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Sample records for directed network modules

  1. Directed network modules

    NASA Astrophysics Data System (ADS)

    Palla, Gergely; Farkas, Illés J.; Pollner, Péter; Derényi, Imre; Vicsek, Tamás

    2007-06-01

    A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos Rényi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs.

  2. Centrality properties of directed module members in social networks

    NASA Astrophysics Data System (ADS)

    Pollner, Péter; Palla, Gergely; Ábel, Dániel; Vicsek, András; Farkas, Illés J.; Derényi, Imre; Vicsek, Tamás

    2008-08-01

    Several recent studies of complex networks have suggested algorithms for locating network communities, also called modules or clusters, which are mostly defined as groups of nodes with dense internal connections. Along with the rapid development of these clustering techniques, the ability of revealing overlaps between communities has become very important as well. An efficient search technique for locating overlapping modules is provided by the Clique Percolation Method (CPM) and its extension to directed graphs, the CPMd algorithm. Here we investigate the centrality properties of directed module members in social networks obtained from e-mail exchanges and from sociometric questionnaires. Our results indicate that nodes in the overlaps between modules play a central role in the studied systems. Furthermore, the two different types of networks show interesting differences in the relation between the centrality measures and the role of the nodes in the directed modules.

  3. Optical beamforming networks employing phase modulation and direct detection

    NASA Astrophysics Data System (ADS)

    Xue, Xiaoxiao; Zheng, Xiaoping; Zhang, Hanyi; Zhou, Bingkun

    2011-06-01

    We propose a novel dispersion-based optical beamforming network scheme employing phase modulation and direct detection. Optical phase modulators have the advantages of simple-structure, low loss and absence of bias. Dispersion-induced phase-to-intensity conversion is utilized to facilitate direct detection. A structure of wideband dispersive device (WDD) cascaded with periodic dispersive device (PDD) is introduced to enhance the system flexibility, so that the delay adjustability and RF response can be properly designed respectively by choosing appropriate dispersions of the WDD and PDD. A concept-proof system with a wideband chirped fiber grating (CFG) as the WDD and two multiband CFGs (MCFG1 and MCFG2) as the PDD separately is built to demonstrate the basic idea. The delay tuning range is 0-1.8 ns with increment of 164.2 ps. The passband center is 30 GHz for MCFG1 and 20 GHz for MCFG2, and the fractional bandwidth is 51.8%. The shot-noise-limited spurious-free dynamic range is also analyzed and measured to be 105.7 dB ṡ Hz2/3 when the average photocurrent is 2.7 mA.

  4. System performance analysis of time-division-multiplexing passive optical network using directly modulated lasers or colorless optical network units

    NASA Astrophysics Data System (ADS)

    Gong, Xiaoxue; Guo, Lei; Liu, Yejun; Zhou, Yufang

    2015-05-01

    As a promising technology for broadband communication, passive optical network (PON) has been deployed to support the last-mile broadband access network. In particular, time-division-multiplexing PON (TDM-PON) has been widely used owing to its mature technology and low cost. To practically implement TDM-PONs, the combination of intensity modulation and direct detection is a very promising technique because it achieves cost reduction in system installation and maintenance. However, the current intensity-modulation and direct-detection TDM-PON still suffers from some problems, which mainly include a high-power penalty, detrimental Brillouin backscattering (BB), and so on. Thus, using directly modulated lasers (DMLs) and colorless optical network units (ONUs), respectively, two intensity-modulation and direct-detection TDM-PON architectures are proposed. Using VPI (an optical simulation software developed by VPIphotonics company) simulators, we first analyze the influences on DML-based intensity-modulation and direct-detection TDM-PON (system 1) performances, which mainly include bit error rate (BER) and power penalty. Next, the BB effect on the BER of the intensity-modulation and direct-detection TDM-PON that uses colorless ONUs (system 2) is also investigated. The simulation results show that: (1) a low-power penalty is achieved without degrading the BER of system 1, and (2) the BB can be effectively reduced using phase modulation of the optical carrier in system 2.

  5. Tunable directly modulated fiber ring laser using a reflective semiconductor optical amplifier for WDM access networks.

    PubMed

    Lin, Zih-Rong; Liu, Cheng-Kuang; Jhang, Yu-Jhu; Keiser, Gerd

    2010-08-16

    We have proposed a stable, wideband, and tunable directly modulated fiber ring laser (TDMFRL) by using a reflective semiconductor optical amplifier (RSOA) and an optical tunable filter (OTF). For use in a bidirectional access network, the TDMFRL not only generates downstream data traffic but also serves as the wavelength-selecting injection light source for the Fabry-Pérot laser diode (FP-LD) located at the subscriber site. We experimentally demonstrated a bidirectional transmission at 1.25-Gb/s direct modulation over a 25-km single-mode fiber (SMF), thereby showing good performance in a wavelength division multiplexing (WDM) access network. PMID:20721147

  6. Direct-Sequence Spread-Spectrum Modulation for Utility Packet Transmission in Underwater Acoustic Communication Networks

    NASA Astrophysics Data System (ADS)

    Duke, Peter S.

    2002-09-01

    This thesis investigates the feasibility and performance of using Direct-Sequence Spread-Spectrum (DSSS) modulation for utility-packet transmission in Seaweb underwater wireless acoustic communications networks, Seaweb networks require robust channel-tolerant utility packets having a low probability of detection (LPD) and allowing for multi-user access, MATLAB code simulated the DSSS transmitter and receiver structures and a modeled channel impulse response represented the underwater environment, The specific modulation scheme implemented is direct-sequence, differentially encoded binary phase-shift keying (DS-DBPSK) with quadrature spreading, Performance is examined using Monte Carlo simulation Bit error rates and packet error rates for various signal-to-noise ratios and channel conditions are presented and the use of a RAKE receiver, forward error-correction coding and symbol interleaving are examined for improving system performance.

  7. Effects of aging on value-directed modulation of semantic network activity during verbal learning.

    PubMed

    Cohen, Michael S; Rissman, Jesse; Suthana, Nanthia A; Castel, Alan D; Knowlton, Barbara J

    2016-01-15

    While impairments in memory recall are apparent in aging, older adults show a remarkably preserved ability to selectively remember information deemed valuable. Here, we use fMRI to compare brain activation in healthy older and younger adults during encoding of high and low value words to determine whether there are differences in how older adults achieve value-directed memory selectivity. We find that memory selectivity in older adults is associated with value-related changes in activation during word presentation in left hemisphere regions that are involved in semantic processing, similar to young adults. However, highly selective young adults show a relatively greater increase in semantic network activity during encoding of high-value items, whereas highly selective older adults show relatively diminished activity during encoding of low-value items. Additionally, only younger adults showed value-related increases in activity in semantic and reward processing regions during presentation of the value cue preceding each to-be-remembered word. Young adults therefore respond to cue value more proactively than do older adults, yet the magnitude of value-related differences in cue period brain activity did not predict individual differences in memory selectivity. Thus, our data also show that age-related reductions in prestimulus activity do not always lead to inefficient performance. PMID:26244278

  8. Community Structure in Directed Networks

    NASA Astrophysics Data System (ADS)

    Leicht, E. A.; Newman, M. E. J.

    2008-03-01

    We consider the problem of finding communities or modules in directed networks. In the past, the most common approach to this problem has been to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used community finding technique of modularity maximization can be generalized in a principled fashion to incorporate information contained in edge directions. We describe an explicit algorithm based on spectral optimization of the modularity and show that it gives demonstrably better results than previous methods on a variety of test networks, both real and computer generated.

  9. Weighted network modules

    NASA Astrophysics Data System (ADS)

    Farkas, Illés; Ábel, Dániel; Palla, Gergely; Vicsek, Tamás

    2007-06-01

    The inclusion of link weights into the analysis of network properties allows a deeper insight into the (often overlapping) modular structure of real-world webs. We introduce a clustering algorithm clique percolation method with weights (CPMw) for weighted networks based on the concept of percolating k-cliques with high enough intensity. The algorithm allows overlaps between the modules. First, we give detailed analytical and numerical results about the critical point of weighted k-clique percolation on (weighted) Erdos Rényi graphs. Then, for a scientist collaboration web and a stock correlation graph we compute three-link weight correlations and with the CPMw the weighted modules. After reshuffling link weights in both networks and computing the same quantities for the randomized control graphs as well, we show that groups of three or more strong links prefer to cluster together in both original graphs.

  10. Modulation of large-scale brain networks by transcranial direct current stimulation evidenced by resting-state functional MRI

    PubMed Central

    Peña-Gómez, Cleofé; Sala-Lonch, Roser; Junqué, Carme; Clemente, Immaculada C.; Vidal, Dídac; Bargalló, Núria; Falcón, Carles; Valls-Solé, Josep; Pascual-Leone, Álvaro; Bartrés-Faz, David

    2013-01-01

    Background Brain areas interact mutually to perform particular complex brain functions such as memory or language. Furthermore, under resting-state conditions several spatial patterns have been identified that resemble functional systems involved in cognitive functions. Among these, the default-mode network (DMN), which is consistently deactivated during task periods and is related to a variety of cognitive functions, has attracted most attention. In addition, in resting-state conditions some brain areas engaged in focused attention (such as the anticorrelated network, AN) show a strong negative correlation with DMN; as task demand increases, AN activity rises, and DMN activity falls. Objective We combined transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) to investigate these brain network dynamics. Methods Ten healthy young volunteers underwent four blocks of resting-state fMRI (10-minutes), each of them immediately after 20 minutes of sham or active tDCS (2 mA), on two different days. On the first day the anodal electrode was placed over the left dorsolateral prefrontal cortex (DLPFC) (part of the AN) with the cathode over the contralateral supraorbital area, and on the second day, the electrode arrangement was reversed (anode right-DLPFC, cathode left-supraorbital). Results After active stimulation, functional network connectivity revealed increased synchrony within the AN components and reduced synchrony in the DMN components. Conclusions Our study reveals a reconfiguration of intrinsic brain activity networks after active tDCS. These effects may help to explain earlier reports of improvements in cognitive functions after anodal-tDCS, where increasing cortical excitability may have facilitated reconfiguration of functional brain networks to address upcoming cognitive demands. PMID:21962981

  11. Clustering signatures classify directed networks

    NASA Astrophysics Data System (ADS)

    Ahnert, S. E.; Fink, T. M. A.

    2008-09-01

    We use a clustering signature, based on a recently introduced generalization of the clustering coefficient to directed networks, to analyze 16 directed real-world networks of five different types: social networks, genetic transcription networks, word adjacency networks, food webs, and electric circuits. We show that these five classes of networks are cleanly separated in the space of clustering signatures due to the statistical properties of their local neighborhoods, demonstrating the usefulness of clustering signatures as a classifier of directed networks.

  12. Reciprocity in directed networks

    NASA Astrophysics Data System (ADS)

    Yin, Mei; Zhu, Lingjiong

    2016-04-01

    Reciprocity is an important characteristic of directed networks and has been widely used in the modeling of World Wide Web, email, social, and other complex networks. In this paper, we take a statistical physics point of view and study the limiting entropy and free energy densities from the microcanonical ensemble, the canonical ensemble, and the grand canonical ensemble whose sufficient statistics are given by edge and reciprocal densities. The sparse case is also studied for the grand canonical ensemble. Extensions to more general reciprocal models including reciprocal triangle and star densities will likewise be discussed.

  13. Extracellular vesicles modulate the glioblastoma microenvironment via a tumor suppression signaling network directed by miR-1

    PubMed Central

    Nowicki, Michal O.; Peruzzi, Pierpaolo; Ansari, Khairul; Ogawa, Daisuke; Balaj, Leonora; De Rienzo, Gianluca; Mineo, Marco; Nakano, Ichiro; Ostrowski, Michael C.; Hochberg, Fred; Weissleder, Ralph; Lawler, Sean E.; Chiocca, E. Antonio; Godlewski, Jakub

    2014-01-01

    Extracellular vesicles (EVs) have emerged as important mediators of intercellular communication in cancer, including by conveying tumor-promoting microRNAs between cells, but their regulation is poorly understood. In this study, we report the findings of a comparative microRNA profiling and functional analysis in human glioblastoma (GBM) that identifies miR-1 as an orchestrator of EV function and GBM growth and invasion. Ectopic expression of miR-1 in GBM cells blocked in vivo growth, neovascularization and invasiveness. These effects were associated with a role for miR-1 in intercellular communication in the microenvironment mediated by EVs released by cancer stem-like GBM cells. An EV-dependent phenotype defined by GBM invasion, neurosphere growth and endothelial tube formation was mitigated by loading miR-1 into GBM-derived EVs. Protein cargo in EVs was characterized to learn how miR-1 directed EV function. The mRNA encoding Annexin A2 (ANXA2), one of the most abundant proteins in GBM-derived EVs, was found to be a direct target of miR-1 control. In addition, EV-derived miR-1 along with other ANXA2 EV networking partners targeted multiple pro-oncogenic signals in cells within the GBM microenvironment. Together, our results showed how EV signalling promotes the malignant character of GBM and how ectopic expression of miR-1 can mitigate this character, with possible implications for how to develop a unique miRNA-based therapy for GBM management. PMID:24310399

  14. Simple model for directed networks

    NASA Astrophysics Data System (ADS)

    Morelli, Luis G.

    2003-06-01

    We study a model for directed networks based on the Watts-Stogatz model for small-world phenomena. We focus on some topological aspects of directed networks inspired in food web theory, namely, the fraction of basal and top nodes in the network and node level distributions. We argue that in directed networks basal nodes play an important role, collecting information or resources from the environment. We give analytical expressions for the fraction of basal and top nodes for the model, and study the node level distributions with numerical simulations.

  15. Epidemic threshold in directed networks.

    PubMed

    Li, Cong; Wang, Huijuan; Van Mieghem, Piet

    2013-12-01

    Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τ(c) for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ(1) in directed networks, where λ(1), also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ(1), principal eigenvector x(1), spectral gap (λ(1)-|λ(2)|), and algebraic connectivity μ(N-1) is studied. Important findings are that the spectral radius λ(1) decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρ(D). Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution. PMID:24483506

  16. Epidemic threshold in directed networks

    NASA Astrophysics Data System (ADS)

    Li, Cong; Wang, Huijuan; Van Mieghem, Piet

    2013-12-01

    Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τc for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ1 in directed networks, where λ1, also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ1, principal eigenvector x1, spectral gap (λ1-λ2), and algebraic connectivity μN-1 is studied. Important findings are that the spectral radius λ1 decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρD. Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

  17. Breakdown of interdependent directed networks.

    PubMed

    Liu, Xueming; Stanley, H Eugene; Gao, Jianxi

    2016-02-01

    Increasing evidence shows that real-world systems interact with one another via dependency connectivities. Failing connectivities are the mechanism behind the breakdown of interacting complex systems, e.g., blackouts caused by the interdependence of power grids and communication networks. Previous research analyzing the robustness of interdependent networks has been limited to undirected networks. However, most real-world networks are directed, their in-degrees and out-degrees may be correlated, and they are often coupled to one another as interdependent directed networks. To understand the breakdown and robustness of interdependent directed networks, we develop a theoretical framework based on generating functions and percolation theory. We find that for interdependent Erdős-Rényi networks the directionality within each network increases their vulnerability and exhibits hybrid phase transitions. We also find that the percolation behavior of interdependent directed scale-free networks with and without degree correlations is so complex that two criteria are needed to quantify and compare their robustness: the percolation threshold and the integrated size of the giant component during an entire attack process. Interestingly, we find that the in-degree and out-degree correlations in each network layer increase the robustness of interdependent degree heterogeneous networks that most real networks are, but decrease the robustness of interdependent networks with homogeneous degree distribution and with strong coupling strengths. Moreover, by applying our theoretical analysis to real interdependent international trade networks, we find that the robustness of these real-world systems increases with the in-degree and out-degree correlations, confirming our theoretical analysis. PMID:26787907

  18. Potential Theory for Directed Networks

    PubMed Central

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

    2013-01-01

    Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

  19. Sampling properties of directed networks.

    PubMed

    Son, S-W; Christensen, C; Bizhani, G; Foster, D V; Grassberger, P; Paczuski, M

    2012-10-01

    For many real-world networks only a small "sampled" version of the original network may be investigated; those results are then used to draw conclusions about the actual system. Variants of breadth-first search (BFS) sampling, which are based on epidemic processes, are widely used. Although it is well established that BFS sampling fails, in most cases, to capture the IN component(s) of directed networks, a description of the effects of BFS sampling on other topological properties is all but absent from the literature. To systematically study the effects of sampling biases on directed networks, we compare BFS sampling to random sampling on complete large-scale directed networks. We present new results and a thorough analysis of the topological properties of seven complete directed networks (prior to sampling), including three versions of Wikipedia, three different sources of sampled World Wide Web data, and an Internet-based social network. We detail the differences that sampling method and coverage can make to the structural properties of sampled versions of these seven networks. Most notably, we find that sampling method and coverage affect both the bow-tie structure and the number and structure of strongly connected components in sampled networks. In addition, at a low sampling coverage (i.e., less than 40%), the values of average degree, variance of out-degree, degree autocorrelation, and link reciprocity are overestimated by 30% or more in BFS-sampled networks and only attain values within 10% of the corresponding values in the complete networks when sampling coverage is in excess of 65%. These results may cause us to rethink what we know about the structure, function, and evolution of real-world directed networks. PMID:23214649

  20. Sampling properties of directed networks

    NASA Astrophysics Data System (ADS)

    Son, S.-W.; Christensen, C.; Bizhani, G.; Foster, D. V.; Grassberger, P.; Paczuski, M.

    2012-10-01

    For many real-world networks only a small “sampled” version of the original network may be investigated; those results are then used to draw conclusions about the actual system. Variants of breadth-first search (BFS) sampling, which are based on epidemic processes, are widely used. Although it is well established that BFS sampling fails, in most cases, to capture the IN component(s) of directed networks, a description of the effects of BFS sampling on other topological properties is all but absent from the literature. To systematically study the effects of sampling biases on directed networks, we compare BFS sampling to random sampling on complete large-scale directed networks. We present new results and a thorough analysis of the topological properties of seven complete directed networks (prior to sampling), including three versions of Wikipedia, three different sources of sampled World Wide Web data, and an Internet-based social network. We detail the differences that sampling method and coverage can make to the structural properties of sampled versions of these seven networks. Most notably, we find that sampling method and coverage affect both the bow-tie structure and the number and structure of strongly connected components in sampled networks. In addition, at a low sampling coverage (i.e., less than 40%), the values of average degree, variance of out-degree, degree autocorrelation, and link reciprocity are overestimated by 30% or more in BFS-sampled networks and only attain values within 10% of the corresponding values in the complete networks when sampling coverage is in excess of 65%. These results may cause us to rethink what we know about the structure, function, and evolution of real-world directed networks.

  1. Weighted Percolation on Directed Networks

    NASA Astrophysics Data System (ADS)

    Restrepo, Juan G.; Ott, Edward; Hunt, Brian R.

    2008-02-01

    We present and numerically test an analysis of the percolation transition for general node removal strategies valid for locally treelike directed networks. On the basis of heuristic arguments we predict that, if the probability of removing node i is pi, the network disintegrates if pi is such that the largest eigenvalue of the matrix with entries Aij(1-pi) is less than 1, where A is the adjacency matrix of the network. The knowledge or applicability of a Markov network model is not required by our theory, thus making it applicable to situations not covered by previous works.

  2. Notational usage modulates attention networks in binumerates

    PubMed Central

    Koul, Atesh; Tyagi, Vaibhav; Singh, Nandini C.

    2014-01-01

    Multicultural environments require learning multiple number notations wherein some are encountered more frequently than others. This leads to differences in exposure and consequently differences in usage between notations. We find that differential notational usage imposes a significant neurocognitive load on number processing. Despite simultaneous acquisition, twenty four adult binumerates, familiar with two positional writing systems namely Hindu Nagari digits and Hindu Arabic digits, reported significantly lower preference and usage for Nagari as compared to Arabic. Twenty-four participants showed significantly increased reaction times and reduced accuracy while performing magnitude comparison tasks in Nagari with respect to Arabic. Functional magnetic resonance imaging revealed that processing Nagari elicited significantly greater activity in number processing and attention networks. A direct subtraction of networks for Nagari and Arabic notations revealed a neural circuit comprising of bilateral Intra-parietal Sulcus (IPS), Inferior and Mid Frontal Gyri, Fusiform Gyrus and the Anterior Cingulate Cortex (FDR p < 0.005). Additionally, whole brain correlation analysis showed that activity in the left inferior parietal region was modulated by task performance in Nagari. We attribute the increased activation in Nagari to increased task difficulty due to infrequent exposure and usage. Our results reiterate the role of left IPS in modulating performance in numeric tasks and highlight the role of the attention network for monitoring symbolic notation mode in binumerates. PMID:24904366

  3. Direct Current Series Circuits: An Educational Module.

    ERIC Educational Resources Information Center

    Sturgess, Keith

    This module was developed as remedial material for physics students who have difficulty understanding concepts of circuits and calculating resistances, and voltage drops and currents. Lists of prerequisite skills and instructional objectives are followed by a pretest (with answers). Students are directed to the subject matter in the module based…

  4. OM300 Direction Drilling Module

    DOE Data Explorer

    MacGugan, Doug

    2013-08-22

    OM300 – Geothermal Direction Drilling Navigation Tool: Design and produce a prototype directional drilling navigation tool capable of high temperature operation in geothermal drilling Accuracies of 0.1° Inclination and Tool Face, 0.5° Azimuth Environmental Ruggedness typical of existing oil/gas drilling Multiple Selectable Sensor Ranges High accuracy for navigation, low bandwidth High G-range & bandwidth for Stick-Slip and Chirp detection Selectable serial data communications Reduce cost of drilling in high temperature Geothermal reservoirs Innovative aspects of project Honeywell MEMS* Vibrating Beam Accelerometers (VBA) APS Flux-gate Magnetometers Honeywell Silicon-On-Insulator (SOI) High-temperature electronics Rugged High-temperature capable package and assembly process

  5. Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice.

    PubMed

    Obertello, Mariana; Shrivastava, Stuti; Katari, Manpreet S; Coruzzi, Gloria M

    2015-08-01

    In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis. PMID:26045464

  6. Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice1[OPEN

    PubMed Central

    Obertello, Mariana; Shrivastava, Stuti; Katari, Manpreet S.; Coruzzi, Gloria M.

    2015-01-01

    In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis. PMID:26045464

  7. Investigation of direct integrated optics modulators

    NASA Technical Reports Server (NTRS)

    Batchman, T. E.; Mcwright, G. M.

    1981-01-01

    Direct optical modulation techniques applicable to integrated optical data preprocessors were studied. Emphasis was placed on the analysis and fabrication of a field effect type modulator. A series of computer modeling studies were performed to determine the effects of semiconductor cladding on the fields of propagating waves in planar dielectric waveguides. These studies predicted that changes in the propagation characteristics of waveguides clad with silicon and gallium arsenide could be made large enough to be useful in modulators. These effects are dependent on the complex permittivity and thickness of the cladding. Since the conductivity of the cladding can be changed by the photon generation of hole-electron pairs, incoherent light may be used as the input to modulate a coherent light beam. Waveguides were fabricated and silicon claddings were applied to verify the theoretical predictions.

  8. Optimal design of reverse osmosis module networks

    SciTech Connect

    Maskan, F.; Wiley, D.E.; Johnston, L.P.M.; Clements, D.J.

    2000-05-01

    The structure of individual reverse osmosis modules, the configuration of the module network, and the operating conditions were optimized for seawater and brackish water desalination. The system model included simple mathematical equations to predict the performance of the reverse osmosis modules. The optimization problem was formulated as a constrained multivariable nonlinear optimization. The objective function was the annual profit for the system, consisting of the profit obtained from the permeate, capital cost for the process units, and operating costs associated with energy consumption and maintenance. Optimization of several dual-stage reverse osmosis systems were investigated and compared. It was found that optimal network designs are the ones that produce the most permeate. It may be possible to achieve economic improvements by refining current membrane module designs and their operating pressures.

  9. Module of network RAID implemention on cluster computing

    NASA Astrophysics Data System (ADS)

    Zhou, Ke; Zhang, Jiangling

    2001-09-01

    Network RAID is a good idea in mass storage field. It can reduce response time and increase data transferring speed of storage system, especially to network application. But it is a problem that how to use network RAID to improve the performance of parallel processing system. It is current to use cluster architecture to develop high performance parallel computer. Cluster is a set of complete computers that can run one task at the same time through a high-speed network. The normal cluster belongs to non-shared architecture. This architecture makes cluster consume most of time on communicating with each other. Network RAID has its natural characteristic that is connected to network directly. Using network RAID in cluster makes a disk-shared architecture of cluster. There are two modules to use network RAID in cluster, one is using network RAID as a shared storage space, the other is using network RAID as a private storage space. As a shared storage space, network RAID records the public data that will be used by some nodes. As a private storage space, each node is provided with a segment of data space in network RAID. The other important problem is how the node of cluster communicates with network RAID. Because network RAID has two channels for network communication, one is command channel, the other is data channel, and nodes must be modified to adapt this communication module. We use TCP/IP protocol, and define some data transferring rules in application level. At last, it must be paid more attention to performance evaluation of cluster system. In normal cluster architecture, load is distributed into each node. But in disk-shared cluster architecture, some part of load may be assigned to network RAID. How to evaluate the performance is due to the part of load assigned to network RAID. This paper discusses above three problems, that are using module, communication module and performance, and provides a new disk-shared architecture of cluster that uses network RAID.

  10. Caffeine Modulates Attention Network Function

    ERIC Educational Resources Information Center

    Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

    2010-01-01

    The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

  11. Downhole drilling network using burst modulation techniques

    DOEpatents

    Hall; David R. , Fox; Joe

    2007-04-03

    A downhole drilling system is disclosed in one aspect of the present invention as including a drill string and a transmission line integrated into the drill string. Multiple network nodes are installed at selected intervals along the drill string and are adapted to communicate with one another through the transmission line. In order to efficiently allocate the available bandwidth, the network nodes are configured to use any of numerous burst modulation techniques to transmit data.

  12. Local community extraction in directed networks

    NASA Astrophysics Data System (ADS)

    Ning, Xuemei; Liu, Zhaoqi; Zhang, Shihua

    2016-06-01

    Network is a simple but powerful representation of real-world complex systems. Network community analysis has become an invaluable tool to explore and reveal the internal organization of nodes. However, only a few methods were directly designed for community-detection in directed networks. In this article, we introduce the concept of local community structure in directed networks and provide a generic criterion to describe a local community with two properties. We further propose a stochastic optimization algorithm to rapidly detect a local community, which allows for uncovering the directional modular characteristics in directed networks. Numerical results show that the proposed method can resolve detailed local communities with directional information and provide more structural characteristics of directed networks than previous methods.

  13. Network management, status and directions

    SciTech Connect

    Cottrell, R.L.A.; Streater, T.C.

    1992-09-01

    It has been said that the ``network is the system``. This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus and across the world and spanning many administrative domains. This talk will review the status of existing tools to address management for networks. It draws on experience from both within and outside the HEP community.

  14. Network management, status and directions

    SciTech Connect

    Cottrell, R.L.A.; Streater, T.C.

    1992-09-01

    It has been said that the network is the system''. This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus and across the world and spanning many administrative domains. This talk will review the status of existing tools to address management for networks. It draws on experience from both within and outside the HEP community.

  15. The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

    SciTech Connect

    Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

    2014-11-07

    In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

  16. Cholinergic modulation of hippocampal network function

    PubMed Central

    Teles-Grilo Ruivo, Leonor M.; Mellor, Jack R.

    2013-01-01

    Cholinergic septohippocampal projections from the medial septal area to the hippocampus are proposed to have important roles in cognition by modulating properties of the hippocampal network. However, the precise spatial and temporal profile of acetylcholine release in the hippocampus remains unclear making it difficult to define specific roles for cholinergic transmission in hippocampal dependent behaviors. This is partly due to a lack of tools enabling specific intervention in, and recording of, cholinergic transmission. Here, we review the organization of septohippocampal cholinergic projections and hippocampal acetylcholine receptors as well as the role of cholinergic transmission in modulating cellular excitability, synaptic plasticity, and rhythmic network oscillations. We point to a number of open questions that remain unanswered and discuss the potential for recently developed techniques to provide a radical reappraisal of the function of cholinergic inputs to the hippocampus. PMID:23908628

  17. Google matrix analysis of directed networks

    NASA Astrophysics Data System (ADS)

    Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

    2015-10-01

    In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

  18. Weakly explosive percolation in directed networks.

    PubMed

    Squires, Shane; Sytwu, Katherine; Alcala, Diego; Antonsen, Thomas M; Ott, Edward; Girvan, Michelle

    2013-05-01

    Percolation, the formation of a macroscopic connected component, is a key feature in the description of complex networks. The dynamical properties of a variety of systems can be understood in terms of percolation, including the robustness of power grids and information networks, the spreading of epidemics and forest fires, and the stability of gene regulatory networks. Recent studies have shown that if network edges are added "competitively" in undirected networks, the onset of percolation is abrupt or "explosive." The unusual qualitative features of this phase transition have been the subject of much recent attention. Here we generalize this previously studied network growth process from undirected networks to directed networks and use finite-size scaling theory to find several scaling exponents. We find that this process is also characterized by a very rapid growth in the giant component, but that this growth is not as sudden as in undirected networks. PMID:23767507

  19. On functional module detection in metabolic networks.

    PubMed

    Koch, Ina; Ackermann, Jörg

    2013-01-01

    Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145

  20. On Functional Module Detection in Metabolic Networks

    PubMed Central

    Koch, Ina; Ackermann, Jörg

    2013-01-01

    Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145

  1. Giant components in directed multiplex networks

    NASA Astrophysics Data System (ADS)

    Azimi-Tafreshi, N.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2014-11-01

    We describe the complex global structure of giant components in directed multiplex networks that generalizes the well-known bow-tie structure, generic for ordinary directed networks. By definition, a directed multiplex network contains vertices of one type and directed edges of m different types. In directed multiplex networks, we distinguish a set of different giant components based on the existence of directed paths of different types between their vertices such that for each type of edges, the paths run entirely through only edges of that type. If, in particular, m =2 , we define a strongly viable component as a set of vertices in which for each type of edges each two vertices are interconnected by at least two directed paths in both directions, running through the edges of only this type. We show that in this case, a directed multiplex network contains in total nine different giant components including the strongly viable component. In general, the total number of giant components is 3m. For uncorrelated directed multiplex networks, we obtain exactly the size and the emergence point of the strongly viable component and estimate the sizes of other giant components.

  2. Giant components in directed multiplex networks.

    PubMed

    Azimi-Tafreshi, N; Dorogovtsev, S N; Mendes, J F F

    2014-11-01

    We describe the complex global structure of giant components in directed multiplex networks that generalizes the well-known bow-tie structure, generic for ordinary directed networks. By definition, a directed multiplex network contains vertices of one type and directed edges of m different types. In directed multiplex networks, we distinguish a set of different giant components based on the existence of directed paths of different types between their vertices such that for each type of edges, the paths run entirely through only edges of that type. If, in particular, m=2, we define a strongly viable component as a set of vertices in which for each type of edges each two vertices are interconnected by at least two directed paths in both directions, running through the edges of only this type. We show that in this case, a directed multiplex network contains in total nine different giant components including the strongly viable component. In general, the total number of giant components is 3^{m}. For uncorrelated directed multiplex networks, we obtain exactly the size and the emergence point of the strongly viable component and estimate the sizes of other giant components. PMID:25493836

  3. Core organization of directed complex networks

    NASA Astrophysics Data System (ADS)

    Azimi-Tafreshi, N.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2013-03-01

    The recursive removal of leaves (dead end vertices) and their neighbors from an undirected network results, when this pruning algorithm stops, in a so-called core of the network. This specific subgraph should be distinguished from k-cores, which are principally different subgraphs in networks. If the vertex mean degree of a network is sufficiently large, the core is a giant cluster containing a finite fraction of vertices. We find that generalization of this pruning algorithm to directed networks provides a significantly more complex picture of cores. By implementing a rate equation approach to this pruning procedure for directed uncorrelated networks, we identify a set of cores progressively embedded into each other in a network and describe their birth points and structure.

  4. Transcranial direct current stimulation modulates pattern separation.

    PubMed

    Cappiello, Marcus; Xie, Weizhen; David, Alexander; Bikson, Marom; Zhang, Weiwei

    2016-08-01

    Maintaining similar memories in a distinct and nonoverlapping manner, known as pattern separation, is an important mnemonic process. The medial temporal lobe, especially the hippocampus, has been implicated in this crucial memory function. The present study thus examines whether it is possible to modulate pattern separation using bilateral transcranial direct current stimulation (tDCS) over the temporal lobes. Specifically, in this study, pattern separation was assessed using the Mnemonic Similarity Task following 15-min offline bilateral temporal lobe tDCS (left cathode and right anode or left anode and right cathode) or sham stimulation. In the Mnemonic Similarity Task, participants studied a series of sequentially presented visual objects. In the subsequent recognition memory test, participants viewed a series of sequentially presented objects that could be old images from study, novel foils, or lures that were visually similar to the studied images. Participants reported whether these images were exactly the same as, similar to, or different from the studied images. Following both active tDCS conditions, participants were less likely to identify lures as 'similar' compared with the sham condition, indicating a reduction in pattern separation resulting from temporal lobe tDCS. In contrast, no significant difference in overall accuracy was found for participants' discrimination of old and new images. Together, these results suggest that temporal lobe tDCS can selectively modulate the pattern separation function without changing participants' baseline recognition memory performance. PMID:27285728

  5. Hierarchy in directed random networks

    NASA Astrophysics Data System (ADS)

    Mones, Enys

    2013-02-01

    In recent years, the theory and application of complex networks have been quickly developing in a markable way due to the increasing amount of data from real systems and the fruitful application of powerful methods used in statistical physics. Many important characteristics of social or biological systems can be described by the study of their underlying structure of interactions. Hierarchy is one of these features that can be formulated in the language of networks. In this paper we present some (qualitative) analytic results on the hierarchical properties of random network models with zero correlations and also investigate, mainly numerically, the effects of different types of correlations. The behavior of the hierarchy is different in the absence and the presence of giant components. We show that the hierarchical structure can be drastically different if there are one-point correlations in the network. We also show numerical results suggesting that the hierarchy does not change monotonically with the correlations and there is an optimal level of nonzero correlations maximizing the level of hierarchy.

  6. RNA Directed Modulation of Phenotypic Plasticity in Human Cells.

    PubMed

    Trakman, Laura; Hewson, Chris; Burdach, Jon; Morris, Kevin V

    2016-01-01

    Natural selective processes have been known to drive phenotypic plasticity, which is the emergence of different phenotypes from one genome following environmental stimulation. Long non-coding RNAs (lncRNAs) have been observed to modulate transcriptional and epigenetic states of genes in human cells. We surmised that lncRNAs are governors of phenotypic plasticity and drive natural selective processes through epigenetic modulation of gene expression. Using heat shocked human cells as a model we find several differentially expressed transcripts with the top candidates being lncRNAs derived from retro-elements. One particular retro-element derived transcripts, Retro-EIF2S2, was found to be abundantly over-expressed in heat shocked cells. Over-expression of Retro-EIF2S2 significantly enhanced cell viability and modulated a predisposition for an adherent cellular phenotype upon heat shock. Mechanistically, we find that this retro-element derived transcript interacts directly with a network of proteins including 40S ribosomal protein S30 (FAU), Eukaryotic translation initiation factor 5A (EIF5A), and Ubiquitin-60S ribosomal protein L40 (UBA52) to affect protein modulated cell adhesion pathways. We find one motif in Retro-EIF2S2 that exhibits binding to FAU and modulates phenotypic cell transitions from adherent to suspension states. The observations presented here suggest that retroviral derived transcripts actively modulate phenotypic plasticity in human cells in response to environmental selective pressures and suggest that natural selection may play out through the action of retro-elements in human cells. PMID:27082860

  7. RNA Directed Modulation of Phenotypic Plasticity in Human Cells

    PubMed Central

    Burdach, Jon; Morris, Kevin V.

    2016-01-01

    Natural selective processes have been known to drive phenotypic plasticity, which is the emergence of different phenotypes from one genome following environmental stimulation. Long non-coding RNAs (lncRNAs) have been observed to modulate transcriptional and epigenetic states of genes in human cells. We surmised that lncRNAs are governors of phenotypic plasticity and drive natural selective processes through epigenetic modulation of gene expression. Using heat shocked human cells as a model we find several differentially expressed transcripts with the top candidates being lncRNAs derived from retro-elements. One particular retro-element derived transcripts, Retro-EIF2S2, was found to be abundantly over-expressed in heat shocked cells. Over-expression of Retro-EIF2S2 significantly enhanced cell viability and modulated a predisposition for an adherent cellular phenotype upon heat shock. Mechanistically, we find that this retro-element derived transcript interacts directly with a network of proteins including 40S ribosomal protein S30 (FAU), Eukaryotic translation initiation factor 5A (EIF5A), and Ubiquitin-60S ribosomal protein L40 (UBA52) to affect protein modulated cell adhesion pathways. We find one motif in Retro-EIF2S2 that exhibits binding to FAU and modulates phenotypic cell transitions from adherent to suspension states. The observations presented here suggest that retroviral derived transcripts actively modulate phenotypic plasticity in human cells in response to environmental selective pressures and suggest that natural selection may play out through the action of retro-elements in human cells. PMID:27082860

  8. Hemispheric modulations of the attentional networks.

    PubMed

    Spagna, Alfredo; Martella, Diana; Fuentes, Luis J; Marotta, Andrea; Casagrande, Maria

    2016-10-01

    Although several recent studies investigated the hemispheric contributions to the attentional networks using the Attention Network Test (ANT), the role of the cerebral hemispheres in modulating the interaction among them remains unclear. In this study, two lateralized versions of this test (LANT) were used to investigate theal effects on the attentional networks under different conflict conditions. One version, the LANTI-A, presented arrows as target and flankers, while the other version, the LANTI-F, had fruits as target and flankers. Data collected from forty-seven participants confirmed well-known results on the efficiency and interactions among the attentional networks. Further, a left visual field advantage was found when a target occurred in an unattended location (e.g. invalid trials), only with the LANTI-F, but not with LANTI-A. The present study adds more evidence to the hemispheric asymmetry of the orienting of attention, and further reveals patterns of interactions between the attentional networks and the visual fields across different conflicting conditions, underlying the dynamic control of attention in complex environments. PMID:27566000

  9. Nonconsensus opinion model on directed networks

    NASA Astrophysics Data System (ADS)

    Qu, Bo; Li, Qian; Havlin, Shlomo; Stanley, H. Eugene; Wang, Huijuan

    2014-11-01

    Dynamic social opinion models have been widely studied on undirected networks, and most of them are based on spin interaction models that produce a consensus. In reality, however, many networks such as Twitter and the World Wide Web are directed and are composed of both unidirectional and bidirectional links. Moreover, from choosing a coffee brand to deciding who to vote for in an election, two or more competing opinions often coexist. In response to this ubiquity of directed networks and the coexistence of two or more opinions in decision-making situations, we study a nonconsensus opinion model introduced by Shao et al. [Phys. Rev. Lett. 103, 018701 (2009), 10.1103/PhysRevLett.103.018701] on directed networks. We define directionality ξ as the percentage of unidirectional links in a network, and we use the linear correlation coefficient ρ between the in-degree and out-degree of a node to quantify the relation between the in-degree and out-degree. We introduce two degree-preserving rewiring approaches which allow us to construct directed networks that can have a broad range of possible combinations of directionality ξ and linear correlation coefficient ρ and to study how ξ and ρ impact opinion competitions. We find that, as the directionality ξ or the in-degree and out-degree correlation ρ increases, the majority opinion becomes more dominant and the minority opinion's ability to survive is lowered.

  10. Optimal synchronization of directed complex networks

    NASA Astrophysics Data System (ADS)

    Skardal, Per Sebastian; Taylor, Dane; Sun, Jie

    2016-09-01

    We study optimal synchronization of networks of coupled phase oscillators. We extend previous theory for optimizing the synchronization properties of undirected networks to the important case of directed networks. We derive a generalized synchrony alignment function that encodes the interplay between the network structure and the oscillators' natural frequencies and serves as an objective measure for the network's degree of synchronization. Using the generalized synchrony alignment function, we show that a network's synchronization properties can be systematically optimized. This framework also allows us to study the properties of synchrony-optimized networks, and in particular, investigate the role of directed network properties such as nodal in- and out-degrees. For instance, we find that in optimally rewired networks, the heterogeneity of the in-degree distribution roughly matches the heterogeneity of the natural frequency distribution, but no such relationship emerges for out-degrees. We also observe that a network's synchronization properties are promoted by a strong correlation between the nodal in-degrees and the natural frequencies of oscillators, whereas the relationship between the nodal out-degrees and the natural frequencies has comparatively little effect. This result is supported by our theory, which indicates that synchronization is promoted by a strong alignment of the natural frequencies with the left singular vectors corresponding to the largest singular values of the Laplacian matrix.

  11. Reconstructing Directed Networks From Noisy Dynamics

    NASA Astrophysics Data System (ADS)

    Tam, Hiu Ching; Ching, Emily Sc

    Complex systems can be fruitfully studied as networks of many elementary units, known as nodes, interacting with one another with the interactions being the links between the nodes. The overall behavior of the systems depends crucially on the network structure depicting how the nodes are linked with each other. It is usually possible to measure the dynamics of the individual nodes but difficult, if not impossible, to directly measure the interactions or links between the nodes. For most systems of interest, the links are directional in that one node affects the dynamics of the other but not vice versa. Moreover, the strength of interaction can vary for different links. Reconstructing directed and weighted networks from dynamics is one of the biggest challenges in network research. We have studied directed and weighted networks modelled by noisy dynamical systems with nonlinear dynamics and developed a method that reconstructs the links and their directions using only the dynamics of the nodes as input. Our method is motivated by a mathematical result derived for dynamical systems that approach a fixed point in the noise-free limit. We show that our method gives good reconstruction results for several directed and weighted networks with different nonlinear dynamics. Supported by Hong Kong Research Grants Council under Grant No. CUHK 14300914.

  12. Multifunction audio digitizer. [producing direct delta and pulse code modulation

    NASA Technical Reports Server (NTRS)

    Monford, L. G., Jr. (Inventor)

    1974-01-01

    An illustrative embodiment of the invention includes apparatus which simultaneously produces both direct delta modulation and pulse code modulation. An input signal, after amplification, is supplied to a window comparator which supplies a polarity control signal to gate the output of a clock to the appropriate input of a binary up-down counter. The control signals provide direct delta modulation while the up-down counter output provides pulse code modulation.

  13. Dynamics-based centrality for directed networks

    NASA Astrophysics Data System (ADS)

    Masuda, Naoki; Kori, Hiroshi

    2010-11-01

    Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

  14. Data reliability in complex directed networks

    NASA Astrophysics Data System (ADS)

    Sanz, Joaquín; Cozzo, Emanuele; Moreno, Yamir

    2013-12-01

    The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimerá and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way.

  15. Multiscale ensemble clustering for finding modules in complex networks

    NASA Astrophysics Data System (ADS)

    Kim, Eun-Youn; Hwang, Dong-Uk; Ko, Tae-Wook

    2012-02-01

    The identification of modules in complex networks is important for the understanding of systems. Here, we propose an ensemble clustering method incorporating node groupings in various sizes and the sequential removal of weak ties between nodes which are rarely grouped together. This method successfully detects modules in various networks, such as hierarchical random networks and the American college football network, with known modular structures. Some of the results are compared with those obtained by modularity optimization and K-means clustering.

  16. Arabidopsis gene co-expression network and its functional modules

    PubMed Central

    Mao, Linyong; Van Hemert, John L; Dash, Sudhansu; Dickerson, Julie A

    2009-01-01

    Background Biological networks characterize the interactions of biomolecules at a systems-level. One important property of biological networks is the modular structure, in which nodes are densely connected with each other, but between which there are only sparse connections. In this report, we attempted to find the relationship between the network topology and formation of modular structure by comparing gene co-expression networks with random networks. The organization of gene functional modules was also investigated. Results We constructed a genome-wide Arabidopsis gene co-expression network (AGCN) by using 1094 microarrays. We then analyzed the topological properties of AGCN and partitioned the network into modules by using an efficient graph clustering algorithm. In the AGCN, 382 hub genes formed a clique, and they were densely connected only to a small subset of the network. At the module level, the network clustering results provide a systems-level understanding of the gene modules that coordinate multiple biological processes to carry out specific biological functions. For instance, the photosynthesis module in AGCN involves a very large number (> 1000) of genes which participate in various biological processes including photosynthesis, electron transport, pigment metabolism, chloroplast organization and biogenesis, cofactor metabolism, protein biosynthesis, and vitamin metabolism. The cell cycle module orchestrated the coordinated expression of hundreds of genes involved in cell cycle, DNA metabolism, and cytoskeleton organization and biogenesis. We also compared the AGCN constructed in this study with a graphical Gaussian model (GGM) based Arabidopsis gene network. The photosynthesis, protein biosynthesis, and cell cycle modules identified from the GGM network had much smaller module sizes compared with the modules found in the AGCN, respectively. Conclusion This study reveals new insight into the topological properties of biological networks. The

  17. Optical waveform generation using a directly modulated laser

    NASA Astrophysics Data System (ADS)

    Cartledge, John C.; Karar, Abdullah S.; Roberts, Kim

    2013-10-01

    The capability of a directly modulated laser (DML) can be dramatically enhanced through precise control of the drive current waveform based on digital signal processing (DSP) and a digital-to-analog convertor (DAC). In this paper, a novel method to pre-compensate fiber dispersion for metro and regional networks is described for a bit rate of 10.709 Gb/s using a DML. A look-up table (LUT) for the drive current is optimized for dispersion mitigation. The entries of the LUT are determined based on the effects of the DML adiabatic and transient chirp on pulse propagation, the nonlinear mapping between the input current and the output optical power, and the bandwidth of the DML package. A DAC operating at 2 samples per bit (21.418 GSa/s with 6 bit resolution) converts the digital samples at the output of the LUT to an analog current waveform driving the DML. Experimental results for a bit rate of 10.709 Gb/s and on-off keying demonstrate a transmission reach of 252 km using a DML intended for 2.5 Gb/s operation and 608 km using a chirp managed laser intended for 10 Gb/s operation. Using this approach (DSP + DAC), the generation of 10.709 Gb/s differential phase shift keying (DPSK) and 56 Gb/s 16-ary quadrature amplitude modulation, sub-carrier multiplexed (QAM SCM) optical signals using the direct modulation of a passive feedback laser is also presented. 6-bit DACs operating at sampling rates of 21.418 GSa/s and 28 GSa/s, respectively, was used to generate the requisite analog current waveform.

  18. Clustering and community detection in directed networks: A survey

    NASA Astrophysics Data System (ADS)

    Malliaros, Fragkiskos D.; Vazirgiannis, Michalis

    2013-12-01

    Networks (or graphs) appear as dominant structures in diverse domains, including sociology, biology, neuroscience and computer science. In most of the aforementioned cases graphs are directed - in the sense that there is directionality on the edges, making the semantics of the edges nonsymmetric as the source node transmits some property to the target one but not vice versa. An interesting feature that real networks present is the clustering or community structure property, under which the graph topology is organized into modules commonly called communities or clusters. The essence here is that nodes of the same community are highly similar while on the contrary, nodes across communities present low similarity. Revealing the underlying community structure of directed complex networks has become a crucial and interdisciplinary topic with a plethora of relevant application domains. Therefore, naturally there is a recent wealth of research production in the area of mining directed graphs - with clustering being the primary method sought and the primary tool for community detection and evaluation. The goal of this paper is to offer an in-depth comparative review of the methods presented so far for clustering directed networks along with the relevant necessary methodological background and also related applications. The survey commences by offering a concise review of the fundamental concepts and methodological base on which graph clustering algorithms capitalize on. Then we present the relevant work along two orthogonal classifications. The first one is mostly concerned with the methodological principles of the clustering algorithms, while the second one approaches the methods from the viewpoint regarding the properties of a good cluster in a directed network. Further, we present methods and metrics for evaluating graph clustering results, demonstrate interesting application domains and provide promising future research directions.

  19. Essential Communication and Documentation Skills. Module: Giving Directions to Residents.

    ERIC Educational Resources Information Center

    Medina, Muriel; And Others

    This module is the fifth of 10 in the Essential Communication and Documentation Skills curriculum. It develops the ability to give directions, a workplace literacy skill identified as being directly related to the job of the direct care worker. The curriculum is designed to improve the competence of New York State Division for Youth direct care…

  20. Random walks in directed modular networks

    NASA Astrophysics Data System (ADS)

    Comin, Cesar H.; Viana, Mateus P.; Antiqueira, Lucas; Costa, Luciano da F.

    2014-12-01

    Because diffusion typically involves symmetric interactions, scant attention has been focused on studying asymmetric cases. However, important networked systems underlain by diffusion (e.g. cortical networks and WWW) are inherently directed. In the case of undirected diffusion, it can be shown that the steady-state probability of the random walk dynamics is fully correlated with the degree, which no longer holds for directed networks. We investigate the relationship between such probability and the inward node degree, which we call efficiency, in modular networks. Our findings show that the efficiency of a given community depends mostly on the balance between its ingoing and outgoing connections. In addition, we derive analytical expressions to show that the internal degree of the nodes does not play a crucial role in their efficiency, when considering the Erdős-Rényi and Barabási-Albert models. The results are illustrated with respect to the macaque cortical network, providing subsidies for improving transportation and communication systems.

  1. Percolation of networks with directed dependency links

    NASA Astrophysics Data System (ADS)

    Niu, Dunbiao; Yuan, Xin; Du, Minhui; Stanley, H. Eugene; Hu, Yanqing

    2016-04-01

    The self-consistent probabilistic approach has proven itself powerful in studying the percolation behavior of interdependent or multiplex networks without tracking the percolation process through each cascading step. In order to understand how directed dependency links impact criticality, we employ this approach to study the percolation properties of networks with both undirected connectivity links and directed dependency links. We find that when a random network with a given degree distribution undergoes a second-order phase transition, the critical point and the unstable regime surrounding the second-order phase transition regime are determined by the proportion of nodes that do not depend on any other nodes. Moreover, we also find that the triple point and the boundary between first- and second-order transitions are determined by the proportion of nodes that depend on no more than one node. This implies that it is maybe general for multiplex network systems, some important properties of phase transitions can be determined only by a few parameters. We illustrate our findings using Erdős-Rényi networks.

  2. Serotonin modulation of cortical neurons and networks

    PubMed Central

    Celada, Pau; Puig, M. Victoria; Artigas, Francesc

    2013-01-01

    The serotonergic pathways originating in the dorsal and median raphe nuclei (DR and MnR, respectively) are critically involved in cortical function. Serotonin (5-HT), acting on postsynaptic and presynaptic receptors, is involved in cognition, mood, impulse control and motor functions by (1) modulating the activity of different neuronal types, and (2) varying the release of other neurotransmitters, such as glutamate, GABA, acetylcholine and dopamine. Also, 5-HT seems to play an important role in cortical development. Of all cortical regions, the frontal lobe is the area most enriched in serotonergic axons and 5-HT receptors. 5-HT and selective receptor agonists modulate the excitability of cortical neurons and their discharge rate through the activation of several receptor subtypes, of which the 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT3 subtypes play a major role. Little is known, however, on the role of other excitatory receptors moderately expressed in cortical areas, such as 5-HT2C, 5-HT4, 5-HT6, and 5-HT7. In vitro and in vivo studies suggest that 5-HT1A and 5-HT2A receptors are key players and exert opposite effects on the activity of pyramidal neurons in the medial prefrontal cortex (mPFC). The activation of 5-HT1A receptors in mPFC hyperpolarizes pyramidal neurons whereas that of 5-HT2A receptors results in neuronal depolarization, reduction of the afterhyperpolarization and increase of excitatory postsynaptic currents (EPSCs) and of discharge rate. 5-HT can also stimulate excitatory (5-HT2A and 5-HT3) and inhibitory (5-HT1A) receptors in GABA interneurons to modulate synaptic GABA inputs onto pyramidal neurons. Likewise, the pharmacological manipulation of various 5-HT receptors alters oscillatory activity in PFC, suggesting that 5-HT is also involved in the control of cortical network activity. A better understanding of the actions of 5-HT in PFC may help to develop treatments for mood and cognitive disorders associated with an abnormal function of the frontal lobe

  3. Exact Computation of Probability Landscape of Stochastic Networks of Single Input and Coupled Toggle Switch Modules

    PubMed Central

    Terebus, Anna; Cao, Youfang; Liang, Jie

    2016-01-01

    Gene regulatory networks depict the interactions between genes, proteins, and other components of the cell. These interactions often are stochastic that can influence behavior of the cells. Discrete Chemical Master Equation (dCME) provides a general framework for understanding the stochastic nature of these networks. However solving dCME is challenging due to the enormous state space, one effective approach is to study the behavior of individual modules of the stochastic network. Here we used the finite buffer dCME method and directly calculated the exact steady state probability landscape for the two stochastic networks of Single Input and Coupled Toggle Switch Modules. The first example is a switch network consisting of three genes, and the second example is a double switching network consisting of four coupled genes. Our results show complex switching behavior of these networks can be quantified. PMID:25571172

  4. A Novel Modulation Classification Approach Using Gabor Filter Network

    PubMed Central

    Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

    2014-01-01

    A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

  5. Direct Gaze Modulates Face Recognition in Young Infants

    ERIC Educational Resources Information Center

    Farroni, Teresa; Massaccesi, Stefano; Menon, Enrica; Johnson, Mark H.

    2007-01-01

    From birth, infants prefer to look at faces that engage them in direct eye contact. In adults, direct gaze is known to modulate the processing of faces, including the recognition of individuals. In the present study, we investigate whether direction of gaze has any effect on face recognition in four-month-old infants. Four-month infants were shown…

  6. Identify Dynamic Network Modules with Temporal and Spatial Constraints

    SciTech Connect

    Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J

    2007-09-24

    Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.

  7. Identification of Biochemical Network Modules Based on Shortest Retroactive Distances

    PubMed Central

    Sridharan, Gautham Vivek; Hassoun, Soha; Lee, Kyongbum

    2011-01-01

    Modularity analysis offers a route to better understand the organization of cellular biochemical networks as well as to derive practically useful, simplified models of these complex systems. While there is general agreement regarding the qualitative properties of a biochemical module, there is no clear consensus on the quantitative criteria that may be used to systematically derive these modules. In this work, we investigate cyclical interactions as the defining characteristic of a biochemical module. We utilize a round trip distance metric, termed Shortest Retroactive Distance (ShReD), to characterize the retroactive connectivity between any two reactions in a biochemical network and to group together network components that mutually influence each other. We evaluate the metric on two types of networks that feature feedback interactions: (i) epidermal growth factor receptor (EGFR) signaling and (ii) liver metabolism supporting drug transformation. For both networks, the ShReD partitions found hierarchically arranged modules that confirm biological intuition. In addition, the partitions also revealed modules that are less intuitive. In particular, ShReD-based partition of the metabolic network identified a ‘redox’ module that couples reactions of glucose, pyruvate, lipid and drug metabolism through shared production and consumption of NADPH. Our results suggest that retroactive interactions arising from feedback loops and metabolic cycles significantly contribute to the modularity of biochemical networks. For metabolic networks, cofactors play an important role as allosteric effectors that mediate the retroactive interactions. PMID:22102800

  8. Control range: a controllability-based index for node significance in directed networks

    NASA Astrophysics Data System (ADS)

    Wang, Bingbo; Gao, Lin; Gao, Yong

    2012-04-01

    While a large number of methods for module detection have been developed for undirected networks, it is difficult to adapt them to handle directed networks due to the lack of consensus criteria for measuring the node significance in a directed network. In this paper, we propose a novel structural index, the control range, motivated by recent studies on the structural controllability of large-scale directed networks. The control range of a node quantifies the size of the subnetwork that the node can effectively control. A related index, called the control range similarity, is also introduced to measure the structural similarity between two nodes. When applying the index of control range to several real-world and synthetic directed networks, it is observed that the control range of the nodes is mainly influenced by the network's degree distribution and that nodes with a low degree may have a high control range. We use the index of control range similarity to detect and analyze functional modules in glossary networks and the enzyme-centric network of homo sapiens. Our results, as compared with other approaches to module detection such as modularity optimization algorithm, dynamic algorithm and clique percolation method, indicate that the proposed indices are effective and practical in depicting structural and modular characteristics of sparse directed networks.

  9. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion

    PubMed Central

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D.; Nolte, Tobias; Walter, Martin

    2016-01-01

    our observation of direct prediction of neuronal responses by individual attachment and trauma characteristics and reversely prediction of subjective experience by intrinsic functional connections. We consider these findings of activation of within-network and between-network connectivity modulated by inter-individual differences as substantial for the understanding of interpersonal processes, particularly in clinical settings. PMID:27014016

  10. HyperModules: identifying clinically and phenotypically significant network modules with disease mutations for biomarker discovery

    PubMed Central

    Leung, Alvin; Bader, Gary D.; Reimand, Jüri

    2014-01-01

    Summary: Correlating disease mutations with clinical and phenotypic information such as drug response or patient survival is an important goal of personalized cancer genomics and a first step in biomarker discovery. HyperModules is a network search algorithm that finds frequently mutated gene modules with significant clinical or phenotypic signatures from biomolecular interaction networks. Availability and implementation: HyperModules is available in Cytoscape App Store and as a command line tool at www.baderlab.org/Sofware/HyperModules. Contact: Juri.Reimand@utoronto.ca or Gary.Bader@utoronto.ca Supplementary information: Supplementary data are available at Bioinformatics online PMID:24713437

  11. Direct digital RF synthesis and modulation for MSAT mobile applications

    NASA Technical Reports Server (NTRS)

    Crozier, Stewart; Datta, Ravi; Sydor, John

    1993-01-01

    A practical method of performing direct digital RF synthesis using the Hilbert transform single sideband (SSB) technique is described. It is also shown that amplitude and phase modulation can be achieved directly at L-band with frequency stability and spurii performance exceeding stringent MSAT system requirements.

  12. Functional module identification in protein interaction networks by interaction patterns

    PubMed Central

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

    Motivation: Identifying functional modules in protein–protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of ‘higher than expected connectivity’, those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks. Results: In this article, we propose a novel optimization formulation LCP2 (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP2 by random walk. A spectral approximate algorithm SLCP2 is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP2 to a new algorithm (greedy algorithm for LCP2) GLCP2 to identify overlapping functional modules. We compare SLCP2 and GLCP2 with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP2 outperform all other compared algorithms. Availability and implementation: All data and code are available at http://www.cse.usf.edu/∼xqian/fmi/slcp2hop

  13. NetWare Loadable Modules for CD-ROM Networking.

    ERIC Educational Resources Information Center

    Starr, Karen J.

    1993-01-01

    Provides an overview of CD-ROM technology and local area networking focusing on NetWare Loadable Modules (NLMs) which provide network access to CD-ROMs, using Novell's NetWare operating system. The characteristics and benefits of various products and concerns in choosing one are discussed, and comparative specifications and vendors are listed.…

  14. Harmonic, Intermodulation and Cross-Modulation Distortion in Directly Modulated Quantum Cascade Lasers

    NASA Astrophysics Data System (ADS)

    Webb, J. F.; Yong, K. S. C.; Haldar, M. K.

    2016-05-01

    Using a simplified rate equation model, expressions for harmonic, intermodulation and cross-modulation distortion for a directly modulated quantum cascade laser can be derived. This paper shows how such derivations can be done and discusses some implications for quantum cascade lasers. It is important to understand such distortion, especially for applcations in communication systems.

  15. Direct ink writing of microvascular networks

    NASA Astrophysics Data System (ADS)

    Wu, Willie

    Nature is replete with examples of embedded microvascular systems that enable efficient fluid flow and distribution for autonomic healing, cooling, and energy harvesting. The ability to incorporate microvascular networks in functional materials systems is therefore both scientifically and technologically important. In this PhD thesis, the direct-write assembly of planar and 3D biomimetic microvascular networks within polymer and hydrogel matrices is demonstrated. In addition, the influence of network design of fluid transport efficiency is characterized. Planar microvascular networks composed of periodic lattices of uniformal microchannels and hierarchical, branching architectures are constructed by direct-write assembly of a fugitive organic ink. Several advancements are required to facilitate their patterning, including pressure valving, dual ink printing, and dynamic pressure variation to allow tunable control of ink deposition. The hydraulic conductance is measured using a high pressure flow meter as a function of network design. For a constant vascular volume and areal coverage, 2- and 4-generation branched architectures that obey Murray's Law exhibited the highest hydraulic conductivity. These experimental observations are in good agreement with predictions made by analytic models. 3D microvascular networks are fabricated by omnidirectional printing a fugitive organic ink into a photopolymerizable hydrogel matrix that is capped with fluid filler of nearly identical composition. Using this approach, 3D networks of arbitrary design can be patterned. After ink deposition is complete, the matrix and fluid filler are chemically cross-linked via UV irradiation, and the ink is removed by liquefication. Aqueous solutions composed of a triblock copolymer of polyethylene oxide (PEO)-polypropylene oxide (PPO)-PEO constitute the materials system of choice due to their thermal- and concentration-dependent phase behavior. Specifically, the fugitive ink consists of a 23 w

  16. Satellite-borne QPSK Direct Modulator for Ka Band

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Li, Changsheng

    2016-02-01

    Ka band is referred to a microwave band whose frequency range is from 24.6 GHz to 40 GHz, it shares a wide available bandwidth, high frequency reuse rate and strong ability of anti-jamming. This paper presents a novel method to design a modulator for Ka-band satellite communication. Using QPSK to improve the ability of anti-jamming, using direct modulation to reduce the weight, volume and cost of electronic equipment, using sub-harmonic mixer to cut the LO power leakage, excellent modulation results are obtained.

  17. eXamine: Exploring annotated modules in networks

    PubMed Central

    2014-01-01

    Background Biological networks have a growing importance for the interpretation of high-throughput “omics” data. Integrative network analysis makes use of statistical and combinatorial methods to extract smaller subnetwork modules, and performs enrichment analysis to annotate the modules with ontology terms or other available knowledge. This process results in an annotated module, which retains the original network structure and includes enrichment information as a set system. A major bottleneck is a lack of tools that allow exploring both network structure of extracted modules and its annotations. Results This paper presents a visual analysis approach that targets small modules with many set-based annotations, and which displays the annotations as contours on top of a node-link diagram. We introduce an extension of self-organizing maps to lay out nodes, links, and contours in a unified way. An implementation of this approach is freely available as the Cytoscape app eXamine Conclusions eXamine accurately conveys small and annotated modules consisting of several dozens of proteins and annotations. We demonstrate that eXamine facilitates the interpretation of integrative network analysis results in a guided case study. This study has resulted in a novel biological insight regarding the virally-encoded G-protein coupled receptor US28. PMID:25002203

  18. Module organization and variance in protein-protein interaction networks

    PubMed Central

    Lin, Chun-Yu; Lee, Tsai-Ling; Chiu, Yi-Yuan; Lin, Yi-Wei; Lo, Yu-Shu; Lin, Chih-Ta; Yang, Jinn-Moon

    2015-01-01

    A module is a group of closely related proteins that act in concert to perform specific biological functions through protein–protein interactions (PPIs) that occur in time and space. However, the underlying module organization and variance remain unclear. In this study, we collected module templates to infer respective module families, including 58,041 homologous modules in 1,678 species, and PPI families using searches of complete genomic database. We then derived PPI evolution scores and interface evolution scores to describe the module elements, including core and ring components. Functions of core components were highly correlated with those of essential genes. In comparison with ring components, core proteins/PPIs were conserved across multiple species. Subsequently, protein/module variance of PPI networks confirmed that core components form dynamic network hubs and play key roles in various biological functions. Based on the analyses of gene essentiality, module variance, and gene co-expression, we summarize the observations of module organization and variance as follows: 1) a module consists of core and ring components; 2) core components perform major biological functions and collaborate with ring components to execute certain functions in some cases; 3) core components are more conserved and essential during organizational changes in different biological states or conditions. PMID:25797237

  19. Inverter power module with distributed support for direct substrate cooling

    DOEpatents

    Miller, David Harold; Korich, Mark D.; Ward, Terence G.; Mann, Brooks S.

    2012-08-21

    Systems and/or methods are provided for an inverter power module with distributed support for direct substrate cooling. An inverter module comprises a power electronic substrate. A first support frame is adapted to house the power electronic substrate and has a first region adapted to allow direct cooling of the power electronic substrate. A gasket is interposed between the power electronic substrate and the first support frame. The gasket is configured to provide a seal between the first region and the power electronic substrate. A second support frame is adapted to house the power electronic substrate and joined to the first support frame to form the seal.

  20. Group scheduling problems in directional sensor networks

    NASA Astrophysics Data System (ADS)

    Singh, Alok; Rossi, André

    2015-12-01

    This article addresses the problem of scheduling a set of groups of directional sensors arising as a result of applying an exact or a heuristic approach for solving a problem involving directional sensors. The problem seeks a schedule for these groups that minimizes the total energy consumed in switching from one group to the next group in the schedule. In practice, when switching from a group to the next one, active sensors in the new group have to rotate in order to face their working direction. These rotations consume energy, and the problem is to schedule the groups so as to minimize the total amount of energy consumed by all the sensor rotations, knowing the initial angular positions of all the sensors. In this article, it is assumed that energy consumption is proportional to the angular movement for all the sensors. Another problem version is also investigated that seeks to minimize the total time during which the sensor network cannot cover all the targets because active sensors are rotating. Both problems are proved to be ?-hard, and a lower bound for the first problem is presented. A greedy heuristic and a genetic algorithm are also proposed for addressing the problem of minimizing total rotation in the general case. Finally, a local search is also proposed to improve the solutions obtained through a genetic algorithm.

  1. Interaction of Motility, Directional Sensing, and Polarity Modules Recreates the Behaviors of Chemotaxing Cells

    PubMed Central

    Shi, Changji; Huang, Chuan-Hsiang; Devreotes, Peter N.; Iglesias, Pablo A.

    2013-01-01

    Chemotaxis involves the coordinated action of separable but interrelated processes: motility, gradient sensing, and polarization. We have hypothesized that these are mediated by separate modules that account for these processes individually and that, when combined, recreate most of the behaviors of chemotactic cells. Here, we describe a mathematical model where the modules are implemented in terms of reaction-diffusion equations. Migration and the accompanying changes in cellular morphology are demonstrated in simulations using a mechanical model of the cell cortex implemented in the level set framework. The central module is an excitable network that accounts for random migration. The response to combinations of uniform stimuli and gradients is mediated by a local excitation, global inhibition module that biases the direction in which excitability is directed. A polarization module linked to the excitable network through the cytoskeleton allows unstimulated cells to move persistently and, for cells in gradients, to gradually acquire distinct sensitivity between front and back. Finally, by varying the strengths of various feedback loops in the model we obtain cellular behaviors that mirror those of genetically altered cell lines. PMID:23861660

  2. Spread of infectious diseases in directed and modular metapopulation networks.

    PubMed

    Lentz, Hartmut H K; Selhorst, Thomas; Sokolov, Igor M

    2012-06-01

    We consider epidemics in metapopulations on different network topologies. Recent work on epidemics on networks has focused on epidemics of humans. In this work we present a model for epidemics on directed networks, which are found, for example, in the livestock trade. We show that the direction of edges and the modular structure of networks have an impact on the outbreak size and the time of the outbreak peak. In some circumstances, the outbreak size in directed networks can even be larger than in undirected systems. The results presented here could be useful for decision-making processes in directed modular systems. PMID:23005166

  3. Protein complexes and functional modules in molecular networks

    NASA Astrophysics Data System (ADS)

    Spirin, Victor; Mirny, Leonid A.

    2003-10-01

    Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

  4. Investigation of direct integrated optics modulators. [applicable to data preprocessors

    NASA Technical Reports Server (NTRS)

    Batchman, T. E.

    1980-01-01

    Direct modulation techniques applicable to integrated optics data preprocessors were investigated. Several methods of modulating a coherent optical beam by interaction with an incoherent beam were studied. It was decided to investigate photon induced conductivity changes in thin semiconductor cladding layers on optical waveguides. Preliminary calculations indicate significant changes can be produced in the phase shift in a propagating wave when the conductivity is changed by ten percent or more. Experimental devices to verify these predicted phase changes and experiments designed to prove the concept are described.

  5. Pinning impulsive directed coupled delayed dynamical network and its applications

    NASA Astrophysics Data System (ADS)

    Lin, Chunnan; Wu, Quanjun; Xiang, Lan; Zhou, Jin

    2015-01-01

    The main objective of the present paper is to further investigate pinning synchronisation of a complex delayed dynamical network with directionally coupling by a single impulsive controller. By developing the analysis procedure of pinning impulsive stability for undirected coupled dynamical network previously, some simple yet general criteria of pinning impulsive synchronisation for such directed coupled network are derived analytically. It is shown that a single impulsive controller can always pin a given directed coupled network to a desired homogenous solution, including an equilibrium point, a periodic orbit, or a chaotic orbit. Subsequently, the theoretical results are illustrated by a directed small-world complex network which is a cellular neural network (CNN) and a directed scale-free complex network with the well-known Hodgkin-Huxley neuron oscillators. Numerical simulations are finally given to demonstrate the effectiveness of the proposed control methodology.

  6. Nicotinic modulation of intrinsic brain networks in schizophrenia

    PubMed Central

    Smucny, Jason; Tregellas, Jason

    2014-01-01

    The nicotinic receptor is a promising drug target currently being investigated for the treatment of cognitive symptoms in schizophrenia. A key step in this process is the development of noninvasive functional neuroimaging biomarkers that can be used to determine if nicotinic agents are eliciting their targeted biological effect, ideally through modulation of a fundamental aspect of neuronal function. To that end, neuroimaging researchers are beginning to understand how nicotinic modulation affects “intrinsic” brain networks to elicit potentially therapeutic effects. An intrinsic network is a functionally and (often) structurally connected network of brain areas whose activity reflects a fundamental neurobiological organizational principle of the brain. This review summarizes findings of the effects of nicotinic drugs on three topics related to intrinsic brain network activity: (1) the default mode network, a group of brain areas for which activity is maximal at rest and reduced during cognitive tasks, (2) the salience network, which integrates incoming sensory data with prior internal representations to guide future actions and change predictive values, and (3) multi-scale complex network dynamics, which describe these brain’s ability to efficiency integrate information while preserving local functional specialization. These early findings can be used to inform future neuroimaging studies that examine the network effects of nicotinic agents. PMID:23796751

  7. Remote Synchronization Reveals Network Symmetries and Functional Modules

    NASA Astrophysics Data System (ADS)

    Nicosia, Vincenzo; Valencia, Miguel; Chavez, Mario; Díaz-Guilera, Albert; Latora, Vito

    2013-04-01

    We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.

  8. Seed selection strategy in global network alignment without destroying the entire structures of functional modules

    PubMed Central

    2012-01-01

    Background Network alignment is one of the most common biological network comparison methods. Aligning protein-protein interaction (PPI) networks of different species is of great important to detect evolutionary conserved pathways or protein complexes across species through the identification of conserved interactions, and to improve our insight into biological systems. Global network alignment (GNA) problem is NP-complete, for which only heuristic methods have been proposed so far. Generally, the current GNA methods fall into global heuristic seed-and-extend approaches. These methods can not get the best overall consistent alignment between networks for the opinionated local seed. Furthermore These methods are lost in maximizing the number of aligned edges between two networks without considering the original structures of functional modules. Methods We present a novel seed selection strategy for global network alignment by constructing the pairs of hub nodes of networks to be aligned into multiple seeds. Beginning from every hub seed and using the membership similarity of nodes to quantify to what extent the nodes can participate in functional modules associated with current seed topologically we align the networks by modules. By this way we can maintain the functional modules are not damaged during the heuristic alignment process. And our method is efficient in resolving the fatal problem of most conventional algorithms that the initialization selected seeds have a direct influence on the alignment result. The similarity measures between network nodes (e.g., proteins) include sequence similarity, centrality similarity, and dynamic membership similarity and our algorithm can be called Multiple Hubs-based Alignment (MHA). Results When applying our seed selection strategy to several pairs of real PPI networks, it is observed that our method is working to strike a balance, extending the conserved interactions while maintaining the functional modules unchanged. In

  9. Receiver bandwidth effects on complex modulation and detection using directly modulated lasers.

    PubMed

    Yuan, Feng; Che, Di; Shieh, William

    2016-05-01

    Directly modulated lasers (DMLs) have long been employed for short- and medium-reach optical communications due to their low cost. Recently, a new modulation scheme called complex modulated DMLs has been demonstrated showing a significant optical signal to noise ratio sensitivity enhancement compared with the traditional intensity-only detection scheme. However, chirp-induced optical spectrum broadening is inevitable in complex modulated systems, which may imply a need for high-bandwidth receivers. In this Letter, we study the impact of receiver bandwidth effects on the performance of complex modulation and coherent detection systems based on DMLs. We experimentally demonstrate that such systems exhibit a reasonable tolerance for the reduced receiver bandwidth. For 10 Gbaud 4-level pulse amplitude modulation signals, the required electrical bandwidth is as low as 8.5 and 7.5 GHz for 7% and 20% forward error correction, respectively. Therefore, it is feasible to realize DML-based complex modulated systems using cost-effective receivers with narrow bandwidth. PMID:27128069

  10. Transcriptional modules related to hepatocellular carcinoma survival: coexpression network analysis.

    PubMed

    Xu, Xinsen; Zhou, Yanyan; Miao, Runchen; Chen, Wei; Qu, Kai; Pang, Qing; Liu, Chang

    2016-06-01

    We performed weighted gene coexpression network analysis (WGCNA) to gain insights into the molecular aspects of hepatocellular carcinoma (HCC). Raw microarray datasets (including 488 samples) were downloaded from the Gene Expression Omnibus (GEO) website. Data were normalized using the RMA algorithm. We utilized the WGCNA to identify the coexpressed genes (modules) after non-specific filtering. Correlation and survival analyses were conducted using the modules, and gene ontology (GO) enrichment was applied to explore the possible mechanisms. Eight distinct modules were identified by the WGCNA. Pink and red modules were associated with liver function, whereas turquoise and black modules were inversely correlated with tumor staging. Poor outcomes were found in the low expression group in the turquoise module and in the high expression group in the red module. In addition, GO enrichment analysis suggested that inflammation, immune, virus-related, and interferon-mediated pathways were enriched in the turquoise module. Several potential biomarkers, such as cyclin-dependent kinase 1 (CDK1), topoisomerase 2α (TOP2A), and serpin peptidase inhibitor clade C (antithrombin) member 1 (SERPINC1), were also identified. In conclusion, gene signatures identified from the genome-based assays could contribute to HCC stratification. WGCNA was able to identify significant groups of genes associated with cancer prognosis. PMID:27052251

  11. Detecting network modules in fMRI time series: a weighted network analysis approach.

    PubMed

    Mumford, Jeanette A; Horvath, Steve; Oldham, Michael C; Langfelder, Peter; Geschwind, Daniel H; Poldrack, Russell A

    2010-10-01

    Many network analyses of fMRI data begin by defining a set of regions, extracting the mean signal from each region and then analyzing the correlations between regions. One essential question that has not been addressed in the literature is how to best define the network neighborhoods over which a signal is combined for network analyses. Here we present a novel unsupervised method for the identification of tightly interconnected voxels, or modules, from fMRI data. This approach, weighted voxel coactivation network analysis (WVCNA), is based on a method that was originally developed to find modules of genes in gene networks. This approach differs from many of the standard network approaches in fMRI in that connections between voxels are described by a continuous measure, whereas typically voxels are considered to be either connected or not connected depending on whether the correlation between the two voxels survives a hard threshold value. Additionally, instead of simply using pairwise correlations to describe the connection between two voxels, WVCNA relies on a measure of topological overlap, which not only compares how correlated two voxels are but also the degree to which the pair of voxels is highly correlated with the same other voxels. We demonstrate the use of WVCNA to parcellate the brain into a set of modules that are reliably detected across data within the same subject and across subjects. In addition we compare WVCNA to ICA and show that the WVCNA modules have some of the same structure as the ICA components, but tend to be more spatially focused. We also demonstrate the use of some of the WVCNA network metrics for assessing a voxel's membership to a module and also how that voxel relates to other modules. Last, we illustrate how WVCNA modules can be used in a network analysis to find connections between regions of the brain and show that it produces reasonable results. PMID:20553896

  12. Detecting network modules in fMRI time series: A weighted network analysis approach

    PubMed Central

    Mumford, Jeanette A; Horvath, Steve; Oldham, Michael C.; Langfelder, Peter; Geschwind, Daniel H.; Poldrack, Russell A

    2010-01-01

    Many network analyses of fMRI data begin by defining a set of regions, extracting the mean signal from each region and then analyzing the correlations between regions. One essential question that has not been addressed in the literature is how to best define the network neighborhoods over which a signal is combined for network analyses. Here we present a novel unsupervised method for the identification of tightly interconnected voxels, or modules, from fMRI data. This approach, weighted voxel coactivation network analysis (WVCNA) is based on a method that was originally developed to find modules of genes in gene networks. This approach differs from many of the standard network approaches in fMRI in that connections between voxels are described by a continuous measure, whereas typically voxels are considered to be either connected or not connected depending on whether the correlation between the two voxels survives a hard threshold value. Additionally, instead of simply using pairwise correlations to describe the connection between two voxels, WVCNA relies on a measure of topological overlap, which not only compares how correlated two voxels are, but also the degree to which the pair of voxels is highly correlated with the same other voxels. We demonstrate the use of WVCNA to parcellate the brain into a set of modules that are reliably detected across data within the same subject and across subjects. In addition we compare WVCNA to ICA and show that the WVCNA modules have some of the same structure as the ICA components, but tend to be more spatially focused. We also demonstrate the use of some of the WVCNA network metrics for assessing a voxel’s membership to a module and also how that voxel relates to other modules. Last, we illustrate how WVCNA modules can be used in a network analysis to find connections between regions of the brain and show that it produces reasonable results. PMID:20553896

  13. Controllability and observability analysis for vertex domination centrality in directed networks

    NASA Astrophysics Data System (ADS)

    Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

    2014-06-01

    Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks.

  14. Controllability and observability analysis for vertex domination centrality in directed networks.

    PubMed

    Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

    2014-01-01

    Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks. PMID:24954137

  15. Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression.

    PubMed

    Tadayonnejad, Reza; Ajilore, Olusola; Mickey, Brian J; Crane, Natania A; Hsu, David T; Kumar, Anand; Zubieta, Jon-Kar; Langenecker, Scott A

    2016-06-30

    The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment. PMID:27148894

  16. Directed network motifs in Alzheimer's disease and mild cognitive impairment.

    PubMed

    Friedman, Eric J; Young, Karl; Tremper, Graham; Liang, Jason; Landsberg, Adam S; Schuff, Norbert

    2015-01-01

    Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains. We show that frequencies of specific directed network motifs can be used to distinguish between patients with Alzheimer's disease (AD) and normal control (NC) subjects. Especially interesting from a clinical standpoint, these motif frequencies can also distinguish between subjects with mild cognitive impairment who remained stable over three years (MCI) and those who converted to AD (CONV). Furthermore, we find that the entropy of the distribution of directed network motifs increased from MCI to CONV to AD, implying that the distribution of pathology is more structured in MCI but becomes less so as it progresses to CONV and further to AD. Thus, directed network motifs frequencies and distributional properties provide new insights into the progression of Alzheimer's disease as well as new imaging markers for distinguishing between normal controls, stable mild cognitive impairment, MCI converters and Alzheimer's disease. PMID:25879535

  17. Fast Fragmentation of Networks Using Module-Based Attacks

    PubMed Central

    Requião da Cunha, Bruno; González-Avella, Juan Carlos; Gonçalves, Sebastián

    2015-01-01

    In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. PMID:26569610

  18. Fast Fragmentation of Networks Using Module-Based Attacks.

    PubMed

    Requião da Cunha, Bruno; González-Avella, Juan Carlos; Gonçalves, Sebastián

    2015-01-01

    In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. PMID:26569610

  19. Transient mode competition in directly modulated DFB semiconductor laser

    NASA Astrophysics Data System (ADS)

    Xiao, RuLei; Shi, YueChun; Zheng, JiLin; Zhang, YunShan; Zheng, JunShou; Chen, XiangFei

    2015-12-01

    A new effect of transient mode competition in directly modulated DFB laser based on equivalent phase-shift (EPS) technique is presented and studied. Since there are multi-order reflections in EPS structure and if the 0th order subgrating is properly designed, the transient lasing of 0th order will occur during the rising time of the injection current. As a result, transient mode competition between -1st order (main mode) and 0th order will occur accordingly. This can consume redundant carrier and suppress the transient relaxation oscillation, which may be applied in some areas like on-off switching modulation of DFB semiconductor lasers. As an example, an equivalent π phase shift (π-EPS) is carefully designed to realize the effect. In such a laser the 0th order wavelength is in the margin of the material gain region and the -1st order wavelength is around the gain peak, while the stable single longitudinal mode (SLM) operation of the -1st order is guaranteed. The simulation investigation is performed. Good results with suppressed relaxation oscillation and 1.25 Gb/s directly on-off modulation (32 dB extinction ratio) are demonstrated. We believe it provides a new kind of method for on-off switching with high extinction ratio and weak relaxation oscillation.

  20. Quantitative assessment of gene expression network module-validation methods.

    PubMed

    Li, Bing; Zhang, Yingying; Yu, Yanan; Wang, Pengqian; Wang, Yongcheng; Wang, Zhong; Wang, Yongyan

    2015-01-01

    Validation of pluripotent modules in diverse networks holds enormous potential for systems biology and network pharmacology. An arising challenge is how to assess the accuracy of discovering all potential modules from multi-omic networks and validating their architectural characteristics based on innovative computational methods beyond function enrichment and biological validation. To display the framework progress in this domain, we systematically divided the existing Computational Validation Approaches based on Modular Architecture (CVAMA) into topology-based approaches (TBA) and statistics-based approaches (SBA). We compared the available module validation methods based on 11 gene expression datasets, and partially consistent results in the form of homogeneous models were obtained with each individual approach, whereas discrepant contradictory results were found between TBA and SBA. The TBA of the Zsummary value had a higher Validation Success Ratio (VSR) (51%) and a higher Fluctuation Ratio (FR) (80.92%), whereas the SBA of the approximately unbiased (AU) p-value had a lower VSR (12.3%) and a lower FR (45.84%). The Gray area simulated study revealed a consistent result for these two models and indicated a lower Variation Ratio (VR) (8.10%) of TBA at 6 simulated levels. Despite facing many novel challenges and evidence limitations, CVAMA may offer novel insights into modular networks. PMID:26470848

  1. Sigma-delta cellular neural network for 2D modulation.

    PubMed

    Aomori, Hisashi; Otake, Tsuyoshi; Takahashi, Nobuaki; Tanaka, Mamoru

    2008-01-01

    Although sigma-delta modulation is widely used for analog-to-digital (A/D) converters, sigma-delta concepts are only for 1D signals. Signal processing in the digital domain is extremely useful for 2D signals such as used in image processing, medical imaging, ultrasound imaging, and so on. The intricate task that provides true 2D sigma-delta modulation is feasible in the spatial domain sigma-delta modulation using the discrete-time cellular neural network (DT-CNN) with a C-template. In the proposed architecture, the A-template is used for a digital-to-analog converter (DAC), the C-template works as an integrator, and the nonlinear output function is used for the bilevel output. In addition, due to the cellular neural network (CNN) characteristics, each pixel of an image corresponds to a cell of a CNN, and each cell is connected spatially by the A-template. Therefore, the proposed system can be thought of as a very large-scale and super-parallel sigma-delta modulator. Moreover, the spatio-temporal dynamics is designed to obtain an optimal reconstruction signal. The experimental results show the excellent reconstruction performance and capabilities of the CNN as a sigma-delta modulator. PMID:18215502

  2. Modules of human micro-RNA co-target network

    NASA Astrophysics Data System (ADS)

    Basu, Mahashweta; Bhattacharyya, Nitai P.; Mohanty, P. K.

    2011-05-01

    Human micro RNAs (miRNAs) target about 90% of the coding genes and form a complex regulatory network. We study the community structure of the miRNA co-target network considering miRNAs as the nodes which are connected by weighted links. The weight of link that connects a pair of miRNAs denote the total number of common transcripts targeted by that pair. We argue that the network consists of about 74 modules, quite similar to the components (or clusters) obtained earlier [Online J Bioinformatics, 10,280], indicating that the components of the miRNA co-target network are self organized in a way to maximize the modularity.

  3. Link module for a downhole drilling network

    DOEpatents

    Hall, David R.; Fox, Joe

    2007-05-29

    A repeater is disclosed in one embodiment of the present invention as including a cylindrical housing, characterized by a proximal end and a distal end, and having a substantially cylindrical wall, the cylindrical wall defining a central bore passing therethrough. The cylindrical housing is formed to define at least one recess in the cylindrical wall, into which a repeater is inserted. The cylindrical housing also includes an annular recess formed into at least one of the proximal end and the distal end. An annular transmission element, operably connected to the repeater, is located in the annular recess. In selected embodiments, the annular transmission element inductively converts electrical energy to magnetic energy. In other embodiments, the annular transmission element includes an electrical contact to transmit electrical energy directly to another contact.

  4. The Direct Digital Modulation of Traveling Wave Tubes

    NASA Technical Reports Server (NTRS)

    Radhamohan, Ranjan S.

    2004-01-01

    Traveling wave tube (TWT) technology, first described by Rudolf Kompfner in the early 1940s, has been a key component of space missions from the earliest communication satellites in the 1960s to the Cassini probe today. TWTs are essentially signal amplifiers that have the special capability of operating at microwave frequencies. The microwave frequency range, which spans from approximately 500 MHz to 300 GHz, is shared by many technologies including cellular phones, satellite television, space communication, and radar. TWT devices are superior in reliability, weight, and efficiency to solid-state amplifiers at the high power and frequency levels required for most space missions. TWTs have three main components -an electron gun, slow wave structure, and collector. The electron gun generates an electron beam that moves along the length of the tube axis, inside of the slow wave circuit. At the same time, the inputted signal is slowed by its travel through the coils of the helical slow wave circuit. The interaction of the electron beam and this slowed signal produces a transfer of kinetic energy to the signal, and in turn, amplification. At the end of its travel, the spent electron beam moves into the collector where its remaining energy is dissipated as heat or harnessed for reuse. TWTs can easily produce gains in the tens of decibels, numbers that are suitable for space missions. To date, however, TWTs have typically operated at fixed levels of gain. This gain is determined by various, unchanging, physical factors of the tube. Traditionally, to achieve varying gain, an input signal s amplitude has had to first be modulated by a separate device before being fed into the TWT. This is not always desirable, as significant distortion can occur in certain situations. My mentor, Mr. Dale Force, has proposed an innovative solution to this problem called direct digital modulation . The testing and implementation of this solution is the focus of my summer internship. The

  5. A directed network of Greek and Roman mythology

    NASA Astrophysics Data System (ADS)

    Choi, Yeon-Mu; Kim, Hyun-Joo

    2007-08-01

    We construct a directed network using a dictionary of Greek and Roman mythology in which the nodes represent the entries listed in the dictionary and we make directional links from an entry to other entries that appear in its explanatory part. We find that this network is clearly not a random network but a directed scale-free network in which the distributions of out-degree and in-degree follow a power-law with exponents γout≈3.0 and γin≈2.5, respectively. Also we measure several quantities which describe the topological properties of the network and compare it to that of other real networks.

  6. Task induced modulation of neural oscillations in electrophysiological brain networks.

    PubMed

    Brookes, M J; Liddle, E B; Hale, J R; Woolrich, M W; Luckhoo, H; Liddle, P F; Morris, P G

    2012-12-01

    In recent years, one of the most important findings in systems neuroscience has been the identification of large scale distributed brain networks. These networks support healthy brain function and are perturbed in a number of neurological disorders (e.g. schizophrenia). Their study is therefore an important and evolving focus for neuroscience research. The majority of network studies are conducted using functional magnetic resonance imaging (fMRI) which relies on changes in blood oxygenation induced by neural activity. However recently, a small number of studies have begun to elucidate the electrical origin of fMRI networks by searching for correlations between neural oscillatory signals from spatially separate brain areas in magnetoencephalography (MEG) data. Here we advance this research area. We introduce two methodological extensions to previous independent component analysis (ICA) approaches to MEG network characterisation: 1) we show how to derive pan-spectral networks that combine independent components computed within individual frequency bands. 2) We show how to measure the temporal evolution of each network with millisecond temporal resolution. We apply our approach to ~10h of MEG data recorded in 28 experimental sessions during 3 separate cognitive tasks showing that a number of networks could be identified and were robust across time, task, subject and recording session. Further, we show that neural oscillations in those networks are modulated by memory load, and task relevance. This study furthers recent findings on electrodynamic brain networks and paves the way for future clinical studies in patients in which abnormal connectivity is thought to underlie core symptoms. PMID:22906787

  7. Connection cube modules for optical backplanes and fiber networks.

    PubMed

    Kostuk, R K; Ramsey, D L; Kim, T J

    1997-07-10

    A modular free-space optical system, called the connection cube, for connecting arrays of electro-optic transceivers and fiber-array connectors is presented. The connection cube module provides bidirectional data transfer between four processing nodes on a cube face and can be used as a basic building block for optical backplanes and interconnect networks. An experimental system for connecting four processing nodes is presented and used to examine alignment and packaging issues. An analysis of the dimensional requirements and scaling capability for systems based on this module is conducted. This analysis shows that, when the connection cube module is adapted to vertical-cavity surface-emitting-laser-based point-to-point fiber-array links currently under development, it can connect up to 14 processing nodes with an aggregate data transfer capacity of 112 Gbits/s with 19.6-W power consumption. PMID:18259270

  8. Studies on controllability of directed networks with extremal optimization

    NASA Astrophysics Data System (ADS)

    Ding, Jin; Lu, Yong-Zai; Chu, Jian

    2013-12-01

    Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and attractive subjects for both network and control communities. In this paper, based on a given directed-weighted network with both state and control nodes, a novel optimization tool with extremal dynamics to generate an optimal network topology with minimum control nodes and complete controllability under Kalman’s rank condition has been developed. The experimental results on a number of popular benchmark networks show the proposed tool is effective to identify the minimum control nodes which are sufficient to guide the whole network’s dynamics and provide the evolution of network topology during the optimization process. We also find the conclusion: “the sparse networks need more control nodes than the dense, and the homogeneous networks need fewer control nodes compared to the heterogeneous” (Liu et al., 2011 [18]), is also applicable to network complete controllability. These findings help us to understand the network dynamics and make a real-world network under the desired control. Moreover, compared with the relevant research results on structural controllability with minimum driver nodes, the proposed solution methodology may also be applied to other constrained network optimization problems beyond complete controllability with minimum control nodes.

  9. Stimulation of Glia Reveals Modulation of Mammalian Spinal Motor Networks by Adenosine.

    PubMed

    Acton, David; Miles, Gareth B

    2015-01-01

    Despite considerable evidence that glia can release modulators to influence the excitability of neighbouring neurons, the importance of gliotransmission for the operation of neural networks and in shaping behaviour remains controversial. Here we characterise the contribution of glia to the modulation of the mammalian spinal central pattern generator for locomotion, the output of which is directly relatable to a defined behaviour. Glia were stimulated by specific activation of protease-activated receptor-1 (PAR1), an endogenous G-protein coupled receptor preferentially expressed by spinal glia during ongoing activity of the spinal central pattern generator for locomotion. Selective activation of PAR1 by the agonist TFLLR resulted in a reversible reduction in the frequency of locomotor-related bursting recorded from ventral roots of spinal cord preparations isolated from neonatal mice. In the presence of the gliotoxins methionine sulfoximine or fluoroacetate, TFLLR had no effect, confirming the specificity of PAR1 activation to glia. The modulation of burst frequency upon PAR1 activation was blocked by the non-selective adenosine-receptor antagonist theophylline and by the A1-receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine, but not by the A2A-receptor antagonist SCH5826, indicating production of extracellular adenosine upon glial stimulation, followed by A1-receptor mediated inhibition of neuronal activity. Modulation of network output following glial stimulation was also blocked by the ectonucleotidase inhibitor ARL67156, indicating glial release of ATP and its subsequent degradation to adenosine rather than direct release of adenosine. Glial stimulation had no effect on rhythmic activity recorded following blockade of inhibitory transmission, suggesting that glial cell-derived adenosine acts via inhibitory circuit components to modulate locomotor-related output. Finally, the modulation of network output by endogenous adenosine was found to scale with the

  10. Stimulation of Glia Reveals Modulation of Mammalian Spinal Motor Networks by Adenosine

    PubMed Central

    Acton, David; Miles, Gareth B.

    2015-01-01

    Despite considerable evidence that glia can release modulators to influence the excitability of neighbouring neurons, the importance of gliotransmission for the operation of neural networks and in shaping behaviour remains controversial. Here we characterise the contribution of glia to the modulation of the mammalian spinal central pattern generator for locomotion, the output of which is directly relatable to a defined behaviour. Glia were stimulated by specific activation of protease-activated receptor-1 (PAR1), an endogenous G-protein coupled receptor preferentially expressed by spinal glia during ongoing activity of the spinal central pattern generator for locomotion. Selective activation of PAR1 by the agonist TFLLR resulted in a reversible reduction in the frequency of locomotor-related bursting recorded from ventral roots of spinal cord preparations isolated from neonatal mice. In the presence of the gliotoxins methionine sulfoximine or fluoroacetate, TFLLR had no effect, confirming the specificity of PAR1 activation to glia. The modulation of burst frequency upon PAR1 activation was blocked by the non-selective adenosine-receptor antagonist theophylline and by the A1-receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine, but not by the A2A-receptor antagonist SCH5826, indicating production of extracellular adenosine upon glial stimulation, followed by A1-receptor mediated inhibition of neuronal activity. Modulation of network output following glial stimulation was also blocked by the ectonucleotidase inhibitor ARL67156, indicating glial release of ATP and its subsequent degradation to adenosine rather than direct release of adenosine. Glial stimulation had no effect on rhythmic activity recorded following blockade of inhibitory transmission, suggesting that glial cell-derived adenosine acts via inhibitory circuit components to modulate locomotor-related output. Finally, the modulation of network output by endogenous adenosine was found to scale with the

  11. Smart Capture Modules for Direct Sensor-to-FPGA Interfaces

    PubMed Central

    Oballe-Peinado, Óscar; Vidal-Verdú, Fernando; Sánchez-Durán, José A.; Castellanos-Ramos, Julián; Hidalgo-López, José A.

    2015-01-01

    Direct sensor–digital device interfaces measure time dependent variables of simple circuits to implement analog-to-digital conversion. Field Programmable Gate Arrays (FPGAs) are devices whose hardware can be reconfigured to work in parallel. They usually do not have analog-to-digital converters, but have many general purpose I/O pins. Therefore, direct sensor-FPGA connection is a good choice in complex systems with many sensors because several capture modules can be implemented to perform parallel analog data acquisition. The possibility to work in parallel and with high frequency clock signals improves the bandwidth compared to sequential devices such as conventional microcontrollers. The price to pay is usually the resolution of measurements. This paper proposes capture modules implemented in an FPGA which are able to perform smart acquisition that filter noise and achieve high precision. A calibration technique is also proposed to improve accuracy. Resolutions of 12 effective number of bits are obtained for the reading of resistors in the range of an example piezoresistive tactile sensor. PMID:26694403

  12. Smart Capture Modules for Direct Sensor-to-FPGA Interfaces.

    PubMed

    Oballe-Peinado, Óscar; Vidal-Verdú, Fernando; Sánchez-Durán, José A; Castellanos-Ramos, Julián; Hidalgo-López, José A

    2015-01-01

    Direct sensor-digital device interfaces measure time dependent variables of simple circuits to implement analog-to-digital conversion. Field Programmable Gate Arrays (FPGAs) are devices whose hardware can be reconfigured to work in parallel. They usually do not have analog-to-digital converters, but have many general purpose I/O pins. Therefore, direct sensor-FPGA connection is a good choice in complex systems with many sensors because several capture modules can be implemented to perform parallel analog data acquisition. The possibility to work in parallel and with high frequency clock signals improves the bandwidth compared to sequential devices such as conventional microcontrollers. The price to pay is usually the resolution of measurements. This paper proposes capture modules implemented in an FPGA which are able to perform smart acquisition that filter noise and achieve high precision. A calibration technique is also proposed to improve accuracy. Resolutions of 12 effective number of bits are obtained for the reading of resistors in the range of an example piezoresistive tactile sensor. PMID:26694403

  13. Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

    PubMed

    Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

    2015-05-01

    Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed. PMID:25969194

  14. Optical modulation of astrocyte network using ultrashort pulsed laser

    NASA Astrophysics Data System (ADS)

    Yoon, Jonghee; Ku, Taeyun; Chong, Kyuha; Ryu, Seung-Wook; Choi, Chulhee

    2012-03-01

    Astrocyte, the most abundant cell type in the central nervous system, has been one of major topics in neuroscience. Even though many tools have been developed for the analysis of astrocyte function, there has been no adequate tool that can modulates astrocyte network without pharmaceutical or genetic interventions. Here we found that ultrashort pulsed laser stimulation can induce label-free activation of astrocytes as well as apoptotic-like cell death in a dose-dependent manner. Upon irradiation with high intensity pulsed lasers, the irradiated cells with short exposure time showed very rapid mitochondria fragmentation, membrane blebbing and cytoskeletal retraction. We applied this technique to investigate in vivo function of astrocyte network in the CNS: in the aspect of neurovascular coupling and blood-brain barrier. We propose that this noninvasive technique can be widely applied for in vivo study of complex cellular network.

  15. Contextual Modulation is Related to Efficiency in a Spiking Network Model of Visual Cortex

    PubMed Central

    Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo; Vanni, Simo

    2016-01-01

    In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response. PMID:26834619

  16. Almost decouplability of any directed weighted network topology

    NASA Astrophysics Data System (ADS)

    Cai, Ning; Cao, Jun-Wei; Khan, M. Junaid

    2015-10-01

    This paper introduces a conception that any weighted directed network topology is almost decouplable, which can help to transform the topology into a similar form composed of uncoupled vertices, and thus reduce the complexity of analysis for networked dynamical systems. As an example of its application, the consensus problem of linear multi-agent systems with time-varying network topologies is addressed. As a result, a necessary and sufficient condition for uniform consensus is proposed.

  17. Reconstructing direct and indirect interactions in networked public goods game

    PubMed Central

    Han, Xiao; Shen, Zhesi; Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    Network reconstruction is a fundamental problem for understanding many complex systems with unknown interaction structures. In many complex systems, there are indirect interactions between two individuals without immediate connection but with common neighbors. Despite recent advances in network reconstruction, we continue to lack an approach for reconstructing complex networks with indirect interactions. Here we introduce a two-step strategy to resolve the reconstruction problem, where in the first step, we recover both direct and indirect interactions by employing the Lasso to solve a sparse signal reconstruction problem, and in the second step, we use matrix transformation and optimization to distinguish between direct and indirect interactions. The network structure corresponding to direct interactions can be fully uncovered. We exploit the public goods game occurring on complex networks as a paradigm for characterizing indirect interactions and test our reconstruction approach. We find that high reconstruction accuracy can be achieved for both homogeneous and heterogeneous networks, and a number of empirical networks in spite of insufficient data measurement contaminated by noise. Although a general framework for reconstructing complex networks with arbitrary types of indirect interactions is yet lacking, our approach opens new routes to separate direct and indirect interactions in a representative complex system. PMID:27444774

  18. Reconstructing direct and indirect interactions in networked public goods game

    NASA Astrophysics Data System (ADS)

    Han, Xiao; Shen, Zhesi; Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    Network reconstruction is a fundamental problem for understanding many complex systems with unknown interaction structures. In many complex systems, there are indirect interactions between two individuals without immediate connection but with common neighbors. Despite recent advances in network reconstruction, we continue to lack an approach for reconstructing complex networks with indirect interactions. Here we introduce a two-step strategy to resolve the reconstruction problem, where in the first step, we recover both direct and indirect interactions by employing the Lasso to solve a sparse signal reconstruction problem, and in the second step, we use matrix transformation and optimization to distinguish between direct and indirect interactions. The network structure corresponding to direct interactions can be fully uncovered. We exploit the public goods game occurring on complex networks as a paradigm for characterizing indirect interactions and test our reconstruction approach. We find that high reconstruction accuracy can be achieved for both homogeneous and heterogeneous networks, and a number of empirical networks in spite of insufficient data measurement contaminated by noise. Although a general framework for reconstructing complex networks with arbitrary types of indirect interactions is yet lacking, our approach opens new routes to separate direct and indirect interactions in a representative complex system.

  19. Reconstructing direct and indirect interactions in networked public goods game.

    PubMed

    Han, Xiao; Shen, Zhesi; Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    Network reconstruction is a fundamental problem for understanding many complex systems with unknown interaction structures. In many complex systems, there are indirect interactions between two individuals without immediate connection but with common neighbors. Despite recent advances in network reconstruction, we continue to lack an approach for reconstructing complex networks with indirect interactions. Here we introduce a two-step strategy to resolve the reconstruction problem, where in the first step, we recover both direct and indirect interactions by employing the Lasso to solve a sparse signal reconstruction problem, and in the second step, we use matrix transformation and optimization to distinguish between direct and indirect interactions. The network structure corresponding to direct interactions can be fully uncovered. We exploit the public goods game occurring on complex networks as a paradigm for characterizing indirect interactions and test our reconstruction approach. We find that high reconstruction accuracy can be achieved for both homogeneous and heterogeneous networks, and a number of empirical networks in spite of insufficient data measurement contaminated by noise. Although a general framework for reconstructing complex networks with arbitrary types of indirect interactions is yet lacking, our approach opens new routes to separate direct and indirect interactions in a representative complex system. PMID:27444774

  20. The theory of pattern formation on directed networks

    NASA Astrophysics Data System (ADS)

    Asllani, Malbor; Challenger, Joseph D.; Pavone, Francesco Saverio; Sacconi, Leonardo; Fanelli, Duccio

    2014-07-01

    Dynamical processes on networks have generated widespread interest in recent years. The theory of pattern formation in reaction-diffusion systems defined on symmetric networks has often been investigated, due to its applications in a wide range of disciplines. Here we extend the theory to the case of directed networks, which are found in a number of different fields, such as neuroscience, computer networks and traffic systems. Owing to the structure of the network Laplacian, the dispersion relation has both real and imaginary parts, at variance with the case for a symmetric, undirected network. The homogeneous fixed point can become unstable due to the topology of the network, resulting in a new class of instabilities, which cannot be induced on undirected graphs. Results from a linear stability analysis allow the instability region to be analytically traced. Numerical simulations show travelling waves, or quasi-stationary patterns, depending on the characteristics of the underlying graph.

  1. Gaze Direction Modulates the Relation between Neural Responses to Faces and Visual Awareness.

    PubMed

    Madipakkam, Apoorva Rajiv; Rothkirch, Marcus; Guggenmos, Matthias; Heinz, Andreas; Sterzer, Philipp

    2015-09-30

    Gaze direction and especially direct gaze is a powerful nonverbal cue that plays an important role in social interactions. Here we studied the neural mechanisms underlying the privileged access of direct gaze to visual awareness. We performed functional magnetic resonance imaging in healthy human volunteers who were exposed to faces with direct or averted gaze under continuous flash suppression, thereby manipulating their awareness of the faces. A gaze processing network comprising fusiform face area (FFA), superior temporal sulcus, amygdala, and intraparietal sulcus showed overall reduced neural responses when participants reported to be unaware of the faces. Interestingly, direct gaze elicited greater responses than averted gaze when participants were aware of the faces, but smaller responses when they were unaware. Additional between-subject correlation and single-trial analyses indicated that this pattern of results was due to a modulation of the relationship between neural responses and awareness by gaze direction: with increasing neural activation in the FFA, direct-gaze faces entered awareness more readily than averted-gaze faces. These findings suggest that for direct gaze, lower levels of neural activity are sufficient to give rise to awareness than for averted gaze, thus providing a neural basis for privileged access of direct gaze to awareness. Significance statement: Another person's eye gaze directed at oneself is a powerful social signal acting as a catalyst for further communication. Here, we studied the neural mechanisms underlying the prioritized access of direct gaze to visual awareness in healthy human volunteers and show that with increasing neural activation, direct-gaze faces enter awareness more readily than averted-gaze faces. This suggests that for a socially highly relevant cue like direct gaze, lower levels of neural activity are sufficient to give rise to awareness compared with averted gaze, possibly because the human brain is attuned

  2. Space station common module network topology and hardware development

    NASA Technical Reports Server (NTRS)

    Anderson, P.; Braunagel, L.; Chwirka, S.; Fishman, M.; Freeman, K.; Eason, D.; Landis, D.; Lech, L.; Martin, J.; Mccorkle, J.

    1990-01-01

    Conceptual space station common module power management and distribution (SSM/PMAD) network layouts and detailed network evaluations were developed. Individual pieces of hardware to be developed for the SSM/PMAD test bed were identified. A technology assessment was developed to identify pieces of equipment requiring development effort. Equipment lists were developed from the previously selected network schematics. Additionally, functional requirements for the network equipment as well as other requirements which affected the suitability of specific items for use on the Space Station Program were identified. Assembly requirements were derived based on the SSM/PMAD developed requirements and on the selected SSM/PMAD network concepts. Basic requirements and simplified design block diagrams are included. DC remote power controllers were successfully integrated into the DC Marshall Space Flight Center breadboard. Two DC remote power controller (RPC) boards experienced mechanical failure of UES 706 stud-mounted diodes during mechanical installation of the boards into the system. These broken diodes caused input to output shorting of the RPC's. The UES 706 diodes were replaced on these RPC's which eliminated the problem. The DC RPC's as existing in the present breadboard configuration do not provide ground fault protection because the RPC was designed to only switch the hot side current. If ground fault protection were to be implemented, it would be necessary to design the system so the RPC switched both the hot and the return sides of power.

  3. Transcranial direct current stimulation modulates efficiency of reading processes

    PubMed Central

    Thomson, Jennifer M.; Doruk, Deniz; Mascio, Bryan; Fregni, Felipe; Cerruti, Carlo

    2015-01-01

    Transcranial direct current stimulation (tDCS) is a neuromodulatory technique that offers promise as an investigative method for understanding complex cognitive operations such as reading. This study explores the ability of a single session of tDCS to modulate reading efficiency and phonological processing performance within a group of healthy adults. Half the group received anodal or cathodal stimulation, on two separate days, of the left temporo-parietal junction while the other half received anodal or cathodal stimulation of the right homologue area. Pre- and post-stimulation assessment of reading efficiency and phonological processing was carried out. A larger pre-post difference in reading efficiency was found for participants who received right anodal stimulation compared to participants who received left anodal stimulation. Further, there was a significant post-stimulation increase in phonological processing speed following right hemisphere anodal stimulation. Implications for models of reading and reading impairment are discussed. PMID:25852513

  4. Directed progression brain networks in Alzheimer's disease: properties and classification.

    PubMed

    Friedman, Eric J; Young, Karl; Asif, Danial; Jutla, Inderjit; Liang, Michael; Wilson, Scott; Landsberg, Adam S; Schuff, Norbert

    2014-06-01

    This article introduces a new approach in brain connectomics aimed at characterizing the temporal spread in the brain of pathologies like Alzheimer's disease (AD). The main instrument is the development of "directed progression networks" (DPNets), wherein one constructs directed edges between nodes based on (weakly) inferred directions of the temporal spreading of the pathology. This stands in contrast to many previously studied brain networks where edges represent correlations, physical connections, or functional progressions. In addition, this is one of a few studies showing the value of using directed networks in the study of AD. This article focuses on the construction of DPNets for AD using longitudinal cortical thickness measurements from magnetic resonance imaging data. The network properties are then characterized, providing new insights into AD progression, as well as novel markers for differentiating normal cognition (NC) and AD at the group level. It also demonstrates the important role of nodal variations for network classification (i.e., the significance of standard deviations, not just mean values of nodal properties). Finally, the DPNets are utilized to classify subjects based on their global network measures using a variety of data-mining methodologies. In contrast to most brain networks, these DPNets do not show high clustering and small-world properties. PMID:24901258

  5. Sinusoidal modulation control method in a chaotic neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Qihanyue; Xie, Xiaoping; Zhu, Ping; Chen, Hongping; He, Guoguang

    2014-08-01

    Chaotic neural networks (CNNs) have chaotic dynamic associative memory properties: The memory states appear non-periodically, and cannot be converged to a stored pattern. Thus, it is necessary to control chaos in a CNN in order to recognize associative memory. In this paper, a novel control method, the sinusoidal modulation control method, has been proposed to control chaos in a CNN. In this method, a sinusoidal wave simplified from brain waves is used as a control signal to modulate a parameter of the CNN. The simulation results demonstrate the effectiveness of this control method. The controlled CNN can be applied to information processing. Moreover, the method provides a way to associate brain waves by controlling CNNs.

  6. Optical vector network analyzer based on amplitude-phase modulation

    NASA Astrophysics Data System (ADS)

    Morozov, Oleg G.; Morozov, Gennady A.; Nureev, Ilnur I.; Kasimova, Dilyara I.; Zastela, Mikhail Y.; Gavrilov, Pavel V.; Makarov, Igor A.; Purtov, Vadim A.

    2016-03-01

    The article describes the principles of optical vector network analyzer (OVNA) design for fiber Bragg gratings (FBG) characterization based on amplitude-phase modulation of optical carrier that allow us to improve the measurement accuracy of amplitude and phase parameters of the elements under test. Unlike existing OVNA based on a single-sideband and unbalanced double sideband amplitude modulation, the ratio of the two side components of the probing radiation is used for analysis of amplitude and phase parameters of the tested elements, and the radiation of the optical carrier is suppressed, or the latter is used as a local oscillator. The suggested OVNA is designed for the narrow band-stop elements (π-phaseshift FBG) and wide band-pass elements (linear chirped FBG) research.

  7. How familiarization and repetition modulate the picture naming network

    PubMed Central

    Llorens, Anaïs; Trébuchon, Agnès; Riès, Stéphanie; Liégeois-Chauvel, Catherine; Alario, F.-Xavier

    2014-01-01

    A common strategy to reveal the components of the speech production network is to use psycholinguistic manipulations previously tested in behavioral protocols. This often disregards how implementation aspects that are nonessential for interpreting behavior may affect the neural response. We compared the electrophysiological (EEG) signature of two popular picture naming protocols involving either unfamiliar pictures without repetitions or repeated familiar pictures. We observed significant semantic interference effects in behavior but not in the EEG, contrary to some previous findings. Remarkably, the two protocols elicited clearly distinct EEG responses. These were not due to naming latency differences nor did they reflect a homogeneous modulation of amplitude over the trial time-window. The effect of protocol is attributed to the familiarization induced by the first encounter with the materials. Picture naming processes can be substantially modulated by specific protocol requirements controlled by familiarity and, to a much lesser degree, the repetition of materials. PMID:24785306

  8. Magnetic vestibular stimulation modulates default mode network fluctuations.

    PubMed

    Boegle, Rainer; Stephan, Thomas; Ertl, Matthias; Glasauer, Stefan; Dieterich, Marianne

    2016-02-15

    Strong magnetic fields (>1 Tesla) can cause dizziness and it was recently shown that healthy subjects (resting in total darkness) developed a persistent nystagmus even when remaining completely motionless within a MR tomograph. Consequently, it was speculated that this magnetic vestibular stimulation (MVS) might influence fMRI results, as nystagmus is indicative of an imbalance in the vestibular system, potentially influencing other systems via multisensory vestibular interactions. The objective of our study was to investigate whether MVS does indeed modulate BOLD signal fluctuations. We recorded eye movements, as well as, resting-state fMRI of 30 volunteers in darkness at 1.5 T and 3.0 T to answer the question whether MVS modulated parts of the default mode resting-state network (DMN) in accordance with the Lorentz-force model for MVS, while distinguishing this from the known signal increase due to field strength related imaging effects. Our results showed that modulation of the default mode network occurred mainly in areas associated with vestibular and ocular motor function, and was in accordance with the Lorentz-force model, i.e., double than the expected signal scaling due to field strength alone. We discuss the implications of our findings for the interpretation of studies using resting-state fMRI, especially those concerning vestibular research. We conclude that MVS needs to be considered in vestibular research to avoid biased results, but it might also offer the possibility of manipulating network dynamics and may thus help in studying the brain as a dynamical system. PMID:26666898

  9. Enhancing complex network controllability by minimum link direction reversal

    NASA Astrophysics Data System (ADS)

    Hou, Lvlin; Lao, Songyang; Small, Michael; Xiao, Yandong

    2015-07-01

    Controllability of complex networks has recently become one of the most popular research fields, but the importance of link direction for controllability has not been systematically considered. We propose a method to enhance controllability of a directed network by changing the direction of a small fraction of links while keeping the total number of links unchanged. The main idea of the method is to find candidate links based on the matching path. Extensive numerical simulation on many modeled networks demonstrates that this method is effective. Furthermore, we find that the nodes linked to candidate links have a distinct character, which provide us with a strategy to improve the controllability based on the local structure. Since the whole topology of many real networks is not visible and we only get some local structure information, this strategy is potentially more practical compared to those that demand complete topology information.

  10. The cascading vulnerability of the directed and weighted network

    NASA Astrophysics Data System (ADS)

    Jin, Wei-Xin; Song, Ping; Liu, Guo-Zhu; Stanley, H. Eugene

    2015-06-01

    The cascading failure can bring a huge loss for most real-world networks; but, we cannot uncover fully the mechanism and law of the cascading events occurrence. Most networks in which the cascading failure occurred are based on the various 'flows', such as power, oils, and information; moreover, the same link degree of the different nodes likely contain the different meanings, where some are large pivotal nodes and some are mini switching centers. Thus, these networks must be described by the directed and weighted network model. Besides, the 'over-loading' cascading failures were more analyzed and studied; but the cascading failures caused by 'short-loading' were less studied relatively. However, for some directed networks, such as power grids, oil pipe nets, gas pipe nets and information networks, the large-scale failures of network nodes substantially could be induced by 'short-loading' in a such similar way as 'over-loading'. Based on the above reasons, in this paper, we first built the 'load-capacity' model of the directed and weighted network. Afterwards the 'over-loading' cascading failure model and the 'short-loading' cascading failure model based on the directed and weighted network were built. Meanwhile, applying the models to two typical real networks-Poisson distribution network and power law distribution network-intensive study and numerical analysis were carried out. Lastly, two classical networks simulation experiment results are provided. After the numerical and simulation analyses, we gained the following conclusions. For the power law network, the power exponent β of 'load-capacity' function should be taken value (0, 1) for a good robustness, and the minimum in-degree and out-degree should be increased respectively, meanwhile, the weight and the scaling exponents of the in-degree and the out-degree distributions should be increased synchronously in the interval (2, 3) for enhancing the resistibility of 'over-loading' and 'short-loading' failures

  11. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    PubMed Central

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  12. Network modules and hubs in plant-root fungal biomes.

    PubMed

    Toju, Hirokazu; Yamamoto, Satoshi; Tanabe, Akifumi S; Hayakawa, Takashi; Ishii, Hiroshi S

    2016-03-01

    Terrestrial plants host phylogenetically and functionally diverse groups of below-ground microbes, whose community structure controls plant growth/survival in both natural and agricultural ecosystems. Therefore, understanding the processes by which whole root-associated microbiomes are organized is one of the major challenges in ecology and plant science. We here report that diverse root-associated fungi can form highly compartmentalized networks of coexistence within host roots and that the structure of the fungal symbiont communities can be partitioned into semi-discrete types even within a single host plant population. Illumina sequencing of root-associated fungi in a monodominant south beech forest revealed that the network representing symbiont-symbiont co-occurrence patterns was compartmentalized into clear modules, which consisted of diverse functional groups of mycorrhizal and endophytic fungi. Consequently, terminal roots of the plant were colonized by either of the two largest fungal species sets (represented by Oidiodendron or Cenococcum). Thus, species-rich root microbiomes can have alternative community structures, as recently shown in the relationships between human gut microbiome type (i.e., 'enterotype') and host individual health. This study also shows an analytical framework for pinpointing network hubs in symbiont-symbiont networks, leading to the working hypothesis that a small number of microbial species organize the overall root-microbiome dynamics. PMID:26962029

  13. Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

    PubMed Central

    Emmert-Streib, Frank

    2012-01-01

    It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level. PMID:22530042

  14. Flux modulation scheme for direct current SQUID readout revisited

    NASA Astrophysics Data System (ADS)

    Hong, Tao; Wang, Hai; Zhang, Yi; Krause, Hans-Joachim; Braginski, Alex I.; Xie, Xiaoming; Offenhäusser, Andreas; Jiang, Mianheng

    2016-02-01

    The flux modulation scheme (FMS) is the standard readout technique of dc SQUIDs, where a step-up transformer links the SQUID to the preamplifier. The transformer's primary winding shunts the SQUID via a large capacitor while the secondary winding connects it to the preamplifier. A modulation flux having a frequency of typically 100 kHz generates an ac voltage across the SQUID, stepped up by the transformer. The SQUID with FMS is customarily operated in the current bias mode, because a constant dc bias current flows only through the SQUID due to the capacitor isolation. With FMS, however, the transformer ac shunts the SQUID so that in reality the operating mode is neither purely current-biased nor voltage-biased but rather nominal current-biased or "mixed biased." Our objective is to experimentally investigate the consequences of ac shunting of the dc SQUID in FMS and the transformer's transfer characteristics. For different shunt values we measure the change in the SQUID bias current due to the ac shunt using another SQUID in the two-stage readout scheme, and simultaneously monitor the SQUID output voltage signal. We then explain our measurements by a simplified graphic analysis of SQUID intrinsic current-voltage (I-V) characteristics. Since the total current flowing through the SQUID is not constant due to the shunting effect of the transformer, the amplitude of SQUID flux-to-voltage characteristics V(Φ) is less as compared to the direct readout scheme (DRS). Furthermore, we analyze and compare V(Φ) obtained by DRS and FMS. We show that in FMS, the transfer characteristics of the SQUID circuit also depend on the isolation capacitance and the dynamic resistance of the SQUID.

  15. The middleware architecture supports heterogeneous network systems for module-based personal robot system

    NASA Astrophysics Data System (ADS)

    Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun

    2005-12-01

    On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general

  16. Discriminating direct and indirect connectivities in biological networks

    PubMed Central

    Kang, Taek; Moore, Richard; Li, Yi; Sontag, Eduardo; Bleris, Leonidas

    2015-01-01

    Reverse engineering of biological pathways involves an iterative process between experiments, data processing, and theoretical analysis. Despite concurrent advances in quality and quantity of data as well as computing resources and algorithms, difficulties in deciphering direct and indirect network connections are prevalent. Here, we adopt the notions of abstraction, emulation, benchmarking, and validation in the context of discovering features specific to this family of connectivities. After subjecting benchmark synthetic circuits to perturbations, we inferred the network connections using a combination of nonparametric single-cell data resampling and modular response analysis. Intriguingly, we discovered that recovered weights of specific network edges undergo divergent shifts under differential perturbations, and that the particular behavior is markedly different between topologies. Our results point to a conceptual advance for reverse engineering beyond weight inference. Investigating topological changes under differential perturbations may address the longstanding problem of discriminating direct and indirect connectivities in biological networks. PMID:26420864

  17. Interarrival times of message propagation on directed networks.

    PubMed

    Mihaljev, Tamara; de Arcangelis, Lucilla; Herrmann, Hans J

    2011-08-01

    One of the challenges in fighting cybercrime is to understand the dynamics of message propagation on botnets, networks of infected computers used to send viruses, unsolicited commercial emails (SPAM) or denial of service attacks. We map this problem to the propagation of multiple random walkers on directed networks and we evaluate the interarrival time distribution between successive walkers arriving at a target. We show that the temporal organization of this process, which models information propagation on unstructured peer to peer networks, has the same features as SPAM reaching a single user. We study the behavior of the message interarrival time distribution on three different network topologies using two different rules for sending messages. In all networks the propagation is not a pure Poisson process. It shows universal features on Poissonian networks and a more complex behavior on scale free networks. Results open the possibility to indirectly learn about the process of sending messages on networks with unknown topologies, by studying interarrival times at any node of the network. PMID:21929069

  18. Interarrival times of message propagation on directed networks

    NASA Astrophysics Data System (ADS)

    Mihaljev, Tamara; de Arcangelis, Lucilla; Herrmann, Hans J.

    2011-08-01

    One of the challenges in fighting cybercrime is to understand the dynamics of message propagation on botnets, networks of infected computers used to send viruses, unsolicited commercial emails (SPAM) or denial of service attacks. We map this problem to the propagation of multiple random walkers on directed networks and we evaluate the interarrival time distribution between successive walkers arriving at a target. We show that the temporal organization of this process, which models information propagation on unstructured peer to peer networks, has the same features as SPAM reaching a single user. We study the behavior of the message interarrival time distribution on three different network topologies using two different rules for sending messages. In all networks the propagation is not a pure Poisson process. It shows universal features on Poissonian networks and a more complex behavior on scale free networks. Results open the possibility to indirectly learn about the process of sending messages on networks with unknown topologies, by studying interarrival times at any node of the network.

  19. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

    PubMed

    Li, Jun; Zhao, Patrick X

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/. PMID:27446133

  20. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach

    PubMed Central

    Li, Jun; Zhao, Patrick X.

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/. PMID:27446133

  1. Mechanical compaction directly modulates the dynamics of bile canaliculi formation.

    PubMed

    Wang, Yan; Toh, Yi-Chin; Li, Qiushi; Nugraha, Bramasta; Zheng, Baixue; Lu, Thong Beng; Gao, Yi; Ng, Mary Mah Lee; Yu, Hanry

    2013-02-01

    Homeostatic pressure-driven compaction is a ubiquitous mechanical force in multicellular organisms and is proposed to be important in the maintenance of multicellular tissue integrity and function. Previous cell-free biochemical models have demonstrated that there are cross-talks between compaction forces and tissue structural functions, such as cell-cell adhesion. However, its involvement in physiological tissue function has yet to be directly demonstrated. Here, we use the bile canaliculus (BC) as a physiological example of a multicellular functional structure in the liver, and employ a novel 3D microfluidic hepatocyte culture system to provide an unprecedented opportunity to experimentally modulate the compaction states of primary hepatocyte aggregates in a 3D physiological-mimicking environment. Mechanical compaction alters the physical attributes of the hepatocyte aggregates, including cell shape, cell packing density and cell-cell contact area, but does not impair the hepatocytes' remodeling and functional capabilities. Characterization of structural and functional polarity shows that BC formation in compact hepatocyte aggregates is accelerated to as early as 12 hours post-seeding; whereas non-compact control requires 48 hours for functional BC formation. Further dynamic immunofluorescence imaging and gene expression profiling reveal that compaction accelerated BC formation is accompanied by changes in actin cytoskeleton remodeling dynamics and transcriptional levels of hepatic nuclear factor 4α and Annexin A2. Our report not only provides a novel strategy of modeling BC formation for in vitro hepatology research, but also shows a first instance that homeostatic pressure-driven compaction force is directly coupled to the higher-order multicellular functions. PMID:23233209

  2. Directed disassembly of an interfacial rubisco protein network.

    PubMed

    Onaizi, Sagheer A; Malcolm, Andrew S; He, Lizhong; Middelberg, Anton P J

    2007-05-22

    We present the first study of the directed disassembly of a protein network at the air-water interface by the synergistic action of a surfactant and an enzyme. We seek to understand the fundamentals of protein network disassembly by using rubisco adsorbed at the air-water interface as a model. We propose that rubisco adsorption at the air-water interface results in the formation of a fishnet-like network of interconnected protein molecules, capable of transmitting lateral force. The mechanical properties of the rubisco network during assembly and disassembly at the air-water interface were characterized by direct measurement of laterally transmitted force through the protein network using the Cambridge interfacial tensiometer. We have shown that, when used individually, either 2 ppm of the surfactant, sodium dodecyl benzyl sulfonate (SDOBS), or 2 ppm of the enzyme, subtilisin A (SA), were insufficient to completely disassemble the rubisco network within 1 h of treatment. However, a combination of 2 ppm SDOBS and 2 ppm SA led to almost complete disassembly within 1 h. Increasing the concentration of SA in the mixture from 2 to 10 ppm, while keeping the SDOBS concentration constant, significantly decreased the time required to completely disassemble the rubisco network. Furthermore, the initial rate of network disassembly using formulations containing SDOBS was surprisingly insensitive to this increase in SA concentration. This study gives insight into the role of lateral interactions between protein molecules at interfaces in stabilizing interfacial protein networks and shows that surfactant and enzyme working in combination proves more effective at disrupting and mobilizing the interfacial protein network than the action of either agent alone. PMID:17447802

  3. Keratinocytes can modulate and directly initiate nociceptive responses

    PubMed Central

    Baumbauer, Kyle M; DeBerry, Jennifer J; Adelman, Peter C; Miller, Richard H; Hachisuka, Junichi; Lee, Kuan Hsien; Ross, Sarah E; Koerber, H Richard; Davis, Brian M; Albers, Kathryn M

    2015-01-01

    How thermal, mechanical and chemical stimuli applied to the skin are transduced into signals transmitted by peripheral neurons to the CNS is an area of intense study. Several studies indicate that transduction mechanisms are intrinsic to cutaneous neurons and that epidermal keratinocytes only modulate this transduction. Using mice expressing channelrhodopsin (ChR2) in keratinocytes we show that blue light activation of the epidermis alone can produce action potentials (APs) in multiple types of cutaneous sensory neurons including SA1, A-HTMR, CM, CH, CMC, CMH and CMHC fiber types. In loss of function studies, yellow light stimulation of keratinocytes that express halorhodopsin reduced AP generation in response to naturalistic stimuli. These findings support the idea that intrinsic sensory transduction mechanisms in epidermal keratinocytes can directly elicit AP firing in nociceptive as well as tactile sensory afferents and suggest a significantly expanded role for the epidermis in sensory processing. DOI: http://dx.doi.org/10.7554/eLife.09674.001 PMID:26329459

  4. TRIM32 modulates pluripotency entry and exit by directly regulating Oct4 stability.

    PubMed

    Bahnassawy, Lamia'a; Perumal, Thanneer M; Gonzalez-Cano, Laura; Hillje, Anna-Lena; Taher, Leila; Makalowski, Wojciech; Suzuki, Yutaka; Fuellen, Georg; del Sol, Antonio; Schwamborn, Jens Christian

    2015-01-01

    Induced pluripotent stem cells (iPSCs) have revolutionized the world of regenerative medicine; nevertheless, the exact molecular mechanisms underlying their generation and differentiation remain elusive. Here, we investigated the role of the cell fate determinant TRIM32 in modulating such processes. TRIM32 is essential for the induction of neuronal differentiation of neural stem cells by poly-ubiquitinating cMyc to target it for degradation resulting in inhibition of cell proliferation. To elucidate the role of TRIM32 in regulating somatic cell reprogramming we analysed the capacity of TRIM32-knock-out mouse embryonic fibroblasts (MEFs) in generating iPSC colonies. TRIM32 knock-out MEFs produced a higher number of iPSC colonies indicating a role for TRIM32 in inhibiting this cellular transition. Further characterization of the generated iPSCs indicated that the TRIM32 knock-out iPSCs show perturbed differentiation kinetics. Additionally, mathematical modelling of global gene expression data revealed that during differentiation an Oct4 centred network in the wild-type cells is replaced by an E2F1 centred network in the TRIM32 deficient cells. We show here that this might be caused by a TRIM32-dependent downregulation of Oct4. In summary, the data presented here reveal that TRIM32 directly regulates at least two of the four Yamanaka Factors (cMyc and Oct4), to modulate cell fate transitions. PMID:26307407

  5. TRIM32 modulates pluripotency entry and exit by directly regulating Oct4 stability

    PubMed Central

    Bahnassawy, Lamia’a; Perumal, Thanneer M.; Gonzalez-Cano, Laura; Hillje, Anna-Lena; Taher, Leila; Makalowski, Wojciech; Suzuki, Yutaka; Fuellen, Georg; Sol, Antonio del; Schwamborn, Jens Christian

    2015-01-01

    Induced pluripotent stem cells (iPSCs) have revolutionized the world of regenerative medicine; nevertheless, the exact molecular mechanisms underlying their generation and differentiation remain elusive. Here, we investigated the role of the cell fate determinant TRIM32 in modulating such processes. TRIM32 is essential for the induction of neuronal differentiation of neural stem cells by poly-ubiquitinating cMyc to target it for degradation resulting in inhibition of cell proliferation. To elucidate the role of TRIM32 in regulating somatic cell reprogramming we analysed the capacity of TRIM32-knock-out mouse embryonic fibroblasts (MEFs) in generating iPSC colonies. TRIM32 knock-out MEFs produced a higher number of iPSC colonies indicating a role for TRIM32 in inhibiting this cellular transition. Further characterization of the generated iPSCs indicated that the TRIM32 knock-out iPSCs show perturbed differentiation kinetics. Additionally, mathematical modelling of global gene expression data revealed that during differentiation an Oct4 centred network in the wild-type cells is replaced by an E2F1 centred network in the TRIM32 deficient cells. We show here that this might be caused by a TRIM32-dependent downregulation of Oct4. In summary, the data presented here reveal that TRIM32 directly regulates at least two of the four Yamanaka Factors (cMyc and Oct4), to modulate cell fate transitions. PMID:26307407

  6. Gate modulation of anodically etched gallium arsenide nanowire random network

    NASA Astrophysics Data System (ADS)

    Aikawa, Shinya; Yamada, Kohei; Asoh, Hidetaka; Ono, Sachiko

    2016-06-01

    Gallium arsenide nanowires (GaAs NWs) formed by anodic etching show an electrically semi-insulating behavior because of charge carrier depletion caused by high interface state density. Here, we demonstrate the gate modulation of an anodically etched GaAs NW random network. By applying a reverse bias voltage after anodic etching of bulk GaAs, hydrogen ion exposure of the depleted NW region occurs, and then the interface state density is possibly decreased owing to the reduction in the amount of excess As generated at the interface between the amorphous Ga2O3 and GaAs layers. Consequently, the drain current of the thin-film transistor (TFT) with the GaAs NW random network was increased and was changed by the gate voltage. In contrast, the random network film remained in the insulator in the absence of reverse electrolysis treatment. The TFT performance is still insufficient but may be improved by optimizing the hydrogen ion exposure conditions.

  7. Development of a synthetic gene network to modulate gene expression by mechanical forces

    PubMed Central

    Kis, Zoltán; Rodin, Tania; Zafar, Asma; Lai, Zhangxing; Freke, Grace; Fleck, Oliver; Del Rio Hernandez, Armando; Towhidi, Leila; Pedrigi, Ryan M.; Homma, Takayuki; Krams, Rob

    2016-01-01

    The majority of (mammalian) cells in our body are sensitive to mechanical forces, but little work has been done to develop assays to monitor mechanosensor activity. Furthermore, it is currently impossible to use mechanosensor activity to drive gene expression. To address these needs, we developed the first mammalian mechanosensitive synthetic gene network to monitor endothelial cell shear stress levels and directly modulate expression of an atheroprotective transcription factor by shear stress. The technique is highly modular, easily scalable and allows graded control of gene expression by mechanical stimuli in hard-to-transfect mammalian cells. We call this new approach mechanosyngenetics. To insert the gene network into a high proportion of cells, a hybrid transfection procedure was developed that involves electroporation, plasmids replication in mammalian cells, mammalian antibiotic selection, a second electroporation and gene network activation. This procedure takes 1 week and yielded over 60% of cells with a functional gene network. To test gene network functionality, we developed a flow setup that exposes cells to linearly increasing shear stress along the length of the flow channel floor. Activation of the gene network varied logarithmically as a function of shear stress magnitude. PMID:27404994

  8. Development of a synthetic gene network to modulate gene expression by mechanical forces.

    PubMed

    Kis, Zoltán; Rodin, Tania; Zafar, Asma; Lai, Zhangxing; Freke, Grace; Fleck, Oliver; Del Rio Hernandez, Armando; Towhidi, Leila; Pedrigi, Ryan M; Homma, Takayuki; Krams, Rob

    2016-01-01

    The majority of (mammalian) cells in our body are sensitive to mechanical forces, but little work has been done to develop assays to monitor mechanosensor activity. Furthermore, it is currently impossible to use mechanosensor activity to drive gene expression. To address these needs, we developed the first mammalian mechanosensitive synthetic gene network to monitor endothelial cell shear stress levels and directly modulate expression of an atheroprotective transcription factor by shear stress. The technique is highly modular, easily scalable and allows graded control of gene expression by mechanical stimuli in hard-to-transfect mammalian cells. We call this new approach mechanosyngenetics. To insert the gene network into a high proportion of cells, a hybrid transfection procedure was developed that involves electroporation, plasmids replication in mammalian cells, mammalian antibiotic selection, a second electroporation and gene network activation. This procedure takes 1 week and yielded over 60% of cells with a functional gene network. To test gene network functionality, we developed a flow setup that exposes cells to linearly increasing shear stress along the length of the flow channel floor. Activation of the gene network varied logarithmically as a function of shear stress magnitude. PMID:27404994

  9. On-chip microwave photonic beamformer circuits operating with phase modulation and direct detection.

    PubMed

    Zhuang, Leimeng; Hoekman, Marcel; Taddei, Caterina; Leinse, Arne; Heideman, René G; Hulzinga, Adriaan; Verpoorte, Jaco; Oldenbeuving, Ruud M; van Dijk, Paulus W L; Boller, Klaus-J; Roeloffzen, Chris G H

    2014-07-14

    We propose and experimentally demonstrate the working principles of two novel microwave photonic (MWP) beamformer circuits operating with phase modulation (PM) and direct detection (DD). The proposed circuits incorporate two major signal processing functionalities, namely a broadband beamforming network employing ring resonator-based delay lines and an optical sideband manipulator that renders the circuit outputs equivalent to those of intensity-modulated MWP beamformers. These functionalities allow the system to employ low-circuit-complexity modulators and detectors, which brings significant benefits on the system construction cost and operation stability. The functionalities of the proposed MWP beamformer circuits were verified in experimental demonstrations performed on two sample circuits realized in Si(3)N(4)/SiO(2) waveguide technology. The measurements exhibit a 2 × 1 beamforming effect for an instantaneous RF transmission band of 3‒7 GHz, which is, to our best knowledge, the first verification of on-chip MWP beamformer circuits operating with PM and DD. PMID:25090522

  10. Part mutual information for quantifying direct associations in networks.

    PubMed

    Zhao, Juan; Zhou, Yiwei; Zhang, Xiujun; Chen, Luonan

    2016-05-01

    Quantitatively identifying direct dependencies between variables is an important task in data analysis, in particular for reconstructing various types of networks and causal relations in science and engineering. One of the most widely used criteria is partial correlation, but it can only measure linearly direct association and miss nonlinear associations. However, based on conditional independence, conditional mutual information (CMI) is able to quantify nonlinearly direct relationships among variables from the observed data, superior to linear measures, but suffers from a serious problem of underestimation, in particular for those variables with tight associations in a network, which severely limits its applications. In this work, we propose a new concept, "partial independence," with a new measure, "part mutual information" (PMI), which not only can overcome the problem of CMI but also retains the quantification properties of both mutual information (MI) and CMI. Specifically, we first defined PMI to measure nonlinearly direct dependencies between variables and then derived its relations with MI and CMI. Finally, we used a number of simulated data as benchmark examples to numerically demonstrate PMI features and further real gene expression data from Escherichia coli and yeast to reconstruct gene regulatory networks, which all validated the advantages of PMI for accurately quantifying nonlinearly direct associations in networks. PMID:27092000

  11. Quetiapine modulates functional connectivity in brain aggression networks.

    PubMed

    Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

    2013-07-15

    Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. PMID:23501053

  12. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

    PubMed Central

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M.; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

    2014-01-01

    In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions

  13. Transcriptional analysis of the MrpJ network: modulation of diverse virulence-associated genes and direct regulation of mrp fimbrial and flhDC flagellar operons in Proteus mirabilis.

    PubMed

    Bode, Nadine J; Debnath, Irina; Kuan, Lisa; Schulfer, Anjelique; Ty, Maureen; Pearson, Melanie M

    2015-06-01

    The enteric bacterium Proteus mirabilis is associated with a significant number of catheter-associated urinary tract infections (UTIs). Strict regulation of the antagonistic processes of adhesion and motility, mediated by fimbriae and flagella, respectively, is essential for disease progression. Previously, the transcriptional regulator MrpJ, which is encoded by the mrp fimbrial operon, has been shown to repress both swimming and swarming motility. Here we show that MrpJ affects an array of cellular processes beyond adherence and motility. Microarray analysis found that expression of mrpJ mimicking levels observed during UTIs leads to differential expression of 217 genes related to, among other functions, bacterial virulence, type VI secretion, and metabolism. We probed the molecular mechanism of transcriptional regulation by MrpJ using transcriptional reporters and chromatin immunoprecipitation (ChIP). Binding of MrpJ to two virulence-associated target gene promoters, the promoters of the flagellar master regulator flhDC and mrp itself, appears to be affected by the condensation state of the native chromosome, although both targets share a direct MrpJ binding site proximal to the transcriptional start. Furthermore, an mrpJ deletion mutant colonized the bladders of mice at significantly lower levels in a transurethral model of infection. Additionally, we observed that mrpJ is widely conserved in a collection of recent clinical isolates. Altogether, these findings support a role of MrpJ as a global regulator of P. mirabilis virulence. PMID:25847961

  14. Transcriptional Analysis of the MrpJ Network: Modulation of Diverse Virulence-Associated Genes and Direct Regulation of mrp Fimbrial and flhDC Flagellar Operons in Proteus mirabilis

    PubMed Central

    Bode, Nadine J.; Debnath, Irina; Kuan, Lisa; Schulfer, Anjelique; Ty, Maureen

    2015-01-01

    The enteric bacterium Proteus mirabilis is associated with a significant number of catheter-associated urinary tract infections (UTIs). Strict regulation of the antagonistic processes of adhesion and motility, mediated by fimbriae and flagella, respectively, is essential for disease progression. Previously, the transcriptional regulator MrpJ, which is encoded by the mrp fimbrial operon, has been shown to repress both swimming and swarming motility. Here we show that MrpJ affects an array of cellular processes beyond adherence and motility. Microarray analysis found that expression of mrpJ mimicking levels observed during UTIs leads to differential expression of 217 genes related to, among other functions, bacterial virulence, type VI secretion, and metabolism. We probed the molecular mechanism of transcriptional regulation by MrpJ using transcriptional reporters and chromatin immunoprecipitation (ChIP). Binding of MrpJ to two virulence-associated target gene promoters, the promoters of the flagellar master regulator flhDC and mrp itself, appears to be affected by the condensation state of the native chromosome, although both targets share a direct MrpJ binding site proximal to the transcriptional start. Furthermore, an mrpJ deletion mutant colonized the bladders of mice at significantly lower levels in a transurethral model of infection. Additionally, we observed that mrpJ is widely conserved in a collection of recent clinical isolates. Altogether, these findings support a role of MrpJ as a global regulator of P. mirabilis virulence. PMID:25847961

  15. Dynamic modulation of intrinsic functional connectivity by transcranial direct current stimulation.

    PubMed

    Sehm, Bernhard; Schäfer, Alexander; Kipping, Judy; Margulies, Daniel; Conde, Virginia; Taubert, Marco; Villringer, Arno; Ragert, Patrick

    2012-12-01

    Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique capable of modulating cortical excitability and thereby influencing behavior and learning. Recent evidence suggests that bilateral tDCS over both primary sensorimotor cortices (SM1) yields more prominent effects on motor performance in both healthy subjects and chronic stroke patients than unilateral tDCS over SM1. To better characterize the underlying neural mechanisms of this effect, we aimed to explore changes in resting-state functional connectivity during both stimulation types. In a randomized single-blind crossover design, 12 healthy subjects underwent functional magnetic resonance imaging at rest before, during, and after 20 min of unilateral, bilateral, and sham tDCS stimulation over SM1. Eigenvector centrality mapping (ECM) was used to investigate tDCS-induced changes in functional connectivity patterns across the whole brain. Uni- and bilateral tDCS over SM1 resulted in functional connectivity changes in widespread brain areas compared with sham stimulation both during and after stimulation. Whereas bilateral tDCS predominantly modulated changes in primary and secondary motor as well as prefrontal regions, unilateral tDCS affected prefrontal, parietal, and cerebellar areas. No direct effect was seen under the stimulating electrode in the unilateral condition. The time course of changes in functional connectivity in the respective brain areas was nonlinear and temporally dispersed. These findings provide evidence toward a network-based understanding regarding the underpinnings of specific tDCS interventions. PMID:22993265

  16. Maintain the structural controllability under malicious attacks on directed networks

    NASA Astrophysics Data System (ADS)

    Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue

    2013-03-01

    The directedness of the links in a network plays a critical role in determining many dynamical processes among which the controllability has received much recent attention. The control robustness of a network against malicious attack and random failure also becomes a significant issue. In this paper, we propose a novel control robustness index motivated by recent studies on the global connectivity and controllability. In its general form, the problem of optimizing the control robustness index is computationally infeasible for large-scale networks. By analysing the influences of several directed topological factors on the dynamical control process, we transform the control robustness problem into the problem of transitivity maximization for control routes, and propose an efficient greedy algorithm to make control routes transitive. A series of experiments on real-world and synthetic networks show that the global connectivity and controllability can be improved simultaneously and we can mitigate the destruction of malicious attack through backing up the control routes.

  17. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    NASA Technical Reports Server (NTRS)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  18. Theory of interface: category theory, directed networks and evolution of biological networks.

    PubMed

    Haruna, Taichi

    2013-11-01

    Biological networks have two modes. The first mode is static: a network is a passage on which something flows. The second mode is dynamic: a network is a pattern constructed by gluing functions of entities constituting the network. In this paper, first we discuss that these two modes can be associated with the category theoretic duality (adjunction) and derive a natural network structure (a path notion) for each mode by appealing to the category theoretic universality. The path notion corresponding to the static mode is just the usual directed path. The path notion for the dynamic mode is called lateral path which is the alternating path considered on the set of arcs. Their general functionalities in a network are transport and coherence, respectively. Second, we introduce a betweenness centrality of arcs for each mode and see how the two modes are embedded in various real biological network data. We find that there is a trade-off relationship between the two centralities: if the value of one is large then the value of the other is small. This can be seen as a kind of division of labor in a network into transport on the network and coherence of the network. Finally, we propose an optimization model of networks based on a quality function involving intensities of the two modes in order to see how networks with the above trade-off relationship can emerge through evolution. We show that the trade-off relationship can be observed in the evolved networks only when the dynamic mode is dominant in the quality function by numerical simulations. We also show that the evolved networks have features qualitatively similar to real biological networks by standard complex network analysis. PMID:24012823

  19. Low-frequency analog signal distribution on digital photonic networks by optical delta-sigma modulation

    NASA Astrophysics Data System (ADS)

    Kanno, Atsushi; Kawanishi, Tetsuya

    2013-12-01

    We propose a delta-sigma modulation scheme for low- and medium-frequency signal transmission in a digital photonic network system. A 10-Gb/s-class optical transceiver with a delta-sigma modulator utilized as a high-speed analog-to-digital converter (ADC) provides a binary optical signal. On the signal reception side, a low-cost and slow-speed photonic receiver directly converts the binary signal into an analog signal at frequencies from several hundreds of kilohertz several tens of megahertz. Further, by using a clock and data recovery circuit at the receiver to reduce jitters, the single-sideband phase noise of the generated signals can be significantly reduced.

  20. Network burst dynamics under heterogeneous cholinergic modulation of neural firing properties and heterogeneous synaptic connectivity

    PubMed Central

    Knudstrup, Scott; Zochowski, Michal; Booth, Victoria

    2016-01-01

    The characteristics of neural network activity depend on intrinsic neural properties and synaptic connectivity in the network. In brain networks, both of these properties are critically affected by the type and levels of neuromodulators present. The expression of many of the most powerful neuromodulators, including acetylcholine (ACh), varies tonically and phasically with behavioural state, leading to dynamic, heterogeneous changes in intrinsic neural properties and synaptic connectivity properties. Namely, ACh significantly alters neural firing properties as measured by the phase response curve in a manner that has been shown to alter the propensity for network synchronization. The aim of this simulation study was to build an understanding of how heterogeneity in cholinergic modulation of neural firing properties and heterogeneity in synaptic connectivity affect the initiation and maintenance of synchronous network bursting in excitatory networks. We show that cells that display different levels of ACh modulation have differential roles in generating network activity: weakly modulated cells are necessary for burst initiation and provide synchronizing drive to the rest of the network, whereas strongly modulated cells provide the overall activity level necessary to sustain burst firing. By applying several quantitative measures of network activity, we further show that the existence of network bursting and its characteristics, such as burst duration and intraburst synchrony, are dependent on the fraction of cell types providing the synaptic connections in the network. These results suggest mechanisms underlying ACh modulation of brain oscillations and the modulation of seizure activity during sleep states. PMID:26869313

  1. Network burst dynamics under heterogeneous cholinergic modulation of neural firing properties and heterogeneous synaptic connectivity.

    PubMed

    Knudstrup, Scott; Zochowski, Michal; Booth, Victoria

    2016-05-01

    The characteristics of neural network activity depend on intrinsic neural properties and synaptic connectivity in the network. In brain networks, both of these properties are critically affected by the type and levels of neuromodulators present. The expression of many of the most powerful neuromodulators, including acetylcholine (ACh), varies tonically and phasically with behavioural state, leading to dynamic, heterogeneous changes in intrinsic neural properties and synaptic connectivity properties. Namely, ACh significantly alters neural firing properties as measured by the phase response curve in a manner that has been shown to alter the propensity for network synchronization. The aim of this simulation study was to build an understanding of how heterogeneity in cholinergic modulation of neural firing properties and heterogeneity in synaptic connectivity affect the initiation and maintenance of synchronous network bursting in excitatory networks. We show that cells that display different levels of ACh modulation have differential roles in generating network activity: weakly modulated cells are necessary for burst initiation and provide synchronizing drive to the rest of the network, whereas strongly modulated cells provide the overall activity level necessary to sustain burst firing. By applying several quantitative measures of network activity, we further show that the existence of network bursting and its characteristics, such as burst duration and intraburst synchrony, are dependent on the fraction of cell types providing the synaptic connections in the network. These results suggest mechanisms underlying ACh modulation of brain oscillations and the modulation of seizure activity during sleep states. PMID:26869313

  2. Direct dark matter search with XMASS: modulation analysis

    NASA Astrophysics Data System (ADS)

    Kobayashi, Kazuyoshi; XMASS Collaboration

    2016-05-01

    Dark matter search by means of the annual modulation was done using large single-phase liquid-xenon detector, XMASS. With the data from November-2013 to March-2015, model independent analysis showed a weak modulation effect, however, the result can be explained by a fluctuation of the background at the level of 7-17%. If we assume the standard weekly interacting massive particles dark matter, we exclude almost all the allowed region claimed by the DAMA/LIBRA experiment. This is the first extensive search over their allowed region exploiting the annual modulation with high statistics data.

  3. Detecting modules in biological networks by edge weight clustering and entropy significance.

    PubMed

    Lecca, Paola; Re, Angela

    2015-01-01

    Detection of the modular structure of biological networks is of interest to researchers adopting a systems perspective for the analysis of omics data. Computational systems biology has provided a rich array of methods for network clustering. To date, the majority of approaches address this task through a network node classification based on topological or external quantifiable properties of network nodes. Conversely, numerical properties of network edges are underused, even though the information content which can be associated with network edges has augmented due to steady advances in molecular biology technology over the last decade. Properly accounting for network edges in the development of clustering approaches can become crucial to improve quantitative interpretation of omics data, finally resulting in more biologically plausible models. In this study, we present a novel technique for network module detection, named WG-Cluster (Weighted Graph CLUSTERing). WG-Cluster's notable features, compared to current approaches, lie in: (1) the simultaneous exploitation of network node and edge weights to improve the biological interpretability of the connected components detected, (2) the assessment of their statistical significance, and (3) the identification of emerging topological properties in the detected connected components. WG-Cluster utilizes three major steps: (i) an unsupervised version of k-means edge-based algorithm detects sub-graphs with similar edge weights, (ii) a fast-greedy algorithm detects connected components which are then scored and selected according to the statistical significance of their scores, and (iii) an analysis of the convolution between sub-graph mean edge weight and connected component score provides a summarizing view of the connected components. WG-Cluster can be applied to directed and undirected networks of different types of interacting entities and scales up to large omics data sets. Here, we show that WG-Cluster can be

  4. Detecting modules in biological networks by edge weight clustering and entropy significance

    PubMed Central

    Lecca, Paola; Re, Angela

    2015-01-01

    Detection of the modular structure of biological networks is of interest to researchers adopting a systems perspective for the analysis of omics data. Computational systems biology has provided a rich array of methods for network clustering. To date, the majority of approaches address this task through a network node classification based on topological or external quantifiable properties of network nodes. Conversely, numerical properties of network edges are underused, even though the information content which can be associated with network edges has augmented due to steady advances in molecular biology technology over the last decade. Properly accounting for network edges in the development of clustering approaches can become crucial to improve quantitative interpretation of omics data, finally resulting in more biologically plausible models. In this study, we present a novel technique for network module detection, named WG-Cluster (Weighted Graph CLUSTERing). WG-Cluster's notable features, compared to current approaches, lie in: (1) the simultaneous exploitation of network node and edge weights to improve the biological interpretability of the connected components detected, (2) the assessment of their statistical significance, and (3) the identification of emerging topological properties in the detected connected components. WG-Cluster utilizes three major steps: (i) an unsupervised version of k-means edge-based algorithm detects sub-graphs with similar edge weights, (ii) a fast-greedy algorithm detects connected components which are then scored and selected according to the statistical significance of their scores, and (iii) an analysis of the convolution between sub-graph mean edge weight and connected component score provides a summarizing view of the connected components. WG-Cluster can be applied to directed and undirected networks of different types of interacting entities and scales up to large omics data sets. Here, we show that WG-Cluster can be

  5. Metastability and inter-band frequency modulation in networks of oscillating spiking neuron populations.

    PubMed

    Bhowmik, David; Shanahan, Murray

    2013-01-01

    Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

  6. Direct electrical-to-optical conversion and light modulation in micro whispering-gallery-mode resonators

    NASA Technical Reports Server (NTRS)

    Maleki, Lute (Inventor); Levi, Anthony F. J. (Inventor)

    2005-01-01

    Techniques for directly converting an electrical signal into an optical signal by using a whispering gallery mode optical resonator formed of a dielectric material that allows for direct modulation of optical absorption by the electrical signal.

  7. Unbiased degree-preserving randomization of directed binary networks

    NASA Astrophysics Data System (ADS)

    Roberts, E. S.; Coolen, A. C. C.

    2012-04-01

    Randomizing networks using a naive “accept-all” edge-swap algorithm is generally biased. Building on recent results for nondirected graphs, we construct an ergodic detailed balance Markov chain with nontrivial acceptance probabilities for directed graphs, which converges to a strictly uniform measure and is based on edge swaps that conserve all in and out degrees. The acceptance probabilities can also be generalized to define Markov chains that target any alternative desired measure on the space of directed graphs in order to generate graphs with more sophisticated topological features. This is demonstrated by defining a process tailored to the production of directed graphs with specified degree-degree correlation functions. The theory is implemented numerically and tested on synthetic and biological network examples.

  8. Network-based survival-associated module biomarker and its crosstalk with cell death genes in ovarian cancer

    PubMed Central

    Jin, Nana; Wu, Hao; Miao, Zhengqiang; Huang, Yan; Hu, Yongfei; Bi, Xiaoman; Wu, Deng; Qian, Kun; Wang, Liqiang; Wang, Changliang; Wang, Hongwei; Li, Kongning; Li, Xia; Wang, Dong

    2015-01-01

    Ovarian cancer remains a dismal disease with diagnosing in the late, metastatic stages, therefore, there is a growing realization of the critical need to develop effective biomarkers for understanding underlying mechanisms. Although existing evidences demonstrate the important role of the single genetic abnormality in pathogenesis, the perturbations of interactors in the complex network are often ignored. Moreover, ovarian cancer diagnosis and treatment still exist a large gap that need to be bridged. In this work, we adopted a network-based survival-associated approach to capture a 12-gene network module based on differential co-expression PPI network in the advanced-stage, high-grade ovarian serous cystadenocarcinoma. Then, regulatory genes (protein-coding genes and non-coding genes) direct interacting with the module were found to be significantly overlapped with cell death genes. More importantly, these overlapping genes tightly clustered together pointing to the module, deciphering the crosstalk between network-based survival-associated module and cell death in ovarian cancer. PMID:26099452

  9. Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity

    PubMed Central

    Hunter, Michael A.; Coffman, Brian A.; Gasparovic, Charles; Calhoun, Vince D.; Trumbo, Michael C.; Clark, Vincent P.

    2015-01-01

    Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain’s neural architecture, from the micro to macro scales, have yet to be illuminated. Using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy (1H-MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-state networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. 1H-MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal-parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia (p < 0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. The observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders. PMID:25312829

  10. Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks

    PubMed Central

    Shen, Ru; Wang, Xiaosheng; Guda, Chittibabu

    2015-01-01

    Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological network analysis. Results. In this study, we developed a new graph theory based method to identify distinct functional modules from nine different cancer protein-protein interaction networks. The method is composed of three major steps: (i) extracting modules from protein-protein interaction networks using network clustering algorithms; (ii) identifying distinct subgraphs from the derived modules; and (iii) identifying distinct subgraph patterns from distinct subgraphs. The subgraph patterns were evaluated using experimentally determined cancer-specific protein-protein interaction data from the Ingenuity knowledgebase, to identify distinct functional modules that are specific to each cancer type. Conclusion. We identified cancer-type specific subgraph patterns that may represent the functional modules involved in the molecular pathogenesis of different cancer types. Our method can serve as an effective tool to discover cancer-type specific functional modules from large protein-protein interaction networks. PMID:26495282

  11. C-element: a new clustering algorithm to find high quality functional modules in PPI networks.

    PubMed

    Ghasemi, Mahdieh; Rahgozar, Maseud; Bidkhori, Gholamreza; Masoudi-Nejad, Ali

    2013-01-01

    Graph clustering algorithms are widely used in the analysis of biological networks. Extracting functional modules in protein-protein interaction (PPI) networks is one such use. Most clustering algorithms whose focuses are on finding functional modules try either to find a clique like sub networks or to grow clusters starting from vertices with high degrees as seeds. These algorithms do not make any difference between a biological network and any other networks. In the current research, we present a new procedure to find functional modules in PPI networks. Our main idea is to model a biological concept and to use this concept for finding good functional modules in PPI networks. In order to evaluate the quality of the obtained clusters, we compared the results of our algorithm with those of some other widely used clustering algorithms on three high throughput PPI networks from Sacchromyces Cerevisiae, Homo sapiens and Caenorhabditis elegans as well as on some tissue specific networks. Gene Ontology (GO) analyses were used to compare the results of different algorithms. Each algorithm's result was then compared with GO-term derived functional modules. We also analyzed the effect of using tissue specific networks on the quality of the obtained clusters. The experimental results indicate that the new algorithm outperforms most of the others, and this improvement is more significant when tissue specific networks are used. PMID:24039752

  12. Integrated Brain Circuits: Astrocytic Networks Modulate Neuronal Activity and Behavior

    PubMed Central

    Halassa, Michael M.; Haydon, Philip G.

    2011-01-01

    The past decade has seen an explosion of research on roles of neuron-astrocyte interactions in the control of brain function. We highlight recent studies performed on the tripartite synapse, the structure consisting of pre- and postsynaptic elements of the synapse and an associated astrocytic process. Astrocytes respond to neuronal activity and neuro-transmitters, through the activation of metabotropic receptors, and can release the gliotransmitters ATP, D-serine, and glutamate, which act on neurons. Astrocyte-derived ATP modulates synaptic transmission, either directly or through its metabolic product adenosine. D-serine modulates NMDA receptor function, whereas glia-derived glutamate can play important roles in relapse following withdrawal from drugs of abuse. Cell type–specific molecular genetics has allowed a new level of examination of the function of astrocytes in brain function and has revealed an important role of these glial cells that is mediated by adenosine accumulation in the control of sleep and in cognitive impairments that follow sleep deprivation. PMID:20148679

  13. 40-Gb/s directly-modulated photonic crystal lasers under optical injection-locking

    NASA Astrophysics Data System (ADS)

    Chen, Chin-Hui; Takeda, Koji; Shinya, Akihiko; Nozaki, Kengo; Sato, Tomonari; Kawaguchi, Yoshihiro; Notomi, Masaya; Matsuo, Shinji

    2011-08-01

    CMOS integrated circuits (IC) usually requires high data bandwidth for off-chip input/output (I/O) data transport with sufficiently low power consumption in order to overcome pin-count limitation. In order to meet future requirements of photonic network interconnect, we propose an optical output device based on an optical injection-locked photonic crystal (PhC) laser to realize low-power and high-speed off-chip interconnects. This device enables ultralow-power operation and is suitable for highly integrated photonic circuits because of its strong light-matter interaction in the PhC nanocavity and ultra-compact size. High-speed operation is achieved by using the optical injection-locking (OIL) technique, which has been shown as an effective means to enhance modulation bandwidth beyond the relaxation resonance frequency limit. In this paper, we report experimental results of the OIL-PhC laser under various injection conditions and also demonstrate 40-Gb/s large-signal direct modulation with an ultralow energy consumption of 6.6 fJ/bit.

  14. 40-Gb/s directly-modulated photonic crystal lasers under optical injection-locking.

    PubMed

    Chen, Chin-Hui; Takeda, Koji; Shinya, Akihiko; Nozaki, Kengo; Sato, Tomonari; Kawaguchi, Yoshihiro; Notomi, Masaya; Matsuo, Shinji

    2011-08-29

    CMOS integrated circuits (IC) usually requires high data bandwidth for off-chip input/output (I/O) data transport with sufficiently low power consumption in order to overcome pin-count limitation. In order to meet future requirements of photonic network interconnect, we propose an optical output device based on an optical injection-locked photonic crystal (PhC) laser to realize low-power and high-speed off-chip interconnects. This device enables ultralow-power operation and is suitable for highly integrated photonic circuits because of its strong light-matter interaction in the PhC nanocavity and ultra-compact size. High-speed operation is achieved by using the optical injection-locking (OIL) technique, which has been shown as an effective means to enhance modulation bandwidth beyond the relaxation resonance frequency limit. In this paper, we report experimental results of the OIL-PhC laser under various injection conditions and also demonstrate 40-Gb/s large-signal direct modulation with an ultralow energy consumption of 6.6 fJ/bit. PMID:21935134

  15. Site-directed deep electronic tunneling through a molecular network

    SciTech Connect

    Caspary, Maytal; Peskin, Uri

    2005-10-15

    Electronic tunneling in a complex molecular network of N(>2) donor/acceptor sites, connected by molecular bridges, is analyzed. The 'deep' tunneling dynamics is formulated using a recursive perturbation expansion, yielding a McConnell-type reduced N-level model Hamiltonian. Applications to models of molecular junctions demonstrate that the donor-bridge contact parameters can be tuned in order to control the tunneling dynamics and particularly to direct the tunneling pathway to either one of the various acceptors.

  16. Oscillatory entrainment of the motor cortical network during motor imagery is modulated by the feedback modality.

    PubMed

    Vukelić, Mathias; Gharabaghi, Alireza

    2015-05-01

    Neurofeedback of self-regulated brain activity in circumscribed cortical regions is used as a novel strategy to facilitate functional restoration following stroke. Basic knowledge about its impact on motor system oscillations and functional connectivity is however scarce. Specifically, a direct comparison between different feedback modalities and their neural signatures is missing. We assessed a neurofeedback training intervention of modulating β-activity in circumscribed sensorimotor regions by kinesthetic motor imagery (MI). Right-handed healthy participants received two different feedback modalities contingent to their MI-associated brain activity in a cross-over design: (I) visual feedback with a brain-computer interface (BCI) and (II) proprioceptive feedback with a brain-robot interface (BRI) orthosis attached to the right hand. High-density electroencephalography was used to examine the reactivity of the cortical motor system during the training session of each task by studying both local oscillatory power entrainment and distributed functional connectivity. Both feedback modalities activated a distributed functional connectivity network of coherent oscillations. A significantly higher skill and lower variability of self-controlled sensorimotor β-band modulation could, however, be achieved in the BRI condition. This gain in controlling regional motor oscillations was accompanied by functional coupling of remote β-band and θ-band activity in bilateral fronto-central regions and left parieto-occipital regions, respectively. The functional coupling of coherent θ-band oscillations correlated moreover with the skill of regional β-modulation thus revealing a motor learning related network. Our findings indicate that proprioceptive feedback is more suitable than visual feedback to entrain the motor network architecture during the interplay between motor imagery and feedback processing thus resulting in better volitional control of regional brain activity. PMID

  17. Learning module networks from genome-wide location and expression data.

    PubMed

    Xu, Xiaojiang; Wang, Lianshui; Ding, Dafu

    2004-12-17

    We develop a systematic algorithm for discovering network of regulatory modules, which identifies regulatory modules and their regulation program by integrating genome-wide location and expression data. Unlike previous approaches [Eisen, M.B., Spellman, P.T., Brown, P.O. and Botstein, D. (1998) Proc. Natl. Acad. Sci. USA 95, 14863-14868; Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J. and Church, G.M. (1999) Nat. Genet. 22, 281-285; Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Nat. Genet. 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Nat. Genet. 34, 166-176] that relied primarily on gene expression data, our algorithm regards the regulator binding data as prior knowledge that provide direct evidence of physical regulatory interactions. We applied the method to a Saccharomyces cerevisiae genome-wide location data [Lee, T.I., Rinaldi, N.J., Robert, F., Odom, D.T., Bar-Joseph, Z., Gerber, G.K., Hannett, N.M., Harbison, C.T., Thompson, C.M., Simon, I., Zeitlinger, J., Jennings, E.G., Murray, H.L. Gordon, D.B., Ren, B., Wyrick, J.J., Tagne, J.B., Volkert, T.L., Fraenkel, E., Gifford, D.K. and Young, R.A. (2002) Science 298, 799-804] for 106 DNA-binding transcription factors and 250 gene expression experiments under the conditions from the cell cycle to responses to various stress conditions. The results show that our method is able to identify functionally coherent modules and their proper regulators. Supplementary materials are available at http://compbio.sibnet.org/projects/module-network/. PMID:15589836

  18. Moving target tracking through distributed clustering in directional sensor networks.

    PubMed

    Enayet, Asma; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

    2014-01-01

    The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works. PMID:25529205

  19. Interest communities and flow roles in directed networks: the Twitter network of the UK riots.

    PubMed

    Beguerisse-Díaz, Mariano; Garduño-Hernández, Guillermo; Vangelov, Borislav; Yaliraki, Sophia N; Barahona, Mauricio

    2014-12-01

    Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e. groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer and topic. The study of flows also allows us to generate an interest distance, which affords a personalized view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterized by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks. PMID:25297320

  20. Interest communities and flow roles in directed networks: the Twitter network of the UK riots

    PubMed Central

    Beguerisse-Díaz, Mariano; Garduño-Hernández, Guillermo; Vangelov, Borislav; Yaliraki, Sophia N.; Barahona, Mauricio

    2014-01-01

    Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e. groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer and topic. The study of flows also allows us to generate an interest distance, which affords a personalized view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterized by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks. PMID:25297320

  1. Phase transitions in Ising models on directed networks.

    PubMed

    Lipowski, Adam; Ferreira, António Luis; Lipowska, Dorota; Gontarek, Krzysztof

    2015-11-01

    We examine Ising models with heat-bath dynamics on directed networks. Our simulations show that Ising models on directed triangular and simple cubic lattices undergo a phase transition that most likely belongs to the Ising universality class. On the directed square lattice the model remains paramagnetic at any positive temperature as already reported in some previous studies. We also examine random directed graphs and show that contrary to undirected ones, percolation of directed bonds does not guarantee ferromagnetic ordering. Only above a certain threshold can a random directed graph support finite-temperature ferromagnetic ordering. Such behavior is found also for out-homogeneous random graphs, but in this case the analysis of magnetic and percolative properties can be done exactly. Directed random graphs also differ from undirected ones with respect to zero-temperature freezing. Only at low connectivity do they remain trapped in a disordered configuration. Above a certain threshold, however, the zero-temperature dynamics quickly drives the model toward a broken symmetry (magnetized) state. Only above this threshold, which is almost twice as large as the percolation threshold, do we expect the Ising model to have a positive critical temperature. With a very good accuracy, the behavior on directed random graphs is reproduced within a certain approximate scheme. PMID:26651748

  2. Phase transitions in Ising models on directed networks

    NASA Astrophysics Data System (ADS)

    Lipowski, Adam; Ferreira, António Luis; Lipowska, Dorota; Gontarek, Krzysztof

    2015-11-01

    We examine Ising models with heat-bath dynamics on directed networks. Our simulations show that Ising models on directed triangular and simple cubic lattices undergo a phase transition that most likely belongs to the Ising universality class. On the directed square lattice the model remains paramagnetic at any positive temperature as already reported in some previous studies. We also examine random directed graphs and show that contrary to undirected ones, percolation of directed bonds does not guarantee ferromagnetic ordering. Only above a certain threshold can a random directed graph support finite-temperature ferromagnetic ordering. Such behavior is found also for out-homogeneous random graphs, but in this case the analysis of magnetic and percolative properties can be done exactly. Directed random graphs also differ from undirected ones with respect to zero-temperature freezing. Only at low connectivity do they remain trapped in a disordered configuration. Above a certain threshold, however, the zero-temperature dynamics quickly drives the model toward a broken symmetry (magnetized) state. Only above this threshold, which is almost twice as large as the percolation threshold, do we expect the Ising model to have a positive critical temperature. With a very good accuracy, the behavior on directed random graphs is reproduced within a certain approximate scheme.

  3. Intrinsic functional network architecture of human semantic processing: Modules and hubs.

    PubMed

    Xu, Yangwen; Lin, Qixiang; Han, Zaizhu; He, Yong; Bi, Yanchao

    2016-05-15

    Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta-analysis of 120 neuroimaging studies (Binder et al., 2009), we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN), the left perisylvian network (Module PSN), and the left frontoparietal network (Module FPN). These three dissociable modules were integrated by multiple connector hubs-the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro-functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control. PMID:26973170

  4. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    NASA Astrophysics Data System (ADS)

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  5. Dopaminergic modulation of motor network dynamics in Parkinson's disease.

    PubMed

    Michely, Jochen; Volz, Lukas J; Barbe, Michael T; Hoffstaedter, Felix; Viswanathan, Shivakumar; Timmermann, Lars; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

    2015-03-01

    Although characteristic motor symptoms of Parkinson's disease such as bradykinesia typically improve under dopaminergic medication, deficits in higher motor control are less responsive. We here investigated the dopaminergic modulation of network dynamics underlying basic motor performance, i.e. finger tapping, and higher motor control, i.e. internally and externally cued movement preparation and selection. Twelve patients, assessed ON and OFF medication, and 12 age-matched healthy subjects underwent functional magnetic resonance imaging. Dynamic causal modelling was used to assess effective connectivity in a motor network comprising cortical and subcortical regions. In particular, we investigated whether impairments in basic and higher motor control, and the effects induced by dopaminergic treatment are due to connectivity changes in (i) the mesial premotor loop comprising the supplementary motor area; (ii) the lateral premotor loop comprising lateral premotor cortex; and (iii) cortico-subcortical interactions. At the behavioural level, we observed a marked slowing of movement preparation and selection when patients were internally as opposed to externally cued. Preserved performance during external cueing was associated with enhanced connectivity between prefrontal cortex and lateral premotor cortex OFF medication, compatible with a context-dependent compensatory role of the lateral premotor loop in the hypodopaminergic state. Dopaminergic medication significantly improved finger tapping speed in patients, which correlated with a drug-induced coupling increase of prefrontal cortex with the supplementary motor area, i.e. the mesial premotor loop. In addition, only in the finger tapping condition, patients ON medication showed enhanced excitatory influences exerted by cortical premotor regions and the thalamus upon the putamen. In conclusion, the amelioration of bradykinesia by dopaminergic medication seems to be driven by enhanced connectivity within the mesial

  6. Network-Dependent Modulation of COMT and DRD2 Polymorphisms in Healthy Young Adults

    PubMed Central

    Zhao, Fangshi; Zhang, Xuejun; Qin, Wen; Liu, Feng; Wang, Qiuhui; Xu, Qiang; Wang, Junping; Yu, Chunshui

    2015-01-01

    Nonlinear modulation of the dopamine signaling on brain functions can be estimated by the interaction effects of dopamine-related genetic variations. We aimed to explore the interaction effects of COMT rs4680 and DRD2 rs1076560 on intra-network connectivity using independent component analysis. In 250 young healthy adults, we identified 11 meaningful resting-state networks (RSNs), including the salience, visual, auditory, default-mode, sensorimotor, attention and frontoparietal networks. A two-way analysis of covariance was used to investigate COMT×DRD2 interactions on intra-network connectivity in each network, controlling for age, gender and education. Significant COMT×DRD2 interaction was found in intra-network connectivity in the left medial prefrontal cortex of the anterior default-mode network, in the right dorsolateral frontal cortex of the right dorsal attention network, and in the left dorsal anterior cingulate cortex of the salience network. Post hoc tests revealed that these interactions were driven by the differential effects of DRD2 genotypes on intra-network connectivity in different COMT genotypic subgroups. Moreover, even in the same COMT subgroup, the modulation effects of DRD2 on intra-network connectivity were different across RSNs. These findings suggest a network-dependent modulation of the DA-related genetic variations on intra-network connectivity. PMID:26642826

  7. Predicting Fault Prone Modules by the Dempster-Shafer Belief Networks

    PubMed Central

    Guo, Lan; Cukic, Bojan; Singh, Harshinder

    2015-01-01

    This paper describes a novel methodology for predicting fault prone modules. The methodology is based on Dempster-Shafer (D-S) belief networks. Our approach consists of three steps: First, building the Dempster-Shafer network by the induction algorithm; Second, selecting the predictors (attributes) by the logistic procedure; Third, feeding the predictors describing the modules of the current project into the inducted Dempster-Shafer network and identifying fault prone modules. We applied this methodology to a NASA dataset. The prediction accuracy of our methodology is higher than that achieved by logistic regression or discriminant analysis on the same dataset. PMID:26120284

  8. Direct DPSK modulation of chirp-managed laser as cost-effective downstream transmitter for symmetrical 10-Gbit/s WDM PONs.

    PubMed

    Le, Quang Trung; Emsia, Ali; Briggmann, Dieter; Küppers, Franko

    2012-12-10

    This paper proposes the use of chirp-managed lasers (CML) as cost-effective downstream (DS) transmitters for next generation access networks. As the laser bandwidth is as high as 10 GHz, the CML could be directly modulated at 10 Gbit/s for downstream transmission in future wavelength division multiplexing passive optical networks (WDM PON). The laser adiabatic chirp, which is the main drawback limiting the transmission performance of directly modulated lasers, is now utilized to generate phase-shift keying (PSK) modulation format by direct modulation. At the user premise, the wavelength reuse technique based on reflective colorless upstream transmitter is applied. The optical network unit (ONU) reflects and orthogonally remodulates the received light with upstream data. A full-duplex transmission with symmetrical 10-Gbit/s bandwidth is demonstrated. Bit-error-rate measurement showed that optical power budgets of 29 dB at BER of 10(-9) or of 36 dB at BER of 10(-3) could be obtained with direct phase-shift-keying modulation of CML which proves that the proposed solution is a viable candidate for future WDM-PONs. PMID:23262890

  9. Nitrogen modulation on plant direct and indirect defenses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Instead of being passively attacked by insect pests, plants possess a myriad of defense mechanisms to protect themselves. These mechanisms function broadly either by directly reducing herbivore fitness (direct plant defense), or by indirectly attracting natural enemies of the herbivores (indirect p...

  10. Facial Sketch Synthesis Using 2D Direct Combined Model-Based Face-Specific Markov Network.

    PubMed

    Tu, Ching-Ting; Chan, Yu-Hsien; Chen, Yi-Chung

    2016-08-01

    A facial sketch synthesis system is proposed, featuring a 2D direct combined model (2DDCM)-based face-specific Markov network. In contrast to the existing facial sketch synthesis systems, the proposed scheme aims to synthesize sketches, which reproduce the unique drawing style of a particular artist, where this drawing style is learned from a data set consisting of a large number of image/sketch pairwise training samples. The synthesis system comprises three modules, namely, a global module, a local module, and an enhancement module. The global module applies a 2DDCM approach to synthesize the global facial geometry and texture of the input image. The detailed texture is then added to the synthesized sketch in a local patch-based manner using a parametric 2DDCM model and a non-parametric Markov random field (MRF) network. Notably, the MRF approach gives the synthesized results an appearance more consistent with the drawing style of the training samples, while the 2DDCM approach enables the synthesis of outcomes with a more derivative style. As a result, the similarity between the synthesized sketches and the input images is greatly improved. Finally, a post-processing operation is performed to enhance the shadowed regions of the synthesized image by adding strong lines or curves to emphasize the lighting conditions. The experimental results confirm that the synthesized facial images are in good qualitative and quantitative agreement with the input images as well as the ground-truth sketches provided by the same artist. The representing power of the proposed framework is demonstrated by synthesizing facial sketches from input images with a wide variety of facial poses, lighting conditions, and races even when such images are not included in the training data set. Moreover, the practical applicability of the proposed framework is demonstrated by means of automatic facial recognition tests. PMID:27244737

  11. Opinion formation of free speech on the directed social network

    NASA Astrophysics Data System (ADS)

    Su, Jiongming; Ma, Hongxu; Liu, Baohong; Li, Qi

    2014-12-01

    A dynamical model with continuous opinion is proposed to study how the speech order and the topology of directed social network affect the opinion formation of free speech. In the model, agents express their opinions one by one with random order (RO) or probability order (PO), other agents paying attentions to the speaking agent, receive provider's opinion, update their opinions and then express their new opinions in their turns. It is proved that with the same agent j repeats its opinion more, other agents who pay their attentions to j and include j's opinion in their confidence level at initial time, will continue approaching j's opinion. Simulation results reveal that on directed scale-free network: (1) the model for PO forms fewer opinion clusters, larger maximum cluster (MC), smaller standard deviation (SD), and needs less waiting time to reach a middle level of consensus than RO; (2) as the parameter of scale-free degree distribution decreases or the confidence level increases, the results often get better for both speech orders; (3) the differences between PO and RO get smaller as the size of network decreases.

  12. 60-GHz Millimeter-wave Over Fiber with Directly Modulated Dual-mode Laser Diode.

    PubMed

    Tsai, Cheng-Ting; Lin, Chi-Hsiang; Lin, Chun-Ting; Chi, Yu-Chieh; Lin, Gong-Ru

    2016-01-01

    A directly modulated dual-mode laser diode (DMLD) with third-order intermodulation distortion (IMD3) suppression is proposed for a 60-GHz millimeter-wave over fiber (MMWoF) architecture, enabling new fiber-wireless communication access to cover 4-km single-mode-fiber (SMF) and 3-m wireless 16-QAM OFDM transmissions. By dual-mode injection-locking, the throughput degradation of the DMLD is mitigated with saturation effect to reduce its threshold, IMD3 power and relative intensity noise to 7.7 mA, -85 dBm and -110.4 dBc/Hz, respectively, providing huge spurious-free dynamic range of 85.8 dB/Hz(2/3). This operation suppresses the noise floor of the DMLD carried QPSK-OFDM spectrum by 5 dB. The optical receiving power is optimized to restrict the power fading effect for improving the bit error rate to 1.9 × 10(-3 )and the receiving power penalty to 1.1 dB. Such DMLD based hybrid architecture for 60-GHz MMW fiber-wireless access can directly cover the current optical and wireless networks for next-generation indoor and short-reach mobile communications. PMID:27297267

  13. 60-GHz Millimeter-wave Over Fiber with Directly Modulated Dual-mode Laser Diode

    PubMed Central

    Tsai, Cheng-Ting; Lin, Chi-Hsiang; Lin, Chun-Ting; Chi, Yu-Chieh; Lin, Gong-Ru

    2016-01-01

    A directly modulated dual-mode laser diode (DMLD) with third-order intermodulation distortion (IMD3) suppression is proposed for a 60-GHz millimeter-wave over fiber (MMWoF) architecture, enabling new fiber-wireless communication access to cover 4-km single-mode-fiber (SMF) and 3-m wireless 16-QAM OFDM transmissions. By dual-mode injection-locking, the throughput degradation of the DMLD is mitigated with saturation effect to reduce its threshold, IMD3 power and relative intensity noise to 7.7 mA, −85 dBm and −110.4 dBc/Hz, respectively, providing huge spurious-free dynamic range of 85.8 dB/Hz2/3. This operation suppresses the noise floor of the DMLD carried QPSK-OFDM spectrum by 5 dB. The optical receiving power is optimized to restrict the power fading effect for improving the bit error rate to 1.9 × 10−3 and the receiving power penalty to 1.1 dB. Such DMLD based hybrid architecture for 60-GHz MMW fiber-wireless access can directly cover the current optical and wireless networks for next-generation indoor and short-reach mobile communications. PMID:27297267

  14. 60-GHz Millimeter-wave Over Fiber with Directly Modulated Dual-mode Laser Diode

    NASA Astrophysics Data System (ADS)

    Tsai, Cheng-Ting; Lin, Chi-Hsiang; Lin, Chun-Ting; Chi, Yu-Chieh; Lin, Gong-Ru

    2016-06-01

    A directly modulated dual-mode laser diode (DMLD) with third-order intermodulation distortion (IMD3) suppression is proposed for a 60-GHz millimeter-wave over fiber (MMWoF) architecture, enabling new fiber-wireless communication access to cover 4-km single-mode-fiber (SMF) and 3-m wireless 16-QAM OFDM transmissions. By dual-mode injection-locking, the throughput degradation of the DMLD is mitigated with saturation effect to reduce its threshold, IMD3 power and relative intensity noise to 7.7 mA, ‑85 dBm and ‑110.4 dBc/Hz, respectively, providing huge spurious-free dynamic range of 85.8 dB/Hz2/3. This operation suppresses the noise floor of the DMLD carried QPSK-OFDM spectrum by 5 dB. The optical receiving power is optimized to restrict the power fading effect for improving the bit error rate to 1.9 × 10‑3 and the receiving power penalty to 1.1 dB. Such DMLD based hybrid architecture for 60-GHz MMW fiber-wireless access can directly cover the current optical and wireless networks for next-generation indoor and short-reach mobile communications.

  15. Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules

    NASA Astrophysics Data System (ADS)

    Menon, Govind; Krishnan, J.

    2016-07-01

    While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

  16. Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules.

    PubMed

    Menon, Govind; Krishnan, J

    2016-07-21

    While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks. PMID:27448907

  17. A biological approach to assembling tissue modules through endothelial capillary network formation.

    PubMed

    Riesberg, Jeremiah J; Shen, Wei

    2015-09-01

    To create functional tissues having complex structures, bottom-up approaches to assembling small tissue modules into larger constructs have been emerging. Most of these approaches are based on chemical reactions or physical interactions at the interface between tissue modules. Here we report a biological assembly approach to integrate small tissue modules through endothelial capillary network formation. When adjacent tissue modules contain appropriate extracellular matrix materials and cell types that support robust endothelial capillary network formation, capillary tubules form and grow across the interface, resulting in assembly of the modules into a single, larger construct. It was shown that capillary networks formed in modules of dense fibrin gels seeded with human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs); adjacent modules were firmly assembled into an integrated construct having a strain to failure of 117 ± 26%, a tensile strength of 2208 ± 83 Pa and a Young's modulus of 2548 ± 574 Pa. Under the same culture conditions, capillary networks were absent in modules of dense fibrin gels seeded with either HUVECs or MSCs alone; adjacent modules disconnected even when handled gently. This biological assembly approach eliminates the need for chemical reactions or physical interactions and their associated limitations. In addition, the integrated constructs are prevascularized, and therefore this bottom-up assembly approach may also help address the issue of vascularization, another key challenge in tissue engineering. PMID:25694020

  18. Wideband phase modulator works directly on carrier. [application of varactor compensated microwave circuit

    NASA Technical Reports Server (NTRS)

    Rippy, R. R.

    1975-01-01

    Multiplier-induced problems related to undesirable effects of the varactor multiplier on the modulation spectrum are eliminated in a modulator circuit which operates directly at the desired output frequency. The principles of operation of the new circuit are discussed and attention is given to requirements for high-Q components and the possibility of linear frequency deviation.

  19. Transcriptionally Regulated Cell Adhesion Network Dictates Distal Tip Cell Directionality

    PubMed Central

    Wong, Ming-Ching; Kennedy, William P.; Schwarzbauer, Jean E.

    2015-01-01

    Background The mechanisms that govern directional changes in cell migration are poorly understood. The migratory paths of two distal tip cells (DTC) determine the U-shape of the C. elegans hermaphroditic gonad. The morphogenesis of this organ provides a model system to identify genes necessary for the DTCs to execute two stereotyped turns. Results Using candidate genes for RNAi knockdown in a DTC-specific strain, we identified two transcriptional regulators required for DTC turning: cbp-1, the CBP/p300 transcriptional coactivator homologue, and let-607, a CREBH transcription factor homologue. Further screening of potential target genes uncovered a network of integrin adhesion-related genes that have roles in turning and are dependent on cbp-1 and let-607 for expression. These genes include src-1/Src kinase, tln-1/talin, pat-2/α integrin and nmy-2, a nonmuscle myosin heavy chain. Conclusions Transcriptional regulation by means of cbp-1 and let-607 is crucial for determining directional changes during DTC migration. These regulators coordinate a gene network that is necessary for integrin-mediated adhesion. Overall, these results suggest that directional changes in cell migration rely on the precise gene regulation of adhesion. PMID:24811939

  20. Signal to Noise Ratios of Pulsed and Sinewave Modulated Direct Detection Lidar for IPDA Measurements

    NASA Technical Reports Server (NTRS)

    Sun, Xiaoli; Abshire, James B.

    2011-01-01

    The signal-to-noise ratios have been derived for IPDA lidar using a direct detection receiver for both pulsed and sinewave laser modulation techniques, and the results and laboratory measurements are presented

  1. RM-SORN: a reward-modulated self-organizing recurrent neural network.

    PubMed

    Aswolinskiy, Witali; Pipa, Gordon

    2015-01-01

    Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain. PMID:25852533

  2. RM-SORN: a reward-modulated self-organizing recurrent neural network

    PubMed Central

    Aswolinskiy, Witali; Pipa, Gordon

    2015-01-01

    Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain. PMID:25852533

  3. Identification of functional modules in a PPI network by clique percolation clustering.

    PubMed

    Zhang, Shihua; Ning, Xuemei; Zhang, Xiang-Sun

    2006-12-01

    Large-scale experiments and data integration have provided the opportunity to systematically analyze and comprehensively understand the topology of biological networks and biochemical processes in cells. Modular architecture which encompasses groups of genes/proteins involved in elementary biological functional units is a basic form of the organization of interacting proteins. Here we apply a graph clustering algorithm based on clique percolation clustering to detect overlapping network modules of a protein-protein interaction (PPI) network. Our analysis of the yeast Sacchromyces cerevisiae suggests that most of the detected modules correspond to one or more experimentally functional modules and half of these annotated modules match well with experimentally determined protein complexes. Our method of analysis can of course be applied to protein-protein interaction data for any species and even other biological networks. PMID:17098476

  4. Different types of laughter modulate connectivity within distinct parts of the laughter perception network.

    PubMed

    Wildgruber, Dirk; Szameitat, Diana P; Ethofer, Thomas; Brück, Carolin; Alter, Kai; Grodd, Wolfgang; Kreifelts, Benjamin

    2013-01-01

    Laughter is an ancient signal of social communication among humans and non-human primates. Laughter types with complex social functions (e.g., taunt and joy) presumably evolved from the unequivocal and reflex-like social bonding signal of tickling laughter already present in non-human primates. Here, we investigated the modulations of cerebral connectivity associated with different laughter types as well as the effects of attention shifts between implicit and explicit processing of social information conveyed by laughter using functional magnetic resonance imaging (fMRI). Complex social laughter types and tickling laughter were found to modulate connectivity in two distinguishable but partially overlapping parts of the laughter perception network irrespective of task instructions. Connectivity changes, presumably related to the higher acoustic complexity of tickling laughter, occurred between areas in the prefrontal cortex and the auditory association cortex, potentially reflecting higher demands on acoustic analysis associated with increased information load on auditory attention, working memory, evaluation and response selection processes. In contrast, the higher degree of socio-relational information in complex social laughter types was linked to increases of connectivity between auditory association cortices, the right dorsolateral prefrontal cortex and brain areas associated with mentalizing as well as areas in the visual associative cortex. These modulations might reflect automatic analysis of acoustic features, attention direction to informative aspects of the laughter signal and the retention of those in working memory during evaluation processes. These processes may be associated with visual imagery supporting the formation of inferences on the intentions of our social counterparts. Here, the right dorsolateral precentral cortex appears as a network node potentially linking the functions of auditory and visual associative sensory cortices with those of the

  5. Infant-Directed Speech Is Modulated by Infant Feedback

    ERIC Educational Resources Information Center

    Smith, Nicholas A.; Trainor, Laurel J.

    2008-01-01

    When mothers engage in infant-directed (ID) speech, their voices change in a number of characteristic ways, including adopting a higher overall pitch. Studies have examined these acoustical cues and have tested infants' preferences for ID speech. However, little is known about how these cues change with maternal sensitivity to infant feedback in…

  6. The second will be first: competition on directed networks

    PubMed Central

    Cencetti, Giulia; Bagnoli, Franco; Di Patti, Francesca; Fanelli, Duccio

    2016-01-01

    Multiple sinks competition is investigated for a walker diffusing on directed complex networks. The asymmetry of the imposed spatial support makes the system non transitive. As a consequence, it is always possible to identify a suitable location for the second absorbing sink that screens at most the flux of agents directed against the first trap, whose position has been preliminarily assigned. The degree of mutual competition between pairs of nodes is analytically quantified through apt indicators that build on the topological characteristics of the hosting graph. Moreover, the positioning of the second trap can be chosen so as to minimize, at the same time, the probability of being in turn shaded by a thirdly added trap. Supervised placing of absorbing traps on a asymmetric disordered and complex graph is hence possible, as follows a robust optimization protocol. This latter is here discussed and successfully tested against synthetic data. PMID:27271996

  7. Teleconnection Paths via Climate Network Direct Link Detection.

    PubMed

    Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

    2015-12-31

    Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales. PMID:26765033

  8. The second will be first: competition on directed networks.

    PubMed

    Cencetti, Giulia; Bagnoli, Franco; Di Patti, Francesca; Fanelli, Duccio

    2016-01-01

    Multiple sinks competition is investigated for a walker diffusing on directed complex networks. The asymmetry of the imposed spatial support makes the system non transitive. As a consequence, it is always possible to identify a suitable location for the second absorbing sink that screens at most the flux of agents directed against the first trap, whose position has been preliminarily assigned. The degree of mutual competition between pairs of nodes is analytically quantified through apt indicators that build on the topological characteristics of the hosting graph. Moreover, the positioning of the second trap can be chosen so as to minimize, at the same time, the probability of being in turn shaded by a thirdly added trap. Supervised placing of absorbing traps on a asymmetric disordered and complex graph is hence possible, as follows a robust optimization protocol. This latter is here discussed and successfully tested against synthetic data. PMID:27271996

  9. The second will be first: competition on directed networks

    NASA Astrophysics Data System (ADS)

    Cencetti, Giulia; Bagnoli, Franco; di Patti, Francesca; Fanelli, Duccio

    2016-06-01

    Multiple sinks competition is investigated for a walker diffusing on directed complex networks. The asymmetry of the imposed spatial support makes the system non transitive. As a consequence, it is always possible to identify a suitable location for the second absorbing sink that screens at most the flux of agents directed against the first trap, whose position has been preliminarily assigned. The degree of mutual competition between pairs of nodes is analytically quantified through apt indicators that build on the topological characteristics of the hosting graph. Moreover, the positioning of the second trap can be chosen so as to minimize, at the same time, the probability of being in turn shaded by a thirdly added trap. Supervised placing of absorbing traps on a asymmetric disordered and complex graph is hence possible, as follows a robust optimization protocol. This latter is here discussed and successfully tested against synthetic data.

  10. Teleconnection Paths via Climate Network Direct Link Detection

    NASA Astrophysics Data System (ADS)

    Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

    2015-12-01

    Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

  11. Very high-capacity short-reach VCSEL systems exploiting multicarrier intensity modulation and direct detection.

    PubMed

    Gatto, Alberto; Argenio, Debora; Boffi, Pierpaolo

    2016-06-13

    Multicarrier intensity modulation of a bandwidth-limited long-wavelength VCSEL is exploited combined to direct detection to achieve very high capacity simple systems for short-reach applications. Tailored FDM subcarriers modulation and allocation allow to match the non-uniform frequency response of the system induced by the direct modulation and detection of the FDM signal and by the uncompensated SSMF propagation, overcoming the VCSEL bandwidth limitations. A whole transported throughput ranging from 34 Gb/s to 25 Gb/s from few hundreds meters to 20 km of SSMF propagation is experimentally demonstrated even by employing a 5-GHz band VCSEL source. PMID:27410296

  12. 10-Gb/s direct modulation of polymer-based tunable external cavity lasers.

    PubMed

    Choi, Byung-Seok; Oh, Su Hwan; Kim, Ki Soo; Yoon, Ki-Hong; Kim, Hyun Soo; Park, Mi-Ran; Jeong, Jong Sool; Kwon, O-Kyun; Seo, Jun-Kyu; Lee, Hak-Kyu; Chung, Yun C

    2012-08-27

    We demonstrate a directly-modulated 10-Gb/s tunable external cavity laser (ECL) fabricated by using a polymer Bragg reflector and a high-speed superluminescent diode (SLD). The tuning range and output power of this ECL are measured to be >11 nm and 2.6 mW (@ 100 mA), respectively. We directly modulate this laser at 10 Gb/s and transmit the modulated signal over 20 km of standard single-mode fiber. The power penalty is measured to be <2.8 dB at the bit-error rate (BER) of 10(-10). PMID:23037087

  13. Increasing Readiness for Self-Directed Learning: A Facilitator's Manual for Ten Self-Directed Learning Group Modules for Adults.

    ERIC Educational Resources Information Center

    Rutland, Adonna M.; Guglielmino, Lucy M.

    This manual was prepared for use by adult education teachers in facilitating a self-directed learning (SDL) group for students based on the modules described in the manual. The SDL group involves 10 sessions with specific objectives and activities for each session. Following an introduction, the manual is organized in five additional sections. The…

  14. Directed assembly of three-dimensional microvascular networks

    NASA Astrophysics Data System (ADS)

    Therriault, Daniel

    Three-dimensional (3-D) microvascular networks with pervasive, interconnected channels less than 300 mum in diameter may find widespread application in microfluidic devices, biotechnology, sensors, and autonomic healing materials. Although microchannel arrays are readily constructed in two-dimensions by photolithographic or soft lithographic techniques, their construction in three-dimensions remains a challenging problem. The development of a microfabrication method to build 3-D microvascular networks based on direct-write assembly is described is this thesis. The method is based on the robotic deposition of a fugitive organic ink to form a free-standing scaffold structure. Secondary infiltration of a structural resin followed by setting of the matrix and removal of the scaffold yields an embedded pervasive network of smooth cylindrical channels (˜10--500 mum) with defined connectivity. Rheological and other material properties studies of fugitive organic ink were performed in order to identify the critical characteristics required for successful deposition of 3-D scaffolds by direct-write assembly. Guided by the results of these studies, several new ink formulations were screened for improved deposition performance. The most successful of these inks (40wt% microcrystalline wax, 60wt% petroleum jelly) showed excellent deposition and had an equilibrium modulus at room temperature (G 'eq ˜ 7.70 kPa 1 Hz) nearly two orders of magnitude higher than the original ink. The optimized ink was used to successfully build thick (i.e., ˜100 layers) scaffold structures at room temperature with negligible time-dependent deformation post-deposition. Secondary infiltration of the resin was accomplished at room temperature while maintaining the scaffold architecture. The optimized ink was also successfully extruded through small micronozzles (1 mum). The construction of 3-D microvascular networks enables microfluidic devices with unparallel geometric complexity. In one example, a

  15. Surface-directed modulation of supramolecular gel properties.

    PubMed

    Angelerou, Maria Galini Faidra; Sabri, Akmal; Creasey, Rhiannon; Angelerou, Polyxeni; Marlow, Maria; Zelzer, Mischa

    2016-03-10

    Supramolecular materials are widely studied and used for a variety of applications; in most applications, these materials are in contact with surfaces of other materials. Whilst much focus has been placed on elucidating factors that affect supramolecular material properties, the influence of the material surface on gel formation is poorly characterised. Here, we demonstrate that surface properties directly affect the fibre architecture and mechanical properties of self-assembled cytidine based gel films. PMID:26960905

  16. Using single side-band modulation for colorless OFDM-WDM access network to alleviate Rayleigh backscattering effects.

    PubMed

    Yeh, Chien-Hung; Chow, Chi-Wai

    2016-05-16

    In this investigation, we demonstrate a new colorless orthogonal-frequency-division-multiplexing (OFDM) wavelength-division-multiplexing passive optical network (WDM-PON) system with Rayleigh backscattering (RB) noise mitigation. Here, only a single laser source at the central office (CO) is needed to produce the downstream signal and distributed continuous-wave (CW) carrier, which will then be modulated at the optical networking unit (ONU) to produce the upstream signal. Single side-band (SSB) modulation is used to wavelength-shift the distributed CW carrier, which will be launched into a reflective semiconductor optical amplifier (RSOA) based ONU for directly modulation of 5.15 Gbps OFDM upstream signal. To avoid the radio-frequency (RF) power fading and chromatic fiber dispersion, the four-band OFDM modulation is proposed to generate a 40 Gbps downstream when a Mach-Zehnder modulator (MZM) with -0.7 chirp parameter is used. Hence, the RB circumvention can be centralized in the CO. Moreover, the signal performances of downstream and upstream are also studied and discussed in this measurement. PMID:27409910

  17. Direct message passing for hybrid Bayesian networks and performance analysis

    NASA Astrophysics Data System (ADS)

    Sun, Wei; Chang, K. C.

    2010-04-01

    Probabilistic inference for hybrid Bayesian networks, which involves both discrete and continuous variables, has been an important research topic over the recent years. This is not only because a number of efficient inference algorithms have been developed and used maturely for simple types of networks such as pure discrete model, but also for the practical needs that continuous variables are inevitable in modeling complex systems. Pearl's message passing algorithm provides a simple framework to compute posterior distribution by propagating messages between nodes and can provides exact answer for polytree models with pure discrete or continuous variables. In addition, applying Pearl's message passing to network with loops usually converges and results in good approximation. However, for hybrid model, there is a need of a general message passing algorithm between different types of variables. In this paper, we develop a method called Direct Message Passing (DMP) for exchanging messages between discrete and continuous variables. Based on Pearl's algorithm, we derive formulae to compute messages for variables in various dependence relationships encoded in conditional probability distributions. Mixture of Gaussian is used to represent continuous messages, with the number of mixture components up to the size of the joint state space of all discrete parents. For polytree Conditional Linear Gaussian (CLG) Bayesian network, DMP has the same computational requirements and can provide exact solution as the one obtained by the Junction Tree (JT) algorithm. However, while JT can only work for the CLG model, DMP can be applied for general nonlinear, non-Gaussian hybrid model to produce approximate solution using unscented transformation and loopy propagation. Furthermore, we can scale the algorithm by restricting the number of mixture components in the messages. Empirically, we found that the approximation errors are relatively small especially for nodes that are far away from

  18. Unraveling the regulatory network in Streptococcus pyogenes: the global response regulator CovR represses rivR directly.

    PubMed

    Roberts, Samantha A; Churchward, Gordon G; Scott, June R

    2007-02-01

    The response regulator CovR acts as a master regulator of virulence in Streptococcus pyogenes by repressing transcription of approximately 15% of the group A streptococcus genome directly or indirectly. We demonstrate that phosphorylated CovR represses transcription of rivR directly by binding to conserved sequences located downstream from the promoter to block procession of RNA polymerase. This establishes the first link in a regulatory network where CovR interacts directly with other proteins that modulate gene expression. PMID:16963575

  19. A periodic network of neurochemical modules in the inferior colliculus.

    PubMed

    Chernock, Michelle L; Larue, David T; Winer, Jeffery A

    2004-02-01

    A new organization has been found in shell nuclei of rat inferior colliculus. Chemically specific modules with a periodic distribution fill about half of layer 2 of external cortex and dorsal cortex. Modules contain clusters of small glutamic acid decarboxylase-positive neurons and large boutons at higher density than in other inferior colliculus subdivisions. The modules are also present in tissue stained for parvalbumin, cytochrome oxidase, nicotinamide adenine dinucleotide phosphate-diaphorase, and acetylcholinesterase. Six to seven bilaterally symmetrical modules extend from the caudal extremity of the external cortex of the inferior colliculus to its rostral pole. Modules are from approximately 800 to 2200 microm long and have areas between 5000 and 40,000 microm2. Modules alternate with immunonegative regions. Similar modules are found in inbred and outbred strains of rat, and in both males and females. They are absent in mouse, squirrel, cat, bat, macaque monkey, and barn owl. Modules are immunonegative for glycine, calbindin, serotonin, and choline acetyltransferase. The auditory cortex and ipsi- and contralateral inferior colliculi project to the external cortex. Somatic sensory influences from the dorsal column nuclei and spinal trigeminal nucleus are the primary ascending sensory input to the external cortex; ascending auditory input to layer 2 is sparse. If the immunopositive modular neurons receive this input, the external cortex could participate in spatial orientation and somatic motor control through its intrinsic and extrinsic projections. PMID:14759566

  20. Multiple Differential Networks Strategy Reveals Carboplatin and Melphalan-Induced Dynamic Module Changes in Retinoblastoma.

    PubMed

    Chen, Cui; Ma, Feng-Wei; Du, Cui-Yun; Wang, Ping

    2016-01-01

    BACKGROUND Retinoblastoma (RB) is the most common malignant tumor of the eye in childhood. The objective of this paper was to investigate carboplatin (CAR)- and melphalan (MEL)-induced dynamic module changes in RB based on multiple (M) differential networks, and to generate systems-level insights into RB progression. MATERIAL AND METHODS To achieve this goal, we constructed M-differential co-expression networks (DCNs), assigned a weight to each edge, and identified seed genes in M DCNs by ranking genes based on their topological features. Starting with seed genes, a module search was performed to explore candidate modules in CAR and MEL condition. M-DMs were detected according to significance evaluations of M-modules, which originated from refinement of candidate modules. Further, we revealed dynamic changes in M-DM activity and connectivity on the basis of significance of Module Connectivity Dynamic Score (MCDS). RESULTS In the present study, M=2, a total of 21 seed genes were obtained. By assessing module search, refinement, and evaluation, we gained 18 2-DMs. Moreover, 3 significant 2-DMs (Module 1, Module 2, and Module 3) with dynamic changes across CAR and MEL condition were determined, and we denoted them as dynamic modules. Module 1 had 27 nodes of which 6 were seed genes and 56 edges. Module 2 was composed of 28 nodes and 54 edges. A total of 28 nodes interacted with 45 edges presented in Module 3. CONCLUSIONS We have identified 3 dynamic modules with changes induced by CAR and MEL in RB, which might give insights in revealing molecular mechanism for RB therapy. PMID:27144687

  1. FPGA-based artificial neural network using CORDIC modules

    NASA Astrophysics Data System (ADS)

    Liddicoat, Albert A.; Slivovsky, Lynne A.; McLenegan, Tim; Heyer, Don

    2006-08-01

    Artificial neural networks have been used in applications that require complex procedural algorithms and in systems which lack an analytical mathematic model. By designing a large network of computing nodes based on the artificial neuron model, new solutions can be developed for computational problems in fields such as image processing and speech recognition. Neural networks are inherently parallel since each neuron, or node, acts as an autonomous computational element. Artificial neural networks use a mathematical model for each node that processes information from other nodes in the same region. The information processing entails computing a weighted average computation followed by a nonlinear mathematical transformation. Some typical artificial neural network applications use the exponential function or trigonometric functions for the nonlinear transformation. Various simple artificial neural networks have been implemented using a processor to compute the output for each node sequentially. This approach uses sequential processing and does not take advantage of the parallelism of a complex artificial neural network. In this work a hardware-based approach is investigated for artificial neural network applications. A Field Programmable Gate Arrays (FPGAs) is used to implement an artificial neuron using hardware multipliers, adders and CORDIC functional units. In order to create a large scale artificial neural network, area efficient hardware units such as CORDIC units are needed. High performance and low cost bit serial CORDIC implementations are presented. Finally, the FPGA resources and the performance of a hardware-based artificial neuron are presented.

  2. ModuleBlast: identifying activated sub-networks within and across species

    PubMed Central

    Zinman, Guy E.; Naiman, Shoshana; O'Dee, Dawn M.; Kumar, Nishant; Nau, Gerard J.; Cohen, Haim Y.; Bar-Joseph, Ziv

    2015-01-01

    Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFκB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein. PMID:25428368

  3. ModuleBlast: identifying activated sub-networks within and across species.

    PubMed

    Zinman, Guy E; Naiman, Shoshana; O'Dee, Dawn M; Kumar, Nishant; Nau, Gerard J; Cohen, Haim Y; Bar-Joseph, Ziv

    2015-02-18

    Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFκB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein. PMID:25428368

  4. Automatic Modulation Recognition Using Wavelet Transform and Neural Networks in Wireless Systems

    NASA Astrophysics Data System (ADS)

    Hassan, K.; Dayoub, I.; Hamouda, W.; Berbineau, M.

    2010-12-01

    Modulation type is one of the most important characteristics used in signal waveform identification. In this paper, an algorithm for automatic digital modulation recognition is proposed. The proposed algorithm is verified using higher-order statistical moments (HOM) of continuous wavelet transform (CWT) as a features set. A multilayer feed-forward neural network trained with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate among different M-ary shift keying modulation schemes and the modulation order without any priori signal information. Pre-processing and features subset selection using principal component analysis is used to reduce the network complexity and to improve the classifier's performance. The proposed algorithm is evaluated through confusion matrix and false recognition probability. The proposed classifier is shown to be capable of recognizing the modulation scheme with high accuracy over wide signal-to-noise ratio (SNR) range over both additive white Gaussian noise (AWGN) and different fading channels.

  5. A Modularity-Based Method Reveals Mixed Modules from Chemical-Gene Heterogeneous Network

    PubMed Central

    Song, Jianglong; Tang, Shihuan; Liu, Xi; Gao, Yibo; Yang, Hongjun; Lu, Peng

    2015-01-01

    For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae. PMID:25927435

  6. An ELMO2-RhoG-ILK network modulates microtubule dynamics

    PubMed Central

    Jackson, Bradley C.; Ivanova, Iordanka A.; Dagnino, Lina

    2015-01-01

    ELMO2 belongs to a family of scaffold proteins involved in phagocytosis and cell motility. ELMO2 can simultaneously bind integrin-linked kinase (ILK) and RhoG, forming tripartite ERI complexes. These complexes are involved in promoting β1 integrin–dependent directional migration in undifferentiated epidermal keratinocytes. ELMO2 and ILK have also separately been implicated in microtubule regulation at integrin-containing focal adhesions. During differentiation, epidermal keratinocytes cease to express integrins, but ERI complexes persist. Here we show an integrin-independent role of ERI complexes in modulation of microtubule dynamics in differentiated keratinocytes. Depletion of ERI complexes by inactivating the Ilk gene in these cells reduces microtubule growth and increases the frequency of catastrophe. Reciprocally, exogenous expression of ELMO2 or RhoG stabilizes microtubules, but only if ILK is also present. Mechanistically, activation of Rac1 downstream from ERI complexes mediates their effects on microtubule stability. In this pathway, Rac1 serves as a hub to modulate microtubule dynamics through two different routes: 1) phosphorylation and inactivation of the microtubule-destabilizing protein stathmin and 2) phosphorylation and inactivation of GSK-3β, which leads to the activation of CRMP2, promoting microtubule growth. At the cellular level, the absence of ERI species impairs Ca2+-mediated formation of adherens junctions, critical to maintaining mechanical integrity in the epidermis. Our findings support a key role for ERI species in integrin-independent stabilization of the microtubule network in differentiated keratinocytes. PMID:25995380

  7. Selective Attention to Semantic and Syntactic Features Modulates Sentence Processing Networks in Anterior Temporal Cortex

    PubMed Central

    Rogalsky, Corianne

    2009-01-01

    Numerous studies have identified an anterior temporal lobe (ATL) region that responds preferentially to sentence-level stimuli. It is unclear, however, whether this activity reflects a response to syntactic computations or some form of semantic integration. This distinction is difficult to investigate with the stimulus manipulations and anomaly detection paradigms traditionally implemented. The present functional magnetic resonance imaging study addresses this question via a selective attention paradigm. Subjects monitored for occasional semantic anomalies or occasional syntactic errors, thus directing their attention to semantic integration, or syntactic properties of the sentences. The hemodynamic response in the sentence-selective ATL region (defined with a localizer scan) was examined during anomaly/error-free sentences only, to avoid confounds due to error detection. The majority of the sentence-specific region of interest was equally modulated by attention to syntactic or compositional semantic features, whereas a smaller subregion was only modulated by the semantic task. We suggest that the sentence-specific ATL region is sensitive to both syntactic and integrative semantic functions during sentence processing, with a smaller portion of this area preferentially involved in the later. This study also suggests that selective attention paradigms may be effective tools to investigate the functional diversity of networks involved in sentence processing. PMID:18669589

  8. Robust criticality of an Ising model on rewired directed networks

    NASA Astrophysics Data System (ADS)

    Lipowski, Adam; Gontarek, Krzysztof; Lipowska, Dorota

    2015-06-01

    We show that preferential rewiring, which is supposed to mimic the behavior of financial agents, changes a directed-network Ising ferromagnet with a single critical point into a model with robust critical behavior. For the nonrewired random graph version, due to a constant number of out-links for each site, we write a simple mean-field-like equation describing the behavior of magnetization; we argue that it is exact and support the claim with extensive Monte Carlo simulations. For the rewired version, this equation is obeyed only at low temperatures. At higher temperatures, rewiring leads to strong heterogeneities, which apparently invalidates mean-field arguments and induces large fluctuations and divergent susceptibility. Such behavior is traced back to the formation of a relatively small core of agents that influence the entire system.

  9. Graph-balancing algorithms for average consensus over directed networks

    NASA Astrophysics Data System (ADS)

    Fan, Yuan; Han, Runzhe; Qiu, Jianbin

    2016-01-01

    Consensus strategies find extensive applications in coordination of robot groups and decision-making of agents. Since balanced graph plays an important role in the average consensus problem and many other coordination problems for directed communication networks, this work explores the conditions and algorithms for the digraph balancing problem. Based on the analysis of graph cycles, we prove that a digraph can be balanced if and only if the null space of its incidence matrix contains positive vectors. Then, based on this result and the corresponding analysis, two weight balance algorithms have been proposed, and the conditions for obtaining a unique balanced solution and a set of analytical results on weight balance problems have been introduced. Then, we point out the relationship between the weight balance problem and the features of the corresponding underlying Markov chain. Finally, two numerical examples are presented to verify the proposed algorithms.

  10. Regulatory module network of basic/helix-loop-helix transcription factors in mouse brain

    PubMed Central

    Li, Jing; Liu, Zijing J; Pan, Yuchun C; Liu, Qi; Fu, Xing; Cooper, Nigel GF; Li, Yixue; Qiu, Mengsheng; Shi, Tieliu

    2007-01-01

    Background The basic/helix-loop-helix (bHLH) proteins are important components of the transcriptional regulatory network, controlling a variety of biological processes, especially the development of the central nervous system. Until now, reports describing the regulatory network of the bHLH transcription factor (TF) family have been scarce. In order to understand the regulatory mechanisms of bHLH TFs in mouse brain, we inferred their regulatory network from genome-wide gene expression profiles with the module networks method. Results A regulatory network comprising 15 important bHLH TFs and 153 target genes was constructed. The network was divided into 28 modules based on expression profiles. A regulatory-motif search shows the complexity and diversity of the network. In addition, 26 cooperative bHLH TF pairs were also detected in the network. This cooperation suggests possible physical interactions or genetic regulation between TFs. Interestingly, some TFs in the network regulate more than one module. A novel cross-repression between Neurod6 and Hey2 was identified, which may control various functions in different brain regions. The presence of TF binding sites (TFBSs) in the promoter regions of their target genes validates more than 70% of TF-target gene pairs of the network. Literature mining provides additional support for five modules. More importantly, the regulatory relationships among selected key components are all validated in mutant mice. Conclusion Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function. It provides a framework for future experimental analyses. PMID:18021424

  11. Transcutaneous spinal direct current stimulation modulates human corticospinal system excitability.

    PubMed

    Bocci, Tommaso; Marceglia, Sara; Vergari, Maurizio; Cognetto, Valeria; Cogiamanian, Filippo; Sartucci, Ferdinando; Priori, Alberto

    2015-07-01

    This study aimed to assess the effects of thoracic anodal and cathodal transcutaneous spinal direct current stimulation (tsDCS) on upper and lower limb corticospinal excitability. Although there have been studies assessing how thoracic tsDCS influences the spinal ascending tract and reflexes, none has assessed the effects of this technique over upper and lower limb corticomotor neuronal connections. In 14 healthy subjects we recorded motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) from abductor hallucis (AH) and hand abductor digiti minimi (ADM) muscles before (baseline) and at different time points (0 and 30 min) after anodal or cathodal tsDCS (2.5 mA, 20 min, T9-T11 level). In 8 of the 14 subjects we also tested the soleus H reflex and the F waves from AH and ADM before and after tsDCS. Both anodal and cathodal tsDCS left the upper limb MEPs and F wave unchanged. Conversely, while leaving lower limb H reflex unchanged, they oppositely affected lower limb MEPs: whereas anodal tsDCS increased resting motor threshold [(mean ± SE) 107.33 ± 3.3% increase immediately after tsDCS and 108.37 ± 3.2% increase 30 min after tsDCS compared with baseline] and had no effects on MEP area and latency, cathodal tsDCS increased MEP area (139.71 ± 12.9% increase immediately after tsDCS and 132.74 ± 22.0% increase 30 min after tsDCS compared with baseline) without affecting resting motor threshold and MEP latency. Our results show that tsDCS induces polarity-specific changes in corticospinal excitability that last for >30 min after tsDCS offset and selectively affect responses in lower limb muscles innervated by lumbar and sacral motor neurons. PMID:25925328

  12. Assessment of absolute added correlative coding in optical intensity modulation and direct detection channels

    NASA Astrophysics Data System (ADS)

    Dong-Nhat, Nguyen; Elsherif, Mohamed A.; Malekmohammadi, Amin

    2016-06-01

    The performance of absolute added correlative coding (AACC) modulation format with direct detection has been numerically and analytically reported, targeting metro data center interconnects. Hereby, the focus lies on the performance of the bit error rate, noise contributions, spectral efficiency, and chromatic dispersion tolerance. The signal space model of AACC, where the average electrical and optical power expressions are derived for the first time, is also delineated. The proposed modulation format was also compared to other well-known signaling, such as on-off-keying (OOK) and four-level pulse-amplitude modulation, at the same bit rate in a directly modulated vertical-cavity surface-emitting laser-based transmission system. The comparison results show a clear advantage of AACC in achieving longer fiber delivery distance due to the higher dispersion tolerance.

  13. Social network modulation of reward-related signals.

    PubMed

    Fareri, Dominic S; Niznikiewicz, Michael A; Lee, Victoria K; Delgado, Mauricio R

    2012-06-27

    Everyday goals and experiences are often shared with others who may hold different places within our social networks. We investigated whether the experience of sharing a reward differs with respect to social network. Twenty human participants played a card guessing game for shared monetary outcomes with three partners: a computer, a confederate (out of network), and a friend (in network). Participants subjectively rated the experience of sharing a reward more positively with their friends than the other partners. Neuroimaging results support participants' subjective reports, as ventral striatal BOLD responses were more robust when sharing monetary gains with a friend as compared to the confederate or computer, suggesting a higher value for sharing with an in-network partner. Interestingly, ratings of social closeness covaried with this activity, resulting in a significant partner × closeness interaction; exploratory analysis showed that only participants reporting higher levels of closeness demonstrated partner-related differences in striatal BOLD response. These results suggest that reward valuation in social contexts is sensitive to distinctions of social network, such that sharing positive experiences with in-network others may carry higher value. PMID:22745503

  14. Hybrid electro-optic plasmonic modulators based on directional coupler switches

    NASA Astrophysics Data System (ADS)

    Zografopoulos, Dimitrios C.; Swillam, Mohamed A.; Shahada, Lamees A.; Beccherelli, Romeo

    2016-04-01

    By breaking the diffraction limit, plasmonics enable the miniaturization of integrated optical signal processing units in a platform compatible with traditional CMOS technology. In such architectures, modulators and switches are essential elements for fast and low-power optical signal processing. This work presents the design of a CMOS-compatible hybrid plasmonic modulator based on directional couplers enhanced with a layer of electro-optic polymer. The modulator shows very broad operating window with low crosstalk values and very small footprint with respect to similar couplers and switches of the silicon photonics platform.

  15. The Psychedelic State Induced by Ayahuasca Modulates the Activity and Connectivity of the Default Mode Network

    PubMed Central

    Palhano-Fontes, Fernanda; Andrade, Katia C.; Tofoli, Luis F.; Santos, Antonio C.; Crippa, Jose Alexandre S.; Hallak, Jaime E. C.; Ribeiro, Sidarta; de Araujo, Draulio B.

    2015-01-01

    The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN. PMID:25693169

  16. Pitx2 modulates a Tbx5-dependent gene regulatory network to maintain atrial rhythm.

    PubMed

    Nadadur, Rangarajan D; Broman, Michael T; Boukens, Bastiaan; Mazurek, Stefan R; Yang, Xinan; van den Boogaard, Malou; Bekeny, Jenna; Gadek, Margaret; Ward, Tarsha; Zhang, Min; Qiao, Yun; Martin, James F; Seidman, Christine E; Seidman, Jon; Christoffels, Vincent; Efimov, Igor R; McNally, Elizabeth M; Weber, Christopher R; Moskowitz, Ivan P

    2016-08-31

    Cardiac rhythm is extremely robust, generating 2 billion contraction cycles during the average human life span. Transcriptional control of cardiac rhythm is poorly understood. We found that removal of the transcription factor gene Tbx5 from the adult mouse caused primary spontaneous and sustained atrial fibrillation (AF). Atrial cardiomyocytes from the Tbx5-mutant mice exhibited action potential abnormalities, including spontaneous depolarizations, which were rescued by chelating free calcium. We identified a multitiered transcriptional network that linked seven previously defined AF risk loci: TBX5 directly activated PITX2, and TBX5 and PITX2 antagonistically regulated membrane effector genes Scn5a, Gja1, Ryr2, Dsp, and Atp2a2 In addition, reduced Tbx5 dose by adult-specific haploinsufficiency caused decreased target gene expression, myocardial automaticity, and AF inducibility, which were all rescued by Pitx2 haploinsufficiency in mice. These results defined a transcriptional architecture for atrial rhythm control organized as an incoherent feed-forward loop, driven by TBX5 and modulated by PITX2. TBX5/PITX2 interplay provides tight control of atrial rhythm effector gene expression, and perturbation of the co-regulated network caused AF susceptibility. This work provides a model for the molecular mechanisms underpinning the genetic implication of multiple AF genome-wide association studies loci and will contribute to future efforts to stratify patients for AF risk by genotype. PMID:27582060

  17. The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

    PubMed

    Palhano-Fontes, Fernanda; Andrade, Katia C; Tofoli, Luis F; Santos, Antonio C; Crippa, Jose Alexandre S; Hallak, Jaime E C; Ribeiro, Sidarta; de Araujo, Draulio B

    2015-01-01

    The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN. PMID:25693169

  18. Stress-response balance drives the evolution of a network module and its host genome

    PubMed Central

    González, Caleb; Ray, Joe Christian J; Manhart, Michael; Adams, Rhys M; Nevozhay, Dmitry; Morozov, Alexandre V; Balázsi, Gábor

    2015-01-01

    Stress response genes and their regulators form networks that underlie drug resistance. These networks often have an inherent tradeoff: their expression is costly in the absence of stress, but beneficial in stress. They can quickly emerge in the genomes of infectious microbes and cancer cells, protecting them from treatment. Yet, the evolution of stress resistance networks is not well understood. Here, we use a two-component synthetic gene circuit integrated into the budding yeast genome to model experimentally the adaptation of a stress response module and its host genome in three different scenarios. In agreement with computational predictions, we find that: (i) intra-module mutations target and eliminate the module if it confers only cost without any benefit to the cell; (ii) intra- and extra-module mutations jointly activate the module if it is potentially beneficial and confers no cost; and (iii) a few specific mutations repeatedly fine-tune the module's noisy response if it has excessive costs and/or insufficient benefits. Overall, these findings reveal how the timing and mechanisms of stress response network evolution depend on the environment. PMID:26324468

  19. Directly executable formal models of middleware for MANET and Cloud Networking and Computing

    NASA Astrophysics Data System (ADS)

    Pashchenko, D. V.; Sadeq Jaafar, Mustafa; Zinkin, S. A.; Trokoz, D. A.; Pashchenko, T. U.; Sinev, M. P.

    2016-04-01

    The article considers some “directly executable” formal models that are suitable for the specification of computing and networking in the cloud environment and other networks which are similar to wireless networks MANET. These models can be easily programmed and implemented on computer networks.

  20. Direct Conversion of Free Space Millimeter Waves to Optical Domain by Plasmonic Modulator Antenna

    PubMed Central

    2015-01-01

    A scheme for the direct conversion of millimeter and THz waves to optical signals is introduced. The compact device consists of a plasmonic phase modulator that is seamlessly cointegrated with an antenna. Neither high-speed electronics nor electronic amplification is required to drive the modulator. A built-in enhancement of the electric field by a factor of 35 000 enables the direct conversion of millimeter-wave signals to the optical domain. This high enhancement is obtained via a resonant antenna that is directly coupled to an optical field by means of a plasmonic modulator. The suggested concept provides a simple and cost-efficient alternative solution to conventional schemes where millimeter-wave signals are first converted to the electrical domain before being up-converted to the optical domain. PMID:26570995

  1. Direct Conversion of Free Space Millimeter Waves to Optical Domain by Plasmonic Modulator Antenna.

    PubMed

    Salamin, Yannick; Heni, Wolfgang; Haffner, Christian; Fedoryshyn, Yuriy; Hoessbacher, Claudia; Bonjour, Romain; Zahner, Marco; Hillerkuss, David; Leuchtmann, Pascal; Elder, Delwin L; Dalton, Larry R; Hafner, Christian; Leuthold, Juerg

    2015-12-01

    A scheme for the direct conversion of millimeter and THz waves to optical signals is introduced. The compact device consists of a plasmonic phase modulator that is seamlessly cointegrated with an antenna. Neither high-speed electronics nor electronic amplification is required to drive the modulator. A built-in enhancement of the electric field by a factor of 35,000 enables the direct conversion of millimeter-wave signals to the optical domain. This high enhancement is obtained via a resonant antenna that is directly coupled to an optical field by means of a plasmonic modulator. The suggested concept provides a simple and cost-efficient alternative solution to conventional schemes where millimeter-wave signals are first converted to the electrical domain before being up-converted to the optical domain. PMID:26570995

  2. Diffusible crosslinkers generate directed forces in microtubule networks.

    PubMed

    Lansky, Zdenek; Braun, Marcus; Lüdecke, Annemarie; Schlierf, Michael; ten Wolde, Pieter Rein; Janson, Marcel E; Diez, Stefan

    2015-03-12

    Cytoskeletal remodeling is essential to eukaryotic cell division and morphogenesis. The mechanical forces driving the restructuring are attributed to the action of molecular motors and the dynamics of cytoskeletal filaments, which both consume chemical energy. By contrast, non-enzymatic filament crosslinkers are regarded as mere friction-generating entities. Here, we experimentally demonstrate that diffusible microtubule crosslinkers of the Ase1/PRC1/Map65 family generate directed microtubule sliding when confined between partially overlapping microtubules. The Ase1-generated forces, directly measured by optical tweezers to be in the piconewton-range, were sufficient to antagonize motor-protein driven microtubule sliding. Force generation is quantitatively explained by the entropic expansion of confined Ase1 molecules diffusing within the microtubule overlaps. The thermal motion of crosslinkers is thus harnessed to generate mechanical work analogous to compressed gas propelling a piston in a cylinder. As confinement of diffusible proteins is ubiquitous in cells, the associated entropic forces are likely of importance for cellular mechanics beyond cytoskeletal networks. PMID:25748652

  3. Identification of network modules by optimization of ratio association.

    PubMed

    Angelini, L; Boccaletti, S; Marinazzo, D; Pellicoro, M; Stramaglia, S

    2007-06-01

    We introduce a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association. This cost function arises when the communities detection problem is described in the probabilistic autoencoder frame. An analogy with kernel k-means methods allows us to develop an efficient optimization algorithm, based on the deterministic annealing scheme. The performance of the proposed method is shown on real data sets and on simulated networks. PMID:17614668

  4. Identification of network modules by optimization of ratio association

    NASA Astrophysics Data System (ADS)

    Angelini, L.; Boccaletti, S.; Marinazzo, D.; Pellicoro, M.; Stramaglia, S.

    2007-06-01

    We introduce a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association. This cost function arises when the communities detection problem is described in the probabilistic autoencoder frame. An analogy with kernel k-means methods allows us to develop an efficient optimization algorithm, based on the deterministic annealing scheme. The performance of the proposed method is shown on real data sets and on simulated networks.

  5. Direct and Propagated Effects of Small Molecules on Protein–Protein Interaction Networks

    PubMed Central

    Cesa, Laura C.; Mapp, Anna K.; Gestwicki, Jason E.

    2015-01-01

    Networks of protein–protein interactions (PPIs) link all aspects of cellular biology. Dysfunction in the assembly or dynamics of PPI networks is a hallmark of human disease, and as such, there is growing interest in the discovery of small molecules that either promote or inhibit PPIs. PPIs were once considered undruggable because of their relatively large buried surface areas and difficult topologies. Despite these challenges, recent advances in chemical screening methodologies, combined with improvements in structural and computational biology have made some of these targets more tractable. In this review, we highlight developments that have opened the door to potent chemical modulators. We focus on how allostery is being used to produce surprisingly robust changes in PPIs, even for the most challenging targets. We also discuss how interfering with one PPI can propagate changes through the broader web of interactions. Through this analysis, it is becoming clear that a combination of direct and propagated effects on PPI networks is ultimately how small molecules re-shape biology. PMID:26380257

  6. Hypnotic modulation of resting state fMRI default mode and extrinsic network connectivity.

    PubMed

    Demertzi, A; Soddu, A; Faymonville, M-E; Bahri, M A; Gosseries, O; Vanhaudenhuyse, A; Phillips, C; Maquet, P; Noirhomme, Q; Luxen, A; Laureys, S

    2011-01-01

    Resting state fMRI (functional magnetic resonance imaging) acquisitions are characterized by low-frequency spontaneous activity in a default mode network (encompassing medial brain areas and linked to self-related processes) and an anticorrelated "extrinsic" system (encompassing lateral frontoparietal areas and modulated via external sensory stimulation). In order to better determine the functional contribution of these networks to conscious awareness, we here sought to transiently modulate their relationship by means of hypnosis. We used independent component analysis (ICA) on resting state fMRI acquisitions during normal wakefulness, under hypnotic state, and during a control condition of autobiographical mental imagery. As compared to mental imagery, hypnosis-induced modulation of resting state fMRI networks resulted in a reduced "extrinsic" lateral frontoparietal cortical connectivity, possibly reflecting a decreased sensory awareness. The default mode network showed an increased connectivity in bilateral angular and middle frontal gyri, whereas its posterior midline and parahippocampal structures decreased their connectivity during hypnosis, supposedly related to an altered "self" awareness and posthypnotic amnesia. In our view, fMRI resting state studies of physiological (e.g., sleep or hypnosis), pharmacological (e.g., sedation or anesthesia), and pathological modulation (e.g., coma or related states) of "intrinsic" default mode and anticorrelated "extrinsic" sensory networks, and their interaction with other cerebral networks, will further improve our understanding of the neural correlates of subjective awareness. PMID:21854971

  7. Cholinergic and serotonergic modulations differentially affect large-scale functional networks in the mouse brain.

    PubMed

    Shah, Disha; Blockx, Ines; Keliris, Georgios A; Kara, Firat; Jonckers, Elisabeth; Verhoye, Marleen; Van der Linden, Annemie

    2016-07-01

    Resting-state functional MRI (rsfMRI) is a widely implemented technique used to investigate large-scale topology in the human brain during health and disease. Studies in mice provide additional advantages, including the possibility to flexibly modulate the brain by pharmacological or genetic manipulations in combination with high-throughput functional connectivity (FC) investigations. Pharmacological modulations that target specific neurotransmitter systems, partly mimicking the effect of pathological events, could allow discriminating the effect of specific systems on functional network disruptions. The current study investigated the effect of cholinergic and serotonergic antagonists on large-scale brain networks in mice. The cholinergic system is involved in cognitive functions and is impaired in, e.g., Alzheimer's disease, while the serotonergic system is involved in emotional and introspective functions and is impaired in, e.g., Alzheimer's disease, depression and autism. Specific interest goes to the default-mode-network (DMN), which is studied extensively in humans and is affected in many neurological disorders. The results show that both cholinergic and serotonergic antagonists impaired the mouse DMN-like network similarly, except that cholinergic modulation additionally affected the retrosplenial cortex. This suggests that both neurotransmitter systems are involved in maintaining integrity of FC within the DMN-like network in mice. Cholinergic and serotonergic modulations also affected other functional networks, however, serotonergic modulation impaired the frontal and thalamus networks more extensively. In conclusion, this study demonstrates the utility of pharmacological rsfMRI in animal models to provide insights into the role of specific neurotransmitter systems on functional networks in neurological disorders. PMID:26195064

  8. Intensity modulation and direct detection quantum key distribution based on quantum noise

    NASA Astrophysics Data System (ADS)

    Ikuta, Takuya; Inoue, Kyo

    2016-01-01

    Quantum key distribution (QKD) has been studied for achieving perfectly secure cryptography based on quantum mechanics. This paper presents a novel QKD scheme that is based on an intensity-modulation and direct-detection system. Two slightly intensity-modulated pulses are sent from a transmitter, and a receiver determines key bits from the directly detected intensity. We analyzed the system performance for two typical eavesdropping methods, a beam splitting attack and an intercept-resend attack, with an assumption that the transmitting and receiving devices are fully trusted. Our brief analysis showed that short- or middle-range QKD systems are achievable with a simple setup.

  9. The segment polarity network is a robust developmental module

    NASA Astrophysics Data System (ADS)

    von Dassow, George; Meir, Eli; Munro, Edwin M.; Odell, Garrett M.

    2000-07-01

    All insects possess homologous segments, but segment specification differs radically among insect orders. In Drosophila, maternal morphogens control the patterned activation of gap genes, which encode transcriptional regulators that shape the patterned expression of pair-rule genes. This patterning cascade takes place before cellularization. Pair-rule gene products subsequently `imprint' segment polarity genes with reiterated patterns, thus defining the primordial segments. This mechanism must be greatly modified in insect groups in which many segments emerge only after cellularization. In beetles and parasitic wasps, for instance, pair-rule homologues are expressed in patterns consistent with roles during segmentation, but these patterns emerge within cellular fields. In contrast, although in locusts pair-rule homologues may not control segmentation, some segment polarity genes and their interactions are conserved. Perhaps segmentation is modular, with each module autonomously expressing a characteristic intrinsic behaviour in response to transient stimuli. If so, evolution could rearrange inputs to modules without changing their intrinsic behaviours. Here we suggest, using computer simulations, that the Drosophila segment polarity genes constitute such a module, and that this module is resistant to variations in the kinetic constants that govern its behaviour.

  10. Temporal modulation of collective cell behavior controls vascular network topology

    PubMed Central

    Kur, Esther; Kim, Jiha; Tata, Aleksandra; Comin, Cesar H; Harrington, Kyle I; Costa, Luciano da F; Bentley, Katie; Gu, Chenghua

    2016-01-01

    Vascular network density determines the amount of oxygen and nutrients delivered to host tissues, but how the vast diversity of densities is generated is unknown. Reiterations of endothelial-tip-cell selection, sprout extension and anastomosis are the basis for vascular network generation, a process governed by the VEGF/Notch feedback loop. Here, we find that temporal regulation of this feedback loop, a previously unexplored dimension, is the key mechanism to determine vascular density. Iterating between computational modeling and in vivo live imaging, we demonstrate that the rate of tip-cell selection determines the length of linear sprout extension at the expense of branching, dictating network density. We provide the first example of a host tissue-derived signal (Semaphorin3E-Plexin-D1) that accelerates tip cell selection rate, yielding a dense network. We propose that temporal regulation of this critical, iterative aspect of network formation could be a general mechanism, and additional temporal regulators may exist to sculpt vascular topology. DOI: http://dx.doi.org/10.7554/eLife.13212.001 PMID:26910011