; a specific range of boundary energy is given as a compromise to make ESE heat engine system work at optimal operation regions. Comparing performance characteristics with different optimization objective functions, the significance of selecting ecological objective function as the design objective is clarified specifically: when changing the design objective from maximum power output into maximum ecological objective function, the improvement of efficiency is 4.56%, while the power output drop is only 2.68%; when changing the design objective from maximum efficiency to maximum ecological objective function, the improvement of power output is 229.13%, and the efficiency drop is only 13.53%. - Highlights: • An irreversible single resonance energy selective electron heat engine is studied. • Heat leakage between two reservoirs is considered. • Power output, efficiency and ecological objective function are derived. • Optimal performance comparison for three objective functions is carried out.

The indirect effects of cheatgrass invasion: Grasshopper herbivory on native grasses determined by neighboring cheatgrass abundance

Science.gov (United States)

Julie Beckstead; Susan E. Meyer; Carol K. Augsperger

2008-01-01

Invasion biology has focused on the direct effects of plant invasion and has generally overlooked indirect interactions. Here we link theories of invasion biology and herbivory to explore an indirect effect of one invading species on associational herbivory (the effect of neighboring plants on herbivory) of native species. We studied a Great Basin shadscale (...

A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications

Science.gov (United States)

Jay M. Ver Hoef; Hailemariam Temesgen; Sergio Gómez

2013-01-01

Forest surveys provide critical information for many diverse interests. Data are often collected from samples, and from these samples, maps of resources and estimates of aerial totals or averages are required. In this paper, two approaches for mapping and estimating totals; the spatial linear model (SLM) and k-NN (k-Nearest Neighbor) are compared, theoretically,...

Selection of the wavelet function for the frequencies estimation

International Nuclear Information System (INIS)

Garcia R, A.

2007-01-01

At the moment the signals are used to diagnose the state of the systems, by means of the extraction of their more important characteristics such as the frequencies, tendencies, changes and temporary evolutions. This characteristics are detected by means of diverse analysis techniques, as Autoregressive methods, Fourier Transformation, Fourier transformation in short time, Wavelet transformation, among others. The present work uses the one Wavelet transformation because it allows to analyze stationary, quasi-stationary and transitory signals in the time-frequency plane. It also describes a methodology to select the scales and the Wavelet function to be applied the one Wavelet transformation with the objective of detecting to the dominant system frequencies. (Author)

Estimating Diversifying Selection and Functional Constraint in the Presence of Recombination

OpenAIRE

Wilson, Daniel J.; McVean, Gilean

2006-01-01

Models of molecular evolution that incorporate the ratio of nonsynonymous to synonymous polymorphism (dN/dS ratio) as a parameter can be used to identify sites that are under diversifying selection or functional constraint in a sample of gene sequences. However, when there has been recombination in the evolutionary history of the sequences, reconstructing a single phylogenetic tree is not appropriate, and inference based on a single tree can give misleading results. In the presence of high le...

Estimation and model selection of semiparametric multivariate survival functions under general censorship.

Science.gov (United States)

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2010-07-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

Selective attention relates to the development of executive functions in 2,5- to 3-year-olds : A longitudinal study

NARCIS (Netherlands)

Veer, Ilona M.; Luyten, Hans; Mulder, Hanna; van Tuijl, Cathy; Sleegers, Peter J.C.

2017-01-01

To study the central role of selective attention in the early development of executive functions (EFs), longitudinal relationships between selective attention, working memory, and simple response inhibition were explored. Selective attention, working memory, and simple response inhibition were

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Science.gov (United States)

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Gemcitabine: Selective cytotoxicity, induction of inflammation and effects on urothelial function

Energy Technology Data Exchange (ETDEWEB)

Farr, Stefanie E; Chess-Williams, Russ; McDermott, Catherine M, E-mail: camcderm@bond.edu.au

2017-02-01

Intravesical gemcitabine has recently been introduced for the treatment of superficial bladder cancer and has a favourable efficacy and toxicity profile in comparison to mitomycin c (MMC), the most commonly used chemotherapeutic agent. The aim of this study was to assess the cytotoxic potency of gemcitabine in comparison to MMC in urothelial cell lines derived from non-malignant (UROtsa) and malignant (RT4 and T24) tissues to assess selectivity. Cells were treated with gemcitabine or mitomycin C at concentrations up to the clinical doses for 1 or 2 h respectively (clinical duration). Treatment combined with hyperthermia was also examined. Cell viability, ROS formation, urothelial function (ATP, acetylcholine and PGE2 release) and secretion of inflammatory cytokines were assessed. Gemcitabine displayed a high cytotoxic selectivity for the two malignant cell lines (RT4, T24) compared to the non-malignant urothelial cells (UROtsa, proliferative and non-proliferative). In contrast, the cytotoxic effects of MMC were non-selective with equivalent potency in each of the cell lines. The cytotoxic effect of gemcitabine in the malignant cell lines was associated with an elevation in free radical formation and was significantly decreased in the presence of an equilibrative nucleoside transporter inhibitor. Transient changes in urothelial ATP and PGE{sub 2} release were observed, with significant increase in release of interleukin-6, interleukin-8 and interleukin-1β from urothelial cells treated with gemcitabine. The selectivity of gemcitabine for malignant urothelial cells may account for the less frequent adverse urological effects with comparison to other commonly used chemotherapeutic agents. - Highlights: • Intravesical gemcitabine has recently been introduced to treat bladder cancer. • Gemcitabine is selectively toxic for malignant urothelial cells. • Urothelial ATP, PGE{sub 2} and inflammatory cytokines were altered by gemcitabine. • Selectivity of gemcitabine

The Impactof the Kurdish Question on Turkey's Relations with its Middle Eastern neighbors

OpenAIRE

Asil, Muhammet Ali

2013-01-01

Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir. This dissertation analyzes the “Kurdish Question” from an International Relations perspective. Focusing on the impact of the Kurdish question on Turkey’s relations in the last decade with its Middle Eastern neighbors, i.e. Iran, Syria, and Iraq, and with the European Union; this study shows how Turkey-Middle East and Turkey-EU relations are shaped differently. In the search for reasons for this difference, Realist and Liberal I...

The value of cows in reference populations for genomic selection of new functional traits

DEFF Research Database (Denmark)

Buch, Line Hjortø; Kargo, Morten; Berg, Peer

2012-01-01

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic...... of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new...... to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls....

Selective Engagement of Cognitive Resources: Motivational Influences on Older Adults’ Cognitive Functioning

Science.gov (United States)

Hess, Thomas M.

2018-01-01

In this article, I present a framework for understanding the impact of aging-related declines in cognitive resources on functioning. I make the assumption that aging is associated with an increase in the costs of cognitive engagement, as reflected in both the effort required to achieve a specific level of task performance and the associated depletion or fatigue effects. I further argue that these costs result in older adults being increasingly selective in the engagement of cognitive resources in response to these declines. This selectivity is reflected in (a) a reduction in the intrinsic motivation to engage in cognitively demanding activities, which, in part, accounts for general reductions in engagement in such activities, and (b) greater sensitivity to the self-related implications of a given task. Both processes are adaptive if viewed in terms of resource conservation, but the former may also be maladaptive to the extent that it results in older adults restricting participation in cognitively demanding activities that could ultimately benefit cognitive health. I review supportive research and make the general case for the importance of considering motivational factors in understanding aging effects on cognitive functioning. PMID:26173272

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

Directory of Open Access Journals (Sweden)

B. Paramasivan

2014-01-01

Full Text Available 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.

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

Science.gov (United States)

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.

Radionuclide content of an exhumed canyon vessel and neighboring soil

International Nuclear Information System (INIS)

Holcomb, H.P.

1976-11-01

The long-term hazard potential associated with burial of process equipment from radiochemical separations plants is being evaluated. As part of this evaluation, a feed adjustment tank was exhumed eighteen years after burial. The tank had been in service in the fuel reprocessing plant for twenty-nine months before it was retired. Assay of the exhumed tank indicated that 7 mg (0.4 mCi) of 239 Pu and 1 mCi of 137 Cs remained on its surfaces; 1.1 mg (0.07 mCi) 239 Pu, 0.4 mCi 137 Cs, and 3.5 mCi 90 Sr were found in neighboring soil. The vessel and surrounding soil have met the present guidelines (less than or equal to 10 nCi/g) of the U. S. Energy Research and Development Administration (ERDA) for nonretrievable waste

Thermodynamic selectivity of functional agents on zeolite for sodium dodecyl sulfate sequestration

Energy Technology Data Exchange (ETDEWEB)

Leng, Ling; Wang, Jian [Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR (China); Qiu, Xianxiu; Zhao, Yanxiang; Yip, Yuk-Wang; Law, Ga-Lai [Department of Applied Biology and Chemical Technology, State Key Laboratory of Chirosciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR (China); Shih, Kaimin; Zhou, Zhengyuan [Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong SAR (China); Lee, Po-Heng, E-mail: poheng76@gmail.com [Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR (China)

2016-11-15

Highlights: • A thermodynamic approach to select a functional agent for adsorbent is proposed. • ITC and QCS were used to interpret the interaction between adsorbate and agent. • The interaction identifies the adsorption mechanism and performance. • This approach enables the manipulation of adsorption capacity optimization. - Abstract: This study proposes a thermodynamic approach to effectively select functional agents onto zeolite for sodium dodecyl sulfate (SDS) sequestration in greywater reuse. We combine isothermal titration calorimetry (ITC) and quantum chemistry simulation (QCS) to identify the interactions between SDS and agents at the molecular level. Three potential agents, cetyl trimethyl ammonium bromide (CTAB), N,N,N-trimethyltetradecan-1-aminium bromide (C{sub 14}TAB), and 14-hydroxy-N,N,N-trimethyltetradecan-1-aminium bromide (C{sub 14}HTAB), differ in carbon chain length and hydrophilic groups. The ITC titration of SDS with CTAB released the highest heat, followed by those with C{sub 14}TAB and C{sub 14}HTAB, as was the same trend for the amounts of SDS adsorbed by the respective functionalized-zeolites. Results suggest that the favorable SDS sorption occurred at the bilayer CTAB-zeolite is driven by enthalpy as similar as the SDS…CTAB interaction found, regardless of the contribution from electrostatic and/or hydrophobic behaviors, while the declined sorption is entropy-driven via the predominant hydrophobic interaction onto the monolayer CTAB-zeolite. The data presented here interpret the nature of molecularly thermodynamic quantities and enable the manipulation of sorption capacity optimization.

Motor-evacuatory gastric function in patients with duodenal cancer after selective proximal vagotomy

Energy Technology Data Exchange (ETDEWEB)

Aliev, M A; Kabdrakhmanov, T K; Kashkin, K A; Darmenov, O K; Kuspangaljeva, Sh U [Kazakhskij Inst. Klinicheskoj i Ehksperimental' noj Khirurgii Minzdrava Kazakhskoj SSR, Alma-Ata

1983-06-01

Motor-evacuatory stomach function by using continuous radiogastrography was studied in patients with duodenal ulcers. Radiogastrograms were analyzed before operation, on the 7th-15th day after selective proximal vagotomy performed either independently or in combination with draining operations. A faster evacuation of food from the stomach prevailed in an uncomplicated form of duodenal ulcer and compensated stenosis of the pyloroduodenal zone, evacuatory stomach function was retarded or absent in subcompensated and decompensated stenosis. Discoordinated gastric peristalsis and a reverse food input were noted in patients with subcompensated stenosis. At early time after operations temporary inhibition of evacuatory stomach function occurred in 94.2% of the patients; it could be corrected with conservative therapeutic measures.

Motor-evacuatory gastric function in patients with duodenal cancer after selective proximal vagotomy

International Nuclear Information System (INIS)

Aliev, M.A.; Kabdrakhmanov, T.K.; Kashkin, K.A.; Darmenov, O.K.; Kuspangaljeva, Sh.U.

1983-01-01

Motor-evacuatory stomach function by using continuous radiogastrography was studied in patients with duodenal ulcers. Radiogastrograms were analyzed before operation, on the 7th-15th day after selective proximal vagotomy performed either independently or in combination with draining operations. A faster evacuation of food from the stomach prevailed in an uncomplicated form of duodenal ulcer and compensated stenosis of the pyloroduodenal zone, evacuatory stomach function was retarded or absent in subcompensated and decompensated stenosis. Discoordinated gastric peristalsis and a reverse food input were noted in patients with subcompensated stenosis. At early time after operations temporary inhibition of evacuatory stomach function occurred in 94.2% of the patients; it could be corrected with conservative therapeutic measures

Wildflower Plantings Do Not Compete With Neighboring Almond Orchards for Pollinator Visits.

Science.gov (United States)

Lundin, Ola; Ward, Kimiora L; Artz, Derek R; Boyle, Natalie K; Pitts-Singer, Theresa L; Williams, Neal M

2017-06-01

The engineering of flowering agricultural field borders has emerged as a research and policy priority to mitigate threats to pollinators. Studies have, however, rarely addressed the potential that flowering field borders might compete with neighboring crops for pollinator visits if they both are in bloom at the same time, despite this being a concern expressed by growers. We evaluated how wildflower plantings added to orchard borders in a large (512 ha) commercial almond orchard affected honey bee and wild bee visitation to orchard borders and the crop. The study was conducted over two consecutive seasons using three large (0.48 ha) wildflower plantings paired with control orchard borders in a highly simplified agricultural landscape in California. Honey bee (Apis mellifera L.) and wild bee visitation to wildflower plots were at least an order of magnitude higher than to control plots, but increased honey bee visitation to wildflower plots did not lead to any detectable shifts in honey bee visitation to almond flowers in the neighboring orchard. Wild bees were rarely observed visiting almond flowers irrespective of border treatment, indicating a limited short-term potential for augmenting crop pollination using wild bees in highly simplified agricultural landscapes. Although further studies are warranted on bee visitation and crop yield from spatially independent orchards, this study indicates that growers can support bees with alternative forage in almond orchards without risking competition between the wildflower plantings and the crop. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Neighboring phosphoSer-Pro motifs in the undefined domain of IRAK1 impart bivalent advantage for Pin1 binding.

Science.gov (United States)

Rogals, Monique J; Greenwood, Alexander I; Kwon, Jeahoo; Lu, Kun Ping; Nicholson, Linda K

2016-12-01

The peptidyl prolyl isomerase Pin1 has two domains that are considered to be its binding (WW) and catalytic (PPIase) domains, both of which interact with phosphorylated Ser/Thr-Pro motifs. This shared specificity might influence substrate selection, as many known Pin1 substrates have multiple sequentially close phosphoSer/Thr-Pro motifs, including the protein interleukin-1 receptor-associated kinase-1 (IRAK1). The IRAK1 undefined domain (UD) contains two sets of such neighboring motifs (Ser131/Ser144 and Ser163/Ser173), suggesting possible bivalent interactions with Pin1. Using a series of NMR titrations with 15N-labeled full-length Pin1 (Pin1-FL), PPIase, or WW domain and phosphopeptides representing the Ser131/Ser144 and Ser163/Ser173 regions of IRAK1-UD, bivalent interactions were investigated. Binding studies using singly phosphorylated peptides showed that individual motifs displayed weak affinities (> 100 μm) for Pin1-FL and each isolated domain. Analysis of dually phosphorylated peptides binding to Pin1-FL showed that inclusion of bivalent states was necessary to fit the data. The resulting complex model and fitted parameters were applied to predict the impact of bivalent states at low micromolar concentrations, demonstrating significant affinity enhancement for both dually phosphorylated peptides (3.5 and 24 μm for peptides based on the Ser131/Ser144 and Ser163/Ser173 regions, respectively). The complementary technique biolayer interferometry confirmed the predicted affinity enhancement for a representative set of singly and dually phosphorylated Ser131/Ser144 peptides at low micromolar concentrations, validating model predictions. These studies provide novel insights regarding the complexity of interactions between Pin1 and activated IRAK1, and more broadly suggest that phosphorylation of neighboring Ser/Thr-Pro motifs in proteins might provide competitive advantage at cellular concentrations for engaging with Pin1. © 2016 Federation of European

Chirality dependence of dipole matrix element of carbon nanotubes in axial magnetic field: A third neighbor tight binding approach

Science.gov (United States)

Chegel, Raad; Behzad, Somayeh

2014-02-01

We have studied the electronic structure and dipole matrix element, D, of carbon nanotubes (CNTs) under magnetic field, using the third nearest neighbor tight binding model. It is shown that the 1NN and 3NN-TB band structures show differences such as the spacing and mixing of neighbor subbands. Applying the magnetic field leads to breaking the degeneracy behavior in the D transitions and creates new allowed transitions corresponding to the band modifications. It is found that |D| is proportional to the inverse tube radius and chiral angle. Our numerical results show that amount of filed induced splitting for the first optical peak is proportional to the magnetic field by the splitting rate ν11. It is shown that ν11 changes linearly and parabolicly with the chiral angle and radius, respectively.

Structural optimization and structure-functional selectivity relationship studies of G protein-biased EP2 receptor agonists.

Science.gov (United States)

Ogawa, Seiji; Watanabe, Toshihide; Moriyuki, Kazumi; Goto, Yoshikazu; Yamane, Shinsaku; Watanabe, Akio; Tsuboi, Kazuma; Kinoshita, Atsushi; Okada, Takuya; Takeda, Hiroyuki; Tani, Kousuke; Maruyama, Toru

2016-05-15

The modification of the novel G protein-biased EP2 agonist 1 has been investigated to improve its G protein activity and develop a better understanding of its structure-functional selectivity relationship (SFSR). The optimization of the substituents on the phenyl ring of 1, followed by the inversion of the hydroxyl group on the cyclopentane moiety led to compound 9, which showed a 100-fold increase in its G protein activity compared with 1 without any increase in β-arrestin recruitment. Furthermore, SFSR studies revealed that the combination of meta and para substituents on the phenyl moiety was crucial to the functional selectivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Economic evaluation of health benefits of mercury emission controls for China and the neighboring countries in East Asia

International Nuclear Information System (INIS)

Zhang, Wei; Zhen, Gengchong; Chen, Long; Wang, Huanhuan; Li, Ying; Ye, Xuejie; Tong, Yindong; Zhu, Yan; Wang, Xuejun

2017-01-01

Globally, coal-fired power plant (CFPP) is a major source of mercury. China is developing its first National Implementation Plan on Mercury Control, which priorities the control of emissions from CFPPs. While social benefits play an important role in designing environmental policies in China, the benefits associated with mercury control are not yet understood, mainly due to the scientific challenges to trace mercury's emissions-to-impacts path. This study evaluates the benefits of mercury reductions in China's CFPPs for China and its three neighboring countries in East Asia. Four policy scenarios are analyzed following the policies-to-impacts path, which links a global atmospheric model to health benefit analysis models to estimate the economic gains from avoided mercury-related adverse health outcomes under each scenario, and take into account key uncertainties in the path. Under the most stringent scenario, the benefits of mercury reduction by 2030 are projected to be $432 billion (95% CI: $166–941 billion), with the benefits for China and the neighboring countries accounting for 96% and 4% of the total benefits, respectively. Policy scenario analysis indicates that coal washing generates the greatest benefits in the near term, whereas upgrading air pollution control devices maximizes health benefits in the long term. - Highlights: • Benefits of mercury controls for China and neighboring countries are analyzed. • Policy analysis shows that coal washing generates the largest benefits in near term. • Upgrading air pollution control devices maximizes health benefits in long term. • For mercury controls, local policies contribute most to local benefits.

Coevolution of Cooperation and Layer Selection Strategy in Multiplex Networks

Directory of Open Access Journals (Sweden)

Katsuki Hayashi

2016-11-01

Full Text Available Recently, the emergent dynamics in multiplex networks, composed of layers of multiple networks, has been discussed extensively in network sciences. However, little is still known about whether and how the evolution of strategy for selecting a layer to participate in can contribute to the emergence of cooperative behaviors in multiplex networks of social interactions. To investigate these issues, we constructed a coevolutionary model of cooperation and layer selection strategies in which each an individual selects one layer from multiple layers of social networks and plays the Prisoner’s Dilemma with neighbors in the selected layer. We found that the proportion of cooperative strategies increased with increasing the number of layers regardless of the degree of dilemma, and this increase occurred due to a cyclic coevolution process of game strategies and layer selection strategies. We also showed that the heterogeneity of links among layers is a key factor for multiplex networks to facilitate the evolution of cooperation, and such positive effects on cooperation were observed regardless of the difference in the stochastic properties of network topologies.

A Novel Quantum Solution to Privacy-Preserving Nearest Neighbor Query in Location-Based Services

Science.gov (United States)

Luo, Zhen-yu; Shi, Run-hua; Xu, Min; Zhang, Shun

2018-04-01

We present a cheating-sensitive quantum protocol for Privacy-Preserving Nearest Neighbor Query based on Oblivious Quantum Key Distribution and Quantum Encryption. Compared with the classical related protocols, our proposed protocol has higher security, because the security of our protocol is based on basic physical principles of quantum mechanics, instead of difficulty assumptions. Especially, our protocol takes single photons as quantum resources and only needs to perform single-photon projective measurement. Therefore, it is feasible to implement this protocol with the present technologies.

Competing neighbors: light perception and root function

NARCIS (Netherlands)

Gundel, Pedro; Pierik, Ronald; Mommer, L.; Ballaré, C.L.

Plant responses to competition have often been described as passive consequences of reduced resource availability. However, plants have mechanisms to forage for favorable conditions and anticipate competition scenarios. Despite the progresses made in understanding the role of light signaling in

Competing neighbors: light perception and root function

NARCIS (Netherlands)

Gundel, P.E.; Pierik, R.; Mommer, L.; Ballare, L.

2014-01-01

Plant responses to competition have often been described as passive consequences of reduced resource availability. However, plants have mechanisms to forage for favorable conditions and anticipate competition scenarios. Despite the progresses made in understanding the role of light signaling in

SiO{sub 2} nanodot arrays using functionalized block copolymer templates and selective silylation

Energy Technology Data Exchange (ETDEWEB)

Kim, Su Min; Ku, Se Jin; Kim, Jin-Baek, E-mail: kjb@kaist.ac.kr [Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), 373-1, Guseong-Dong, Yuseong-Gu, Daejeon, 305-701 (Korea, Republic of)

2010-06-11

Silicon oxide nanodot arrays were fabricated using functionalized block copolymer templates and selective silylation. A polystyrene-b-poly(acrylic acid/acrylic anhydride) (PS-b-PAA/AN) thin film containing spherical nanodomains was used as a template to build nanoscopic silica structures. A PS-b-PAA/AN thin film was prepared by acid-catalyzed thermal deprotection of polystyrene-b-poly(tert-butyl acrylate) on an SU-8 resist film containing a photoacid generator. This resulting film has excellent solvent and thermal resistance due to crosslinked anhydride linkages in carboxyl-functionalized PAA/AN block domains. Silicon was introduced by spin-spraying of hexamethyldisilazane (HMDS) over the entire surface of a self-assembled PS-b-PAA/AN thin film. HMDS was selectively reacted with carboxylic acid groups in spherical domains of a PAA/AN block. SiO{sub 2} nanodot arrays were generated by oxygen reactive ion etching.

Competing growth processes induced by next-nearest-neighbor interactions: Effects on meandering wavelength and stiffness

Science.gov (United States)

Blel, Sonia; Hamouda, Ajmi BH.; Mahjoub, B.; Einstein, T. L.

2017-02-01

In this paper we explore the meandering instability of vicinal steps with a kinetic Monte Carlo simulations (kMC) model including the attractive next-nearest-neighbor (NNN) interactions. kMC simulations show that increase of the NNN interaction strength leads to considerable reduction of the meandering wavelength and to weaker dependence of the wavelength on the deposition rate F. The dependences of the meandering wavelength on the temperature and the deposition rate obtained with simulations are in good quantitative agreement with the experimental result on the meandering instability of Cu(0 2 24) [T. Maroutian et al., Phys. Rev. B 64, 165401 (2001), 10.1103/PhysRevB.64.165401]. The effective step stiffness is found to depend not only on the strength of NNN interactions and the Ehrlich-Schwoebel barrier, but also on F. We argue that attractive NNN interactions intensify the incorporation of adatoms at step edges and enhance step roughening. Competition between NNN and nearest-neighbor interactions results in an alternative form of meandering instability which we call "roughening-limited" growth, rather than attachment-detachment-limited growth that governs the Bales-Zangwill instability. The computed effective wavelength and the effective stiffness behave as λeff˜F-q and β˜eff˜F-p , respectively, with q ≈p /2 .

Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN classification method

Directory of Open Access Journals (Sweden)

D.A. Adeniyi

2016-01-01

Full Text Available The major problem of many on-line web sites is the presentation of many choices to the client at a time; this usually results to strenuous and time consuming task in finding the right product or information on the site. In this work, we present a study of automatic web usage data mining and recommendation system based on current user behavior through his/her click stream data on the newly developed Really Simple Syndication (RSS reader website, in order to provide relevant information to the individual without explicitly asking for it. The K-Nearest-Neighbor (KNN classification method has been trained to be used on-line and in Real-Time to identify clients/visitors click stream data, matching it to a particular user group and recommend a tailored browsing option that meet the need of the specific user at a particular time. To achieve this, web users RSS address file was extracted, cleansed, formatted and grouped into meaningful session and data mart was developed. Our result shows that the K-Nearest Neighbor classifier is transparent, consistent, straightforward, simple to understand, high tendency to possess desirable qualities and easy to implement than most other machine learning techniques specifically when there is little or no prior knowledge about data distribution.

Habitat quality influences population distribution, individual space use and functional responses in habitat selection by a large herbivore.

Science.gov (United States)

Bjørneraas, Kari; Herfindal, Ivar; Solberg, Erling Johan; Sæther, Bernt-Erik; van Moorter, Bram; Rolandsen, Christer Moe

2012-01-01

Identifying factors shaping variation in resource selection is central for our understanding of the behaviour and distribution of animals. We examined summer habitat selection and space use by 108 Global Positioning System (GPS)-collared moose in Norway in relation to sex, reproductive status, habitat quality, and availability. Moose selected habitat types based on a combination of forage quality and availability of suitable habitat types. Selection of protective cover was strongest for reproducing females, likely reflecting the need to protect young. Males showed strong selection for habitat types with high quality forage, possibly due to higher energy requirements. Selection for preferred habitat types providing food and cover was a positive function of their availability within home ranges (i.e. not proportional use) indicating functional response in habitat selection. This relationship was not found for unproductive habitat types. Moreover, home ranges with high cover of unproductive habitat types were larger, and smaller home ranges contained higher proportions of the most preferred habitat type. The distribution of moose within the study area was partly related to the distribution of different habitat types. Our study shows how distribution and availability of habitat types providing cover and high-quality food shape ungulate habitat selection and space use.

Building good relationships with neighbors of Japan's oldest plant, Tsuruga

International Nuclear Information System (INIS)

Hata, Emi

1992-01-01

Since its establishment in 1957 as a pioneer company of nuclear power development in Japan, the Japan Atomic Power Company (JAPC) has gained a great deal of experience with construction and operation of four nuclear power plants - one gas-cooled reactor, two boiling water reactors (BWRs), and one pressurized water reactor (PWR) - at two sites, Tsuruga and Tokai. To gain the understanding and cooperation of the local community, the Tsuruga station must keep running. Each employee is encouraged to make every possible effort not only to ensure the safe and reliable operation of the two units, but also to ensure conscientious coexistence and coprosperity within the local community. The Tsuruga office in the city and the Public Relations (PR) Pavilion (visitor's center) at the site work together as an open window of communication with the local community. Under these basic philosophies, various good neighbor activities are developed and carried out

Implementation of Nearest Neighbor using HSV to Identify Skin Disease

Science.gov (United States)

Gerhana, Y. A.; Zulfikar, W. B.; Ramdani, A. H.; Ramdhani, M. A.

2018-01-01

Today, Android is one of the most widely used operating system in the world. Most of android device has a camera that could capture an image, this feature could be optimized to identify skin disease. The disease is one of health problem caused by bacterium, fungi, and virus. The symptoms of skin disease usually visible. In this work, the symptoms that captured as image contains HSV in every pixel of the image. HSV can extracted and then calculate to earn euclidean value. The value compared using nearest neighbor algorithm to discover closer value between image testing and image training to get highest value that decide class label or type of skin disease. The testing result show that 166 of 200 or about 80% is accurate. There are some reasons that influence the result of classification model like number of image training and quality of android device’s camera.

A Context-Aware Mobile User Behavior-Based Neighbor Finding Approach for Preference Profile Construction †

Science.gov (United States)

Gao, Qian; Fu, Deqian; Dong, Xiangjun

2016-01-01

In this paper, a new approach is adopted to update the user preference profile by seeking users with similar interests based on the context obtainable for a mobile network instead of from desktop networks. The trust degree between mobile users is calculated by analyzing their behavior based on the context, and then the approximate neighbors are chosen by combining the similarity of the mobile user preference and the trust degree. The approach first considers the communication behaviors between mobile users, the mobile network services they use as well as the corresponding context information. Then a similarity degree of the preference between users is calculated with the evaluation score of a certain mobile web service provided by a mobile user. Finally, based on the time attenuation function, the users with similar preference are found, through which we can dynamically update the target user’s preference profile. Experiments are then conducted to test the effect of the context on the credibility among mobile users, the effect of time decay factors and trust degree thresholds. Simulation shows that the proposed approach outperforms two other methods in terms of Recall Ratio, Precision Ratio and Mean Absolute Error, because neither of them consider the context mobile information. PMID:26805852

k-Nearest Neighbors Algorithm in Profiling Power Analysis Attacks

Directory of Open Access Journals (Sweden)

Z. Martinasek

2016-06-01

Full Text Available Power analysis presents the typical example of successful attacks against trusted cryptographic devices such as RFID (Radio-Frequency IDentifications and contact smart cards. In recent years, the cryptographic community has explored new approaches in power analysis based on machine learning models such as Support Vector Machine (SVM, RF (Random Forest and Multi-Layer Perceptron (MLP. In this paper, we made an extensive comparison of machine learning algorithms in the power analysis. For this purpose, we implemented a verification program that always chooses the optimal settings of individual machine learning models in order to obtain the best classification accuracy. In our research, we used three datasets, the first containing the power traces of an unprotected AES (Advanced Encryption Standard implementation. The second and third datasets are created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4. The obtained results revealed some interesting facts, namely, an elementary k-NN (k-Nearest Neighbors algorithm, which has not been commonly used in power analysis yet, shows great application potential in practice.

Memory and executive functioning in obsessive-compulsive disorder: a selective review.

Science.gov (United States)

Olley, Amanda; Malhi, Gin; Sachdev, Perminder

2007-12-01

The neurocognitive deficits that underlie the unique features of obsessive-compulsive disorder (OCD) are not yet completely understood. This paper reviews the main neuropsychological findings in memory and executive functioning in this disorder, and examines a number of challenges facing this area of research. A selective review of the neuropsychological literature on OCD was conducted using MEDLINE and drawing on literature known to the authors. The neuropsychological profile of OCD appears to be one of primary executive dysfunction. Although memory functioning may be affected, these deficits appear secondary to an executive failure of organizational strategies during encoding. On tasks of executive functioning patients with OCD demonstrate increased response latencies, perseveration of responses, and difficulties utilizing feedback to adapt to change. A statistical meta-analysis was not performed and only the cognitive domains of memory and executive functioning were examined. Given the prominence of chronic doubt and indecision in clinical settings, it is surprising that decision making as a cognitive construct as related to OCD has not received greater attention in the neuropsychological literature. On the basis of emerging literature we suggest that it is a potential area of dysfunction and one that warrants further investigation as it may assist in enhancing our understanding of the pathophysiology of OCD.

Hole motion in the t-J and Hubbard models: Effect of a next-nearest-neighbor hopping

International Nuclear Information System (INIS)

Gagliano, E.; Bacci, S.; Dagotto, E.

1990-01-01

Using exact diagonalization techniques, we study one dynamical hole in the two-dimensional t-J and Hubbard models on a square lattice including a next-nearest-neighbor hopping t'. We present the phase diagram in the parameter space (J/t,t'/t), discussing the ground-state properties of the hole. At J=0, a crossing of levels exists at some value of t' separating a ferromagnetic from an antiferromagnetic ground state. For nonzero J, at least four different regions appear where the system behaves like an antiferromagnet or a (not fully saturated) ferromagnet. We study the quasiparticle behavior of the hole, showing that for small values of |t'| the previously presented string picture is still valid. We also find that, for a realistic set of parameters derived from the Cu-O Hamiltonian, the hole has momentum (π/2,π/2), suggesting an enhancement of the p-wave superconducting mode due to the second-neighbor interactions in the spin-bag picture. Results for the t-t'-U model are also discussed with conclusions similar to those of the t-t'-J model. In general we found that t'=0 is not a singular point of these models

Classification of matrix-product ground states corresponding to one-dimensional chains of two-state sites of nearest neighbor interactions

International Nuclear Information System (INIS)

Fatollahi, Amir H.; Khorrami, Mohammad; Shariati, Ahmad; Aghamohammadi, Amir

2011-01-01

A complete classification is given for one-dimensional chains with nearest-neighbor interactions having two states in each site, for which a matrix product ground state exists. The Hamiltonians and their corresponding matrix product ground states are explicitly obtained.

The influence of further-neighbor spin-spin interaction on a ground state of 2D coupled spin-electron model in a magnetic field

Science.gov (United States)

Čenčariková, Hana; Strečka, Jozef; Gendiar, Andrej; Tomašovičová, Natália

2018-05-01

An exhaustive ground-state analysis of extended two-dimensional (2D) correlated spin-electron model consisting of the Ising spins localized on nodal lattice sites and mobile electrons delocalized over pairs of decorating sites is performed within the framework of rigorous analytical calculations. The investigated model, defined on an arbitrary 2D doubly decorated lattice, takes into account the kinetic energy of mobile electrons, the nearest-neighbor Ising coupling between the localized spins and mobile electrons, the further-neighbor Ising coupling between the localized spins and the Zeeman energy. The ground-state phase diagrams are examined for a wide range of model parameters for both ferromagnetic as well as antiferromagnetic interaction between the nodal Ising spins and non-zero value of external magnetic field. It is found that non-zero values of further-neighbor interaction leads to a formation of new quantum states as a consequence of competition between all considered interaction terms. Moreover, the new quantum states are accompanied with different magnetic features and thus, several kinds of field-driven phase transitions are observed.

Adaptive evolution in locomotor performance: How selective pressures and functional relationships produce diversity.

Science.gov (United States)

Scales, Jeffrey A; Butler, Marguerite A

2016-01-01

Despite the complexity of nature, most comparative studies of phenotypic evolution consider selective pressures in isolation. When competing pressures operate on the same system, it is commonly expected that trade-offs will occur that will limit the evolution of phenotypic diversity, however, it is possible that interactions among selective pressures may promote diversity instead. We explored the evolution of locomotor performance in lizards in relation to possible selective pressures using the Ornstein-Uhlenbeck process. Here, we show that a combination of selection based on foraging mode and predator escape is required to explain variation in performance phenotypes. Surprisingly, habitat use contributed little explanatory power. We find that it is possible to evolve very different abilities in performance which were previously thought to be tightly correlated, supporting a growing literature that explores the many-to-one mapping of morphological design. Although we generally find the expected trade-off between maximal exertion and speed, this relationship surprisingly disappears when species experience selection for both performance types. We conclude that functional integration need not limit adaptive potential, and that an integrative approach considering multiple major influences on a phenotype allows a more complete understanding of adaptation and the evolution of diversity. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Orientation of rod molecules in selective slits: a density functional theory

International Nuclear Information System (INIS)

Xu Xiaofei; Cao Dapeng; Wang Wenchuan

2008-01-01

A density functional theory (DFT) is used to investigate molecular orientation of rod fluids in selective slits. The DFT approach combines a modified fundamental measure theory (MFMT) for excluded-volume effect, the first-order thermodynamics perturbation theory for chain connectivity and the mean-field approximation for van der Waals (vdW) attraction. To study the molecular orientation, the intramolecular bonding orientation function is introduced into the DFT. First, we investigate the orientation of the surfactant-like rod molecule of AB 6 (i.e. ABBBBBB) in a nanoslit of H 20σ, where the walls selectively adsorb segment 'A'. It is observed that, with the increase of the surface energy of the wall to head segment (i.e. 'A' segment) of the rod molecule, the rod molecules adsorbed on the wall present the perpendicular orientation gradually, and assemble into a smectic-A-like monolayer finally. In addition, we also explore the molecular orientation of the rods with both end segments preferring to the wall, i.e. AB 8 A and AB 7 A, in a nanoslit of H = 10σ. Interestingly, the AB 8 A rod monolayer is compatible with either a smectic-A-like or a smectic-C-like organization, but AB 7 A rod molecules exhibit the smectic-A-like organization. The orientation factor of the AB 7 A rod molecule reaches 1, suggesting that AB 7 A rod molecules self-assemble into an ordered structure with perfectly perpendicular orientation to the wall.

Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

OpenAIRE

Samir Brahim Belhaouari

2009-01-01

By taking advantage of both k-NN which is highly accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less ...

Refuse dumps from leaf-cutting ant nests reduce the intensity of above-ground competition among neighboring plants in a Patagonian steppe

Science.gov (United States)

Farji-Brener, Alejandro G.; Lescano, María Natalia

2017-11-01

In arid environments, the high availability of sunlight due to the scarcity of trees suggests that plant competition take place mainly belowground for water and nutrients. However, the occurrence of soil disturbances that increase nutrient availability and thereby promote plant growth may enhance shoot competition between neighboring plants. We conducted a greenhouse experiment to evaluate the influence of the enriched soil patches generated by the leaf-cutting ant, Acromyrmex lobicornis, on the performance of the alien forb Carduus thoermeri (Asteraceae) under different intraspecific competition scenarios. Our results showed that substrate type and competition scenario affected mainly aboveground plant growth. As expected, plants growing without neighbors and in nutrient-rich ant refuse dumps showed more aboveground biomass than plants growing with neighbors and in nutrient-poor steppe soils. However, aboveground competition was more intense in nutrient-poor substrates: plants under shoot and full competition growing in the nutrient-rich ant refuse dumps showed higher biomass than those growing on steppe soils. Belowground biomass was similar among focal plants growing under different substrate type. Our results support the traditional view that increments in resource availability reduce competition intensity. Moreover, the fact that seedlings in this sunny habitat mainly compete aboveground illustrates how limiting factors may be scale-dependent and change in importance as plants grow.

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

Science.gov (United States)

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

Variant Selection during Alpha Precipitation in Titanium Alloys: A Simulation Study

Science.gov (United States)

Shi, Rongpei

Variant selection of alpha phase during its precipitation from beta matrix plays a key role in determining transformation texture and final mechanical properties of alpha/beta and beta titanium alloys. In this study we develop a three-dimensional quantitative phase field model (PFM) to predict variant selection and microstructure evolution during beta to alpha transformation in polycrystalline Ti-6Al-4V under the influence of different processing variables. The model links its inputs directly to thermodynamic and mobility databases, and incorporates crystallography of BCC to HCP transformation, elastic anisotropy, defects within semi-coherent alpha/beta interfaces and elastic inhomogeneities among different beta grains. In particular, microstructure and transformation texture evolution are treated simultaneously via orientation distribution function (ODF) modeling of alpha/beta two-phase microstructure in beta polycrystalline obtained by PFM. It is found that, for a given undercooling, the development of transformation texture of the alpha phase due to variant selection during precipitation depends on both externally applied stress or strain, initial texture state of parent beta sample and internal stress generated by the precipitation reaction itself. Moreover, the growth of pre-existing widmanstatten alpha precipitates is accompanied by selective nucleation and growth of secondary alpha plates of preferred variants. We further develop a crystallographic model based on the ideal Burgers orientation relationship (BOR) between GBalpha and one of the two adjacent beta grains to investigate how a prior beta grain boundary contributes to variant selection of grain boundary allotriomorph (GBalpha). The model is able to predict all possible special beta grain boundaries where GBalpha is able to maintain BOR with two neighboring grain. In particular, the model has been used to evaluate the validity of all current empirical variant selection rules to obtain more insight of

Nearest neighbor spacing distributions of low-lying levels of vibrational nuclei

International Nuclear Information System (INIS)

Abul-Magd, A.Y.; Simbel, M.H.

1996-01-01

Energy-level statistics are considered for nuclei whose Hamiltonian is divided into intrinsic and collective-vibrational terms. The levels are described as a random superposition of independent sequences, each corresponding to a given number of phonons. The intrinsic motion is assumed chaotic. The level spacing distribution is found to be intermediate between the Wigner and Poisson distributions and similar in form to the spacing distribution of a system with classical phase space divided into separate regular and chaotic domains. We have obtained approximate expressions for the nearest neighbor spacing and cumulative spacing distribution valid when the level density is described by a constant-temperature formula and not involving additional free parameters. These expressions have been able to achieve good agreement with the experimental spacing distributions. copyright 1996 The American Physical Society

Guilt-selective functional disconnection of anterior temporal and subgenual cortices in major depressive disorder.

Science.gov (United States)

Green, Sophie; Lambon Ralph, Matthew A; Moll, Jorge; Deakin, John F W; Zahn, Roland

2012-10-01

Proneness to overgeneralization of self-blame is a core part of cognitive vulnerability to major depressive disorder (MDD) and remains dormant after remission of symptoms. Current neuroanatomical models of MDD, however, assume general increases of negative emotions and are unable to explain biases toward emotions entailing self-blame (eg, guilt) relative to those associated with blaming others (eg, indignation). Recent functional magnetic resonance imaging (fMRI) studies in healthy participants have shown that moral feelings such as guilt activate representations of social meaning within the right superior anterior temporal lobe (ATL). Furthermore, this area was selectively coupled with the subgenual cingulate cortex and adjacent septal region (SCSR) during the experience of guilt compared with indignation. Despite its psychopathological importance, the functional neuroanatomy of guilt in MDD is unknown. To use fMRI to test the hypothesis that, in comparison with control individuals, participants with remitted MDD exhibit guilt-selective SCSR-ATL decoupling as a marker of deficient functional integration. Case-control study from May 1, 2008, to June 1, 2010. Clinical research facility. Twenty-five patients with remitted MDD (no medication in 16 patients) with no current comorbid Axis I disorders and 22 controls with no personal or family history of MDD. Between-group difference of ATL coupling with a priori SCSR region of interest for guilt vs indignation. We corroborated the prediction of a guilt-selective reduction in ATL-SCSR coupling in MDD vs controls (familywise error-corrected P=.001 over the region of interest) and revealed additional medial frontopolar, right hippocampal, and lateral hypothalamic areas of decoupling while controlling for medication status and intensity of negative emotions. Lower levels of ATL-SCSR coupling were associated with higher scores on a validated measure of overgeneralized self-blame (67-item Interpersonal Guilt Questionnaire

Unsynchronized influenza epidemics in two neighboring subtropical cities

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Xiujuan Tang

2018-04-01

Full Text Available Objective: The aim of this study was to examine the synchrony of influenza epidemics between Hong Kong and Shenzhen, two neighboring subtropical cities in South China. Methods: Laboratory-confirmed influenza data for the period January 2006 to December 2016 were obtained from the Shenzhen Center for Disease Control and Prevention and the Department of Health in Hong Kong. The population data were retrieved from the 2011 population censuses. The weekly rates of laboratory-confirmed influenza cases were compared between Shenzhen and Hong Kong. Results: Unsynchronized influenza epidemics between Hong Kong and Shenzhen were frequently observed during the study period. Influenza A/H1N1 caused a more severe pandemic in Hong Kong in 2009, but the subsequent seasonal epidemics showed similar magnitudes in both cities. Two influenza A/H3N2 dominant epidemic waves were seen in Hong Kong in 2015, but these epidemics were very minor in Shenzhen. More influenza B epidemics occurred in Shenzhen than in Hong Kong. Conclusions: Influenza epidemics appeared to be unsynchronized between Hong Kong and Shenzhen most of the time. Given the close geographical locations of these two cities, this could be due to the strikingly different age structures of their populations. Keywords: Influenza epidemics, Synchrony, Shenzhen, Hong Kong

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

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Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Selectivity switch for nitrogen functionalization of styrene on Au(1 1 1)

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Deng, Xingyi; Friend, Cynthia M.

2008-03-01

Functionalization of styrene to form N-containing hydrocarbons, e.g. 2-phenylaziridine, benzonitrile, and benzyl nitrile, is achieved by reaction with adsorbed NH a and N a on Au(1 1 1). Electron-induced decomposition of condensed NH 3 was used to produce NH a, N a and H a on Au(1 1 1) at 110 K. The selectivity of the reactions is strongly dependent on the relative concentrations of the surface species. The addition of NH to styrene results in the production of 2-phenylaziridine, whereas adsorbed N and H atoms lead to the formation of nitriles benzonitrile and benzyl nitrile and, respectively, ethylbenzene. This work clearly establishes the utility of Au for promoting functionalization of olefins with nitrogen.

Common Nearest Neighbor Clustering—A Benchmark

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Oliver Lemke

2018-02-01

Full Text Available Cluster analyses are often conducted with the goal to characterize an underlying probability density, for which the data-point density serves as an estimate for this probability density. We here test and benchmark the common nearest neighbor (CNN cluster algorithm. This algorithm assigns a spherical neighborhood R to each data point and estimates the data-point density between two data points as the number of data points N in the overlapping region of their neighborhoods (step 1. The main principle in the CNN cluster algorithm is cluster growing. This grows the clusters by sequentially adding data points and thereby effectively positions the border of the clusters along an iso-surface of the underlying probability density. This yields a strict partitioning with outliers, for which the cluster represents peaks in the underlying probability density—termed core sets (step 2. The removal of the outliers on the basis of a threshold criterion is optional (step 3. The benchmark datasets address a series of typical challenges, including datasets with a very high dimensional state space and datasets in which the cluster centroids are aligned along an underlying structure (Birch sets. The performance of the CNN algorithm is evaluated with respect to these challenges. The results indicate that the CNN cluster algorithm can be useful in a wide range of settings. Cluster algorithms are particularly important for the analysis of molecular dynamics (MD simulations. We demonstrate how the CNN cluster results can be used as a discretization of the molecular state space for the construction of a core-set model of the MD improving the accuracy compared to conventional full-partitioning models. The software for the CNN clustering is available on GitHub.

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention.

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Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L

2013-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. We have hypothesized that the changes in neural activity observed during increased cholinergic function reflect an increase in neural efficiency that leads to improved task performance. The current study tested this hypothesis by assessing neural efficiency based on cholinergically-mediated effects on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover fMRI study. Following an infusion of physostigmine (1 mg/h) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Physostigmine administration also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus

Synonymous codon bias and functional constraint on GC3-related DNA backbone dynamics in the prokaryotic nucleoid.

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Babbitt, Gregory A; Alawad, Mohammed A; Schulze, Katharina V; Hudson, André O

2014-01-01

While mRNA stability has been demonstrated to control rates of translation, generating both global and local synonymous codon biases in many unicellular organisms, this explanation cannot adequately explain why codon bias strongly tracks neighboring intergene GC content; suggesting that structural dynamics of DNA might also influence codon choice. Because minor groove width is highly governed by 3-base periodicity in GC, the existence of triplet-based codons might imply a functional role for the optimization of local DNA molecular dynamics via GC content at synonymous sites (≈GC3). We confirm a strong association between GC3-related intrinsic DNA flexibility and codon bias across 24 different prokaryotic multiple whole-genome alignments. We develop a novel test of natural selection targeting synonymous sites and demonstrate that GC3-related DNA backbone dynamics have been subject to moderate selective pressure, perhaps contributing to our observation that many genes possess extreme DNA backbone dynamics for their given protein space. This dual function of codons may impose universal functional constraints affecting the evolution of synonymous and non-synonymous sites. We propose that synonymous sites may have evolved as an 'accessory' during an early expansion of a primordial genetic code, allowing for multiplexed protein coding and structural dynamic information within the same molecular context. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Strong Selective Adsorption of Polymers.

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Ge, Ting; Rubinstein, Michael

2015-06-09

A scaling theory is developed for selective adsorption of polymers induced by the strong binding between specific monomers and complementary surface adsorption sites. By "selective" we mean specific attraction between a subset of all monomers, called "sticky", and a subset of surface sites, called "adsorption sites". We demonstrate that, in addition to the expected dependence on the polymer volume fraction ϕ bulk in the bulk solution, selective adsorption strongly depends on the ratio between two characteristic length scales, the root-mean-square distance l between neighboring sticky monomers along the polymer, and the average distance d between neighboring surface adsorption sites. The role of the ratio l / d arises from the fact that a polymer needs to deform to enable the spatial commensurability between its sticky monomers and the surface adsorption sites for selective adsorption. We study strong selective adsorption of both telechelic polymers with two end monomers being sticky and multisticker polymers with many sticky monomers between sticky ends. For telechelic polymers, we identify four adsorption regimes at l / d 1, we expect that the adsorption layer at exponentially low ϕ bulk consists of separated unstretched loops, while as ϕ bulk increases the layer crosses over to a brush of extended loops with a second layer of weakly overlapping tails. For multisticker chains, in the limit of exponentially low ϕ bulk , adsorbed polymers are well separated from each other. As l / d increases, the conformation of an individual polymer changes from a single-end-adsorbed "mushroom" to a random walk of loops. For high ϕ bulk , adsorbed polymers at small l / d are mushrooms that cover all the adsorption sites. At sufficiently large l / d , adsorbed multisticker polymers strongly overlap. We anticipate the formation of a self-similar carpet and with increasing l / d a two-layer structure with a brush of loops covered by a self-similar carpet. As l / d exceeds the

Software For Computing Selected Functions

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Grant, David C.

1992-01-01

Technical memorandum presents collection of software packages in Ada implementing mathematical functions used in science and engineering. Provides programmer with function support in Pascal and FORTRAN, plus support for extended-precision arithmetic and complex arithmetic. Valuable for testing new computers, writing computer code, or developing new computer integrated circuits.

Functional MRI mapping of visual function and selective attention for performance assessment and presurgical planning using conjunctive visual search.

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Parker, Jason G; Zalusky, Eric J; Kirbas, Cemil

2014-03-01

Accurate mapping of visual function and selective attention using fMRI is important in the study of human performance as well as in presurgical treatment planning of lesions in or near visual centers of the brain. Conjunctive visual search (CVS) is a useful tool for mapping visual function during fMRI because of its greater activation extent compared with high-capacity parallel search processes. The purpose of this work was to develop and evaluate a CVS that was capable of generating consistent activation in the basic and higher level visual areas of the brain by using a high number of distractors as well as an optimized contrast condition. Images from 10 healthy volunteers were analyzed and brain regions of greatest activation and deactivation were determined using a nonbiased decomposition of the results at the hemisphere, lobe, and gyrus levels. The results were quantified in terms of activation and deactivation extent and mean z-statistic. The proposed CVS was found to generate robust activation of the occipital lobe, as well as regions in the middle frontal gyrus associated with coordinating eye movements and in regions of the insula associated with task-level control and focal attention. As expected, the task demonstrated deactivation patterns commonly implicated in the default-mode network. Further deactivation was noted in the posterior region of the cerebellum, most likely associated with the formation of optimal search strategy. We believe the task will be useful in studies of visual and selective attention in the neuroscience community as well as in mapping visual function in clinical fMRI.

Clinical evaluation of 64-slice CT assessment of global left ventricular function using automated cardiac phase selection

International Nuclear Information System (INIS)

Joemai, Raoul M.S.; Geleijns, Joemai; Veldkamp, Wouter J.H.; Kroft, Lucia J.M.

2008-01-01

Left ventricular (LV) function provides prognostic information regarding the morbidity and mortality of patients. An automated cardiac phase selection algorithm has the potential to support the assessment of LV function with computed tomography (CT). This algorithm is clinically evaluated for 64-slice cardiac CT. Examinations of twenty consecutive patients were selected. Electrocardiogram gated contrast-enhanced CT was performed. Reconstructions were performed using an automated and a manual method, followed by the determination of the global LV function. Significances were tested using 2-sided Student's t-tests. Reduction in post processing time and storage capacity were estimated. A slightly smaller mean end-systolic volume was found with the automated method (52±18 ml vs 54±17 ml, p=0.02, r=0.99). The mean LV ejection fraction was slightly larger with the automated method (65±8% vs 64±8%, p=0.004, r=0.99). The estimated reduction in post processing time was maximal 5 min per patient with a potential 80% data storage reduction. Results of the automated phase selection algorithm are similar to the manual method. The automated tool reduces post processing time, reconstruction time and transfer time. (author)

Lysenin Toxin Membrane Insertion Is pH-Dependent but Independent of Neighboring Lysenins.

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Munguira, Ignacio L B; Takahashi, Hirohide; Casuso, Ignacio; Scheuring, Simon

2017-11-07

Pore-forming toxins form a family of proteins that act as virulence factors of pathogenic bacteria, but similar proteins are found in all kingdoms of life, including the vertebrate immune system. They are secreted as soluble monomers that oligomerize on target membranes in the so-called prepore state; after activation, they insert into the membrane and adopt the pore state. Lysenin is a pore-forming toxin from the earthworm Eisenida foetida, of which both the soluble and membrane-inserted structures are solved. However, the activation and membrane-insertion mechanisms have remained elusive. Here, we used high-speed atomic force microscopy to directly visualize the membrane-insertion mechanism. Changing the environmental pH from pH 7.5 to below pH 6.0 favored membrane insertion. We detected a short α-helix in the soluble structure that comprised three glutamic acids (Glu92, Glu94, and Glu97) that we hypothesized may represent a pH-sensor (as in similar toxins, e.g., Listeriolysin). Mutant lysenin still can form pores, but mutating these glutamic acids to glutamines rendered the toxin pH-insensitive. On the other hand, toxins in the pore state did not favor insertion of neighboring prepores; indeed, pore insertion breaks the hexagonal ordered domains of prepores and separates from neighboring molecules in the membrane. pH-dependent activation of toxins may represent a common feature of pore-forming toxins. High-speed atomic force microscopy with single-molecule resolution at high temporal resolution and the possibility of exchanging buffers during the experiments presents itself as a unique tool for the study of toxin-state conversion. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Development of new methods in modern selective organic synthesis: preparation of functionalized molecules with atomic precision

International Nuclear Information System (INIS)

Ananikov, V P; Khemchyan, L L; Ivanova, Yu V; Dilman, A D; Levin, V V; Bukhtiyarov, V I; Sorokin, A M; Prosvirin, I P; Romanenko, A V; Simonov, P A; Vatsadze, S Z; Medved'ko, A V; Nuriev, V N; Nenajdenko, V G; Shmatova, O I; Muzalevskiy, V M; Koptyug, I V; Kovtunov, K V; Zhivonitko, V V; Likholobov, V A

2014-01-01

The challenges of the modern society and the growing demand of high-technology sectors of industrial production bring about a new phase in the development of organic synthesis. A cutting edge of modern synthetic methods is introduction of functional groups and more complex structural units into organic molecules with unprecedented control over the course of chemical transformation. Analysis of the state-of-the-art achievements in selective organic synthesis indicates the appearance of a new trend — the synthesis of organic molecules, biologically active compounds, pharmaceutical substances and smart materials with absolute selectivity. Most advanced approaches to organic synthesis anticipated in the near future can be defined as 'atomic precision' in chemical reactions. The present review considers selective methods of organic synthesis suitable for transformation of complex functionalized molecules under mild conditions. Selected key trends in the modern organic synthesis are considered including the preparation of organofluorine compounds, catalytic cross-coupling and oxidative cross-coupling reactions, atom-economic addition reactions, methathesis processes, oxidation and reduction reactions, synthesis of heterocyclic compounds, design of new homogeneous and heterogeneous catalytic systems, application of photocatalysis, scaling up synthetic procedures to industrial level and development of new approaches to investigation of mechanisms of catalytic reactions. The bibliography includes 840 references

A surface acoustic wave sensor functionalized with a polypyrrole molecularly imprinted polymer for selective dopamine detection.

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Maouche, Naima; Ktari, Nadia; Bakas, Idriss; Fourati, Najla; Zerrouki, Chouki; Seydou, Mahamadou; Maurel, François; Chehimi, Mohammed Mehdi

2015-11-01

A surface acoustic wave sensor operating at 104 MHz and functionalized with a polypyrrole molecularly imprinted polymer has been designed for selective detection of dopamine (DA). Optimization of pyrrole/DA ratio, polymerization and immersion times permitted to obtain a highly selective sensor, which has a sensitivity of 0.55°/mM (≈ 550 Hz/mM) and a detection limit of ≈ 10 nM. Morphology and related roughness parameters of molecularly imprinted polymer surfaces, before and after extraction of DA, as well as that of the non imprinted polymer were characterized by atomic force microscopy. The developed chemosensor selectively recognized dopamine over the structurally similar compound 4-hydroxyphenethylamine (referred as tyramine), or ascorbic acid,which co-exists with DA in body fluids at a much higher concentration. Selectivity tests were also carried out with dihydroxybenzene, for which an unexpected phase variation of order of 75% of the DA one was observed. Quantum chemical calculations, based on the density functional theory, were carried out to determine the nature of interactions between each analyte and the PPy matrix and the DA imprinted PPy polypyrrole sensing layer in order to account for the important phase variation observed during dihydroxybenzene injection. Copyright © 2015 John Wiley & Sons, Ltd.

Proteomic characterization of host response to Yersinia pestis and near neighbors

International Nuclear Information System (INIS)

Chromy, Brett A.; Perkins, Julie; Heidbrink, Jenny L.; Gonzales, Arlene D.; Murphy, Gloria A.; Fitch, J. Patrick; McCutchen-Maloney, Sandra L.

2004-01-01

Host-pathogen interactions result in protein expression changes within both the host and the pathogen. Here, results from proteomic characterization of host response following exposure to Yersinia pestis, the causative agent of plague, and to two near neighbors, Yersinia pseudotuberculosis and Yersinia enterocolitica, are reported. Human monocyte-like cells were chosen as a model for macrophage immune response to pathogen exposure. Two-dimensional electrophoresis followed by mass spectrometry was used to identify host proteins with differential expression following exposure to these three closely related Yersinia species. This comparative proteomic characterization of host response clearly shows that host protein expression patterns are distinct for the different pathogen exposures, and contributes to further understanding of Y. pestis virulence and host defense mechanisms. This work also lays the foundation for future studies aimed at defining biomarkers for presymptomatic detection of plague

Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods

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Kenneth B. Pierce; Janet L. Ohmann; Michael C. Wimberly; Matthew J. Gregory; Jeremy S. Fried

2009-01-01

Land managers need consistent information about the geographic distribution of wildland fuels and forest structure over large areas to evaluate fire risk and plan fuel treatments. We compared spatial predictions for 12 fuel and forest structure variables across three regions in the western United States using gradient nearest neighbor (GNN) imputation, linear models (...

Dispersion interactions between neighboring Bi atoms in (BiH3 )2 and Te(BiR2 )2.

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Haack, Rebekka; Schulz, Stephan; Jansen, Georg

2018-03-13

Triggered by the observation of a short Bi⋯Bi distance and a BiTeBi bond angle of only 86.6° in the crystal structure of bis(diethylbismuthanyl)tellurane quantum chemical computations on interactions between neighboring Bi atoms in Te(BiR 2 ) 2 molecules (R = H, Me, Et) and in (BiH 3 ) 2 were undertaken. Bi⋯Bi distances atoms were found to significantly shorten upon inclusion of the d shells of the heavy metal atoms into the electron correlation treatment, and it was confirmed that interaction energies from spin component-scaled second-order Møller-Plesset theory (SCS-MP2) agree well with coupled-cluster singles and doubles theory including perturbative triples (CCSD(T)). Density functional theory-based symmetry-adapted perturbation theory (DFT-SAPT) was used to study the anisotropy of the interplay of dispersion attraction and steric repulsion between the Bi atoms. Finally, geometries and relative stabilities of syn-syn and syn-anti conformers of Te(BiR 2 ) 2 (R = H, Me, Et) and interconversion barriers between them were computed. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Selection of Functional Quorum Sensing Systems by Lysogenic Bacteriophages in Pseudomonas aeruginosa

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Miguel A. Saucedo-Mora

2017-08-01

Full Text Available Quorum sensing (QS in Pseudomonas aeruginosa coordinates the expression of virulence factors, some of which are used as public goods. Since their production is a cooperative behavior, it is susceptible to social cheating in which non-cooperative QS deficient mutants use the resources without investing in their production. Nevertheless, functional QS systems are abundant; hence, mechanisms regulating the amount of cheating should exist. Evidence that demonstrates a tight relationship between QS and the susceptibility of bacteria against the attack of lytic phages is increasing; nevertheless, the relationship between temperate phages and QS has been much less explored. Therefore, in this work, we studied the effects of having a functional QS system on the susceptibility to temperate bacteriophages and how this affects the bacterial and phage dynamics. We find that both experimentally and using mathematical models, that the lysogenic bacteriophages D3112 and JBD30 select QS-proficient P. aeruginosa phenotypes as compared to the QS-deficient mutants during competition experiments with mixed strain populations in vitro and in vivo in Galleria mellonella, in spite of the fact that both phages replicate better in the wild-type background. We show that this phenomenon restricts social cheating, and we propose that temperate phages may constitute an important selective pressure toward the conservation of bacterial QS.

Beta-1-Selective Beta-Blockers and Cognitive Functions in Patients With Coronary Artery Disease: A Cross-Sectional Study.

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Burkauskas, Julius; Noreikaite, Aurelija; Bunevicius, Adomas; Brozaitiene, Julija; Neverauskas, Julius; Mickuviene, Narseta; Bunevicius, Robertas

2016-01-01

The association between current beta-1-selective beta-blocker use and cognitive function was evaluated in 722 patients with coronary artery disease without dementia. Beta-1-selective beta-blocker use was associated with worse incidental learning independently of sociodemographic characteristics, clinical coronary artery disease severity, and depression/anxiety.

Evaluation of functional substances in the selected food materials for space agriculture

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Tomita-Yokotani, Kaori; Kimura, Yasuko; Yamashita, Masamichi; Kimura, Shunta; Sato, Seigo; Katoh, Hiroshi; Abe, Yusuke; Ajioka, Reiko

We have been studying the useful life-support system in closed bio-ecosystem for space agriculture. We have already proposed the several species as food material, such as Nostoc sp. HK-01 and Prunnus sp., cyanobacterium and Japanese cherry tree, respectively. The cyanobacterium, Nostoc sp Hk-01, has high tolerances to several space environment. Furthermore, the woody plant materials have useful utilization elements in our habitation environment. The studies of woody plants under a space-environment in the vegetable kingdom have a high contribution to the study of various and exotic environmental responses, too. We have already found that they can produce the important functional substances for human. Here, we will show the evaluation of functional substances in the selected food materials under the possible conditions for space agriculture after cooking.

Distributed Function Calculation over Noisy Networks

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Zhidun Zeng

2016-01-01

Full Text Available Considering any connected network with unknown initial states for all nodes, the nearest-neighbor rule is utilized for each node to update its own state at every discrete-time step. Distributed function calculation problem is defined for one node to compute some function of the initial values of all the nodes based on its own observations. In this paper, taking into account uncertainties in the network and observations, an algorithm is proposed to compute and explicitly characterize the value of the function in question when the number of successive observations is large enough. While the number of successive observations is not large enough, we provide an approach to obtain the tightest possible bounds on such function by using linear programing optimization techniques. Simulations are provided to demonstrate the theoretical results.

A novel and selective fluoride opening of aziridines by XtalFluor-E. synthesis of fluorinated diamino acid derivatives.

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Nonn, Melinda; Kiss, Loránd; Haukka, Matti; Fustero, Santos; Fülöp, Ferenc

2015-03-06

The selective introduction of fluorine onto the skeleton of an aminocyclopentane or cyclohexane carboxylate has been developed through a novel and efficient fluoride opening of an activated aziridine ring with XtalFluor-E. The reaction proceeded through a stereoselective aziridination of the olefinic bond of a bicyclic lactam and regioselective aziridine ring opening with difluorosulfiliminium tetrafluoroborate with the neighboring group assistance of the sulfonamide moiety to yield fluorinated diamino acid derivatives. The method based on the selective aziridine opening by fluoride has been generalized to afford access to mono- or bicyclic fluorinated substances.

Effects of chemical functional groups on elemental mercury adsorption on carbonaceous surfaces

Energy Technology Data Exchange (ETDEWEB)

Liu Jing, E-mail: liujing27@mail.hust.edu.cn [State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074 (China); Cheney, Marcos A. [Department of Natural Sciences, University of Maryland Eastern Shore, Princess Anne, MD 21853 (United States); Wu Fan; Li Meng [State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074 (China)

2011-02-15

A systematic theoretical study using density functional theory is performed to provide molecular-level understanding of the effects of chemical functional groups on mercury adsorption on carbonaceous surfaces. The zigzag and armchair edges were used in modeling the carbonaceous surfaces to simulate different adsorption sites. The edge atoms on the upper side of the models are unsaturated to simulate active sites. All calculations (optimizations, energies, and frequencies) were made at B3PW91 density functional theory level, using RCEP60VDZ basis set for mercury and 6-31G(d) pople basis set for other atoms. The results indicate that the embedding of halogen atom can increase the activity of its neighboring site which in turn increases the adsorption capacity of the carbonaceous surface for Hg{sup 0}. The adsorption belongs to chemisorptions, which is in good agreement with the experimental results. For the effects of oxygen functional groups, lactone, carbonyl and semiquinone favor Hg{sup 0} adsorption because they increase the neighboring site's activity for mercury adsorption. On the contrary, phenol and carboxyl functional groups show a physisorption of Hg{sup 0}, and reduce Hg capture. This result can explain the seemingly conflicting experimental results reported in the literature concerning the influence of oxygen functional groups on mercury adsorption on carbonaceous surface.

Evidence of codon usage in the nearest neighbor spacing distribution of bases in bacterial genomes

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Higareda, M. F.; Geiger, O.; Mendoza, L.; Méndez-Sánchez, R. A.

2012-02-01

Statistical analysis of whole genomic sequences usually assumes a homogeneous nucleotide density throughout the genome, an assumption that has been proved incorrect for several organisms since the nucleotide density is only locally homogeneous. To avoid giving a single numerical value to this variable property, we propose the use of spectral statistics, which characterizes the density of nucleotides as a function of its position in the genome. We show that the cumulative density of bases in bacterial genomes can be separated into an average (or secular) plus a fluctuating part. Bacterial genomes can be divided into two groups according to the qualitative description of their secular part: linear and piecewise linear. These two groups of genomes show different properties when their nucleotide spacing distribution is studied. In order to analyze genomes having a variable nucleotide density, statistically, the use of unfolding is necessary, i.e., to get a separation between the secular part and the fluctuations. The unfolding allows an adequate comparison with the statistical properties of other genomes. With this methodology, four genomes were analyzed Burkholderia, Bacillus, Clostridium and Corynebacterium. Interestingly, the nearest neighbor spacing distributions or detrended distance distributions are very similar for species within the same genus but they are very different for species from different genera. This difference can be attributed to the difference in the codon usage.

Pupil Dilation and EEG Alpha Frequency Band Power Reveal Load on Executive Functions for Link-Selection Processes during Text Reading.

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Christian Scharinger

Full Text Available Executive working memory functions play a central role in reading comprehension. In the present research we were interested in additional load imposed on executive functions by link-selection processes during computer-based reading. For obtaining process measures, we used a methodology of concurrent electroencephalographic (EEG and eye-tracking data recording that allowed us to compare epochs of pure text reading with epochs of hyperlink-like selection processes in an online reading situation. Furthermore, this methodology allowed us to directly compare the two physiological load-measures EEG alpha frequency band power and pupil dilation. We observed increased load on executive functions during hyperlink-like selection processes on both measures in terms of decreased alpha frequency band power and increased pupil dilation. Surprisingly however, the two measures did not correlate. Two additional experiments were conducted that excluded potential perceptual, motor, or structural confounds. In sum, EEG alpha frequency band power and pupil dilation both turned out to be sensitive measures for increased load during hyperlink-like selection processes in online text reading.

A method of neighbor classes based SVM classification for optical printed Chinese character recognition.