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Sample records for determine overlapping network

  1. Correlated edge overlaps in multiplex networks

    NASA Astrophysics Data System (ADS)

    Baxter, Gareth J.; Bianconi, Ginestra; da Costa, Rui A.; Dorogovtsev, Sergey N.; Mendes, José F. F.

    2016-07-01

    We develop the theory of sparse multiplex networks with partially overlapping links based on their local treelikeness. This theory enables us to find the giant mutually connected component in a two-layer multiplex network with arbitrary correlations between connections of different types. We find that correlations between the overlapping and nonoverlapping links markedly change the phase diagram of the system, leading to multiple hybrid phase transitions. For assortative correlations we observe recurrent hybrid phase transitions.

  2. Dynamics of overlapping structures in modular networks.

    PubMed

    Almendral, J A; Leyva, I; Li, D; Sendiña-Nadal, I; Havlin, S; Boccaletti, S

    2010-07-01

    Modularity is a fundamental feature of real networks, being intimately bounded to their functionality, i.e., to their capability of performing parallel tasks in a coordinated way. Although the modular structure of real graphs has been intensively studied, very little is known on the interactions between functional modules of a graph. Here, we present a general method based on synchronization of networking oscillators, that is able to detect overlapping structures in multimodular environments. We furthermore report the full analytical and theoretical description on the relationship between the overlapping dynamics and the underlying network topology. The method is illustrated by means of a series of applications.

  3. Overlapping Community Detection based on Network Decomposition

    NASA Astrophysics Data System (ADS)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  4. Overlapping Community Detection based on Network Decomposition

    PubMed Central

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  5. Visualizing fuzzy overlapping communities in networks.

    PubMed

    Vehlow, Corinna; Reinhardt, Thomas; Weiskopf, Daniel

    2013-12-01

    An important feature of networks for many application domains is their community structure. This is because objects within the same community usually have at least one property in common. The investigation of community structure can therefore support the understanding of object attributes from the network topology alone. In real-world systems, objects may belong to several communities at the same time, i.e., communities can overlap. Analyzing fuzzy community memberships is essential to understand to what extent objects contribute to different communities and whether some communities are highly interconnected. We developed a visualization approach that is based on node-link diagrams and supports the investigation of fuzzy communities in weighted undirected graphs at different levels of detail. Starting with the network of communities, the user can continuously drill down to the network of individual nodes and finally analyze the membership distribution of nodes of interest. Our approach uses layout strategies and further visual mappings to graphically encode the fuzzy community memberships. The usefulness of our approach is illustrated by two case studies analyzing networks of different domains: social networking and biological interactions. The case studies showed that our layout and visualization approach helps investigate fuzzy overlapping communities. Fuzzy vertices as well as the different communities to which they belong can be easily identified based on node color and position.

  6. Infrared lidar overlap function: an experimental determination.

    PubMed

    Guerrero-Rascado, Juan Luis; Costa, Maria João; Bortoli, Daniele; Silva, Ana Maria; Lyamani, Hassan; Alados-Arboledas, Lucas

    2010-09-13

    The most recent works demonstrate that the lidar overlap function, which describes the overlap between the laser beam and the receiver field of view, can be determined experimentally for the 355 and 532 nm channels using Raman signals. Nevertheless, the Raman channels cannot be used to determine the lidar overlap for the infrared channel (1064 nm) because of their low intensity. In addition, many Raman lidar systems only provide inelastic signals with reasonable signal-to-noise ratio at nighttime. In view of this fact, this work presents a modification of that method, based on the comparison of attenuated backscatter profiles derived from lidar and ceilometer, to retrieve the overlap function for the lidar infrared channel. Similarly to the Raman overlap method, the approach presented here allows to derive the overlap correction without an explicit knowledge of all system parameters. The application of the proposed methodology will improve the potential of Raman lidars to investigate the aerosol microphysical properties in the planetary boundary layer, extending the information of 1064 nm backscatter profiles to the ground and allowing the retrieval of microphysical properties practically close to the surface.

  7. Architecture and dynamics of overlapped RNA regulatory networks.

    PubMed

    Lapointe, Christopher P; Preston, Melanie A; Wilinski, Daniel; Saunders, Harriet A J; Campbell, Zachary T; Wickens, Marvin

    2017-08-02

    A single protein can bind and regulate many mRNAs. Multiple proteins with similar specificities often bind and control overlapping sets of mRNAs. Yet, little is known about the architecture or dynamics of overlapped networks. We focused on three proteins with similar structures and related RNA-binding specificities ‒ Puf3p, Puf4p, and Puf5p of S. cerevisiae. Using RNA Tagging, we identified a "super-network" comprised of four sub-networks: Puf3p, Puf4p, and Puf5p sub-networks, and one controlled by both Puf4p and Puf5p. The architecture of individual sub-networks, and thus the super-network, are determined by competition among particular PUF proteins to bind mRNAs, their affinities for binding elements, and the abundances of the proteins. The super-network responds dramatically: the remaining network can either expand or contract. These strikingly opposite outcomes are determined by an interplay between the relative abundance of the RNAs and proteins, and their affinities for one another. The diverse interplay between overlapping RNA-protein networks provides versatile opportunities for regulation and evolution. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  8. Serial FBG sensor network allowing overlapping spectra

    NASA Astrophysics Data System (ADS)

    Abbenseth, S.; Lochmann, S.; Ahrens, A.; Rehm, B.

    2016-05-01

    For structure or material monitoring low impact serial fiber Bragg grating (FBG) networks have attracted increasing research interest. Common sensor networks using wavelength division multiplexing (WDM) for FBG interrogation are limited in their efficiency by the spectral width of their light source, the FBG tuning range and the spectral guard bands. Overlapping spectra are strictly forbidden in this case. Applying time division multiplexing (TDM) or active resonator schemes may overcome these restrictions. However, they introduce other substantial disadvantages like signal roundtrip dependency or sophisticated control of active resonating structures. Code division multiplexing (CDM) as a means of FBG interrogation by simple autocorrelation of appropriate codes has been shown to be superior in this respect. However, it came at the cost of a second spectrometer introducing additional equalization efforts. We demonstrate a new serial FBG sensor network utilizing CDM signal processing for efficient sensor interrogation without the need of a second spectrometer and additional state of polarization (SOP) controlling components. It allows overlapping spectra even when all sensing FBGs are positioned at the same centre wavelength and it shows a high degree of insensitivity to SOP. Sequence inversed keyed (SIK) serial signal processing utilizing quasi-orthogonal balanced codes ensures simple and quick sensor interrogation with high signal-to-interference/noise ratio.

  9. Overlapping community detection using a generative model for networks

    NASA Astrophysics Data System (ADS)

    Wang, Zhenwen; Hu, Yanli; Xiao, Weidong; Ge, Bin

    2013-10-01

    Detecting overlapping communities is a challenging task in analyzing networks, where nodes may belong to more than one community. Many present methods optimize quality functions to extract the communities from a network. In this paper, we present a probabilistic method for detecting overlapping communities using a generative model. The model describes the probability of generating a network with the model parameters, which reflect the communities in the network. The community memberships of each node are determined based on a probabilistic approach using those model parameters, whose values can be obtained by fitting the model to the network. This method has the advantage that the node participation degrees in each community are also computed. The proposed method is compared with some other community detection methods on both synthetic networks and real-world networks. The experiments show that this method is efficient at detecting overlapping communities and can provide better performance on the networks where a majority of nodes belong to more than one community.

  10. Plasticity of Sensorimotor Networks: Multiple Overlapping Mechanisms.

    PubMed

    Buch, Ethan R; Liew, Sook-Lei; Cohen, Leonardo G

    2016-03-16

    Redundancy is an important feature of the motor system, as abundant degrees of freedom are prominent at every level of organization across the central and peripheral nervous systems, and musculoskeletal system. This basic feature results in a system that is both flexible and robust, and which can be sustainably adapted through plasticity mechanisms in response to intrinsic organismal changes and dynamic environments. While much early work of motor system organization has focused on synaptic-based plasticity processes that are driven via experience, recent investigations of neuron-glia interactions, epigenetic mechanisms and large-scale network dynamics have revealed a plethora of plasticity mechanisms that support motor system organization across multiple, overlapping spatial and temporal scales. Furthermore, an important role of these mechanisms is the regulation of intrinsic variability. Here, we review several of these mechanisms and discuss their potential role in neurorehabilitation.

  11. Spousal Network Overlap as a Basis for Spousal Support

    ERIC Educational Resources Information Center

    Cornwell, Benjamin

    2012-01-01

    The role social network structure plays in facilitating flows of support between spouses is often overlooked. This study examined whether levels of support between spouses depended on the degree of overlap between spouses' networks. Network overlap may enhance spouses' support capacities by increasing their understanding of each other's support…

  12. Spousal Network Overlap as a Basis for Spousal Support

    ERIC Educational Resources Information Center

    Cornwell, Benjamin

    2012-01-01

    The role social network structure plays in facilitating flows of support between spouses is often overlooked. This study examined whether levels of support between spouses depended on the degree of overlap between spouses' networks. Network overlap may enhance spouses' support capacities by increasing their understanding of each other's support…

  13. Overlapping community detection in weighted networks via a Bayesian approach

    NASA Astrophysics Data System (ADS)

    Chen, Yi; Wang, Xiaolong; Xiang, Xin; Tang, Buzhou; Chen, Qingcai; Fan, Shixi; Bu, Junzhao

    2017-02-01

    Complex networks as a powerful way to represent complex systems have been widely studied during the past several years. One of the most important tasks of complex network analysis is to detect communities embedded in networks. In the real world, weighted networks are very common and may contain overlapping communities where a node is allowed to belong to multiple communities. In this paper, we propose a novel Bayesian approach, called the Bayesian mixture network (BMN) model, to detect overlapping communities in weighted networks. The advantages of our method are (i) providing soft-partition solutions in weighted networks; (ii) providing soft memberships, which quantify 'how strongly' a node belongs to a community. Experiments on a large number of real and synthetic networks show that our model has the ability in detecting overlapping communities in weighted networks and is competitive with other state-of-the-art models at shedding light on community partition.

  14. Compression of Flow Can Reveal Overlapping-Module Organization in Networks

    NASA Astrophysics Data System (ADS)

    Viamontes Esquivel, Alcides; Rosvall, Martin

    2011-10-01

    To better understand the organization of overlapping modules in large networks with respect to flow, we introduce the map equation for overlapping modules. In this information-theoretic framework, we use the correspondence between compression and regularity detection. The generalized map equation measures how well we can compress a description of flow in the network when we partition it into modules with possible overlaps. When we minimize the generalized map equation over overlapping network partitions, we detect modules that capture flow and determine which nodes at the boundaries between modules should be classified in multiple modules and to what degree. With a novel greedy-search algorithm, we find that some networks, for example, the neural network of the nematode Caenorhabditis elegans, are best described by modules dominated by hard boundaries, but that others, for example, the sparse European-roads network, have an organization of highly overlapping modules.

  15. Geometrical constraint experimental determination of Raman lidar overlap profile.

    PubMed

    Li, Jian; Li, Chengcai; Zhao, Yiming; Li, Jing; Chu, Yiqi

    2016-06-20

    A simple experimental method to determine the overlap profile of Raman lidar is presented in this paper. Based on Mie and Raman backscattering signals and a geometrically constrained condition, the overlap profile of a Raman lidar system can be determined. Our approach simultaneously retrieves the lidar ratio of aerosols, which is one of the most important sources of uncertainty in the overlap profile determination. The results indicate that the overlap factor is significantly influenced by the lidar ratio in experimental methods. A representative case study indicates that the correction of the overlap profile obtained by this method is practical and feasible.

  16. Quantifying and identifying the overlapping community structure in networks

    NASA Astrophysics Data System (ADS)

    Shen, Hua-Wei; Cheng, Xue-Qi; Guo, Jia-Feng

    2009-07-01

    It has been shown that the communities of complex networks often overlap with each other. However, there is no effective method to quantify the overlapping community structure. In this paper, we propose a metric to address this problem. Instead of assuming that one node can only belong to one community, our metric assumes that a maximal clique only belongs to one community. In this way, the overlaps between communities are allowed. To identify the overlapping community structure, we construct a maximal clique network from the original network, and prove that the optimization of our metric on the original network is equivalent to the optimization of Newman's modularity on the maximal clique network. Thus the overlapping community structure can be identified through partitioning the maximal clique network using any modularity optimization method. The effectiveness of our metric is demonstrated by extensive tests on both artificial networks and real world networks with a known community structure. The application to the word association network also reproduces excellent results.

  17. Detection of node group membership in networks with group overlap

    NASA Astrophysics Data System (ADS)

    Sawardecker, E. N.; Sales-Pardo, M.; Amaral, L. A. N.

    2009-02-01

    Most networks found in social and biochemical systems have modular structures. An important question prompted by the modularity of these networks is whether nodes can be said to belong to a single group. If they cannot, we would need to consider the role of “overlapping communities.” Despite some efforts in this direction, the problem of detecting overlapping groups remains unsolved because there is neither a formal definition of overlapping community, nor an ensemble of networks with which to test the performance of group detection algorithms when nodes can belong to more than one group. Here, we introduce an ensemble of networks with overlapping groups. We then apply three group identification methods - modularity maximization, k-clique percolation, and modularity-landscape surveying - to these networks. We find that the modularity-landscape surveying method is the only one able to detect heterogeneities in node memberships, and that those heterogeneities are only detectable when the overlap is small. Surprisingly, we find that the k-clique percolation method is unable to detect node membership for the overlapping case.

  18. Efficient discovery of overlapping communities in massive networks

    PubMed Central

    Gopalan, Prem K.; Blei, David M.

    2013-01-01

    Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks. PMID:23950224

  19. Efficient discovery of overlapping communities in massive networks.

    PubMed

    Gopalan, Prem K; Blei, David M

    2013-09-03

    Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks.

  20. Peer Network Overlap in Twin, Sibling, and Friend Dyads

    ERIC Educational Resources Information Center

    McGuire, Shirley; Segal, Nancy L.

    2013-01-01

    Research suggests that sibling–peer connections are important for understanding adolescent problem behaviors. Using a novel behavioral genetic design, the current study investigated peer network overlap in 300 child–child pairs (aged 7-13 years) in 5 dyad types: monozygotic (MZ), dizygotic twins, full siblings (FSs), friend pairs, and virtual…

  1. Peer Network Overlap in Twin, Sibling, and Friend Dyads

    ERIC Educational Resources Information Center

    McGuire, Shirley; Segal, Nancy L.

    2013-01-01

    Research suggests that sibling–peer connections are important for understanding adolescent problem behaviors. Using a novel behavioral genetic design, the current study investigated peer network overlap in 300 child–child pairs (aged 7-13 years) in 5 dyad types: monozygotic (MZ), dizygotic twins, full siblings (FSs), friend pairs, and virtual…

  2. A local immunization strategy for networks with overlapping community structure

    NASA Astrophysics Data System (ADS)

    Taghavian, Fatemeh; Salehi, Mostafa; Teimouri, Mehdi

    2017-02-01

    Since full coverage treatment is not feasible due to limited resources, we need to utilize an immunization strategy to effectively distribute the available vaccines. On the other hand, the structure of contact network among people has a significant impact on epidemics of infectious diseases (such as SARS and influenza) in a population. Therefore, network-based immunization strategies aim to reduce the spreading rate by removing the vaccinated nodes from contact network. Such strategies try to identify more important nodes in epidemics spreading over a network. In this paper, we address the effect of overlapping nodes among communities on epidemics spreading. The proposed strategy is an optimized random-walk based selection of these nodes. The whole process is local, i.e. it requires contact network information in the level of nodes. Thus, it is applicable to large-scale and unknown networks in which the global methods usually are unrealizable. Our simulation results on different synthetic and real networks show that the proposed method outperforms the existing local methods in most cases. In particular, for networks with strong community structures, high overlapping membership of nodes or small size communities, the proposed method shows better performance.

  3. Uncovering Overlap Community Structure in Complex Networks Using Particle Competition

    NASA Astrophysics Data System (ADS)

    Breve, Fabricio; Zhao, Liang; Quiles, Marcos

    Identification and classification of overlap nodes in communities is an important topic in data mining. In this paper, a new clustering method to uncover overlap nodes in complex networks is proposed. It is based on particles walking and competing with each other, using random-deterministic movement. The new community detection algorithm can output not only hard labels, but also continuous-valued output (soft labels), which corresponds to the levels of membership from the nodes to each of the communities. Computer simulations were performed with synthetic and real data and good results were achieved.

  4. A model for evolution of overlapping community networks

    NASA Astrophysics Data System (ADS)

    Karan, Rituraj; Biswal, Bibhu

    2017-05-01

    A model is proposed for the evolution of network topology in social networks with overlapping community structure. Starting from an initial community structure that is defined in terms of group affiliations, the model postulates that the subsequent growth and loss of connections is similar to the Hebbian learning and unlearning in the brain and is governed by two dominant factors: the strength and frequency of interaction between the members, and the degree of overlap between different communities. The temporal evolution from an initial community structure to the current network topology can be described based on these two parameters. It is possible to quantify the growth occurred so far and predict the final stationary state to which the network is likely to evolve. Applications in epidemiology or the spread of email virus in a computer network as well as finding specific target nodes to control it are envisaged. While facing the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities one faces the most basic questions: how do communities evolve in time? This work aims to address this issue by developing a mathematical model for the evolution of community networks and studying it through computer simulation.

  5. Niche Overlap and Network Specialization of Flower-Visiting Bees in an Agricultural System.

    PubMed

    Carvalho, D M; Presley, S J; Santos, G M M

    2014-12-01

    Different resource use strategies manifest as differences in the realized niches of species. Niche segregation may involve several dimensions of the niche, such as diet, space, and time. We measured the level of redundancy and complementarity of a bee-plant interaction network in an agricultural system. Because flower resource diversity is high and resource abundance associated with flowering phenology varies throughout the year, we hypothesized that trophic overlap in the community would be low (i.e., high niche complementarity). In contrast, we expected a combination of physiological constraints and exploitation competition to create high temporal overlap, leading to high redundancy in the time of use of floral resources. Dietary overlap was low (NOih = 0.18): niches of 88% of species pairs had less than 30% overlap. In contrast, temporal overlap was intermediate (NOih = 0.49): niches of 65% of species pairs had 30% to 60% overlap. Network analysis showed that bees separated their dietary niches and had intermediate complementary specialization (H2' = 0.46). In terms of their temporal niches (H2' = 0.12), bees were generalists, with high temporal redundancy. Temperature was not a key factor in the determination of niche overlap, suggesting that environmental factors do not likely have a primary role in determining high redundancy in the temporal use of floral resources. Rather, temporal overlap is likely associated with the timing of nectar production by flowers. Our results suggest that bees partition a wide variety of available floral resources, resulting in low dietary overlap and intermediate temporal overlap.

  6. Statistically validated network of portfolio overlaps and systemic risk

    PubMed Central

    Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien

    2016-01-01

    Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007–2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains). PMID:28000764

  7. Statistically validated network of portfolio overlaps and systemic risk.

    PubMed

    Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien

    2016-12-21

    Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007-2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).

  8. Statistical mechanics of multiplex networks: Entropy and overlap

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra

    2013-06-01

    There is growing interest in multiplex networks where individual nodes take part in several layers of networks simultaneously. This is the case, for example, in social networks where each individual node has different kinds of social ties or transportation systems where each location is connected to another location by different types of transport. Many of these multiplexes are characterized by a significant overlap of the links in different layers. In this paper we introduce a statistical mechanics framework to describe multiplex ensembles. A multiplex is a system formed by N nodes and M layers of interactions where each node belongs to the M layers at the same time. Each layer α is formed by a network Gα. Here we introduce the concept of correlated multiplex ensembles in which the existence of a link in one layer is correlated with the existence of a link in another layer. This implies that a typical multiplex of the ensemble can have a significant overlap of the links in the different layers. Moreover, we characterize microcanonical and canonical multiplex ensembles satisfying respectively hard and soft constraints and we discuss how to construct multiplexes in these ensembles. Finally, we provide the expression for the entropy of these ensembles that can be useful to address different inference problems involving multiplexes.

  9. Non-overlapping Neural Networks in Hydra vulgaris.

    PubMed

    Dupre, Christophe; Yuste, Rafael

    2017-03-24

    To understand the emergent properties of neural circuits, it would be ideal to record the activity of every neuron in a behaving animal and decode how it relates to behavior. We have achieved this with the cnidarian Hydra vulgaris, using calcium imaging of genetically engineered animals to measure the activity of essentially all of its neurons. Although the nervous system of Hydra is traditionally described as a simple nerve net, we surprisingly find instead a series of functional networks that are anatomically non-overlapping and are associated with specific behaviors. Three major functional networks extend through the entire animal and are activated selectively during longitudinal contractions, elongations in response to light, and radial contractions, whereas an additional network is located near the hypostome and is active during nodding. These results demonstrate the functional sophistication of apparently simple nerve nets, and the potential of Hydra and other basal metazoans as a model system for neural circuit studies.

  10. Growing networks of overlapping communities with internal structure

    NASA Astrophysics Data System (ADS)

    Young, Jean-Gabriel; Hébert-Dufresne, Laurent; Allard, Antoine; Dubé, Louis J.

    2016-08-01

    We introduce an intuitive model that describes both the emergence of community structure and the evolution of the internal structure of communities in growing social networks. The model comprises two complementary mechanisms: One mechanism accounts for the evolution of the internal link structure of a single community, and the second mechanism coordinates the growth of multiple overlapping communities. The first mechanism is based on the assumption that each node establishes links with its neighbors and introduces new nodes to the community at different rates. We demonstrate that this simple mechanism gives rise to an effective maximal degree within communities. This observation is related to the anthropological theory known as Dunbar's number, i.e., the empirical observation of a maximal number of ties which an average individual can sustain within its social groups. The second mechanism is based on a recently proposed generalization of preferential attachment to community structure, appropriately called structural preferential attachment (SPA). The combination of these two mechanisms into a single model (SPA+) allows us to reproduce a number of the global statistics of real networks: The distribution of community sizes, of node memberships, and of degrees. The SPA+ model also predicts (a) three qualitative regimes for the degree distribution within overlapping communities and (b) strong correlations between the number of communities to which a node belongs and its number of connections within each community. We present empirical evidence that support our findings in real complex networks.

  11. Investigation of Overlap Correction Techniques for Application in the Micro-Pulse Lidar Network (MPLNET)

    NASA Technical Reports Server (NTRS)

    Berkoff, Timothy A.; Welton, Ellsworth J.; Campbell, James R.; Scott, Vibart S.; Spinhirne, James D.

    2003-01-01

    The Micro-Pulse Lidar NETwork (MPLNET) is comprised of micro-pulse lidars (MPL) stationed around the globe to provide measurements of aerosol and cloud vertical distribution on a continuous basis. MPLNET sites are co-located with sunphotometers in the AErosol Robotic NETwork (AERONET) to provide joint measurements of aerosol optical depth, size, and other inherent optical properties. The IPCC 2001 report discusses . the importance of obtaining routine measurements of aerosol vertical structure, especially for absorbing aerosols. MPLNET provides exactly this sort of measurement, including calculation of aerosol extinction profiles, in a near real-time basis for all sites in the network. In order to obtain aerosol profiles, near range signal returns (0-6 km) must be accurately measured by the MPL. This measurement is complicated by the instrument s overlap range: Le., the minimum distance at which returning signals are completely in the instrument s field-of-view (FOV). Typical MPL overlap distances are large, between 5 - 6 km, due to the narrow FOV of the MPL receiver. A function describing the MPL overlap must be determined and used to correct signals in this range. Currently, overlap functions for MPLNET are determined using horizontal MPL measurements along a path with 10-1 5 km clear line-of-sight and a homogenous atmosphere. These conditions limit the location and ease in which successful overlaps can be obtained. Furthermore, the current MPLNET process of correcting for overlap increases the uncertainty and bias error for the near range signals and the resulting aerosol extinction profiles. To address these issues, an alternative overlap correction method using a small-diameter, wide FOV receiver is being considered for potential use in MPLNET. The wide FOV receiver has a much shorter overlap distance and will be used to calculate the overlap function of the MPL receiver. This approach has a significant benefit in that overlap corrections could be obtained

  12. An Overlapping Structured P2P for REIK Overlay Network

    NASA Astrophysics Data System (ADS)

    Liu, Wenjun; Song, Jingjing; Yu, Jiguo

    REIK is based on a ring which embedded an inverse Kautz digraph, to enable multi-path P2P routing. It has the constant degree and the logarithmic diameter DHT scheme with constant congestion and Byzantine fault tolerance. However, REIK did not consider the interconnection of many independent smaller networks. In this paper, we propose a new approach to build overlay network, OLS-REIK which is an overlapping structured P2P for REIK overlay network. It is a more flexible interconnecting different REIK network. Peers can belong to several rings, allowing this interconnection. By connecting smaller structured overlay networks in an unstructured way, it provides a cost effective alternative to hierarchical structured P2P systems requiring costly merging. Routing of lookup messages is performed as in REIK within one ring, but a peer belonging to several rings forwards the request to the different rings it belongs to. Furthermore a small number of across point is enough to ensure a high exhaustiveness level.

  13. Detecting overlapping protein complexes by rough-fuzzy clustering in protein-protein interaction networks.

    PubMed

    Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks.

  14. Detecting Overlapping Protein Complexes by Rough-Fuzzy Clustering in Protein-Protein Interaction Networks

    PubMed Central

    Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks. PMID:24642838

  15. The Overlapping Community Structure of Structural Brain Network in Young Healthy Individuals

    PubMed Central

    Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Sassa, Yuko; Inoue, Kentaro; Goto, Ryoi; Okada, Ken; Kawashima, Ryuta; He, Yong; Evans, Alan C.; Fukuda, Hiroshi

    2011-01-01

    Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities overlap and share many edges and nodes. Uncovering the overlapping community structure of complex networks remains largely unknown in human brain networks. Here, using regional gray matter volume, we investigated the structural brain network among 90 brain regions (according to a predefined anatomical atlas) in 462 young, healthy individuals. Overlapped nodes between communities were defined by assuming that nodes (brain regions) can belong to more than one community. We demonstrated that 90 brain regions were organized into 5 overlapping communities associated with several well-known brain systems, such as the auditory/language, visuospatial, emotion, decision-making, social, control of action, memory/learning, and visual systems. The overlapped nodes were mostly involved in an inferior-posterior pattern and were primarily related to auditory and visual perception. The overlapped nodes were mainly attributed to brain regions with higher node degrees and nodal efficiency and played a pivotal role in the flow of informa- tion through the structural brain network. Our results revealed fuzzy boundaries between communities by identifying overlapped nodes and provided new insights into the understanding of the relationship between the structure and function of the human brain. This study provides the first report of the overlapping community structure of the structural network of the human brain. PMID:21573111

  16. Dynamic-overlapped-grid simulation of aerodynamically determined relative motion

    NASA Technical Reports Server (NTRS)

    Yen, Guan-Wei; Baysal, Oktay

    1993-01-01

    Currently, there is a need to develop a means of analyzing and studying unsteady flowfields which involve multiple component configurations with at least one of the components in relative motion with respect to the others. Two of the important phenomena that such analyses can help to understand are the unsteady aerodynamic interference and the boundary-induced component of the flowfield. With this motivation, a computational method is developed which couples the governing equations of the unsteady flowfield and the rigid-body dynamics in six degrees-of-freedom. These equations are solved on composite meshes of overlapped subdomain grids which can move with respect to each other. Initially, several measures that reduce the numerical error are studied and compared with the exact solution of a moving normal shock in a tube. It is concluded that a second-order accurate method, for spatial and temporal discretizations as well as for the moving subdomain interpolations, is needed as a minimum measure. Furthermore, the CFL numbers should be restricted to unity. Then, the method is used to simulate the flowfield history and predict the aerodynamically determined trajectory of a store dropped from its initial position under a wing.

  17. Investigation of Overlap Correction Techniques for the Micro-Pulse Lidar NETwork (MPLNET)

    NASA Technical Reports Server (NTRS)

    Berkoff, T. A.; Welton, E. J.; Campbell, J. R.; Scott, V. S.; Spinhirne, J. D.

    2003-01-01

    The Micro-Pulse Lidar NETwork (MPLNET) uses elastic-scattering lidars stationed at sites around the globe to produce aerosol and cloud vertical profiles on a continuous year-round basis. Processing of MPLNET data requires a correction for the lidar overlap function in the 0-6 km range, to take into account the loss in near-field receiver efficiency. This correction is normally determined from recording horizontal profiles that require a approximately 10 km clear line-of-sight and homogenous atmospheric conditions, limiting the practicality in which successful corrections can be obtained. An alternative overlap correction method using a secondary receiver is considered that eliminates the need for horizontal measurements. A review of both methods is presented, including a discussion of signal uncertainties.

  18. Uncovering the overlapping community structure of complex networks by maximal cliques

    NASA Astrophysics Data System (ADS)

    Li, Junqiu; Wang, Xingyuan; Cui, Yaozu

    2014-12-01

    In this paper, a unique algorithm is proposed to detect overlapping communities in the un-weighted and weighted networks with considerable accuracy. The maximal cliques, overlapping vertex, bridge vertex and isolated vertex are introduced. First, all the maximal cliques are extracted by the algorithm based on the deep and bread searching. Then two maximal cliques can be merged into a larger sub-graph by some given rules. In addition, the proposed algorithm successfully finds overlapping vertices and bridge vertices between communities. Experimental results using some real-world networks data show that the performance of the proposed algorithm is satisfactory.

  19. Identifying overlapping and hierarchical thematic structures in networks of scholarly papers: a comparison of three approaches.

    PubMed

    Havemann, Frank; Gläser, Jochen; Heinz, Michael; Struck, Alexander

    2012-01-01

    The aim of this paper is to introduce and assess three algorithms for the identification of overlapping thematic structures in networks of papers. We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles, abstracts, and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three predefined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

  20. Correlations between weights and overlap in ensembles of weighted multiplex networks

    NASA Astrophysics Data System (ADS)

    Menichetti, Giulia; Remondini, Daniel; Bianconi, Ginestra

    2014-12-01

    Multiplex networks describe a large number of systems ranging from social networks to the brain. These multilayer structure encode information in their structure. This information can be extracted by measuring the correlations present in the multiplex networks structure, such as the overlap of the links in different layers. Many multiplex networks are also weighted, and the weights of the links can be strongly correlated with the structural properties of the multiplex network. For example, in multiplex network formed by the citation and collaboration networks between PRE scientists it was found that the statistical properties of citations to coauthors differ from the one of citations to noncoauthors, i.e., the weights depend on the overlap of the links. Here we present a theoretical framework for modeling multiplex weighted networks with different types of correlations between weights and overlap. To this end, we use the framework of canonical network ensembles, and the recently introduced concept of multilinks, showing that null models of a large variety of network structures can be constructed in this way. In order to provide a concrete example of how this framework apply to real data we consider a multiplex constructed from gene expression data of healthy and cancer tissues.

  1. Critical effects of overlapping of connectivity and dependence links on percolation of networks

    NASA Astrophysics Data System (ADS)

    Li, Ming; Liu, Run-Ran; Jia, Chun-Xiao; Wang, Bing-Hong

    2013-09-01

    In a recent work Parshani et al (2011 Proc. Natl Acad. Sci. USA 108 1007), dependence links have been introduced to the percolation model and used to study the robustness of the networks with such links, which shows that the networks are more vulnerable than the classical networks with only connectivity links. This model usually demonstrates a first order transition, rather than the second order transition found in classical network percolation. In this paper, considering the real situation that the interdependent nodes are usually connected, we study the cascading dynamics of networks when dependence links partially overlap with connectivity links. We find that the percolation transitions are not always sharpened by making nodes interdependent. For a high fraction of overlapping, the network is robust for random failures, and the percolation transition is second order, while for a low fraction of overlapping, the percolation process shows a first order transition. This work demonstrates that the crossover between two types of transitions does not only depend on the density of dependence links but also on the overlapping fraction of connectivity and dependence links. Using generating function techniques, we present exact solutions for the size of the giant component and the critical point, which are in good agreement with the simulations.

  2. Identifying Spatially Overlapping Local Cortical Networks with MEG

    PubMed Central

    Duncan, Keith Kawabata; Hadjipapas, Avgis; Li, Sheng; Kourtzi, Zoe; Bagshaw, Andy; Barnes, Gareth

    2010-01-01

    Recent modelling studies (Hadjipapas et al. [2009]: Neuroimage 44:1290-1303) have shown that it may be possible to distinguish between different neuronal populations on the basis of their macroscopically measured (EEG/MEG) mean field. We set out to test whether the different orientation columns contributing to a signal at a specific cortical location could be identified based on the measured MEG signal. We used 1.5deg square, static, obliquely oriented grating stimuli to generate sustained gamma oscillations in a focal region of primary visual cortex. We then used multivariate classifier methods to predict the orientation (left or right oblique) of the stimuli based purely on the time-series data from this one location. Both the single trial evoked response (0–300 ms) and induced post-transient power spectra (300–2,300 ms, 20–70 Hz band) due to the different stimuli were classifiable significantly above chance in 11/12 and 10/12 datasets respectively. Interestingly, stimulus-specific information is preserved in the sustained part of the gamma oscillation, long after perception has occurred and all neuronal transients have decayed. Importantly, the classification of this induced oscillation was still possible even when the power spectra were rank-transformed showing that the different underlying networks give rise to different characteristic temporal signatures. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. PMID:19998365

  3. Overlapping networks engaged during spoken language production and its cognitive control.

    PubMed

    Geranmayeh, Fatemeh; Wise, Richard J S; Mehta, Amrish; Leech, Robert

    2014-06-25

    Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and "rest," to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production.

  4. Neighbor overlap is enriched in the yeast interaction network: analysis and implications.

    PubMed

    Feiglin, Ariel; Moult, John; Lee, Byungkook; Ofran, Yanay; Unger, Ron

    2012-01-01

    The yeast protein-protein interaction network has been shown to have distinct topological features such as a scale free degree distribution and a high level of clustering. Here we analyze an additional feature which is called Neighbor Overlap. This feature reflects the number of shared neighbors between a pair of proteins. We show that Neighbor Overlap is enriched in the yeast protein-protein interaction network compared with control networks carefully designed to match the characteristics of the yeast network in terms of degree distribution and clustering coefficient. Our analysis also reveals that pairs of proteins with high Neighbor Overlap have higher sequence similarity, more similar GO annotations and stronger genetic interactions than pairs with low ones. Finally, we demonstrate that pairs of proteins with redundant functions tend to have high Neighbor Overlap. We suggest that a combination of three mechanisms is the basis for this feature: The abundance of protein complexes, selection for backup of function, and the need to allow functional variation.

  5. Neighbor Overlap Is Enriched in the Yeast Interaction Network: Analysis and Implications

    PubMed Central

    Feiglin, Ariel; Moult, John; Lee, Byungkook; Ofran, Yanay; Unger, Ron

    2012-01-01

    The yeast protein-protein interaction network has been shown to have distinct topological features such as a scale free degree distribution and a high level of clustering. Here we analyze an additional feature which is called Neighbor Overlap. This feature reflects the number of shared neighbors between a pair of proteins. We show that Neighbor Overlap is enriched in the yeast protein-protein interaction network compared with control networks carefully designed to match the characteristics of the yeast network in terms of degree distribution and clustering coefficient. Our analysis also reveals that pairs of proteins with high Neighbor Overlap have higher sequence similarity, more similar GO annotations and stronger genetic interactions than pairs with low ones. Finally, we demonstrate that pairs of proteins with redundant functions tend to have high Neighbor Overlap. We suggest that a combination of three mechanisms is the basis for this feature: The abundance of protein complexes, selection for backup of function, and the need to allow functional variation. PMID:22761860

  6. Determinants of public cooperation in multiplex networks

    NASA Astrophysics Data System (ADS)

    Battiston, Federico; Perc, Matjaž; Latora, Vito

    2017-07-01

    Synergies between evolutionary game theory and statistical physics have significantly improved our understanding of public cooperation in structured populations. Multiplex networks, in particular, provide the theoretical framework within network science that allows us to mathematically describe the rich structure of interactions characterizing human societies. While research has shown that multiplex networks may enhance the resilience of cooperation, the interplay between the overlap in the structure of the layers and the control parameters of the corresponding games has not yet been investigated. With this aim, we consider here the public goods game on a multiplex network, and we unveil the role of the number of layers and the overlap of links, as well as the impact of different synergy factors in different layers, on the onset of cooperation. We show that enhanced public cooperation emerges only when a significant edge overlap is combined with at least one layer being able to sustain some cooperation by means of a sufficiently high synergy factor. In the absence of either of these conditions, the evolution of cooperation in multiplex networks is determined by the bounds of traditional network reciprocity with no enhanced resilience. These results caution against overly optimistic predictions that the presence of multiple social domains may in itself promote cooperation, and they help us better understand the complexity behind prosocial behavior in layered social systems.

  7. Identifying Modular Flows on Multilayer Networks Reveals Highly Overlapping Organization in Interconnected Systems

    NASA Astrophysics Data System (ADS)

    De Domenico, Manlio; Lancichinetti, Andrea; Arenas, Alex; Rosvall, Martin

    2015-01-01

    To comprehend interconnected systems across the social and natural sciences, researchers have developed many powerful methods to identify functional modules. For example, with interaction data aggregated into a single network layer, flow-based methods have proven useful for identifying modular dynamics in weighted and directed networks that capture constraints on flow processes. However, many interconnected systems consist of agents or components that exhibit multiple layers of interactions, possibly from several different processes. Inevitably, representing this intricate network of networks as a single aggregated network leads to information loss and may obscure the actual organization. Here, we propose a method based on a compression of network flows that can identify modular flows both within and across layers in nonaggregated multilayer networks. Our numerical experiments on synthetic multilayer networks, with some layers originating from the same interaction process, show that the analysis fails in aggregated networks or when treating the layers separately, whereas the multilayer method can accurately identify modules across layers that originate from the same interaction process. We capitalize on our findings and reveal the community structure of two multilayer collaboration networks with topics as layers: scientists affiliated with the Pierre Auger Observatory and scientists publishing works on networks on the arXiv. Compared to conventional aggregated methods, the multilayer method uncovers connected topics and reveals smaller modules with more overlap that better capture the actual organization.

  8. Data on overlapping brain disorders and emerging drug targets in human Dopamine Receptors Interaction Network.

    PubMed

    Podder, Avijit; Latha, N

    2017-06-01

    Intercommunication of Dopamine Receptors (DRs) with their associate protein partners is crucial to maintain regular brain function in human. Majority of the brain disorders arise due to malfunctioning of such communication process. Hence, contributions of genetic factors, as well as phenotypic indications for various neurological and psychiatric disorders are often attributed as sharing in nature. In our earlier research article entitled "Human Dopamine Receptors Interaction Network (DRIN): a systems biology perspective on topology, stability and functionality of the network" (Podder et al., 2014) [1], we had depicted a holistic interaction map of human Dopamine Receptors. Given emphasis on the topological parameters, we had characterized the functionality along with the vulnerable properties of the network. In support of this, we hereby provide an additional data highlighting the genetic overlapping of various brain disorders in the network. The data indicates the sharing nature of disease genes for various neurological and psychiatric disorders in dopamine receptors connecting protein-protein interactions network. The data also indicates toward an alternative approach to prioritize proteins for overlapping brain disorders as valuable drug targets in the network.

  9. The Relationship between Health Plan Performance Measures and Physician Network Overlap: Implications for Measuring Plan Quality

    PubMed Central

    Maeng, Daniel D; Scanlon, Dennis P; Chernew, Michael E; Gronniger, Tim; Wodchis, Walter P; McLaughlin, Catherine G

    2010-01-01

    Objective To examine the extent to which health plan quality measures capture physician practice patterns rather than plan characteristics. Data Source We gathered and merged secondary data from the following four sources: a private firm that collected information on individual physicians and their health plan affiliations, The National Committee for Quality Assurance, InterStudy, and the Dartmouth Atlas. Study Design We constructed two measures of physician network overlap for all health plans in our sample and linked them to selected measures of plan performance. Two linear regression models were estimated to assess the relationship between the measures of physician network overlap and the plan performance measures. Principal Findings The results indicate that in the presence of a higher degree of provider network overlap, plan performance measures tend to converge to a lower level of quality. Conclusions Standard health plan performance measures reflect physician practice patterns rather than plans' effort to improve quality. This implies that more provider-oriented measurement, such as would be possible with accountable care organizations or medical homes, may facilitate patient decision making and provide further incentives to improve performance. PMID:20403064

  10. The relationship between health plan performance measures and physician network overlap: implications for measuring plan quality.

    PubMed

    Maeng, Daniel D; Scanlon, Dennis P; Chernew, Michael E; Gronniger, Tim; Wodchis, Walter P; McLaughlin, Catherine G

    2010-08-01

    To examine the extent to which health plan quality measures capture physician practice patterns rather than plan characteristics. We gathered and merged secondary data from the following four sources: a private firm that collected information on individual physicians and their health plan affiliations, The National Committee for Quality Assurance, InterStudy, and the Dartmouth Atlas. We constructed two measures of physician network overlap for all health plans in our sample and linked them to selected measures of plan performance. Two linear regression models were estimated to assess the relationship between the measures of physician network overlap and the plan performance measures. The results indicate that in the presence of a higher degree of provider network overlap, plan performance measures tend to converge to a lower level of quality. Standard health plan performance measures reflect physician practice patterns rather than plans' effort to improve quality. This implies that more provider-oriented measurement, such as would be possible with accountable care organizations or medical homes, may facilitate patient decision making and provide further incentives to improve performance.

  11. An improved transmutation method for quantitative determination of the components in multicomponent overlapping chromatograms.

    PubMed

    Shao, Xueguang; Yu, Zhengliang; Ma, Chaoxiong

    2004-06-01

    An improved method is proposed for the quantitative determination of multicomponent overlapping chromatograms based on a known transmutation method. To overcome the main limitation of the transmutation method caused by the oscillation generated in the transmutation process, two techniques--wavelet transform smoothing and the cubic spline interpolation for reducing data points--were adopted, and a new criterion was also developed. By using the proposed algorithm, the oscillation can be suppressed effectively, and quantitative determination of the components in both the simulated and experimental overlapping chromatograms is successfully obtained.

  12. [Resolution of overlapping chromatographic peaks by radial basis function neural network].

    PubMed

    Li, Y B; Huang, X Y; Sha, M; Meng, X S

    2001-03-01

    A new algorithm-resolution of overlapping chromatographic peaks by radial basis function neural network(RBFNN) is presented. A two-phase genetic algorithm(GA) which has robustness and random globe optimization is used to train RBFNN so that it has the ability on the resolution of overlapping chromatographic peaks. The two-phase genetic algorithm involves two procedures: training structure and optimizing parameter. The first procedure uses GA to train the architectures of RBFNN, the second procedure uses gradient descent to train the center(tR) and the width(sigma) of RBFNN. The alternate use of these two procedures makes the network having the ability to learn structure, therefore makes itself adaptable to resolution of the chromatographic peaks with unknown number of components. The method proposed here needs no artificial interference, not only has it robustness and globalism, but also the ability of accurate resolution to completely overlapped chromatographic peaks. The simulation experiments show that this method is more accurate than other methods.

  13. Community Structure Detection for Overlapping Modules through Mathematical Programming in Protein Interaction Networks

    PubMed Central

    Bennett, Laura; Kittas, Aristotelis; Liu, Songsong; Papageorgiou, Lazaros G.; Tsoka, Sophia

    2014-01-01

    Community structure detection has proven to be important in revealing the underlying properties of complex networks. The standard problem, where a partition of disjoint communities is sought, has been continually adapted to offer more realistic models of interactions in these systems. Here, a two-step procedure is outlined for exploring the concept of overlapping communities. First, a hard partition is detected by employing existing methodologies. We then propose a novel mixed integer non linear programming (MINLP) model, known as OverMod, which transforms disjoint communities to overlapping. The procedure is evaluated through its application to protein-protein interaction (PPI) networks of the rat, E. coli, yeast and human organisms. Connector nodes of hard partitions exhibit topological and functional properties indicative of their suitability as candidates for multiple module membership. OverMod identifies two types of connector nodes, inter and intra-connector, each with their own particular characteristics pertaining to their topological and functional role in the organisation of the network. Inter-connector proteins are shown to be highly conserved proteins participating in pathways that control essential cellular processes, such as proliferation, differentiation and apoptosis and their differences with intra-connectors is highlighted. Many of these proteins are shown to possess multiple roles of distinct nature through their participation in different network modules, setting them apart from proteins that are simply ‘hubs’, i.e. proteins with many interaction partners but with a more specific biochemical role. PMID:25412367

  14. Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks.

    PubMed

    Tang, Xiaolan; Xie, Hua; Chen, Wenlong; Niu, Jianwei; Wang, Shuhang

    2017-06-29

    Wireless sensor networks are required in smart applications to provide accurate control, where the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However, most of aggregation schemes reduce information accuracy and prolong end-to-end delay when eliminating transmission overhead. In this paper, we propose a data aggregation scheme based on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in wireless sensor networks with high information accuracy. According to aggregation rules, gathering nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps the original entropy by only deleting the duplicated data. Experiment results show that compared with others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.

  15. Community structure detection for overlapping modules through mathematical programming in protein interaction networks.

    PubMed

    Bennett, Laura; Kittas, Aristotelis; Liu, Songsong; Papageorgiou, Lazaros G; Tsoka, Sophia

    2014-01-01

    Community structure detection has proven to be important in revealing the underlying properties of complex networks. The standard problem, where a partition of disjoint communities is sought, has been continually adapted to offer more realistic models of interactions in these systems. Here, a two-step procedure is outlined for exploring the concept of overlapping communities. First, a hard partition is detected by employing existing methodologies. We then propose a novel mixed integer non linear programming (MINLP) model, known as OverMod, which transforms disjoint communities to overlapping. The procedure is evaluated through its application to protein-protein interaction (PPI) networks of the rat, E. coli, yeast and human organisms. Connector nodes of hard partitions exhibit topological and functional properties indicative of their suitability as candidates for multiple module membership. OverMod identifies two types of connector nodes, inter and intra-connector, each with their own particular characteristics pertaining to their topological and functional role in the organisation of the network. Inter-connector proteins are shown to be highly conserved proteins participating in pathways that control essential cellular processes, such as proliferation, differentiation and apoptosis and their differences with intra-connectors is highlighted. Many of these proteins are shown to possess multiple roles of distinct nature through their participation in different network modules, setting them apart from proteins that are simply 'hubs', i.e. proteins with many interaction partners but with a more specific biochemical role.

  16. Consensus of Multiagent Systems Subject to Partially Accessible and Overlapping Markovian Network Topologies.

    PubMed

    Ge, Xiaohua; Han, Qing-Long

    2016-06-07

    This paper addresses the consensus problem for a continuous-time multiagent system (MAS) with Markovian network topologies and external disturbance. Different from some existing results, global jumping modes of the Markovian network topologies are not required to be completely available for consensus protocol design. A network topology mode regulator (NTMR) is first developed to decompose unavailable global modes into several overlapping groups, where overlapping groups refer to the scenario that there exist commonly shared local modes between any two distinct groups. The NTMR schedules which group modes each agent may access at every time step. Then a new group mode-dependent distributed consensus protocol on the basis of relative measurement outputs of neighboring agents is delicately constructed. In this sense, the proposed consensus protocol relies only on group and partial modes and eliminates the need for complete knowledge of global modes. Sufficient conditions on the existence of desired distributed consensus protocols are derived to ensure consensus of the MAS with a prescribed H∞ performance level. Two examples are provided to show the effectiveness of the proposed consensus protocol.

  17. GENERAL: Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

    NASA Astrophysics Data System (ADS)

    Yang, Xu-Hua; Sun, Bao; Wang, Bo; Sun, You-Xian

    2010-04-01

    Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper.

  18. Oscillatory neural networks with self-organized segmentation of overlapping patterns.

    PubMed

    Burwick, Thomas

    2007-08-01

    Temporal coding is considered with an oscillatory network model that generalizes the Cohen-Grossberg-Hopfield model. It is assumed that the frequency of oscillating units increases with stronger and more coherent input. We refer to this mechanism as acceleration. In the context of Hebbian memory, synchronization and acceleration take complementary roles, and their combined effect on the storage of patterns is profound. Acceleration implies the desynchronization that is needed for self-organized segmention of two overlapping patterns. The superposition problem is thereby solved even without including competition couplings. With respect to brain dynamics, we point to analogies with oscillation spindles in the gamma range and responses to perceptual rivalries.

  19. Word and face processing engage overlapping distributed networks: Evidence from RSVP and EEG investigations.

    PubMed

    Robinson, Amanda K; Plaut, David C; Behrmann, Marlene

    2017-07-01

    Words and faces have vastly different visual properties, but increasing evidence suggests that word and face processing engage overlapping distributed networks. For instance, fMRI studies have shown overlapping activity for face and word processing in the fusiform gyrus despite well-characterized lateralization of these objects to the left and right hemispheres, respectively. To investigate whether face and word perception influences perception of the other stimulus class and elucidate the mechanisms underlying such interactions, we presented images using rapid serial visual presentations. Across 3 experiments, participants discriminated 2 face, word, and glasses targets (T1 and T2) embedded in a stream of images. As expected, T2 discrimination was impaired when it followed T1 by 200 to 300 ms relative to longer intertarget lags, the so-called attentional blink. Interestingly, T2 discrimination accuracy was significantly reduced at short intertarget lags when a face was followed by a word (face-word) compared with glasses-word and word-word combinations, indicating that face processing interfered with word perception. The reverse effect was not observed; that is, word-face performance was no different than the other object combinations. EEG results indicated the left N170 to T1 was correlated with the word decrement for face-word trials, but not for other object combinations. Taken together, the results suggest face processing interferes with word processing, providing evidence for overlapping neural mechanisms of these 2 object types. Furthermore, asymmetrical face-word interference points to greater overlap of face and word representations in the left than the right hemisphere. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Detecting hierarchical and overlapping network communities using locally optimal modularity changes

    NASA Astrophysics Data System (ADS)

    Barber, Michael J.

    2013-09-01

    Agglomerative clustering is a well established strategy for identifying communities in networks. Communities are successively merged into larger communities, coarsening a network of actors into a more manageable network of communities. The order in which merges should occur is not in general clear, necessitating heuristics for selecting pairs of communities to merge. We describe a hierarchical clustering algorithm based on a local optimality property. For each edge in the network, we associate the modularity change for merging the communities it links. For each community vertex, we call the preferred edge that edge for which the modularity change is maximal. When an edge is preferred by both vertices that it links, it appears to be the optimal choice from the local viewpoint. We use the locally optimal edges to define the algorithm: simultaneously merge all pairs of communities that are connected by locally optimal edges that would increase the modularity, redetermining the locally optimal edges after each step and continuing so long as the modularity can be further increased. We apply the algorithm to model and empirical networks, demonstrating that it can efficiently produce high-quality community solutions. We relate the performance and implementation details to the structure of the resulting community hierarchies. We additionally consider a complementary local clustering algorithm, describing how to identify overlapping communities based on the local optimality condition.

  1. The (un)supervised NMF methods for discovering overlapping communities as well as hubs and outliers in networks

    NASA Astrophysics Data System (ADS)

    Wang, Xiao; Cao, Xiaochun; Jin, Di; Cao, Yixin; He, Dongxiao

    2016-03-01

    For its crucial importance in the study of large-scale networks, many researchers devote to the detection of communities in various networks. It is now widely agreed that the communities usually overlap with each other. In some communities, there exist members that play a special role as hubs (also known as leaders), whose importance merits special attention. Moreover, it is also observed that some members of the network do not belong to any communities in a convincing way, and hence recognized as outliers. Failure to detect and exclude outliers will distort, sometimes significantly, the outcome of the detected communities. In short, it is preferable for a community detection method to detect all three structures altogether. This becomes even more interesting and also more challenging when we take the unsupervised assumption, that is, we do not assume the prior knowledge of the number K of communities. Our approach here is to define a novel generative model and formalize the detection of overlapping communities as well as hubs and outliers as an optimization problem on it. When K is given, we propose a normalized symmetric nonnegative matrix factorization algorithm based on Kullback-Leibler (KL) divergence to learn the parameters of the model. Otherwise, by combining KL divergence and prior model on parameters, we introduce another parameter learning method based on Bayesian symmetric nonnegative matrix factorization to learn the parameters of the model, while determining K. Therefore, we present a community detection method arguably in the most general sense, which detects all three structures altogether without prior knowledge of the number of communities. Finally, we test the proposed method on various real-world networks. The experimental results, in contrast to several state-of-art algorithms, indicate its superior performance over other ones in terms of both clustering accuracy and community quality.

  2. Determination of the deposition order of overlapping latent fingerprints and inks using secondary ion mass spectrometry.

    PubMed

    Bright, Nicholas J; Webb, Roger P; Bleay, Stephen; Hinder, Steven; Ward, Neil I; Watts, John F; Kirkby, Karen J; Bailey, Melanie J

    2012-05-01

    A new protocol using time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been developed to identify the deposition order of a fingerprint overlapping an ink line on paper. By taking line scans of fragment ions characteristic of the ink molecules (m/z 358.2 and 372.2) where the fingerprint and ink overlap and by calculating the normalized standard deviation of the intensity variation across the line scan, it is possible to determine whether or not a fingerprint is above ink on a paper substrate. The protocol adopted works for a selection of fingerprints from four donors tested here and for a fingerprint that was aged for six months; for one donor, the very faint fingerprints could not be visualized using either standard procedures (ninhydrin development) or SIMS, and therefore the protocol correctly gives an inconclusive result.

  3. A Complex Network of Factors with Overlapping Affinities Repress Splicing through Intronic Elements

    PubMed Central

    Wang, Yang; Xiao, Xinshu; Zhang, Jianming; Choudhury, Rajarshi; Robertson, Alex; Li, Kai; Ma, Meng; Burge, Christopher B.; Wang, Zefeng

    2012-01-01

    To better understand splicing regulation, we used a cell-based screen to identify ten diverse motifs that inhibit splicing from intron. Each motif was validated in another human cell type and gene context, and their presence correlated with in vivo splicing changes. All motifs exhibited exonic splicing enhancer or silencer activity, and grouping these motifs based on their distributions yielded clusters with distinct patterns of context-dependent activity. Candidate regulatory factors associated with each motif were identified, recovering 24 known and novel splicing regulators. Specific domains in selected factors were sufficient to confer ISS activity. Many factors bound multiple distinct motifs with similar affinity, and all motifs were recognized by multiple factors, revealing a complex, overlapping network of protein:RNA interactions. This arrangement enables individual cis-element to function differently in distinct cellular contexts depending on the spectrum of regulatory factors present. PMID:23241926

  4. Dynamic functional network connectivity reveals unique and overlapping profiles of insula subdivisions.

    PubMed

    Nomi, Jason S; Farrant, Kristafor; Damaraju, Eswar; Rachakonda, Srinivas; Calhoun, Vince D; Uddin, Lucina Q

    2016-05-01

    The human insular cortex consists of functionally diverse subdivisions that engage during tasks ranging from interoception to cognitive control. The multiplicity of functions subserved by insular subdivisions calls for a nuanced investigation of their functional connectivity profiles. Four insula subdivisions (dorsal anterior, dAI; ventral, VI; posterior, PI; middle, MI) derived using a data-driven approach were subjected to static- and dynamic functional network connectivity (s-FNC and d-FNC) analyses. Static-FNC analyses replicated previous work demonstrating a cognition-emotion-interoception division of the insula, where the dAI is functionally connected to frontal areas, the VI to limbic areas, and the PI and MI to sensorimotor areas. Dynamic-FNC analyses consisted of k-means clustering of sliding windows to identify variable insula connectivity states. The d-FNC analysis revealed that the most frequently occurring dynamic state mirrored the cognition-emotion-interoception division observed from the s-FNC analysis, with less frequently occurring states showing overlapping and unique subdivision connectivity profiles. In two of the states, all subdivisions exhibited largely overlapping profiles, consisting of subcortical, sensory, motor, and frontal connections. Two other states showed the dAI exhibited a unique connectivity profile compared with other insula subdivisions. Additionally, the dAI exhibited the most variable functional connections across the s-FNC and d-FNC analyses, and was the only subdivision to exhibit dynamic functional connections with regions of the default mode network. These results highlight how a d-FNC approach can capture functional dynamics masked by s-FNC approaches, and reveal dynamic functional connections enabling the functional flexibility of the insula across time. Hum Brain Mapp 37:1770-1787, 2016. © 2016 Wiley Periodicals, Inc.

  5. Extrinsic calibration of a non-overlapping camera network based on close-range photogrammetry.

    PubMed

    Dong, Shuai; Shao, Xinxing; Kang, Xin; Yang, Fujun; He, Xiaoyuan

    2016-08-10

    In this paper, an extrinsic calibration method for a non-overlapping camera network is presented based on close-range photogrammetry. The method does not require calibration targets or the cameras to be moved. The visual sensors are relatively motionless and do not see the same area at the same time. The proposed method combines the multiple cameras using some arbitrarily distributed encoded targets. The calibration procedure consists of three steps: reconstructing the three-dimensional (3D) coordinates of the encoded targets using a hand-held digital camera, performing the intrinsic calibration of the camera network, and calibrating the extrinsic parameters of each camera with only one image. A series of experiments, including 3D reconstruction, rotation, and translation, are employed to validate the proposed approach. The results show that the relative error for the 3D reconstruction is smaller than 0.003%, the relative errors of both rotation and translation are less than 0.066%, and the re-projection error is only 0.09 pixels.

  6. Quaking and PTB control overlapping splicing regulatory networks during muscle cell differentiation.

    PubMed

    Hall, Megan P; Nagel, Roland J; Fagg, W Samuel; Shiue, Lily; Cline, Melissa S; Perriman, Rhonda J; Donohue, John Paul; Ares, Manuel

    2013-05-01

    Alternative splicing contributes to muscle development, but a complete set of muscle-splicing factors and their combinatorial interactions are unknown. Previous work identified ACUAA ("STAR" motif) as an enriched intron sequence near muscle-specific alternative exons such as Capzb exon 9. Mass spectrometry of myoblast proteins selected by the Capzb exon 9 intron via RNA affinity chromatography identifies Quaking (QK), a protein known to regulate mRNA function through ACUAA motifs in 3' UTRs. We find that QK promotes inclusion of Capzb exon 9 in opposition to repression by polypyrimidine tract-binding protein (PTB). QK depletion alters inclusion of 406 cassette exons whose adjacent intron sequences are also enriched in ACUAA motifs. During differentiation of myoblasts to myotubes, QK levels increase two- to threefold, suggesting a mechanism for QK-responsive exon regulation. Combined analysis of the PTB- and QK-splicing regulatory networks during myogenesis suggests that 39% of regulated exons are under the control of one or both of these splicing factors. This work provides the first evidence that QK is a global regulator of splicing during muscle development in vertebrates and shows how overlapping splicing regulatory networks contribute to gene expression programs during differentiation.

  7. Sex differences in the structure and stability of children's playground social networks and their overlap with friendship relations.

    PubMed

    Baines, Ed; Blatchford, Peter

    2009-09-01

    Gender segregated peer networks during middle childhood have been highlighted as important for explaining later sex differences in behaviour, yet few studies have examined the structural composition of these networks and their implications. This short-term longitudinal study of 119 children (7-8 years) examined the size and internal structure of boys' and girls' social networks, their overlap with friendship relations, and their stability over time. Data collection at the start and end of the year involved systematic playground observations of pupils' play networks during team and non-team activities and measures of friendship from peer nomination interviews. Social networks were identified by aggregating play network data at each time point. Findings showed that the size of boy's play networks on the playground, but not their social networks, varied according to activity type. Social network cores consisted mainly of friends. Girl's social networks were more likely to be composed of friends and boys' networks contained friends and non-friends. Girls had more friends outside of the social network than boys. Stability of social network membership and internal network relations were higher for boys than girls. These patterns have implications for the nature of social experiences within these network contexts.

  8. Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks

    PubMed Central

    Karahanoğlu, Fikret Işik; Van De Ville, Dimitri

    2015-01-01

    Dynamics of resting-state functional magnetic resonance imaging (fMRI) provide a new window onto the organizational principles of brain function. Using state-of-the-art signal processing techniques, we extract innovation-driven co-activation patterns (iCAPs) from resting-state fMRI. The iCAPs' maps are spatially overlapping and their sustained-activity signals temporally overlapping. Decomposing resting-state fMRI using iCAPs reveals the rich spatiotemporal structure of functional components that dynamically assemble known resting-state networks. The temporal overlap between iCAPs is substantial; typically, three to four iCAPs occur simultaneously in combinations that are consistent with their behaviour profiles. In contrast to conventional connectivity analysis, which suggests a negative correlation between fluctuations in the default-mode network (DMN) and task-positive networks, we instead find evidence for two DMN-related iCAPs consisting the posterior cingulate cortex that differentially interact with the attention network. These findings demonstrate how the fMRI resting state can be functionally decomposed into spatially and temporally overlapping building blocks using iCAPs. PMID:26178017

  9. Overlapping ontologies and Indigenous knowledge. From integration to ontological self-determination.

    PubMed

    Ludwig, David

    2016-10-01

    Current controversies about knowledge integration reflect conflicting ideas of what it means to "take Indigenous knowledge seriously". While there is increased interest in integrating Indigenous and Western scientific knowledge in various disciplines such as anthropology and ethnobiology, integration projects are often accused of recognizing Indigenous knowledge only insofar as it is useful for Western scientists. The aim of this article is to use tools from philosophy of science to develop a model of both successful integration and integration failures. On the one hand, I argue that cross-cultural recognition of property clusters leads to an ontological overlap that makes knowledge integration often epistemically productive and socially useful. On the other hand, I argue that knowledge integration is limited by ontological divergence. Adequate models of Indigenous knowledge will therefore have to take integration failures seriously and I argue that integration efforts need to be complemented by a political notion of ontological self-determination.

  10. Efficient, sparse biological network determination

    PubMed Central

    August, Elias; Papachristodoulou, Antonis

    2009-01-01

    Background Determining the interaction topology of biological systems is a topic that currently attracts significant research interest. Typical models for such systems take the form of differential equations that involve polynomial and rational functions. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data much harder. The use of linear dynamics and linearization techniques that have been proposed in the past can circumvent this, but the general problem of developing efficient algorithms for models that provide more accurate system descriptions remains open. Results We present a network determination algorithm that can treat model descriptions with polynomial and rational functions and which does not make use of linearization. For this purpose, we make use of the observation that biochemical networks are in general 'sparse' and minimize the 1-norm of the decision variables (sum of weighted network connections) while constraints keep the error between data and the network dynamics small. The emphasis of our methodology is on determining the interconnection topology rather than the specific reaction constants and it takes into account the necessary properties that a chemical reaction network should have – something that techniques based on linearization can not. The problem can be formulated as a Linear Program, a convex optimization problem, for which efficient algorithms are available that can treat large data sets efficiently and uncertainties in data or model parameters. Conclusion The presented methodology is able to predict with accuracy and efficiency the connectivity structure of a chemical reaction network with mass action kinetics and of a gene regulatory network from simulation data even if the dynamics of these systems are non-polynomial (rational) and uncertainties in the data are taken into account. It also produces a network structure that can explain the real experimental

  11. Locating overlapping dense subgraphs in gene (protein) association networks and predicting novel protein functional groups among these subgraphs

    NASA Astrophysics Data System (ADS)

    Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas

    2006-03-01

    Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.

  12. Selective spectrophotometric methods for determination of ternary mixture with overlapping spectra: a comparative study.

    PubMed

    Abdelrahman, Maha M

    2014-04-24

    Comparable double divisor ratio spectra derivative, area under curve of derivative ratio and mean centering of ratio spectra spectrophotometric methods were introduced for determination of orphenadrine citrate (ORPH), caffeine (CAF) and aspirin (ASP); a combination for symptomatic relief of mild to moderate pain of acute musculoskeletal disorders; with evident accuracy and precision. The suggested methods have the advantage over the previously published spectrophotometric method for determination of the same combination in that they did not require a preliminary separation step and able to resolve the ternary mixture, with severe overlapping spectra, with competent sensitivity and selectivity. The recommended methods allow the determination of ORPH, CAF and ASP in the range of 2-32, 2-28 and 3-28 μg mL(-1), respectively. The validity of the proposed methods was examined by analysis of different laboratory prepared mixtures of ORPH, CAF and ASP and assay of their tablet formulation where reliable results were obtained. Statistical analysis between the suggested spectrophotometric methods and the reported HPLC method using student's-t and F-ratio tests reveals that the suggested methods are as accurate and precise as the reported one.

  13. Resolution of overlapped spectra for the determination of ternary mixture using different and modified spectrophotometric methods

    NASA Astrophysics Data System (ADS)

    Moussa, Bahia Abbas; El-Zaher, Asmaa Ahmed; Mahrouse, Marianne Alphonse; Ahmed, Maha Said

    2016-08-01

    Four new spectrophotometric methods were developed, applied to resolve the overlapped spectra of a ternary mixture of [aliskiren hemifumarate (ALS)-amlodipine besylate (AM)-hydrochlorothiazide (HCT)] and to determine the three drugs in pure form and in combined dosage form. Method A depends on simultaneous determination of ALS, AM and HCT using principal component regression and partial least squares chemometric methods. In Method B, a modified isosbestic spectrophotometric method was applied for the determination of the total concentration of ALS and HCT by measuring the absorbance at 274.5 nm (isosbestic point, Aiso). On the other hand, the concentration of HCT in ternary mixture with ALS and AM could be calculated without interference using first derivative spectrophotometric method by measuring the amplitude at 279 nm (zero crossing of ALS and zero value of AM). Thus, the content of ALS was calculated by subtraction. Method C, double divisor first derivative ratio spectrophotometry (double divisor 1DD method), was based on that for the determination of one drug, the ratio spectra were obtained by dividing the absorption spectra of its different concentrations by the sum of the absorption spectra of the other two drugs as a double divisor. The first derivative of the obtained ratio spectra were then recorded using the appropriate smoothing factor. The amplitudes at 291 nm, 380 nm and 274.5 nm were selected for the determination of ALS, AM and HCT in their ternary mixture, respectively. Method D was based on mean centering of ratio spectra. The mean centered values at 287, 295.5 and 269 nm were recorded and used for the determination of ALS, AM and HCT, respectively. The developed methods were validated according to ICH guidelines and proved to be accurate, precise and selective. Satisfactory results were obtained by applying the proposed methods to the analysis of pharmaceutical dosage form.

  14. Resolution of overlapped spectra for the determination of ternary mixture using different and modified spectrophotometric methods.

    PubMed

    Moussa, Bahia Abbas; El-Zaher, Asmaa Ahmed; Mahrouse, Marianne Alphonse; Ahmed, Maha Said

    2016-08-05

    Four new spectrophotometric methods were developed, applied to resolve the overlapped spectra of a ternary mixture of [aliskiren hemifumarate (ALS)-amlodipine besylate (AM)-hydrochlorothiazide (HCT)] and to determine the three drugs in pure form and in combined dosage form. Method A depends on simultaneous determination of ALS, AM and HCT using principal component regression and partial least squares chemometric methods. In Method B, a modified isosbestic spectrophotometric method was applied for the determination of the total concentration of ALS and HCT by measuring the absorbance at 274.5nm (isosbestic point, Aiso). On the other hand, the concentration of HCT in ternary mixture with ALS and AM could be calculated without interference using first derivative spectrophotometric method by measuring the amplitude at 279nm (zero crossing of ALS and zero value of AM). Thus, the content of ALS was calculated by subtraction. Method C, double divisor first derivative ratio spectrophotometry (double divisor (1)DD method), was based on that for the determination of one drug, the ratio spectra were obtained by dividing the absorption spectra of its different concentrations by the sum of the absorption spectra of the other two drugs as a double divisor. The first derivative of the obtained ratio spectra were then recorded using the appropriate smoothing factor. The amplitudes at 291nm, 380nm and 274.5nm were selected for the determination of ALS, AM and HCT in their ternary mixture, respectively. Method D was based on mean centering of ratio spectra. The mean centered values at 287, 295.5 and 269nm were recorded and used for the determination of ALS, AM and HCT, respectively. The developed methods were validated according to ICH guidelines and proved to be accurate, precise and selective. Satisfactory results were obtained by applying the proposed methods to the analysis of pharmaceutical dosage form.

  15. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    NASA Astrophysics Data System (ADS)

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  16. Novel two wavelength spectrophotometric methods for simultaneous determination of binary mixtures with severely overlapping spectra

    NASA Astrophysics Data System (ADS)

    Lotfy, Hayam M.; Saleh, Sarah S.; Hassan, Nagiba Y.; Salem, Hesham

    2015-02-01

    This work presents the application of different spectrophotometric techniques based on two wavelengths for the determination of severely overlapped spectral components in a binary mixture without prior separation. Four novel spectrophotometric methods were developed namely: induced dual wavelength method (IDW), dual wavelength resolution technique (DWRT), advanced amplitude modulation method (AAM) and induced amplitude modulation method (IAM). The results of the novel methods were compared to that of three well-established methods which were: dual wavelength method (DW), Vierordt's method (VD) and bivariate method (BV). The developed methods were applied for the analysis of the binary mixture of hydrocortisone acetate (HCA) and fusidic acid (FSA) formulated as topical cream accompanied by the determination of methyl paraben and propyl paraben present as preservatives. The specificity of the novel methods was investigated by analyzing laboratory prepared mixtures and the combined dosage form. The methods were validated as per ICH guidelines where accuracy, repeatability, inter-day precision and robustness were found to be within the acceptable limits. The results obtained from the proposed methods were statistically compared with official ones where no significant difference was observed. No difference was observed between the obtained results when compared to the reported HPLC method, which proved that the developed methods could be alternative to HPLC techniques in quality control laboratories.

  17. Novel two wavelength spectrophotometric methods for simultaneous determination of binary mixtures with severely overlapping spectra.

    PubMed

    Lotfy, Hayam M; Saleh, Sarah S; Hassan, Nagiba Y; Salem, Hesham

    2015-02-05

    This work presents the application of different spectrophotometric techniques based on two wavelengths for the determination of severely overlapped spectral components in a binary mixture without prior separation. Four novel spectrophotometric methods were developed namely: induced dual wavelength method (IDW), dual wavelength resolution technique (DWRT), advanced amplitude modulation method (AAM) and induced amplitude modulation method (IAM). The results of the novel methods were compared to that of three well-established methods which were: dual wavelength method (DW), Vierordt's method (VD) and bivariate method (BV). The developed methods were applied for the analysis of the binary mixture of hydrocortisone acetate (HCA) and fusidic acid (FSA) formulated as topical cream accompanied by the determination of methyl paraben and propyl paraben present as preservatives. The specificity of the novel methods was investigated by analyzing laboratory prepared mixtures and the combined dosage form. The methods were validated as per ICH guidelines where accuracy, repeatability, inter-day precision and robustness were found to be within the acceptable limits. The results obtained from the proposed methods were statistically compared with official ones where no significant difference was observed. No difference was observed between the obtained results when compared to the reported HPLC method, which proved that the developed methods could be alternative to HPLC techniques in quality control laboratories.

  18. Overlap in Bibliographic Databases.

    ERIC Educational Resources Information Center

    Hood, William W.; Wilson, Concepcion S.

    2003-01-01

    Examines the topic of Fuzzy Set Theory to determine the overlap of coverage in bibliographic databases. Highlights include examples of comparisons of database coverage; frequency distribution of the degree of overlap; records with maximum overlap; records unique to one database; intra-database duplicates; and overlap in the top ten databases.…

  19. Social network determinants of depression

    PubMed Central

    Rosenquist, JN; Fowler, JH; Christakis, NA

    2013-01-01

    The etiology of depression has long been thought to include social environmental factors. To quantitatively explore the novel possibility of person-to-person spread and network-level determination of depressive symptoms, analyses were performed on a densely interconnected social network of 12 067 people assessed repeatedly over 32 years as part of the Framingham Heart Study. Longitudinal statistical models were used to examine whether depressive symptoms in one person were associated with similar scores in friends, co-workers, siblings, spouses and neighbors. Depressive symptoms were assessed using CES-D scores that were available for subjects in three waves measured between 1983 and 2001. Results showed both low and high CES-D scores (and classification as being depressed) in a given period were strongly correlated with such scores in one's friends and neighbors. This association extended up to three degrees of separation (to one's friends’ friends’ friends). Female friends appear to be especially influential in the spread of depression from one person to another. The results are robust to multiple network simulation and estimation methods, suggesting that network phenomena appear relevant to the epidemiology of depression and would benefit from further study. PMID:20231839

  20. Sequence Determination from Overlapping Fragments: A Simple Model of Whole-Genome Shotgun Sequencing

    NASA Astrophysics Data System (ADS)

    Derrida, Bernard; Fink, Thomas M.

    2002-02-01

    Assembling fragments randomly sampled from along a sequence is the basis of whole-genome shotgun sequencing, a technique used to map the DNA of the human and other genomes. We calculate the probability that a random sequence can be recovered from a collection of overlapping fragments. We provide an exact solution for an infinite alphabet and in the case of constant overlaps. For the general problem we apply two assembly strategies and give the probability that the assembly puzzle can be solved in the limit of infinitely many fragments.

  1. Sequence determination from overlapping fragments: a simple model of whole-genome shotgun sequencing.

    PubMed

    Derrida, Bernard; Fink, Thomas M A

    2002-02-11

    Assembling fragments randomly sampled from along a sequence is the basis of whole-genome shotgun sequencing, a technique used to map the DNA of the human and other genomes. We calculate the probability that a random sequence can be recovered from a collection of overlapping fragments. We provide an exact solution for an infinite alphabet and in the case of constant overlaps. For the general problem we apply two assembly strategies and give the probability that the assembly puzzle can be solved in the limit of infinitely many fragments.

  2. Configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks

    DOEpatents

    Archer, Charles J.; Inglett, Todd A.; Ratterman, Joseph D.; Smith, Brian E.

    2010-03-02

    Methods, apparatus, and products are disclosed for configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks, the compute nodes in the operational group connected together for data communications through a global combining network, that include: partitioning the compute nodes in the operational group into a plurality of non-overlapping subgroups; designating one compute node from each of the non-overlapping subgroups as a master node; and assigning, to the compute nodes in each of the non-overlapping subgroups, class routing instructions that organize the compute nodes in that non-overlapping subgroup as a collective network such that the master node is a physical root.

  3. Overlapping functions of ABC transporters in topotecan disposition as determined in gene knockout mouse models

    PubMed Central

    Tiwari, Amit K.; Zhang, Rong; Gallo, James M.

    2013-01-01

    It is established that efflux transporters of the ABC superfamily can affect the pharmacokinetics (PKs) of drugs through mechanisms pertaining to drug absorption, elimination and distribution. To characterize the role of multiple transporters in topotecan's PKs, total (lactone+carboxylate) and lactone forms were measured by LC/MS/MS in plasma, bile, urine and feces following IV administration at doses of 1 mg/kg and 4 mg/kg to eight mouse strains; C57BL/6 (WT), Abcb1−/−, Abcc2−/−, Abcc4−/−, Abcg2−/−, Abcc2;Abcb1−/−, Abcc2;Abcg2−/−, Abcc4;Abcg2−/−. Compared with WT mice and at both dose levels, the plasma areas under the curve (AUC) for topotecan lactone were not significantly different in the Abcc2−/−, Abcc4−/−, Abcb1−/− strains, whereas significant differences were found in Abcg2−/−, Abcc2;Abcb1−/− (only at the high dose), Abcc4;Abcg2−/− and Abcc2;Abcg2−/− mice and ranged from 2.1-fold to 3.3-fold higher. Consistent with these changes, the fecal and biliary excretion of topotecan was reduced, while renal elimination was elevated in Abcg2−/− based strains. Similarly, the Abcc2;Abcb1−/− strain also had elevated renal elimination and reduced fecal excretion of topotecan lactone, this was more pronounced at the 4 mg/kg dose level, suggesting possible saturation of Abcg2. The Abcc4 transporter was found not to be a major determinant of topotecan PKs. It is concluded that Abcg2 has the most significant effect on topotecan elimination, whereas both Abcb1 and Abcc2 have overlapping functions with Abcg2. As such it is relevant to examine how polymorphisms in these transporters influence topotecan activity in patients and whether coadministration of transport modulators could positively affect efficacy without increasing toxicity. PMID:23635651

  4. Friending, IMing, and hanging out face-to-face: overlap in adolescents' online and offline social networks.

    PubMed

    Reich, Stephanie M; Subrahmanyam, Kaveri; Espinoza, Guadalupe

    2012-03-01

    Many new and important developmental issues are encountered during adolescence, which is also a time when Internet use becomes increasingly popular. Studies have shown that adolescents are using these online spaces to address developmental issues, especially needs for intimacy and connection to others. Online communication with its potential for interacting with unknown others, may put teens at increased risk. Two hundred and fifty-one high school students completed an in-person survey, and 126 of these completed an additional online questionnaire about how and why they use the Internet, their activities on social networking sites (e.g., Facebook, MySpace) and their reasons for participation, and how they perceive these online spaces to impact their friendships. To examine the extent of overlap between online and offline friends, participants were asked to list the names of their top interaction partners offline and online (Facebook and instant messaging). Results reveal that adolescents mainly use social networking sites to connect with others, in particular with people known from offline contexts. While adolescents report little monitoring by their parents, there was no evidence that teens are putting themselves at risk by interacting with unknown others. Instead, adolescents seem to use the Internet, especially social networking sites, to connect with known others. While the study found moderate overlap between teens' closest online and offline friends, the patterns suggest that adolescents use online contexts to strengthen offline relationships.

  5. Genome-Wide Analysis of PDZ Domain Binding Reveals Inherent Functional Overlap within the PDZ Interaction Network

    PubMed Central

    te Velthuis, Aartjan J. W.; Sakalis, Philippe A.; Fowler, Donald A.; Bagowski, Christoph P.

    2011-01-01

    Binding selectivity and cross-reactivity within one of the largest and most abundant interaction domain families, the PDZ family, has long been enigmatic. The complete human PDZ domain complement (the PDZome) consists of 267 domains and we applied here a Bayesian selectivity model to predict hundreds of human PDZ domain interactions, using target sequences of 22,997 non-redundant proteins. Subsequent analysis of these binding scores shows that PDZs can be divided into two genome-wide clusters that coincide well with the division between canonical class 1 and 2 PDZs. Within the class 1 PDZs we observed binding overlap at unprecedented levels, mediated by two residues at positions 1 and 5 of the second α-helix of the binding pocket. Eight PDZ domains were subsequently selected for experimental binding studies and to verify the basics of our predictions. Overall, the PDZ domain class 1 cross-reactivity identified here implies that auxiliary mechanisms must be in place to overcome this inherent functional overlap and to minimize cross-selectivity within the living cell. Indeed, when we superimpose PDZ domain binding affinities with gene ontologies, network topology data and the domain position within a PDZ superfamily protein, functional overlap is minimized and PDZ domains position optimally in the binding space. We therefore propose that PDZ domain selectivity is achieved through cellular context rather than inherent binding specificity. PMID:21283644

  6. Overlap of phonetic features as a determinant of the between-stream phonological similarity effect.

    PubMed

    Eagan, Danielle E; Chein, Jason M

    2012-03-01

    Serial recall from working memory is known to be impaired by the presence of irrelevant background speech, but several prior studies have concluded that the magnitude of the impairment is independent of the phonological relationship between to-be-remembered (TBR) and to-be-ignored (TBI) sources of information. In the present study, we examined the influence of between-stream phonological similarity in serial recall while attending to a heretofore uncontrolled variable, the phonetic feature. We found that TBI items sharing many phonetic features with TBR items produced significantly stronger working-memory impairments than TBI items with minimal phonetic feature overlap. In addition, participants were more likely to report remembering incorrect items that incorporated phonological characteristics of the TBI stream in the high-overlap condition. These findings provide evidence for subphonemic between-stream interactions and suggest that multiple parallel processes contribute to the irrelevant speech effect. We propose that a 2-component model, which combines the assumptions of process- and content-based accounts for the irrelevant speech effect, offers the best explanation for these findings.

  7. Top-down controlled and bottom-up triggered orienting of auditory attention to pitch activate overlapping brain networks.

    PubMed

    Alho, Kimmo; Salmi, Juha; Koistinen, Sonja; Salonen, Oili; Rinne, Teemu

    2015-11-11

    A number of previous studies have suggested segregated networks of brain areas for top-down controlled and bottom-up triggered orienting of visual attention. However, the corresponding networks involved in auditory attention remain less studied. Our participants attended selectively to a tone stream with either a lower pitch or higher pitch in order to respond to infrequent changes in duration of attended tones. The participants were also required to shift their attention from one stream to the other when guided by a visual arrow cue. In addition to these top-down controlled cued attention shifts, infrequent task-irrelevant louder tones occurred in both streams to trigger attention in a bottom-up manner. Both cued shifts and louder tones were associated with enhanced activity in the superior temporal gyrus and sulcus, temporo-parietal junction, superior parietal lobule, inferior and middle frontal gyri, frontal eye field, supplementary motor area, and anterior cingulate gyrus. Thus, the present findings suggest that in the auditory modality, unlike in vision, top-down controlled and bottom-up triggered attention activate largely the same cortical networks. Comparison of the present results with our previous results from a similar experiment on spatial auditory attention suggests that fronto-parietal networks of attention to location or pitch overlap substantially. However, the auditory areas in the anterior superior temporal cortex might have a more important role in attention to the pitch than location of sounds. This article is part of a Special Issue entitled SI: Prediction and Attention.

  8. Scope of partial least-squares regression applied to the enantiomeric composition determination of ketoprofen from strongly overlapped chromatographic profiles.

    PubMed

    Padró, Juan M; Osorio-Grisales, Jaiver; Arancibia, Juan A; Olivieri, Alejandro C; Castells, Cecilia B

    2015-07-01

    Valuable quantitative information could be obtained from strongly overlapped chromatographic profiles of two enantiomers by using proper chemometric methods. Complete separation profiles where the peaks are fully resolved are difficult to achieve in chiral separation methods, and this becomes a particularly severe problem in case that the analyst needs to measure the chiral purity, i.e., when one of the enantiomers is present in the sample in very low concentrations. In this report, we explore the scope of a multivariate chemometric technique based on unfolded partial least-squares regression, as a mathematical tool to solve this quite frequent difficulty. This technique was applied to obtain quantitative results from partially overlapped chromatographic profiles of R- and S-ketoprofen, with different values of enantioresolution factors (from 0.81 down to less than 0.2 resolution units), and also at several different S:R enantiomeric ratios. Enantiomeric purity below 1% was determined with excellent precision even from almost completely overlapped signals. All these assays were tested on the most demanding condition, i.e., when the minor peak elutes immediately after the main peak. The results were validated using univariate calibration of completely resolved profiles and the method applied to the determination of enantiomeric purity of commercial pharmaceuticals.

  9. Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks.

    PubMed

    Garrido, Jesús A; Luque, Niceto R; Tolu, Silvia; D'Angelo, Egidio

    2016-08-01

    The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly understood. Here, we have used a simple model of afferent excitatory neurons and interneurons with lateral inhibition, reproducing a network topology found in many brain areas from the cerebellum to cortical columns. When endowed with spike-timing dependent plasticity (STDP) at the excitatory input synapses and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input patterns. The combination of plasticity in lateral inhibitory connections and homeostatic mechanisms in the inhibitory interneurons optimized mutual information (MI) transfer. The storage of multiple complex patterns in plastic interneuron networks could be critical for the generation of sparse representations of information in excitatory neuron populations falling under their control.

  10. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks

    PubMed Central

    Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner’s bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings. PMID:26844888

  11. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks.

    PubMed

    Fang, Gengfa; Orgun, Mehmet A; Shankaran, Rajan; Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner's bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings.

  12. Motor cortical plasticity in extrinsic hand muscles is determined by the resting thresholds of overlapping representations.

    PubMed

    Mirdamadi, J L; Suzuki, L Y; Meehan, S K

    2016-10-01

    Knowledge of the properties that govern the effectiveness of transcranial magnetic stimulation (TMS) interventions is critical to clinical application. Extrapolation to clinical populations has been limited by high inter-subject variability and a focus on intrinsic muscles of the hand in healthy populations. Therefore, the current study assessed variability of continuous theta burst stimulation (cTBS), a patterned TMS protocol, across an agonist-antagonist pair of extrinsic muscles of the hand. Secondarily, we assessed whether concurrent agonist contraction could enhance the efficacy of cTBS. Motor evoked potentials (MEP) were simultaneously recorded from the agonist flexor (FCR) and antagonist extensor (ECR) carpi radialis before and after cTBS over the FCR hotspot. cTBS was delivered with the FCR relaxed (cTBS-Relax) or during isometric wrist flexion (cTBS-Contract). cTBS-Relax suppressed FCR MEPs evoked from the FCR hotspot. However, the extent of FCR MEP suppression was strongly correlated with the relative difference between FCR and ECR resting motor thresholds. cTBS-Contract decreased FCR suppression but increased suppression of ECR MEPs elicited from the FCR hotspot. The magnitude of ECR MEP suppression following cTBS-Contract was independent of the threshold-amplitude relationships observed with cTBS-Relax. Contraction alone had no effect confirming the effect of cTBS-Contract was driven by the interaction between neuromuscular activity and cTBS. Interactions across muscle representations should be taken into account when predicting cTBS outcomes in healthy and clinical populations. Contraction during cTBS may be a useful means of focusing aftereffects when differences in baseline excitability across overlapping agonist-antagonist cortical representations may mitigate the inhibitory effect of cTBS. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  13. A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks

    PubMed Central

    Acikalin, M. Yavuz; Gorgolewski, Krzysztof J.; Poldrack, Russell A.

    2017-01-01

    Previous research has provided qualitative evidence for overlap in a number of brain regions across the subjective value network (SVN) and the default mode network (DMN). In order to quantitatively assess this overlap, we conducted a series of coordinate-based meta-analyses (CBMA) of results from 466 functional magnetic resonance imaging experiments on task-negative or subjective value-related activations in the human brain. In these analyses, we first identified significant overlaps and dissociations across activation foci related to SVN and DMN. Second, we investigated whether these overlapping subregions also showed similar patterns of functional connectivity, suggesting a shared functional subnetwork. We find considerable overlap between SVN and DMN in subregions of central ventromedial prefrontal cortex (cVMPFC) and dorsal posterior cingulate cortex (dPCC). Further, our findings show that similar patterns of bidirectional functional connectivity between cVMPFC and dPCC are present in both networks. We discuss ways in which our understanding of how subjective value (SV) is computed and represented in the brain can be synthesized with what we know about the DMN, mind-wandering, and self-referential processing in light of our findings. PMID:28154520

  14. The ABN Database: Sampling Strategies for Collection Overlap Studies.

    ERIC Educational Resources Information Center

    Rochester, Maxine K.

    1987-01-01

    Reports the methodology and results of a study which explored the potential of three approaches to sampling the Australian Bibliographic Network (ABN) database files for determining collection overlap among Australian libraries. (Author/CLB)

  15. Macromolecular geometries determined with field-flow fractionation and their impact on the overlap concentration.

    PubMed

    Rojas, Cinthia Carola; Wahlund, Karl-Gustav; Bergenståhl, Björn; Nilsson, Lars

    2008-06-01

    In this paper we aim to understand the size/conformation relationship in waxy barley starch, a polydisperse and ultrahigh molar mass biomacromolecule. Characterizations are performed with asymmetrical flow field-flow fractionation (AsFlFFF). Furthermore, we study the effect of homogenization on the molar mass, rms radius (r rms) and hydrodynamic radius (r h). For the untreated sample, the macromolecules are elongated objects with low apparent density. As a result of homogenization, molar mass, and r rms decrease, while r h remains unaffected. The process also induces an increase, and scaling with size, of apparent density as well as changes in conformation, represented qualitatively by r rms/ r h. Finally, results from AsFlFFF are compared with viscosimetry and discussed in terms of concentration and close-packing in relation to macromolecular shape and conformation. Hence, the results show that AsFlFFF and our novel methodology enable the determination of several physical properties with high relevance for the solution behavior of polydisperse macromolecules.

  16. Overlap between the neural correlates of cued recall and source memory: evidence for a generic recollection network?

    PubMed

    Hayama, Hiroki R; Vilberg, Kaia L; Rugg, Michael D

    2012-05-01

    Recall of a studied item and retrieval of its encoding context (source memory) both depend on recollection of qualitative information about the study episode. This study investigated whether recall and source memory engage overlapping neural regions. Participants (n = 18) studied a series of words, which were presented either to the left or right of fixation. fMRI data were collected during a subsequent test phase in which three-letter word-stems were presented, two thirds of which could be completed by a study item. Instructions were to use each stem as a cue to recall a studied word and, when recall was successful, to indicate the word's study location. When recall failed, the stem was to be completed with the first word to come to mind. Relative to stems for which recall failed, word-stems eliciting successful recall were associated with enhanced activity in a variety of cortical regions, including bilateral parietal, posterior midline, and parahippocampal cortex. Activity in these regions was enhanced when recall was accompanied by successful rather than unsuccessful source retrieval. It is proposed that the regions form part of a "recollection network" in which activity is graded according to the amount of information retrieved about a study episode.

  17. A Network-Based Target Overlap Score for Characterizing Drug Combinations: High Correlation with Cancer Clinical Trial Results

    PubMed Central

    Ligeti, Balázs; Pénzváltó, Zsófia; Vera, Roberto; Győrffy, Balázs; Pongor, Sándor

    2015-01-01

    Drug combinations are highly efficient in systemic treatment of complex multigene diseases such as cancer, diabetes, arthritis and hypertension. Most currently used combinations were found in empirical ways, which limits the speed of discovery for new and more effective combinations. Therefore, there is a substantial need for efficient and fast computational methods. Here, we present a principle that is based on the assumption that perturbations generated by multiple pharmaceutical agents propagate through an interaction network and can cause unexpected amplification at targets not immediately affected by the original drugs. In order to capture this phenomenon, we introduce a novel Target Overlap Score (TOS) that is defined for two pharmaceutical agents as the number of jointly perturbed targets divided by the number of all targets potentially affected by the two agents. We show that this measure is correlated with the known effects of beneficial and deleterious drug combinations taken from the DCDB, TTD and Drugs.com databases. We demonstrate the utility of TOS by correlating the score to the outcome of recent clinical trials evaluating trastuzumab, an effective anticancer agent utilized in combination with anthracycline- and taxane- based systemic chemotherapy in HER2-receptor (erb-b2 receptor tyrosine kinase 2) positive breast cancer. PMID:26047322

  18. Angle-resolved x-ray spectroscopic scheme to determine overlapping hyperfine splittings in highly charged heliumlike ions

    NASA Astrophysics Data System (ADS)

    Wu, Z. W.; Volotka, A. V.; Surzhykov, A.; Fritzsche, S.

    2017-07-01

    An angle-resolved x-ray spectroscopic scheme is presented for determining the hyperfine splitting of highly charged ions. For heliumlike ions, in particular, we propose to measure either the angular distribution or polarization of the 1 s 2 p P31,F →1 s2 S10,Ff emission following the stimulated decay of the initial 1 s 2 s S10,Fi level. It is found that both the angular and polarization characteristics of the emitted x-ray photons strongly depend on the (relative) splitting of the partially overlapping hyperfine 1 s 2 p P31,F resonances and may thus help resolve their hyperfine structure. The proposed scheme is feasible with present-day photon detectors and allows a measurement of the hyperfine splitting of heliumlike ions with a relative accuracy of about 10-4.

  19. miR-124, -128, and -137 Orchestrate Neural Differentiation by Acting on Overlapping Gene Sets Containing a Highly Connected Transcription Factor Network.

    PubMed

    Santos, Márcia C T; Tegge, Allison N; Correa, Bruna R; Mahesula, Swetha; Kohnke, Luana Q; Qiao, Mei; Ferreira, Marco A R; Kokovay, Erzsebet; Penalva, Luiz O F

    2016-01-01

    The ventricular-subventricular zone harbors neural stem cells (NSCs) that can differentiate into neurons, astrocytes, and oligodendrocytes. This process requires loss of stem cell properties and gain of characteristics associated with differentiated cells. miRNAs function as important drivers of this transition; miR-124, -128, and -137 are among the most relevant ones and have been shown to share commonalities and act as proneurogenic regulators. We conducted biological and genomic analyses to dissect their target repertoire during neurogenesis and tested the hypothesis that they act cooperatively to promote differentiation. To map their target genes, we transfected NSCs with antagomiRs and analyzed differences in their mRNA profile throughout differentiation with respect to controls. This strategy led to the identification of 910 targets for miR-124, 216 for miR-128, and 652 for miR-137. The target sets show extensive overlap. Inspection by gene ontology and network analysis indicated that transcription factors are a major component of these miRNAs target sets. Moreover, several of these transcription factors form a highly interconnected network. Sp1 was determined to be the main node of this network and was further investigated. Our data suggest that miR-124, -128, and -137 act synergistically to regulate Sp1 expression. Sp1 levels are dramatically reduced as cells differentiate and silencing of its expression reduced neuronal production and affected NSC viability and proliferation. In summary, our results show that miRNAs can act cooperatively and synergistically to regulate complex biological processes like neurogenesis and that transcription factors are heavily targeted to branch out their regulatory effect.

  20. CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

    NASA Astrophysics Data System (ADS)

    Tian, Li-Jun; Huang, Hai-Jun; Liu, Tian-Liang

    2009-07-01

    We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers' route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers' travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

  1. A dual-wavelength overlapping resonance Rayleigh scattering method for the determination of chondroitin sulfate with nile blue sulfate

    NASA Astrophysics Data System (ADS)

    Cui, Zhiping; Hu, Xiaoli; Liu, Shaopu; Liu, Zhongfang

    2011-12-01

    A dual-wavelength overlapping resonance Rayleigh scattering (DWO-RRS) method was developed to detect chondroitin sulfate (CS) with nile blue sulfate (NBS). At pH 3.0-4.0 Britton-Robinson (BR) buffer medium, CS interacted with NBS to form an ion-association complex. As a result, the new spectra of resonance Rayleigh scattering (RRS), second order scattering (SOS) and frequence doubling scattering (FDS) appeared and their intensities were enhanced greatly. Their maximum wavelengths were located at 303 nm (RRS), 362 nm (RRS), 588 nm (SOS) and 350 nm (FDS), respectively. The scattering intensities of the three methods were proportional to the concentration of CS in certain ranges. The methods had high sensitivity and the detection limits were between 1.5 and 7.1 ng mL -1. The DWO-RRS method had the highest sensitivity with the detection limit being 1.5 ng mL -1. The characteristics of the spectra and optimal reaction conditions of RRS method were investigated. The effects of coexistent substances on the determination of CS were evaluated. Owing to the high sensitivity, RRS method had been applied to the determination of CS in eye drops with satisfactory results. The recovery range was between 99.4% and 104.6% and the relative standard deviation (RSD) was between 0.4% and 0.8%. In addition, the reasons for RRS enhancement were discussed and the shape of ion-association complex was characterized by atomic force microscopy (AFM).

  2. Determination of the overlapping pK(a) values of chrysin using UV-vis spectroscopy and ab initio methods.

    PubMed

    Castro, G T; Ferretti, F H; Blanco, S E

    2005-11-01

    The overlapping pK(a) values of 5,7-dihydroxyflavone (chrysin) in EtOH-water solutions were determined by means of a UV-vis spectroscopic method that uses absorbance diagrams, at constant ionic strength (0.050 M) and temperature (25.0+/-0.1 degrees C). It was observed that the pK(a) values increase when the polarity-polarizability and solvation abilities of the reaction medium decrease. In order to calculate the pK(a1) and pK(a2) of chrysin in pure water, various relationships between the determined pK(a) and properties of solvents (relative permittivity, alpha-parameter of Taft and parameter Acity), are proposed. Moreover, with the aim of explaining the first pK(a1) value obtained, the molecular conformations and solute-solvent interactions of the 7(O(-))chrysinate monoanion were also investigated, using ab initio methods. Several ionization reactions and equilibria in water, which possesses a high hydrogen-bond-donor ability, are proposed. These reactions and equilibria constituted the necessary theoretical basis to calculate the first acidity constant of chrysin. The HF/6-31G(d) and HF/6-31+G(d) methods were used for calculations. Tomasi's method was used to analyze the formation of intermolecular hydrogen bonds between the 7(O(-))chrysinate monoanion and water molecules. It was proposed that in alkaline aqueous solutions the monoanion of chrysin is solvated with one water molecule. The agreement between the experimental and theoretical pK(a1) values provides good support for the acid-base reactions proposed in this paper.

  3. PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation.

    PubMed

    Cao, Buwen; Luo, Jiawei; Liang, Cheng; Wang, Shulin; Ding, Pingjian

    2016-10-01

    Identifying overlapping protein complexes in protein-protein interaction (PPI) networks can provide insight into cellular functional organization and thus elucidate underlying cellular mechanisms. Recently, various algorithms for protein complexes detection have been developed for PPI networks. However, majority of algorithms primarily depend on network topological feature and/or gene expression profile, failing to consider the inherent biological meanings between protein pairs. In this paper, we propose a novel method to detect protein complexes using pseudo-clique extension based on fuzzy relation (PCE-FR). Our algorithm operates in three stages: it first forms the nonoverlapping protein substructure based on fuzzy relation and then expands each substructure by adding neighbor proteins to maximize the cohesive score. Finally, highly overlapped candidate protein complexes are merged to form the final protein complex set. Particularly, our algorithm employs the biological significance hidden in protein pairs to construct edge weight for protein interaction networks. The experiment results show that our method can not only outperform classical algorithms such as CFinder, ClusterONE, CMC, RRW, HC-PIN, and ProRank +, but also achieve ideal overall performance in most of the yeast PPI datasets in terms of composite score consisting of precision, accuracy, and separation. We further apply our method to a human PPI network from the HPRD dataset and demonstrate it is very effective in detecting protein complexes compared to other algorithms.

  4. Determining Application Runtimes Using Queueing Network Modeling

    SciTech Connect

    Elliott, Michael L.

    2006-12-14

    Determination of application times-to-solution for large-scale clustered computers continues to be a difficult problem in high-end computing, which will only become more challenging as multi-core consumer machines become more prevalent in the market. Both researchers and consumers of these multi-core systems desire reasonable estimates of how long their programs will take to run (time-to-solution, or TTS), and how many resources will be consumed in the execution. Currently there are few methods of determining these values, and those that do exist are either overly simplistic in their assumptions or require great amounts of effort to parameterize and understand. One previously untried method is queuing network modeling (QNM), which is easy to parameterize and solve, and produces results that typically fall within 10 to 30% of the actual TTS for our test cases. Using characteristics of the computer network (bandwidth, latency) and communication patterns (number of messages, message length, time spent in communication), the QNM model of the NAS-PB CG application was applied to MCR and ALC, supercomputers at LLNL, and the Keck Cluster at USF, with average errors of 2.41%, 3.61%, and -10.73%, respectively, compared to the actual TTS observed. While additional work is necessary to improve the predictive capabilities of QNM, current results show that QNM has a great deal of promise for determining application TTS for multi-processor computer systems.

  5. Divide and Conquer Approach to Contact Map Overlap Problem Using 2D-Pattern Mining of Protein Contact Networks.

    PubMed

    Koneru, Suvarna Vani; Bhavani, Durga S

    2015-01-01

    A novel approach to Contact Map Overlap (CMO) problem is proposed using the two dimensional clusters present in the contact maps. Each protein is represented as a set of the non-trivial clusters of contacts extracted from its contact map. The approach involves finding matching regions between the two contact maps using approximate 2D-pattern matching algorithm and dynamic programming technique. These matched pairs of small contact maps are submitted in parallel to a fast heuristic CMO algorithm. The approach facilitates parallelization at this level since all the pairs of contact maps can be submitted to the algorithm in parallel. Then, a merge algorithm is used in order to obtain the overall alignment. As a proof of concept, MSVNS, a heuristic CMO algorithm is used for global as well as local alignment. The divide and conquer approach is evaluated for two benchmark data sets that of Skolnick and Ding et al. It is interesting to note that along with achieving saving of time, better overlap is also obtained for certain protein folds.

  6. Partially overlapping sensorimotor networks underlie speech praxis and verbal short-term memory: evidence from apraxia of speech following acute stroke.

    PubMed

    Hickok, Gregory; Rogalsky, Corianne; Chen, Rong; Herskovits, Edward H; Townsley, Sarah; Hillis, Argye E

    2014-01-01

    We tested the hypothesis that motor planning and programming of speech articulation and verbal short-term memory (vSTM) depend on partially overlapping networks of neural regions. We evaluated this proposal by testing 76 individuals with acute ischemic stroke for impairment in motor planning of speech articulation (apraxia of speech, AOS) and vSTM in the first day of stroke, before the opportunity for recovery or reorganization of structure-function relationships. We also evaluated areas of both infarct and low blood flow that might have contributed to AOS or impaired vSTM in each person. We found that AOS was associated with tissue dysfunction in motor-related areas (posterior primary motor cortex, pars opercularis; premotor cortex, insula) and sensory-related areas (primary somatosensory cortex, secondary somatosensory cortex, parietal operculum/auditory cortex); while impaired vSTM was associated with primarily motor-related areas (pars opercularis and pars triangularis, premotor cortex, and primary motor cortex). These results are consistent with the hypothesis, also supported by functional imaging data, that both speech praxis and vSTM rely on partially overlapping networks of brain regions.

  7. Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

    PubMed Central

    Villandre, Luc; Günthard, Huldrych F.; Kouyos, Roger; Stadler, Tanja

    2016-01-01

    Background Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. Methods The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index. Results and Conclusion Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network

  8. Overlap between the neural correlates of cued recall and source memory: evidence for a generic recollection network?

    PubMed Central

    Hayama, Hiroki R.; Vilberg, Kaia L.

    2012-01-01

    Recall of a studied item and retrieval of its encoding context (source memory) both depend upon recollection of qualitative information about the study episode. The present study investigated whether recall and source memory engage overlapping neural regions. Subjects (N=18) studied a series of words which were presented either to the left or right of fixation. fMRI data were collected during a subsequent test phase in which three-letter word stems were presented, two-thirds of which could be completed by a study item. Instructions were to use each stem as a cue to recall a studied word and, when recall was successful, to indicate the word’s study location. When recall failed, the stem was to be completed with the first word to come to mind. Relative to stems for which recall failed, word stems eliciting successful recall were associated with enhanced activity in a variety of cortical regions, including bilateral parietal, posterior midline, and parahippocampal cortex. Activity in these regions was enhanced when recall was accompanied by successful rather than unsuccessful source retrieval. It is proposed that the regions form part of a ‘recollection network’ in which activity is graded according to the amount of information retrieved about a study episode. PMID:22288393

  9. Apathy and impaired emotional facial recognition networks overlap in Parkinson's disease: a PET study with conjunction analyses.

    PubMed

    Robert, Gabriel; Le Jeune, Florence; Dondaine, Thibault; Drapier, Sophie; Péron, Julie; Lozachmeur, Clément; Sauleau, Paul; Houvenaghel, Jean-François; Travers, David; Millet, Bruno; Vérin, Marc; Drapier, Dominique

    2014-10-01

    Apathy is a disabling non-motor symptom that is frequently observed in Parkinson's disease (PD). Its description and physiopathology suggest that it is partially mediated by emotional impairment, but this research issue has never been addressed at a clinical and metabolic level. We therefore conducted a metabolic study using (18)fluorodeoxyglucose positron emission tomography ((18)FDG PET) in 36 PD patients without depression and dementia. Apathy was assessed on the Apathy Evaluation Scale (AES), and emotional facial recognition (EFR) performances (ie, percentage of correct responses) were calculated for each patient. Confounding factors such as age, antiparkinsonian and antidepressant medication, global cognitive functions and depressive symptoms were controlled for. We found a significant negative correlation between AES scores and performances on the EFR task. The apathy network was characterised by increased metabolism within the left posterior cingulate (PC) cortex (Brodmann area (BA) 31). The impaired EFR network was characterised by decreased metabolism within the bilateral PC gyrus (BA 31), right superior frontal gyrus (BAs 10, 9 and 6) and left superior frontal gyrus (BA 10 and 11). By applying conjunction analyses to both networks, we identified the right premotor cortex (BA 6), right orbitofrontal cortex (BA 10), left middle frontal gyrus (BA 8) and left posterior cingulate gyrus (BA 31) as the structures supporting the association between apathy and impaired EFR. These results confirm that apathy in PD is partially mediated by impaired EFR, opening up new prospects for alleviating apathy in PD, such as emotional rehabilitation.

  10. Determination of optimum structure of backpropagation networks

    NASA Astrophysics Data System (ADS)

    Phien, Huynh N.; Sureerattanan, Songyot

    2000-10-01

    The paper proposes the use of the Baysian Information Criterion (BIC), along with an algorithm to systematically select the appropriate structure of the backpropagation (BP) network for a given set of data. Simulation results with hydrological and economic data show that the algorithm performs very satisfactorily. Moreover, it compares with the method of Daqi and Shouyi for one hidden layer network and it is also used for the networks with more than one hidden layer.

  11. Overlapping clusters for distributed computation.

    SciTech Connect

    Mirrokni, Vahab; Andersen, Reid; Gleich, David F.

    2010-11-01

    Scalable, distributed algorithms must address communication problems. We investigate overlapping clusters, or vertex partitions that intersect, for graph computations. This setup stores more of the graph than required but then affords the ease of implementation of vertex partitioned algorithms. Our hope is that this technique allows us to reduce communication in a computation on a distributed graph. The motivation above draws on recent work in communication avoiding algorithms. Mohiyuddin et al. (SC09) design a matrix-powers kernel that gives rise to an overlapping partition. Fritzsche et al. (CSC2009) develop an overlapping clustering for a Schwarz method. Both techniques extend an initial partitioning with overlap. Our procedure generates overlap directly. Indeed, Schwarz methods are commonly used to capitalize on overlap. Elsewhere, overlapping communities (Ahn et al, Nature 2009; Mishra et al. WAW2007) are now a popular model of structure in social networks. These have long been studied in statistics (Cole and Wishart, CompJ 1970). We present two types of results: (i) an estimated swapping probability {rho}{infinity}; and (ii) the communication volume of a parallel PageRank solution (link-following {alpha} = 0.85) using an additive Schwarz method. The volume ratio is the amount of extra storage for the overlap (2 means we store the graph twice). Below, as the ratio increases, the swapping probability and PageRank communication volume decreases.

  12. How Structure Determines Correlations in Neuronal Networks

    PubMed Central

    Pernice, Volker; Staude, Benjamin; Cardanobile, Stefano; Rotter, Stefan

    2011-01-01

    Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, we face an intricate interplay between the topology of the network and the dynamics of the system, which is generally very hard to disentangle. A dynamical feature that has been subject of intense research in various fields are correlations between the noisy activity of nodes in a network. We consider a class of systems, where discrete signals are sent along the links of the network. Such systems are of particular relevance in neuroscience, because they provide models for networks of neurons that use action potentials for communication. We study correlations in dynamic networks with arbitrary topology, assuming linear pulse coupling. With our novel approach, we are able to understand in detail how specific structural motifs affect pairwise correlations. Based on a power series decomposition of the covariance matrix, we describe the conditions under which very indirect interactions will have a pronounced effect on correlations and population dynamics. In random networks, we find that indirect interactions may lead to a broad distribution of activation levels with low average but highly variable correlations. This phenomenon is even more pronounced in networks with distance dependent connectivity. In contrast, networks with highly connected hubs or patchy connections often exhibit strong average correlations. Our results are particularly relevant in view of new experimental techniques that enable the parallel recording of spiking activity from a large number of neurons, an appropriate interpretation of which is hampered by the currently limited understanding of structure-dynamics relations in complex networks. PMID:21625580

  13. Finding overlapping communities using seed set

    NASA Astrophysics Data System (ADS)

    Yang, Jin-Xuan; Zhang, Xiao-Dong

    2017-02-01

    The local optimization algorithm using seed set to find overlapping communities has become more and more a significant method, but it is a great challenge how to choose a good seed set. In this paper, a new method is proposed to achieve the choice of candidate seed sets, and yields a new algorithm to find overlapping communities in complex networks. By testing in real world networks and synthetic networks, this method can successfully detect overlapping communities and outperform other state-of-the-art overlapping community detection methods.

  14. Pathway Network Analyses for Autism Reveal Multisystem Involvement, Major Overlaps with Other Diseases and Convergence upon MAPK and Calcium Signaling

    PubMed Central

    Wen, Ya; Alshikho, Mohamad J.; Herbert, Martha R.

    2016-01-01

    We used established databases in standard ways to systematically characterize gene ontologies, pathways and functional linkages in the large set of genes now associated with autism spectrum disorders (ASDs). These conditions are particularly challenging—they lack clear pathognomonic biological markers, they involve great heterogeneity across multiple levels (genes, systemic biological and brain characteristics, and nuances of behavioral manifestations)—and yet everyone with this diagnosis meets the same defining behavioral criteria. Using the human gene list from Simons Foundation Autism Research Initiative (SFARI) we performed gene set enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database, and then derived a pathway network from pathway-pathway functional interactions again in reference to KEGG. Through identifying the GO (Gene Ontology) groups in which SFARI genes were enriched, mapping the coherence between pathways and GO groups, and ranking the relative strengths of representation of pathway network components, we 1) identified 10 disease-associated and 30 function-associated pathways 2) revealed calcium signaling pathway and neuroactive ligand-receptor interaction as the most enriched, statistically significant pathways from the enrichment analysis, 3) showed calcium signaling pathways and MAPK signaling pathway to be interactive hubs with other pathways and also to be involved with pervasively present biological processes, 4) found convergent indications that the process “calcium-PRC (protein kinase C)-Ras-Raf-MAPK/ERK” is likely a major contributor to ASD pathophysiology, and 5) noted that perturbations associated with KEGG’s category of environmental information processing were common. These findings support the idea that ASD-associated genes may contribute not only to core features of ASD themselves but also to vulnerability to other chronic and systemic problems potentially including cancer, metabolic

  15. Factors determining nestedness in complex networks.

    PubMed

    Jonhson, Samuel; Domínguez-García, Virginia; Muñoz, Miguel A

    2013-01-01

    Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure of nestedness and study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that most of the empirically found nestedness stems from heterogeneity in the degree distribution. Once such an influence has been discounted - as a second factor - we find that nestedness is strongly correlated with disassortativity and hence - as random networks have been recently found to be naturally disassortative - they also tend to be naturally nested just as the result of chance.

  16. Factors Determining Nestedness in Complex Networks

    PubMed Central

    Jonhson, Samuel; Domínguez-García, Virginia; Muñoz, Miguel A.

    2013-01-01

    Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure of nestedness and study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that most of the empirically found nestedness stems from heterogeneity in the degree distribution. Once such an influence has been discounted – as a second factor – we find that nestedness is strongly correlated with disassortativity and hence – as random networks have been recently found to be naturally disassortative – they also tend to be naturally nested just as the result of chance. PMID:24069264

  17. DETERMINANTS OF NETWORK OUTCOMES: THE IMPACT OF MANAGEMENT STRATEGIES

    PubMed Central

    YSA, TAMYKO; SIERRA, VICENTA; ESTEVE, MARC

    2014-01-01

    The literature on network management is extensive. However, it generally explores network structures, neglecting the impact of management strategies. In this article we assess the effect of management strategies on network outcomes, providing empirical evidence from 119 urban revitalization networks. We go beyond current work by testing a path model for the determinants of network outcomes and considering the interactions between the constructs: management strategies, trust, complexity, and facilitative leadership. Our results suggest that management strategies have a strong effect on network outcomes and that they enhance the level of trust. We also found that facilitative leadership has a positive impact on network management as well as on trust in the network. Our findings also show that complexity has a negative impact on trust. A key finding of our research is that managers may wield more influence on network dynamics than previously theorized. PMID:25520529

  18. Approach of Complex Networks for the Determination of Brain Death

    NASA Astrophysics Data System (ADS)

    Sun, Wei-Gang; Cao, Jian-Ting; Wang, Ru-Bin

    2011-06-01

    In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death.

  19. [Study on the determination of contents of Zn, Cu and Co by using artifical neural network and ultraviolet spectrum].

    PubMed

    Yan, Z; Jiang, X; Zhang, S

    2000-06-01

    By means of artificial neural network and back-propagation train algorithm, the three-component metal coordinate compounds of PAR-Zn, Cu, Co were determined simultaneously, in which the spectra overlapped. In 580-440 nm, the absorbance(A) at 14 wavelength were taken as character parameter of artificial neural network, and samples were arranged by method of uniformity design. The mean recovery of Zn, Cu, Co were 95.22%, 95.98% and 100.5%. The experiment results show that the determination is accurate, and the method has good performance.

  20. Heat Shock Partially Dissociates the Overlapping Modules of the Yeast Protein-Protein Interaction Network: A Systems Level Model of Adaptation

    PubMed Central

    Mihalik, Ágoston; Csermely, Peter

    2011-01-01

    Network analysis became a powerful tool giving new insights to the understanding of cellular behavior. Heat shock, the archetype of stress responses, is a well-characterized and simple model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights of the yeast interactome from the changes of mRNA expression levels upon heat shock. The major finding of our study is that heat shock induced a significant decrease in both the overlaps and connections of yeast interactome modules. In agreement with this the weighted diameter of the yeast interactome had a 4.9-fold increase in heat shock. Several key proteins of the heat shock response became centers of heat shock-induced local communities, as well as bridges providing a residual connection of modules after heat shock. The observed changes resemble to a ‘stratus-cumulus’ type transition of the interactome structure, since the unstressed yeast interactome had a globally connected organization, similar to that of stratus clouds, whereas the heat shocked interactome had a multifocal organization, similar to that of cumulus clouds. Our results showed that heat shock induces a partial disintegration of the global organization of the yeast interactome. This change may be rather general occurring in many types of stresses. Moreover, other complex systems, such as single proteins, social networks and ecosystems may also decrease their inter-modular links, thus develop more compact modules, and display a partial disintegration of their global structure in the initial phase of crisis. Thus, our work may provide a model of a general, system-level adaptation mechanism to environmental changes. PMID:22022244

  1. Structural determinants of criticality in biological networks

    PubMed Central

    Valverde, Sergi; Ohse, Sebastian; Turalska, Malgorzata; West, Bruce J.; Garcia-Ojalvo, Jordi

    2015-01-01

    Many adaptive evolutionary systems display spatial and temporal features, such as long-range correlations, typically associated with the critical point of a phase transition in statistical physics. Empirical and theoretical studies suggest that operating near criticality enhances the functionality of biological networks, such as brain and gene networks, in terms for instance of information processing, robustness, and evolvability. While previous studies have explained criticality with specific system features, we still lack a general theory of critical behavior in biological systems. Here we look at this problem from the complex systems perspective, since in principle all critical biological circuits have in common the fact that their internal organization can be described as a complex network. An important question is how self-similar structure influences self-similar dynamics. Modularity and heterogeneity, for instance, affect the location of critical points and can be used to tune the system toward criticality. We review and discuss recent studies on the criticality of neuronal and genetic networks, and discuss the implications of network theory when assessing the evolutionary features of criticality. PMID:26005422

  2. Label free checkerboard assay to determine overlapping epitopes of Ebola virus VP-40 antibodies using surface plasmon resonance.

    PubMed

    Anderson, George P; Liu, Jinny L; Zabetakis, Dan; Legler, Patricia M; Goldman, Ellen R

    2017-03-01

    Immunoassay formats, in which antibodies provide sensitivity and specificity, are often utilized to provide rapid and simple diagnostic tests. Surface plasmon resonance is frequently used to evaluate the suitability of antibodies by determining binding kinetics to agents or surrogate antigens. We used SPR to evaluate a number of commercial monoclonal antibodies as well as single domain antibodies produced in-house. All the antibodies targeted the Ebola virus viral protein 40 (VP40). We determined the ability of each antibody to bind to immobilized VP40, and ensured they did not bind Ebola glycoprotein or the nucleoprotein. A subset of the monoclonal antibodies was immobilized to characterize antigen capture in solution. It can be advantageous to utilize antibodies that recognize distinct epitopes when choosing reagents for detection and diagnostic assays. We determined the uniqueness of the epitope recognized by the anti-VP40 antibodies using a checkerboard format that exploits the 6×6 array of interactions monitored by the Bio-Rad ProteOn XPR36 SPR instrument. The results demonstrate the utility of surface plasmon resonance to characterize monoclonal and recombinant antibodies. Additionally, the analysis presented here enabled the identification of pairs of anti-VP40 antibodies which could potentially be utilized in sandwich type immunoassays for the detection of Ebola virus.

  3. Seeding for pervasively overlapping communities

    NASA Astrophysics Data System (ADS)

    Lee, Conrad; Reid, Fergal; McDaid, Aaron; Hurley, Neil

    2011-06-01

    In some social and biological networks, the majority of nodes belong to multiple communities. It has recently been shown that a number of the algorithms specifically designed to detect overlapping communities do not perform well in such highly overlapping settings. Here, we consider one class of these algorithms, those which optimize a local fitness measure, typically by using a greedy heuristic to expand a seed into a community. We perform synthetic benchmarks which indicate that an appropriate seeding strategy becomes more important as the extent of community overlap increases. We find that distinct cliques provide the best seeds. We find further support for this seeding strategy with benchmarks on a Facebook network and the yeast interactome.

  4. Metal-Sulfur Valence Orbital Interaction Energies in Metal–Dithiolene Complexes: Determination of Charge and Overlap Interaction Energies by Comparison of Core and Valence Ionization Energy Shifts

    PubMed Central

    Wiebelhaus, Nicholas J.; Cranswick, Matthew A.; Klein, Eric L.; Lockett, L. Tori; Lichtenberger, Dennis L.; Enemark, John H.

    2011-01-01

    The electronic interactions between metals and dithiolenes are important in the biological processes of many metalloenzymes as well as in diverse chemical and material applications. Of special note is the ability of the dithiolene ligand to support metal centers in multiple coordination environments and oxidation states. To better understand the nature of metal-dithiolene electronic interactions, new capabilities in gas-phase core photoelectron spectroscopy for molecules with high sublimation temperatures have been developed and applied to a series of molecules of the type Cp2M(bdt) (Cp = η5-cyclopentadienyl, M = Ti, V, Mo, and bdt = benzenedithiolato). Comparison of the gas-phase core and valence ionization energy shifts provides a unique quantitative energy measure of valence orbital overlap interactions between the metal and sulfur orbitals that is separated from the effects of charge redistribution. The results explain the large amount of sulfur character in the redox-active orbitals and the ‘leveling’ of oxidation state energies in metal-dithiolene systems. The experimentally-determined orbital interaction energies reveal a previously unidentified overlap interaction of the predominantly sulfur HOMO of the bdt ligand with filled π orbitals of the Cp ligands, suggesting that direct dithiolene interactions with other ligands bound to the metal could be significant for other metal-dithiolene systems in chemistry and biology. PMID:21988484

  5. Enantiomeric analysis of overlapped chromatographic profiles in the presence of interferences. Determination of ibuprofen in a pharmaceutical formulation containing homatropine.

    PubMed

    Padró, J M; Osorio-Grisales, J; Arancibia, J A; Olivieri, A C; Castells, C B

    2016-10-07

    In this work, we studied the combination of chemometric methods with chromatographic separations as a strategy applied to the analysis of enantiomers when complete enantioseparation is difficult or requires long analysis times and, in addition, the target signals have interference from the matrix. We present the determination of ibuprofen enantiomers in pharmaceutical formulations containing homatropine as interference by chiral HPLC-DAD detection in combination with partial least-squares algorithms. The method has been applied to samples containing enantiomeric ratios from 95:5 to 99.5:0.5 and coelution of interferents. The results were validated using univariate calibration and without homatropine. Relative error of the method was less than 4.0%, for both enantiomers. Limits of detection (LOD) and quantification (LOQ) for (S)-(+)-ibuprofen were 4.96×10(-10) and 1.50×10(-9)mol, respectively. LOD and LOQ for the R-(-)-ibuprofen were LOD=1.60×10(-11)mol and LOQ=4.85×10(-11)mol, respectively. Finally, the chemometric method was applied to the determination of enantiomeric purity of commercial pharmaceuticals. The ultimate goal of this research was the development of rapid, reliable, and robust methods for assessing enantiomeric purity by conventional diode array detector assisted by chemometric tools.

  6. HUNTing the Overlap

    SciTech Connect

    Iancu, Costin; Parry, Husbands; Hargrove, Paul

    2005-07-08

    Hiding communication latency is an important optimization for parallel programs. Programmers or compilers achieve this by using non-blocking communication primitives and overlapping communication with computation or other communication operations. Using non-blocking communication raises two issues: performance and programmability. In terms of performance, optimizers need to find a good communication schedule and are sometimes constrained by lack of full application knowledge. In terms of programmability, efficiently managing non-blocking communication can prove cumbersome for complex applications. In this paper we present the design principles of HUNT, a runtime system designed to search and exploit some of the available overlap present at execution time in UPC programs. Using virtual memory support, our runtime implements demand-driven synchronization for data involved in communication operations. It also employs message decomposition and scheduling heuristics to transparently improve the non-blocking behavior of applications. We provide a user level implementation of HUNT on a variety of modern high performance computing systems. Results indicate that our approach is successful in finding some of the overlap available at execution time. While system and application characteristics influence performance, perhaps the determining factor is the time taken by the CPU to execute a signal handler. Demand driven synchronization at execution time eliminates the need for the explicit management of non-blocking communication. Besides increasing programmer productivity, this feature also simplifies compiler analysis for communication optimizations.

  7. Function approximation using adaptive and overlapping intervals

    SciTech Connect

    Patil, R.B.

    1995-05-01

    A problem common to many disciplines is to approximate a function given only the values of the function at various points in input variable space. A method is proposed for approximating a function of several to one variable. The model takes the form of weighted averaging of overlapping basis functions defined over intervals. The number of such basis functions and their parameters (widths and centers) are automatically determined using given training data and a learning algorithm. The proposed algorithm can be seen as placing a nonuniform multidimensional grid in the input domain with overlapping cells. The non-uniformity and overlap of the cells is achieved by a learning algorithm to optimize a given objective function. This approach is motivated by the fuzzy modeling approach and a learning algorithms used for clustering and classification in pattern recognition. The basics of why and how the approach works are given. Few examples of nonlinear regression and classification are modeled. The relationship between the proposed technique, radial basis neural networks, kernel regression, probabilistic neural networks, and fuzzy modeling is explained. Finally advantages and disadvantages are discussed.

  8. Spectrophotometric methods manipulating ratio spectra for simultaneous determination of binary mixtures with sever overlapping spectra: a comparative study.

    PubMed

    Moustafa, H; Fayez, Y

    2014-12-10

    Three simple, specific and accurate spectrophotometric methods manipulating ratio spectra were developed and validated for simultaneous determination of Rabeprazole sodium (RB) and Domperidone (DP) in their binary mixture without prior separation. Method A, is constant center spectrophotometric method (CC). Method B is a ratio difference spectrophotometric one (RD), while method C is a combined ratio isoabsorptive point-ratio difference method (RIRD). Linear correlations were obtained in range of 4-44μg/mL for both Rabeprazole sodium and Domperidone. The mean percentage recoveries of RB were 99.69±0.504 for method A, 99.83±0.483 for (B) and 100.31±0.499 for (C), respectively, and that of DP were 99.52±0.474 for method A, 100.12±0.505 for (B) and 100.16±0.498 for (C), respectively. Specificity was investigated by analysis of laboratory prepared mixtures containing the cited drugs and their combined tablet dosage form. The obtained results were statistically compared with those obtained by the reported methods, showing no significant difference with respect to accuracy and precision. The three methods were validated as per ICH guidelines and can be applied for routine analysis in quality control laboratories. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Incorporation of flow injection analysis with dual-wavelength overlapping resonance Rayleigh scattering for rapid determination of malachite green and its metabolite in fish.

    PubMed

    Zhu, Jinghui; Qin, Mingyou; Liu, Shaopu; Liu, Zhongfang; Yang, Jidong; Hu, Xiaoli

    2014-09-15

    A flow injection analysis (FIA) system combined with dual-wavelength overlapping resonance Rayleigh scattering (DWO-RRS) has been established and validated for rapid determination of malachite green (MG) and its metabolite in fish samples. Under experimental condition, MG would react with Erythrosin (Ery) to form ion-association complexes, resulting in the occurrence of two RRS peaks and a dramatic enhancement of RRS intensity. The maximum RRS peaks were located at 286 nm and 337 nm. It is noted that the increments of both of these two peaks were proportional to the concentration of MG. The detection limit of DWO-RRS was 1.5 ng/mL, which was comparable to several reported methods. Moreover, the results of real sample analysis exhibited an acceptable recovery between 97.5% and 103.6%, indicating that the method had good reproducibility.

  10. Incorporation of flow injection analysis with dual-wavelength overlapping resonance Rayleigh scattering for rapid determination of malachite green and its metabolite in fish

    NASA Astrophysics Data System (ADS)

    Zhu, Jinghui; Qin, Mingyou; Liu, Shaopu; Liu, Zhongfang; Yang, Jidong; Hu, Xiaoli

    2014-09-01

    A flow injection analysis (FIA) system combined with dual-wavelength overlapping resonance Rayleigh scattering (DWO-RRS) has been established and validated for rapid determination of malachite green (MG) and its metabolite in fish samples. Under experimental condition, MG would react with Erythrosin (Ery) to form ion-association complexes, resulting in the occurrence of two RRS peaks and a dramatic enhancement of RRS intensity. The maximum RRS peaks were located at 286 nm and 337 nm. It is noted that the increments of both of these two peaks were proportional to the concentration of MG. The detection limit of DWO-RRS was 1.5 ng/mL, which was comparable to several reported methods. Moreover, the results of real sample analysis exhibited an acceptable recovery between 97.5% and 103.6%, indicating that the method had good reproducibility.

  11. Determination of lithology from well logs using a neural network

    SciTech Connect

    Rogers, S.J.; Fang, J.H. ); Karr, C.L.; Stanley, D.A. )

    1992-05-01

    The authors have developed a computer program to automatically determine lithologies from well logs using a back-propagation neural network. Unlike a conventional serial computer, a neural network is a computational system composed of nodes (sometimes called neurons, neurodes, or units) and the connections between these nodes. Neural computing attempts to emulate the functions of the mammalian brain, thus mimicking thought processes. The neural network approach differs from previous pattern recognition methods in its ability to learn from examples. Unlike conventional statistical methods, this new approach does not require sophisticated mathematics and a large amount of statistical data. This paper discusses the application of neural networks to a pattern recognition problem in geology: the determination of lithology from well logs. The neural network determined the lithologies (limestone, dolomite, sandstone, shale, sandy and dolomitic limestones, sandy dolomite, and shale sandstone) from selected well logs in a fraction of the time required by an experienced human log analyst.

  12. Harmonic analysis of Boolean networks: determinative power and perturbations

    PubMed Central

    2013-01-01

    Consider a large Boolean network with a feed forward structure. Given a probability distribution on the inputs, can one find, possibly small, collections of input nodes that determine the states of most other nodes in the network? To answer this question, a notion that quantifies the determinative power of an input over the states of the nodes in the network is needed. We argue that the mutual information (MI) between a given subset of the inputs X={X1,...,Xn} of some node i and its associated function fi(X) quantifies the determinative power of this set of inputs over node i. We compare the determinative power of a set of inputs to the sensitivity to perturbations to these inputs, and find that, maybe surprisingly, an input that has large sensitivity to perturbations does not necessarily have large determinative power. However, for unate functions, which play an important role in genetic regulatory networks, we find a direct relation between MI and sensitivity to perturbations. As an application of our results, we analyze the large-scale regulatory network of Escherichia coli. We identify the most determinative nodes and show that a small subset of those reduces the overall uncertainty of the network state significantly. Furthermore, the network is found to be tolerant to perturbations of its inputs. PMID:23642003

  13. Determining ecoregions for environmental and GMO monitoring networks.

    PubMed

    Graef, F; Schmidt, G; Schröder, W; Stachow, U

    2005-09-01

    A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.

  14. Structural Analysis to Determine the Core of Hypoxia Response Network

    PubMed Central

    Heiner, Monika; Sriram, K.

    2010-01-01

    The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network's dynamics. The question that begs for an answer is how to identify the core that is representative of a network's dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent. PMID:20098728

  15. Clique graphs and overlapping communities

    NASA Astrophysics Data System (ADS)

    Evans, T. S.

    2010-12-01

    It is shown how to construct a clique graph in which properties of cliques of a fixed order in a given graph are represented by vertices in a weighted graph. Various definitions and motivations for these weights are given. The detection of communities or clusters is used to illustrate how a clique graph may be exploited. In particular a benchmark network is shown where clique graphs find the overlapping communities accurately while vertex partition methods fail.

  16. Overlapping structures in sensory-motor mappings.

    PubMed

    Earland, Kevin; Lee, Mark; Shaw, Patricia; Law, James

    2014-01-01

    This paper examines a biologically-inspired representation technique designed for the support of sensory-motor learning in developmental robotics. An interesting feature of the many topographic neural sheets in the brain is that closely packed receptive fields must overlap in order to fully cover a spatial region. This raises interesting scientific questions with engineering implications: e.g. is overlap detrimental? does it have any benefits? This paper examines the effects and properties of overlap between elements arranged in arrays or maps. In particular we investigate how overlap affects the representation and transmission of spatial location information on and between topographic maps. Through a series of experiments we determine the conditions under which overlap offers advantages and identify useful ranges of overlap for building mappings in cognitive robotic systems. Our motivation is to understand the phenomena of overlap in order to provide guidance for application in sensory-motor learning robots.

  17. Overlapping Structures in Sensory-Motor Mappings

    PubMed Central

    Earland, Kevin; Lee, Mark; Shaw, Patricia; Law, James

    2014-01-01

    This paper examines a biologically-inspired representation technique designed for the support of sensory-motor learning in developmental robotics. An interesting feature of the many topographic neural sheets in the brain is that closely packed receptive fields must overlap in order to fully cover a spatial region. This raises interesting scientific questions with engineering implications: e.g. is overlap detrimental? does it have any benefits? This paper examines the effects and properties of overlap between elements arranged in arrays or maps. In particular we investigate how overlap affects the representation and transmission of spatial location information on and between topographic maps. Through a series of experiments we determine the conditions under which overlap offers advantages and identify useful ranges of overlap for building mappings in cognitive robotic systems. Our motivation is to understand the phenomena of overlap in order to provide guidance for application in sensory-motor learning robots. PMID:24392118

  18. Logical Reduction of Biological Networks to Their Most Determinative Components.

    PubMed

    Matache, Mihaela T; Matache, Valentin

    2016-07-01

    Boolean networks have been widely used as models for gene regulatory networks, signal transduction networks, or neural networks, among many others. One of the main difficulties in analyzing the dynamics of a Boolean network and its sensitivity to perturbations or mutations is the fact that it grows exponentially with the number of nodes. Therefore, various approaches for simplifying the computations and reducing the network to a subset of relevant nodes have been proposed in the past few years. We consider a recently introduced method for reducing a Boolean network to its most determinative nodes that yield the highest information gain. The determinative power of a node is obtained by a summation of all mutual information quantities over all nodes having the chosen node as a common input, thus representing a measure of information gain obtained by the knowledge of the node under consideration. The determinative power of nodes has been considered in the literature under the assumption that the inputs are independent in which case one can use the Bahadur orthonormal basis. In this article, we relax that assumption and use a standard orthonormal basis instead. We use techniques of Hilbert space operators and harmonic analysis to generate formulas for the sensitivity to perturbations of nodes, quantified by the notions of influence, average sensitivity, and strength. Since we work on finite-dimensional spaces, our formulas and estimates can be and are formulated in plain matrix algebra terminology. We analyze the determinative power of nodes for a Boolean model of a signal transduction network of a generic fibroblast cell. We also show the similarities and differences induced by the alternative complete orthonormal basis used. Among the similarities, we mention the fact that the knowledge of the states of the most determinative nodes reduces the entropy or uncertainty of the overall network significantly. In a special case, we obtain a stronger result than in previous

  19. Precise orbit determination of BeiDou constellation based on BETS and MGEX network.

    PubMed

    Lou, Yidong; Liu, Yang; Shi, Chuang; Yao, Xiuguang; Zheng, Fu

    2014-04-15

    Chinese BeiDou Navigation Satellite System is officially operational as a regional constellation with five Geostationary Earth Orbit (GEO) satellites, five Inclined Geosynchronous Satellite Orbit (IGSO) satellites and four Medium Earth Orbit (MEO) satellites. Observations from the BeiDou Experimental Tracking Stations (BETS) and the IGS Multi-GNSS Experiment (MGEX) network from 1 January to 31 March 2013 are processed for orbit determination of the BeiDou constellation. Various arc lengths and solar radiation pressure parameters are investigated. The reduced set of ECOM five-parameter model produces better performance than the full set of ECOM nine-parameter model for BeiDou IGSO and MEO. The orbit overlap for the middle days of 3-day arc solutions is better than 20 cm and 14 cm for IGSO and MEO in RMS, respectively. Satellite laser ranging residuals are better than 10 cm for both IGSO and MEO. For BeiDou GEO, the orbit overlap of several meters and satellite laser ranging residuals of several decimetres can be achieved.

  20. Precise orbit determination of BeiDou constellation based on BETS and MGEX network

    PubMed Central

    Lou, Yidong; Liu, Yang; Shi, Chuang; Yao, Xiuguang; Zheng, Fu

    2014-01-01

    Chinese BeiDou Navigation Satellite System is officially operational as a regional constellation with five Geostationary Earth Orbit (GEO) satellites, five Inclined Geosynchronous Satellite Orbit (IGSO) satellites and four Medium Earth Orbit (MEO) satellites. Observations from the BeiDou Experimental Tracking Stations (BETS) and the IGS Multi-GNSS Experiment (MGEX) network from 1 January to 31 March 2013 are processed for orbit determination of the BeiDou constellation. Various arc lengths and solar radiation pressure parameters are investigated. The reduced set of ECOM five-parameter model produces better performance than the full set of ECOM nine-parameter model for BeiDou IGSO and MEO. The orbit overlap for the middle days of 3-day arc solutions is better than 20 cm and 14 cm for IGSO and MEO in RMS, respectively. Satellite laser ranging residuals are better than 10 cm for both IGSO and MEO. For BeiDou GEO, the orbit overlap of several meters and satellite laser ranging residuals of several decimetres can be achieved. PMID:24733025

  1. Investigating the overlap function of a ceilometer with different methods

    NASA Astrophysics Data System (ADS)

    Wagner, Frank; Mattis, Ina; Geiss, Alexander; Wiegner, Matthias

    2015-04-01

    The DWD ceilometer network was created in 2008. In the following years more and more ceilometers of type CHM15k (manufacturer Jenoptik) were installed with the aim of observing atmospheric aerosol particles. Now, 58 ceilometers are in continuous operation. The overlap function of a ceilometer is important for the correction of the measurements in the near field of the instrument. In this work the overlap function for a ceilometer CHM15k Nimbus was determined with different methods and the results are compared taking into accounts the respective errors and error propagation. The first method is based on the comparison of measurements with another CHM15k Nimbus device which has a known overlap function. For this type of instrument the overlap is complete at about 1.5km distance. Co-located measurements of the 2 devices were done at Hohenpeissenberg Meteorological Observatory during several months in summer 2013. The second method resembles the first one but the comparison is done with a CHM15k near field instrument. For this type of instrument the overlap is complete at about 500m distance. Co-located measurements of the 2 devices were done at the Meteorological Institute of the University of Munich during one week in July 2013.The third method is based on horizontal measurements under the assumption that the aerosol particles are horizontally homogenously spread. This is assured by measurements in different (horizontal) directions, i.e. different azimuth angles, under suitable meteorological conditions. The measurements were acquired during one night at Hohenpeissenberg Meteorological Observatory. All three methods were used to determine the overlap function of a CHM15k ceilometer. The results were similar although the final error of the obtained overlap function differs due to different assumptions and measurement errors.

  2. Heterogeneity in ecological mutualistic networks dominantly determines community stability

    PubMed Central

    Feng, Wenfeng; Takemoto, Kazuhiro

    2014-01-01

    Although the hypothesis that nestedness determines mutualistic ecosystem dynamics is accepted in general, results of some recent data analyses and theoretical studies have begun to cast doubt on the impact of nestedness on ecosystem stability. However, definite conclusions have not yet been reached because previous studies are mainly based on numerical simulations. Therefore, we reveal a mathematical architecture in the relationship between ecological mutualistic networks and local stability based on spectral graph analysis. In particular, we propose a theoretical method for estimating the dominant eigenvalue (i.e., spectral radius) of quantitative (or weighted) bipartite networks by extending spectral graph theory, and provide a theoretical prediction that the heterogeneity of node degrees and link weights primarily determines the local stability; on the other hand, nestedness additionally affects it. Numerical simulations demonstrate the validity of our theory and prediction. This study emphasizes the importance of ecological network heterogeneity in ecosystem dynamics, and it enhances our understanding of structure–stability relationships. PMID:25081499

  3. Heterogeneity in ecological mutualistic networks dominantly determines community stability.

    PubMed

    Feng, Wenfeng; Takemoto, Kazuhiro

    2014-08-01

    Although the hypothesis that nestedness determines mutualistic ecosystem dynamics is accepted in general, results of some recent data analyses and theoretical studies have begun to cast doubt on the impact of nestedness on ecosystem stability. However, definite conclusions have not yet been reached because previous studies are mainly based on numerical simulations. Therefore, we reveal a mathematical architecture in the relationship between ecological mutualistic networks and local stability based on spectral graph analysis. In particular, we propose a theoretical method for estimating the dominant eigenvalue (i.e., spectral radius) of quantitative (or weighted) bipartite networks by extending spectral graph theory, and provide a theoretical prediction that the heterogeneity of node degrees and link weights primarily determines the local stability; on the other hand, nestedness additionally affects it. Numerical simulations demonstrate the validity of our theory and prediction. This study emphasizes the importance of ecological network heterogeneity in ecosystem dynamics, and it enhances our understanding of structure-stability relationships.

  4. Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance

    PubMed Central

    Guimerà, Roger; Uzzi, Brian; Spiro, Jarrett; Nunes Amaral, Luís A.

    2007-01-01

    Agents in creative enterprises are embedded in networks that inspire, support, and evaluate their work. Here, we investigate how the mechanisms by which creative teams self-assemble determine the structure of these collaboration networks. We propose a model for the self-assembly of creative teams that has its basis in three parameters: team size, the fraction of newcomers in new productions, and the tendency of incumbents to repeat previous collaborations. The model suggests that the emergence of a large connected community of practitioners can be described as a phase transition. We find that team assembly mechanisms determine both the structure of the collaboration network and team performance for teams derived from both artistic and scientific fields. PMID:15860629

  5. Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity.

    PubMed

    Xu, Jiansong; Calhoun, Vince D; Worhunsky, Patrick D; Xiang, Hui; Li, Jian; Wall, John T; Pearlson, Godfrey D; Potenza, Marc N

    2015-01-01

    Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.

  6. Functional Network Overlap as Revealed by fMRI Using sICA and Its Potential Relationships with Functional Heterogeneity, Balanced Excitation and Inhibition, and Sparseness of Neuron Activity

    PubMed Central

    Xu, Jiansong; Calhoun, Vince D.; Worhunsky, Patrick D.; Xiang, Hui; Li, Jian; Wall, John T.; Pearlson, Godfrey D.; Potenza, Marc N.

    2015-01-01

    Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation. PMID:25714362

  7. The Interaction of Intrinsic Dynamics and Network Topology in Determining Network Burst Synchrony

    PubMed Central

    Gaiteri, Chris; Rubin, Jonathan E.

    2011-01-01

    The pre-Bötzinger complex (pre-BötC), within the mammalian respiratory brainstem, represents an ideal system for investigating the synchronization properties of complex neuronal circuits via the interaction of cell-type heterogeneity and network connectivity. In isolation, individual respiratory neurons from the pre-BötC may be tonically active, rhythmically bursting, or quiescent. Despite this intrinsic heterogeneity, coupled networks of pre-BötC neurons en bloc engage in synchronized bursting that can drive inspiratory motor neuron activation. The region's connection topology has been recently characterized and features dense clusters of cells with occasional connections between clusters. We investigate how the dynamics of individual neurons (quiescent/bursting/tonic) and the betweenness centrality of neurons’ positions within the network connectivity graph interact to govern network burst synchrony, by simulating heterogeneous networks of computational model pre-BötC neurons. Furthermore, we compare the prevalence and synchrony of bursting across networks constructed with a variety of connection topologies, analyzing the same collection of heterogeneous neurons in small-world, scale-free, random, and regularly structured networks. We find that several measures of network burst synchronization are determined by interactions of network topology with the intrinsic dynamics of neurons at central network positions and by the strengths of synaptic connections between neurons. Surprisingly, despite the functional role of synchronized bursting within the pre-BötC, we find that synchronized network bursting is generally weakest when we use its specific connection topology, which leads to synchrony within clusters but poor coordination across clusters. Overall, our results highlight the relevance of interactions between topology and intrinsic dynamics in shaping the activity of networks and the concerted effects of connectivity patterns and dynamic heterogeneities

  8. The interaction of intrinsic dynamics and network topology in determining network burst synchrony.

    PubMed

    Gaiteri, Chris; Rubin, Jonathan E

    2011-01-01

    The pre-Bötzinger complex (pre-BötC), within the mammalian respiratory brainstem, represents an ideal system for investigating the synchronization properties of complex neuronal circuits via the interaction of cell-type heterogeneity and network connectivity. In isolation, individual respiratory neurons from the pre-BötC may be tonically active, rhythmically bursting, or quiescent. Despite this intrinsic heterogeneity, coupled networks of pre-BötC neurons en bloc engage in synchronized bursting that can drive inspiratory motor neuron activation. The region's connection topology has been recently characterized and features dense clusters of cells with occasional connections between clusters. We investigate how the dynamics of individual neurons (quiescent/bursting/tonic) and the betweenness centrality of neurons' positions within the network connectivity graph interact to govern network burst synchrony, by simulating heterogeneous networks of computational model pre-BötC neurons. Furthermore, we compare the prevalence and synchrony of bursting across networks constructed with a variety of connection topologies, analyzing the same collection of heterogeneous neurons in small-world, scale-free, random, and regularly structured networks. We find that several measures of network burst synchronization are determined by interactions of network topology with the intrinsic dynamics of neurons at central network positions and by the strengths of synaptic connections between neurons. Surprisingly, despite the functional role of synchronized bursting within the pre-BötC, we find that synchronized network bursting is generally weakest when we use its specific connection topology, which leads to synchrony within clusters but poor coordination across clusters. Overall, our results highlight the relevance of interactions between topology and intrinsic dynamics in shaping the activity of networks and the concerted effects of connectivity patterns and dynamic heterogeneities.

  9. Determinants of Microvascular Network Topologies in Implanted Neovasculatures

    PubMed Central

    Chang, Carlos C.; Krishnan, Laxminarayanan; Nunes, Sara S.; Church, Kenneth H.; Edgar, Lowell T.; Boland, Eugene D.; Weiss, Jeffery A.; Williams, Stuart K.; Hoying, James B.

    2011-01-01

    Objectives During neovascularization, the end result is a new functional microcirculation comprised of a network of mature microvessels with specific topologies. While much is known concerning the mechanisms underlying the initiation of angiogenesis, it remains unclear how the final architecture of microcirculatory beds is regulated. To begin to address this, we determined the impact of angiogenic neovessel pre-patterning on the final microvascular network topology using an implant model of implant neovascularization. Methods and Results To test this, we used 3-D direct-write bioprinting or physical constraints in a manner permitting post-angiogenesis vascular remodeling and adaptation to pattern angiogenic microvascular precursors (neovessels formed from isolated microvessel segments) in 3-dimensional collagen gels prior to implantation and subsequent network formation. Neovasculatures pre-patterned into parallel arrays formed functional networks following 4 weeks post-implantation, but lost the pre-patterned architecture. However, maintenance of uniaxial physical constraints during post-angiogenesis remodeling of the implanted neovasculatures produced networks with aligned microvessels as well as an altered proportional distribution of arterioles, capillaries and venules. Conclusions Here we show that network topology resulting from implanted microvessel precursors is independent from pre-patterning of precursors but can be influenced by a patterning stimulus involving tissue deformation during post-angiogenesis remodeling and maturation. PMID:22053070

  10. Inline hyperspectral thickness determination of thin films using neural networks

    NASA Astrophysics Data System (ADS)

    Tremmel, Anton J.; Weiss, Roman; Schardt, Michael; Koch, Alexander W.

    2017-04-01

    Combining reflectometry and hyperspectral imaging allows mapping of thin film thickness. Therefore, layer thickness is calculated by comparing a dataset of simulated spectra with the measured data. Utilizing the maximum frame rate of the hyperspectral imager, the pixel wise spectra comparing procedure cannot be performed using a standard computer due to the processing load. In this work, a method using neural networks for calculating layer thickness is presented. By the use of the nonlinear equation as result of a trained neural network, thickness data can be determined with a measurement rate matching the maximum frame rate of the hyperspectral imager.

  11. Laser tracker error determination using a network measurement

    NASA Astrophysics Data System (ADS)

    Hughes, Ben; Forbes, Alistair; Lewis, Andrew; Sun, Wenjuan; Veal, Dan; Nasr, Karim

    2011-04-01

    We report on a fast, easily implemented method to determine all the geometrical alignment errors of a laser tracker, to high precision. The technique requires no specialist equipment and can be performed in less than an hour. The technique is based on the determination of parameters of a geometric model of the laser tracker, using measurements of a set of fixed target locations, from multiple locations of the tracker. After fitting of the model parameters to the observed data, the model can be used to perform error correction of the raw laser tracker data or to derive correction parameters in the format of the tracker manufacturer's internal error map. In addition to determination of the model parameters, the method also determines the uncertainties and correlations associated with the parameters. We have tested the technique on a commercial laser tracker in the following way. We disabled the tracker's internal error compensation, and used a five-position, fifteen-target network to estimate all the geometric errors of the instrument. Using the error map generated from this network test, the tracker was able to pass a full performance validation test, conducted according to a recognized specification standard (ASME B89.4.19-2006). We conclude that the error correction determined from the network test is as effective as the manufacturer's own error correction methodologies.

  12. Leveraging disjoint communities for detecting overlapping community structure

    NASA Astrophysics Data System (ADS)

    Chakraborty, Tanmoy

    2015-05-01

    Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overlapping communities from the network. In this paper, we present PVOC (Permanence based Vertex-replication algorithm for Overlapping Community detection), a two-stage framework to detect overlapping community structure. We build on a novel observation that non-overlapping community structure detected by a standard disjoint community detection algorithm from a network has high resemblance with its actual overlapping community structure, except the overlapping part. Based on this observation, we posit that there is perhaps no need of building yet another overlapping community finding algorithm; but one can efficiently manipulate the output of any existing disjoint community finding algorithm to obtain the required overlapping structure. We propose a new post-processing technique that by combining with any existing disjoint community detection algorithm, can suitably process each vertex using a new vertex-based metric, called permanence, and thereby finds out overlapping candidates with their community memberships. Experimental results on both synthetic and large real-world networks show that PVOC significantly outperforms six state-of-the-art overlapping community detection algorithms in terms of high similarity of the output with the ground-truth structure. Thus our framework not only finds meaningful overlapping communities from the network, but also allows us to put an end to the constant effort of building yet another overlapping community detection algorithm.

  13. Clustering determines the dynamics of complex contagions in multiplex networks

    NASA Astrophysics Data System (ADS)

    Zhuang, Yong; Arenas, Alex; Yaǧan, Osman

    2017-01-01

    We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.

  14. Steganalysis of overlapping images

    NASA Astrophysics Data System (ADS)

    Whitaker, James M.; Ker, Andrew D.

    2015-03-01

    We examine whether steganographic images can be detected more reliably when there exist other images, taken with the same camera under the same conditions, of the same scene. We argue that such a circumstance is realistic and likely in practice. In `laboratory conditions' mimicking circumstances favourable to the analyst, and with a custom set of digital images which capture the same scenes with controlled amounts of overlap, we use an overlapping reference image to calibrate steganographic features of the image under analysis. Experimental results show that the analysed image can be classified as cover or stego with much greater reliability than traditional steganalysis not exploiting overlapping content, and the improvement in reliability depends on the amount of overlap. These results are curious because two different photographs of exactly the same scene, taken only a few seconds apart with a fixed camera and settings, typically have steganographic features that differ by considerably more than a cover and stego image.

  15. Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions

    SciTech Connect

    MacArthur, Stewart; Li, Xiao-Yong; Li, Jingyi; Brown, James B.; Chu, Hou Cheng; Zeng, Lucy; Grondona, Brandi P.; Hechmer, Aaron; Simirenko, Lisa; Keranen, Soile V.E.; Knowles, David W.; Stapleton, Mark; Bickel, Peter; Biggin, Mark D.; Eisen, Michael B.

    2009-05-15

    BACKGROUND: We previously established that six sequence-specific transcription factors that initiate anterior/posterior patterning in Drosophila bind to overlapping sets of thousands of genomic regions in blastoderm embryos. While regions bound at high levels include known and probable functional targets, more poorly bound regions are preferentially associated with housekeeping genes and/or genes not transcribed in the blastoderm, and are frequently found in protein coding sequences or in less conserved non-coding DNA, suggesting that many are likely non-functional. RESULTS: Here we show that an additional 15 transcription factors that regulate other aspects of embryo patterning show a similar quantitative continuum of function and binding to thousands of genomic regions in vivo. Collectively, the 21 regulators show a surprisingly high overlap in the regions they bind given that they belong to 11 DNA binding domain families, specify distinct developmental fates, and can act via different cis-regulatory modules. We demonstrate, however, that quantitative differences in relative levels of binding to shared targets correlate with the known biological and transcriptional regulatory specificities of these factors. CONCLUSIONS: It is likely that the overlap in binding of biochemically and functionally unrelated transcription factors arises from the high concentrations of these proteins in nuclei, which, coupled with their broad DNA binding specificities, directs them to regions of open chromatin. We suggest that most animal transcription factors will be found to show a similar broad overlapping pattern of binding in vivo, with specificity achieved by modulating the amount, rather than the identity, of bound factor.

  16. Illusion induced overlapped optics.

    PubMed

    Zang, XiaoFei; Shi, Cheng; Li, Zhou; Chen, Lin; Cai, Bin; Zhu, YiMing; Zhu, HaiBin

    2014-01-13

    The traditional transformation-based cloak seems like it can only hide objects by bending the incident electromagnetic waves around the hidden region. In this paper, we prove that invisible cloaks can be applied to realize the overlapped optics. No matter how many in-phase point sources are located in the hidden region, all of them can overlap each other (this can be considered as illusion effect), leading to the perfect optical interference effect. In addition, a singular parameter-independent cloak is also designed to obtain quasi-overlapped optics. Even more amazing of overlapped optics is that if N identical separated in-phase point sources covered with the illusion media, the total power outside the transformation region is N2I0 (not NI0) (I0 is the power of just one point source, and N is the number point sources), which seems violating the law of conservation of energy. A theoretical model based on interference effect is proposed to interpret the total power of these two kinds of overlapped optics effects. Our investigation may have wide applications in high power coherent laser beams, and multiple laser diodes, and so on.

  17. Physical determinants of vascular network remodeling during tumor growth.

    PubMed

    Welter, M; Rieger, H

    2010-10-01

    The process in which a growing tumor transforms a hierarchically organized arterio-venous blood vessel network into a tumor specific vasculature is analyzed with a theoretical model. The physical determinants of this remodeling involve the morphological and hydrodynamic properties of the initial network, generation of new vessels (sprouting angiogenesis), vessel dilation (circumferential growth), vessel regression, tumor cell proliferation and death, and the interdependence of these processes via spatio-temporal changes of blood flow parameters, oxygen/nutrient supply and growth factor concentration fields. The emerging tumor vasculature is non-hierarchical, compartmentalized into well-characterized zones, displays a complex geometry with necrotic zones and "hot spots" of increased vascular density and blood flow of varying size, and transports drug injections efficiently. Implications for current theoretical views on tumor-induced angiogenesis are discussed.

  18. A Boolean network model of human gonadal sex determination.

    PubMed

    Ríos, Osiris; Frias, Sara; Rodríguez, Alfredo; Kofman, Susana; Merchant, Horacio; Torres, Leda; Mendoza, Luis

    2015-11-16

    Gonadal sex determination (GSD) in humans is a complex biological process that takes place in early stages of embryonic development when the bipotential gonadal primordium (BGP) differentiates towards testes or ovaries. This decision is directed by one of two distinct pathways embedded in a GSD network activated in a population of coelomic epithelial cells, the Sertoli progenitor cells (SPC) and the granulosa progenitor cells (GPC). In males, the pathway is activated when the Sex-Determining Region Y (SRY) gene starts to be expressed, whereas in females the WNT4/ β-catenin pathway promotes the differentiation of the GPCs towards ovaries. The interactions and dynamics of the elements that constitute the GSD network are poorly understood, thus our group is interested in inferring the general architecture of this network as well as modeling the dynamic behavior of a set of genes associated to this process under wild-type and mutant conditions. We reconstructed the regulatory network of GSD with a set of genes directly associated with the process of differentiation from SPC and GPC towards Sertoli and granulosa cells, respectively. These genes are experimentally well-characterized and the effects of their deficiency have been clinically reported. We modeled this GSD network as a synchronous Boolean network model (BNM) and characterized its attractors under wild-type and mutant conditions. Three attractors with a clear biological meaning were found; one of them corresponding to the currently known gene expression pattern of Sertoli cells, the second correlating to the granulosa cells and, the third resembling a disgenetic gonad. The BNM of GSD that we present summarizes the experimental data on the pathways for Sertoli and granulosa establishment and sheds light on the overall behavior of a population of cells that differentiate within the developing gonad. With this model we propose a set of regulatory interactions needed to activate either the SRY or the WNT4/

  19. Optical neural network system for pose determination of spinning satellites

    NASA Astrophysics Data System (ADS)

    Lee, Andrew J.; Casasent, David P.

    1990-09-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning sateffites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time and hence the paths of object (sateffite) parts. The path traced out by a given part or region is approximately elliptical in image space and the position shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite and the effiptical path of a part in image space the 3-D pose of the satellite is determined. Digital simulation results using this algorithm are presented for various sateffite poses and lighting conditions. 1

  20. Optical neural network system for pose determination of spinning satellites

    NASA Technical Reports Server (NTRS)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  1. Optical neural network system for pose determination of spinning satellites

    NASA Technical Reports Server (NTRS)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  2. Overlap among Environmental Databases.

    ERIC Educational Resources Information Center

    Miller, Betty

    1981-01-01

    Describes the methodology and results of a study comparing the overlap of Enviroline, Pollution, and the Environmental Periodicals Bibliography files through searches on acid rain, asbestos and water, diesel, glass recycling, Lake Erie, Concorde, reverse osmosis wastewater treatment cost, and Calspan. Nine tables are provided. (RBF)

  3. Overlap among Environmental Databases.

    ERIC Educational Resources Information Center

    Miller, Betty

    1981-01-01

    Describes the methodology and results of a study comparing the overlap of Enviroline, Pollution, and the Environmental Periodicals Bibliography files through searches on acid rain, asbestos and water, diesel, glass recycling, Lake Erie, Concorde, reverse osmosis wastewater treatment cost, and Calspan. Nine tables are provided. (RBF)

  4. Distal tibiofibular radiological overlap

    PubMed Central

    Sowman, B.; Radic, R.; Kuster, M.; Yates, P.; Breidiel, B.; Karamfilef, S.

    2012-01-01

    Objectives Overlap between the distal tibia and fibula has always been quoted to be positive. If the value is not positive then an injury to the syndesmosis is thought to exist. Our null hypothesis is that it is a normal variant in the adult population. Methods We looked at axial CT scans of the ankle in 325 patients for the presence of overlap between the distal tibia and fibula. Where we thought this was possible we reconstructed the images to represent a plain film radiograph which we were able to rotate and view in multiple planes to confirm the assessment. Results The scans were taken for reasons other than pathology of the ankle. We found there was no overlap in four patients. These patients were then questioned about previous injury, trauma, surgery or pain, in order to exclude underlying pathology. Conclusion We concluded that no overlap between the tibia and fibula may exist in the population, albeit in a very small proportion. PMID:23610666

  5. Probing genetic overlap among complex human phenotypes.

    PubMed

    Rzhetsky, Andrey; Wajngurt, David; Park, Naeun; Zheng, Tian

    2007-07-10

    Geneticists and epidemiologists often observe that certain hereditary disorders cooccur in individual patients significantly more (or significantly less) frequently than expected, suggesting there is a genetic variation that predisposes its bearer to multiple disorders, or that protects against some disorders while predisposing to others. We suggest that, by using a large number of phenotypic observations about multiple disorders and an appropriate statistical model, we can infer genetic overlaps between phenotypes. Our proof-of-concept analysis of 1.5 million patient records and 161 disorders indicates that disease phenotypes form a highly connected network of strong pairwise correlations. Our modeling approach, under appropriate assumptions, allows us to estimate from these correlations the size of putative genetic overlaps. For example, we suggest that autism, bipolar disorder, and schizophrenia share significant genetic overlaps. Our disease network hypothesis can be immediately exploited in the design of genetic mapping approaches that involve joint linkage or association analyses of multiple seemingly disparate phenotypes.

  6. An Integrated Centroid Finding and Particle Overlap Decomposition Algorithm for Stereo Imaging Velocimetry

    NASA Technical Reports Server (NTRS)

    McDowell, Mark

    2004-01-01

    An integrated algorithm for decomposing overlapping particle images (multi-particle objects) along with determining each object s constituent particle centroid(s) has been developed using image analysis techniques. The centroid finding algorithm uses a modified eight-direction search method for finding the perimeter of any enclosed object. The centroid is calculated using the intensity-weighted center of mass of the object. The overlap decomposition algorithm further analyzes the object data and breaks it down into its constituent particle centroid(s). This is accomplished with an artificial neural network, feature based technique and provides an efficient way of decomposing overlapping particles. Combining the centroid finding and overlap decomposition routines into a single algorithm allows us to accurately predict the error associated with finding the centroid(s) of particles in our experiments. This algorithm has been tested using real, simulated, and synthetic data and the results are presented and discussed.

  7. Determining Locations by Use of Networks of Passive Beacons

    NASA Technical Reports Server (NTRS)

    Okino, Clayton; Gray, Andrew; Jennings, Esther

    2009-01-01

    Networks of passive radio beacons spanning moderate-sized terrain areas have been proposed to aid navigation of small robotic aircraft that would be used to explore Saturn s moon Titan. Such networks could also be used on Earth to aid navigation of robotic aircraft, land vehicles, or vessels engaged in exploration or reconnaissance in situations or locations (e.g., underwater locations) in which Global Positioning System (GPS) signals are unreliable or unavailable. Prior to use, it would be necessary to pre-position the beacons at known locations that would be determined by use of one or more precise independent global navigation system(s). Thereafter, while navigating over the area spanned by a given network of passive beacons, an exploratory robot would use the beacons to determine its position precisely relative to the known beacon positions (see figure). If it were necessary for the robot to explore multiple, separated terrain areas spanned by different networks of beacons, the robot could use a long-haul, relatively coarse global navigation system for the lower-precision position determination needed during transit between such areas. The proposed method of precise determination of position of an exploratory robot relative to the positions of passive radio beacons is based partly on the principles of radar and partly on the principles of radio-frequency identification (RFID) tags. The robot would transmit radar-like signals that would be modified and reflected by the passive beacons. The distance to each beacon would be determined from the roundtrip propagation time and/or round-trip phase shift of the signal returning from that beacon. Signals returned from different beacons could be distinguished by means of their RFID characteristics. Alternatively or in addition, the antenna of each beacon could be designed to radiate in a unique pattern that could be identified by the navigation system. Also, alternatively or in addition, sets of identical beacons could

  8. Overlap and Differences in Brain Networks Underlying the Processing of Complex Sentence Structures in Second Language Users Compared with Native Speakers.

    PubMed

    Weber, Kirsten; Luther, Lisa; Indefrey, Peter; Hagoort, Peter

    2016-05-01

    When we learn a second language later in life, do we integrate it with the established neural networks in place for the first language or is at least a partially new network recruited? While there is evidence that simple grammatical structures in a second language share a system with the native language, the story becomes more multifaceted for complex sentence structures. In this study, we investigated the underlying brain networks in native speakers compared with proficient second language users while processing complex sentences. As hypothesized, complex structures were processed by the same large-scale inferior frontal and middle temporal language networks of the brain in the second language, as seen in native speakers. These effects were seen both in activations and task-related connectivity patterns. Furthermore, the second language users showed increased task-related connectivity from inferior frontal to inferior parietal regions of the brain, regions related to attention and cognitive control, suggesting less automatic processing for these structures in a second language.

  9. The Plate Overlap Technique.

    DTIC Science & Technology

    1978-07-31

    INTRODUCTION 1 II. NOTATION 2 III. THE GNOMONIC PROJECTION 4 IV . THE PLATE OVERLAP TECHNIQUE 6 A. MOTIVATION 6 B. FORNULATION 9 C. ON STATISTICAL RIGOR 14 D...and new hardware. Since this aim was clearly recognized long ago, wherever possible in earlier documents or software development flexibility was...reader should see 1, 2, and 3. The procedures one should use to update stellar positions are discussed in 4 with applica- tions to the SAOC in 5. Non

  10. Genetically determined phenotype covariation networks control bone strength.

    PubMed

    Jepsen, Karl J; Courtland, Hayden-William; Nadeau, Joseph H

    2010-07-01

    To identify genes affecting bone strength, we studied how genetic variants regulate components of a phenotypic covariation network that was previously shown to accurately characterize the compensatory trait interactions involved in functional adaptation during growth. Quantitative trait loci (QTLs) regulating femoral robustness, morphologic compensation, and mineralization (tissue quality) were mapped at three ages during growth using AXB/BXA Recombinant Inbred (RI) mouse strains and adult B6-i(A) Chromosome Substitution Strains (CSS). QTLs for robustness were identified on chromosomes 8, 12, 18, and 19 and confirmed at all three ages, indicating that genetic variants established robustness postnatally without further modification. A QTL for morphologic compensation, which was measured as the relationship between cortical area and body weight, was identified on chromosome 8. This QTL limited the amount of bone formed during growth and thus acted as a setpoint for diaphyseal bone mass. Additional QTLs were identified from the CSS analysis. QTLs for robustness and morphologic compensation regulated bone structure independently (ie, in a nonpleiotropic manner), indicating that each trait may be targeted separately to individualize treatments aiming to improve strength. Multiple regression analyses showed that variation in morphologic compensation and tissue quality, not bone size, determined femoral strength relative to body weight. Thus an individual inheriting slender bones will not necessarily inherit weak bones unless the individual also inherits a gene that impairs compensation. This systems genetic analysis showed that genetically determined phenotype covariation networks control bone strength, suggesting that incorporating functional adaptation into genetic analyses will advance our understanding of the genetic basis of bone strength.

  11. Communication issues in determining departmental local area networks requirements

    NASA Astrophysics Data System (ADS)

    Dabipi, I. K.; Donaldson, A.; Anderson, James A.

    1995-07-01

    One of the major issues when configuring networks is about the way in which the decision on what kind of a network to install is made. The Electrical Engineering Department at Southern University has recently gone through this process. This paper addresses the related network design issues as a class project simulation of the different network designs. The simulation details the network simulation and the network connectivity issues. A comparison of the various designs is presented and the reason for the choice of the final configuration is also given.

  12. Determination of vegetation phenology across the National Ecological Observatory Network

    NASA Astrophysics Data System (ADS)

    Musinsky, J.; Goulden, T.

    2016-12-01

    The National Ecological Observatory Network (NEON) airborne observation platform (AOP) is collecting co-registered high-resolution hyperspectral imagery, discrete and waveform lidar, and high-resolution digital photography across 48 terrestrial and 32 aquatic sites throughout the continental United States, Puerto Rico, Alaska and Hawaii on an annual basis over the next 30 years. These remote sensing data, made freely available to the public, enable researchers to characterize vegetation structure and canopy biochemistry at multiple scales and contribute to our understanding of ecosystem forcings and responses as represented by vegetation states and processes. In an effort to minimize the impact of inter-annual phenological variability on higher level data products obtained from airborne surveys from multiple years, AOP flight campaigns are scheduled so that data acquisition occurs during the period of forecasted peak greenness at each site, defined as the range of dates where mean MODIS NDVI values for the survey area are greater than 90% of the site maximum. As part of baseline scheduling for AOP flight operations, analyses of historical vegetation phenology were performed for each terrestrial and aquatic site in the NEON network to identify the dates of acceptable airborne remote sensing data acquisition. 15-year time series (2001-2015) of 16-day composite MODIS NDVI and EVI data from Oak Ridge National Laboratory were compiled for each site, cropped to the dimensions of the airborne survey boundary (ranging from 100-720 km2) and analyzed to determine the dates of >90% mean peak greenness, the earliest onset dates of peak greenness and the average annual deviation from mean onset of peak greenness. In situ phenophase observations acquired from select NEON sites were then used to determine the accuracy of the MODIS peak greenness estimates. This presentation explores how historical phenology observations are being used throughout the NEON network to guide both

  13. High-Throughput Chiral LC-MS/MS Method Using Overlapping Injection Mode for the Determination of Pantoprazole Enantiomers in Human Plasma with Application to Pharmacokinetic Study.

    PubMed

    Li, Shengni; Jiang, Huafang; Wang, Yiya; Liu, Yinli; Shen, Xiaohang; Liang, Wenzhong; Hong, Zhanying

    2016-07-01

    A sensitive and high-throughput chiral liquid chromatography-tandem mass spectrometry method was developed and validated for the quantification of R-pantoprazole and S-pantoprazole in human plasma. Sample extraction was carried out by using ethyl acetate liquid-liquid extraction in 96-well plate format. The separation of pantoprazole enantiomers was performed on a CHIRALCEL OJ-RH column and an overlapping injection mode was used to achieve a run time of 5.0 min/sample. The mobile phase consisted of 1) 10 mM ammonium acetate in methanol: acetonitrile (1:1, v/v) and 2) 20 mM ammonium acetate in water. Isocratic elution was used with flow rate at 500 μL/min. The enantiomers were quantified on a triple-quadrupole mass spectrometer under multiple reaction monitoring (MRM) mode with m/z 382.1/230.0 for pantoprazole and m/z 388.4/230.1 for pantoprazole-d7. Linearity from 20.0 to 5000 ng/mL was established for each enantiomer (r(2)  > 0.99). Extraction recovery ranged from 91.7% to 96.4% for R-pantoprazole and from 92.5% to 96.5% for S-pantoprazole and the IS-normalized matrix factor was 0.98 to 1.07 for R-pantoprazole and S-pantoprazole, respectively. The method was demonstrated with acceptable accuracy, precision, selectivity, and stability and the method was applied to support a pharmacokinetic study of a phase I clinical trial of racemic pantoprazole in healthy Chinese subjects. Chirality 28:569-575, 2016. © 2016 Wiley Periodicals, Inc.

  14. Determinants of Communication Network Involvement: Connectedness and Integration.

    ERIC Educational Resources Information Center

    Monge, Peter R.; And Others

    1983-01-01

    Developed structural equation models of involvement in communication networks in organizations for communication network connectedness and for network integration. A questionnaire was administered to members of a naval training facility (N=125). Models showed acceptable goodness-of-fit for the connectedness model and excellent goodness-of-fit for…

  15. Optimal Parameter Determination for Tritiated Water Storage in Polyacrylic Networks

    SciTech Connect

    Postolache, C.; Matei, Lidia; Georgescu, Rodica; Ionita, Gh.

    2005-07-15

    Due to the remarkable capacity of water retaining, croslinked polyacrylic acids (PAA) represent an interesting alternative for tritiated water trapping. The study was developed on radiolytical processes in PAA:HTO systems derivated from irradiation of polymeric network by disintegration of tritium atoms from HTO. The aim of these studies is the identification of polymeric structures and optimal storage conditions.Sol and gel fractions were determinated by radiometrical methods using PAA labeled with 14-C at carboxylic groups and T at main chains of the polymer. Simulation of radiolytical processes was realized using {gamma} radiation field emitted by a irradiation source of 60-Co which ensures a maximum of absorbed dose rate of 3 kGy/h. Self-radiolytical effects were investigated using labeled PAA in HTO with great radioactive concentration (37-185 GBq/mL). The experiment suggests as optimum for HTO storage as tritium liquid wastes a 1:30 PAA:HTO swelling degree at 18.5-37 MBqL. HTO radioactive concentration.RES studies of radiolytical processes were also realized on dry polyacrylic acid (PAA) and polyacrylic based hydrogels irradiated and determined at 77 K. In the study we observed the effect of swelling capacity of hydrogel o the formation of free radicals.

  16. Metabolic network architecture and carbon source determine metabolite production costs.

    PubMed

    Waschina, Silvio; D'Souza, Glen; Kost, Christian; Kaleta, Christoph

    2016-06-01

    Metabolism is essential to organismal life, because it provides energy and building block metabolites. Even though it is known that the biosynthesis of metabolites consumes a significant proportion of the resources available to a cell, the factors that determine their production costs remain less well understood. In this context, it is especially unclear how the nutritional environment affects the costs of metabolite production. Here, we use the amino acid metabolism of Escherichia coli as a model to show that the point at which a carbon source enters central metabolic pathways is a major determinant of individual metabolite production costs. Growth rates of auxotrophic genotypes, which in the presence of the required amino acid save biosynthetic costs, were compared to the growth rates that prototrophic cells achieved under the same conditions. The experimental results showed a strong concordance with computationally estimated biosynthetic costs, which allowed us, for the first time, to systematically quantify carbon source-dependent metabolite production costs. Thus, we demonstrate that the nutritional environment in combination with network architecture is an important but hitherto underestimated factor influencing biosynthetic costs and thus microbial growth. Our observations are highly relevant for the optimization of biotechnological processes as well as for understanding the ecology of microorganisms in their natural environments. © 2016 Federation of European Biochemical Societies.

  17. Segmentation of fault networks determined from spatial clustering of earthquakes

    NASA Astrophysics Data System (ADS)

    Ouillon, G.; Sornette, D.

    2011-02-01

    We present a new method of data clustering applied to earthquake catalogs, with the goal of reconstructing the seismically active part of fault networks. We first use an original method to separate clustered events from uncorrelated seismicity using the distribution of volumes of tetrahedra defined by closest neighbor events in the original and randomized seismic catalogs. The spatial disorder of the complex geometry of fault networks is then taken into account by defining faults as probabilistic anisotropic kernels. The structure of those kernels is motivated by properties of discontinuous tectonic deformation and by previous empirical observations of the geometry of faults and of earthquake clusters at many spatial and temporal scales. Combining this a priori knowledge with information theoretical arguments, we propose the Gaussian mixture approach implemented in an expectation maximization (EM) procedure. A cross-validation scheme is then used that allows the determination of the number of kernels which provides an optimal data clustering of the catalog. This three-step approach is applied to a high-quality catalog of relocated seismicity following the 1986 Mount Lewis (Ml = 5.7) event in California. It reveals that events cluster along planar patches of about 2 km2, i.e., comparable to the size of the main event. The finite thickness of those clusters (about 290 m) suggests that events do not occur on well-defined and smooth Euclidean fault core surfaces but rather that there exist a deforming area and a damage zone surrounding faults which may be seismically active at depth. Finally, we propose a connection between our methodology and multiscale spatial analysis, based on the derivation of a spatial fractal dimension of about 1.8 for the set of hypocenters in the Mount Lewis area, consistent with recent observations on relocated catalogs.

  18. Determination of the CMSSM parameters using neural networks

    NASA Astrophysics Data System (ADS)

    Bornhauser, Nicki; Drees, Manuel

    2013-10-01

    In most (weakly interacting) extensions of the Standard Model the relation mapping the parameter values onto experimentally measurable quantities can be computed (with some uncertainties), but the inverse relation is usually not known. In this paper we demonstrate the ability of artificial neural networks to find this unknown relation, by determining the unknown parameters of the constrained minimal supersymmetric extension of the Standard Model from quantities that can be measured at the LHC. We expect that the method works also for many other new physics models. We compare its performance with the results of a straightforward χ2 minimization. We simulate LHC signals at a center of mass energy of 14 TeV at the hadron level. In this proof-of-concept study we do not explicitly simulate Standard Model backgrounds, but apply cuts that have been shown to enhance the signal-to-background ratio. We analyze four different benchmark points that lie just beyond current lower limits on superparticle masses, each of which leads to around 1000 events after cuts for an integrated luminosity of 10fb-1. We use up to 84 observables, most of which are counting observables; we do not attempt to directly reconstruct (differences of) masses from kinematic edges or kinks of distributions. We nevertheless find that m0 and m1/2 can be determined reliably, with errors as small as 1% in some cases. With 500fb-1 of data tan⁡β as well as A0 can also be determined quite accurately. For comparable computational effort the χ2 minimization yielded much worse results.

  19. Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity.

    PubMed

    Sahasranamam, Ajith; Vlachos, Ioannis; Aertsen, Ad; Kumar, Arvind

    2016-05-23

    Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.

  20. Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

    PubMed Central

    Böck, Matthias; Ogishima, Soichi; Tanaka, Hiroshi; Kramer, Stefan; Kaderali, Lars

    2012-01-01

    Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often controlled by a small number of hub genes, while most other genes have only limited influence on the network's dynamic. We model gene regulation using a Bayesian network with discrete, Boolean nodes. A hierarchical prior is employed to identify hub genes. The first layer of the prior is used to regularize weights on edges emanating from one specific node. A second prior on hyperparameters controls the magnitude of the former regularization for different nodes. The net effect is that central nodes tend to form in reconstructed networks. Network reconstruction is then performed by maximization of or sampling from the posterior distribution. We evaluate our approach on simulated and real experimental data, indicating that we can reconstruct main regulatory interactions from the data. We furthermore compare our approach to other state-of-the art methods, showing superior performance in identifying hubs. Using a large publicly available dataset of over 800 cell cycle regulated genes, we are able to identify several main hub genes. Our method may thus provide a valuable tool to identify interesting candidate genes for further study. Furthermore, the approach presented may stimulate further developments in regularization methods for network reconstruction from data. PMID:22570688

  1. Securely measuring the overlap between private datasets with cryptosets.

    PubMed

    Swamidass, S Joshua; Matlock, Matthew; Rozenblit, Leon

    2015-01-01

    Many scientific questions are best approached by sharing data--collected by different groups or across large collaborative networks--into a combined analysis. Unfortunately, some of the most interesting and powerful datasets--like health records, genetic data, and drug discovery data--cannot be freely shared because they contain sensitive information. In many situations, knowing if private datasets overlap determines if it is worthwhile to navigate the institutional, ethical, and legal barriers that govern access to sensitive, private data. We report the first method of publicly measuring the overlap between private datasets that is secure under a malicious model without relying on private protocols or message passing. This method uses a publicly shareable summary of a dataset's contents, its cryptoset, to estimate its overlap with other datasets. Cryptosets approach "information-theoretic" security, the strongest type of security possible in cryptography, which is not even crackable with infinite computing power. We empirically and theoretically assess both the accuracy of these estimates and the security of the approach, demonstrating that cryptosets are informative, with a stable accuracy, and secure.

  2. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health

    PubMed Central

    Wei, Zhong; Yang, Tianjie; Friman, Ville-Petri; Xu, Yangchun; Shen, Qirong; Jousset, Alexandre

    2015-01-01

    Host-associated bacterial communities can function as an important line of defence against pathogens in animals and plants. Empirical evidence and theoretical predictions suggest that species-rich communities are more resistant to pathogen invasions. Yet, the underlying mechanisms are unclear. Here, we experimentally test how the underlying resource competition networks of resident bacterial communities affect invasion resistance to the plant pathogen Ralstonia solanacearum in microcosms and in tomato plant rhizosphere. We find that bipartite resource competition networks are better predictors of invasion resistance compared with resident community diversity. Specifically, communities with a combination of stabilizing configurations (low nestedness and high connectance), and a clear niche overlap with the pathogen, reduce pathogen invasion success, constrain pathogen growth within invaded communities and have lower levels of diseased plants in greenhouse experiments. Bacterial resource competition network characteristics can thus be important in explaining positive diversity–invasion resistance relationships in bacterial rhizosphere communities. PMID:26400552

  3. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health.

    PubMed

    Wei, Zhong; Yang, Tianjie; Friman, Ville-Petri; Xu, Yangchun; Shen, Qirong; Jousset, Alexandre

    2015-09-24

    Host-associated bacterial communities can function as an important line of defence against pathogens in animals and plants. Empirical evidence and theoretical predictions suggest that species-rich communities are more resistant to pathogen invasions. Yet, the underlying mechanisms are unclear. Here, we experimentally test how the underlying resource competition networks of resident bacterial communities affect invasion resistance to the plant pathogen Ralstonia solanacearum in microcosms and in tomato plant rhizosphere. We find that bipartite resource competition networks are better predictors of invasion resistance compared with resident community diversity. Specifically, communities with a combination of stabilizing configurations (low nestedness and high connectance), and a clear niche overlap with the pathogen, reduce pathogen invasion success, constrain pathogen growth within invaded communities and have lower levels of diseased plants in greenhouse experiments. Bacterial resource competition network characteristics can thus be important in explaining positive diversity-invasion resistance relationships in bacterial rhizosphere communities.

  4. 78 FR 1264 - CalAmp Wireless Networks Corporation, Waseca, MN; Notice of Negative Determination Regarding...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-08

    ... Employment and Training Administration CalAmp Wireless Networks Corporation, Waseca, MN; Notice of Negative... workers of the subject firm (TA-W-80,399A; CalAmp Wireless Networks Corporation, Waseca, Minnesota... Wireless Networks Corporation, Waseca, Minnesota to apply for TAA, the Department determines that an...

  5. Generating Composite Overlapping Grids on CAD Geometries

    SciTech Connect

    Henshaw, W.D.

    2002-02-07

    We describe some algorithms and tools that have been developed to generate composite overlapping grids on geometries that have been defined with computer aided design (CAD) programs. This process consists of five main steps. Starting from a description of the surfaces defining the computational domain we (1) correct errors in the CAD representation, (2) determine topology of the patched-surface, (3) build a global triangulation of the surface, (4) construct structured surface and volume grids using hyperbolic grid generation, and (5) generate the overlapping grid by determining the holes and the interpolation points. The overlapping grid generator which is used for the final step also supports the rapid generation of grids for block-structured adaptive mesh refinement and for moving grids. These algorithms have been implemented as part of the Overture object-oriented framework.

  6. Development and validation of different methods manipulating zero order and first order spectra for determination of the partially overlapped mixture benazepril and amlodipine: A comparative study

    NASA Astrophysics Data System (ADS)

    Hemdan, A.

    2016-07-01

    Three simple, selective, and accurate spectrophotometric methods have been developed and then validated for the analysis of Benazepril (BENZ) and Amlodipine (AML) in bulk powder and pharmaceutical dosage form. The first method is the absorption factor (AF) for zero order and amplitude factor (P-F) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 238 nm or from their first order spectra at 253 nm. The second method is the constant multiplication coupled with constant subtraction (CM-CS) for zero order and successive derivative subtraction-constant multiplication (SDS-CM) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 240 nm and 238 nm, respectively, or from their first order spectra at 214 nm and 253 nm for Benazepril and Amlodipine respectively. The third method is the novel constant multiplication coupled with derivative zero crossing (CM-DZC) which is a stability indicating assay method for determination of Benazepril and Amlodipine in presence of the main degradation product of Benazepril which is Benazeprilate (BENZT). The three methods were validated as per the ICH guidelines and the standard curves were found to be linear in the range of 5-60 μg/mL for Benazepril and 5-30 for Amlodipine, with well accepted mean correlation coefficient for each analyte. The intra-day and inter-day precision and accuracy results were well within the acceptable limits.

  7. A study of selective spectrophotometric methods for simultaneous determination of Itopride hydrochloride and Rabeprazole sodium binary mixture: Resolving sever overlapping spectra.

    PubMed

    Mohamed, Heba M

    2015-02-05

    Itopride hydrochloride (IT) and Rabeprazole sodium (RB) are co-formulated together for the treatment of gastro-esophageal reflux disease. Three simple, specific and accurate spectrophotometric methods were applied and validated for simultaneous determination of Itopride hydrochloride (IT) and Rabeprazole sodium (RB) namely; constant center (CC), ratio difference (RD) and mean centering of ratio spectra (MCR) spectrophotometric methods. Linear correlations were obtained in range of 10-110μg/μL for Itopride hydrochloride and 4-44μg/mL for Rabeprazole sodium. No preliminary separation steps were required prior the analysis of the two drugs using the proposed methods. Specificity was investigated by analyzing the synthetic mixtures containing the two cited drugs and their capsules dosage form. The obtained results were statistically compared with those obtained by the reported method, no significant difference was obtained with respect to accuracy and precision. The three methods were validated in accordance with ICH guidelines and can be used for quality control laboratories for IT and RB. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Optimal Space Station solar array gimbal angle determination via radial basis function neural networks

    NASA Technical Reports Server (NTRS)

    Clancy, Daniel J.; Oezguener, Uemit; Graham, Ronald E.

    1994-01-01

    The potential for excessive plume impingement loads on Space Station Freedom solar arrays, caused by jet firings from an approaching Space Shuttle, is addressed. An artificial neural network is designed to determine commanded solar array beta gimbal angle for minimum plume loads. The commanded angle would be determined dynamically. The network design proposed involves radial basis functions as activation functions. Design, development, and simulation of this network design are discussed.

  9. Cellular and network mechanisms of genetically-determined absence seizures

    PubMed Central

    Pinault, Didier; O'Brien, Terence J.

    2005-01-01

    The absence epilepsies are characterized by recurrent episodes of loss of consciousness associated with generalized spike-and-wave discharges, with an abrupt onset and offset, in the thalamocortical system. In the absence of detailed neurophysiological studies in humans, many of the concepts regarding the pathophysiological basis of absence seizures are based on studies in animal models. Each of these models has its particular strengths and limitations, and the validity of findings from these models for the human condition cannot be assumed. Consequently, studies in different models have produced some conflicting findings and conclusions. A long-standing concept, based primarily from studies in vivo in cats and in vitro brain slices, is that these paroxysmal electrical events develop suddenly from sleep-related spindle oscillations. More specifically, it is proposed that the initial mechanisms that underlie absence-related spike-and-wave discharges are located in the thalamus, involving especially the thalamic reticular nucleus. By contrast, more recent studies in well-established, genetic models of absence epilepsy in rats demonstrate that spike-and-wave discharges originate in a cortical focus and develop from a wake-related natural corticothalamic sensorimotor rhythm. In this review we integrate recent findings showing that, in both the thalamus and the neocortex, genetically-determined, absence-related spike-and-wave discharges are the manifestation of hypersynchronized, cellular, rhythmic excitations and inhibitions that result from a combination of complex, intrinsic, synaptic mechanisms. Arguments are put forward supporting the hypothesis that layer VI corticothalamic neurons act as ‘drivers’ in the generation of spike-and-wave discharges in the somatosensory thalamocortical system that result in corticothalamic resonances particularly initially involving the thalamic reticular nucleus. However an important unresolved question is: what are the cellular

  10. Actin network architecture can determine myosin motor activity.

    PubMed

    Reymann, Anne-Cécile; Boujemaa-Paterski, Rajaa; Martiel, Jean-Louis; Guérin, Christophe; Cao, Wenxiang; Chin, Harvey F; De La Cruz, Enrique M; Théry, Manuel; Blanchoin, Laurent

    2012-06-08

    The organization of actin filaments into higher-ordered structures governs eukaryotic cell shape and movement. Global actin network size and architecture are maintained in a dynamic steady state through regulated assembly and disassembly. Here, we used experimentally defined actin structures in vitro to investigate how the activity of myosin motors depends on network architecture. Direct visualization of filaments revealed myosin-induced actin network deformation. During this reorganization, myosins selectively contracted and disassembled antiparallel actin structures, while parallel actin bundles remained unaffected. The local distribution of nucleation sites and the resulting orientation of actin filaments appeared to regulate the scalability of the contraction process. This "orientation selection" mechanism for selective contraction and disassembly suggests how the dynamics of the cellular actin cytoskeleton can be spatially controlled by actomyosin contractility.

  11. Clustering algorithm for determining community structure in large networks

    NASA Astrophysics Data System (ADS)

    Pujol, Josep M.; Béjar, Javier; Delgado, Jordi

    2006-07-01

    We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.

  12. Autism and ADHD: Overlapping and Discriminating Symptoms

    ERIC Educational Resources Information Center

    Mayes, Susan Dickerson; Calhoun, Susan L.; Mayes, Rebecca D.; Molitoris, Sarah

    2012-01-01

    Children with ADHD and autism have some similar features, complicating a differential diagnosis. The purpose of our study was to determine the degree to which core ADHD and autistic symptoms overlap in and discriminate between children 2-16 years of age with autism and ADHD. Our study demonstrated that 847 children with autism were easily…

  13. Autism and ADHD: Overlapping and Discriminating Symptoms

    ERIC Educational Resources Information Center

    Mayes, Susan Dickerson; Calhoun, Susan L.; Mayes, Rebecca D.; Molitoris, Sarah

    2012-01-01

    Children with ADHD and autism have some similar features, complicating a differential diagnosis. The purpose of our study was to determine the degree to which core ADHD and autistic symptoms overlap in and discriminate between children 2-16 years of age with autism and ADHD. Our study demonstrated that 847 children with autism were easily…

  14. Attractive interactions among intermediate filaments determine network mechanics in vitro.

    PubMed

    Pawelzyk, Paul; Mücke, Norbert; Herrmann, Harald; Willenbacher, Norbert

    2014-01-01

    Mechanical and structural properties of K8/K18 and vimentin intermediate filament (IF) networks have been investigated using bulk mechanical rheometry and optical microrheology including diffusing wave spectroscopy and multiple particle tracking. A high elastic modulus G0 at low protein concentration c, a weak concentration dependency of G0 (G0 ∼ c(0.5 ± 0.1)) and pronounced strain stiffening are found for these systems even without external crossbridgers. Strong attractive interactions among filaments are required to maintain these characteristic mechanical features, which have also been reported for various other IF networks. Filament assembly, the persistence length of the filaments and the network mesh size remain essentially unaffected when a nonionic surfactant is added, but strain stiffening is completely suppressed, G0 drops by orders of magnitude and exhibits a scaling G0 ∼ c(1.9 ± 0.2) in agreement with microrheological measurements and as expected for entangled networks of semi-flexible polymers. Tailless K8Δ/K18ΔT and various other tailless filament networks do not exhibit strain stiffening, but still show high G0 values. Therefore, two binding sites are proposed to exist in IF networks. A weaker one mediated by hydrophobic amino acid clusters in the central rod prevents stretched filaments between adjacent cross-links from thermal equilibration and thus provides the high G0 values. Another strong one facilitating strain stiffening is located in the tail domain with its high fraction of hydrophobic amino acid sequences. Strain stiffening is less pronounced for vimentin than for K8/K18 due to electrostatic repulsion forces partly compensating the strong attraction at filament contact points.

  15. Automatic segmentation of overlapping and touching chromosomes

    NASA Astrophysics Data System (ADS)

    Yuan, Zhiqiang; Chen, Xiaohua; Zhang, Renli; Yu, Chang

    2001-09-01

    reaches to another boundary or tracing route. For overlapping chromosomes, the searching algorithm fails. We proposed a topology information based method for analyzing overlapping and touching chromosomes. Mihail Popescu adopts Cross Section Sequence Graph (CSSG) method for shape analyzing. Gady Agam proposed Discrete Curvature Function for splitting touching and overlapping chromosomes. But due to the non-rigid property of chromosomes, it is hard to determine the actual topology structure of chromosomes. In this paper we proposed a new method to produce topology information of chromosomes and had got good results in chromosome segmentation.

  16. Vulnerability and cosusceptibility determine the size of network cascades

    DOE PAGES

    Yang, Yang; Nishikawa, Takashi; Motter, Adilson E.

    2017-01-27

    In a network, a local disturbance can propagate and eventually cause a substantial part of the system to fail in cascade events that are easy to conceptualize but extraordinarily difficult to predict. Furthermore, we develop a statistical framework that can predict cascade size distributions by incorporating two ingredients only: the vulnerability of individual components and the cosusceptibility of groups of components (i.e., their tendency to fail together). Using cascades in power grids as a representative example, we show that correlations between component failures define structured and often surprisingly large groups of cosusceptible components. Aside from their implications for blackout studies,more » these results provide insights and a new modeling framework for understanding cascades in financial systems, food webs, and complex networks in general.« less

  17. Vulnerability and Cosusceptibility Determine the Size of Network Cascades

    NASA Astrophysics Data System (ADS)

    Yang, Yang; Nishikawa, Takashi; Motter, Adilson E.

    2017-01-01

    In a network, a local disturbance can propagate and eventually cause a substantial part of the system to fail in cascade events that are easy to conceptualize but extraordinarily difficult to predict. Here, we develop a statistical framework that can predict cascade size distributions by incorporating two ingredients only: the vulnerability of individual components and the cosusceptibility of groups of components (i.e., their tendency to fail together). Using cascades in power grids as a representative example, we show that correlations between component failures define structured and often surprisingly large groups of cosusceptible components. Aside from their implications for blackout studies, these results provide insights and a new modeling framework for understanding cascades in financial systems, food webs, and complex networks in general.

  18. Security management based on trust determination in cognitive radio networks

    NASA Astrophysics Data System (ADS)

    Li, Jianwu; Feng, Zebing; Wei, Zhiqing; Feng, Zhiyong; Zhang, Ping

    2014-12-01

    Security has played a major role in cognitive radio networks. Numerous researches have mainly focused on attacking detection based on source localization and detection probability. However, few of them took the penalty of attackers into consideration and neglected how to implement effective punitive measures against attackers. To address this issue, this article proposes a novel penalty mechanism based on cognitive trust value. The main feature of this mechanism has been realized by six functions: authentication, interactive, configuration, trust value collection, storage and update, and punishment. Data fusion center (FC) and cluster heads (CHs) have been put forward as a hierarchical architecture to manage trust value of cognitive users. Misbehaving users would be punished by FC by declining their trust value; thus, guaranteeing network security via distinguishing attack users is of great necessity. Simulation results verify the rationality and effectiveness of our proposed mechanism.

  19. Determining a bisection bandwidth for a multi-node data communications network

    DOEpatents

    Faraj, Ahmad A.

    2010-01-26

    Methods, systems, and products are disclosed for determining a bisection bandwidth for a multi-node data communications network that include: partitioning nodes in the network into a first sub-network and a second sub-network in dependence upon a topology of the network; sending, by each node in the first sub-network to a destination node in the second sub-network, a first message having a predetermined message size; receiving, by each node in the first sub-network from a source node in the second sub-network, a second message; measuring, by each node in the first sub-network, the elapsed communications time between the sending of the first message and the receiving of the second message; selecting the longest elapsed communications time; and calculating the bisection bandwidth for the network in dependence upon the number of the nodes in the first sub-network, the predetermined message size of the first test message, and the longest elapsed communications time.

  20. Dynamic rewiring of the Drosophila retinal determination network switches its function from selector to differentiation.

    PubMed

    Atkins, Mardelle; Jiang, Yuwei; Sansores-Garcia, Leticia; Jusiak, Barbara; Halder, Georg; Mardon, Graeme

    2013-08-01

    Organ development is directed by selector gene networks. Eye development in the fruit fly Drosophila melanogaster is driven by the highly conserved selector gene network referred to as the "retinal determination gene network," composed of approximately 20 factors, whose core comprises twin of eyeless (toy), eyeless (ey), sine oculis (so), dachshund (dac), and eyes absent (eya). These genes encode transcriptional regulators that are each necessary for normal eye development, and sufficient to direct ectopic eye development when misexpressed. While it is well documented that the downstream genes so, eya, and dac are necessary not only during early growth and determination stages but also during the differentiation phase of retinal development, it remains unknown how the retinal determination gene network terminates its functions in determination and begins to promote differentiation. Here, we identify a switch in the regulation of ey by the downstream retinal determination genes, which is essential for the transition from determination to differentiation. We found that central to the transition is a switch from positive regulation of ey transcription to negative regulation and that both types of regulation require so. Our results suggest a model in which the retinal determination gene network is rewired to end the growth and determination stage of eye development and trigger terminal differentiation. We conclude that changes in the regulatory relationships among members of the retinal determination gene network are a driving force for key transitions in retinal development.

  1. Automated iterative reclustering framework for determining hierarchical functional networks in resting state fMRI.

    PubMed

    Shams, Seyed-Mohammad; Afshin-Pour, Babak; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali; Strother, Stephen C

    2015-09-01

    To spatially cluster resting state-functional magnetic resonance imaging (rs-fMRI) data into potential networks, there are only a few general approaches that determine the number of networks/clusters, despite a wide variety of techniques proposed for clustering. For individual subjects, extraction of a large number of spatially disjoint clusters results in multiple small networks that are spatio-temporally homogeneous but irreproducible across subjects. Alternatively, extraction of a small number of clusters creates spatially large networks that are temporally heterogeneous but spatially reproducible across subjects. We propose a fully automatic, iterative reclustering framework in which a small number of spatially large, heterogeneous networks are initially extracted to maximize spatial reproducibility. Subsequently, the large networks are iteratively subdivided to create spatially reproducible subnetworks until the overall within-network homogeneity does not increase substantially. The proposed approach discovers a rich network hierarchy in the brain while simultaneously optimizing spatial reproducibility of networks across subjects and individual network homogeneity. We also propose a novel metric to measure the connectivity of brain regions, and in a simulation study show that our connectivity metric and framework perform well in the face of low signal to noise and initial segmentation errors. Experimental results generated using real fMRI data show that the proposed metric improves stability of network clusters across subjects, and generates a meaningful pattern for spatially hierarchical structure of the brain. © 2015 Wiley Periodicals, Inc.

  2. Determination of a Limited Scope Network's Lightning Detection Efficiency

    NASA Technical Reports Server (NTRS)

    Rompala, John T.; Blakeslee, R.

    2008-01-01

    This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

  3. Host Centrality in Food Web Networks Determines Parasite Diversity

    PubMed Central

    Anderson, Tavis K.; Sukhdeo, Michael V. K.

    2011-01-01

    Background Parasites significantly alter topological metrics describing food web structure, yet few studies have explored the relationship between food web topology and parasite diversity. Methods/Principal Findings This study uses quantitative metrics describing network structure to investigate the relationship between the topology of the host food web and parasite diversity. Food webs were constructed for four restored brackish marshes that vary in species diversity, time post restoration and levels of parasitism. Our results show that the topology of the food web in each brackish marsh is highly nested, with clusters of generalists forming a distinct modular structure. The most consistent predictors of parasite diversity within a host were: trophic generality, and eigenvector centrality. These metrics indicate that parasites preferentially colonise host species that are highly connected, and within modules of tightly interacting species in the food web network. Conclusions/Significance These results suggest that highly connected free-living species within the food web may represent stable trophic relationships that allow for the persistence of complex parasite life cycles. Our data demonstrate that the structure of host food webs can have a significant effect on the establishment of parasites, and on the potential for evolution of complex parasite life cycles. PMID:22046360

  4. On the Neuberger overlap operator

    NASA Astrophysics Data System (ADS)

    Boriçi, Artan

    1999-04-01

    We compute Neuberger's overlap operator by the Lanczos algorithm applied to the Wilson-Dirac operator. Locality of the operator for quenched QCD data and its eigenvalue spectrum in an instanton background are studied.

  5. Comparison of Different Methods of the Datum Determination in Control Networks

    NASA Astrophysics Data System (ADS)

    Nasari, H.

    2009-04-01

    Establishment of the geodetic control networks and observations in regular epochs is a commonly used method for detection of displacement and structures health monitoring. Determination of the reference coordinate system and the appropriate adjustment technique are the critical parts of the network analysis. Results mainly depend on the determination of the reference coordinate system. They can be chosen either by minimum, inner or weighted constraints. This paper is focused on the comparison of these methods for determination of the reference coordinate systems in control networks and their effects on the detection of displacement. The results reveal that weighted constraint adjustment method is superior to other methods when the weights are selected based on the rate of displacement. Keywords: Datum determination, Control Networks, Minimum constraints, Inner constraints, Weighted constraints, Detection of displacement

  6. 77 FR 7229 - Culturally Significant Objects Imported for Exhibition Determinations: “Nomads and Networks: The...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-10

    ... and Culture of Kazakhstan'' SUMMARY: Notice is hereby given of the following determinations: Pursuant... Networks: The Ancient Art and Culture of Kazakhstan,'' imported from abroad for temporary exhibition within...

  7. 77 FR 37730 - Culturally Significant Objects Imported for Exhibition Determinations: “Nomads and Networks: The...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-22

    ... and Culture of Kazakhstan'' SUMMARY: Notice is hereby given of the following determinations: Pursuant... Networks: The Ancient Art and Culture of Kazakhstan,'' imported from abroad for temporary exhibition within...

  8. Magnesium degradation as determined by artificial neural networks.

    PubMed

    Willumeit, Regine; Feyerabend, Frank; Huber, Norbert

    2013-11-01

    Magnesium degradation under physiological conditions is a highly complex process in which temperature, the use of cell culture growth medium and the presence of CO2, O2 and proteins can influence the corrosion rate and the composition of the resulting corrosion layer. Due to the complexity of this process it is almost impossible to predict the parameters that are most important and whether some parameters have a synergistic effect on the corrosion rate. Artificial neural networks are a mathematical tool that can be used to approximate and analyse non-linear problems with multiple inputs. In this work we present the first analysis of corrosion data obtained using this method, which reveals that CO2 and the composition of the buffer system play a crucial role in the corrosion of magnesium, whereas O2, proteins and temperature play a less prominent role.

  9. Spatial reasoning to determine stream network from LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.; Wang, S.; Elliott, D. B.

    1983-01-01

    In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

  10. An Exposition of Fischer's Model of Overlapping Contracts.

    ERIC Educational Resources Information Center

    Fields, T. Windsor; Hart, William R.

    1992-01-01

    Suggests how the classic model of overlapping contracts can be incorporated into the contract wage model of aggregate supply. Illustrates dynamics of macroeconomic adjustment following a shock to aggregate demand. Concludes that overlapping contracts do not prolong the adjustment process; rather, the longest remaining contract determines the time…

  11. Method and apparatus for determining and utilizing a time-expanded decision network

    NASA Technical Reports Server (NTRS)

    Silver, Matthew (Inventor); de Weck, Olivier (Inventor)

    2012-01-01

    A method, apparatus and computer program for determining and utilizing a time-expanded decision network is presented. A set of potential system configurations is defined. Next, switching costs are quantified to create a "static network" that captures the difficulty of switching among these configurations. A time-expanded decision network is provided by expanding the static network in time, including chance and decision nodes. Minimum cost paths through the network are evaluated under plausible operating scenarios. The set of initial design configurations are iteratively modified to exploit high-leverage switches and the process is repeated to convergence. Time-expanded decision networks are applicable, but not limited to, the design of systems, products, services and contracts.

  12. Determinants of Sexual Network Structure and Their Impact on Cumulative Network Measures

    PubMed Central

    Schmid, Boris V.; Kretzschmar, Mirjam

    2012-01-01

    There are four major quantities that are measured in sexual behavior surveys that are thought to be especially relevant for the performance of sexual network models in terms of disease transmission. These are (i) the cumulative distribution of lifetime number of partners, (ii) the distribution of partnership durations, (iii) the distribution of gap lengths between partnerships, and (iv) the number of recent partners. Fitting a network model to these quantities as measured in sexual behavior surveys is expected to result in a good description of Chlamydia trachomatis transmission in terms of the heterogeneity of the distribution of infection in the population. Here we present a simulation model of a sexual contact network, in which we explored the role of behavioral heterogeneity of simulated individuals on the ability of the model to reproduce population-level sexual survey data from the Netherlands and UK. We find that a high level of heterogeneity in the ability of individuals to acquire and maintain (additional) partners strongly facilitates the ability of the model to accurately simulate the powerlaw-like distribution of the lifetime number of partners, and the age at which these partnerships were accumulated, as surveyed in actual sexual contact networks. Other sexual network features, such as the gap length between partnerships and the partnership duration, could–at the current level of detail of sexual survey data against which they were compared–be accurately modeled by a constant value (for transitional concurrency) and by exponential distributions (for partnership duration). Furthermore, we observe that epidemiological measures on disease prevalence in survey data can be used as a powerful tool for building accurate sexual contact networks, as these measures provide information on the level of mixing between individuals of different levels of sexual activity in the population, a parameter that is hard to acquire through surveying individuals. PMID

  13. Finding Hierarchical and Overlapping Dense Subgraphs using Nucleus Decompositions

    SciTech Connect

    Seshadhri, Comandur; Pinar, Ali; Sariyuce, Ahmet Erdem; Catalyurek, Umit

    2014-11-01

    Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasiclique, k-densest subgraph) are NP-hard. Furthermore, the goal is rarely to nd the \\true optimum", but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine a hierarchical structure among them. Current dense subgraph nding algorithms usually optimize some objective, and only nd a few such subgraphs without providing any hierarchy. It is also not clear how to account for overlaps in dense substructures. We de ne the nucleus decomposition of a graph, which represents the graph as a forest of nuclei. Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases as we proceed towards leaf nuclei. Sibling nuclei can have limited intersections, which allows for discovery of overlapping dense subgraphs. With the right parameters, the nuclear decomposition generalizes the classic notions of k-cores and k-trusses. We give provable e cient algorithms for nuclear decompositions, and empirically evaluate their behavior in a variety of real graphs. The tree of nuclei consistently gives a global, hierarchical snapshot of dense substructures, and outputs dense subgraphs of higher quality than other state-of-theart solutions. Our algorithm can process graphs with tens of millions of edges in less than an hour.

  14. A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence.

    PubMed

    Balasubramanian, Deepak; Schneper, Lisa; Kumari, Hansi; Mathee, Kalai

    2013-01-07

    Pseudomonas aeruginosa is a metabolically versatile bacterium that is found in a wide range of biotic and abiotic habitats. It is a major human opportunistic pathogen causing numerous acute and chronic infections. The critical traits contributing to the pathogenic potential of P. aeruginosa are the production of a myriad of virulence factors, formation of biofilms and antibiotic resistance. Expression of these traits is under stringent regulation, and it responds to largely unidentified environmental signals. This review is focused on providing a global picture of virulence gene regulation in P. aeruginosa. In addition to key regulatory pathways that control the transition from acute to chronic infection phenotypes, some regulators have been identified that modulate multiple virulence mechanisms. Despite of a propensity for chaotic behaviour, no chaotic motifs were readily observed in the P. aeruginosa virulence regulatory network. Having a 'birds-eye' view of the regulatory cascades provides the forum opportunities to pose questions, formulate hypotheses and evaluate theories in elucidating P. aeruginosa pathogenesis. Understanding the mechanisms involved in making P. aeruginosa a successful pathogen is essential in helping devise control strategies.

  15. A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence

    PubMed Central

    Balasubramanian, Deepak; Schneper, Lisa; Kumari, Hansi; Mathee, Kalai

    2013-01-01

    Pseudomonas aeruginosa is a metabolically versatile bacterium that is found in a wide range of biotic and abiotic habitats. It is a major human opportunistic pathogen causing numerous acute and chronic infections. The critical traits contributing to the pathogenic potential of P. aeruginosa are the production of a myriad of virulence factors, formation of biofilms and antibiotic resistance. Expression of these traits is under stringent regulation, and it responds to largely unidentified environmental signals. This review is focused on providing a global picture of virulence gene regulation in P. aeruginosa. In addition to key regulatory pathways that control the transition from acute to chronic infection phenotypes, some regulators have been identified that modulate multiple virulence mechanisms. Despite of a propensity for chaotic behaviour, no chaotic motifs were readily observed in the P. aeruginosa virulence regulatory network. Having a ‘birds-eye’ view of the regulatory cascades provides the forum opportunities to pose questions, formulate hypotheses and evaluate theories in elucidating P. aeruginosa pathogenesis. Understanding the mechanisms involved in making P. aeruginosa a successful pathogen is essential in helping devise control strategies. PMID:23143271

  16. A Novel Clustering Algorithm for Mobile Ad Hoc Networks Based on Determination of Virtual Links' Weight to Increase Network Stability

    PubMed Central

    Karimi, Abbas; Afsharfarnia, Abbas; Zarafshan, Faraneh; Al-Haddad, S. A. R.

    2014-01-01

    The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure. PMID:25114965

  17. Overlap-Based Cell Tracker

    PubMed Central

    Chalfoun, Joe; Cardone, Antonio; Dima, Alden A.; Allen, Daniel P.; Halter, Michael W.

    2010-01-01

    In order to facilitate the extraction of quantitative data from live cell image sets, automated image analysis methods are needed. This paper presents an introduction to the general principle of an overlap cell tracking software developed by the National Institute of Standards and Technology (NIST). This cell tracker has the ability to track cells across a set of time lapse images acquired at high rates based on the amount of overlap between cellular regions in consecutive frames. It is designed to be highly flexible, requires little user parameterization, and has a fast execution time. PMID:27134800

  18. International Network of Passive Correlation Ranging for Orbit Determination of a Geostationary Satellite

    NASA Astrophysics Data System (ADS)

    Kaliuzhnyi, Mykola; Bushuev, Felix; Shulga, Oleksandr; Sybiryakova, Yevgeniya; Shakun, Leonid; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Malynovskyi, Yevgen

    2016-12-01

    An international network of passive correlation ranging of a geostationary telecommunication satellite is considered in the article. The network is developed by the RI "MAO". The network consists of five spatially separated stations of synchronized reception of DVB-S signals of digital satellite TV. The stations are located in Ukraine and Latvia. The time difference of arrival (TDOA) on the network stations of the DVB-S signals, radiated by the satellite, is a measured parameter. The results of TDOA estimation obtained by the network in May-August 2016 are presented in the article. Orbital parameters of the tracked satellite are determined using measured values of the TDOA and two models of satellite motion: the analytical model SGP4/SDP4 and the model of numerical integration of the equations of satellite motion. Both models are realized using the free low-level space dynamics library OREKIT (ORbit Extrapolation KIT).

  19. Analyzing the Coordinated Gene Network Underlying Temperature-Dependent Sex Determination in Reptiles

    PubMed Central

    Shoemaker, Christina M.; Crews, David

    2009-01-01

    Although gonadogenesis has been extensively studied in vertebrates with genetic sex determination, investigations at the molecular level in nontraditional model organisms with temperature-dependent sex determination are a relatively new area of research. Results show that while the key players of the molecular network underlying gonad development appear to be retained, their functions range from conserved to novel roles. In this review, we summarize experiments investigating candidate molecular players underlying temperature-dependent sex determination. We discuss some of the problems encountered unraveling this network, pose potential solutions, and suggest rewarding future directions of research. PMID:19022389

  20. Laser ranging network performance and routine orbit determination at D-PAF

    NASA Technical Reports Server (NTRS)

    Massmann, Franz-Heinrich; Reigber, C.; Li, H.; Koenig, Rolf; Raimondo, J. C.; Rajasenan, C.; Vei, M.

    1993-01-01

    ERS-1 is now about 8 months in orbit and has been tracked by the global laser network from the very beginning of the mission. The German processing and archiving facility for ERS-1 (D-PAF) is coordinating and supporting the network and performing the different routine orbit determination tasks. This paper presents details about the global network status, the communication to D-PAF and the tracking data and orbit processing system at D-PAF. The quality of the preliminary and precise orbits are shown and some problem areas are identified.

  1. Aspects and the Overlap Function.

    ERIC Educational Resources Information Center

    Levine, Marilyn M.; Levine, Leonard P.

    1984-01-01

    Presents system for automatic handling of ordered sets, states based on these sets, and differing points of view regarding Universe of Discourse. Aspects are represented by new logical "overlap" function with examples taken from Ranganathan's horse and carriage parable and several books involving four main concepts (history, geography,…

  2. A neural network approach to fault detection in spacecraft attitude determination and control systems

    NASA Astrophysics Data System (ADS)

    Schreiner, John N.

    This thesis proposes a method of performing fault detection and isolation in spacecraft attitude determination and control systems. The proposed method works by deploying a trained neural network to analyze a set of residuals that are defined such that they encompass the attitude control, guidance, and attitude determination subsystems. Eight neural networks were trained using either the resilient backpropagation, Levenberg-Marquardt, or Levenberg-Marquardt with Bayesian regularization training algorithms. The results of each of the neural networks were analyzed to determine the accuracy of the networks with respect to isolating the faulty component or faulty subsystem within the ADCS. The performance of the proposed neural network-based fault detection and isolation method was compared and contrasted with other ADCS FDI methods. The results obtained via simulation showed that the best neural networks employing this method successfully detected the presence of a fault 79% of the time. The faulty subsystem was successfully isolated 75% of the time and the faulty components within the faulty subsystem were isolated 37% of the time.

  3. Differential Selection within the Drosophila Retinal Determination Network and Evidence for Functional Divergence between Paralog Pairs

    PubMed Central

    Datta, Rhea R.; Cruickshank, Tami; Kumar, Justin P.

    2011-01-01

    The retinal determination (RD) network in Drosophila comprises fourteen known nuclear proteins that include DNA binding proteins, transcriptional co-activators, kinases and phosphatases. The composition of the network varies considerably throughout the animal kingdom, with the network in several basal insects having fewer members and with vertebrates having potentially significantly higher numbers of retinal determination genes. One important contributing factor for the variation in gene number within the network is gene duplication. For example, ten members of the RD network in Drosophila are derived from duplication events. Here we present an analysis of the coding regions of the five pairs of duplicate genes from within the retinal determination network of several different Drosophila species. We demonstrate that there is differential selection across the coding regions of all RD genes. Additionally, some of the most significant differences in ratios of non-silent to silent site substitutions (dN/dS) between paralog pairs are found within regions that have no ascribed function. Previous structure/function analyses of several duplicate genes have identified areas within one gene that contain novel activities when compared to its paralog. The evolutionary analysis presented here identifies these same areas in the paralogs as being under high levels of relaxed selection. We suggest that sequence divergence between paralogs and selection signatures can be used as a reasonable predictor of functional changes in rapidly evolving motifs. PMID:21210943

  4. An algorithm Walktrap-SPM for detecting overlapping community structure

    NASA Astrophysics Data System (ADS)

    Hu, Fang; Zhu, Youze; Shi, Yuan; Cai, Jianchao; Chen, Luogeng; Shen, Shaowu

    2017-06-01

    In this paper, based on Walktrap algorithm with the idea of random walk, and by selecting the neighbor communities, introducing improved signed probabilistic mixture (SPM) model and considering the edges within the community as positive links and the edges between the communities as negative links, a novel algorithm Walktrap-SPM for detecting overlapping community is proposed. This algorithm not only can identify the overlapping communities, but also can greatly increase the objectivity and accuracy of the results. In order to verify the accuracy, the performance of this algorithm is tested on several representative real-world networks and a set of computer-generated networks based on LFR benchmark. The experimental results indicate that this algorithm can identify the communities accurately, and it is more suitable for overlapping community detection. Compared with Walktrap, SPM and LMF algorithms, the presented algorithm can acquire higher values of modularity and NMI. Moreover, this new algorithm has faster running time than SPM and LMF algorithms.

  5. Topological Small-World Organization of the Fibroblastic Reticular Cell Network Determines Lymph Node Functionality

    PubMed Central

    Abe, Jun; Bomze, David; Cremasco, Viviana; Scandella, Elke; Stein, Jens V.; Turley, Shannon J.; Ludewig, Burkhard

    2016-01-01

    Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses. PMID:27415420

  6. Topological Small-World Organization of the Fibroblastic Reticular Cell Network Determines Lymph Node Functionality.

    PubMed

    Novkovic, Mario; Onder, Lucas; Cupovic, Jovana; Abe, Jun; Bomze, David; Cremasco, Viviana; Scandella, Elke; Stein, Jens V; Bocharov, Gennady; Turley, Shannon J; Ludewig, Burkhard

    2016-07-01

    Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses.

  7. Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases.

    PubMed

    Mariani, Simona; Dell'Orco, Daniele; Felline, Angelo; Raimondi, Francesco; Fanelli, Francesca

    2013-01-01

    A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEγ binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

  8. Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization.

    PubMed

    Livi, Lorenzo; Bianchi, Filippo Maria; Alippi, Cesare

    2017-01-16

    It is a widely accepted fact that the computational capability of recurrent neural networks (RNNs) is maximized on the so-called "edge of criticality." Once the network operates in this configuration, it performs efficiently on a specific application both in terms of: 1) low prediction error and 2) high short-term memory capacity. Since the behavior of recurrent networks is strongly influenced by the particular input signal driving the dynamics, a universal, application-independent method for determining the edge of criticality is still missing. In this paper, we aim at addressing this issue by proposing a theoretically motivated, unsupervised method based on Fisher information for determining the edge of criticality in RNNs. It is proved that Fisher information is maximized for (finite-size) systems operating in such critical regions. However, Fisher information is notoriously difficult to compute and requires the analytic form of the probability density function ruling the system behavior. This paper takes advantage of a recently developed nonparametric estimator of the Fisher information matrix and provides a method to determine the critical region of echo state networks (ESNs), a particular class of recurrent networks. The considered control parameters, which indirectly affect the ESN performance, are explored to identify those configurations lying on the edge of criticality and, as such, maximizing Fisher information and computational performance. Experimental results on benchmarks and real-world data demonstrate the effectiveness of the proposed method.

  9. Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate

    PubMed Central

    Coulombe-Huntington, Jasmin; Xia, Yu

    2012-01-01

    The evolution of transcriptional regulatory networks has thus far mostly been studied at the level of cis-regulatory elements. To gain a complete understanding of regulatory network evolution we must also study the evolutionary role of trans-factors, such as transcription factors (TFs). Here, we systematically assess genomic and network-level determinants of TF evolutionary rate in yeast, and how they compare to those of generic proteins, while carefully controlling for differences of the TF protein set, such as expression level. We found significantly distinct trends relating TF evolutionary rate to mRNA expression level, codon adaptation index, the evolutionary rate of physical interaction partners, and, confirming previous reports, to protein-protein interaction degree and regulatory in-degree. We discovered that for TFs, the dominant determinants of evolutionary rate lie in the structure of the regulatory network, such as the median evolutionary rate of target genes and the fraction of species-specific target genes. Decomposing the regulatory network by edge sign, we found that this modular evolution of TFs and their targets is limited to activating regulatory relationships. We show that fast evolving TFs tend to regulate other TFs and niche-specific processes and that their targets show larger evolutionary expression changes than targets of other TFs. We also show that the positive trend relating TF regulatory in-degree and evolutionary rate is likely related to the species-specificity of the transcriptional regulation modules. Finally, we discuss likely causes for TFs' different evolutionary relationship to the physical interaction network, such as the prevalence of transient interactions in the TF subnetwork. This work suggests that positive and negative regulatory networks follow very different evolutionary rules, and that transcription factor evolution is best understood at a network- or systems-level. PMID:23093926

  10. Combining core drop policy and edge determinant threshold in TCP over OBS networks with retransmission

    NASA Astrophysics Data System (ADS)

    Peng, Shuping; Li, Zhengbin; He, Yongqi; Xu, Anshi

    2007-11-01

    We proposed a novel drop policy in the core nodes which is combined with the determinant strategy in the ingress edge nodes. The proposed drop policy is based on the field of Hop Number (HN) taken by the burst control packets, which is introduced to determine which burst should be dropped when the contention happened in the core nodes. In the drop policy, the long-hop traffic is given the high priority, and most of the retransmitted traffic is left to be short-hop traffic. Therefore, there is a trade-off between the short-hop traffic and the long-hop traffic. The determinant strategy in the edge nodes is an initialized threshold, Retransmission Number Threshold (RNT), which is introduced to determine whether to start a retransmission operation when NAK is received. The unnecessary retransmissions in the network are limited, and the burst loss rate is reduced. The mechanism also takes the upper layer, TCP layer, into account. When the network has already been in the state of real congestion, the retransmission will only deteriorate the network performance. In the case, the combined mechanism leaves the retransmission process to the TCP layer. It can improve the network performance cost-effectively.

  11. Data Mining and Concept Clustering in Determining the Nature of a Network Attack

    DTIC Science & Technology

    2002-08-01

    UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP013329 TITLE: Data Mining and Concept Clustering in Determining the...Click here to view PowerPoint presentation; Press Esc to exit 18-1 Data Mining and Concept Clustering in Determining the Nature of a Network Attack...by a rule. The USAF Enterprise Defence project is intended to develop * Better data mining tools and techniques are needed to the next-generation

  12. An evolutionary game approach for determination of the structural conflicts in signed networks

    PubMed Central

    Tan, Shaolin; Lü, Jinhu

    2016-01-01

    Social or biochemical networks can often divide into two opposite alliances in response to structural conflicts between positive (friendly, activating) and negative (hostile, inhibiting) interactions. Yet, the underlying dynamics on how the opposite alliances are spontaneously formed to minimize the structural conflicts is still unclear. Here, we demonstrate that evolutionary game dynamics provides a felicitous possible tool to characterize the evolution and formation of alliances in signed networks. Indeed, an evolutionary game dynamics on signed networks is proposed such that each node can adaptively adjust its choice of alliances to maximize its own fitness, which yet leads to a minimization of the structural conflicts in the entire network. Numerical experiments show that the evolutionary game approach is universally efficient in quality and speed to find optimal solutions for all undirected or directed, unweighted or weighted signed networks. Moreover, the evolutionary game approach is inherently distributed. These characteristics thus suggest the evolutionary game dynamic approach as a feasible and effective tool for determining the structural conflicts in large-scale on-line signed networks. PMID:26915581

  13. An evolutionary game approach for determination of the structural conflicts in signed networks

    NASA Astrophysics Data System (ADS)

    Tan, Shaolin; Lü, Jinhu

    2016-02-01

    Social or biochemical networks can often divide into two opposite alliances in response to structural conflicts between positive (friendly, activating) and negative (hostile, inhibiting) interactions. Yet, the underlying dynamics on how the opposite alliances are spontaneously formed to minimize the structural conflicts is still unclear. Here, we demonstrate that evolutionary game dynamics provides a felicitous possible tool to characterize the evolution and formation of alliances in signed networks. Indeed, an evolutionary game dynamics on signed networks is proposed such that each node can adaptively adjust its choice of alliances to maximize its own fitness, which yet leads to a minimization of the structural conflicts in the entire network. Numerical experiments show that the evolutionary game approach is universally efficient in quality and speed to find optimal solutions for all undirected or directed, unweighted or weighted signed networks. Moreover, the evolutionary game approach is inherently distributed. These characteristics thus suggest the evolutionary game dynamic approach as a feasible and effective tool for determining the structural conflicts in large-scale on-line signed networks.

  14. Master regulators in development: Views from the Drosophila retinal determination and mammalian pluripotency gene networks.

    PubMed

    Davis, Trevor L; Rebay, Ilaria

    2017-01-15

    Among the mechanisms that steer cells to their correct fate during development, master regulatory networks are unique in their sufficiency to trigger a developmental program outside of its normal context. In this review we discuss the key features that underlie master regulatory potency during normal and ectopic development, focusing on two examples, the retinal determination gene network (RDGN) that directs eye development in the fruit fly and the pluripotency gene network (PGN) that maintains cell fate competency in the early mammalian embryo. In addition to the hierarchical transcriptional activation, extensive positive transcriptional feedback, and cooperative protein-protein interactions that enable master regulators to override competing cellular programs, recent evidence suggests that network topology must also be dynamic, with extensive rewiring of the interactions and feedback loops required to navigate the correct sequence of developmental transitions to reach a final fate. By synthesizing the in vivo evidence provided by the RDGN with the extensive mechanistic insight gleaned from the PGN, we highlight the unique regulatory capabilities that continual reorganization into new hierarchies confers on master control networks. We suggest that deeper understanding of such dynamics should be a priority, as accurate spatiotemporal remodeling of network topology will undoubtedly be essential for successful stem cell based therapeutic efforts.

  15. A Compact Optical Instrument with Artificial Neural Network for pH Determination

    PubMed Central

    Capel-Cuevas, Sonia; López-Ruiz, Nuria; Martinez-Olmos, Antonio; Cuéllar, Manuel P.; Pegalajar, Maria del Carmen; Palma, Alberto José; de Orbe-Payá, Ignacio; Capitán-Vallvey, Luis Fermin

    2012-01-01

    The aim of this work was the determination of pH with a sensor array-based optical portable instrument. This sensor array consists of eleven membranes with selective colour changes at different pH intervals. The method for the pH calculation is based on the implementation of artificial neural networks that use the responses of the membranes to generate a final pH value. A multi-objective algorithm was used to select the minimum number of sensing elements required to achieve an accurate pH determination from the neural network, and also to minimise the network size. This helps to minimise instrument and array development costs and save on microprocessor energy consumption. A set of artificial neural networks that fulfils these requirements is proposed using different combinations of the membranes in the sensor array, and is evaluated in terms of accuracy and reliability. In the end, the network including the response of the eleven membranes in the sensor was selected for validation in the instrument prototype because of its high accuracy. The performance of the instrument was evaluated by measuring the pH of a large set of real samples, showing that high precision can be obtained in the full range. PMID:22778668

  16. Adaptive k-means algorithm for overlapped graph clustering.

    PubMed

    Bello-Orgaz, Gema; Menéndez, Héctor D; Camacho, David

    2012-10-01

    The graph clustering problem has become highly relevant due to the growing interest of several research communities in social networks and their possible applications. Overlapped graph clustering algorithms try to find subsets of nodes that can belong to different clusters. In social network-based applications it is quite usual for a node of the network to belong to different groups, or communities, in the graph. Therefore, algorithms trying to discover, or analyze, the behavior of these networks needed to handle this feature, detecting and identifying the overlapped nodes. This paper shows a soft clustering approach based on a genetic algorithm where a new encoding is designed to achieve two main goals: first, the automatic adaptation of the number of communities that can be detected and second, the definition of several fitness functions that guide the searching process using some measures extracted from graph theory. Finally, our approach has been experimentally tested using the Eurovision contest dataset, a well-known social-based data network, to show how overlapped communities can be found using our method.

  17. Comparison of methods to determine point-to-point resistance in nearly rectangular networks with application to a ‘hammock’ network

    PubMed Central

    Essam, John W.; Izmailyan, Nikolay Sh.; Kenna, Ralph; Tan, Zhi-Zhong

    2015-01-01

    Considerable progress has recently been made in the development of techniques to exactly determine two-point resistances in networks of various topologies. In particular, two types of method have emerged. One is based on potentials and the evaluation of eigenvalues and eigenvectors of the Laplacian matrix associated with the network or its minors. The second method is based on a recurrence relation associated with the distribution of currents in the network. Here, these methods are compared and used to determine the resistance distances between any two nodes of a network with topology of a hammock. PMID:26064635

  18. Social support and social network as intermediary social determinants of dental caries in adolescents.

    PubMed

    Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

    2015-04-01

    The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  19. Hospital mergers and market overlap.

    PubMed Central

    Brooks, G R; Jones, V G

    1997-01-01

    OBJECTIVE: To address two questions: What are the characteristics of hospitals that affect the likelihood of their being involved in a merger? What characteristics of particular pairs of hospitals affect the likelihood of the pair engaging in a merger? DATA SOURCES/STUDY SETTING: Hospitals in the 12 county region surrounding the San Francisco Bay during the period 1983 to 1992 were the focus of the study. Data were drawn from secondary sources, including the Lexis/Nexis database, the American Hospital Association, and the Office of Statewide Health Planning and Development of the State of California. STUDY DESIGN: Seventeen hospital mergers during the study period were identified. A random sample of pairs of hospitals that did not merge was drawn to establish a statistically efficient control set. Models constructed from hypotheses regarding hospital and market characteristics believed to be related to merger likelihood were tested using logistic regression analysis. DATA COLLECTION: See Data Sources/Study Setting. PRINCIPAL FINDINGS: The analysis shows that the likelihood of a merger between a particular pair of hospitals is positively related to the degree of market overlap that exists between them. Furthermore, market overlap and performance difference interact in their effect on merger likelihood. In an analysis of individual hospitals, conditions of rivalry, hospital market share, and hospital size were not found to influence the likelihood that a hospital will engage in a merger. CONCLUSIONS: Mergers between hospitals are not driven directly by considerations of market power or efficiency as much as by the existence of specific merger opportunities in the hospitals' local markets. Market overlap is a condition that enables a merger to occur, but other factors, such as the relative performance levels of the hospitals in question and their ownership and teaching status, also play a role in influencing the likelihood that a merger will in fact take place. PMID

  20. Hospital mergers and market overlap.

    PubMed

    Brooks, G R; Jones, V G

    1997-02-01

    To address two questions: What are the characteristics of hospitals that affect the likelihood of their being involved in a merger? What characteristics of particular pairs of hospitals affect the likelihood of the pair engaging in a merger? Hospitals in the 12 county region surrounding the San Francisco Bay during the period 1983 to 1992 were the focus of the study. Data were drawn from secondary sources, including the Lexis/Nexis database, the American Hospital Association, and the Office of Statewide Health Planning and Development of the State of California. Seventeen hospital mergers during the study period were identified. A random sample of pairs of hospitals that did not merge was drawn to establish a statistically efficient control set. Models constructed from hypotheses regarding hospital and market characteristics believed to be related to merger likelihood were tested using logistic regression analysis. See Data Sources/Study Setting. The analysis shows that the likelihood of a merger between a particular pair of hospitals is positively related to the degree of market overlap that exists between them. Furthermore, market overlap and performance difference interact in their effect on merger likelihood. In an analysis of individual hospitals, conditions of rivalry, hospital market share, and hospital size were not found to influence the likelihood that a hospital will engage in a merger. Mergers between hospitals are not driven directly by considerations of market power or efficiency as much as by the existence of specific merger opportunities in the hospitals' local markets. Market overlap is a condition that enables a merger to occur, but other factors, such as the relative performance levels of the hospitals in question and their ownership and teaching status, also play a role in influencing the likelihood that a merger will in fact take place.

  1. Determination of individual contact interfaces in carbon nanotube network-based transistors.

    PubMed

    Yoon, Jinsu; Lim, Meehyun; Choi, Bongsik; Kim, Dong Myong; Kim, Dae Hwan; Kim, Sungho; Choi, Sung-Jin

    2017-07-14

    Carbon nanotubes (CNTs) used as semiconducting channels induce high mobility, thermal conductivity, mechanical flexibility, and chemical stability in field-effect, thin-film transistors (TFTs). However, the contact interfaces in CNT-TFTs have contact resistances that are difficult to reduce; this contact resistance can eventually limit the overall performance of CNT-TFTs. The contact interface between the source/drain electrodes and CNTs, especially for those CNT-TFTs in which the channel comprises randomly networked CNTs, plays a particularly dominant role in determining the performance and degree of variability in CNT-TFTs. However, no studies have reported a determination method that individually extracts each contact resistance at the source/drain electrodes. The present work presents an efficient method for directly determining the contact interfaces in CNT-TFTs by extracting each contact resistance produced at the source (R S ) and drain (R D ) electrodes. Moreover, we comprehensively simulated the randomly networked CNTs using an in-depth Monte-Carlo method, which provides an efficient method for visualizing the uniformity of a CNT network with various controllable CNT parameters. The proposed method provides guidance and a means for optimizing the design of the CNT network channel in CNT-TFTs and additional insights into improving the performance of CNT-TFTs.

  2. What determines social capital in a social-ecological system? Insights from a network perspective.

    PubMed

    Barnes-Mauthe, Michele; Gray, Steven Allen; Arita, Shawn; Lynham, John; Leung, PingSun

    2015-02-01

    Social capital is an important resource that can be mobilized for purposive action or competitive gain. The distribution of social capital in social-ecological systems can determine who is more productive at extracting ecological resources and who emerges as influential in guiding their management, thereby empowering some while disempowering others. Despite its importance, the factors that contribute to variation in social capital among individuals have not been widely studied. We adopt a network perspective to examine what determines social capital among individuals in social-ecological systems. We begin by identifying network measures of social capital relevant for individuals in this context, and review existing evidence concerning their determinants. Using a complete social network dataset from Hawaii's longline fishery, we employ social network analysis and other statistical methods to empirically estimate these measures and determine the extent to which individual stakeholder attributes explain variation within them. We find that ethnicity is the strongest predictor of social capital. Measures of human capital (i.e., education, experience), years living in the community, and information-sharing attitudes are also important. Surprisingly, we find that when controlling for other factors, industry leaders and formal fishery representatives are generally not well connected. Our results offer new quantitative insights on the relationship between stakeholder diversity, social networks, and social capital in a coupled social-ecological system, which can aid in identifying barriers and opportunities for action to overcome resource management problems. Our results also have implications for achieving resource governance that is not only ecologically and economically sustainable, but also equitable.

  3. What Determines Social Capital in a Social-Ecological System? Insights from a Network Perspective

    NASA Astrophysics Data System (ADS)

    Barnes-Mauthe, Michele; Gray, Steven Allen; Arita, Shawn; Lynham, John; Leung, PingSun

    2015-02-01

    Social capital is an important resource that can be mobilized for purposive action or competitive gain. The distribution of social capital in social-ecological systems can determine who is more productive at extracting ecological resources and who emerges as influential in guiding their management, thereby empowering some while disempowering others. Despite its importance, the factors that contribute to variation in social capital among individuals have not been widely studied. We adopt a network perspective to examine what determines social capital among individuals in social-ecological systems. We begin by identifying network measures of social capital relevant for individuals in this context, and review existing evidence concerning their determinants. Using a complete social network dataset from Hawaii's longline fishery, we employ social network analysis and other statistical methods to empirically estimate these measures and determine the extent to which individual stakeholder attributes explain variation within them. We find that ethnicity is the strongest predictor of social capital. Measures of human capital (i.e., education, experience), years living in the community, and information-sharing attitudes are also important. Surprisingly, we find that when controlling for other factors, industry leaders and formal fishery representatives are generally not well connected. Our results offer new quantitative insights on the relationship between stakeholder diversity, social networks, and social capital in a coupled social-ecological system, which can aid in identifying barriers and opportunities for action to overcome resource management problems. Our results also have implications for achieving resource governance that is not only ecologically and economically sustainable, but also equitable.

  4. Social acceleration and the network effect: a defence of social 'science fiction' and network determinism.

    PubMed

    Hassan, Robert

    2010-06-01

    This essay is a response to Judy Wajcman's essay 'Life in the fast lane? Towards a sociology of technology and time' (2008: 59-77). In that article Wajcman argued that recent developments in the sociology of temporal change had been marked by a tendency in social theory towards a form of 'science fiction'--a sociological theorizing, she maintains, that bears no real relation to actual, empirically provable developments in the field and should therefore be viewed as not contributing to 'a richer analysis of the relationship between technology and time' (2008: 61). This reply argues that as Wajcman suggests in her essay, there is indeed an 'urgent need for increased dialogue to connect social theory with detailed empirical studies' (2008: 59) but that the most fruitful way to proceed would not be through a constraining of 'science fiction' social theorizing but, rather, through its expansion--and more, that 'science fiction' should take the lead in the process. This essay suggests that the connection between social theory and empirical studies would be strengthened by a wider understanding of the function of knowledge and research in the context of what is termed 'true originality' and 'routine originality'. The former is the domain of social theory and the latter resides within traditional sociological disciplines. It is argued that both need each other to advance our understanding of society, especially in the context of the fast-changing processes of technological development. The example of 'technological determinism' is discussed as illustrative of how 'routine originality' can harden into dogma without the application of 'true originality' to continually question (sometimes through ideas that may appear to border on 'science fiction') comfortable assumptions that may have become 'routine' and shorn of their initial 'originality'.

  5. Warming effect of dust aerosols modulated by overlapping clouds below

    NASA Astrophysics Data System (ADS)

    Xu, Hui; Guo, Jianping; Wang, Yuan; Zhao, Chuanfeng; Zhang, Zhibo; Min, Min; Miao, Yucong; Liu, Huan; He, Jing; Zhou, Shunwu; Zhai, Panmao

    2017-10-01

    Due to the substantial warming effect of dust aerosols overlying clouds and its poor representation in climate models, it is imperative to accurately quantify the direct radiative forcing (DRF) of above-cloud dust aerosols. When absorbing aerosol layers are located above clouds, the warming effect of aerosols strongly depends on the cloud macro- and micro-physical properties underneath, such as cloud optical depth and cloud fraction at visible wavelength. A larger aerosol-cloud overlap is believed to cause a larger warming effect of absorbing aerosols, but the influence of overlapping cloud fraction and cloud optical depth remains to be explored. In this study, the impact of overlapping cloud properties on the shortwave all-sky DRF due to springtime above-cloud dust aerosols is quantified over northern Pacific Ocean based on 10-year satellite measurements. On average, the DRF is roughly 0.62 Wm-2. Furthermore, the warming effect of dust aerosols linearly increases with both overlapping cloud fraction and cloud optical depth. An increase of 1% in overlapping cloud fraction will amplify this warming effect by 1.11 Wm-2τ-1. For the springtime northern Pacific Ocean, top-of-atmosphere cooling by dust aerosols turns into warming when overlapping cloud fraction is beyond 0.20. The variation of critical cloud optical depth beyond which dust aerosols switch from exerting a net cooling to a net warming effect depends on the concurrent overlapping cloud fraction. When the overlapping cloud coverage range increases from 0.2 to -0.4 to 0.6-0.8, the corresponding critical cloud optical depth reduces from 6.92 to 1.16. Our results demonstrate the importance of overlapping cloud properties for determining the springtime warming effect of dust aerosols.

  6. Detection of Functional Overlapping Genes: Simulation and Case Studies

    PubMed Central

    Sabath, Niv; Graur, Dan

    2010-01-01

    As far as protein-coding genes are concerned, there is a non-zero probability that at least one of the five possible overlapping sequences of any gene will contain an open-reading frame (ORF) of a length that may be suitable for coding a functional protein. It is, however, very difficult to determine whether or not such an ORF is functional. Recently, we proposed a method that predicts functionality of an overlapping ORF if it can be shown that it has been subject to purifying selection during its evolution. Here, we use simulation to test this method under several conditions and compare it with the method of Firth and Brown. We found that under most conditions, our method detects functional overlapping genes with higher sensitivity than Firth and Brown’s method, while maintaining high specificity. Further, we tested the hypothesis that the two aminoacyl tRNA synthetase classes have originated from a pair of overlapping genes. A central piece of evidence ostensibly supporting this hypothesis is the assertion that an overlapping ORF of a heat-shock protein-70 gene, which exhibits some similarity to class 2 aminoacyl tRNA synthetases, is functional. We found signature of purifying selection only in highly divergent sequences, suggesting that the method yields false-positives in high sequence divergence and that the overlapping ORF is not a functional gene. Finally, we examined three cases of overlap in the human genome. We find varying signatures of purifying selection acting on these overlaps, raising the possibility that two of the overlapping genes may not be functional. PMID:20820768

  7. A Boolean Model of the Cardiac Gene Regulatory Network Determining First and Second Heart Field Identity

    PubMed Central

    Zhou, Dao; Kestler, Hans A.; Kühl, Michael

    2012-01-01

    Two types of distinct cardiac progenitor cell populations can be identified during early heart development: the first heart field (FHF) and second heart field (SHF) lineage that later form the mature heart. They can be characterized by differential expression of transcription and signaling factors. These regulatory factors influence each other forming a gene regulatory network. Here, we present a core gene regulatory network for early cardiac development based on published temporal and spatial expression data of genes and their interactions. This gene regulatory network was implemented in a Boolean computational model. Simulations reveal stable states within the network model, which correspond to the regulatory states of the FHF and the SHF lineages. Furthermore, we are able to reproduce the expected temporal expression patterns of early cardiac factors mimicking developmental progression. Additionally, simulations of knock-down experiments within our model resemble published phenotypes of mutant mice. Consequently, this gene regulatory network retraces the early steps and requirements of cardiogenic mesoderm determination in a way appropriate to enhance the understanding of heart development. PMID:23056457

  8. Epidemic threshold determined by the first moments of network with alternating degree distributions

    NASA Astrophysics Data System (ADS)

    Li, Kezan; Zhang, Haifeng; Fu, Xinchu; Ding, Yong; Small, Michael

    2015-02-01

    During the alternating day-night cycle, people have differing behavior and hence different connection patterns-such as going to work or home, shopping and so on. Hence, the true topological structure of human contact networks are not only time-varying but also exhibit certain distribution regularity. In this paper, we will investigate epidemic spreading on time-varying human contact networks, which follow one degree distribution during daytime, but another at night. Based on SIS (susceptible/infected/susceptible) propagation mechanism, we study the epidemic threshold of this network with alternating distributions. A surprising result is that for the discrete-time case the epidemic threshold is determined only by the first moments of the two alternating degree distributions, if the degree of each node is constant for all nights. A similar result is valid for the continuous-time case if the duration is sufficiently small. This work shows that the spreading dynamics of time-varying networks with alternating distributions is completely different from the widely studied case of static spreading networks.

  9. Overlap in Facebook Profiles Reflects Relationship Closeness.

    PubMed

    Castañeda, Araceli M; Wendel, Markie L; Crockett, Erin E

    2015-01-01

    We assessed the association between self-reported Inclusion of Other in the Self (IOS) and Facebook overlap. Ninety-two participants completed online measures of IOS and investment model constructs. Researchers then recorded Facebook data from participants' profile pages. Results from multilevel models revealed that IOS predicted Facebook overlap. Furthermore, Facebook overlap was associated with commitment and investment in ways comparable to self-reported IOS. These findings suggest that overlap in Facebook profiles can be used to measure relationship closeness.

  10. Determination of the dissipative loss of a two-port network from noise temperature measurements

    NASA Technical Reports Server (NTRS)

    Otoshi, T. Y.

    1992-01-01

    When radiometric equipment is available, noise temperature measurement techniques provide a convenient and accurate means for determining the dissipative component of the insertion loss of a two-port network. It is increasingly becoming the practice to ignore mismatch errors caused by multiple reflections between the source, the receiver, and the component whose dissipative loss is being measured. Mismatch errors are difficult to determine in practice because of the requirements of having full knowledge of the magnitudes of reflection coefficients and S-parameters. This article shows it is permissible to neglect the effects of mismatch errors if special conditions are met. These special conditions only require that the reflection coefficients of the source and load be made negligibly small and that the two-port network being evaluated has reciprocal and symmetrical properties.

  11. Determination of DPPH free radical scavenging activity: application of artificial neural networks.

    PubMed

    Musa, Khalid Hamid; Abdullah, Aminah; Al-Haiqi, Ahmed

    2016-03-01

    A new computational approach for the determination of 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity (DPPH-RSA) in food is reported, based on the concept of machine learning. Trolox standard was mix with DPPH at different concentrations to produce different colors from purple to yellow. Artificial neural network (ANN) was trained on a typical set of images of the DPPH radical reacting with different levels of Trolox. This allowed the neural network to classify future images of any sample into the correct class of RSA level. The ANN was then able to determine the DPPH-RSA of cinnamon, clove, mung bean, red bean, red rice, brown rice, black rice and tea extract and the results were compared with data obtained using a spectrophotometer. The application of ANN correlated well to the spectrophotometric classical procedure and thus do not require the use of spectrophotometer, and it could be used to obtain semi-quantitative results of DPPH-RSA.

  12. On Multigrid for Overlapping Grids

    SciTech Connect

    Henshaw, W

    2004-01-13

    The solution of elliptic partial differential equations on composite overlapping grids using multigrid is discussed. An approach is described that provides a fast and memory efficient scheme for the solution of boundary value problems in complex geometries. The key aspects of the new scheme are an automatic coarse grid generation algorithm, an adaptive smoothing technique for adjusting residuals on different component grids, and the use of local smoothing near interpolation boundaries. Other important features include optimizations for Cartesian component grids, the use of over-relaxed Red-Black smoothers and the generation of coarse grid operators through Galerkin averaging. Numerical results in two and three dimensions show that very good multigrid convergence rates can be obtained for both Dirichlet and Neumann/mixed boundary conditions. A comparison to Krylov based solvers shows that the multigrid solver can be much faster and require significantly less memory.

  13. A Contents Analysis of a Commercial TV Network to Determine Negative Conditioning toward Reading Activities.

    ERIC Educational Resources Information Center

    Stura, Sandra

    To provide information concerning television and its impact on reading, a study was conducted to determine if the programing on a commercial television network would reveal a low number of positive references to reading. Programing was observed from 3:00 p. m. until 9:00 p. m. daily and from 9:00 A. M. to noon on Saturdays for a period of three…

  14. Social externalities, overlap and the poverty trap

    PubMed Central

    Kim, Young-Chul; Loury, Glenn C.

    2014-01-01

    Previous studies find that some social groups are stuck in poverty traps because of network effects. However, these studies do not carefully analyze how these groups overcome low human capital investment activities. Unlike previous studies, the model in this paper includes network externalities in both the human capital investment stage and the subsequent career stages. This implies that not only the current network quality, but also the expectations about future network quality affect the current investment decision. Consequently, the coordinated expectation among the group members can play a crucial role in the determination of the final state. We define “overlap” for some initial skill ranges, whereby the economic performance of a group can be improved simply by increasing expectations of a brighter future. We also define “poverty trap” for some ranges, wherein a disadvantaged group is constrained by its history, and we explore the egalitarian policies to mobilize the group out of the trap. PMID:25484637

  15. Intrinsic Disorder in Male Sex Determination: Disorderedness of Proteins from the Sry Transcriptional Network.

    PubMed

    Merone, Jean; Nwogu, Onyekahi; Redington, Jennifer M; Uversky, Vladimir N

    2016-10-28

    Sex differentiation is a complex process where sexually indifferent embryo progressively acquires male or female characteristics via tightly controlled, perfectly timed, and sophisticatedly intertwined chain of events. This process is controlled and regulated by a set of specific proteins, with one of the first steps in sex differentiation being the activation of the Y-chromosomal Sry gene (sex-determining region Y) in males that acts as a switch from undifferentiated gonad somatic cells to testis development. There are several key players in this process, which constitute the Sry transcriptional network, and collective action of which governs testis determination. Although it is accepted now that many proteins engaged in signal transduction as well as regulation and control of various biological processes are intrinsically disordered (i.e., do not have unique structure and remain unstructured, or incompletely structured, under physiological conditions), the roles and profusion of intrinsic disorder in proteins involved in the male sex determination have not been accessed as of yet. The goal of this study is to cover this gap by analyzing some key players of the Sry transcriptional network. To this end, we employed a broad set of computational tools for intrinsic disorder analysis and conducted intensive literature search in order to gain information on the structural peculiarities of the Sry network-related proteins, their intrinsic disorder predispositions, and the roles of intrinsic disorder in their functions.

  16. Tree-average distances on certain phylogenetic networks have their weights uniquely determined.

    PubMed

    Willson, Stephen J

    2012-01-01

    A phylogenetic network N has vertices corresponding to species and arcs corresponding to direct genetic inheritance from the species at the tail to the species at the head. Measurements of DNA are often made on species in the leaf set, and one seeks to infer properties of the network, possibly including the graph itself. In the case of phylogenetic trees, distances between extant species are frequently used to infer the phylogenetic trees by methods such as neighbor-joining. This paper proposes a tree-average distance for networks more general than trees. The notion requires a weight on each arc measuring the genetic change along the arc. For each displayed tree the distance between two leaves is the sum of the weights along the path joining them. At a hybrid vertex, each character is inherited from one of its parents. We will assume that for each hybrid there is a probability that the inheritance of a character is from a specified parent. Assume that the inheritance events at different hybrids are independent. Then for each displayed tree there will be a probability that the inheritance of a given character follows the tree; this probability may be interpreted as the probability of the tree. The tree-average distance between the leaves is defined to be the expected value of their distance in the displayed trees. For a class of rooted networks that includes rooted trees, it is shown that the weights and the probabilities at each hybrid vertex can be calculated given the network and the tree-average distances between the leaves. Hence these weights and probabilities are uniquely determined. The hypotheses on the networks include that hybrid vertices have indegree exactly 2 and that vertices that are not leaves have a tree-child.

  17. Shortest-Path Network Analysis Is a Useful Approach toward Identifying Genetic Determinants of Longevity

    PubMed Central

    Managbanag, J. R.; Witten, Tarynn M.; Bonchev, Danail; Fox, Lindsay A.; Tsuchiya, Mitsuhiro; Kennedy, Brian K.; Kaeberlein, Matt

    2008-01-01

    Background Identification of genes that modulate longevity is a major focus of aging-related research and an area of intense public interest. In addition to facilitating an improved understanding of the basic mechanisms of aging, such genes represent potential targets for therapeutic intervention in multiple age-associated diseases, including cancer, heart disease, diabetes, and neurodegenerative disorders. To date, however, targeted efforts at identifying longevity-associated genes have been limited by a lack of predictive power, and useful algorithms for candidate gene-identification have also been lacking. Methodology/Principal Findings We have utilized a shortest-path network analysis to identify novel genes that modulate longevity in Saccharomyces cerevisiae. Based on a set of previously reported genes associated with increased life span, we applied a shortest-path network algorithm to a pre-existing protein–protein interaction dataset in order to construct a shortest-path longevity network. To validate this network, the replicative aging potential of 88 single-gene deletion strains corresponding to predicted components of the shortest-path longevity network was determined. Here we report that the single-gene deletion strains identified by our shortest-path longevity analysis are significantly enriched for mutations conferring either increased or decreased replicative life span, relative to a randomly selected set of 564 single-gene deletion strains or to the current data set available for the entire haploid deletion collection. Further, we report the identification of previously unknown longevity genes, several of which function in a conserved longevity pathway believed to mediate life span extension in response to dietary restriction. Conclusions/Significance This work demonstrates that shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity and represents the first application of network analysis of aging

  18. A Co-Association Network Analysis of the Genetic Determination of Pig Conformation, Growth and Fatness

    PubMed Central

    Puig-Oliveras, Anna; Ballester, Maria; Corominas, Jordi; Revilla, Manuel; Estellé, Jordi; Fernández, Ana I.; Ramayo-Caldas, Yuliaxis; Folch, Josep M.

    2014-01-01

    Background Several QTLs have been identified for major economically relevant traits in livestock, such as growth and meat quality, revealing the complex genetic architecture of these traits. The use of network approaches considering the interactions of multiple molecules and traits provides useful insights into the molecular underpinnings of complex traits. Here, a network based methodology, named Association Weight Matrix, was applied to study gene interactions and pathways affecting pig conformation, growth and fatness traits. Results The co-association network analysis underpinned three transcription factors, PPARγ, ELF1, and PRDM16 involved in mesoderm tissue differentiation. Fifty-four genes in the network belonged to growth-related ontologies and 46 of them were common with a similar study for growth in cattle supporting our results. The functional analysis uncovered the lipid metabolism and the corticotrophin and gonadotrophin release hormone pathways among the most important pathways influencing these traits. Our results suggest that the genes and pathways here identified are important determining either the total body weight of the animal and the fat content. For instance, a switch in the mesoderm tissue differentiation may determinate the age-related preferred pathways being in the puberty stage those related with the miogenic and osteogenic lineages; on the contrary, in the maturity stage cells may be more prone to the adipocyte fate. Hence, our results demonstrate that an integrative genomic co-association analysis is a powerful approach for identifying new connections and interactions among genes. Conclusions This work provides insights about pathways and key regulators which may be important determining the animal growth, conformation and body proportions and fatness traits. Molecular information concerning genes and pathways here described may be crucial for the improvement of genetic breeding programs applied to pork meat production. PMID:25503799

  19. How events determine spreading patterns: information transmission via internal and external influences on social networks

    NASA Astrophysics Data System (ADS)

    Liu, Chuang; Zhan, Xiu-Xiu; Zhang, Zi-Ke; Sun, Gui-Quan; Hui, Pak Ming

    2015-11-01

    Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo, show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks.

  20. Pathway structure determination in complex stochastic networks with non-exponential dwell times

    SciTech Connect

    Li, Xin; Kolomeisky, Anatoly B.; Valleriani, Angelo

    2014-05-14

    Analysis of complex networks has been widely used as a powerful tool for investigating various physical, chemical, and biological processes. To understand the emergent properties of these complex systems, one of the most basic issues is to determine the structure and topology of the underlying networks. Recently, a new theoretical approach based on first-passage analysis has been developed for investigating the relationship between structure and dynamic properties for network systems with exponential dwell time distributions. However, many real phenomena involve transitions with non-exponential waiting times. We extend the first-passage method to uncover the structure of distinct pathways in complex networks with non-exponential dwell time distributions. It is found that the analysis of early time dynamics provides explicit information on the length of the pathways associated to their dynamic properties. It reveals a universal relationship that we have condensed in one general equation, which relates the number of intermediate states on the shortest path to the early time behavior of the first-passage distributions. Our theoretical predictions are confirmed by extensive Monte Carlo simulations.

  1. Lithology determination from well logs with fuzzy associative memory neural network

    SciTech Connect

    Chang, H.C.; Chen, H.C.; Fang, J.H.

    1997-05-01

    An artificial intelligence technique of fuzzy associative memory is used to determine rock types from well-log signatures. Fuzzy associative memory (FAM) is a hybrid of neutral network and fuzzy expert system. This new approach combines the learning ability of neural network and the strengths of fuzzy linguistic modeling to adaptively infer lithologies from well-log signatures based on (1) the relationships between the lithology and log signature that the neural network have learned during the training and/or (2) geologist`s knowledge about the rocks. The method is applied to a sequence of the Ordovician rock units in northern Kansas. This paper also compares the performances of two different methods, using the same data set for meaningful comparison. The advantages of FAM are (1) expert knowledge acquired by geologists is fully utilized; (2) this knowledge is augmented by the neural network learning from the data, when available; and (3) FAM is transparent in that the knowledge is explicitly stated in the fuzzy rules.

  2. Orthogonal projection approach and continuous wavelet transform-feed forward neural networks for simultaneous spectrophotometric determination of some heavy metals in diet samples.

    PubMed

    Abbasi Tarighat, Maryam

    2016-02-01

    Simultaneous spectrophotometric determination of a mixture of overlapped complexes of Fe(3+), Mn(2+), Cu(2+), and Zn(2+) ions with 2-(3-hydroxy-1-phenyl-but-2-enylideneamino) pyridine-3-ol(HPEP) by orthogonal projection approach-feed forward neural network (OPA-FFNN) and continuous wavelet transform-feed forward neural network (CWT-FFNN) is discussed. Ionic complexes HPEP were formulated with varying reagent concentration, pH and time of color formation for completion of complexation reactions. It was found that, at 5.0 × 10(-4) mol L(-1) of HPEP, pH 9.5 and 10 min after mixing the complexation reactions were completed. The spectral data were analyzed using partial response plots, and identified non-linearity modeled using FFNN. Reducing the number of OPA-FFNN and CWT-FFNN inputs were simplified using dissimilarity pure spectra of OPA and selected wavelet coefficients. Once the pure dissimilarity plots ad optimal wavelet coefficients are selected, different ANN models were employed for the calculation of the final calibration models. The performance of these two approaches were tested with regard to root mean square errors of prediction (RMSE %) values, using synthetic solutions. Under the working conditions, the proposed methods were successfully applied to the simultaneous determination of metal ions in different vegetable and foodstuff samples. The results show that, OPA-FFNN and CWT-FFNN were effective in simultaneously determining Fe(3+), Mn(2+), Cu(2+), and Zn(2+) concentration. Also, concentrations of metal ions in the samples were determined by flame atomic absorption spectrometry (FAAS). The amounts of metal ions obtained by the proposed methods were in good agreement with those obtained by FAAS. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions

    PubMed Central

    Ouyang, Q.

    2016-01-01

    Deduction of biological regulatory networks from their functions is one of the focus areas of systems biology. Among the different techniques used in this reverse-engineering task, one powerful method is to enumerate all candidate network structures to find suitable ones. However, this method is severely limited by calculation capability: due to the brute-force approach, it is infeasible for networks with large number of nodes to be studied using traditional enumeration method because of the combinatorial explosion. In this study, we propose a new reverse-engineering technique based on the enumerating method: sub-network combinations. First, a complex biological function is divided into several sub-functions. Next, the three-node-network enumerating method is applied to search for sub-networks that are able to realize each of the sub-functions. Finally, complex whole networks are constructed by enumerating all possible combinations of sub-networks. The optimal ones are selected and analyzed. To demonstrate the effectiveness of this new method, we used it to deduct the network structures of a Pavlovian-like function. The whole Pavlovian-like network was successfully constructed by combining robust sub-networks, and the results were analyzed. With sub-network combination, the complexity has been largely reduced. Our method also provides a functional modular view of biological systems. PMID:27992476

  4. Determination of relaxation modulus of time-dependent materials using neural networks

    NASA Astrophysics Data System (ADS)

    Aulova, Alexandra; Govekar, Edvard; Emri, Igor

    2017-08-01

    Health monitoring systems for plastic based structures require the capability of real time tracking of changes in response to the time-dependent behavior of polymer based structures. The paper proposes artificial neural networks as a tool of solving inverse problem appearing within time-dependent material characterization, since the conventional methods are computationally demanding and cannot operate in the real time mode. Abilities of a Multilayer Perceptron (MLP) and a Radial Basis Function Neural Network (RBFN) to solve ill-posed inverse problems on an example of determination of a time-dependent relaxation modulus curve segment from constant strain rate tensile test data are investigated. The required modeling data composed of strain rate, tensile and related relaxation modulus were generated using existing closed-form solution. Several neural networks topologies were tested with respect to the structure of input data, and their performance was compared to an exponential fitting technique. Selected optimal topologies of MLP and RBFN were tested for generalization and robustness on noisy data; performance of all the modeling methods with respect to the number of data points in the input vector was analyzed as well. It was shown that MLP and RBFN are capable of solving inverse problems related to the determination of a time dependent relaxation modulus curve segment. Particular topologies demonstrate good generalization and robustness capabilities, where the topology of RBFN with data provided in parallel proved to be superior compared to other methods.

  5. Hierarchical neural network model of the visual system determining figure/ground relation

    NASA Astrophysics Data System (ADS)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  6. Determination of relaxation modulus of time-dependent materials using neural networks

    NASA Astrophysics Data System (ADS)

    Aulova, Alexandra; Govekar, Edvard; Emri, Igor

    2016-10-01

    Health monitoring systems for plastic based structures require the capability of real time tracking of changes in response to the time-dependent behavior of polymer based structures. The paper proposes artificial neural networks as a tool of solving inverse problem appearing within time-dependent material characterization, since the conventional methods are computationally demanding and cannot operate in the real time mode. Abilities of a Multilayer Perceptron (MLP) and a Radial Basis Function Neural Network (RBFN) to solve ill-posed inverse problems on an example of determination of a time-dependent relaxation modulus curve segment from constant strain rate tensile test data are investigated. The required modeling data composed of strain rate, tensile and related relaxation modulus were generated using existing closed-form solution. Several neural networks topologies were tested with respect to the structure of input data, and their performance was compared to an exponential fitting technique. Selected optimal topologies of MLP and RBFN were tested for generalization and robustness on noisy data; performance of all the modeling methods with respect to the number of data points in the input vector was analyzed as well. It was shown that MLP and RBFN are capable of solving inverse problems related to the determination of a time dependent relaxation modulus curve segment. Particular topologies demonstrate good generalization and robustness capabilities, where the topology of RBFN with data provided in parallel proved to be superior compared to other methods.

  7. Void percolation and conduction of overlapping ellipsoids.

    PubMed

    Yi, Y B

    2006-09-01

    The void percolation and conduction problems for equisized overlapping ellipsoids of revolution are investigated using the discretization method. The method is validated by comparing the estimated percolation threshold of spheres with the precise result found in literature. The technique is then extended to determine the threshold of void percolation as a function of the geometric aspect ratio of ellipsoidal particles. The finite element method is also applied to evaluate the equivalent conductivity of the void phase in the system. The results confirm that there are no universalities for void percolation threshold and conductivity in particulate systems, and these properties are clearly dependent on the geometrical shape of particles. As a consequence, void percolation and conduction associated with ellipsoidal particles of large aspect ratio should be treated differently from spheres.

  8. Application of the lamp mapping technique for overlap function for Raman lidar systems.

    PubMed

    Walker, Monique; Venable, Demetrius; Whiteman, David N; Sakai, Tetsu

    2016-04-01

    Traditionally, the lidar water vapor mixing ratio (WVMR) is corrected for overlap using data from another instrument, such as a radiosonde. Here we introduce a new experimental method to determine the overlap function using the lamp mapping technique (LMT), which relies on the lidar optics and detection system. The LMT discussed here involves a standard halogen lamp being scanned over the aperture of a Raman lidar telescope in synchronization with the lidar detection system [Appl. Opt.50, 4622 (2011)APOPAI0003-693510.1364/AO.50.004622, Appl. Opt.53, 8538 (2014)APOPAI0003-693510.1364/AO.53.008535]. In this paper, we show results for a LMT-determined overlap function for individual channels, as well as a WVMR overlap function. We found that the LMT-determined WVMR overlap functions deviate within 5% of the traditional radiosonde-determined overlap.

  9. Spatio-temporal filtering for determination of common mode error in regional GNSS networks

    NASA Astrophysics Data System (ADS)

    Bogusz, Janusz; Gruszczynski, Maciej; Figurski, Mariusz; Klos, Anna

    2015-04-01

    The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

  10. Analysis of a distributed algorithm to determine multiple routes with path diversity in ad hoc networks.

    SciTech Connect

    Ghosal, Dipak; Mueller, Stephen Ng

    2005-04-01

    With multipath routing in mobile ad hoc networks (MANETs), a source can establish multiple routes to a destination for routing data. In MANETs, mulitpath routing can be used to provide route resilience, smaller end-to-end delay, and better load balancing. However, when the multiple paths are close together, transmissions of different paths may interfere with each other, causing degradation in performance. Besides interference, the physical diversity of paths also improves fault tolerance. We present a purely distributed multipath protocol based on the AODV-Multipath (AODVM) protocol called AODVM with Path Diversity (AODVM/PD) that finds multiple paths with a desired degree of correlation between paths specified as an input parameter to the algorithm. We demonstrate through detailed simulation analysis that multiple paths with low degree of correlation determined by AODVM/PD provides both smaller end-to-end delay than AODVM in networks with low mobility and better route resilience in the presence of correlated node failures.

  11. Earth-Mars Telecommunications and Information Management System (TIMS): Antenna Visibility Determination, Network Simulation, and Management Models

    NASA Technical Reports Server (NTRS)

    Odubiyi, Jide; Kocur, David; Pino, Nino; Chu, Don

    1996-01-01

    This report presents the results of our research on Earth-Mars Telecommunications and Information Management System (TIMS) network modeling and unattended network operations. The primary focus of our research is to investigate the feasibility of the TIMS architecture, which links the Earth-based Mars Operations Control Center, Science Data Processing Facility, Mars Network Management Center, and the Deep Space Network of antennae to the relay satellites and other communication network elements based in the Mars region. The investigation was enhanced by developing Build 3 of the TIMS network modeling and simulation model. The results of several 'what-if' scenarios are reported along with reports on upgraded antenna visibility determination software and unattended network management prototype.

  12. Heuristic overlap-exchange model of noble gas chemical shifts

    NASA Astrophysics Data System (ADS)

    Adrian, Frank J.

    2004-05-01

    It is now generally recognized that overlap-exchange interactions are the primary cause of the medium-dependent magnetic shielding (chemical shift) in all noble gases except helium, although the attractive electrostatic-dispersion (van der Waals) interactions play an indirect role in determining the penetration of the interacting species into the repulsive overlap-exchange region. The short-range nature of these overlap-exchange interactions, combined with the fact that they often can be approximated by simple functions of the overlap of the wave functions of the interacting species, suggests a useful semiempirical model of these chemical shifts. In it the total shielding is the sum of shieldings due to pairwise interactions of the noble gas atom with the individual atoms of the medium, with the "atomic" shielding terms either estimated by simple functions of the atomic overlap integrals averaged over their Boltzmann-weighted separations, or determined by fits to experimental data in systems whose complexity makes the former procedure impractical. Results for 129Xe chemical shifts in the noble gases and in a variety of molecular and condensed systems, including families of n-alkanes, straight-chain alcohols, and the endohedral compounds Xe@C60 and Xe@C70 are encouraging for the applicability of the model to systems of technical and biomedical interest.

  13. Solving Partial Differential Equations on Overlapping Grids

    SciTech Connect

    Henshaw, W D

    2008-09-22

    We discuss the solution of partial differential equations (PDEs) on overlapping grids. This is a powerful technique for efficiently solving problems in complex, possibly moving, geometry. An overlapping grid consists of a set of structured grids that overlap and cover the computational domain. By allowing the grids to overlap, grids for complex geometries can be more easily constructed. The overlapping grid approach can also be used to remove coordinate singularities by, for example, covering a sphere with two or more patches. We describe the application of the overlapping grid approach to a variety of different problems. These include the solution of incompressible fluid flows with moving and deforming geometry, the solution of high-speed compressible reactive flow with rigid bodies using adaptive mesh refinement (AMR), and the solution of the time-domain Maxwell's equations of electromagnetism.

  14. Comparing discriminant analysis and neural network for the determination of sex using femur head measurements.

    PubMed

    Alunni, Véronique; Jardin, Philippe du; Nogueira, Luisa; Buchet, Luc; Quatrehomme, Gérald

    2015-08-01

    The measurement of the femoral head is usually considered an interesting variable for the sex determination of skeletal remains. To date, there are few published reference measurements of the femoral head in a modern European population for the purpose of sex determination. In this study, 116 femurs from 58 individuals of the South of France (Nice Bone Collection, Nice, France) were studied. Three measurements of the femoral head were taken: the vertical head diameter (VHD), the transversal head diameter (THD) and the head circumference (HC). The results show that: (i) there is no statistical difference between the right and left femurs for each of the three measurements (VHD, THD and HC). Therefore we arbitrarily chose to use the measures from the right femurs (N=58) to pursue our experiments; (ii) the measurements of the femoral head are similar to those of contemporary American populations; (iii) the dimensions of the femoral head place the measurements of the French population somewhere between Germany or Croatia, and Spain; (iv) there is no significant secular trend (in contrast with the femoral neck diameter); (v) the femoral head measurement as a single variable is useful for sex determination: a 96.5% rate of accuracy was obtained using THD and HC measurements with the artificial neural network; and a 94.8% rate of accuracy using VHD, both with the discriminant analysis and the neural network.

  15. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks.

    PubMed

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-12-15

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.

  16. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    PubMed Central

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. PMID:26694394

  17. Determining electron temperature for small spherical probes from network analyzer measurements of complex impedance

    NASA Astrophysics Data System (ADS)

    Walker, David N.; Fernsler, Richard F.; Blackwell, David D.; Amatucci, William E.

    2008-11-01

    In earlier work, using a network analyzer, we have shown the existence of collisionless resistance (CR) in the sheath of a spherical probe when driven by a small rf signal. As shown in that paper the CR depends on the plasma density gradient at a given location. Because of this there is a cutoff in the CR which is proportional to the applied bias level and which will occur at the plasma frequency at the surface of the probe, r = r0. We show that, in the frequency regime φpi<<φ<<φpe(r0), the complex impedance measurements made with a network analyzer can be used to determine electron temperature. We present an overview of the theory used along with comparisons to data sets made using three small spherical probes of different sizes. The numerical algorithm requires only a solution of the Poisson equation to determine the approximate sheath dimensions and integrals to determine approximate plasma and sheath inductances. We compare the results of the temperature measurements to those made by conventional Langmuir probe sweeps. Walker, D.N., R.F. Fernsler, D.D. Blackwell, W.E. Amatucci, S.J. Messer, Phys of Plasmas, 13, 032108 (2006)

  18. Selected Problems of Determining the Course of Railway Routes by Use of GPS Network Solution

    NASA Astrophysics Data System (ADS)

    Koc, Władysław; Specht, Cezary

    2011-09-01

    The main problem related to railroad surveying design and its maintenance is the necessity to operate in local geodetic reference systems caused by the long rail sections with straight lines and curvatures of the running edge. Due to that reason the geodetic railroad classical surveying methods requires to divide all track for a short measurement section and that caused additional errors. Development of the Global Navigational Satellite Systems (GNSS) positioning methods operating in the standardized World Geodetic System (WGS-84) allowed verification of capability of utilization GPS measurements for railroad surveying. It can be stated that implemented satellite measurement techniques opens a whole new perspective on applied research and enables very precise determination of data for railway line determining, modernization and design. The research works focused on implementation GNSS multi-receivers measurement positioning platform for projecting and stock-taking working based on polish active geodesic network ASG-EUPOS, as a reference frame. In order to eliminate the influence of random measurement errors and to obtain the coordinates representing the actual shape of the track few campaigns were realized in 2009 and 2010. Leica GPS Total station system 1200 SmartRover (with ATX1230 GG antennas) receivers were located in the diameter of the measurement platform. Polish Active Geodetic Network ASG-EUPOS was used as a reference network transmitted Real Time Kinematic Positioning Service according to RTCM 3.1 standard. Optimum time period were selected for GNSS campaign and testing area was chosen without large obstructions. The article presents some surveying results of the measurement campaigns and also discusses the accuracy of the course determination. Analyzes and implementation of results in railroad design process are also discussed.

  19. Overlap syndromes among autoimmune liver diseases.

    PubMed

    Rust, Christian; Beuers, Ulrich

    2008-06-07

    The three major immune disorders of the liver are autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Variant forms of these diseases are generally called overlap syndromes, although there has been no standardised definition. Patients with overlap syndromes present with both hepatitic and cholestatic serum liver tests and have histological features of AIH and PBC or PSC. The AIH-PBC overlap syndrome is the most common form, affecting almost 10% of adults with AIH or PBC. Single cases of AIH and autoimmune cholangitis (AMA-negative PBC) overlap syndrome have also been reported. The AIH-PSC overlap syndrome is predominantly found in children, adolescents and young adults with AIH or PSC. Interestingly, transitions from one autoimmune to another have also been reported in a minority of patients, especially transitions from PBC to AIH-PBC overlap syndrome. Overlap syndromes show a progressive course towards liver cirrhosis and liver failure without treatment. Therapy for overlap syndromes is empiric, since controlled trials are not available in these rare disorders. Anticholestatic therapy with ursodeoxycholic acid is usually combined with immunosuppressive therapy with corticosteroids and/or azathioprine in both AIH-PBC and AIH-PSC overlap syndromes. In end-stage disease, liver transplantation is the treatment of choice.

  20. Overlap syndromes among autoimmune liver diseases

    PubMed Central

    Rust, Christian; Beuers, Ulrich

    2008-01-01

    The three major immune disorders of the liver are autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Variant forms of these diseases are generally called overlap syndromes, although there has been no standardized definition. Patients with overlap syndromes present with both hepatitic and cholestatic serum liver tests and have histological features of AIH and PBC or PSC. The AIH-PBC overlap syndrome is the most common form, affecting almost 10% of adults with AIH or PBC. Single cases of AIH and autoimmune cholangitis (AMA-negative PBC) overlap syndrome have also been reported. The AIH-PSC overlap syndrome is predominantly found in children, adolescents and young adults with AIH or PSC. Interestingly, transitions from one autoimmune to another have also been reported in a minority of patients, especially transitions from PBC to AIH-PBC overlap syndrome. Overlap syndromes show a progressive course towards liver cirrhosis and liver failure without treatment. Therapy for overlap syndromes is empiric, since controlled trials are not available in these rare disorders. Anticholestatic therapy with ursodeoxycholic acid is usually combined with immunosuppressive therapy with corticosteroids and/or azathioprine in both AIH-PBC and AIH-PSC overlap syndromes. In end-stage disease, liver transplantation is the treatment of choice. PMID:18528934

  1. From gene networks underlying sex determination and gonadal differentiation to the development of neural networks regulating sociosexual behavior.

    PubMed

    Crews, David; Lou, Wendy; Fleming, Alison; Ogawa, Sonoko

    2006-12-18

    Genes are not expressed in isolation any more than social behavior has meaning outside of society. Both are in dynamic flux with the immediate environment that the gene/individual finds itself, which in turn establishes the timing, pattern, and conditions of expression. This means that complex behaviors and their genetic underpinnings should be viewed as a cumulative process, or as the result of experiences up to that point in time and, at the same time, as setting the stage for what will follow. The evidence indicates that as experiences accumulate throughout life, early experiences shape how genes/individuals will respond to later experiences, whereas later experiences modify the effects of these earlier experiences. A method of graphically representing and analyzing change in gene and neural networks is presented. Results from several animal model systems will be described to illustrate these methods. First, we will consider the phenomenon of temperature-dependent sex determination in reptiles. We will illustrate how the experience of a particular temperature during a sensitive period of embryogenesis sculpts not only the patterns of expression of genes involved in sex determination and gonadal differentiation but also the morphological, physiological, neuroendocrine, and behavioral traits of the adult phenotype. The second model system concerns the effects of the sex ratio in the litter in rats, and the genotype ratio in the litter of transgenic mice, on the nature and frequency of maternal care and how this in turn influences the patterns of activation of identified neural circuits subserving the offspring's sociosexual behavior when it is an adult.

  2. From gene networks underlying sex determination and gonadal differentiation to the development of neural networks regulating sociosexual behavior

    PubMed Central

    Crews, David; Lou, Wendy; Fleming, Alison; Ogawa, Sonoko

    2008-01-01

    Genes are not expressed in isolation any more than social behavior has meaning outside of society. Both are in dynamic flux with the immediate environment that the gene/individual finds itself, which in turn establishes the timing, pattern, and conditions of expression. This means that complex behaviors and their genetic underpinnings should be viewed as a cumulative process, or as the result of experiences up to that point in time and, at the same time, as setting the stage for what will follow. The evidence indicates that as experiences accumulate throughout life, early experiences shape how genes/individuals will respond to later experiences, whereas later experiences modify the effects of these earlier experiences. A method of graphically representing and analyzing change in gene and neural networks is presented. Results from several animal model systems will be described to illustrate these methods. First, we will consider the phenomenon of temperature-dependent sex determination in reptiles. We will illustrate how the experience of a particular temperature during a sensitive period of embryogenesis sculpts not only the patterns of expression of genes involved in sex determination and gonadal differentiation but also the morphological, physiological, neuroendocrine, and behavioral traits of the adult phenotype. The second model system concerns the effects of the sex ratio in the litter in rats, and the genotype ratio in the litter of transgenic mice, on the nature and frequency of maternal care and how this in turn influences the patterns of activation of identified neural circuits subserving the offspring's sociosexual behavior when it is an adult. PMID:16905124

  3. Unsupervised Learning of Overlapping Image Components Using Divisive Input Modulation

    PubMed Central

    Spratling, M. W.; De Meyer, K.; Kompass, R.

    2009-01-01

    This paper demonstrates that nonnegative matrix factorisation is mathematically related to a class of neural networks that employ negative feedback as a mechanism of competition. This observation inspires a novel learning algorithm which we call Divisive Input Modulation (DIM). The proposed algorithm provides a mathematically simple and computationally efficient method for the unsupervised learning of image components, even in conditions where these elementary features overlap considerably. To test the proposed algorithm, a novel artificial task is introduced which is similar to the frequently-used bars problem but employs squares rather than bars to increase the degree of overlap between components. Using this task, we investigate how the proposed method performs on the parsing of artificial images composed of overlapping features, given the correct representation of the individual components; and secondly, we investigate how well it can learn the elementary components from artificial training images. We compare the performance of the proposed algorithm with its predecessors including variations on these algorithms that have produced state-of-the-art performance on the bars problem. The proposed algorithm is more successful than its predecessors in dealing with overlap and occlusion in the artificial task that has been used to assess performance. PMID:19424442

  4. Interferometric particle sizing with overlapping images despite Moiré

    NASA Astrophysics Data System (ADS)

    Talbi, Mohamed; Brunel, Marc

    2017-10-01

    Interferometric particle imaging is investigated in the case of overlapping images and sub-sampling conditions. It is shown that particle size estimation of a pair of particles remains possible despite Moiré. Particle sizing can be achieved although the determination of the separation between both particles is no longer possible.

  5. Sarcomeric thick and thin filament overlap influences postmortem proteolysis

    USDA-ARS?s Scientific Manuscript database

    The interaction between sarcomere length (SL) and proteolysis on meat tenderness is not clear. Indeed, the extent of thick and thin filament overlap alters actomyosin binding and may alter substrate availability during aging. The objective of this study was to determine the influence of sarcomere le...

  6. A MULTIPLEXED ASSAY FOR DETERMINATION OF NEUROTOXICANT EFFECTS ON SPONTANEOUS NETWORK ACTIVITY AND CELL VIABILITY FROM MICROELECTRODE ARRAYS

    EPA Science Inventory

    AbstractTITLE: A MULTIPLEXED ASSAY FOR DETERMINATION OF NEUROTOXICANT EFFECTS ON SPONTANEOUS NETWORK ACTIVITY AND CELL VIABILITY FROM MICROELECTRODE ARRAYSABSTRACT BODY: Microelectrode array (MEA) recordings are increasingly being used as an in vitro method to detect and characte...

  7. A MULTIPLEXED ASSAY FOR DETERMINATION OF NEUROTOXICANT EFFECTS ON SPONTANEOUS NETWORK ACTIVITY AND CELL VIABILITY FROM MICROELECTRODE ARRAYS

    EPA Science Inventory

    AbstractTITLE: A MULTIPLEXED ASSAY FOR DETERMINATION OF NEUROTOXICANT EFFECTS ON SPONTANEOUS NETWORK ACTIVITY AND CELL VIABILITY FROM MICROELECTRODE ARRAYSABSTRACT BODY: Microelectrode array (MEA) recordings are increasingly being used as an in vitro method to detect and characte...

  8. A note on Cohen's overlapping proportions of normal distributions.

    PubMed

    Grice, James W; Barrett, Paul T

    2014-12-01

    Social scientists are often interested in computing the proportion of overlap and nonoverlap between two normal distributions that are separated by some magnitude. In his popular book, Statistical Power Analysis for the Behavioral Sciences (1988, 2nd ed.), Jacob Cohen provided a table (Table 2.2.1) for determining such proportions from common values of separation. Unfortunately, Cohen's proportions are inconsistent with his explication of the popular index of effect size, d; and his proportions are underestimates of distributional overlap and overestimates of nonoverlap. The authors explain how Cohen derived his values and then provide a revised, corrected table of proportions that also match values presented elsewhere.

  9. Ex vivo determination of chewing patterns using FBG and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Karam, L. Z.; Pegorini, V.; Pitta, C. S. R.; Assmann, T. S.; Cardoso, R.; Kalinowski, H. J.; Silva, J. C. C.

    2014-05-01

    This paper reports the experimental procedures performed in a bovine head for the determination of chewing patterns during the mastication process. Mandible movements during the chewing have been simulated either by using two plasticine materials with different textures or without material. Fibre Bragg grating sensors were fixed in the jaw to monitor the biomechanical forces involved in the chewing process. The acquired signals from the sensors fed the input of an artificial neural network aiming at the classification of the measured chewing patterns for each material used in the experiment. The results obtained from the simulation of the chewing process presented different patterns for the different textures of plasticine, resulting on the determination of three chewing patterns with a classification error of 5%.

  10. Content patterns in topic-based overlapping communities.

    PubMed

    Ríos, Sebastián A; Muñoz, Ricardo

    2014-01-01

    Understanding the underlying community structure is an important challenge in social network analysis. Most state-of-the-art algorithms only consider structural properties to detect disjoint subcommunities and do not include the fact that people can belong to more than one community and also ignore the information contained in posts that users have made. To tackle this problem, we developed a novel methodology to detect overlapping subcommunities in online social networks and a method to analyze the content patterns for each subcommunities using topic models. This paper presents our main contribution, a hybrid algorithm which combines two different overlapping sub-community detection approaches: the first one considers the graph structure of the network (topology-based subcommunities detection approach) and the second one takes the textual information of the network nodes into consideration (topic-based subcommunities detection approach). Additionally we provide a method to analyze and compare the content generated. Tests on real-world virtual communities show that our algorithm outperforms other methods.

  11. Potential spatial overlap of heritage sites and protected areas in a boreal region of northern Canada.

    PubMed

    Leroux, Shawn J; Schmiegelow, Fiona K A; Nagy, John A

    2007-04-01

    Under article 8-J of the Convention on Biological Diversity, governments must engage indigenous and local communities in the designation and management of protected areas. A better understanding of the relationship between community heritage sites and sites identified to protect conventional conservation features could inform conservation-planning exercises on indigenous lands. We examined the potential overlap between Gwich'in First Nations' (Northwest Territories, Canada) heritage sites and areas independently identified for the protection of conventional conservation targets. We designed nine hypothetical protected-area networks with different targets for woodland caribou (Rangifer tarandus caribou) habitat, high-quality wetland areas, representative vegetation types, water bodies, environmentally significant area, territorial parks, and network aggregation. We compared the spatial overlap of heritage sites to these nine protected-area networks. The degree of spatial overlap (Jaccard similarity) between heritage sites and the protected-area networks with moderate or high aggregation was significantly higher (p < 0.001) than random spatial overlap, whereas the overlap between heritage sites and the protected-area networks with no aggregation was not significant or significantly lower (p < 0.001) than random spatial overlap. Our results suggest that protected-area networks designed to capture conventional conservation features may protect key heritage sites but only if the underlying characteristics of these sites are considered. The Gwich'in heritage sites are highly aggregated and only protected-area networks that had moderate and high aggregation had significant overlap with the heritage sites. We suggest that conventional conservation plans incorporate heritage sites into their design criteria to complement conventional conservation targets and effectively protect indigenous heritage sites.

  12. 47 CFR 73.509 - Prohibited overlap.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... operation would involve overlap of signal strength contours with any other station licensed by the... separation Contour of proposed station Contour of other station Co-channel 0.1mV/m (40 dBu)1 mV/m (60 dBu) 1... if the proposed operation would involve overlap of signal strength contours with any other station...

  13. 47 CFR 73.509 - Prohibited overlap.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... operation would involve overlap of signal strength contours with any other station licensed by the... separation Contour of proposed station Contour of other station Co-channel 0.1mV/m (40 dBu)1 mV/m (60 dBu) 1... if the proposed operation would involve overlap of signal strength contours with any other station...

  14. 47 CFR 73.509 - Prohibited overlap.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... operation would involve overlap of signal strength contours with any other station licensed by the... separation Contour of proposed station Contour of other station Co-channel 0.1mV/m (40 dBu)1 mV/m (60 dBu) 1... if the proposed operation would involve overlap of signal strength contours with any other station...

  15. Fast evaluation and locality of overlap fermions

    NASA Astrophysics Data System (ADS)

    Bietenholz, W.; Hip, I.; Schilling, K.

    2002-03-01

    In order to construct improved overlap fermions, we start from a short ranged approximate Ginsparg-Wilson fermion and insert it into the overlap formula. We show that its polynomial evaluation is accelerated considerably compared to the standard Neuberger fermion. In addition the degree of locality is strongly improved.

  16. Fast evaluation and locality of overlap fermions

    NASA Astrophysics Data System (ADS)

    Bietenholz, W.; Hip, I.; Schilling, K.

    In order to construct improved overlap fermions, we start from a short ranged approximate Ginsparg-Wilson fermion and insert it into the overlap formula. We show that its polynomial evaluation is accelerated considerably compared to the standard Neuberger fermion. In addition the degree of locality is strongly improved.

  17. Neural overlap in processing music and speech.

    PubMed

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing.

  18. Neural overlap in processing music and speech

    PubMed Central

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  19. Determining minimum set of driver nodes in protein-protein interaction networks.

    PubMed

    Zhang, Xiao-Fei; Ou-Yang, Le; Zhu, Yuan; Wu, Meng-Yun; Dai, Dao-Qing

    2015-05-07

    Recently, several studies have drawn attention to the determination of a minimum set of driver proteins that are important for the control of the underlying protein-protein interaction (PPI) networks. In general, the minimum dominating set (MDS) model is widely adopted. However, because the MDS model does not generate a unique MDS configuration, multiple different MDSs would be generated when using different optimization algorithms. Therefore, among these MDSs, it is difficult to find out the one that represents the true driver set of proteins. To address this problem, we develop a centrality-corrected minimum dominating set (CC-MDS) model which includes heterogeneity in degree and betweenness centralities of proteins. Both the MDS model and the CC-MDS model are applied on three human PPI networks. Unlike the MDS model, the CC-MDS model generates almost the same sets of driver proteins when we implement it using different optimization algorithms. The CC-MDS model targets more high-degree and high-betweenness proteins than the uncorrected counterpart. The more central position allows CC-MDS proteins to be more important in maintaining the overall network connectivity than MDS proteins. To indicate the functional significance, we find that CC-MDS proteins are involved in, on average, more protein complexes and GO annotations than MDS proteins. We also find that more essential genes, aging genes, disease-associated genes and virus-targeted genes appear in CC-MDS proteins than in MDS proteins. As for the involvement in regulatory functions, the sets of CC-MDS proteins show much stronger enrichment of transcription factors and protein kinases. The results about topological and functional significance demonstrate that the CC-MDS model can capture more driver proteins than the MDS model. Based on the results obtained, the CC-MDS model presents to be a powerful tool for the determination of driver proteins that can control the underlying PPI networks. The software

  20. Determination of the Human Cardiomyocyte mRNA and miRNA Differentiation Network by Fine-Scale Profiling

    PubMed Central

    Babiarz, Joshua E.; Ravon, Morgane; Sridhar, Sriram; Ravindran, Palanikumar; Swanson, Brad; Bitter, Hans; Weiser, Thomas; Chiao, Eric; Certa, Ulrich

    2012-01-01

    To gain insight into the molecular regulation of human heart development, a detailed comparison of the mRNA and miRNA transcriptomes across differentiating human-induced pluripotent stem cell (hiPSC)–derived cardiomyocytes and biopsies from fetal, adult, and hypertensive human hearts was performed. Gene ontology analysis of the mRNA expression levels of the hiPSCs differentiating into cardiomyocytes revealed 3 distinct groups of genes: pluripotent specific, transitional cardiac specification, and mature cardiomyocyte specific. Hierarchical clustering of the mRNA data revealed that the transcriptome of hiPSC cardiomyocytes largely stabilizes 20 days after initiation of differentiation. Nevertheless, analysis of cells continuously cultured for 120 days indicated that the cardiomyocytes continued to mature toward a more adult-like gene expression pattern. Analysis of cardiomyocyte-specific miRNAs (miR-1, miR-133a/b, and miR-208a/b) revealed an miRNA pattern indicative of stem cell to cardiomyocyte specification. A biostatistitical approach integrated the miRNA and mRNA expression profiles revealing a cardiomyocyte differentiation miRNA network and identified putative mRNAs targeted by multiple miRNAs. Together, these data reveal the miRNA network in human heart development and support the notion that overlapping miRNA networks re-enforce transcriptional control during developmental specification. PMID:22050602

  1. Auditing Complex Concepts in Overlapping Subsets of SNOMED

    PubMed Central

    Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A.; Hripcsak, George

    2008-01-01

    Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries. PMID:18998838

  2. Template overlap method for massive jets

    NASA Astrophysics Data System (ADS)

    Almeida, Leandro G.; Lee, Seung J.; Perez, Gilad; Sterman, George; Sung, Ilmo

    2010-09-01

    We introduce a new class of infrared safe jet observables, which we refer to as template overlaps, designed to filter targeted highly-boosted particle decays from QCD jets and other background. Template overlaps are functional measures that quantify how well the energy flow of a physical jet matches the flow of a boosted partonic decay. Any region of the partonic phase space for the boosted decays defines a template. We will refer to the maximum functional overlap found this way as the template overlap. To illustrate the method, we test lowest-order templates designed to distinguish highly-boosted top and Higgs decays from backgrounds produced by event generators. For the functional overlap, we find good results with a simple construction based on a Gaussian in energy differences within angular regions surrounding the template partons. Although different event generators give different averages for our template overlaps, we find in each case excellent rejection power, especially when combined with cuts based on jet shapes. The template overlaps are capable of systematic improvement by including higher-order corrections in the template phase space.

  3. Asteroseismic determination of fundamental parameters of Sun-like stars using multilayered neural networks

    NASA Astrophysics Data System (ADS)

    Verma, Kuldeep; Hanasoge, Shravan; Bhattacharya, Jishnu; Antia, H. M.; Krishnamurthi, Ganapathy

    2016-10-01

    The advent of space-based observatories such as Convection, Rotation and planetary Transits (CoRoT) and Kepler has enabled the testing of our understanding of stellar evolution on thousands of stars. Evolutionary models typically require five input parameters, the mass, initial helium abundance, initial metallicity, mixing length (assumed to be constant over time), and the age to which the star must be evolved. Some of these parameters are also very useful in characterizing the associated planets and in studying Galactic archaeology. How to obtain these parameters from observations rapidly and accurately, specifically in the context of surveys of thousands of stars, is an outstanding question, one that has eluded straightforward resolution. For a given star, we typically measure the effective temperature and surface metallicity spectroscopically and low-degree oscillation frequencies through space observatories. Here we demonstrate that statistical learning, using artificial neural networks, is successful in determining the evolutionary parameters based on spectroscopic and seismic measurements. Our trained networks show robustness over a broad range of parameter space, and critically, are entirely computationally inexpensive and fully automated. We analyse the observations of a few stars using this method and the results compare well to inferences obtained using other techniques. This method is both computationally cheap and inferentially accurate, paving the way for analysing the vast quantities of stellar observations from past, current, and future missions.

  4. Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

    PubMed Central

    Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

    2013-01-01

    Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors. PMID:24453846

  5. Determination of important topographic factors for landslide mapping analysis using MLP network.

    PubMed

    Alkhasawneh, Mutasem Sh; Ngah, Umi Kalthum; Tay, Lea Tien; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

    2013-01-01

    Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

  6. Overlaps among phenological phases in flood plain forest ecosystem

    NASA Astrophysics Data System (ADS)

    Bartošová, Lenka; Bauer, Zdeněk; Trnka, Miroslav; Možný, Martin; Štěpánek, Petr; Žalud, Zdeněk

    2015-04-01

    There is a growing concern that climate change has significant impacts on species phenology, seasonal population dynamics, and thus interaction (a)synchrony between species. Species that have historically undergone life history events on the same seasonal calendar may lose synchrony and therefore lose the ability to interact as they have in the past. In view of the match/mismatch hypothesis, the different extents or directions of the phenological shifts among interacting species may have significant implications for community structure and dynamics. That's why our principal goal of the study is to determine the phenological responses within the ecosystem of flood plain forest and analyzed the phenological overlapping among each phenological periods of given species. The phenological observations were done at flood-plain forest experimental site during the period 1961-2012. The whole ecosystem in this study create 17 species (15 plants and 2 bird species) and each species is composed of 2 phenological phases. Phenological periods of all species of ecosystem overlap each other and 43 of these overlapping were chosen and the length, trend and correlation with temperature were elaborated. The analysis of phenophases overlapping of chosen species showed that the length of overlay is getting significantly shorter in 1 case. On the other hand the situation when the length of overlaps is getting significantly longer arose in 4 cases. Remaining overlaps (38) of all phenological periods among various species is getting shorter or longer but with no significance or have not changed anyhow. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248. and of projects no. LD13030 supporting participation of the Czech Republic in the COST action ES1106.

  7. [Asthma and chronic obstructive pulmonary disease overlap].

    PubMed

    Müller, Veronika; Gálffy, Gabriella; Tamási, Lilla

    2011-01-16

    Asthma bronchiale and chronic obstructive pulmonary disease are the most prevalent lung diseases characterized by inflammation of the airways. International and Hungarian guidelines provide proper definitions for clinical symptoms, diagnostics and therapy of both diseases. However, in everyday clinical practice, overlap of asthma and chronic obstructive pulmonary disease has become more frequent. As guidelines are mainly based on large, multicenter, randomized, controlled trials that exclude overlap patients, there is a lack of diagnostic and especially therapeutic strategies for these patients. This review summarizes clinical characteristics of asthma and chronic obstructive pulmonary disease overlap, and provides daily practical examples for its management.

  8. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  9. Neural networks for real time determination of radiated power in JET

    NASA Astrophysics Data System (ADS)

    Barana, O.; Murari, A.; Franz, P.; Ingesson, L. C.; Manduchi, G.

    2002-05-01

    This article describes the use of neural networks (NNs) for the on-line computation of the radiated power in JET. The NNs have been trained using a database of about 120 discharges, for which the emitted power had been calculated via tomographic inversion of JET bolometric signals. In addition to the bolometric data, elongation and triangularity have been used as input to the NN, since these provide useful complementary information. Dedicated NNs have been designed for the determination of the total radiated power, the power from the bulk, and from the divertor region. All the NNs have been tested with a set of about 30 discharges with positive results. Moreover, the NNs can operate at full sampling speed and are therefore suited to follow edge localized modes and other rapid phenomena. The sensitivity of the NNs to failures in the input signals has also been tested, proving their robustness. Their possible use in feedback applications is finally briefly discussed.

  10. Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method.

    PubMed

    Isik, Nimet

    2016-04-01

    Multi-element electrostatic aperture lens systems are widely used to control electron or charged particle beams in many scientific instruments. By means of applied voltages, these lens systems can be operated for different purposes. In this context, numerous methods have been performed to calculate focal properties of these lenses. In this study, an artificial neural network (ANN) classification method is utilized to determine the focused/unfocused charged particle beam in the image point as a function of lens voltages for multi-element electrostatic aperture lenses. A data set for training and testing of ANN is taken from the SIMION 8.1 simulation program, which is a well known and proven accuracy program in charged particle optics. Mean squared error results of this study indicate that the ANN classification method provides notable performance characteristics for electrostatic aperture zoom lenses.

  11. Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination

    PubMed Central

    Wu, Fuqing; Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao

    2017-01-01

    The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation. DOI: http://dx.doi.org/10.7554/eLife.23702.001 PMID:28397688

  12. Determining nanocapillary geometry from electrochemical impedance spectroscopy using a variable topology network circuit model.

    PubMed

    Vitarelli, Michael J; Prakash, Shaurya; Talaga, David S

    2011-01-15

    Solid-state nanopores and nanocapillaries find increasing use in a variety of applications including DNA sequencing, synthetic nanopores, next-generation membranes for water purification, and other nanofluidic structures. This paper develops the use of electrochemical impedance spectroscopy to determine the geometry of nanocapillaries. A network equivalent circuit element is derived to include the effects of the capacitive double layer inside the nanocapillaries as well as the influence of varying nanocapillary radius. This variable topology function is similar to the finite Warburg impedance in certain limits. Analytical expressions for several different nanocapillary shapes are derived. The functions are evaluated to determine how the impedance signals will change with different nanocapillary aspect ratios and different degrees of constriction or inflation at the capillary center. Next, the complex impedance spectrum of a nanocapillary array membrane is measured at varying concentrations of electrolyte to separate the effects of nanocapillary double layer capacitance from those of nanocapillary geometry. The variable topology equivalent circuit element model of the nanocapillary is used in an equivalent circuit model that included contributions from the membrane and the measurement apparatus. The resulting values are consistent with the manufacturer's specified tolerances of the nanocapillary geometry. It is demonstrated that electrochemical impedance spectroscopy can be used as a tool for in situ determination of the geometry of nanocapillaries.

  13. Mapping the nomological network of employee self-determined safety motivation: A preliminary measure in China.

    PubMed

    Jiang, Li; Tetrick, Lois E

    2016-09-01

    The present study introduced a preliminary measure of employee safety motivation based on the definition of self-determination theory from Fleming (2012) research and validated the structure of self-determined safety motivation (SDSM) by surveying 375 employees in a Chinese high-risk organization. First, confirmatory factor analysis (CFA) was used to examine the factor structure of SDSM, and indices of five-factor model CFA met the requirements. Second, a nomological network was examined to provide evidence of the construct validity of SDSM. Beyond construct validity, the analysis also produced some interesting results concerning the relationship between leadership antecedents and safety motivation, and between safety motivation and safety behavior. Autonomous motivation was positively related to transformational leadership, negatively related to abusive supervision, and positively related to safety behavior. Controlled motivation with the exception of introjected regulation was negatively related to transformational leadership, positively related to abusive supervision, and negatively related to safety behavior. The unique role of introjected regulation and future research based on self-determination theory were discussed.

  14. Efficient construction of robust artificial neural networks for accurate determination of superficial sample optical properties.

    PubMed

    Chen, Yu-Wen; Tseng, Sheng-Hao

    2015-03-01

    In general, diffuse reflectance spectroscopy (DRS) systems work with photon diffusion models to determine the absorption coefficient μa and reduced scattering coefficient μs' of turbid samples. However, in some DRS measurement scenarios, such as using short source-detector separations to investigate superficial tissues with comparable μa and μs', photon diffusion models might be invalid or might not have analytical solutions. In this study, a systematic workflow of constructing a rapid, accurate photon transport model that is valid at short source-detector separations (SDSs) and at a wide range of sample albedo is revealed. To create such a model, we first employed a GPU (Graphic Processing Unit) based Monte Carlo model to calculate the reflectance at various sample optical property combinations and established a database at high speed. The database was then utilized to train an artificial neural network (ANN) for determining the sample absorption and reduced scattering coefficients from the reflectance measured at several SDSs without applying spectral constraints. The robustness of the produced ANN model was rigorously validated. We evaluated the performance of a successfully trained ANN using tissue simulating phantoms. We also determined the 500-1000 nm absorption and reduced scattering spectra of in-vivo skin using our ANN model and found that the values agree well with those reported in several independent studies.

  15. Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination.

    PubMed

    Wu, Fuqing; Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao

    2017-04-11

    The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation.

  16. Analytical and numerical solutions to the amplifier with incoherent pulse temporal overlap

    NASA Astrophysics Data System (ADS)

    Li, M.; Zhang, X. M.; Wang, Z. G.; Cui, X. D.; Yan, X. W.; Jiang, X. Y.; Zheng, J. G.; Wang, W.; Li, Mingzhong

    2017-01-01

    Serious pulse temporal overlap in amplifiers would result in the decrease of energy extraction efficiency and the increase of pulse-shape distortion (PSD). Precisely predicting pulse temporal overlap is of significance to an effective amplifier design. In this work, the analytical expressions with complete pulse overlap are derived and a numerical method is proposed to solve the case with partial temporal overlap for a double-pass Nd:YAG amplifier. Our studies, in which pulse temporal overlap is taken into account, can precisely predict the output energy and temporal shape, compared to the results from Hirano and other experiments. In addition, our numerical routes could provide the applicable range of analytical solutions to conventional Frantz-Nodvik equations in the case of pulse overlap, further extending the applicability and reducing computational costs. For given conditions, energy reduction and PSD are mainly determined by the overlap degree. For step-shaped pulse, we demonstrate that avoiding overlap in the peak pulse and allowing overlap in the foot pulse have small impacts on the energy extraction and PSD, which extends the range of duration of the pulse for a designed amplifier. Our investigations might provide an efficient way to carefully design a pulsed amplifier with controllable temporal overlap.

  17. Continuum percolation of congruent overlapping spherocylinders

    NASA Astrophysics Data System (ADS)

    Xu, Wenxiang; Su, Xianglong; Jiao, Yang

    2016-09-01

    Continuum percolation of randomly orientated congruent overlapping spherocylinders (composed of cylinder of height H with semispheres of diameter D at the ends) with aspect ratio α =H /D in [0 ,∞ ) is studied. The percolation threshold ϕc, percolation transition width Δ, and correlation-length critical exponent ν for spherocylinders with α in [0, 200] are determined with a high degree of accuracy via extensive finite-size scaling analysis. A generalized excluded-volume approximation for percolation threshold with an exponent explicitly depending on both aspect ratio and excluded volume for arbitrary α values in [0 ,∞ ) is proposed and shown to yield accurate predictions of ϕc for an extremely wide range of α in [0, 2000] based on available numerical and experimental data. We find ϕc is a universal monotonic decreasing function of α and is independent of the effective particle size. Our study has implications in percolation theory for nonspherical particles and composite material design.

  18. Base drive and overlap protection circuit

    DOEpatents

    Gritter, David J.

    1983-01-01

    An inverter (34) which provides power to an A. C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A. C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A. C. machine is optimized. The control circuit includes a microcomputer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). A base drive and overlap protection circuit is included to insure that both transistors of a complimentary pair are not conducting at the same time. In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

  19. Effect of Receiver Choosing on Point Positions Determination in Network RTK

    NASA Astrophysics Data System (ADS)

    Bulbul, Sercan; Inal, Cevat

    2016-04-01

    Nowadays, the developments in GNSS technique allow to determinate point positioning in real time. Initially, point positioning was determined by RTK (Real Time Kinematic) based on a reference station. But, to avoid systematic errors in this method, distance between the reference points and rover receiver must be shorter than10 km. To overcome this restriction in RTK method, the idea of setting more than one reference point had been suggested and, CORS (Continuously Operations Reference Systems) was put into practice. Today, countries like ABD, Germany, Japan etc. have set CORS network. CORS-TR network which has 146 reference points has also been established in 2009 in Turkey. In CORS-TR network, active CORS approach was adopted. In Turkey, CORS-TR reference stations covering whole country are interconnected and, the positions of these stations and atmospheric corrections are continuously calculated. In this study, in a selected point, RTK measurements based on CORS-TR, were made with different receivers (JAVAD TRIUMPH-1, TOPCON Hiper V, MAGELLAN PRoMark 500, PENTAX SMT888-3G, SATLAB SL-600) and with different correction techniques (VRS, FKP, MAC). In the measurements, epoch interval was taken as 5 seconds and measurement time as 1 hour. According to each receiver and each correction technique, means and differences between maximum and minimum values of measured coordinates, root mean squares in the directions of coordinate axis and 2D and 3D positioning precisions were calculated, the results were evaluated by statistical methods and the obtained graphics were interpreted. After evaluation of the measurements and calculations, for each receiver and each correction technique; the coordinate differences between maximum and minimum values were measured to be less than 8 cm, root mean squares in coordinate axis directions less than ±1.5 cm, 2D point positioning precisions less than ±1.5 cm and 3D point positioning precisions less than ±1.5 cm. In the measurement

  20. Entry Abort Determination Using Non-Adaptive Neural Networks for Mars Precision Landers

    NASA Technical Reports Server (NTRS)

    Graybeal, Sarah R.; Kranzusch, Kara M.

    2005-01-01

    The 2009 Mars Science Laboratory (MSL) will attempt the first precision landing on Mars using a modified version of the Apollo Earth entry guidance program. The guidance routine, Entry Terminal Point Controller (ETPC), commands the deployment of a supersonic parachute after converging the range to the landing target. For very dispersed cases, ETPC may not converge the range to the target and safely command parachute deployment within Mach number and dynamic pressure constraints. A full-lift up abort can save 85% of these failed trajectories while abandoning the precision landing objective. Though current MSL requirements do not call for an abort capability, an autonomous abort capability may be desired, for this mission or future Mars precision landers, to make the vehicle more robust. The application of artificial neural networks (NNs) as an abort determination technique was evaluated by personnel at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC). In order to implement an abort, a failed trajectory needs to be recognized in real time. Abort determination is dependent upon several trajectory parameters whose relationships to vehicle survival are not well understood, and yet the lander must be trained to recognize unsafe situations. Artificial neural networks (NNs) provide a way to model these parameters and can provide MSL with the artificial intelligence necessary to independently declare an abort. Using the 2009 Mars Science Laboratory (MSL) mission as a case study, a non-adaptive NN was designed, trained and tested using Monte Carlo simulations of MSL descent and incorporated into ETPC. Neural network theory, the development history of the MSL NN, and initial testing with severe dust storm entry trajectory cases are discussed in Reference 1 and will not be repeated here. That analysis demonstrated that NNs are capable of recognizing failed descent trajectories and can significantly increase the survivability of MSL for very

  1. Entry Abort Determination Using Non-Adaptive Neural Networks for Mars Precision Landers

    NASA Technical Reports Server (NTRS)

    Graybeal, Sarah R.; Kranzusch, Kara M.

    2005-01-01

    The 2009 Mars Science Laboratory (MSL) will attempt the first precision landing on Mars using a modified version of the Apollo Earth entry guidance program. The guidance routine, Entry Terminal Point Controller (ETPC), commands the deployment of a supersonic parachute after converging the range to the landing target. For very dispersed cases, ETPC may not converge the range to the target and safely command parachute deployment within Mach number and dynamic pressure constraints. A full-lift up abort can save 85% of these failed trajectories while abandoning the precision landing objective. Though current MSL requirements do not call for an abort capability, an autonomous abort capability may be desired, for this mission or future Mars precision landers, to make the vehicle more robust. The application of artificial neural networks (NNs) as an abort determination technique was evaluated by personnel at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC). In order to implement an abort, a failed trajectory needs to be recognized in real time. Abort determination is dependent upon several trajectory parameters whose relationships to vehicle survival are not well understood, and yet the lander must be trained to recognize unsafe situations. Artificial neural networks (NNs) provide a way to model these parameters and can provide MSL with the artificial intelligence necessary to independently declare an abort. Using the 2009 Mars Science Laboratory (MSL) mission as a case study, a non-adaptive NN was designed, trained and tested using Monte Carlo simulations of MSL descent and incorporated into ETPC. Neural network theory, the development history of the MSL NN, and initial testing with severe dust storm entry trajectory cases are discussed in Reference 1 and will not be repeated here. That analysis demonstrated that NNs are capable of recognizing failed descent trajectories and can significantly increase the survivability of MSL for very

  2. Rigidity and soft percolation in the glass transition of an atomistic model of ionic liquid, 1-ethyl-3-methyl imidazolium nitrate, from molecular dynamics simulations—Existence of infinite overlapping networks in a fragile ionic liquid

    SciTech Connect

    Habasaki, Junko; Ngai, K. L.

    2015-04-28

    The typical ionic liquid, 1-ethyl-3-methyl imidazolium nitrate (EMIM-NO{sub 3}), was examined by molecular dynamics simulations of an all-atomistic model to show the characteristics of networks of cages and/or bonds in the course of vitrification of this fragile glass-former. The system shows changes of dynamics at two characteristic temperatures, T{sub B} (or T{sub c}) and the glass transition temperature T{sub g}, found in other fragile glass forming liquids [K. L. Ngai and J. Habasaki, J. Chem. Phys. 141, 114502 (2014)]. On decreasing temperature, the number of neighboring cation-anion pairs, N{sub B}, within the first minimum of the pair correlation function, g(r){sub min}, increases. On crossing T{sub B} (>T{sub g}), the system volume and diffusion coefficient both show changes in temperature dependence, and as usual at T{sub g}. The glass transition temperature, T{sub g}, is characterized by the saturation of the total number of “bonds,” N{sub B} and the corresponding decrease in degree of freedom, F = [(3N − 6) − N{sub B}], of the system consisting of N particles. Similar behavior holds for the other ion-ion pairs. Therefore, as an alternative, the dynamics of glass transition can be interpreted conceptually by rigidity percolation. Before saturation occurring at T{sub g}, the number of bonds shows a remarkable change at around T{sub B}. This temperature is associated with the disappearance of the loosely packed coordination polyhedra of anions around cation (or vice versa), related to the loss of geometrical freedom of the polyhedra, f{sub g}, of each coordination polyhedron, which can be defined by f{sub g} = [(3N{sub V} − 6) − N{sub b}]. Here, 3N{sub v} is the degree of freedom of N{sub V} vertices of the polyhedron, and N{sub b} is number of fictive bonds. The packing of polyhedra is characterized by the soft percolation of cages, which allows further changes with decreasing temperature. The power spectrum of displacement of the central ion

  3. Rigidity and soft percolation in the glass transition of an atomistic model of ionic liquid, 1-ethyl-3-methyl imidazolium nitrate, from molecular dynamics simulations--Existence of infinite overlapping networks in a fragile ionic liquid.

    PubMed

    Habasaki, Junko; Ngai, K L

    2015-04-28

    The typical ionic liquid, 1-ethyl-3-methyl imidazolium nitrate (EMIM-NO3), was examined by molecular dynamics simulations of an all-atomistic model to show the characteristics of networks of cages and/or bonds in the course of vitrification of this fragile glass-former. The system shows changes of dynamics at two characteristic temperatures, TB (or Tc) and the glass transition temperature Tg, found in other fragile glass forming liquids [K. L. Ngai and J. Habasaki, J. Chem. Phys. 141, 114502 (2014)]. On decreasing temperature, the number of neighboring cation-anion pairs, NB, within the first minimum of the pair correlation function, g(r)min, increases. On crossing TB (>Tg), the system volume and diffusion coefficient both show changes in temperature dependence, and as usual at Tg. The glass transition temperature, Tg, is characterized by the saturation of the total number of "bonds," NB and the corresponding decrease in degree of freedom, F = [(3N - 6) - NB], of the system consisting of N particles. Similar behavior holds for the other ion-ion pairs. Therefore, as an alternative, the dynamics of glass transition can be interpreted conceptually by rigidity percolation. Before saturation occurring at Tg, the number of bonds shows a remarkable change at around TB. This temperature is associated with the disappearance of the loosely packed coordination polyhedra of anions around cation (or vice versa), related to the loss of geometrical freedom of the polyhedra, fg, of each coordination polyhedron, which can be defined by fg = [(3NV - 6) - Nb]. Here, 3Nv is the degree of freedom of NV vertices of the polyhedron, and Nb is number of fictive bonds. The packing of polyhedra is characterized by the soft percolation of cages, which allows further changes with decreasing temperature. The power spectrum of displacement of the central ion in the cage is found to be correlated with the fluctuation of Nb of cation-cation (or anion-anion) pairs in the polyhedron, although the

  4. Determination of multifractal dimensions of complex networks by means of the sandbox algorithm

    NASA Astrophysics Data System (ADS)

    Liu, Jin-Long; Yu, Zu-Guo; Anh, Vo

    2015-02-01

    Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we employ the sandbox (SB) algorithm proposed by Tél et al. (Physica A 159, 155-166 (1989)), for MFA of complex networks. First, we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning algorithm proposed by Furuya and Yakubo (Phys. Rev. E 84, 036118 (2011)), and the improved box-counting algorithm proposed by Li et al. (J. Stat. Mech.: Theor. Exp. 2014, P02020 (2014)) by calculating the mass exponents τ(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents τ(q) and to explore the multifractal behavior of complex networks. Then, we apply the SB algorithm to study the multifractal property of some classic model networks, such as scale-free networks, small-world networks, and random networks. Our results show that multifractality exists in scale-free networks, that of small-world networks is not obvious, and it almost does not exist in random networks.

  5. Determination of multifractal dimensions of complex networks by means of the sandbox algorithm.

    PubMed

    Liu, Jin-Long; Yu, Zu-Guo; Anh, Vo

    2015-02-01

    Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we employ the sandbox (SB) algorithm proposed by Tél et al. (Physica A 159, 155-166 (1989)), for MFA of complex networks. First, we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning algorithm proposed by Furuya and Yakubo (Phys. Rev. E 84, 036118 (2011)), and the improved box-counting algorithm proposed by Li et al. (J. Stat. Mech.: Theor. Exp. 2014, P02020 (2014)) by calculating the mass exponents τ(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents τ(q) and to explore the multifractal behavior of complex networks. Then, we apply the SB algorithm to study the multifractal property of some classic model networks, such as scale-free networks, small-world networks, and random networks. Our results show that multifractality exists in scale-free networks, that of small-world networks is not obvious, and it almost does not exist in random networks.

  6. Experimental and numerical determination of the correlation function of level velocities for microwave networks simulating quantum graphs

    NASA Astrophysics Data System (ADS)

    Ławniczak, Michał; Nicolau-Kuklińska, Agata; Hul, Oleh; Masiak, Paweł; Bauch, Szymon; Sirko, Leszek

    2013-03-01

    The parameter-dependent correlation function \\tilde {c}_{\\delta }(\\omega ,\\mathsf {x}) of level velocities is studied experimentally and numerically. The measurements were made for microwave networks simulating quantum graphs. One- and two-port measurements of the scattering matrix \\hat {S} necessary for determining the correlation function \\tilde {c}_{\\delta }(\\omega ,\\mathsf {x}) were realized for the five vertices networks. For the fully connected six vertices network, one-port measurements were made. The obtained experimental and numerical results are compared with the predictions of random matrix theory.

  7. Determinants on the quality of social networks among Hong Kong Chinese.

    PubMed

    Rochelle, Tina L; Chan, O F

    2015-01-01

    The aim of the present study is to examine prospectively the quality of social networks of Hong Kong Chinese adults. A randomized household survey was employed. A total of 1170 Hong Kong Chinese respondents were recruited to the study. Participants ranged in age from 18 to 79 years, 43% of respondents were male. Findings revealed a negative association between familial trust and social network size. Network trust, social identification, and structural networks were all found to be positively associated with social network size and perceived respect from social network. The importance of family and the prioritization of the needs of the family over individual needs has implications on social network size and formation for Hong Kong Chinese individuals. More research is needed to further examine the importance of familial relationships and the prioritization of family and the impact this has on social network development and maintenance among Hong Kong Chinese.

  8. Overlapping Antisense Transcription in the Human Genome

    PubMed Central

    Fahey, M. E.; Moore, T. F.

    2002-01-01

    Accumulating evidence indicates an important role for non-coding RNA molecules in eukaryotic cell regulation. A small number of coding and non-coding overlapping antisense transcripts (OATs) in eukaryotes have been reported, some of which regulate expression of the corresponding sense transcript. The prevalence of this phenomenon is unknown, but there may be an enrichment of such transcripts at imprinted gene loci. Taking a bioinformatics approach, we systematically searched a human mRNA database (RefSeq) for complementary regions that might facilitate pairing with other transcripts. We report 56 pairs of overlapping transcripts, in which each member of the pair is transcribed from the same locus. This allows us to make an estimate of 1000 for the minimum number of such transcript pairs in the entire human genome. This is a surprisingly large number of overlapping gene pairs and, clearly, some of the overlaps may not be functionally significant. Nonetheless, this may indicate an important general role for overlapping antisense control in gene regulation. EST databases were also investigated in order to address the prevalence of cases of imprinted genes with associated non-coding overlapping, antisense transcripts. However, EST databases were found to be completely inappropriate for this purpose. PMID:18628857

  9. Simple Evaluation of the Chiral Jacobian with the Overlap Dirac Operator

    NASA Astrophysics Data System (ADS)

    Suzuki, H.

    1999-07-01

    The chiral Jacobian, which is defined with Neuberger's overlap Dirac operator of the lattice fermion, is explicitly evaluated in the continuum limit without expanding it in the gauge coupling constant. Our calculational scheme is simple and straightforward. We determine a coefficient of the chiral anomaly for general values of the mass parameter and the Wilson parameter of the overlap Dirac operator.

  10. The Quality of Social Networks: Its Determinants and Impacts on Helping and Volunteering in Macao

    ERIC Educational Resources Information Center

    Tong, Kwok Kit; Hung, Eva P. W.; Yuen, Sze Man

    2011-01-01

    Pro-social behaviors serve essential societal functions. This study examines the factors affecting the quality of social networks, in terms of network size and perceived respect. It further explores the role of social networks in enhancing helping intention and helping behaviors. Eight hundred and eighty people were randomly interviewed by phone.…

  11. The Quality of Social Networks: Its Determinants and Impacts on Helping and Volunteering in Macao

    ERIC Educational Resources Information Center

    Tong, Kwok Kit; Hung, Eva P. W.; Yuen, Sze Man

    2011-01-01

    Pro-social behaviors serve essential societal functions. This study examines the factors affecting the quality of social networks, in terms of network size and perceived respect. It further explores the role of social networks in enhancing helping intention and helping behaviors. Eight hundred and eighty people were randomly interviewed by phone.…

  12. Vibrational relaxation and internal conversion in the overlapped optically-allowed 1Bu+ and optically-forbidden 1Bu- or 3Ag- vibronic levels of carotenoids: Effects of diabatic mixing as determined by Kerr-gate fluorescence spectroscopy

    NASA Astrophysics Data System (ADS)

    Kakitani, Yoshinori; Miki, Takeshi; Koyama, Yasushi; Nagae, Hiroyoshi; Nakamura, Ryosuke; Kanematsu, Yasuo

    2009-07-01

    The time constants of the vibrational relaxation, υ = 2 → υ = 1 and υ = 1 → υ = 0, in the 1Bu+ manifold and those of internal conversion from the 1Bu+(0) level, which is isoenergetic (so-called 'diabatic') with the 1Bu- vibronic levels in neurosporene and spheroidene and with the 3Ag- vibronic levels in lycopene and anhydrorhodovibrin, were determined by Kerr-gate fluorescence spectroscopy. The time constants of the vibrational relaxation were in the ˜1:2 ratio, and those of internal conversion agreed with the lifetimes of the diabatic counterparts, i.e., the 1Bu- and 3Ag- electronic states, respectively.

  13. Determining electron temperature for small spherical probes from network analyzer measurements of complex impedance

    NASA Astrophysics Data System (ADS)

    Walker, D. N.; Fernsler, R. F.; Blackwell, D. D.; Amatucci, W. E.

    2008-12-01

    In earlier work, using a network analyzer, it was shown that collisionless resistance (CR) exists in the sheath of a spherical probe when driven by a small rf signal. The CR is inversely proportional to the plasma density gradient at the location where the applied angular frequency equals the plasma frequency ωpe. Recently, efforts have concentrated on a study of the low-to-intermediate frequency response of the probe to the rf signal. At sufficiently low frequencies, the CR is beyond cutoff, i.e., below the plasma frequency at the surface of the probe. Since the electron density at the probe surface decreases as a function of applied (negative) bias, the CR will extend to lower frequencies as the magnitude of negative bias increases. Therefore to eliminate both CR and ion current contributions, the frequencies presently being considered are much greater than the ion plasma frequency, ωpi, but less than the plasma frequency, ωpe(r0), where r0 is the probe radius. It is shown that, in this frequency regime, the complex impedance measurements made with a network analyzer can be used to determine electron temperature. An overview of the theory is presented along with comparisons to data sets made using three stainless steel spherical probes of different sizes in different experimental environments and different plasma parameter regimes. The temperature measurements made by this method are compared to those made by conventional Langmuir probe sweeps; the method shown here requires no curve fitting as is the usual procedure with Langmuir probes when a Maxwell-Boltzmann electron distribution is assumed. The new method requires, however, a solution of the Poisson equation to determine the approximate sheath dimensions and integrals to determine approximate plasma and sheath inductances. The solution relies on the calculation of impedance for a spherical probe immersed in a collisionless plasma and is based on a simple circuit analogy for the plasma. Finally, the

  14. Artificial neural networks for defining the water quality determinants of groundwater abstraction in coastal aquifer

    NASA Astrophysics Data System (ADS)

    Lallahem, S.; Hani, A.

    2017-02-01

    Water sustainability in the lower Seybouse River basin, eastern Algeria, must take into account the importance of water quantity and quality integration. So, there is a need for a better knowledge and understanding of the water quality determinants of groundwater abstraction to meet the municipal and agricultural uses. In this paper, the artificial neural network (ANN) models were used to model and predict the relationship between groundwater abstraction and water quality determinants in the lower Seybouse River basin. The study area chosen is the lower Seybouse River basin and real data were collected from forty five wells for reference year 2006. Results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the important water quality parameters of groundwater abstraction and use. The model evaluation shows that the correlation coefficients are more than 95% for training, verification and testing data. The model aims to link the water quantity and quality with the objective to strengthen the Integrated Water Resources Management approach. It assists water planners and managers to better assess the water quality parameters and progress towards the provision of appropriate quantities of water of suitable quality.

  15. Artificial neural network approach for moiré fringe center determination

    NASA Astrophysics Data System (ADS)

    Woo, Wing Hon; Ratnam, Mani Maran; Yen, Kin Sam

    2015-11-01

    The moiré effect has been used in high-accuracy positioning and alignment systems for decades. Various methods have been proposed to identify and locate moiré fringes in order to relate the pattern information to dimensional and displacement measurement. These methods can be broadly categorized into manual interpretation based on human knowledge and image processing based on computational algorithms. An artificial neural network (ANN) is proposed to locate moiré fringe centers within circular grating moiré patterns. This ANN approach aims to mimic human decision making by eliminating complex mathematical computations or time-consuming image processing algorithms in moiré fringe recognition. A feed-forward backpropagation ANN architecture was adopted in this work. Parametric studies were performed to optimize the ANN architecture. The finalized ANN approach was able to determine the location of the fringe centers with average deviations of 3.167 pixels out of 200 pixels (≈1.6%) and 6.166 pixels out of 200 pixels (≈3.1%) for real moiré patterns that lie within and outside the training intervals, respectively. In addition, a reduction of 43.4% in the computational time was reported using the ANN approach. Finally, the applicability of the ANN approach for moiré fringe center determination was confirmed.

  16. Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

    PubMed

    Alvarez-Silva, María Camila; Álvarez-Yela, Astrid Catalina; Gómez-Cano, Fabio; Zambrano, María Mercedes; Husserl, Johana; Danies, Giovanna; Restrepo, Silvia; González-Barrios, Andrés Fernando

    2017-01-01

    Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.

  17. Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils

    PubMed Central

    Álvarez-Yela, Astrid Catalina; Gómez-Cano, Fabio; Zambrano, María Mercedes; Husserl, Johana; Danies, Giovanna; Restrepo, Silvia; González-Barrios, Andrés Fernando

    2017-01-01

    Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. PMID:28767679

  18. Overlapping node discovery for improving classification of lung nodules.

    PubMed

    Zhang, Fan; Cai, Weidong; Song, Yang; Lee, Min-Zhao; Shan, Shimin; Dagan, David

    2013-01-01

    Distinguishing malignant lung nodules from benign nodules is an important aspect of lung cancer diagnosis. In this paper, we propose an automatic method to classify lung nodules into four different types, i.e. well-circumscribed, juxta-vascular, juxta-pleural and pleural-tail. Additionally, since the morphology of lung nodules forms a continuum between the different types, our proposed method is superior to previous methods that classify single nodules into a single type. First, a weighted similarity network is constructed based on the SVM with probability estimates, turning the 128-length SIFT descriptor to a 4-length probability vector against the four types. Then, the classification of nodules while identifying those with overlapping types is made using the weighed Clique Percolation Method (CPMw). We evaluate the proposed method on low-dose CT images from ELCAP. Our results show that there is more overlap between well-circumscribed and juxta-vascular, and between juxta-pleural and pleural tail. Also, quantitative comparisons among various methods demonstrate highly effective nodule classification results by identifying the overlapping nodule types.

  19. [Impact of the Overlap Region Between Acoustic and Electric Stimulation].

    PubMed

    Baumann, Uwe; Mocka, Moritz

    2017-02-08

    Patients with residual hearing in the low frequencies and ski-slope hearing loss with partial deafness at medium and high frequencies receive a cochlear implant treatment with electric-acoustic stimulation (EAS, "hybrid" stimulation). In the border region between electric and acoustic stimulation a superposition of the 2 types of stimulation is expected. The area of overlap is determined by the insertion depth of the stimulating electrode and the lower starting point of signal transmission provided by the CI speech processor. The study examined the influence of the variation of the electric-acoustic overlap area on speech perception in noise, whereby the width of the "transmission gap" between the 2 different stimulus modalities was varied by 2 different methods. The results derived from 9 experienced users of the MED-EL Duet 2 speech processor show that the electric-acoustic overlapping area and with it the crossover frequency between the acoustic part and the CI should be adjusted individually. Overall, speech reception thresholds (SRT) showed a wide variation of results in between subjects. Further studies shall investigate whether generalized procedures about the setting of the overlap between electric and acoustic stimulation are reasonable, whereby an increased number of subjects and a longer period of acclimatization prior to the conduction of hearing tests deemed necessary.

  20. Sarcoidosis Blood Transcriptome Reflects Lung Inflammation and Overlaps with Tuberculosis

    PubMed Central

    Solberg, Owen D.; Peng, Jeffrey C.; Bhakta, Nirav R.; Nguyen, Christine P.; Woodruff, Prescott G.

    2011-01-01

    Rationale: Sarcoidosis is a granulomatous disease of unknown etiology, although M. tuberculosis may play a role in the pathogenesis. The traditional view holds that inflammation in sarcoidosis is compartmentalized to involved organs. Objectives: To determine whether whole blood gene expression signatures reflect inflammatory pathways in the lung in sarcoidosis and whether these signatures overlap with tuberculosis. Methods: We analyzed transcriptomic data from blood and lung biopsies in sarcoidosis and compared these profiles with blood transcriptomic data from tuberculosis and other diseases. Measurements and Main Results: Applying machine learning algorithms to blood gene expression data, we built a classifier that distinguished sarcoidosis from health in derivation and validation cohorts (92% sensitivity, 92% specificity). The most discriminative genes were confirmed by quantitative PCR and correlated with disease severity. Transcript profiles significantly induced in blood overlapped with those in lung biopsies and identified shared dominant inflammatory pathways (e.g., Type-I/II interferons). Sarcoidosis and tuberculosis shared more overlap in blood gene expression compared with other diseases using the 86-gene signature reported to be specific for tuberculosis and the sarcoidosis signature presented herein, although reapplication of machine learning algorithms could identify genes specific for sarcoidosis. Conclusions: These data indicate that blood transcriptome analysis provides a noninvasive method for identifying inflammatory pathways in sarcoidosis, that these pathways may be leveraged to complement more invasive procedures for diagnosis or assessment of disease severity, and that sarcoidosis and tuberculosis share overlap in gene regulation of specific inflammatory pathways. PMID:21852540

  1. Determination of the uncertainties of reflection coefficient measurements of a microwave network analyzer

    SciTech Connect

    Duda, L.E.; Moyer, R.D.

    1998-04-01

    A method that calculates the residual uncertainties of a microwave network analyzer for the frequency range of 300 kHz to 50 GHz is described. The method utilizes measurements on NIST-certified standards (such as an airline or load) plus additional measurements to estimate the combined standard uncertainties for measurements using the network analyzer. The uncertainties of the standards are incorporated by means of a Monte Carlo technique. The uncertainties assigned to a network analyzer then provide the basis for estimating the uncertainties assigned to devices measured using a network analyzer. The results of this method for characterizing network analyzer uncertainties are presented for several connector types.

  2. Determination of configuration matrix element and outer synchronization among networks with different topologies

    NASA Astrophysics Data System (ADS)

    Lü, Ling; Liu, Shuo; Li, Gang; Zhao, Guannan; Gu, Jiajia; Tian, Jing; Wang, Zhouyang

    2016-11-01

    In this paper, we research the outer synchronization among discrete networks with different topologies. Based on Lyapunov theorem, a novel synchronization technique is designed. Further, the control inputs of the networks and the adaptive laws of configuration matrix element are obtained. In the end, a numerical example is given to illustrate the effectiveness of the synchronization technique. It is found that the designed control input of the networks ensures the convergence of the errors among the networks to zero. And the designed adaptive law of configuration matrix element can replace effectively configuration matrix element in networks.

  3. Bayesian belief network analysis applied to determine the progression of temporomandibular disorders using MRI.

    PubMed

    Iwasaki, H

    2015-01-01

    This study investigated the applicability of a Bayesian belief network (BBN) to MR images to diagnose temporomandibular disorders (TMDs). Our aim was to determine the progression of TMDs, focusing on how each finding affects the other. We selected 1.5-T MRI findings (33 variables) and diagnoses (bone changes and disc displacement) of patients with TMD from 2007 to 2008. There were a total of 295 cases with 590 sides of temporomandibular joints (TMJs). The data were modified according to the research diagnostic criteria of TMD. We compared the accuracy of the BBN using 11 algorithms (necessary path condition, path condition, greedy search-and-score with Bayesian information criterion, Chow-Liu tree, Rebane-Pearl poly tree, tree augmented naïve Bayes model, maximum log likelihood, Akaike information criterion, minimum description length, K2 and C4.5), a multiple regression analysis and an artificial neural network using resubstitution validation and 10-fold cross-validation. There were 191 TMJs (32.4%) with bone changes and 340 (57.6%) with articular disc displacement. The BBN path condition algorithm using resubstitution validation and 10-fold cross-validation was >99% accurate. However, the main advantage of a BBN is that it can represent the causal relationships between different findings and assign conditional probabilities, which can then be used to interpret the progression of TMD. Osteoarthritic bone changes progressed from condyle to articular fossa and finally to mandibular bone contours. Disc displacement was directly related to severe bone changes. Early bone changes were not directly related to disc displacement. TMJ functional factors (condylar translation, bony space and disc form) and age mediated between bone changes and disc displacement.

  4. Bayesian belief network analysis applied to determine the progression of temporomandibular disorders using MRI

    PubMed Central

    2015-01-01

    Objectives: This study investigated the applicability of a Bayesian belief network (BBN) to MR images to diagnose temporomandibular disorders (TMDs). Our aim was to determine the progression of TMDs, focusing on how each finding affects the other. Methods: We selected 1.5-T MRI findings (33 variables) and diagnoses (bone changes and disc displacement) of patients with TMD from 2007 to 2008. There were a total of 295 cases with 590 sides of temporomandibular joints (TMJs). The data were modified according to the research diagnostic criteria of TMD. We compared the accuracy of the BBN using 11 algorithms (necessary path condition, path condition, greedy search-and-score with Bayesian information criterion, Chow–Liu tree, Rebane–Pearl poly tree, tree augmented naïve Bayes model, maximum log likelihood, Akaike information criterion, minimum description length, K2 and C4.5), a multiple regression analysis and an artificial neural network using resubstitution validation and 10-fold cross-validation. Results: There were 191 TMJs (32.4%) with bone changes and 340 (57.6%) with articular disc displacement. The BBN path condition algorithm using resubstitution validation and 10-fold cross-validation was >99% accurate. However, the main advantage of a BBN is that it can represent the causal relationships between different findings and assign conditional probabilities, which can then be used to interpret the progression of TMD. Conclusions: Osteoarthritic bone changes progressed from condyle to articular fossa and finally to mandibular bone contours. Disc displacement was directly related to severe bone changes. Early bone changes were not directly related to disc displacement. TMJ functional factors (condylar translation, bony space and disc form) and age mediated between bone changes and disc displacement. PMID:25472616

  5. Role of disorder in determining the vibrational properties of mass-spring networks

    NASA Astrophysics Data System (ADS)

    Nie, Yunhuan; Tong, Hua; Liu, Jun; Zu, Mengjie; Xu, Ning

    2017-06-01

    By introducing four fundamental types of disorders into a two-dimensional triangular lattice separately, we determine the role of each type of disorder in the vibration of the resulting mass-spring networks. We are concerned mainly with the origin of the boson peak and the connection between the boson peak and the transverse Ioffe-Regel limit. For all types of disorders, we observe the emergence of the boson peak and Ioffe-Regel limits. With increasing disorder, the boson peak frequency ω BP , transverse Ioffe-Regel frequency ω IR T , and longitudinal Ioffe-Regel frequency ω IR L all decrease. We find that there are two ways for the boson peak to form: developing from and coexisting with (but remaining independent of) the transverse van Hove singularity without and with local coordination number fluctuation. In the presence of a single type of disorder, ω IR T ≥ ω BP , and ω IR T ≈ ω BP only when the disorder is sufficiently strong and causes spatial fluctuation of the local coordination number. Moreover, if there is no positional disorder, ω IR T ≈ ω IR L . Therefore, the argument that the boson peak is equivalent to the transverse Ioffe-Regel limit is not general. Our results suggest that both local coordination number and positional disorder are necessary for the argument to hold, which is actually the case for most disordered solids such as marginally jammed solids and structural glasses. We further combine two types of disorders to cause disorder in both the local coordination number and lattice site position. The density of vibrational states of the resulting networks resembles that of marginally jammed solids well. However, the relation between the boson peak and the transverse Ioffe-Regel limit is still indefinite and condition-dependent. Therefore, the interplay between different types of disorders is complicated, and more in-depth studies are required to sort it out.

  6. Determinants of successful clinical networks: the conceptual framework and study protocol.

    PubMed

    Haines, Mary; Brown, Bernadette; Craig, Jonathan; D'Este, Catherine; Elliott, Elizabeth; Klineberg, Emily; McInnes, Elizabeth; Middleton, Sandy; Paul, Christine; Redman, Sally; Yano, Elizabeth M

    2012-03-13

    Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.

  7. Determinants of successful clinical networks: the conceptual framework and study protocol

    PubMed Central

    2012-01-01

    Background Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. Methods/Design The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. Discussion This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks. PMID:22414246

  8. An Interactive network of long non-coding RNAs facilitates the Drosophila sex determination decision

    PubMed Central

    Mulvey, Brett B.; Olcese, Ursula; Cabrera, Janel R.; Horabin, Jamila I.

    2014-01-01

    Genome analysis in several eukaryotes shows a surprising number of transcripts which do not encode conventional messenger RNAs. Once considered noise, these non-coding RNAs (ncRNAs) appear capable of controlling gene expression by various means. We find Drosophila sex determination, specifically the master-switch gene Sex-lethal (Sxl), is regulated by long ncRNAs (>200 nt). The lncRNAs influence the dose sensitive establishment promoter of Sxl, SxlPe, which must be activated to specify female sex. They are primarily from two regions, R1 and R2, upstream of SxlPeand show a dynamic developmental profile. Of the four lncRNA strands only one, R2 antisense, has its peak coincident with SxlPe transcription, suggesting it may promote activation. Indeed, its expression is regulated by the X chromosome counting genes, whose dose determines whether SxlPe is transcribed. Transgenic lines which ectopically express each of the lncRNAs show they can act in trans, impacting the process of sex determination but also altering the levels of the other lncRNAs. Generally, expression of R1 is negative whereas R2 is positive to females. This ectopic expression also results in a change in the local chromatin marks, affecting the timing and strength of SxlPe transcription. The chromatin marks are those deposited by the Polycomb and Trithorax groups of chromatin modifying proteins, which we find bind to the lncRNAs. We suggest the increasing numbers of non-coding transcripts being identified are a harbinger of interacting networks similar to the one we describe. PMID:24954180

  9. Temporal Proximity Promotes Integration of Overlapping Events.

    PubMed

    Zeithamova, Dagmar; Preston, Alison R

    2017-03-02

    Events with overlapping elements can be encoded as two separate representations or linked into an integrated representation; yet, we know little about the conditions that promote one form of representation over the other. Here, we tested the hypothesis that the proximity of overlapping events would increase the probability of integration. Participants first established memories for house-object and face-object pairs; half of the pairs were learned 24 hr before a fMRI session, and the other half 30 min before the session. During scanning, participants encoded object-object pairs that overlapped with the initial pairs acquired on the same or prior day. Participants were also scanned as they made inference judgments about the relationships among overlapping pairs learned on the same or different day. Participants were more accurate and faster when inferring relationships among memories learned on the same day relative to those acquired across days, suggesting that temporal proximity promotes integration. Evidence for reactivation of existing memories-as measured by a visual content classifier-was equivalent during encoding of overlapping pairs from the two temporal conditions. In contrast, evidence for integration-as measured by a mnemonic strategy classifier from an independent study [Richter, F. R., Chanales, A. J. H., & Kuhl, B. A. Predicting the integration of overlapping memories by decoding mnemonic processing states during learning. Neuroimage, 124, 323-335, 2016]-was greater for same-day overlapping events, paralleling the behavioral results. During inference itself, activation patterns further differentiated when participants were making inferences about events acquired on the same day versus across days. These findings indicate that temporal proximity of events promotes integration and further influences the neural mechanisms engaged during inference.

  10. Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks

    PubMed Central

    Chen, Yin-ying; Yu, Ya-nan; Zhang, Ying-ying; Li, Bing; Liu, Jun; Li, Dong-feng; Wu, Ping; Wang, Jie; Wang, Zhong; Wang, Yong-yan

    2016-01-01

    Targeting modules or signalings may open a new path to understanding the complex pharmacological mechanisms of reversing disease processes. However, determining how to quantify the structural alteration of these signalings or modules in pharmacological networks poses a great challenge towards realizing rational drug use in clinical medicine. Here, we explore a novel approach for dynamic comparative and quantitative analysis of the topological structural variation of modules in molecular networks, proposing the concept of allosteric modules (AMs). Based on the ischemic brain of mice, we optimize module distribution in different compound-dependent modular networks by using the minimum entropy criterion and then calculate the variation in similarity values of AMs under various conditions using a novel method of SimiNEF. The diverse pharmacological dynamic stereo-scrolls of AMs with functional gradient alteration, which consist of five types of AMs, may robustly deconstruct modular networks under the same ischemic conditions. The concept of AMs can not only integrate the responsive mechanisms of different compounds based on topological cascading variation but also obtain valuable structural information about disease and pharmacological networks beyond pathway analysis. We thereby provide a new systemic quantitative strategy for rationally determining pharmacological mechanisms of altered modular networks based on topological variation. PMID:27383195

  11. Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

    PubMed

    Nicola, Wilten; Tripp, Bryan; Scott, Matthew

    2016-01-01

    A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

  12. Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

    PubMed Central

    Nicola, Wilten; Tripp, Bryan; Scott, Matthew

    2016-01-01

    A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks. PMID:26973503

  13. Determination of groundwater abstractions by means of GRACE data and Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Gemitzi, Alexandra; Tsagkarakis, Konstantinos; Lakshmi, Venkat

    2017-04-01

    The EU Water Framework Directive requires for each groundwater body the determination of annual average rates of abstraction from all points providing more than 10m3 per day as well as groundwater level monitoring, so as to ensure that the available groundwater resource is not exceeded by the long-term annual average rate of abstraction. In order to acquire such information in situ observation networks are necessary. However, there are cases, e.g. Greece where WFD monitoring programme has not yet become operational due to bureaucratic, socioeconomic and often political constraints. The present study aims at determining groundwater use at the aquifer scale by using Gravity Recovery and Climate Experiment (GRACE) satellite data coupled with readily available meteorological data. Traditionally, GRACE data have been used at the global and regional scale due to their coarse resolution and the difficulties in disaggregating the various Total Water Storage (TWS) components. Previous works have evaluated the subsurface anomalies (ΔGW), using supplementary data sets and hydrologic modeling results in order to disaggregate GRACE TWS anomalies into their various components. Recent works however, have shown that changes in groundwater storage are dominating the GRACE Total Water Storage (TWS) changes, therefore it was though reasonable to use changes in Grace derived TWS in order to quantify abstractions from a groundwater body. Statistical downscaling was performed using an Artificial Neural Network in the form a Multilayer Perceptron model, in conjunction with local meteorological data. An ensemble of 100 ANNs provided a means of quantifying uncertainty and improving generalization. The methodology was applied in Rhodope area (NE Greece) and proved to be an efficient way of downscaling GRACE data in order to estimate the monthly quantity of water extracted from a certain aquifer. Although our methodology does not aim at estimating abstractions at single points, it manages

  14. Displayed Trees Do Not Determine Distinguishability Under the Network Multispecies Coalescent.

    PubMed

    Zhu, Sha; Degnan, James H

    2017-03-01

    Recent work in estimating species relationships from gene trees has included inferring networks assuming that past hybridization has occurred between species. Probabilistic models using the multispecies coalescent can be used in this framework for likelihood-based inference of both network topologies and parameters, including branch lengths and hybridization parameters. A difficulty for such methods is that it is not always clear whether, or to what extent, networks are identifiable-that is whether there could be two distinct networks that lead to the same distribution of gene trees. For cases in which incomplete lineage sorting occurs in addition to hybridization, we demonstrate a new representation of the species network likelihood that expresses the probability distribution of the gene tree topologies as a linear combination of gene tree distributions given a set of species trees. This representation makes it clear that in some cases in which two distinct networks give the same distribution of gene trees when sampling one allele per species, the two networks can be distinguished theoretically when multiple individuals are sampled per species. This result means that network identifiability is not only a function of the trees displayed by the networks but also depends on allele sampling within species. We additionally give an example in which two networks that display exactly the same trees can be distinguished from their gene trees even when there is only one lineage sampled per species. [gene tree, hybridization, identifiability, maximum likelihood, species tree, phylogeny.].

  15. Interplay between excitability type and distributions of neuronal connectivity determines neuronal network synchronization.

    PubMed

    Mofakham, Sima; Fink, Christian G; Booth, Victoria; Zochowski, Michal R

    2016-10-01

    While the interplay between neuronal excitability properties and global properties of network topology is known to affect network propensity for synchronization, it is not clear how detailed characteristics of these properties affect spatiotemporal pattern formation. Here we study mixed networks, composed of neurons having type I and/or type II phase response curves, with varying distributions of local and random connections and show that not only average network properties, but also the connectivity distribution statistics, significantly affect network synchrony. Namely, we study networks with fixed networkwide properties, but vary the number of random connections that nodes project. We show that varying node excitability (type I vs type II) influences network synchrony most dramatically for systems with long-tailed distributions of the number of random connections per node. This indicates that a cluster of even a few highly rewired cells with a high propensity for synchronization can alter the degree of synchrony in the network as a whole. We show this effect generally on a network of coupled Kuramoto oscillators and investigate the impact of this effect more thoroughly in pulse-coupled networks of biophysical neurons.

  16. Interplay between excitability type and distributions of neuronal connectivity determines neuronal network synchronization

    NASA Astrophysics Data System (ADS)

    Mofakham, Sima; Fink, Christian G.; Booth, Victoria; Zochowski, Michal R.

    2016-10-01

    While the interplay between neuronal excitability properties and global properties of network topology is known to affect network propensity for synchronization, it is not clear how detailed characteristics of these properties affect spatiotemporal pattern formation. Here we study mixed networks, composed of neurons having type I and/or type II phase response curves, with varying distributions of local and random connections and show that not only average network properties, but also the connectivity distribution statistics, significantly affect network synchrony. Namely, we study networks with fixed networkwide properties, but vary the number of random connections that nodes project. We show that varying node excitability (type I vs type II) influences network synchrony most dramatically for systems with long-tailed distributions of the number of random connections per node. This indicates that a cluster of even a few highly rewired cells with a high propensity for synchronization can alter the degree of synchrony in the network as a whole. We show this effect generally on a network of coupled Kuramoto oscillators and investigate the impact of this effect more thoroughly in pulse-coupled networks of biophysical neurons.

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

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

  18. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

    Networking is an information giving and receiving system, a support system, and a means whereby women can get ahead in careers--either in new jobs or in current positions. Networking information can create many opportunities: women can talk about how other women handle situations and tasks, and previously established contacts can be used in…

  19. Adaptive Estimation with Partially Overlapping Models

    PubMed Central

    Shin, Sunyoung; Fine, Jason; Liu, Yufeng

    2015-01-01

    In many problems, one has several models of interest that capture key parameters describing the distribution of the data. Partially overlapping models are taken as models in which at least one covariate effect is common to the models. A priori knowledge of such structure enables efficient estimation of all model parameters. However, in practice, this structure may be unknown. We propose adaptive composite M-estimation (ACME) for partially overlapping models using a composite loss function, which is a linear combination of loss functions defining the individual models. Penalization is applied to pairwise differences of parameters across models, resulting in data driven identification of the overlap structure. Further penalization is imposed on the individual parameters, enabling sparse estimation in the regression setting. The recovery of the overlap structure enables more efficient parameter estimation. An oracle result is established. Simulation studies illustrate the advantages of ACME over existing methods that fit individual models separately or make strong a priori assumption about the overlap structure. PMID:26917931

  20. SAGE: String-overlap Assembly of GEnomes.

    PubMed

    Ilie, Lucian; Haider, Bahlul; Molnar, Michael; Solis-Oba, Roberto

    2014-09-15

    De novo genome assembly of next-generation sequencing data is one of the most important current problems in bioinformatics, essential in many biological applications. In spite of significant amount of work in this area, better solutions are still very much needed. We present a new program, SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers. SAGE benefits from innovations in almost every aspect of the assembly process: error correction of input reads, string-overlap graph construction, read copy counts estimation, overlap graph analysis and reduction, contig extraction, and scaffolding. We hope that these new ideas will help advance the current state-of-the-art in an essential area of research in genomics.

  1. Bayesian neural network approach for determining the risk of re-intervention after endovascular aortic aneurysm repair.

    PubMed

    Attallah, Omneya; Ma, Xianghong

    2014-09-01

    This article proposes a Bayesian neural network approach to determine the risk of re-intervention after endovascular aortic aneurysm repair surgery. The target of proposed technique is to determine which patients have high chance to re-intervention (high-risk patients) and which are not (low-risk patients) after 5 years of the surgery. Two censored datasets relating to the clinical conditions of aortic aneurysms have been collected from two different vascular centers in the United Kingdom. A Bayesian network was first employed to solve the censoring issue in the datasets. Then, a back propagation neural network model was built using the uncensored data of the first center to predict re-intervention on the second center and classify the patients into high-risk and low-risk groups. Kaplan-Meier curves were plotted for each group of patients separately to show whether there is a significant difference between the two risk groups. Finally, the logrank test was applied to determine whether the neural network model was capable of predicting and distinguishing between the two risk groups. The results show that the Bayesian network used for uncensoring the data has improved the performance of the neural networks that were built for the two centers separately. More importantly, the neural network that was trained with uncensored data of the first center was able to predict and discriminate between groups of low risk and high risk of re-intervention after 5 years of endovascular aortic aneurysm surgery at center 2 (p = 0.0037 in the logrank test).

  2. Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

    PubMed Central

    Rich, Scott; Booth, Victoria; Zochowski, Michal

    2016-01-01

    The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics

  3. Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks.

    PubMed

    Rich, Scott; Booth, Victoria; Zochowski, Michal

    2016-01-01

    The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics

  4. Determining Protein Complex Connectivity Using a Probabilistic Deletion Network Derived from Quantitative Proteomics

    PubMed Central

    Sardiu, Mihaela E.; Gilmore, Joshua M.; Carrozza, Michael J.; Li, Bing; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

    2009-01-01

    Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex. PMID:19806189

  5. Female mating preferences determine system-level evolution in a gene network model.

    PubMed

    Fierst, Janna L

    2013-06-01

    Environmental patterns of directional, stabilizing and fluctuating selection can influence the evolution of system-level properties like evolvability and mutational robustness. Intersexual selection produces strong phenotypic selection and these dynamics may also affect the response to mutation and the potential for future adaptation. In order to to assess the influence of mating preferences on these evolutionary properties, I modeled a male trait and female preference determined by separate gene regulatory networks. I studied three sexual selection scenarios: sexual conflict, a Gaussian model of the Fisher process described in Lande (in Proc Natl Acad Sci 78(6):3721-3725, 1981) and a good genes model in which the male trait signalled his mutational condition. I measured the effects these mating preferences had on the potential for traits and preferences to evolve towards new states, and mutational robustness of both the phenotype and the individual's overall viability. All types of sexual selection increased male phenotypic robustness relative to a randomly mating population. The Fisher model also reduced male evolvability and mutational robustness for viability. Under good genes sexual selection, males evolved an increased mutational robustness for viability. Females choosing their mates is a scenario that is sufficient to create selective forces that impact genetic evolution and shape the evolutionary response to mutation and environmental selection. These dynamics will inevitably develop in any population where sexual selection is operating, and affect the potential for future adaptation.

  6. On the Determination of Magnetic Field Strength and Flux in Inter-Network

    NASA Astrophysics Data System (ADS)

    Khomenko, E.; Collados, M.,

    2006-12-01

    The results of the determination of magnetic field strength and flux from weak polarimetric signals in solar inter-network regions are contradictory. We investigate the origin of this contradiction with the help of MHD simulations. It is shown that the Stokes-V line ratio of the Fe I 5247/5250 Å and 15652/15648 Å line pairs is a good indicator of kG magnetic field concentrations, even for magnetic fields with a complex internal structure like those in MHD simulations. On the contrary, the Stokes-V line ratio of the Fe I 6301/6302 Å lines shows no correlation with magnetic field strength. The reason lies in the large difference in the heights of formation of these two lines. The value of the magnetic field strength obtained from the inversion of the Fe I 6301 Å and 6302 Å lines depends crucially on the treatment of gradients of magnetic field, LOS velocity, and temperature even at numerical spatial resolution of 20 km.

  7. Rapid determination of bacterial abundance, biovolume, morphology, and growth by neural network-based image analysis

    PubMed

    Blackburn; Hagstrom; Wikner; Cuadros-Hansson; Bjornsen

    1998-09-01

    Annual bacterial plankton dynamics at several depths and locations in the Baltic Sea were studied by image analysis. Individual bacteria were classified by using an artificial neural network which also effectively identified nonbacterial objects. Cell counts and frequencies of dividing cells were determined, and the data obtained agreed well with visual observations and previously published values. Cell volumes were measured accurately by comparison with bead standards. The survey included 690 images from a total of 138 samples. Each image contained approximately 200 bacteria. The images were analyzed automatically at a rate of 100 images per h. Bacterial abundance exhibited coherent patterns with time and depth, and there were distinct subsurface peaks in the summer months. Four distinct morphological classes were resolved by the image analyzer, and the dynamics of each could be visualized. The bacterial growth rates estimated from frequencies of dividing cells were different from the bacterial growth rates estimated by the thymidine incorporation method. With minor modifications, the image analysis technique described here can be used to analyze other planktonic classes.

  8. Rapid Determination of Bacterial Abundance, Biovolume, Morphology, and Growth by Neural Network-Based Image Analysis

    PubMed Central

    Blackburn, Nicholas; Hagström, Åke; Wikner, Johan; Cuadros-Hansson, Rocio; Bjørnsen, Peter Koefoed

    1998-01-01

    Annual bacterial plankton dynamics at several depths and locations in the Baltic Sea were studied by image analysis. Individual bacteria were classified by using an artificial neural network which also effectively identified nonbacterial objects. Cell counts and frequencies of dividing cells were determined, and the data obtained agreed well with visual observations and previously published values. Cell volumes were measured accurately by comparison with bead standards. The survey included 690 images from a total of 138 samples. Each image contained approximately 200 bacteria. The images were analyzed automatically at a rate of 100 images per h. Bacterial abundance exhibited coherent patterns with time and depth, and there were distinct subsurface peaks in the summer months. Four distinct morphological classes were resolved by the image analyzer, and the dynamics of each could be visualized. The bacterial growth rates estimated from frequencies of dividing cells were different from the bacterial growth rates estimated by the thymidine incorporation method. With minor modifications, the image analysis technique described here can be used to analyze other planktonic classes. PMID:9726867

  9. Using Non-supervised Artificial Neural Network for Determination of Anthropogenic Disturbance in a River System

    PubMed Central

    Rosli, Nurul Ruhayu Mohd; Yahya, Khairun

    2017-01-01

    The study of river water quality plays an important role in assessing the pollution status and health of the water bodies. Human-induced activities such as domestic activities, aquaculture, agriculture and industries have detrimentally affected the river water quality. Pinang River is one of the important rivers in Balik Pulau District that supplies freshwater for human consumption. A total of 442 physical and chemical parameters data of the Pinang River, Balik Pulau catchment were analysed to determine the sources of pollutants entering the river. Non-supervised artificial neural network (ANN) was employed to classify and cluster the river into upstream, middle-stream and downstream zones. The monitored data and non-supervised ANN analysis demonstrated that the source of nitrate was derived from the upper part of the Pinang River, Balik Pulau while the sources of nitrite, ammonia and ortho-phosphate are predominant at the middle-stream of the river system. Meanwhile, the sources of high total suspended solid and biological oxygen demand were concentrated at the downstream of the river. PMID:28890770

  10. Columnar interactions determine horizontal propagation of recurrent network activity in neocortex

    PubMed Central

    Wester, Jason C.; Contreras, Diego

    2012-01-01

    The cortex is organized in vertical and horizontal circuits that determine the spatiotemporal properties of distributed cortical activity. Despite detailed knowledge of synaptic interactions among individual cells in the neocortex, little is known about the rules governing interactions among local populations. Here we used self-sustained recurrent activity generated in cortex, also known as up-states, in rat thalamocortical slices in vitro to understand interactions among laminar and horizontal circuits. By means of intracellular recordings and fast optical imaging with voltage sensitive dyes, we show that single thalamic inputs activate the cortical column in a preferential L4→L2/3→L5 sequence, followed by horizontal propagation with a leading front in supra and infragranular layers. To understand the laminar and columnar interactions, we used focal injections of TTX to block activity in small local populations, while preserving functional connectivity in the rest of the network. We show that L2/3 alone, without underlying L5, does not generate self-sustained activity and is inefficient propagating activity horizontally. In contrast, L5 sustains activity in the absence of L2/3 and is necessary and sufficient to propagate activity horizontally. However, loss of L2/3 delays horizontal propagation via L5. Finally, L5 amplifies activity in L2/3. Our results show for the first time that columnar interactions between supra and infragranular layers are required for the normal propagation of activity in the neocortex. Our data suggest that supra and infragranular circuits with their specific and complex set of inputs and outputs, work in tandem to determine the patterns of cortical activation observed in vivo. PMID:22514308

  11. Application of neural networks to determine moisture content on humidity-attenuated NIR spectra

    SciTech Connect

    Lopez, T.; Philipp, B.L.; Thompson-Bachmeier, S.

    1995-12-31

    Moisture has been identified as one of the critical tank waste parameters that impacts the safety status of the wastes, particularly tanks containing ferro/ferricyanide materials. Since water content is affected by a number of factors, including gravity, one hypothesis, currently being tested by Westinghouse Hanford`s Waste Tank Safety organization, is that the surface of the waste contains a minimum of water compared to the material deeper in the tank. Assuming this hypothesis is correct, a minimum internal waste water content will be obtained by measuring the surface water content. Near infrared analysis is a nondestructive technique that takes advantage of the tendency of water molecules to absorb specific wavelengths of NIR energy. When a sample containing water is exposed to those wavelengths, a certain portion of the energy will be absorbed by the water, and the remainder will be reflected. By measuring the reflected energy, the concentration of water in the sample can be determined. An initial investigation into the feasibility of remote sensing for hot cell and waste tank applications was performed at the University of Washington`s Center for Process Analytical Chemistry (CPAC) under the direction of Westinghouse Hanford Company. The BY-104 waste tank simulant test data showed that for these samples, ten percent of the incident radiation is scattered. When collected, this signal is available for determining moisture content because the moisture content of the waste affects the scattering. However, atmospheric relative humidity causes a signal attenuation that will impact any in situ measurements being obtained. For simulation, this spectra was used along with software generated atmospheric transmission data from 0-60 meters to produce a modified sample set. These data are analyzed using a backpropagation neural network algorithm to construct a model that would predict surface moisture content.

  12. Gene regulatory network analysis reveals differences in site-specific cell fate determination in mammalian brain

    PubMed Central

    Ertaylan, Gökhan; Okawa, Satoshi; Schwamborn, Jens C.; del Sol, Antonio

    2014-01-01

    Neurogenesis—the generation of new neurons—is an ongoing process that persists in the adult mammalian brain of several species, including humans. In this work we analyze two discrete brain regions: the subventricular zone (SVZ) lining the walls of the lateral ventricles; and the subgranular zone (SGZ) of the dentate gyrus (DG) of the hippocampus in mice and shed light on the SVZ and SGZ specific neurogenesis. We propose a computational model that relies on the construction and analysis of region specific gene regulatory networks (GRNs) from the publicly available data on these two regions. Using this model a number of putative factors involved in neuronal stem cell (NSC) identity and maintenance were identified. We also demonstrate potential gender and niche-derived differences based on cell surface and nuclear receptors via Ar, Hif1a, and Nr3c1. We have also conducted cell fate determinant analysis for SVZ NSC populations to Olfactory Bulb interneurons and SGZ NSC populations to the granule cells of the Granular Cell Layer. We report 31 candidate cell fate determinant gene pairs, ready to be validated. We focus on Ar—Pax6 in SVZ and Sox2—Ncor1 in SGZ. Both pairs are expressed and localized in the suggested anatomical structures as shown by in situ hybridization and found to physically interact. Finally, we conclude that there are fundamental differences between SGZ and SVZ neurogenesis. We argue that these regulatory mechanisms are linked to the observed differential neurogenic potential of these regions. The presence of nuclear and cell surface receptors in the region specific regulatory circuits indicate the significance of niche derived extracellular factors, hormones and region specific factors such as the oxygen sensitivity, dictating SGZ and SVZ specific neurogenesis. PMID:25565969

  13. Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

    NASA Astrophysics Data System (ADS)

    Andersen, Hendrik; Cermak, Jan

    2015-04-01

    This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

  14. Phonon Overlaps in Molecular Quantum Dot Systems

    NASA Astrophysics Data System (ADS)

    Chang, Connie; Sethna, James

    2004-03-01

    We model the amplitudes and frequencies of the vibrational sidebands for the new molecular quantum dot systems. We calculate the Franck-Condon phonon overlaps in the 3N-dimensional configuration sapce. We solve the general case where the vibrational frequencies and eigenmodes change during the transition. We perform PM3 and DFT calculations for the case of the dumb bell-shaped C140 molecule. We find that the strongest amplitudes are associated with the 11 meV stretch mode, in agreement with experiment. The experimental amplitudes vary from molecule to molecule; indicating that the molecular overlaps are environment dependent. We explore overlaps in the presence of external electric fields from image charges and counter ions.

  15. Locality and Scaling of Quenched Overlap Fermions

    SciTech Connect

    Terrence Draper; Nilmani Mathur; Jianbo Zhang; Andrei Alexandru; Ying Chen; Shao-Jing Dong; Ivan Horvath; Frank Lee; Sonali Tamhankar

    2005-07-01

    The overlap fermion offers the tremendous advantage of exact chiral symmetry on the lattice, but is numerically intensive. This can be made affordable while still providing large lattice volumes, by using coarse lattice spacing, given that good scaling and localization properties are established. Here, using overlap fermions on quenched Iwasaki gauge configurations, we demonstrate directly that the overlap Dirac operator's range is comfortably small in lattice units for each of the lattice spacings 0.20 fm, 0.17 fm, and 0.13 fm (and scales to zero in physical units in the continuum limit). In particular, our direct results contradict recent speculation that an inverse lattice spacing of 1 GeV is too low to have satisfactory localization. Furthermore, hadronic masses (available on the two coarser lattices) scale very well.

  16. Analyzing the impact of overlap, offload, and independent progress for MPI.

    SciTech Connect

    Riesen, Rolf E.; Underwood, Keith Douglas; Brightwell, Ronald Brian

    2005-06-01

    The overlap of computation and communication has long been considered to be a significant performance benefit for applications. Similarly, the ability of the Message Passing Interface (MPI) to make independent progress (that is, to make progress on outstanding communication operations while not in the MPI library) is also believed to yield performance benefits. Using an intelligent network interface to offload the work required to support overlap and independent progress is thought to be an ideal solution, but the benefits of this approach have not been studied in depth at the application level. This lack of analysis is complicated by the fact that most MPI implementations do not sufficiently support overlap or independent progress. Recent work has demonstrated a quantifiable advantage for an MPI implementation that uses offload to provide overlap and independent progress. The study is conducted on two different platforms with each having two MPI implementations (one with and one without independent progress). Thus, identical network hardware and virtually identical software stacks are used. Furthermore, one platform, ASCI Red, allows further separation of features such as overlap and offload. Thus, this paper extends previous work by further qualifying the source of the performance advantage: offload, overlap, or independent progress.

  17. Sub-Plate Overlap Code Documentation

    NASA Technical Reports Server (NTRS)

    Taff, L. G.; Bucciarelli, B.; Zarate, N.

    1997-01-01

    An expansion of the plate overlap method of astrometric data reduction to a single plate has been proposed and successfully tested. Each plate is (artificially) divided into sub-plates which can then be overlapped. This reduces the area of a 'plate' over which a plate model needs to accurately represent the relationship between measured coordinates and standard coordinates. Application is made to non-astrographic plates such as Schmidt plates and to wide-field astrographic plates. Indeed, the method is completely general and can be applied to any type of recording media.

  18. The QCD vacuum probed by overlap fermions

    NASA Astrophysics Data System (ADS)

    Weinberg, Volker

    2006-12-01

    We summarize different uses of the eigenmodes of the Neuberger overlap operator for the analysis of the QCD vacuum, here applied to quenched configurations simulated by means of the Lüscher-Weisz action. We describe the localization and chiral properties of the lowest modes. The overlap-based topological charge density (with and without UV-filtering) is compared with the re- sults of UV-filtering for the field strength tensor. The latter allows to identify domains of good (anti-)selfduality. All these techniques together lead to a dual picture of the vacuum, unifying the infrared instanton picture with the presence of singular defects co-existent at different scales.

  19. On the SOR method with overlapping subsystems

    NASA Astrophysics Data System (ADS)

    Maleev, A. A.

    2006-06-01

    A description is given of the iterative Jacobi method with overlapping subsystems and the corresponding Gauss-Seidel method. Similarly to the classical case, a generalized SOR method with overlapping subsystems is constructed by introducing an relaxation parameter. The concept of a ω-consistent matrix is defined. It is shown that, with the optimal choice of the parameter, the theory developed by Young remains valid for ω-consistent matrices. This implies certain results for ω-consistent H-matrices. The theoretical conclusions obtained in the paper are supported by numerical results.

  20. Social networks, social support and psychiatric symptoms: social determinants and associations within a multicultural community population.

    PubMed

    Smyth, Natasha; Siriwardhana, Chesmal; Hotopf, Matthew; Hatch, Stephani L

    2015-07-01

    Little is known about how social networks and social support are distributed within diverse communities and how different types of each are associated with a range of psychiatric symptoms. This study aims to address such shortcomings by: (1) describing the demographic and socioeconomic characteristics of social networks and social support in a multicultural population and (2) examining how each is associated with multiple mental health outcomes. Data is drawn from the South East London Community Health Study; a cross-sectional study of 1,698 adults conducted between 2008 and 2010. The findings demonstrate variation in social networks and social support by socio-demographic factors. Ethnic minority groups reported larger family networks but less perceived instrumental support. Older individuals and migrant groups reported lower levels of particular network and support types. Individuals from lower socioeconomic groups tended to report less social networks and support across the indicators measured. Perceived emotional and instrumental support, family and friend network size emerged as protective factors for common mental disorder, personality dysfunction and psychotic experiences. In contrast, both social networks and social support appear less relevant for hazardous alcohol use. The findings both confirm established knowledge that social networks and social support exert differential effects on mental health and furthermore suggest that the particular type of social support may be important. In contrast, different types of social network appear to impact upon poor mental health in a more uniform way. Future psychosocial strategies promoting mental health should consider which social groups are vulnerable to reduced social networks and poor social support and which diagnostic groups may benefit most.

  1. Random Access in Wireless Networks With Overlapping Cells

    DTIC Science & Technology

    2010-06-01

    Downloaded on May 19,2010 at 21:13:10 UTC from IEEE Xplore . Restrictions apply. Report Documentation Page Form ApprovedOMB No. 0704-0188 Public...Authorized licensed use limited to: NRL. Downloaded on May 19,2010 at 21:13:10 UTC from IEEE Xplore . Restrictions apply. NGUYEN et al.: RANDOM ACCESS IN...21:13:10 UTC from IEEE Xplore . Restrictions apply. 2890 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 6, JUNE 2010 5) For a single

  2. Random Access in Wireless Networks With Overlapping Cells

    DTIC Science & Technology

    2010-06-01

    Downloaded on May 19,2010 at 21:13:10 UTC from IEEE Xplore . Restrictions apply. Report Documentation Page Form ApprovedOMB No. 0704-0188 Public...Authorized licensed use limited to: NRL. Downloaded on May 19,2010 at 21:13:10 UTC from IEEE Xplore . Restrictions apply. NGUYEN et al.: RANDOM ACCESS IN...21:13:10 UTC from IEEE Xplore . Restrictions apply. 2890 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 6, JUNE 2010 5) For a single

  3. Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories.

    PubMed

    Oyarzún, Javiera P; Morís, Joaquín; Luque, David; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

    2017-08-09

    System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength.SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks. Copyright © 2017 the authors 0270-6474/17/377748-11$15.00/0.

  4. PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

    NASA Astrophysics Data System (ADS)

    Cam, Hasan

    2012-06-01

    As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

  5. Registration of partially overlapping laser-radar range images

    NASA Astrophysics Data System (ADS)

    Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

    2015-10-01

    To register partially overlapping three-dimensional point sets from different viewpoints, it is necessary to remove spurious corresponding point pairs that are not located in overlapping regions. Most variants of the iterative closest point (ICP) algorithm require users to manually select the rejection parameters for discarding spurious point pairs between the registering views. This requirement often results in unreliable and inaccurate registration. To overcome this problem, we present an improved ICP algorithm that can automatically determine the rejection percentage to reliably and accurately align partially overlapping laser-radar (ladar) range images. The similarity of k neighboring features of each nonplanar point is employed to determine reasonable point pairs in nonplanar regions, and the distance measurement method is used to find reasonable point pairs in planar regions. The rejection percentage can be obtained from these two sets of reasonable pairs. The performance of our algorithm is compared with that of five other algorithms using various models with low and high curvatures. The experimental results show that our algorithm is more accurate and robust than the other algorithms.

  6. Adaptive braking by Ase1 prevents overlapping microtubules from sliding completely apart.

    PubMed

    Braun, Marcus; Lansky, Zdenek; Fink, Gero; Ruhnow, Felix; Diez, Stefan; Janson, Marcel E

    2011-09-04

    Short regions of overlap between ends of antiparallel microtubules are central elements within bipolar microtubule arrays. Although their formation requires motors, recent in vitro studies demonstrated that stable overlaps cannot be generated by molecular motors alone. Motors either slide microtubules along each other until complete separation or, in the presence of opposing motors, generate oscillatory movements. Here, we show that Ase1, a member of the conserved MAP65/PRC1 family of microtubule-bundling proteins, enables the formation of stable antiparallel overlaps through adaptive braking of Kinesin-14-driven microtubule-microtubule sliding. As overlapping microtubules start to slide apart, Ase1 molecules become compacted in the shrinking overlap and the sliding velocity gradually decreases in a dose-dependent manner. Compaction is driven by moving microtubule ends that act as barriers to Ase1 diffusion. Quantitative modelling showed that the molecular off-rate of Ase1 is sufficiently low to enable persistent overlap stabilization over tens of minutes. The finding of adaptive braking demonstrates that sliding can be slowed down locally to stabilize overlaps at the centre of bipolar arrays, whereas sliding proceeds elsewhere to enable network self-organization.

  7. Social network as a determinant of pathway to mental health service utilization among psychotic patients in a Nigerian hospital.

    PubMed

    Lasebikan, Victor O; Owoaje, Eme T; Asuzu, Michael C

    2012-01-01

    The main objectives of the study were to determine the relationship between social network and pathway to service utilization among psychotic patients. This descriptive study was carried out in a psychiatric unit in a general hospital in South West Nigeria. Using structured questionnaires, primary data were collected from 652 psychotic patients on their social network, health behaviors and pathway to current service use. Logistic regression analysis was used to assess the effect of social network on patients' use of services, controlling for sociodemographics, health and functional status. Mean age of the respondents was 29.0 ± 7.5 years, range 14-58 years, males constituted 52.6%. Regarding pathway to services, alternative sources of care such as priests, spiritualists, natural therapists, herbalists, was the first port of call for 78.9% of respondents. Family dominated the social network in 51.1% of patients. The presence of some social network and social support structures were significantly associated with the use of general medical and specialty psychiatric services for patients with schizophrenia (P = 0.03), schizoaffective disorder (P = 0.02), bipolar I disorder (P = 0.01), but not with major depression and symptoms of psychological distress. Findings indicate that social support and social network enhanced utilization of mental health services for psychiatric patients except for those with psychotic depression or those with symptoms of psychological distress. In addition, alternative sources of care are still relevant in mental health service delivery in South West Nigeria.

  8. 47 CFR 73.509 - Prohibited overlap.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Noncommercial Educational FM Broadcast Stations § 73.509 Prohibited overlap. (a) An application for a new or modified NCE-FM station other than a Class D (secondary) station will not be accepted if the...

  9. 47 CFR 73.509 - Prohibited overlap.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Noncommercial Educational FM Broadcast Stations § 73.509 Prohibited overlap. (a) An application for a new or modified NCE-FM station other than a Class D (secondary) station will not be accepted if the...

  10. Stochastic Cooling with Schottky Band Overlap

    NASA Astrophysics Data System (ADS)

    Lebedev, Valeri

    2006-03-01

    Optimal use of stochastic cooling is essential to maximize the antiproton stacking rate for Tevatron Run II. Good understanding and characterization of the cooling is important for the optimization. The paper is devoted to derivation of the Fokker-Plank equations justified in the case of near or full Schottky base overlap for both longitudinal and transverse coolings.

  11. Stochastic Cooling with Schottky Band Overlap

    SciTech Connect

    Lebedev, Valeri; /Fermilab

    2005-12-01

    Optimal use of stochastic cooling is essential to maximize the antiproton stacking rate for Tevatron Run II. Good understanding and characterization of the cooling is important for the optimization. The paper is devoted to derivation of the Fokker-Planck equations justified in the case of near or full Schottky base overlap for both longitudinal and transverse coolings.

  12. Stochastic Cooling with Schottky Band Overlap

    SciTech Connect

    Lebedev, Valeri

    2006-03-20

    Optimal use of stochastic cooling is essential to maximize the antiproton stacking rate for Tevatron Run II. Good understanding and characterization of the cooling is important for the optimization. The paper is devoted to derivation of the Fokker-Plank equations justified in the case of near or full Schottky base overlap for both longitudinal and transverse coolings.

  13. Australian University Libraries: Collections Overlap Study

    ERIC Educational Resources Information Center

    Missingham, Roxanne; Walls, Robert

    2003-01-01

    In 2002, the Department of Education, Science and Training (DEST), Higher Education Information Infrastructure Advisory Committee commissioned the National Library of Australia to analyse the uniqueness and overlap of Australian university library collections, comparing library collections in each state, using the National Bibliographic Database…

  14. Overlap: A Selected Review of Recent Literature.

    ERIC Educational Resources Information Center

    Knight, Stephanie L.

    1985-01-01

    This article presents an annotated bibliography of journal articles and documents which discuss both theoretical and research findings related to issues surrounding the concept of overlap between standardized tests and the content, curricular, and instructional domains of teaching and learning. (MT)

  15. Liberal Education: An Overlapping Pragmatic Consensus.

    ERIC Educational Resources Information Center

    Paris, David C.; Kimball, Bruce A.

    2000-01-01

    Suggests in Bruce Kimball's thesis that a pragmatic consensus was emerging about the understanding of liberal education offers that it might be best understood by comparing it to J. Rawl's idea of an "overlapping consensus." States that by comparing and contrasting these ideas that the emerging consensus is pragmatic in nature. (CMK)

  16. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market.

    PubMed

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk.

  17. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market

    PubMed Central

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk. PMID:27257816

  18. Determination of the critical coupling of explosive synchronization transitions in scale-free networks by mean-field approximations.

    PubMed

    Peron, Thomas Kauê Dal'maso; Rodrigues, Francisco A

    2012-11-01

    An explosive synchronization can be observed in scale-free networks when Kuramoto oscillators have natural frequencies equal to their number of connections. The present paper reports on mean-field approximations to determine the critical coupling of such explosive synchronization. It has been verified that the equation obtained for the critical coupling has an inverse dependence on the network average degree. This expression differs from those whose frequency distributions are unimodal and even. In this case, the critical coupling depends on the ratio between the first and second statistical moments of the degree distribution. Numerical simulations were also conducted to verify our analytical results.

  19. Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

    NASA Astrophysics Data System (ADS)

    Coffey, T.

    2016-12-01

    Distributary channel bifurcations on river deltas are important features in both modern systems, where the channels control water, sediment, and nutrient routing, and in ancient deltas, where the channel networks can dictate large-scale stratigraphic heterogeneity. Geometric features of distributary channels, such as channel dimensions and network structure, have long been thought to be defined by factors such as flow velocity, grain size, or channel aspect ratio where the channel enters the basin. We use theory originally developed for tributary networks fed by groundwater seepage to understand the dynamics of distributary channel bifurcations. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to evolve dependent on the diffusive flow patterns around the channel network. These networks possess a characteristic bifurcation angle of 72°, due to Laplacian flow (gradient2h2=0, where h is water surface elevation) in the groundwater flow field near tributary channel tips. We develop and test the hypothesis that bifurcation angles in distributary channel networks are likewise dictated by the external flow field, in this case the shallow surface water surrounding the subaqueous portion of distributary channel bifurcations in a deltaic setting. We measured 130 unique distributary channel bifurcations in a single experimental delta and in 10 natural deltas, yielding a mean angle of 70.35°±2.59° (95% confidence interval), in line with the theoretical prediction. This similarity implies that flow outside of the distributary channel network is also Laplacian, which we use scaling arguments to justify. We conclude that the dynamics of the unchannelized flow control bifurcation formation in distributary networks.

  20. Determining the control networks regulating stem cell lineages in colonic crypts.

    PubMed

    Yang, Jienian; Axelrod, David E; Komarova, Natalia L

    2017-09-21

    The question of stem cell control is at the center of our understanding of tissue functioning, both in healthy and cancerous conditions. It is well accepted that cellular fate decisions (such as divisions, differentiation, apoptosis) are orchestrated by a network of regulatory signals emitted by different cell populations in the lineage and the surrounding tissue. The exact regulatory network that governs stem cell lineages in a given tissue is usually unknown. Here we propose an algorithm to identify a set of candidate control networks that are compatible with (a) measured means and variances of cell populations in different compartments, (b) qualitative information on cell population dynamics, such as the existence of local controls and oscillatory reaction of the system to population size perturbations, and (c) statistics of correlations between cell numbers in different compartments. Using the example of human colon crypts, where lineages are comprised of stem cells, transit amplifying cells, and differentiated cells, we start with a theoretically known set of 32 smallest control networks compatible with tissue stability. Utilizing near-equilibrium stochastic calculus of stem cells developed earlier, we apply a series of tests, where we compare the networks' expected behavior with the observations. This allows us to exclude most of the networks, until only three, very similar, candidate networks remain, which are most compatible with the measurements. This work demonstrates how theoretical analysis of control networks combined with only static biological data can shed light onto the inner workings of stem cell lineages, in the absence of direct experimental assessment of regulatory signaling mechanisms. The resulting candidate networks are dominated by negative control loops and possess the following properties: (1) stem cell division decisions are negatively controlled by the stem cell population, (2) stem cell differentiation decisions are negatively

  1. Experimental model for determining developmental stage of chicken embryo using infrared images and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Jung, Seung Kwon "Paul"; Hsieh, Sheng-Jen "Tony"; Chen, Che-Hao

    2013-05-01

    Development of a chicken embryo is conventionally assumed to follow a set growth pattern over the course of 21 days. However, despite identical incubation settings, many factors may contribute to an egg developing at a different rate from those around it. Being able to determine an embryo's actual development instead of relying on chronological assumptions of normal growth should prove to be a useful tool in the poultry industry for responding early to abnormal development and improving hatch rates. Previous studies have used infrared imaging to enhance candling observation, but relatively little has been done to implement infrared imaging in problem-solving. The purpose of this research is to construct a quantitative model for predicting the development stage and early viability of a chicken embryo during incubation. It may be noted that a similar project was conducted previously using different input parameters. This study seeks to improve upon the results from the earlier project. In this project, infrared images of eggs were processed to calculate air cell volumes and cooling rates, and daily measurements of egg weight and ambient temperature were compiled. Artificial neural networks (ANNs) were "trained" using multiple input parameters to recognize patterns in the data. Various training functions and topologies were evaluated in order to optimize prediction rates and consistency. The prediction rates obtained for the ANNs were around 81% for development stage and around 92% for viability. It is recommended for future research to expand the potential combinations of input parameters used in order to increase this model's versatility in the field.

  2. Cumacean (Peracarida, Crustacea) endemism and faunal overlap in Antarctic deep-sea basins

    NASA Astrophysics Data System (ADS)

    Mühlenhardt-Siegel, Ute

    2011-03-01

    At least 155 morphotypes of Cumaceans have been determined from samples collected by various expeditions over the past 15 years. Among them, only 38 species were previously described, while at least 116 morphotypes (75%) represent species new to science. The faunal overlap of Antarctic Cumacea (Peracarida) is calculated between various deep-sea basins, between the deep sea and the shelf, and between different shelf areas of Antarctica and the Sub Antarctic islands. The degree of endemism is high (about 80%) for the Antarctic Cumacea, but within the Antarctic regions faunal overlaps are detectable. Maximal faunal overlap (about 50%) is found among the Antarctic shelf regions, but the deep-sea basins of the Antarctic Peninsula region and the Weddell Sea have also a high (about 30%) species overlap. Including the new findings of Cumacea from the various deep-sea basins, the overlap between the Antarctic shelf and the deep sea is only 18%.

  3. The overlap syndromes of autoimmune hepatitis.

    PubMed

    Czaja, Albert J

    2013-02-01

    Autoimmune hepatitis has two major variant phenotypes in which the features of classical disease are co-mingled with those of primary biliary cirrhosis or primary sclerosing cholangitis. These overlap syndromes lack codified diagnostic criteria, established pathogenic mechanisms, and confident management strategies. Their clinical importance relates mainly to the identification of patients who respond poorly to conventional corticosteroid treatment. Scoring systems that lack discriminative power have been used in their definition, and a clinical phenotype based on pre-defined laboratory and histological findings has not been promulgated. The frequency of overlap with primary biliary cirrhosis is 7-13 %, and the frequency of overlap with primary sclerosing cholangitis is 8-17 %. Patients with autoimmune hepatitis and features of cholestatic disease must be distinguished from patients with cholestatic disease and features of autoimmune hepatitis. Variants of the overlap syndromes include patients with small duct primary sclerosing cholangitis, antimitochondrial antibody-negative primary biliary cirrhosis, autoimmune sclerosing cholangitis, and immunoglobulin G4-associated disease. Conventional corticosteroid therapy alone or in conjunction with ursodeoxycholic acid (13-15 mg/kg daily) has been variably effective, and cyclosporine, mycophenolate mofetil, and budesonide have been beneficial in selected patients. The key cholestatic features that influence the prognosis of autoimmune hepatitis must be defined and incorporated into the definition of the syndrome rather than rely on designations that imply the co-mingling of different diseases with manifestations of variable clinical relevance. The overlap syndromes in autoimmune hepatitis are imprecise, heterogeneous, and unfounded, but they constitute a clinical reality that must be accepted, diagnosed, refined, treated, and studied.

  4. Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization.

    PubMed

    Cao, Xiaochun; Wang, Xiao; Jin, Di; Cao, Yixin; He, Dongxiao

    2013-10-21

    Community detection is important for understanding networks. Previous studies observed that communities are not necessarily disjoint and might overlap. It is also agreed that some outlier vertices participate in no community, and some hubs in a community might take more important roles than others. Each of these facts has been independently addressed in previous work. But there is no algorithm, to our knowledge, that can identify these three structures altogether. To overcome this limitation, we propose a novel model where vertices are measured by their centrality in communities, and define the identification of overlapping communities, hubs, and outliers as an optimization problem, calculated by nonnegative matrix factorization. We test this method on various real networks, and compare it with several competing algorithms. The experimental results not only demonstrate its ability of identifying overlapping communities, hubs, and outliers, but also validate its superior performance in terms of clustering quality.

  5. Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization

    PubMed Central

    Cao, Xiaochun; Wang, Xiao; Jin, Di; Cao, Yixin; He, Dongxiao

    2013-01-01

    Community detection is important for understanding networks. Previous studies observed that communities are not necessarily disjoint and might overlap. It is also agreed that some outlier vertices participate in no community, and some hubs in a community might take more important roles than others. Each of these facts has been independently addressed in previous work. But there is no algorithm, to our knowledge, that can identify these three structures altogether. To overcome this limitation, we propose a novel model where vertices are measured by their centrality in communities, and define the identification of overlapping communities, hubs, and outliers as an optimization problem, calculated by nonnegative matrix factorization. We test this method on various real networks, and compare it with several competing algorithms. The experimental results not only demonstrate its ability of identifying overlapping communities, hubs, and outliers, but also validate its superior performance in terms of clustering quality. PMID:24129402

  6. Evaluation of attractors and basins of asynchronous random Boolean networks.

    PubMed

    Yang, Meng; Chu, Tianguang

    2012-05-01

    We present an algebraic approach for determining the attractors and their basins of random Boolean networks under an asynchronous stochastic update based on the recently developed matrix semitensor product theory, which allows for converting the logical dynamics of a Boolean network into a standard iterative dynamics. In this setting, all attractors and basins are specified by the network transition matrices. We then devise procedures that can find all attractors and their basins exactly. We also discuss the issue of overlapping basins in asynchronous random Boolean networks, and we propose methods to compute the weight of each attractor and the basin entropy of the systems.

  7. Determining the Impact of Personal Mobility Carbon Allowance Schemes in Transportation Networks

    SciTech Connect

    Aziz, H. M. Abdul; Ukkusuri, Satish V.; Zhan, Xianyuan

    2016-10-17

    We know that personal mobility carbon allowance (PMCA) schemes are designed to reduce carbon consumption from transportation networks. PMCA schemes influence the travel decision process of users and accordingly impact the system metrics including travel time and greenhouse gas (GHG) emissions. Here, we develop a multi-user class dynamic user equilibrium model to evaluate the transportation system performance when PMCA scheme is implemented. The results using Sioux-Falls test network indicate that PMCA schemes can achieve the emissions reduction goals for transportation networks. Further, users characterized by high value of travel time are found to be less sensitive to carbon budget in the context of work trips. Results also show that PMCA scheme can lead to higher emissions for a path compared with the case without PMCA because of flow redistribution. The developed network equilibrium model allows us to examine the change in system states at different carbon allocation levels and to design parameters of PMCA schemes accounting for population heterogeneity.

  8. Determinants of Network News Coverage of the Oil Industry during the Late 1970s.

    ERIC Educational Resources Information Center

    Erfle, Stephen; McMillan, Henry

    1989-01-01

    Examines which firms and products best predict media coverage of the oil industry. Reports that price variations in testing oil and gasoline correlate with the extent of news coverage provided by network television. (MM)

  9. Determinants of Network News Coverage of the Oil Industry during the Late 1970s.

    ERIC Educational Resources Information Center

    Erfle, Stephen; McMillan, Henry

    1989-01-01

    Examines which firms and products best predict media coverage of the oil industry. Reports that price variations in testing oil and gasoline correlate with the extent of news coverage provided by network television. (MM)

  10. The clinical and genetic features of the COPD asthma overlap syndrome

    PubMed Central

    Hardin, Megan; Cho, Michael; McDonald, Merry-Lynn; Beaty, Terri; Ramsdell, Joe; Bhatt, Surya; van Beek, Edwin J. R.; Make, Barry J.; Crapo, James D.; Silverman, Edwin K.; Hersh, Craig P.

    2014-01-01

    Background Individuals with COPD and asthma are an important but poorly characterized group. The genetic determinants of COPD-asthma overlap have not been studied. Objective Identify clinical features and genetic risk factors for COPD-asthma overlap. Methods Subjects were current or former smoking non-Hispanic whites (NHW) or African-Americans (AA) with COPD. Overlap subjects reported a history of physician-diagnosed asthma before the age of 40. We compared clinical and radiographic features between COPD and overlap subjects. We performed genome-wide association studies (GWAS) in the NHW and AA populations, and combined these results in a meta-analysis. Results More women and African Americans reported a history of asthma. Overlap subjects had more severe and more frequent respiratory exacerbations, less emphysema, and greater airway wall thickness compared to subjects with COPD alone. The NHW GWAS identified SNPs in CSMD1 (rs11779254, P=1.57×10−6) and SOX5(rs59569785, P=1.61×10−6) and the meta-analysis identified SNPs in the gene GPR65 (rs6574978, P=1.18×10−7) associated with COPD-asthma overlap. Conclusions Overlap subjects have more exacerbations, less emphysema and more airway disease for any degree of lung function impairment compared to COPD alone. We identified novel genetic variants associated with this syndrome. COPD-asthma overlap is an important syndrome and may require distinct clinical management. PMID:24876173

  11. Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif.

    PubMed

    de Franciscis, Sebastiano; Caravagna, Giulio; Mauri, Giancarlo; d'Onofrio, Alberto

    2016-06-03

    Gene switching dynamics is a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we consider a common network motif - the positive feedback of a transcription factor on its own synthesis - and assess its response to extrinsic noises perturbing gene deactivation in a variety of settings where the network might operate. These settings are representative of distinct cellular types, abundance of transcription factors and ratio between gene switching and protein synthesis rates. By investigating noise-induced transitions among the different network operative states, our results suggest that gene switching rates are key parameters to shape network response to external perturbations, and that such response depends on the particular biological setting, i.e. the characteristic time scales and protein abundance. These results might have implications on our understanding of irreversible transitions for noise-related phenomena such as cellular differentiation. In addition these evidences suggest to adopt the appropriate mathematical model of the network in order to analyze the system consistently to the reference biological setting.

  12. Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

    NASA Astrophysics Data System (ADS)

    de Franciscis, Sebastiano; Caravagna, Giulio; Mauri, Giancarlo; D’Onofrio, Alberto

    2016-06-01

    Gene switching dynamics is a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we consider a common network motif - the positive feedback of a transcription factor on its own synthesis - and assess its response to extrinsic noises perturbing gene deactivation in a variety of settings where the network might operate. These settings are representative of distinct cellular types, abundance of transcription factors and ratio between gene switching and protein synthesis rates. By investigating noise-induced transitions among the different network operative states, our results suggest that gene switching rates are key parameters to shape network response to external perturbations, and that such response depends on the particular biological setting, i.e. the characteristic time scales and protein abundance. These results might have implications on our understanding of irreversible transitions for noise-related phenomena such as cellular differentiation. In addition these evidences suggest to adopt the appropriate mathematical model of the network in order to analyze the system consistently to the reference biological setting.

  13. Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

    PubMed Central

    de Franciscis, Sebastiano; Caravagna, Giulio; Mauri, Giancarlo; d’Onofrio, Alberto

    2016-01-01

    Gene switching dynamics is a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we consider a common network motif - the positive feedback of a transcription factor on its own synthesis - and assess its response to extrinsic noises perturbing gene deactivation in a variety of settings where the network might operate. These settings are representative of distinct cellular types, abundance of transcription factors and ratio between gene switching and protein synthesis rates. By investigating noise-induced transitions among the different network operative states, our results suggest that gene switching rates are key parameters to shape network response to external perturbations, and that such response depends on the particular biological setting, i.e. the characteristic time scales and protein abundance. These results might have implications on our understanding of irreversible transitions for noise-related phenomena such as cellular differentiation. In addition these evidences suggest to adopt the appropriate mathematical model of the network in order to analyze the system consistently to the reference biological setting. PMID:27256916

  14. Overlapping Modularity at the Critical Point of k-Clique Percolation

    NASA Astrophysics Data System (ADS)

    Tóth, Bálint; Vicsek, Tamás; Palla, Gergely

    2013-05-01

    One of the most remarkable social phenomena is the formation of communities in social networks corresponding to families, friendship circles, work teams, etc. Since people usually belong to several different communities at the same time, the induced overlaps result in an extremely complicated web of the communities themselves. Thus, uncovering the intricate community structure of social networks is a non-trivial task with great potential for practical applications, gaining a notable interest in the recent years. The Clique Percolation Method (CPM) is one of the earliest overlapping community finding methods, which was already used in the analysis of several different social networks. In this approach the communities correspond to k-clique percolation clusters, and the general heuristic for setting the parameters of the method is to tune the system just below the critical point of k-clique percolation. However, this rule is based on simple physical principles and its validity was never subject to quantitative analysis. Here we examine the quality of the partitioning in the vicinity of the critical point using recently introduced overlapping modularity measures. According to our results on real social and other networks, the overlapping modularities show a maximum close to the critical point, justifying the original criteria for the optimal parameter settings.

  15. Securely Measuring the Overlap between Private Datasets with Cryptosets

    PubMed Central

    Swamidass, S. Joshua; Matlock, Matthew; Rozenblit, Leon

    2015-01-01

    Many scientific questions are best approached by sharing data—collected by different groups or across large collaborative networks—into a combined analysis. Unfortunately, some of the most interesting and powerful datasets—like health records, genetic data, and drug discovery data—cannot be freely shared because they contain sensitive information. In many situations, knowing if private datasets overlap determines if it is worthwhile to navigate the institutional, ethical, and legal barriers that govern access to sensitive, private data. We report the first method of publicly measuring the overlap between private datasets that is secure under a malicious model without relying on private protocols or message passing. This method uses a publicly shareable summary of a dataset’s contents, its cryptoset, to estimate its overlap with other datasets. Cryptosets approach “information-theoretic” security, the strongest type of security possible in cryptography, which is not even crackable with infinite computing power. We empirically and theoretically assess both the accuracy of these estimates and the security of the approach, demonstrating that cryptosets are informative, with a stable accuracy, and secure. PMID:25714898

  16. Habitat Characteristics of Forest Fragments Determine Specialisation of Plant-Frugivore Networks in a Mosaic Forest Landscape

    PubMed Central

    Chama, Lackson; Berens, Dana G.; Downs, Colleen T.; Farwig, Nina

    2013-01-01

    Plant-frugivore networks play a key role in the regeneration of sub-tropical forest ecosystems. However, information about the impact of habitat characteristics on plant-frugivore networks in fragmented forests is scarce. We investigated the importance of fruit abundance, fruiting plant species richness and canopy cover within habitat fragments for the structure and robustness of plant-frugivore networks in a mosaic forest landscape of South Africa. In total, 53 avian species were involved in fruit removal of 31 fleshy-fruiting plant species. Species specialisation was always higher for plants than for frugivores. Both species and network-level specialisation increased with increasing fruit abundance and decreased with increasing fruiting plant species richness and canopy cover within fragments. Interaction diversity was unaffected by fruit abundance and canopy cover, but increased slightly with increasing fruiting plant species richness. These findings suggest that especially the availability of resources is an important determinant of the structure of plant-frugivore networks in a fragmented forest landscape. PMID:23365688

  17. The Carbon Assimilation Network in Escherichia coli Is Densely Connected and Largely Sign-Determined by Directions of Metabolic Fluxes

    PubMed Central

    Baldazzi, Valentina; Ropers, Delphine; Markowicz, Yves; Kahn, Daniel; Geiselmann, Johannes; de Jong, Hidde

    2010-01-01

    Gene regulatory networks consist of direct interactions but also include indirect interactions mediated by metabolites and signaling molecules. We describe how these indirect interactions can be derived from a model of the underlying biochemical reaction network, using weak time-scale assumptions in combination with sensitivity criteria from metabolic control analysis. We apply this approach to a model of the carbon assimilation network in Escherichia coli. Our results show that the derived gene regulatory network is densely connected, contrary to what is usually assumed. Moreover, the network is largely sign-determined, meaning that the signs of the indirect interactions are fixed by the flux directions of biochemical reactions, independently of specific parameter values and rate laws. An inversion of the fluxes following a change in growth conditions may affect the signs of the indirect interactions though. This leads to a feedback structure that is at the same time robust to changes in the kinetic properties of enzymes and that has the flexibility to accommodate radical changes in the environment. PMID:20548959

  18. Networks of soil biota in a secondary succession gradient: Is it biodiversity or network structure that determines soil function?

    NASA Astrophysics Data System (ADS)

    Morriën, Elly; Hannula, Emilia; Snoek, Basten; Hol, Gera; van Veen, Hans; van der Putten, Wim

    2017-04-01

    experiment we did a field sampling of intact soil cores within the same chronosequence of ex-arable fields. We identified bacteria and fungi by pyrosequencing, while archaea were identified using TRFLP. The protists, micro-fauna, nematodes, enchytraeids and earthworms were extracted and morphologically identified until high taxonomic levels, often species level. In total, around 15 000 species were identified from the soils. We created a Spearman-rank correlation matrix based on abundance data of species which we visualized in a network categorized as recent, mid-term and long-term abandoned fields as an overview of the soil community present. After stable isotope probing using similar methods the soil food web structure was resolved by identifying the microbes using phospholipid markers and identifying soil fauna by morphology into similar groups as for the network analysis, both combined with isotopic measurements. We show that structural changes in the food web topology also leads to functional changes in the soil food web which can act as a driving force during land use change after human disturbance.

  19. Earthquake location determination using data from DOMERAPI and BMKG seismic networks: A preliminary result of DOMERAPI project

    SciTech Connect

    Ramdhan, Mohamad; Nugraha, Andri Dian; Widiyantoro, Sri; Métaxian, Jean-Philippe; Valencia, Ayunda Aulia

    2015-04-24

    DOMERAPI project has been conducted to comprehensively study the internal structure of Merapi volcano, especially about deep structural features beneath the volcano. DOMERAPI earthquake monitoring network consists of 46 broad-band seismometers installed around the Merapi volcano. Earthquake hypocenter determination is a very important step for further studies, such as hypocenter relocation and seismic tomographic imaging. Ray paths from earthquake events occurring outside the Merapi region can be utilized to delineate the deep magma structure. Earthquakes occurring outside the DOMERAPI seismic network will produce an azimuthal gap greater than 180{sup 0}. Owing to this situation the stations from BMKG seismic network can be used jointly to minimize the azimuthal gap. We identified earthquake events manually and carefully, and then picked arrival times of P and S waves. The data from the DOMERAPI seismic network were combined with the BMKG data catalogue to determine earthquake events outside the Merapi region. For future work, we will also use the BPPTKG (Center for Research and Development of Geological Disaster Technology) data catalogue in order to study shallow structures beneath the Merapi volcano. The application of all data catalogues will provide good information as input for further advanced studies and volcano hazards mitigation.

  20. Earthquake location determination using data from DOMERAPI and BMKG seismic networks: A preliminary result of DOMERAPI project

    NASA Astrophysics Data System (ADS)

    Ramdhan, Mohamad; Nugraha, Andri Dian; Widiyantoro, Sri; Métaxian, Jean-Philippe; Valencia, Ayunda Aulia

    2015-04-01

    DOMERAPI project has been conducted to comprehensively study the internal structure of Merapi volcano, especially about deep structural features beneath the volcano. DOMERAPI earthquake monitoring network consists of 46 broad-band seismometers installed around the Merapi volcano. Earthquake hypocenter determination is a very important step for further studies, such as hypocenter relocation and seismic tomographic imaging. Ray paths from earthquake events occurring outside the Merapi region can be utilized to delineate the deep magma structure. Earthquakes occurring outside the DOMERAPI seismic network will produce an azimuthal gap greater than 1800. Owing to this situation the stations from BMKG seismic network can be used jointly to minimize the azimuthal gap. We identified earthquake events manually and carefully, and then picked arrival times of P and S waves. The data from the DOMERAPI seismic network were combined with the BMKG data catalogue to determine earthquake events outside the Merapi region. For future work, we will also use the BPPTKG (Center for Research and Development of Geological Disaster Technology) data catalogue in order to study shallow structures beneath the Merapi volcano. The application of all data catalogues will provide good information as input for further advanced studies and volcano hazards mitigation.

  1. Diffuse interstitial lung disease: overlaps and uncertainties.

    PubMed

    Walsh, Simon L F; Hansell, David M

    2010-08-01

    Histopathological analysis of lung biopsy material allows the diagnosis of idiopathic interstitial pneumonias; however, the strength of this diagnosis is sometimes subverted by interobserver variation and sampling. The American Thoracic Society and European Respiratory Society recommendations of 2002 provide a framework for the diagnosis of interstitial lung disease (ILD) and proposed an integrated clinical, radiological and histopathological approach. These recommendations represent a break with tradition by replacing the 'gold standard' of histopathology with the combined 'silver standards' of clinical, imaging and histopathological information. One of the pitfalls of a rigid classification system for the diagnosis of interstitial lung disease is its failure to accommodate the phenomenon of overlapping disease patterns. This article reviews the various ways that interstitial lung disease may be classified and discusses their applicability. In addition the issue of overlap disease patterns is considered in the context of histopathological interobserver variation and sampling error and how a pigeonhole approach to disease classification may overlook these hybrid entities.

  2. Partial-overlap biocular image misalignment tolerance

    NASA Astrophysics Data System (ADS)

    Kalich, Melvyn E.; Lont, Lisa M.; van de Pol, Corina; Rash, Clarence E.

    2004-09-01

    Partial-overlap biocular helmet-mounted display (HMD) design flexibility and cost are directly related to image misalignment standards. Currently suggested standards are based on highly variable data from a number of studies, most using subjective discomfort or diplopia measures. This study tested the suggested standard for divergent horizontal image misalignment in a partial-overlap biocular optical system by exercising vigilance performance during image misalignment. Also, pre- and post-image misalignment divergence, convergence and heterophoria measurements were taken. The results revealed that clinical visual diagnoses, associated with accommodation and vergence, were clearly related to vigilance task performance, showing a greater number of vigilance errors for subjects viewing misaligned displays. In-device post-image misalignment divergence recovery and convergence break-recovery were significantly decreased. This was not found for the no-offset controls.

  3. Imaging of autoimmune hepatitis and overlap syndromes.

    PubMed

    Malik, Neera; Venkatesh, Sudhakar K

    2017-01-01

    Autoimmune hepatitis (AIH) is an uncommon, chronic inflammatory, and relapsing liver disease of unknown origin that may lead to liver cirrhosis, hepatocellular carcinoma, liver transplantation, or death. AIH occurs in all age groups and races but can frequently manifest as acute fulminant hepatitis. Clinical presentation of AIH can have features similar to primary sclerosing cholangitis (PSC) and primary biliary cirrhosis (PBC), and these diseases may coexist leading to overlap syndromes. Although histological diagnosis is necessary, imaging features often can demonstrate characteristics that may be helpful to distinguish these diseases. Imaging features of AIH are those of chronic liver disease, and imaging plays important role in detection of complications and ruling out other possible causes of chronic liver disease. Emerging techniques such as elastography provide non-invasive options for diagnosis of significant fibrosis and cirrhosis during clinical follow-up as well as assessment of response to treatment. In this study, we will describe imaging findings in AIH and overlap syndromes.

  4. Adaptive threshold determination for efficient channel sensing in cognitive radio network using mobile sensors

    NASA Astrophysics Data System (ADS)

    Morshed, M. N.; Khatun, S.; Kamarudin, L. M.; Aljunid, S. A.; Ahmad, R. B.; Zakaria, A.; Fakir, M. M.

    2017-03-01

    Spectrum saturation problem is a major issue in wireless communication systems all over the world. Huge number of users is joining each day to the existing fixed band frequency but the bandwidth is not increasing. These requirements demand for efficient and intelligent use of spectrum. To solve this issue, the Cognitive Radio (CR) is the best choice. Spectrum sensing of a wireless heterogeneous network is a fundamental issue to detect the presence of primary users' signals in CR networks. In order to protect primary users (PUs) from harmful interference, the spectrum sensing scheme is required to perform well even in low signal-to-noise ratio (SNR) environments. Meanwhile, the sensing period is usually required to be short enough so that secondary (unlicensed) users (SUs) can fully utilize the available spectrum. CR networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary user's licensed frequency bands. In this paper, we have proposed an adaptive threshold detection method to detect presence of PU signal using free space path loss (FSPL) model in 2.4 GHz WLAN network. The model is designed for mobile sensors embedded in smartphones. The mobile sensors acts as SU while the existing WLAN network (channels) works as PU. The theoretical results show that the desired threshold range detection of mobile sensors mainly depends on the noise floor level of the location in consideration.

  5. Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

    NASA Astrophysics Data System (ADS)

    Coffey, T.

    2016-02-01

    Distributary channel bifurcations on river deltas are important features in both actively prograding river deltas and in lithified deltas within the stratigraphic record. Attributes of distributary channels have long been thought to be defined by flow velocity, grain size and channel aspect ratio where the channel enters the basin. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to grow and bifurcate independent of flow within the exposed channel network. These networks possess a characteristic bifurcation angle of 72°, based on Laplacian flow (water surface concavity equals zero) in the groundwater flow field near tributary channel tips. Based on the tributary channel model, we develop and test the hypothesis that bifurcation angles in distributary channels are likewise dictated by the external flow field, in this case the surface water surrounding the subaqueous portion of distributary channel tips in a deltaic setting. We measured 64 unique distributary bifurcations in an experimental delta, yielding a characteristic angle of 70.2°±2.2° (95% confidence interval), in line with the theoretical prediction for tributary channels. This similarity between bifurcation angles suggests that (A) flow directly outside of the distributary network is Laplacian, (B) the external flow field controls the bifurcation dynamics of distributary channels, and (C) that flow within the channel plays a secondary role in network dynamics.

  6. Overlap of fibromyalgia with other medical conditions.

    PubMed

    Martínez-Lavín, M

    2001-08-01

    Fibromyalgia is a multisystem illness. One of its defining features, generalized pain, may also be present in other rheumatic entities. The diagnosis of fibromyalgia is not easy by any means, it requires a profound knowledge of internal medicine. This article discusses the different rheumatic and nonrheumatic diseases that overlap or are prone to be confused with fibromyalgia. It emphasizes the key points in the differential diagnosis.

  7. Overlap fermions on a twisted mass sea

    NASA Astrophysics Data System (ADS)

    Schaefer, Stefan

    2006-12-01

    We present first results of a mixed action project. We analyze gauge configurations generated with two flavors of dynamical twisted mass fermions. Neuberger's overlap Dirac operator is used for the valence sector. The various choices in the setup of the simulation are discussed. We employ chiral perturbation theory to describe the effects of using different actions in the sea and valence sector at non-zero lattice spacing.

  8. "Overlapped" rhinitis: a real trap for rhinoallergologists.

    PubMed

    Gelardi, M

    2014-11-01

    Under the broad heading of "vasomotor" rhinitis two big groups can be distinguished: allergic rhinitis (IgE-mediated), and nonallergic rhinitis. Since they are two separate nosological entities, they can co-exist in the same patient, classifying themselves in the group of "overlapped" rhinitis (OR). Although not absolutely rare (indeed it is estimated a 15-20% incidence among all vasomotor rhinopathies), this condition is not investigated and diagnosed, with significant implications in the clinical-diagnostic and therapeutic field.

  9. The overlap between cyberbullying and traditional bullying.

    PubMed

    Waasdorp, Tracy E; Bradshaw, Catherine P

    2015-05-01

    Cyberbullying appears to be on the rise among adolescents due in part to increased access to electronic devices and less online supervision. Less is known about how cyberbullying differs from traditional bullying which occurs in person and the extent to which these two forms overlap. Our first aim was to examine the overlap of traditional bullying (relational, verbal, and physical) with cyberbullying. The second aim examined student- and school-level correlates of cyber victimization as compared to traditional victims. The final aim explored details of the cyberbullying experience (e.g., who sent the message, how was the message sent, and what was the message about). Data came from 28,104 adolescents (grades, 9-12) attending 58 high schools. Approximately 23% of the youth reported being victims of any form of bullying (cyber, relational, physical, and verbal) within the last month, with 25.6% of those victims reporting being cyberbullied. The largest proportion (50.3%) of victims reported they were victimized by all four forms, whereas only 4.6% reported being only cyberbullied. Multilevel analyses indicated that as compared to those who were only traditionally bullied, those who were cyberbullied were more likely to have externalizing (odds ratio = 1.44) and internalizing symptoms (odds ratio = 1.25). Additional analyses examined detailed characteristics of the cyberbullying experiences, indicating a relatively high level of overlap between cyber and traditional bullying. Implications for preventive interventions targeting youth involved with cyberbullying and its overlap with other forms of bullying are discussed. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  10. Classification of Antarctic algae by applying Kohonen neural network with 14 elements determined by inductively coupled plasma optical emission spectrometry

    NASA Astrophysics Data System (ADS)

    Balbinot, L.; Smichowski, P.; Farias, S.; Arruda, M. A. Z.; Vodopivez, C.; Poppi, R. J.

    2005-06-01

    Optical emission spectrometers can generate results, which sometimes are not easy to interpret, mainly when the analyses involve classifications. To make simultaneous data interpretation possible, the Kohonen neural network is used to classify different Antarctic algae according to their taxonomic groups from the determination of 14 analytes. The Kohonen neural network architecture used was 5×5 neurons, thus reducing 14-dimension input data to two-dimensional space. The input data were 14 analytes (As, Co, Cu, Fe, Mn, Sr, Zn, Cd, Cr, Mo, Ni, Pb, Se, V) with their concentrations, determined by inductively coupled plasma optical emission spectrometry in 11 different species of algae. Three taxonomic groups ( Rhodophyta, Phaeophyta and Cholorophyta) can be differentiated and classified through only their Cu content.

  11. Burnout-depression overlap: a review.

    PubMed

    Bianchi, Renzo; Schonfeld, Irvin Sam; Laurent, Eric

    2015-03-01

    Whether burnout is a form of depression or a distinct phenomenon is an object of controversy. The aim of the present article was to provide an up-to-date review of the literature dedicated to the question of burnout-depression overlap. A systematic literature search was carried out in PubMed, PsycINFO, and IngentaConnect. A total of 92 studies were identified as informing the issue of burnout-depression overlap. The current state of the art suggests that the distinction between burnout and depression is conceptually fragile. It is notably unclear how the state of burnout (i.e., the end stage of the burnout process) is conceived to differ from clinical depression. Empirically, evidence for the distinctiveness of the burnout phenomenon has been inconsistent, with the most recent studies casting doubt on that distinctiveness. The absence of consensual diagnostic criteria for burnout and burnout research's insufficient consideration of the heterogeneity of depressive disorders constitute major obstacles to the resolution of the raised issue. In conclusion, the epistemic status of the seminal, field-dominating definition of burnout is questioned. It is suggested that systematic clinical observation should be given a central place in future research on burnout-depression overlap.

  12. Overlaps between Frailty and Sarcopenia Definitions.

    PubMed

    Cederholm, Tommy

    2015-01-01

    Aging is characterized by the catabolism of muscles leading to sarcopenia and frailty. These are two geriatric syndromes with partly overlapping phenotypes. Primary sarcopenia, i.e. loss of muscle mass and function related to aging alone, usually precedes frailty. Thus, robustness passes from sarcopenia over frailty to disability leading eventually to a mortal outcome. Frailty (defined according to the phenotype model) encompasses states as exhaustion, weakness, and slowness, whereas sarcopenia, combining mass and function, is more strictly focused on muscles. Frailty is age related, whereas sarcopenia is also related to disease, starvation, and disuse. In general, the criteria for the two conditions overlap, but frailty requires weight loss, whereas sarcopenia requires muscle loss. Both gait speed and hand grip strength are suggested to be used as diagnostic measures for the two conditions since muscle function is crucial for any of the two syndromes. It is suggested that frailty screening should be part of the geriatric comprehensive assessment starting with measuring walking capacity and complemented by taking a history of fatigue and low activity. For younger adults (i.e. <70 years), sarcopenia screening could first register gait speed or hand grip strength and then body composition measurements. Simple questionnaires are feasible clinical alternatives. Treatment of frailty and sarcopenia overlaps, i.e. provide adequate protein and vitamin D supplementation, and encourage resistance exercise.

  13. Nodal dynamics, not degree distributions, determine the structural controllability of complex networks.

    PubMed

    Cowan, Noah J; Chastain, Erick J; Vilhena, Daril A; Freudenberg, James S; Bergstrom, Carl T

    2012-01-01

    Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set, is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.

  14. Nodal Dynamics, Not Degree Distributions, Determine the Structural Controllability of Complex Networks

    PubMed Central

    Cowan, Noah J.; Chastain, Erick J.; Vilhena, Daril A.; Freudenberg, James S.; Bergstrom, Carl T.

    2012-01-01

    Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167–173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set, is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations. PMID:22761682

  15. Immigrant and refugee social networks: determinants and consequences of social support among women newcomers to Canada.

    PubMed

    Hynie, Michaela; Crooks, Valorie A; Barragan, Jackeline

    2011-12-01

    Recent immigrants and refugees (newcomers) vary on many dimensions but do share similar challenges. Newcomers must rebuild social networks to obtain needed social support but often face social exclusion because of their race, language, religion, or immigrant status. In addition, most have limited access to personal, social, and community resources. Effects of situational and personal variables on the benefits and limitations associated with the social networks of female newcomers were explored through interviews and focus groups with 87 women from 7 communities. Using thematic analysis, the authors identify 5 sources of informal support across all 7 communities, which were almost exclusively limited to co-ethnic relationships, and the types of support, limitations, and reciprocity within each. Perceived support was strongest from family and close friends and, when support from close relationships was unavailable, from primary care providers. The results suggest that co-ethnic peer support networks may be overwhelmed in newcomer communities because of their limited size and resources.

  16. Vertical overlap of probability density functions of cloud and precipitation hydrometeors: CLOUD AND PRECIPITATION PDF OVERLAP

    SciTech Connect

    Ovchinnikov, Mikhail; Lim, Kyo-Sun Sunny; Larson, Vincent E.; Wong, May; Thayer-Calder, Katherine; Ghan, Steven J.

    2016-11-05

    Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.

  17. 78 FR 79649 - Energy Conservation Program: Proposed Determination of Set-Top Boxes and Network Equipment as a...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-31

    ...The U.S. Department of Energy (DOE) withdraws a proposed determination published June 15, 2011 that set-top boxes (STBs) and network equipment qualify as a covered product under Part A of Title III of the Energy Policy and Conservation Act (EPCA), as amended. DOE is taking this action in light of a consensus agreement entered by a broadly representative group that DOE believes has the potential to achieve significant energy savings in STBs.

  18. Photonic crystal fiber sensor array based on modes overlapping.

    PubMed

    Cárdenas-Sevilla, Guillermo A; Finazzi, Vittoria; Villatoro, Joel; Pruneri, Valerio

    2011-04-11

    An alternative method to build point and sensor array based on photonic crystal fibers (PCFs) is presented. A short length (in the 9-12 mm range) of properly selected index-guiding PCF is fusion spliced between conventional single mode fibers. By selective excitation and overlapping of specific modes in the PCF we make the transmission spectra of the sensors to exhibit a single and narrow notch. The notch position changes with external perturbation which allows sensing diverse parameters. The well-defined single notch, the extinction ratio exceeding 30 dB and the low overall insertion loss allow placing the sensors in series. This makes the implementation of sensor networks possible.

  19. Neural networks for determining protein specificity and multiple alignment of binding sites

    SciTech Connect

    Heumann, J.M.; Lapedes, A.S.; Stormo, G.D.

    1994-12-31

    We use a quantitative definition of specificity to develop a neural network for the identification of common protein binding sites in a collection of unaligned DNA fragments. We demonstrate the equivalence of the method to maximizing Information Content of the aligned sites when simple models of the binding energy and the genome are employed. The network method subsumes those simple models and is capable of working with more complicated ones. This is demonstrated using a Markov model of the E. coli genome and a sampling method to approximate the partition function. A variation of Gibbs sampling aids in avoiding local minima.

  20. Mechanical spectroscopy and relaxometry on alginate hydrogels: a comparative analysis for structural characterization and network mesh size determination.

    PubMed

    Turco, Gianluca; Donati, Ivan; Grassi, Mario; Marchioli, Giulia; Lapasin, Romano; Paoletti, Sergio

    2011-04-11

    The structure of calcium-saturated alginate hydrogels has been studied by combining rheological determinations and relaxometry measurements. The mechanical spectroscopy analyses performed on alginate gel cylinders at different polysaccharide concentration allowed estimating their main structural features such as the average mesh size. The calculation was based on the introduction of a front factor in the classical rubber elasticity approach which was correlated to the average length of the Guluronic acid blocks along the polysaccharide chain. Transverse relaxation time (T(2)) determinations performed on the cylinders revealed the presence of two relaxation rates of the water entrapped within the hydrogel network. The cross-correlation of the latter data with the rheological measurements allowed estimating the mesh size distribution of the hydrogel network. The results obtained for the hydrogel cylinders were found to be consistent with the relaxometric analysis performed on the alginate microbeads where, however, only one type of water bound into the network structure was detected. A good correlation was found in the average mesh size determined by means of relaxometric measurements on alginate microbeads and by a statistical analysis performed on TEM micrographs. Finally, the addition of a solution containing calcium ions allowed investigating further the different water relaxation modes within alginate hydrogels.

  1. Simultaneous determination of some components in detergent washing powder by mid-infrared spectrometry and artificial neural network.

    PubMed

    Khanmohammadi, Mohammadreza; Garmarudi, Amir Bagheri; Rouchi, Mohammad Babaei; Khoddami, Nafiseh

    2011-01-01

    A method has been established for simultaneous determination of sodium sulfate, sodium carbonate, and sodium tripolyphosphate in detergent washing powder samples based on attenuated total reflectance Fourier transform IR spectrometry in the mid-IR spectral region (800-1550 cm(-1)). Genetic algorithm (GA) wavelength selection followed by feed forward back-propagation artificial neural network (BP-ANN) was the chemometric approach. Root mean square error of prediction for BP-ANN and GA-BP-ANN was 0.0051 and 0.0048, respectively. The proposed method is simple, with no tedious pretreatment step, for simultaneous determination of the above-mentioned components in commercial washing powder samples.

  2. DNA-Binding Kinetics Determines the Mechanism of Noise-Induced Switching in Gene Networks.

    PubMed

    Tse, Margaret J; Chu, Brian K; Roy, Mahua; Read, Elizabeth L

    2015-10-20

    Gene regulatory networks are multistable dynamical systems in which attractor states represent cell phenotypes. Spontaneous, noise-induced transitions between these states are thought to underlie critical cellular processes, including cell developmental fate decisions, phenotypic plasticity in fluctuating environments, and carcinogenesis. As such, there is increasing interest in the development of theoretical and computational approaches that can shed light on the dynamics of these stochastic state transitions in multistable gene networks. We applied a numerical rare-event sampling algorithm to study transition paths of spontaneous noise-induced switching for a ubiquitous gene regulatory network motif, the bistable toggle switch, in which two mutually repressive genes compete for dominant expression. We find that the method can efficiently uncover detailed switching mechanisms that involve fluctuations both in occupancies of DNA regulatory sites and copy numbers of protein products. In addition, we show that the rate parameters governing binding and unbinding of regulatory proteins to DNA strongly influence the switching mechanism. In a regime of slow DNA-binding/unbinding kinetics, spontaneous switching occurs relatively frequently and is driven primarily by fluctuations in DNA-site occupancies. In contrast, in a regime of fast DNA-binding/unbinding kinetics, switching occurs rarely and is driven by fluctuations in levels of expressed protein. Our results demonstrate how spontaneous cell phenotype transitions involve collective behavior of both regulatory proteins and DNA. Computational approaches capable of simulating dynamics over many system variables are thus well suited to exploring dynamic mechanisms in gene networks.

  3. Determining the Impact of Personal Mobility Carbon Allowance Schemes in Transportation Networks

    DOE PAGES

    Aziz, H. M. Abdul; Ukkusuri, Satish V.; Zhan, Xianyuan

    2016-10-17

    We know that personal mobility carbon allowance (PMCA) schemes are designed to reduce carbon consumption from transportation networks. PMCA schemes influence the travel decision process of users and accordingly impact the system metrics including travel time and greenhouse gas (GHG) emissions. Here, we develop a multi-user class dynamic user equilibrium model to evaluate the transportation system performance when PMCA scheme is implemented. The results using Sioux-Falls test network indicate that PMCA schemes can achieve the emissions reduction goals for transportation networks. Further, users characterized by high value of travel time are found to be less sensitive to carbon budget inmore » the context of work trips. Results also show that PMCA scheme can lead to higher emissions for a path compared with the case without PMCA because of flow redistribution. The developed network equilibrium model allows us to examine the change in system states at different carbon allocation levels and to design parameters of PMCA schemes accounting for population heterogeneity.« less

  4. Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

    NASA Astrophysics Data System (ADS)

    Lin, Yi-Kuei; Yeh, Cheng-Ta

    2013-05-01

    From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

  5. Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control.

    PubMed

    Kagami, Haruna; Akutsu, Tatsuya; Maegawa, Shingo; Hosokawa, Hiroshi; Nacher, Jose C

    2015-10-13

    Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(-109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies.

  6. Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks

    NASA Astrophysics Data System (ADS)

    Lombardi, F.; Herrmann, H. J.; de Arcangelis, L.

    2017-04-01

    The 1/f-like decay observed in the power spectrum of electro-physiological signals, along with scale-free statistics of the so-called neuronal avalanches, constitutes evidence of criticality in neuronal systems. Recent in vitro studies have shown that avalanche dynamics at criticality corresponds to some specific balance of excitation and inhibition, thus suggesting that this is a basic feature of the critical state of neuronal networks. In particular, a lack of inhibition significantly alters the temporal structure of the spontaneous avalanche activity and leads to an anomalous abundance of large avalanches. Here, we study the relationship between network inhibition and the scaling exponent β of the power spectral density (PSD) of avalanche activity in a neuronal network model inspired in Self-Organized Criticality. We find that this scaling exponent depends on the percentage of inhibitory synapses and tends to the value β = 1 for a percentage of about 30%. More specifically, β is close to 2, namely, Brownian noise, for purely excitatory networks and decreases towards values in the interval [1, 1.4] as the percentage of inhibitory synapses ranges between 20% and 30%, in agreement with experimental findings. These results indicate that the level of inhibition affects the frequency spectrum of resting brain activity and suggest the analysis of the PSD scaling behavior as a possible tool to study pathological conditions.

  7. Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control

    NASA Astrophysics Data System (ADS)

    Kagami, Haruna; Akutsu, Tatsuya; Maegawa, Shingo; Hosokawa, Hiroshi; Nacher, Jose C.

    2015-10-01

    Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10-109). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies.

  8. A Study to Determine Damage Assessment Methods or Models on Air Force Networks

    DTIC Science & Technology

    2005-03-01

    which has made this endeavor possible. Special thanks go to my advisor, Dr . Dennis Strouble for his patience and understanding through the entire... Dennis Strouble , PhD (Chairman) date /signed/ 16 Mar 05...AF network 16. SECURITY CLASSIFICATION OF: UNCLASS 19a. NAME OF RESPONSIBLE PERSON Dennis

  9. Plasticity of gene-regulatory networks controlling sex determination: of masters, slaves, usual suspects, newcomers, and usurpators.

    PubMed

    Herpin, Amaury; Schartl, Manfred

    2015-10-01

    Sexual dimorphism is one of the most pervasive and diverse features of animal morphology, physiology, and behavior. Despite the generality of the phenomenon itself, the mechanisms controlling how sex is determined differ considerably among various organismic groups, have evolved repeatedly and independently, and the underlying molecular pathways can change quickly during evolution. Even within closely related groups of organisms for which the development of gonads on the morphological, histological, and cell biological level is undistinguishable, the molecular control and the regulation of the factors involved in sex determination and gonad differentiation can be substantially different. The biological meaning of the high molecular plasticity of an otherwise common developmental program is unknown. While comparative studies suggest that the downstream effectors of sex-determining pathways tend to be more stable than the triggering mechanisms at the top, it is still unclear how conserved the downstream networks are and how all components work together. After many years of stasis, when the molecular basis of sex determination was amenable only in the few classical model organisms (fly, worm, mouse), recently, sex-determining genes from several animal species have been identified and new studies have elucidated some novel regulatory interactions and biological functions of the downstream network, particularly in vertebrates. These data have considerably changed our classical perception of a simple linear developmental cascade that makes the decision for the embryo to develop as male or female, and how it evolves. © 2015 The Authors.

  10. Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes.

    PubMed

    Zelezniak, Aleksej; Sheridan, Steven; Patil, Kiran Raosaheb

    2014-04-01

    One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First, at the level of individual reactions, metabolite levels are non-linearly dependent on enzyme abundances as per the reaction kinetics mechanisms. Secondly, specific metabolite pools are tightly interlinked with the rest of the metabolic network through their production and consumption reactions. While the role of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different biological perturbations, namely gene knockout, nutrient shock and nutrient change. While the kinetic constraints applied at the level of individual reactions were found to be poor descriptors of the mRNA-metabolite relationship, their use in the context of the network enabled us to correlate changes in the expression of enzyme-coding genes to the alterations in metabolite levels. Our results highlight the key contribution of metabolic network connectivity in mediating cellular control over metabolite levels, and have implications towards bridging the gap between genotype and metabolic phenotype.

  11. Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution.

    PubMed

    Jenkins, Dafyd J; Stekel, Dov J

    2010-02-01

    Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

  12. Interference Cognizant Network Scheduling

    NASA Technical Reports Server (NTRS)

    Varadarajan, Srivatsan (Inventor); Hall, Brendan (Inventor); Smithgall, William Todd (Inventor); Bonk, Ted (Inventor); DeLay, Benjamin F. (Inventor)

    2017-01-01

    Systems and methods for interference cognizant network scheduling are provided. In certain embodiments, a method of scheduling communications in a network comprises identifying a bin of a global timeline for scheduling an unscheduled virtual link, wherein a bin is a segment of the timeline; identifying a pre-scheduled virtual link in the bin; and determining if the pre-scheduled and unscheduled virtual links share a port. In certain embodiments, if the unscheduled and pre-scheduled virtual links don't share a port, scheduling transmission of the unscheduled virtual link to overlap with the scheduled transmission of the pre-scheduled virtual link; and if the unscheduled and pre-scheduled virtual links share a port: determining a start time delay for the unscheduled virtual link based on the port; and scheduling transmission of the unscheduled virtual link in the bin based on the start time delay to overlap part of the scheduled transmission of the pre-scheduled virtual link.

  13. Cell-free Determination of Binary Complexes That Comprise Extended Protein-Protein Interaction Networks of Yersinia pestis.

    PubMed

    Keasey, Sarah L; Natesan, Mohan; Pugh, Christine; Kamata, Teddy; Wuchty, Stefan; Ulrich, Robert G

    2016-10-01

    Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (KD ∼μm) to high-affinity (KD ∼nm) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  14. Earthquake locations determined by the Southern Alaska seismograph network for October 1971 through May 1989

    USGS Publications Warehouse

    Fogleman, Kent A.; Lahr, John C.; Stephens, Christopher D.; Page, Robert A.

    1993-01-01

    This report describes the instrumentation and evolution of the U.S. Geological Survey’s regional seismograph network in southern Alaska, provides phase and hypocenter data for seismic events from October 1971 through May 1989, reviews the location methods used, and discusses the completeness of the catalog and the accuracy of the computed hypocenters. Included are arrival time data for explosions detonated under the Trans-Alaska Crustal Transect (TACT) in 1984 and 1985.The U.S. Geological Survey (USGS) operated a regional network of seismographs in southern Alaska from 1971 to the mid 1990s. The principal purpose of this network was to record seismic data to be used to precisely locate earthquakes in the seismic zones of southern Alaska, delineate seismically active faults, assess seismic risks, document potential premonitory earthquake phenomena, investigate current tectonic deformation, and study the structure and physical properties of the crust and upper mantle. A task fundamental to all of these goals was the routine cataloging of parameters for earthquakes located within and adjacent to the seismograph network.The initial network of 10 stations, 7 around Cook Inlet and 3 near Valdez, was installed in 1971. In subsequent summers additions or modifications to the network were made. By the fall of 1973, 26 stations extended from western Cook Inlet to eastern Prince William Sound, and 4 stations were located to the east between Cordova and Yakutat. A year later 20 additional stations were installed. Thirteen of these were placed along the eastern Gulf of Alaska with support from the National Oceanic and Atmospheric Administration (NOAA) under the Outer Continental Shelf Environmental Assessment Program to investigate the seismicity of the outer continental shelf, a region of interest for oil exploration. Since then the region covered by the network remained relatively fixed while efforts were made to make the stations more reliable through improved electronic

  15. Influence of slice overlap on positron emission tomography image quality

    NASA Astrophysics Data System (ADS)

    McKeown, Clare; Gillen, Gerry; Dempsey, Mary Frances; Findlay, Caroline

    2016-02-01

    PET scans use overlapping acquisition beds to correct for reduced sensitivity at bed edges. The optimum overlap size for the General Electric (GE) Discovery 690 has not been established. This study assesses how image quality is affected by slice overlap. Efficacy of 23% overlaps (recommended by GE) and 49% overlaps (maximum possible overlap) were specifically assessed. European Association of Nuclear Medicine (EANM) guidelines for calculating minimum injected activities based on overlap size were also reviewed. A uniform flood phantom was used to assess noise (coefficient of variation, (COV)) and voxel accuracy (activity concentrations, Bq ml-1). A NEMA (National Electrical Manufacturers Association) body phantom with hot/cold spheres in a background activity was used to assess contrast recovery coefficients (CRCs) and signal to noise ratios (SNR). Different overlap sizes and sphere-to-background ratios were assessed. COVs for 49% and 23% overlaps were 9% and 13% respectively. This increased noise was difficult to visualise on the 23% overlap images. Mean voxel activity concentrations were not affected by overlap size. No clinically significant differences in CRCs were observed. However, visibility and SNR of small, low contrast spheres (⩽13 mm diameter, 2:1 sphere to background ratio) may be affected by overlap size in low count studies if they are located in the overlap area. There was minimal detectable influence on image quality in terms of noise, mean activity concentrations or mean CRCs when comparing 23% overlap with 49% overlap. Detectability of small, low contrast lesions may be affected in low count studies—however, this is a worst-case scenario. The marginal benefits of increasing overlap from 23% to 49% are likely to be offset by increased patient scan times. A 23% overlap is therefore appropriate for clinical use. An amendment to EANM guidelines for calculating injected activities is also proposed which better reflects the effect overlap size has

  16. Cenozoic Motion of Greenland - Overlaps and Seaways

    NASA Astrophysics Data System (ADS)

    Lawver, L. A.; Norton, I. O.; Gahagan, L.

    2014-12-01

    Using the seafloor magnetic anomalies found in the Labrador Sea, North Atlantic and Eurasian basin to constrain the Cenozoic motion of Greenland, we have produced a new model for the tectonic evolution of the region. The aeromagnetic data collected by the Naval Research Lab [Brozena et al., 2003] in the Eurasian Basin and Canadian data from the Labrador Sea have been re-evaluated using new gridding algorithms and profile modeling using ModMag (Mendel et al., 2005). As a consequence, we have changed the published correlations, mostly prior to Chron C6 [19.05 Ma]. Presently published seafloor magnetic anomalies from the Labrador Sea assume that seafloor spreading ceased at C13 [33.06 Ma] but such an assumption produces an unacceptable overlap of Kronprins Christian Land of northeast Greenland with Svalbard, up to 140 km of overlap in some models. Our new model does not need any "unacceptable" overlap but does produce a slight amount of Eocene compression on Svalbard as is found on land there. Our model allows for an Early Eocene seaway between Ellesmere Island and northwest Greenland that may have connected the Labrador Sea through Baffin Bay and ultimately to the nascent Eurasian Basin, although its depth or even its essential existence is unknowable. During the Miocene, there is no room for a deepwater seaway in Fram Strait until at least the very end of the Early Miocene and perhaps not until Middle Miocene. Brozena, J. and six others, 2003. New aerogeophysical study of the Eurasia Basin and Lomonosov Ridge: Implications for basin development. Geology 31, 825-828. Mendel, V., M. Munschy and D.Sauter, 2005, MODMAG, a MATLAB program to model marine magnetic anomalies, Comp. Geosci., 31, .589-597

  17. Overextended sarcomeres regain filament overlap following stretch.

    PubMed

    Panchangam, Appaji; Herzog, Walter

    2012-09-21

    Sarcomere overextension has been widely implicated in stretch-induced muscle injury. Yet, sarcomere overextensions are typically inferred based on indirect evidence obtained in muscle and fibre preparations, where individual sarcomeres cannot be observed during dynamic contractions. Therefore, it remains unclear whether sarcomere overextensions are permanent following injury-inducing stretch-shortening cycles, and thus, if they can explain stretch-induced force loss. We tested the hypothesis that overextended sarcomeres can regain filament overlap in isolated myofibrils from rabbit psoas muscles. Maximally activated myofibrils (n=13) were stretched from an average sarcomere length of 2.6±0.04μm by 0.9μm sarcomere(-1) at a speed of 0.1μm sarcomere(-1)s(-1) and immediately returned to the starting lengths at the same speed (sarcomere strain=34.1±2.3%). Myofibrils were then allowed to contract isometrically at the starting lengths (2.6μm) for ∼30s before relaxing. Force and individual sarcomere lengths were measured continuously. Out of the 182 sarcomeres, 35 sarcomeres were overextended at the peak of stretch, out of which 26 regained filament overlap in the shortening phase while 9 (∼5%) remained overextended. About 35% of the sarcomeres with initial lengths on the descending limb of the force-length relationship and ∼2% of the sarcomeres with shorter initial lengths were overextended. These findings provide first ever direct evidence that overextended sarcomeres can regain filament overlap in the shortening phase following stretch, and that the likelihood of overextension is higher for sarcomeres residing initially on the descending limb.

  18. Review of metabolic pathways activated in cancer cells as determined through isotopic labeling and network analysis.

    PubMed

    Dong, Wentao; Keibler, Mark A; Stephanopoulos, Gregory

    2017-02-10

    Cancer metabolism has emerged as an indispensable part of contemporary cancer research. During the past 10 years, the use of stable isotopic tracers and network analysis have unveiled a number of metabolic pathways activated in cancer cells. Here, we review such pathways along with the particular tracers and labeling observations that led to the discovery of their rewiring in cancer cells. The list of such pathways comprises the reductive metabolism of glutamine, altered glycolysis, serine and glycine metabolism, mutant isocitrate dehydrogenase (IDH) induced reprogramming and the onset of acetate metabolism. Additionally, we demonstrate the critical role of isotopic labeling and network analysis in identifying these pathways. The alterations described in this review do not constitute a complete list, and future research using these powerful tools is likely to discover other cancer-related pathways and new metabolic targets for cancer therapy.

  19. A wireless sensor network system to determine biomechanics of spinal braces during daily living.

    PubMed

    Lou, Edmond; Hill, Doug L; Raso, James V

    2010-03-01

    A spinal brace is a hard shell corset used to treat scoliosis. The force distribution inside the brace is not well understood. This study developed a battery-powered wireless sensor network to continuously monitor forces exerted by the braces to scoliotic patients. This network consisted of one master, up to 15 slave loggers, and one base station. The time of the loggers were synchronized every 6 h to ensure that force measurements were taken at the same time. Each logger could continuously log data for at least 4 months with a sample rate of 1 sample/min. The wireless system was fully tested in the laboratory and individual logger units were tested in 6 patients. The power consumption of each logger for 4 months at 1.2 V was 454 mAh. This system will allow us to investigate the force distribution inside the brace during daily activities.

  20. Technology initiatives with government/business overlap

    NASA Astrophysics Data System (ADS)

    Knapp, Robert H., Jr.

    2015-03-01

    Three important present-day technology development settings involve significant overlap between government and private sectors. The Advanced Research Project Agency for Energy (ARPA-E) supports a wide range of "high risk, high return" projects carried out in academic, non-profit or private business settings. The Materials Genome Initiative (MGI), based in the White House, aims at radical acceleration of the development process for advanced materials. California public utilities such as Pacific Gas & Electric operate under a structure of financial returns and political program mandates that make them arms of public policy as much as independent businesses.

  1. What Determines the Assembly of Transcriptional Network Motifs in Escherichia coli?

    PubMed Central

    Camas, Francisco M.; Poyatos, Juan F.

    2008-01-01

    Transcriptional networks are constituted by a collection of building blocks known as network motifs. Why do motifs appear? An adaptive model of motif emergence was recently questioned in favor of neutralist scenarios. Here, we provide a new picture of motif assembly in Escherichia coli which partially clarifies these contrasting explanations. This is based on characterizing the linkage between motifs and sensing or response specificity of their constituent transcriptional factors (TFs). We find that sensing specificity influences the distribution of autoregulation, while the tendency of a TF to establish feed-forward loops (FFLs) depends on response specificity, i.e., regulon size. Analysis of the latter pattern reveals that coregulation between large regulon-size TFs is common under a network neutral model, leading to the assembly of a great number of FFLs and bifans. In addition, neutral exclusive regulation also leads to a collection of single input modules -the fourth basic motif. On the whole, and even under the conservative neutralist scenario considered, a substantial group of regulatory structures revealed adaptive. These structures visibly function as fully-fledged working units. PMID:18987754

  2. Background Mole Fractions of Hydrocarbons in North America Determined from NOAA Global Reference Network Data

    NASA Astrophysics Data System (ADS)

    Mielke-Maday, I.

    2015-12-01

    The National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division (GMD) maintains a global reference network for over 50 trace gas species and analyzes discrete air samples collected by this network throughout the world at the Earth System Research Laboratory in Boulder, Colorado. In particular, flask samples are analyzed for a number of hydrocarbons with policy and health relevance such as ozone precursors, greenhouse gases, and hazardous air pollutants. Because this global network's sites are remote and therefore minimally influenced by local anthropogenic emissions, these data yield information about background ambient mole fractions and can provide a context for observations collected in intensive field campaigns, such as the Front Range Air Pollution and Photochemistry Experiment (FRAPPE), the Southeast Nexus (SENEX) study, and the DISCOVER-AQ deployments. Information about background mole fractions during field campaigns is critical for calculating hydrocarbon enhancements in the region of study and for assessing the extent to which a particular region's local emissions sources contribute to these enhancements. Understanding the geographic variability of the background and its contribution to regional ambient mole fractions is also crucial for the development of realistic regulations. We present background hydrocarbon mole fractions and their ratios in North America using data from air samples collected in the planetary boundary layer at tall towers and aboard aircraft from 2008 to 2014. We discuss the spatial and seasonal variability in these data. We present trends over the time period of measurements and propose possible explanations for these trends.

  3. Non-destructive determination of metronidazole powder by using artificial neural networks on short-wavelength NIR spectroscopy

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

    The present study aimed at providing a new method in sight into short-wavelength near-infrared (NIR) spectroscopy of in pharmaceutical quantitative analysis. To do that, 124 experimental samples of metronidazole powder were analyzed using artificial neural networks (ANNs) in the 780-1100 nm region of short-wavelength NIR spectra. In this paper, metronidazole was as active component and other two components (magnesium stearate and starch) were as excipients. Different preprocessing spectral data (first-derivative, second-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC)) were applied to establish the ANNs models of metronidazole powder. The degree of approximation, a new evaluation criterion of the networks was employed to prove the accuracy of the predicted results. The results presented here demonstrate that the short-wavelength NIR region is promising for the fast and reliable determination of major component in pharmaceutical analysis.

  4. Determining the amount of anesthetic medicine to be applied by using Elman's recurrent neural networks via resilient back propagation.

    PubMed

    Güntürkün, Rüştü

    2010-08-01

    In this study, Elman recurrent neural networks have been defined by using Resilient Back Propagation in order to determine the depth of anesthesia in the continuation stage of the anesthesia and to estimate the amount of medicine to be applied at that moment. From 30 patients, 57 distinct EEG recordings have been collected prior to during anaesthesia of different levels. The applied artificial neural network is composed of three layers, namely the input layer, the middle layer and the output layer. The nonlinear activation function sigmoid (sigmoid function) has been used in the hidden layer and the output layer. Prediction has been made by means of ANN. Training and testing the ANN have been used previous anaesthesia amount, total power/normal power and total power/previous. The system has been able to correctly purposeful responses in average accuracy of 95% of the cases. This method is also computationally fast and acceptable real-time clinical performance has been obtained.

  5. Extending the dynamic range of copper determination in differential pulse adsorption cathodic stripping voltammetry using wavelet neural network.

    PubMed

    Khayamian, T; Ensafi, Ali A; Benvidi, A

    2006-07-15

    A wavelet neural network (WNN) model is proposed for extending the dynamic range of Cu(II) determination by differential pulse adsorption cathodic stripping voltammetry (DP-AdSV) using xylenol orange (XO) as a suitable ligand. All of voltammograms data consisting of Cu(II) and Cu(II)-XO peak currents were used in WNN model. The WNN model consisted of three layers (2-8-1) with the Morlet mother wavelet transfer function in the hidden layer. The model was able to extend the dynamic range of Cu(II) from its narrow linear range (1-50 ng ml(-1)) to the higher dynamic range (1-1500 ng ml(-1)). The results of the WNN model was also compared with artificial neural network (ANN) model and it was demonstrated the superiority of the WNN model relative to ANN model.

  6. Determining the optimal spatial distribution of weather station networks for lumped and distributed hydrological modelling purposes using RCM datasets

    NASA Astrophysics Data System (ADS)

    Arsenault, R.; Brissette, F.

    2012-04-01

    In many hydrological studies, the main limiting factor in model performance is low meteorological data quality and quantity. In some cases, like in Northern Canada and other sparsely populated areas, the meteorological records are practically inexistent. Installing weather stations becomes a necessity in these areas when water resource management becomes an issue, like when harnessing a river for hydropower generation for example. No guide exists as to where new stations should be located to optimize hydrological performance. The objective of this study is to propose a new experimental and exploratory method for determining the optimal density of a weather station network when being used for long-term hydrological modelling. Data from the Canadian Regional Climate Model at 15km resolution (CRCM15) was used to create a virtual network of stations with long and complete series of meteorological data over the Toulnustouc River basin in central Québec. Three hydrological models were used in this study. Two are lumped (HSAMI and HMETS) while the last is distributed (Hydrotel). The weather stations to be fed to the models were selected in order to minimize the number of stations while maintaining the best hydrological performance possible. A multi-objective genetic algorithm was put in place to determine which stations were to be used, and by the same occasion, where the stations should be located. It was shown that the number of stations making up the network on the Toulnustouc River basin should be at least two (2) but not higher than five (5), no matter what hydrological model is chosen. If the stations are positioned optimally, there is little to no gain to be made with a denser network. The optimization algorithm clearly identified that the right combinations of two or three stations can result in better hydrological performance than if a high density network was fed to the models. However, it was shown that a high number of stations will definitely reduce the

  7. Computational assessment of the influence of the overlap ratio on the power characteristics of a Classical Savonius wind turbine

    NASA Astrophysics Data System (ADS)

    Kacprzak, Konrad; Sobczak, Krzysztof

    2015-09-01

    An influence of the overlap on the performance of the Classical Savonius wind turbine was investigated. Unsteady two-dimensional numerical simulations were carried out for a wide range of overlap ratios. For selected configurations computation quality was verified by comparison with three-dimensional simulations and the wind tunnel experimental data available in literature. A satisfactory agreement was achieved. Power characteristics were determined for all the investigated overlap ratios for selected tip speed ratios. Obtained results indicate that the maximum device performance is achieved for the buckets overlap ratio close to 0.

  8. The Hippocampus and Disambiguation of Overlapping Sequences

    PubMed Central

    Agster, Kara L.; Fortin, Norbert J.; Eichenbaum, Howard

    2010-01-01

    Recent models of hippocampal function emphasize its potential role in disambiguating sequences of events that compose distinct episodic memories. In this study, rats were trained to distinguish two overlapping sequences of odor choices. The capacity to disambiguate the sequences was measured by the critical odor choice after the overlapping elements of the sequences. When the sequences were presented in rapid alternation, damage to the hippocampus, produced either by infusions of the neurotoxin ibotenic acid or by radiofrequency current, produced a severe deficit, although animals with radiofrequency lesions relearned the task. When the sequences were presented spaced apart and in random order, animals with radiofrequency hippocampal lesions could perform the task. However, they failed when a memory delay was imposed before the critical choice. These findings support the hypothesis that the hippocampus is involved in representing sequences of nonspatial events, particularly when interference between the sequences is high or when animals must remember across a substantial delay preceding items in a current sequence. PMID:12097529

  9. Activation of words with phonological overlap

    PubMed Central

    Friedrich, Claudia K.; Felder, Verena; Lahiri, Aditi; Eulitz, Carsten

    2013-01-01

    Multiple lexical representations overlapping with the input (cohort neighbors) are temporarily activated in the listener's mental lexicon when speech unfolds in time. Activation for cohort neighbors appears to rapidly decline as soon as there is mismatch with the input. However, it is a matter of debate whether or not they are completely excluded from further processing. We recorded behavioral data and event-related brain potentials (ERPs) in auditory-visual word onset priming during a lexical decision task. As primes we used the first two syllables of spoken German words. In a carrier word condition, the primes were extracted from spoken versions of the target words (ano-ANORAK “anorak”). In a cohort neighbor condition, the primes were taken from words that overlap with the target word up to the second nucleus (ana—taken from ANANAS “pineapple”). Relative to a control condition, where primes and targets were unrelated, lexical decision responses for cohort neighbors were delayed. This reveals that cohort neighbors are disfavored by the decision processes at the behavioral front end. In contrast, left-anterior ERPs reflected long-lasting facilitated processing of cohort neighbors. We interpret these results as evidence for extended parallel processing of cohort neighbors. That is, in parallel to the preparation and elicitation of delayed lexical decision responses to cohort neighbors, aspects of the processing system appear to keep track of those less efficient word candidates. PMID:24009593

  10. Boundary overlap for medical image segmentation evaluation

    NASA Astrophysics Data System (ADS)

    Yeghiazaryan, Varduhi; Voiculescu, Irina

    2017-03-01

    All medical image segmentation algorithms need to be validated and compared, and yet no evaluation framework is widely accepted within the imaging community. Collections of segmentation results often need to be compared and ranked by their effectiveness. Evaluation measures which are popular in the literature are based on region overlap or boundary distance. None of these are consistent in the way they rank segmentation results: they tend to be sensitive to one or another type of segmentation error (size, location, shape) but no single measure covers all error types. We introduce a new family of measures, with hybrid characteristics. These measures quantify similarity/difference of segmented regions by considering their overlap around the region boundaries. This family is more sensitive than other measures in the literature to combinations of segmentation error types. We compare measure performance on collections of segmentation results sourced from carefully compiled 2D synthetic data, and also on 3D medical image volumes. We show that our new measure: (1) penalises errors successfully, especially those around region boundaries; (2) gives a low similarity score when existing measures disagree, thus avoiding overly inflated scores; and (3) scores segmentation results over a wider range of values. We consider a representative measure from this family and the effect of its only free parameter on error sensitivity, typical value range, and running time.

  11. Adaptive overlapped sub-blocks contrast enhancement

    NASA Astrophysics Data System (ADS)

    Chen, Anqiu; Yuan, Fei; Liu, Jing; Liu, Siqi; Li, An; Zheng, Zhenrong

    2016-09-01

    In this paper, an overlapped sub-block gray-level average method for contrast enhancement is presented. The digital image correction of uneven illumination under microscope transmittance is a problem in image processing, also sometimes the image in the dark place need to correct the uneven problem. A new correction method was proposed based on the mask method and sub-blocks gray-level average method because Traditional mask method and background fitting method are restricted due to application scenarios, and the corrected image brightness is low by using background fitting method, so it has some limitations of the application. In this paper, we introduce a new method called AOSCE for image contrast enhancement. The image is divided into many sub-blocks which are overlapped, calculate the average gray-level of the whole image as M and the calculate the average gray-level of each one as mi, next for each block it can get d = mi - m, each block minus d to get a new image, and then get the minimum gray-level of each block into a matrix DD to get the background, and use bilinearity to get the same scale of the image. over fitting the image in matlab in order to get smoother image, then minus the background to get the contrast enhancement image.

  12. Heterogeneity of asthma–COPD overlap syndrome

    PubMed Central

    Joo, Hyonsoo; Han, Deokjae; Lee, Jae Ha; Rhee, Chin Kook

    2017-01-01

    Many patients suffering from asthma or COPD have overlapping features of both diseases. However, a phenotypical approach for evaluating asthma–COPD overlap syndrome (ACOS) has not been established. In this report, we examined the phenotypes in patients with ACOS. Patients diagnosed with ACOS between 2011 and 2015 were identified and classified into four phenotype groups. Group A was composed of patients who smoked <10 pack years and had blood eosinophil counts ≥300. Group B was composed of patients who smoked <10 pack years and had blood eosinophil counts <300. Group C was composed of patients who smoked ≥10 pack years and had blood eosinophil counts ≥300. Group D was composed of patients who smoked <10 pack years and had blood eosinophil counts <300. Clinical characteristics were analyzed and compared among groups. Comparisons were made among 103 ACOS patients. Patients in group D were oldest, while patients in group A were youngest. There were relatively more female patients in groups A and B; the majority of patients in groups C and D were male. The degree of airflow obstruction was most severe in group C. The rate of being free of severe exacerbation was significantly lower in group C than in the other groups. In this study, each ACOS phenotype showed different characteristics. The proportion of patients free of severe exacerbation differed significantly among groups. At this time, further studies on the phenotypes of ACOS are required. PMID:28260876

  13. Visual object cognition precedes but also temporally overlaps mental rotation.

    PubMed

    Schendan, Haline E; Lucia, Lisa C

    2009-10-19

    Two-dimensional, mental rotation of alphanumeric characters and geometric figures is related to linear increases in parietal negativity between 400 and 800 ms as rotation increases, similar to linear increases with rotation in response times. This suggests that the frontoparietal networks implicated in mental rotation are engaged after 400 ms. However, the time course of three-dimensional object mental rotation using the classic Shepard-Metzler task has not been studied, even though this is one of the most commonly used versions in behavioral and neuroimaging work. Using this task, this study replicated a prior neuroimaging version using event-related potentials. Results confirmed linear mental rotation effects on performance and parietal negativity. In addition, a frontocentral N350 complex that indexes visual object cognition processes was more negative with mental rotation and showed linear trends at frontopolar sites from 200 to 700 ms and centrofrontal sites from 400 to 500 ms. The centrofrontal negativity has been implicated in object working memory processes in ventrolateral prefrontal and occipitotemporal areas. The frontopolar N350 has been implicated in processes that compute the spatial relations among parts of objects to resolve visual differences between object representations and enable an accurate cognitive decision involving a network of ventrocaudal intraparietal, ventral premotor, and inferotemporal cortices. Overall, the time course indicates that visual object cognition processes precede (200-500 ms) but also overlap the initial phase of mental rotation (500-700 ms) indexed by parietal negativity.

  14. New experimental method for lidar overlap factor using a CCD side-scatter technique.

    PubMed

    Wang, Zhenzhu; Tao, Zongming; Liu, Dong; Wu, Decheng; Xie, Chenbo; Wang, Yingjian

    2015-04-15

    In theory, lidar overlap factor can be derived from the difference between the particle backscatter coefficient retrieved from lidar elastic signal without overlap correction and the actual particle backscatter coefficient, which can be obtained by other measured techniques. The side-scatter technique using a CCD camera is testified to be a powerful tool to detect the particle backscatter coefficient in near ground layer during night time. A new experiment approach to determine the overlap factor for vertically pointing lidar is presented in this study, which can be applied to Mie lidars. The effect of overlap factor on Mie lidar is corrected by an iteration algorithm combining the retrieved particle backscatter coefficient using CCD side-scatter method and Fernald method. This method has been successfully applied to Mie lidar measurements during a routine campaign, and the comparison of experimental results in different atmosphere conditions demonstrated that this method is available in practice.

  15. Artificial neural network for the determination of Hubble Space Telescope aberration from stellar images.

    PubMed

    Barrett, T K; Sandler, D G

    1993-04-01

    An artificial-neural-network method, first developed for the measurement and control of atmospheric phase distortion, using stellar images, was used to estimate the optical aberration of the Hubble Space Telescope. A total of 26 estimates of distortion was obtained from 23 stellar images acquired at several secondary-mirror axial positions. The results were expressed as coefficients of eight orthogonal Zernike polynomials: focus through third-order spherical. For all modes other than spherical the measured aberration was small. The average spherical aberration of the estimates was -0.299 microm rms, which is in good agreement with predictions obtained when iterative phase-retrieval algorithms were used.

  16. Artificial neural network for the determination of Hubble Space Telescope aberration from stellar images

    NASA Technical Reports Server (NTRS)

    Barrett, Todd K.; Sandler, David G.

    1993-01-01

    An artificial-neural-network method, first developed for the measurement and control of atmospheric phase distortion, using stellar images, was used to estimate the optical aberration of the Hubble Space Telescope. A total of 26 estimates of distortion was obtained from 23 stellar images acquired at several secondary-mirror axial positions. The results were expressed as coefficients of eight orthogonal Zernike polynomials: focus through third-order spherical. For all modes other than spherical the measured aberration was small. The average spherical aberration of the estimates was -0.299 micron rms, which is in good agreement with predictions obtained when iterative phase-retrieval algorithms were used.

  17. Artificial neural network for the determination of Hubble Space Telescope aberration from stellar images

    NASA Technical Reports Server (NTRS)

    Barrett, Todd K.; Sandler, David G.

    1993-01-01

    An artificial-neural-network method, first developed for the measurement and control of atmospheric phase distortion, using stellar images, was used to estimate the optical aberration of the Hubble Space Telescope. A total of 26 estimates of distortion was obtained from 23 stellar images acquired at several secondary-mirror axial positions. The results were expressed as coefficients of eight orthogonal Zernike polynomials: focus through third-order spherical. For all modes other than spherical the measured aberration was small. The average spherical aberration of the estimates was -0.299 micron rms, which is in good agreement with predictions obtained when iterative phase-retrieval algorithms were used.

  18. Information theoretic approach using neural network for determining radiometer observations from radar and vice versa

    NASA Astrophysics Data System (ADS)

    Kannan, Srinivasa Ramanujam; Chandrasekar, V.

    2016-05-01

    Even though both the rain measuring instruments, radar and radiometer onboard the TRMM observe the same rain scenes, they both are fundamentally different instruments. Radar is an active instrument and measures backscatter component from vertical rain structure; whereas radiometer is a passive instrument that obtains integrated observation of full depth of the cloud and rain structure. Further, their spatial resolutions on ground are different. Nevertheless, both the instruments are observing the same rain scene and retrieve three dimensional rainfall products. Hence it is only natural to seek answer to the question, what type of information about radiometric observations can be directly retrieved from radar observations. While there are several ways to answer this question, an informational theoretic approach using neural networks has been described in the present work to find if radiometer observations can be predicted from radar observations. A database of TMI brightness temperature and collocated TRMM vertical attenuation corrected reflectivity factor from the year 2012 was considered. The entire database is further classified according to surface type. Separate neural networks were trained for land and ocean and the results are presented.

  19. The spatial variability of vehicle densities as determinant of urban network capacity.

    PubMed

    Mazloumian, Amin; Geroliminis, Nikolas; Helbing, Dirk

    2010-10-13

    Due to the complexity of the traffic flow dynamics in urban road networks, most quantitative descriptions of city traffic so far have been based on computer simulations. This contribution pursues a macroscopic (fluid-dynamic) simulation approach, which facilitates a simple simulation of congestion spreading in cities. First, we show that a quantization of the macroscopic turning flows into units of single vehicles is necessary to obtain realistic fluctuations in the traffic variables, and how this can be implemented in a fluid-dynamic model. Then, we propose a new method to simulate destination flows without the requirement of individual route assignments. Combining both methods allows us to study a variety of different simulation scenarios. These reveal fundamental relationships between the average flow, the average density and the variability of the vehicle densities. Considering the inhomogeneity of traffic as an independent variable can eliminate the scattering of congested flow measurements. The variability also turns out to be a key variable of urban traffic performance. Our results can be explained through the number of full links of the road network, and approximated by a simple analytical formula.

  20. Multiple mechanisms determine ER network morphology during the cell cycle in Xenopus egg extracts

    PubMed Central

    Wang, Songyu; Romano, Fabian B.; Field, Christine M.

    2013-01-01

    In metazoans the endoplasmic reticulum (ER) changes during the cell cycle, with the nuclear envelope (NE) disassembling and reassembling during mitosis and the peripheral ER undergoing extensive remodeling. Here we address how ER morphology is generated during the cell cycle using crude and fractionated Xenopus laevis egg extracts. We show that in interphase the ER is concentrated at the microtubule (MT)-organizing center by dynein and is spread by outward extension of ER tubules through their association with plus ends of growing MTs. Fusion of membranes into an ER network is dependent on the guanosine triphosphatase atlastin (ATL). NE assembly requires fusion by both ATL and ER-soluble N-ethyl-maleimide–sensitive factor adaptor protein receptors. In mitotic extracts, the ER converts into a network of sheets connected by ER tubules and loses most of its interactions with MTs. Together, these results indicate that fusion of ER membranes by ATL and interaction of ER with growing MT ends and dynein cooperate to generate distinct ER morphologies during the cell cycle. PMID:24297752

  1. Dendritic and Axonal Propagation Delays Determine Emergent Structures of Neuronal Networks with Plastic Synapses

    PubMed Central

    Madadi Asl, Mojtaba; Valizadeh, Alireza; Tass, Peter A.

    2017-01-01

    Spike-timing-dependent plasticity (STDP) modifies synaptic strengths based on the relative timing of pre- and postsynaptic spikes. The temporal order of spikes turned out to be crucial. We here take into account how propagation delays, composed of dendritic and axonal delay times, may affect the temporal order of spikes. In a minimal setting, characterized by neglecting dendritic and axonal propagation delays, STDP eliminates bidirectional connections between two coupled neurons and turns them into unidirectional connections. In this paper, however, we show that depending on the dendritic and axonal propagation delays, the temporal order of spikes at the synapses can be different from those in the cell bodies and, consequently, qualitatively different connectivity patterns emerge. In particular, we show that for a system of two coupled oscillatory neurons, bidirectional synapses can be preserved and potentiated. Intriguingly, this finding also translates to large networks of type-II phase oscillators and, hence, crucially impacts on the overall hierarchical connectivity patterns of oscillatory neuronal networks. PMID:28045109

  2. Modeling access network: Maximum node-degree determines the traffic of the internet

    NASA Astrophysics Data System (ADS)

    Chen, Yan; Chen, Lixue; Zhang, Songlin; Zhang, Jie; Li, Ping

    2013-01-01

    It has been demonstrated that both routers and domains in the Internet have a scale-invariant fractal structure. However, nodes in access network (AN) level are found demonstrate a random geographic distribution. In this paper, we investigate the AN by proposing a model in which the nodes are randomly posited at given regions. In particular, we design a new node-attachment strategy that can yield a connectivity pattern more consistent with real configuration. Taking into account of both the geographical distribution of the nodes and specific local connectivity, our model can therefore serve as more accurate description of real-world Internet. We furthermore use this model to study the traffic load of the Internet, and we found that the optimal betweenness centrality variance and average path length, which is associated with an optimal traffic load, can be obtained by setting a suitable maximum degree K max for the AN. Our results indicates that the optimal value of K max increases linearly with the number of nodes, which provide useful guidance to improve throughput and transmission efficiency when designing the access network.

  3. Dendritic and Axonal Propagation Delays Determine Emergent Structures of Neuronal Networks with Plastic Synapses.

    PubMed

    Madadi Asl, Mojtaba; Valizadeh, Alireza; Tass, Peter A

    2017-01-03

    Spike-timing-dependent plasticity (STDP) modifies synaptic strengths based on the relative timing of pre- and postsynaptic spikes. The temporal order of spikes turned out to be crucial. We here take into account how propagation delays, composed of dendritic and axonal delay times, may affect the temporal order of spikes. In a minimal setting, characterized by neglecting dendritic and axonal propagation delays, STDP eliminates bidirectional connections between two coupled neurons and turns them into unidirectional connections. In this paper, however, we show that depending on the dendritic and axonal propagation delays, the temporal order of spikes at the synapses can be different from those in the cell bodies and, consequently, qualitatively different connectivity patterns emerge. In particular, we show that for a system of two coupled oscillatory neurons, bidirectional synapses can be preserved and potentiated. Intriguingly, this finding also translates to large networks of type-II phase oscillators and, hence, crucially impacts on the overall hierarchical connectivity patterns of oscillatory neuronal networks.

  4. Separation and sequence detection of overlapped fingerprints: experiments and first results

    NASA Astrophysics Data System (ADS)

    Kärgel, Rainer; Giebel, Sascha; Leich, Marcus; Dittmann, Jana

    2011-11-01

    Latent fingerprints provide vital information in modern crime scene investigation. On frequently touched surfaces the fingerprints may overlap which poses a major problem for forensic analysis. In order to make such overlapping fingerprints available for analysis, they have to be separated. An additional evaluation of the sequence in which the fingerprints were brought onto the surface can help to reconstruct the progression of events. Advances in both tasks can considerably aid crime investigation agencies and are the subject of this work. Here, a statistical approach, initially devised for the separation of overlapping text patterns by Tonazzini et al.,1 is employed to separate overlapping fingerprints. The method involves a maximum a posteriori estimation of the single fingerprints and the mixing coefficients, computed by an expectation-maximization algorithm. A fingerprint age determination feature based on corrosion is evaluated for sequence estimation. The approaches are evaluated using 30 samples of overlapping latent fingerprints on two different substrates. The fingerprint images are acquired with a non-destructive chromatic white light surface measurement device, each sample containing exactly two fingerprints that overlap in the center of the image. Since forensic investigations rely on manual assessment of acquired fingerprints by forensics experts, a subjective scale ranging from 0 to 8 is used to rate the separation results. Our results indicate that the chosen method can separate overlapped fingerprints which exhibit strong differences in contrast, since results gradually improve with the growing contrast difference of the overlapping fingerprints. Investigating the effects of corrosion leads to a reliable determination of the fingerprints' sequence as the timespan between their leaving increases.

  5. Phonological and orthographic overlap effects in fast and masked priming.

    PubMed

    Frisson, Steven; Bélanger, Nathalie N; Rayner, Keith

    2014-01-01

    We investigated how orthographic and phonological information is activated during reading, using a fast priming task, and during single-word recognition, using masked priming. Specifically, different types of overlap between prime and target were contrasted: high orthographic and high phonological overlap (track-crack), high orthographic and low phonological overlap (bear-gear), or low orthographic and high phonological overlap (fruit-chute). In addition, we examined whether (orthographic) beginning overlap (swoop-swoon) yielded the same priming pattern as end (rhyme) overlap (track-crack). Prime durations were 32 and 50 ms in the fast priming version and 50 ms in the masked priming version, and mode of presentation (prime and target in lower case) was identical. The fast priming experiment showed facilitatory priming effects when both orthography and phonology overlapped, with no apparent differences between beginning and end overlap pairs. Facilitation was also found when prime and target only overlapped orthographically. In contrast, the masked priming experiment showed inhibition for both types of end overlap pairs (with and without phonological overlap) and no difference for begin overlap items. When prime and target only shared principally phonological information, facilitation was only found with a long prime duration in the fast priming experiment, while no differences were found in the masked priming version. These contrasting results suggest that fast priming and masked priming do not necessarily tap into the same type of processing.

  6. Phonological and Orthographic Overlap Effects in Fast and Masked Priming

    PubMed Central

    Frisson, Steven; Bélanger, Nathalie N.; Rayner, Keith

    2014-01-01

    We investigated how orthographic and phonological information is activated during reading, using a fast priming task, and during single word recognition, using masked priming. Specifically, different types of overlap between prime and target were contrasted: high orthographic and high phonological overlap (track-crack), high orthographic and low phonological overlap (bear-gear), or low orthographic and high phonological overlap (fruit-chute). In addition, we examined whether (orthographic) beginning overlap (swoop-swoon) yielded the same priming pattern as end (rhyme) overlap (track-crack). Prime durations were 32 and 50ms in the fast priming version, and 50ms in the masked priming version, and mode of presentation (prime and target in lower case) was identical. The fast priming experiment showed facilitatory priming effects when both orthography and phonology overlapped, with no apparent differences between beginning and end overlap pairs. Facilitation was also found when prime and target only overlapped orthographically. In contrast, the masked priming experiment showed inhibition for both types of end overlap pairs (with and without phonological overlap), and no difference for begin overlap items. When prime and target only shared principally phonological information, facilitation was only found with a long prime duration in the fast priming experiment, while no differences were found in the masked priming version. These contrasting results suggest that fast priming and masked priming do not necessarily tap into the same type of processing. PMID:24365065

  7. Determination of UT1 and polar motion by the deep space network using very long baseline interferometry

    NASA Technical Reports Server (NTRS)

    Fanselow, J. L.; Thomas, J. B.; Cohen, E. J.; Macdoran, P. F.; Melbourne, W. G.; Mulhall, B. D.; Purcell, G. H.; Rogstad, D. H.; Skjerve, L. J.; Spitzmesser, D. J.

    1979-01-01

    Measurements of UT1 with a formal accuracy as low as 0.6 msec with only 6 hr of data and construction of a radio astrometric catalog of approximately 45 sources whose positions are known to better than 0.05 arcsec are described which were made possible by very long-baseline interferometry (VLBI) with the Deep Space Network (DSN). The characteristics and anticipated performance of the complete VLBI system being implemented within the DSN are discussed. It is noted that one of the capabilities of this system is the measurement of UT1 and polar motion at weekly intervals and that the determinations should be obtained with decimeter accuracy.

  8. Discrimination Analysis of Earthquakes and Man-Made Events Using ARMA Coefficients Determination by Artificial Neural Networks

    SciTech Connect

    AllamehZadeh, Mostafa

    2011-12-15

    A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neural system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.

  9. Time-quefrency analysis of overlapping similar microseismic events

    NASA Astrophysics Data System (ADS)

    Nagano, Koji

    2016-05-01

    In this paper, I describe a new technique to determine the interval between P-waves in similar, overlapping microseismic events. The similar microseismic events that occur with overlapping waveforms are called `proximate microseismic doublets' herein. Proximate microseismic doublets had been discarded in previous studies because we had not noticed their usefulness. Analysis of similar events can show relative locations of sources between them. Analysis of proximate microseismic doublets can provide more precise relative source locations because variation in the velocity structure has little influence on their relative travel times. It is necessary to measure the interval between the P-waves in the proximate microseismic doublets to determine their relative source locations. A `proximate microseismic doublet' is a pair of microseismic events in which the second event arrives before the attenuation of the first event. Cepstrum analysis can provide the interval even though the second event overlaps the first event. However, a cepstrum of a proximate microseismic doublet generally has two peaks, one representing the interval betwe