WorldWideScience

Sample records for networked rh processing

  1. A Network Model of the Periodic Synchronization Process in the Dynamics of Calcium Concentration in GnRH Neurons

    Science.gov (United States)

    2013-01-01

    Mathematical neuroendocrinology is a branch of mathematical neurosciences that is specifically interested in endocrine neurons, which have the uncommon ability of secreting neurohormones into the blood. One of the most striking features of neuroendocrine networks is their ability to exhibit very slow rhythms of neurosecretion, on the order of one or several hours. A prototypical instance is that of the pulsatile secretion pattern of GnRH (gonadotropin releasing hormone), the master hormone controlling the reproductive function, whose origin remains a puzzle issue since its discovery in the seventies. In this paper, we investigate the question of GnRH neuron synchronization on a mesoscopic scale, and study how synchronized events in calcium dynamics can arise from the average electric activity of individual neurons. We use as reference seminal experiments performed on embryonic GnRH neurons from rhesus monkeys, where calcium imaging series were recorded simultaneously in tens of neurons, and which have clearly shown the occurrence of synchronized calcium peaks associated with GnRH pulses, superposed on asynchronous, yet oscillatory individual background dynamics. We design a network model by coupling 3D individual dynamics of FitzHugh–Nagumo type. Using phase-plane analysis, we constrain the model behavior so that it meets qualitative and quantitative specifications derived from the experiments, including the precise control of the frequency of the synchronization episodes. In particular, we show how the time scales of the model can be tuned to fit the individual and synchronized time scales of the experiments. Finally, we illustrate the ability of the model to reproduce additional experimental observations, such as partial recruitment of cells within the synchronization process or the occurrence of doublets of synchronization. PMID:23574739

  2. Investigation of the formation process of photodeposited Rh nanoparticles on TiO2 by in situ time-resolved energy-dispersive XAFS analysis.

    Science.gov (United States)

    Ohyama, Junya; Teramura, Kentaro; Okuoka, Shin-ichi; Yamazoe, Seiji; Kato, Kazuo; Shishido, Tetsuya; Tanaka, Tsunehiro

    2010-09-07

    The photodeposition process of Rh metal nanoparticles on a TiO(2) photocatalyst from RhCl(3) aqueous solution in the presence of methanol as a sacrificial oxidant, which consists of the direct reduction of Rh(3+) ions to Rh metal and the formation of Rh nanoparticles, was uncovered by in situ time-resolved energy-dispersive X-ray absorption fine structure (DXAFS) analysis in a liquid-solid suspension state. The fractions of Rh metal particles and Rh(3+) precursor were estimated by the least-squares fitting of each X-ray absorption near-edge structure (XANES) spectrum by a linear combination of authentic spectra corresponding to Rh(0) and Rh(3+). The fraction of Rh metal linearly increased with photoirradiation time and saturated after 90 min of photoirradiation. The coordination number (Rh-Rh pair) was evaluated by the curve fitting of the Rh-Rh scattering at 2.45 A in the Fourier transforms (FT) of extended XAFS (EXAFS) spectra. The coordination number linearly increased with photoirradiation time and attained a constant value of 10 after 90 min of photoirradiation. This value is lower than that for the Rh foil (12). These suggest the formation of fine Rh metal nanoparticles on TiO(2). In addition, the diminution rate of Rh(3+) as determined by ICP analysis was in good agreement with the increased rates for the fraction of Rh metal particles estimated by XANES spectra and the coordination number (Rh-Rh pair) evaluated by FT-EXAFS spectra. This result strongly supports the fact that electrons generated by charge separation reduce the Rh(3+) precursor to an Rh metal particle at a moment in time and at a constant rate. The Rh particles do not grow in incremental steps, but Rh particles with a uniform size appear one after another on the surface.

  3. Preparation of PtSn/C, PtRu/C, PtRh/C, PtRuRh/C and PtSnRh/C electrocatalysts using an alcohol-reduction process for methanol and ethanol oxidation; Preparacao e caracterizacao de eletrocatalisadores PtRu, PtSn, PtRh, PtRuRh e PtSnRh para oxidacao direta de alcoois em celulas a combustivel tipo PEM utilizando a metodologia da reducao por alcool

    Energy Technology Data Exchange (ETDEWEB)

    Dias, Ricardo Rodrigues

    2009-07-01

    In this work, Pt/C, PtRh (90:10), PtRh/C (50:50), PtSn/C (50:50), PtRu (50:50)/C, PtRuRh/C (50:40:10) and PtSnRh/C (50:40:10) were prepared by an alcohol-reduction process with metal loading of 20 wt.% using H{sub 2}PtCl{sub 6}.6H{sub 2}O (Aldrich), SnCl{sub 2}.2H{sub 2}O (Aldrich),and RhCl{sub 2}.XH{sub 2}O (Aldrich) as metals sources and Vulcan XC72 as support. The electrocatalysts were characterized by EDX, XRD and cyclic voltammetry (CV). The electro-oxidation of ethanol was studied by CV, chronoamperomety at room temperature in acid medium and tests at 100 deg C on a single cell of a direct methanol or ethanol fuel cell. The EDX analysis showed that the metal atomic ratios of the obtained electrocatalysts were similar to the nominal atomic ratios used in the preparation. The diffractograms of electrocatalysts prepared showed four peaks at approximately 2{theta} =40 deg, 47 deg, 67 deg and 82 deg, which are associated with the (111), (200), (220) and (311) planes, respectively, of a face cubic-centered (fcc) structure characteristic of platinum and platinum alloys. The average crystallite sizes using the Scherrer equation and the calculated values were in the range of 2-3 nm. For Pt Sn/C and PtSnRh/C two additional peaks were observed at 2 = 34 deg and 52 deg that were identified as a SnO{sub 2} phase. Pt Sn/C (50:50) and PtSnRh/C (50:40:10) electro catalyst showed the best performance for ethanol oxidation at room temperature. For methanol oxidation at room temperature Pt Ru/C, Pt Sn/C and PtRuRh/C electrocatalysts showed the best performance. Tests at 100 deg C on a single cell of a direct ethanol fuel cell PtSnRh/C showed the best performance, for methanol oxidation PtRuRh/C showed the best performance. (author)

  4. Temporal Sequence of Hemispheric Network Activation during Semantic Processing: A Functional Network Connectivity Analysis

    Science.gov (United States)

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince; Kraut, Michael; Hart, John, Jr.; Pearlson, Godfrey

    2009-01-01

    To explore the temporal sequence of, and the relationship between, the left and right hemispheres (LH and RH) during semantic memory (SM) processing we identified the neural networks involved in the performance of functional MRI semantic object retrieval task (SORT) using group independent component analysis (ICA) in 47 healthy individuals. SORT…

  5. Biological process linkage networks.

    Directory of Open Access Journals (Sweden)

    Dikla Dotan-Cohen

    Full Text Available The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN.We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods.Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes.

  6. Oxidative leaching process with cupric ion in hydrochloric acid media for recovery of Pd and Rh from spent catalytic converters

    Energy Technology Data Exchange (ETDEWEB)

    Nogueira, C.A., E-mail: carlos.nogueira@lneg.pt [Laboratório Nacional de Energia e Geologia, I.P., Campus do Lumiar, 1649-038 Lisboa (Portugal); Paiva, A.P., E-mail: appaiva@fc.ul.pt [Centro de Química e Bioquímica, Departamento de Química e Bioquímica, Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisboa (Portugal); Oliveira, P.C. [Laboratório Nacional de Energia e Geologia, I.P., Campus do Lumiar, 1649-038 Lisboa (Portugal); Costa, M.C., E-mail: mcorada@ualg.pt [Centro de Ciências do Mar, Departamento de Química e Farmácia, Faculdade de Ciências e de Tecnologia, Campus de Gambelas, 8005-139 Faro (Portugal); Costa, A.M. Rosa da, E-mail: amcosta@ualg.pt [Centro de Investigação em Química do Algarve, Departamento de Química e Farmácia, Faculdade de Ciências e de Tecnologia, Campus de Gambelas, 8005-139 Faro (Portugal)

    2014-08-15

    Highlights: • A new leaching process based on Cu{sup 2+}/HCl media for recovering Pd and Rh from spent autocatalytic converters is presented. • Palladium and rhodium were efficiently leached, with attained maximum yields of 95% and 86%, respectively. • Temperature, time, and HCl and Cu{sup 2+} concentrations were found to be significant factors in the leaching of Pd and Rh. - Abstract: The recycling of platinum-group metals from wastes such as autocatalytic converters is getting growing attention due to the scarcity of these precious metals and the market pressure originated by increase of demand in current and emerging applications. Hydrometallurgical treatment of such wastes is an alternative way to the most usual pyrometallurgical processes based on smelter operations. This paper focuses on the development of a leaching process using cupric chloride as oxidising agent, in HCl media, for recovery of palladium and rhodium from a spent catalyst. The chloride media allows the adequate conditions for oxidising and solubilising the metals, as demonstrated by equilibrium calculations based on thermodynamic data. The experimental study of the leaching process revealed that Pd solubilisation is clearly easier than that of Rh. The factors temperature, time, and HCl and Cu{sup 2+} concentrations were significant regarding Pd and Rh leaching, the latter requiring higher factor values to achieve the same results. Leaching yields of 95% Pd and 86% Rh were achieved under optimised conditions (T = 80 °C, t = 4 h, [HCl] = 6 M, [Cu{sup 2+}] = 0.3 M)

  7. First Measurement of the $^{96}$Ru(p,$\\gamma$)$^{97}$Rh Cross Section for the p-Process with a Storage Ring

    CERN Document Server

    Mei, Bo; Bishop, Shawn; Blaum, Klaus; Boretzky, Konstanze; Bosch, Fritz; Brandau, Carsten; Bräuning, Harald; Davinson, Thomas; Dillmann, Iris; Dimopoulou, Christina; Ershova, Olga; Fülöp, Zsolt; Geissel, Hans; Glorius, Jan; Gyürky, György; Heil, Michael; Käppeler, Franz; Kelic-Heil, Aleksandra; Kozhuharov, Christophor; Langer, Christoph; Bleis, Tudi Le; Litvinov, Yuri; Lotay, Gavin; Marganiec, Justyna; Münzenberg, Gottfried; Nolden, Fritz; Petridis, Nikolaos; Plag, Ralf; Popp, Ulrich; Rastrepina, Ganna; Reifarth, René; Riese, Björn; Rigollet, Catherine; Scheidenberger, Christoph; Simon, Haik; Sonnabend, Kerstin; Steck, Markus; Stöhlke, Thomas; Szücs, Tamás; Sümmerer, Klaus; Weber, Günter; Weick, Helmut; Winters, Danyal; Winters, Natalya; Woods, Philip; Zhong, Qiping

    2015-01-01

    This work presents a direct measurement of the $^{96}$Ru($p, \\gamma$)$^{97}$Rh cross section via a novel technique using a storage ring, which opens opportunities for reaction measurements on unstable nuclei. A proof-of-principle experiment was performed at the storage ring ESR at GSI in Darmstadt, where circulating $^{96}$Ru ions interacted repeatedly with a hydrogen target. The $^{96}$Ru($p, \\gamma$)$^{97}$Rh cross section between 9 and 11 MeV has been determined using two independent normalization methods. As key ingredients in Hauser-Feshbach calculations, the $\\gamma$-ray strength function as well as the level density model can be pinned down with the measured ($p, \\gamma$) cross section. Furthermore, the proton optical potential can be optimized after the uncertainties from the $\\gamma$-ray strength function and the level density have been removed. As a result, a constrained $^{96}$Ru($p, \\gamma$)$^{97}$Rh reaction rate over a wide temperature range is recommended for $p$-process network calculations.

  8. Oxidative leaching process with cupric ion in hydrochloric acid media for recovery of Pd and Rh from spent catalytic converters.

    Science.gov (United States)

    Nogueira, C A; Paiva, A P; Oliveira, P C; Costa, M C; da Costa, A M Rosa

    2014-08-15

    The recycling of platinum-group metals from wastes such as autocatalytic converters is getting growing attention due to the scarcity of these precious metals and the market pressure originated by increase of demand in current and emerging applications. Hydrometallurgical treatment of such wastes is an alternative way to the most usual pyrometallurgical processes based on smelter operations. This paper focuses on the development of a leaching process using cupric chloride as oxidising agent, in HCl media, for recovery of palladium and rhodium from a spent catalyst. The chloride media allows the adequate conditions for oxidising and solubilising the metals, as demonstrated by equilibrium calculations based on thermodynamic data. The experimental study of the leaching process revealed that Pd solubilisation is clearly easier than that of Rh. The factors temperature, time, and HCl and Cu(2+) concentrations were significant regarding Pd and Rh leaching, the latter requiring higher factor values to achieve the same results. Leaching yields of 95% Pd and 86% Rh were achieved under optimised conditions (T = 80 °C, t = 4h, [HCl] = 6M, [Cu(2+)] = 0.3M). Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Rh Disease

    Science.gov (United States)

    ... immunoglobulin called Rho(D) immune globulin (brand name RhoGAM®). RhoGAM can prevent your body from producing Rh antibodies ... and future pregnancies won’t get Rh disease. RhoGAM doesn’t work if your body has already ...

  10. Network Dynamics of Innovation Processes

    Science.gov (United States)

    Iacopini, Iacopo; Milojević, Staša; Latora, Vito

    2018-01-01

    We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

  11. Modeling biogeochemical processes in sediments from the Rhône River prodelta area (NW Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    L. Pastor

    2011-05-01

    Full Text Available In situ oxygen microprofiles, sediment organic carbon content, and pore-water concentrations of nitrate, ammonium, iron, manganese, and sulfides obtained in sediments from the Rhône River prodelta and its adjacent continental shelf were used to constrain a numerical diagenetic model. Results showed that (1 the organic matter from the Rhône River is composed of a fraction of fresh material associated to high first-order degradation rate constants (11–33 yr−1; (2 the burial efficiency (burial/input ratio in the Rhône prodelta (within 3 km of the river outlet can be up to 80 %, and decreases to ~20 % on the adjacent continental shelf 10–15 km further offshore; (3 there is a large contribution of anoxic processes to total mineralization in sediments near the river mouth, certainly due to large inputs of fresh organic material combined with high sedimentation rates; (4 diagenetic by-products originally produced during anoxic organic matter mineralization are almost entirely precipitated (>97 % and buried in the sediment, which leads to (5 a low contribution of the re-oxidation of reduced products to total oxygen consumption. Consequently, total carbon mineralization rates as based on oxygen consumption rates and using Redfield stoichiometry can be largely underestimated in such River-dominated Ocean Margins (RiOMar environments.

  12. Substituted Polyacetylenes Prepared with Rh Catalysts: From Linear to Network-Type Conjugated Polymers

    Czech Academy of Sciences Publication Activity Database

    Sedláček, J.; Balcar, Hynek

    2017-01-01

    Roč. 57, č. 1 (2017), s. 31-51 ISSN 1558-3724 Institutional support: RVO:61388955 Keywords : conjugated polymers * polyacetylenes * conjugated polymer networks Subject RIV: CF - Physical ; Theoretical Chemistry OBOR OECD: Physical chemistry Impact factor: 6.459, year: 2016

  13. Rh incompatibility

    Science.gov (United States)

    ... incompatibility can be prevented with the use of RhoGAM. Therefore, prevention remains the best treatment. Treatment of ... their providers during pregnancy. Special immune globulins, called RhoGAM, are now used to prevent RH incompatibility in ...

  14. Synthesis of Pyridobenzazepines Using a One-Pot Rh/Pd-Catalyzed Process.

    Science.gov (United States)

    Lam, Heather; Tsoung, Jennifer; Lautens, Mark

    2017-06-16

    In recent years, our group has been developing multicatalytic reactions for the synthesis of biologically relevant heterocyclic compounds. An efficient dual-metal catalyzed reaction of electron-deficient o-chlorovinylpyridines with o-aminophenylboronic esters to access pyridobenzazepines is described. Combining a RhI-catalyzed arylation followed by a Pd0-catalyzed C-N coupling, in a one-pot procedure, provides a simplified method to access heterocycles without workup and purification after each step. The substrate scope encompasses a variety of N-H and N-alkylated pyridobenzazepine variants with yields up to 93%.

  15. Impact of Materials Processing on Microstructural Evolution and Hydrogen Isotope Storage Properties of Pd-Rh Alloy Powders.

    Energy Technology Data Exchange (ETDEWEB)

    Yee, Joshua K [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-02-01

    Cryomilled Pd - 10Rh was investiga ted as potential solid - state storage material of hydrogen. Pd - 10Rh was first atomized, and then subsequently cryomilled. The cryomilled Pd - 10Rh was then examined using microstructural characterization techniques including op tical microscopy, electron microscopy, and X - ray diffraction. Pd - 10Rh particles were significantly flattened, increasing the apparent surface area. Microstructural refinement was observed in the cryomilled Pd - 10Rh, generating grains at the nanom etric scale through dislocation - based activity. Hydrogen sorption properties were also characterized, generating both capacity as well as kinetics measurements. It was found that the microstructural refinement due to cryomilling did not play a significant role on hyd rogen sorption properties until the smallest grain size (on the order of %7E25 nm) was achieved. Additionally, the increased surface area and other changes in particle morphology were associated with cryomilling changed the kinetics of hydrogen absorption.

  16. Inferring network topology via the propagation process

    CERN Document Server

    Zeng, An

    2013-01-01

    Inferring the network topology from the dynamics is a fundamental problem with wide applications in geology, biology and even counter-terrorism. Based on the propagation process, we present a simple method to uncover the network topology. The numerical simulation on artificial networks shows that our method enjoys a high accuracy in inferring the network topology. We find the infection rate in the propagation process significantly influences the accuracy, and each network is corresponding to an optimal infection rate. Moreover, the method generally works better in large networks. These finding are confirmed in both real social and nonsocial networks. Finally, the method is extended to directed networks and a similarity measure specific for directed networks is designed.

  17. Developmental exposure to ethinylestradiol affects reproductive physiology, the GnRH neuroendocrine network and behaviors in female mouse

    Directory of Open Access Journals (Sweden)

    Lyes eDerouiche

    2015-12-01

    Full Text Available During development, environmental estrogens are able to induce an estrogen mimetic action that may interfere with endocrine and neuroendocrine systems. The present study investigated the effects on the reproductive function in female mice following developmental exposure to pharmaceutical ethinylestradiol (EE2, the most widespread and potent synthetic steroid present in aquatic environments. EE2 was administrated in drinking water at environmentally relevant (ENVIR or pharmacological (PHARMACO doses (0.1 and 1 µg/kg (body weight/day respectively, from embryonic day 10 until postnatal day 40. Our results show that both groups of EE2-exposed females had advanced vaginal opening and shorter estrus cycles, but a normal fertility rate compared to CONTROL females. The hypothalamic population of GnRH neurons was affected by EE2 exposure with a significant increase in the number of perikarya in the preoptic area of the PHARMACO group and a modification in their distribution in the ENVIR group, both associated with a marked decrease in GnRH fibers immunoreactivity in the median eminence. In EE2-exposed females, behavioral tests highlighted a disturbed maternal behavior, a higher lordosis response, a lack of discrimination between gonad-intact and castrated males in sexually experienced females, and an increased anxiety-related behavior. Altogether, these results put emphasis on the high sensitivity of sexually dimorphic behaviors and neuroendocrine circuits to disruptive effects of EDCs.

  18. Social Network Supported Process Recommender System

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

    Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

  19. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...

  20. Process query systems for network security monitoring

    Science.gov (United States)

    Berk, Vincent; Fox, Naomi

    2005-05-01

    In this paper we present the architecture of our network security monitoring infrastructure based on a Process Query System (PQS). PQS offers a new and powerful way of efficiently processing data streams, based on process descriptions that are submitted as queries. In this case the data streams are familiar network sensors, such as Snort, Netfilter, and Tripwire. The process queries describe the dynamics of network attacks and failures, such as worms, multistage attacks, and router failures. Using PQS the task of monitoring enterprise class networks is simplified, offering a priority-based GUI to the security administrator that clearly outlines events that require immediate attention. The PQS-Net system is deployed on an unsecured production network; the system has successfully detected many diverse attacks and failures.

  1. Environmental application of millimetre-scale sponge iron (s-Fe0) particles (IV): New insights into visible light photo-Fenton-like process with optimum dosage of H2O2 and RhB photosensitizers.

    Science.gov (United States)

    Ju, Yongming; Yu, Yunjiang; Wang, Xiaoyan; Xiang, Mingdeng; Li, Liangzhong; Deng, Dongyang; Dionysiou, Dionysios D

    2017-02-05

    In this study, we firstly develop the photo-Fenton-like system with millimetric sponge iron (s-Fe0), H2O2, visible light (vis, λ≥420nm) and rhodamine B (RhB), and present a comprehensive study concerning the mechanism. Thus, we investigate (1) the adsorption of RhB onto s-Fe0, (2) the photo-Fenton-like removal of RhB over iron oxides generated from the corrosion of s-Fe0, (3) the homogeneous photo-Fenton removal of RhB over Fe2+ or Fe3+, (4) the Fe3+-RhB complexes, and (5) the photo-Fenton-like removal of tetrabromobisphenol A (TBBPA). The results show that neither the adsorption process over s-Fe0 nor the photo-Fenton-like process over FeOOH, Fe3O4 and Fe2O3, achieved efficient removal of RhB. For comparison, in homogeneous photo-Fenton process, the presence of Fe3+ ions, rather than Fe2+ ions, effectively eliminated RhB. Furthermore, the UV-vis spectra showing new absorbance at∼285nm indicate the complexes of RhB and Fe3+ ions, adopting vis photons to form excited state and further eject one electron via ligand-to-metal charge-transfer to activate H2O2. Additionally, efficient TBBPA removal was obtained only in the presence of RhB. Accordingly, the s-Fe0- based photo-Fenton-like process assisted with dyestuff wastewater is promising for removing a series of persistent organic pollutants. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Signal processing devices and networks

    Science.gov (United States)

    Graveline, S. W.

    1985-02-01

    According to an axiom employed with respect to electronic warfare (EW) behavior, system effectiveness increases directly with the amount of information recovered from an intercepted signal. The evolution in EW signal processing capability has proceeded accordingly. After an initiation of EW systems as broadband receivers, the most significant advance was related to the development of digital instantaneous frequency measurement (DIFM) devices. The use of such devices provides significant improvements regarding signal identification and RF measurement to within a few MHz. An even more accurate processing device, the digital RF memory (DRFM), allows frequency characterization to within a few Hz. This invention was made in response to the need to process coherent pulse signals. Attention is given to the generic EW system, the modern EW system, and the generic receiver function for a modern EW system showing typical output signals.

  3. Synthesis and Design of Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2012-01-01

    In this contribution, we propose an integrated business and engineering framework for synthesis and design of processing networks under uncertainty. In our framework, an adapted formulation of the transhipment problem is integrated with a superstructure, leading to a Stochastic Mixed Integer Non...... Linear Program (sMINLP), which is solved to determine simultaneously the optimal strategic and tactical decisions with respect to the processing network, the material flows, raw material and product portfolio. The framework allows time-effective and robust formulation, solution and analysis of largescale...... synthesis problems in presence of uncertainty parameters, contributing to broaden the range of application of stochastic programming and optimization to real industrial problems. The framework is applied to an industrial case study based on soybean processing, to identify the optimal processing network...

  4. Coevolution of functional flow processing networks

    Science.gov (United States)

    Kaluza, Pablo

    2017-04-01

    We present a study about the construction of functional flow processing networks that produce prescribed output patterns (target functions). The constructions are performed with a process of mutations and selections by an annealing-like algorithm. We consider the coevolution of the prescribed target functions during the optimization processes. We propose three different paths for these coevolutions in order to evolve from a simple initial function to a more complex final one. We compute several network properties during the optimizations by using the different path-coevolutions as mean values over network ensembles. As a function of the number of iterations of the optimization we find a similar behavior like a phase transition in the network structures. This result can be seen clearly in the mean motif distributions of the constructed networks. Coevolution allows to identify that feed-forward loops are responsible for the development of the temporal response of these systems. Finally, we observe that with a large number of iterations the optimized networks present similar properties despite the path-coevolution we employed.

  5. Reconfigurable real-time distributed processing network

    Science.gov (United States)

    Page, S. F.; Seely, R. D.; Hickman, D.

    2011-06-01

    This paper describes a novel real-time image and signal processing network, RONINTM, which facilitates the rapid design and deployment of systems providing advanced geospatial surveillance and situational awareness capability. RONINTM is a distributed software architecture consisting of multiple agents or nodes, which can be configured to implement a variety of state-of-the-art computer vision and signal processing algorithms. The nodes operate in an asynchronous fashion and can run on a variety of hardware platforms, thus providing a great deal of scalability and flexibility. Complex algorithmic configuration chains can be assembled using an intuitive graphical interface in a plug-and- play manner. RONINTM has been successfully exploited for a number of applications, ranging from remote event detection to complex multiple-camera real-time 3D object reconstruction. This paper describes the motivation behind the creation of the network, the core design features, and presents details of an example application. Finally, the on-going development of the network is discussed, which is focussed on dynamic network reconfiguration. This allows to the network to automatically adapt itself to node or communications failure by intelligently re-routing network communications and through adaptive resource management.

  6. Cascading Edge Failures: A Dynamic Network Process

    CERN Document Server

    Zhang, June

    2016-01-01

    This paper considers the dynamics of edges in a network. The Dynamic Bond Percolation (DBP) process models, through stochastic local rules, the dependence of an edge $(a,b)$ in a network on the states of its neighboring edges. Unlike previous models, DBP does not assume statistical independence between different edges. In applications, this means for example that failures of transmission lines in a power grid are not statistically independent, or alternatively, relationships between individuals (dyads) can lead to changes in other dyads in a social network. We consider the time evolution of the probability distribution of the network state, the collective states of all the edges (bonds), and show that it converges to a stationary distribution. We use this distribution to study the emergence of global behaviors like consensus (i.e., catastrophic failure or full recovery of the entire grid) or coexistence (i.e., some failed and some operating substructures in the grid). In particular, we show that, depending on...

  7. Sustainable Process Networks for CO2 Conversion

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Kongpanna, P.; Pavarajam, V.

    that are thermodynamically feasible, including the co-reactants, catalysts, operating conditions and reactions. Research has revealed that there are a variety of reactions that fulfill the aforementioned criteria. The products that are formed fall into categories: fuels, bulk chemicals and specialty chemicals. While fuels...... the emissions is the conversion of CO2 into useful products, such as methanol [3]. In this work, through a computer-aided framework for process network synthesis-design, a network of feasible conversion processes that all use emitted CO2 is investigated. CO2 is emitted into the environment from various sources......, such as methanol (MeOH) have the largest market, this network will include a variety of thermodynamically feasible conversion paths [4]. From reviews of work previously done, there are ranges of possible products that are formed from CO2 and another co-reactant directly. Methanol, dimethyl ether, dimethyl...

  8. Criminal Network Investigation: Processes, Tools, and Techniques

    DEFF Research Database (Denmark)

    Petersen, Rasmus Rosenqvist

    intelligence products that can be disseminated to their customers. Investigators deal with an increasing amount of information from a variety of sources, especially the Internet, all of which are important to their analysis and decision making process. But information abundance is far from the only or most...... a target-centric process model (acquisition, synthesis, sense-making, dissemination, cooperation) encouraging and supporting an iterative and incremental evolution of the criminal network across all five investigation processes. The first priority of the process model is to address the problems of linear...

  9. Aqueous hydrodechlorination of 4-chlorophenol over an Rh/reduced graphene oxide synthesized by a facile one-pot solvothermal process under mild conditions

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Yanlin [Chemical Synthesis and Pollution Control, Key Laboratory of Sichuan Province, College of Chemistry and Chemical Industry, China West Normal University, Nanchong 637002 (China); Fan, Guangyin, E-mail: fanguangyin@cwnu.edu.cn [Chemical Synthesis and Pollution Control, Key Laboratory of Sichuan Province, College of Chemistry and Chemical Industry, China West Normal University, Nanchong 637002 (China); Wang, Chenyu [Department of Chemistry, State University of New York at Binghamton, Binghamton, NY 13902 (United States)

    2014-06-01

    Graphical abstract: The Rh nanoparticles/reduced graphene oxide (Rh NPs/RGO) nanocatalyst synthesized by a solvothermal technique showed high activity and stability for the hydrodechlorination of 4-chlorophenol under mild conditions. - Highlights: • Rh/RGO was synthesized through a one-pot polyol reduction of GO and RhCl{sub 3}. • Complete HDC of 4-chlorophenol was obtained in aqueous phase without any additive. • The Rh/RGO exhibited an excellent catalytic performance for HDC reaction. - Abstract: Reduced graphene oxide (RGO) supported rhodium nanoparticles (Rh-NPs/RGO) was synthesized through one-pot polyol co-reduction of graphene oxide (GO) and rhodium chloride. The catalytic property of Rh-NPs/RGO was investigated for the aqueous phase hydrodechlorination (HDC) of 4-chlorophenol (4-CP). A complete conversion of 4-CP into high valued products of cyclohexanone (selectivity: 23.2%) and cyclohexanol (selectivity: 76.8%) was successfully achieved at 303 K and balloon hydrogen pressure in a short reaction time of 50 min when 1.5 g/L of 4-CP was introduced. By comparing with Rh-NPs deposited on the other supports, Rh-NPs/RGO delivered the highest initial rate (111.4 mmol/g{sub Rh} min) for 4-CP HDC reaction under the identical conditions. The substantial catalytic activity of Rh-NPs/RGO can be ascribed to the small and uniform particle size of Rh (average particle size was 1.7 ± 0.14 nm) on the surface of the RGO sheets and an electron-deficient state of Rh in the catalyst as a result of the strong interaction between the active sites and the surface function groups of RGO.

  10. Interacting Social Processes on Interconnected Networks.

    Directory of Open Access Journals (Sweden)

    Lucila G Alvarez-Zuzek

    Full Text Available We propose and study a model for the interplay between two different dynamical processes -one for opinion formation and the other for decision making- on two interconnected networks A and B. The opinion dynamics on network A corresponds to that of the M-model, where the state of each agent can take one of four possible values (S = -2,-1, 1, 2, describing its level of agreement on a given issue. The likelihood to become an extremist (S = ±2 or a moderate (S = ±1 is controlled by a reinforcement parameter r ≥ 0. The decision making dynamics on network B is akin to that of the Abrams-Strogatz model, where agents can be either in favor (S = +1 or against (S = -1 the issue. The probability that an agent changes its state is proportional to the fraction of neighbors that hold the opposite state raised to a power β. Starting from a polarized case scenario in which all agents of network A hold positive orientations while all agents of network B have a negative orientation, we explore the conditions under which one of the dynamics prevails over the other, imposing its initial orientation. We find that, for a given value of β, the two-network system reaches a consensus in the positive state (initial state of network A when the reinforcement overcomes a crossover value r*(β, while a negative consensus happens for r βc. We develop an analytical mean-field approach that gives an insight into these regimes and shows that both dynamics are equivalent along the crossover line (r*, β*.

  11. Social Networks in Software Process Improvement

    DEFF Research Database (Denmark)

    Nielsen, Peter Axel; Tjørnehøj, Gitte

    2010-01-01

    Software process improvement in small organisation is often problematic and communication and knowledge sharing is more informal. To improve software processes we need to understand how they communicate and share knowledge. In this article have studied the company SmallSoft through action research....... In the action research we have applied the framework of social network analysis and we show this can be used to understand the underlying structures of communication and knowledge sharing between software developers and managers. We show in detail how the analysis can be done and how the management can utilise...... the findings. From this we conclude that social network analysis was a useful framework together with accompanying tools and techniques. Copyright © 2009 John Wiley & Sons, Ltd....

  12. Tensegrity II. How structural networks influence cellular information processing networks

    Science.gov (United States)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  13. Materials, Processes, and Environmental Engineering Network

    Science.gov (United States)

    White, Margo M.

    1993-01-01

    Attention is given to the Materials, Processes, and Environmental Engineering Network (MPEEN), which was developed as a central holding facility for materials testing information generated by the Materials and Processes Laboratory of NASA-Marshall. It contains information from other NASA centers and outside agencies, and also includes the NASA Environmental Information System (NEIS) and Failure Analysis Information System (FAIS) data. The data base is NEIS, which is accessible through MPEEN. Environmental concerns are addressed regarding materials identified by the NASA Operational Environment Team (NOET) to be hazardous to the environment. The data base also contains the usage and performance characteristics of these materials.

  14. The GnRH Pulse Generator

    Directory of Open Access Journals (Sweden)

    Pasha Grachev

    2016-12-01

    Full Text Available The pulsatile secretion of hormones is an efficient way of coding a large variety of chemical messages. The GnRH pulse pattern determines which gonadotropin is released when and at what concentration, prescribing a detailed set of instructions to the gonads that produce changes in the steroid hormone milieu. Although GnRH neurons possess some inherent rhythmicity, they are diffusely situated within the hypothalamus and in isolation are only capable of generating physiologically irrelevant messages, hence a synchronization module exists upstream. The identity of the neural unit comprising the GnRH pulse generator is now generally thought to include KNDy neurons in the arcuate nucleus. These neurons coexpress the neuropeptides kisspeptin, neurokinin B and dynorphin A, as well as other transmitters, and are in intimate contact with the GnRH network. The GnRH pulse generator’s function is the precise control of GnRH neuron excitability, coordinated activation, stimulation of neurosecretory events, modulation of gene transcription and the mediation of the negative feedback effect of gonadal steroids. Additionally, the GnRH pulse generator is an ideal venue for the integration of various sensory and homeostatic cues that regulate reproductive functions. In this chapter we provide a historical perspective of the elegant science that sparked interest in the central mechanisms underlying the functions of the reproductive system, explain how hypotheses surrounding GnRH pulse generation have evolved and describe the current state of knowledge within the dynamic field of GnRH pulse generator research.

  15. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  16. Materials, processes, and environmental engineering network

    Science.gov (United States)

    White, Margo M.

    1993-01-01

    The Materials, Processes, and Environmental Engineering Network (MPEEN) was developed as a central holding facility for materials testing information generated by the Materials and Processes Laboratory. It contains information from other NASA centers and outside agencies, and also includes the NASA Environmental Information System (NEIS) and Failure Analysis Information System (FAIS) data. Environmental replacement materials information is a newly developed focus of MPEEN. This database is the NASA Environmental Information System, NEIS, which is accessible through MPEEN. Environmental concerns are addressed regarding materials identified by the NASA Operational Environment Team, NOET, to be hazardous to the environment. An environmental replacement technology database is contained within NEIS. Environmental concerns about materials are identified by NOET, and control or replacement strategies are formed. This database also contains the usage and performance characteristics of these hazardous materials. In addition to addressing environmental concerns, MPEEN contains one of the largest materials databases in the world. Over 600 users access this network on a daily basis. There is information available on failure analysis, metals and nonmetals testing, materials properties, standard and commercial parts, foreign alloy cross-reference, Long Duration Exposure Facility (LDEF) data, and Materials and Processes Selection List data.

  17. Rh Factor Blood Test

    Science.gov (United States)

    ... June 3, 2015. Rh factor blood test About Advertisement Mayo Clinic does not endorse companies or products. ... a Job Site Map About This Site Twitter Facebook Google YouTube Pinterest Mayo Clinic is a not- ...

  18. Gonadotropin-Releasing Hormone (GnRH) Receptor Structure and GnRH Binding.

    Science.gov (United States)

    Flanagan, Colleen A; Manilall, Ashmeetha

    2017-01-01

    Gonadotropin-releasing hormone (GnRH) regulates reproduction. The human GnRH receptor lacks a cytoplasmic carboxy-terminal tail but has amino acid sequence motifs characteristic of rhodopsin-like, class A, G protein-coupled receptors (GPCRs). This review will consider how recent descriptions of X-ray crystallographic structures of GPCRs in inactive and active conformations may contribute to understanding GnRH receptor structure, mechanism of activation and ligand binding. The structures confirmed that ligands bind to variable extracellular surfaces, whereas the seven membrane-spanning α-helices convey the activation signal to the cytoplasmic receptor surface, which binds and activates heterotrimeric G proteins. Forty non-covalent interactions that bridge topologically equivalent residues in different transmembrane (TM) helices are conserved in class A GPCR structures, regardless of activation state. Conformation-independent interhelical contacts account for a conserved receptor protein structure and their importance in the GnRH receptor structure is supported by decreased expression of receptors with mutations of residues in the network. Many of the GnRH receptor mutations associated with congenital hypogonadotropic hypogonadism, including the Glu2.53(90) Lys mutation, involve amino acids that constitute the conserved network. Half of the ~250 intramolecular interactions in GPCRs differ between inactive and active structures. Conformation-specific interhelical contacts depend on amino acids changing partners during activation. Conserved inactive conformation-specific contacts prevent receptor activation by stabilizing proximity of TM helices 3 and 6 and a closed G protein-binding site. Mutations of GnRH receptor residues involved in these interactions, such as Arg3.50(139) of the DRY/S motif or Tyr7.53(323) of the N/DPxxY motif, increase or decrease receptor expression and efficiency of receptor coupling to G protein signaling, consistent with the native residues

  19. Neural network training as a dissipative process.

    Science.gov (United States)

    Gori, Marco; Maggini, Marco; Rossi, Alessandro

    2016-09-01

    This paper analyzes the practical issues and reports some results on a theory in which learning is modeled as a continuous temporal process driven by laws describing the interactions of intelligent agents with their own environment. The classic regularization framework is paired with the idea of temporal manifolds by introducing the principle of least cognitive action, which is inspired by the related principle of mechanics. The introduction of the counterparts of the kinetic and potential energy leads to an interpretation of learning as a dissipative process. As an example, we apply the theory to supervised learning in neural networks and show that the corresponding Euler-Lagrange differential equations can be connected to the classic gradient descent algorithm on the supervised pairs. We give preliminary experiments to confirm the soundness of the theory. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Competing dynamical processes on two interacting networks

    CERN Document Server

    Alvarez-Zuzek, L G; Braunstein, L A; Vazquez, F

    2016-01-01

    We propose and study a model for the competition between two different dynamical processes, one for opinion formation and the other for decision making, on two interconnected networks. The networks represent two interacting social groups, the society and the Congress. An opinion formation process takes place on the society, where the opinion S of each individual can take one of four possible values (S=-2,-1,1,2), describing its level of agreement on a given issue, from totally against (S=-2) to totally in favor (S=2). The dynamics is controlled by a reinforcement parameter r, which measures the ratio between the likelihood to become an extremist or a moderate. The dynamics of the Congress is akin to that of the Abrams-Strogatz model, where congressmen can adopt one of two possible positions, to be either in favor (+) or against (-) the issue. The probability that a congressman changes his decision is proportional to the fraction of interacting neighbors that hold the opposite opinion raised to a power $\\beta$...

  1. Discovery of Information Diffusion Process in Social Networks

    Science.gov (United States)

    Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

    Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

  2. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  3. Survey on Neural Networks Used for Medical Image Processing.

    Science.gov (United States)

    Shi, Zhenghao; He, Lifeng; Suzuki, Kenji; Nakamura, Tsuyoshi; Itoh, Hidenori

    2009-02-01

    This paper aims to present a review of neural networks used in medical image processing. We classify neural networks by its processing goals and the nature of medical images. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of neural network application for medical image processing and an outlook for the future research are also discussed. By this survey, we try to answer the following two important questions: (1) What are the major applications of neural networks in medical image processing now and in the nearby future? (2) What are the major strengths and weakness of applying neural networks for solving medical image processing tasks? We believe that this would be very helpful researchers who are involved in medical image processing with neural network techniques.

  4. Synthesis and Design of Integrated Process and Water Networks

    DEFF Research Database (Denmark)

    Handani, Zainatul B.; Quaglia, Alberto; Gani, Rafiqul

    2015-01-01

    possible options with respect to the topology of the process and water networks, leading to Mixed Integer Non Linear Programming (MINLP) problem. A solution strategy to solve the multi-network problem accounts explicitly the interactions between the networks by selecting suitable technologies in order...... to transform raw materials into products and produce clean water to be reused in the process at the early stage of design. Since the connection between the process network and the wastewater treatment network is not a straight forward connection, a new converter interval is introduced in order to convert......This work presents the development of a systematic framework for a simultaneous synthesis and design of process and water networks using the superstructure-based optimization approach. In this framework, a new superstructure combining both networks is developed by attempting to consider all...

  5. Learning Processes of Layered Neural Networks

    OpenAIRE

    Fujiki, Sumiyoshi; FUJIKI, Nahomi, M.

    1995-01-01

    A positive reinforcement type learning algorithm is formulated for a stochastic feed-forward neural network, and a learning equation similar to that of the Boltzmann machine algorithm is obtained. By applying a mean field approximation to the same stochastic feed-forward neural network, a deterministic analog feed-forward network is obtained and the back-propagation learning rule is re-derived.

  6. Survey on Neural Networks Used for Medical Image Processing

    OpenAIRE

    Shi, Zhenghao; He, Lifeng; Suzuki, Kenji; Nakamura, Tsuyoshi; Itoh, Hidenori

    2009-01-01

    This paper aims to present a review of neural networks used in medical image processing. We classify neural networks by its processing goals and the nature of medical images. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of neural network application for medical image processing and an outlook for the future research are also discussed. By this survey, we try to answer the following two important questions: (1) Wh...

  7. Pre-processing for Triangulation of Probabilistic Networks

    NARCIS (Netherlands)

    Bodlaender, H.L.; Koster, A.M.C.A.; Eijkhof, F. van den; Gaag, L.C. van der

    2001-01-01

    The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a networks graph. In this paper, we show that pre-processing can help in finding good triangulations for probabilistic networks, that is, triangulations with a minimal maximum

  8. Nanostructured FeRh in metallic and insulating films

    Energy Technology Data Exchange (ETDEWEB)

    Kaeswurm, B.; Jimenez-Villacorta, F. [Department of Chemical Engineering, Northeastern University, Boston, MA 02115 (United States); Bennett, S.P. [Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115 (United States); Heiman, D. [Department of Physics, Northeastern University, Boston, MA 02115 (United States); Lewis, L.H. [Department of Chemical Engineering, Northeastern University, Boston, MA 02115 (United States)

    2014-03-15

    The formation of nanostructured FeRh in nonmagnetic metallic and insulating matrices is investigated and correlated with their structural and magnetic properties, with the goal of clarifying synthesis–structure–property relationships in confined geometries. Films containing FeRh with Al{sub 2}O{sub 3} and Cu matrices were deposited on Si substrates using RF sputtering and then annealed up to 1073 K to form chemically-ordered FeRh particles with the B2 structure. FeRh nanostructures formed within the refractory Al{sub 2}O{sub 3} matrix are rounded in shape and have a smaller average particle size of 60 nm, compared to the more irregular nanostructures obtained in the metallic Cu–FeRh sample with a larger average particle size ∼150 nm. The different morphology of the two samples is explained in terms of the dissimilar properties of the matrices, and opens pathways for potential control of the fabrication of FeRh nanostructures. Keywords: FeRh, Magneto caloric effect, Magneto structural transition, Ferromagnetism. - Highlights: • First report of attainment of films of FeRh nanostructures on insulating and conducting matrices. • FeRh nanostructures on insulating matrix (Al{sub 2}O{sub 3}) show a more homogeneous size distribution and spherical shape. • Insight provided on aspects of chemical ordering in FeRh as a function of synthesis and processing.

  9. Data Farming Process and Initial Network Analysis Capabilities

    Directory of Open Access Journals (Sweden)

    Gary Horne

    2016-01-01

    Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.

  10. Optimizing information processing in neuronal networks beyond critical states.

    Science.gov (United States)

    Ferraz, Mariana Sacrini Ayres; Melo-Silva, Hiago Lucas Cardeal; Kihara, Alexandre Hiroaki

    2017-01-01

    Critical dynamics have been postulated as an ideal regime for neuronal networks in the brain, considering optimal dynamic range and information processing. Herein, we focused on how information entropy encoded in spatiotemporal activity patterns may vary in critical networks. We employed branching process based models to investigate how entropy can be embedded in spatiotemporal patterns. We determined that the information capacity of critical networks may vary depending on the manipulation of microscopic parameters. Specifically, the mean number of connections governed the number of spatiotemporal patterns in the networks. These findings are compatible with those of the real neuronal networks observed in specific brain circuitries, where critical behavior is necessary for the optimal dynamic range response but the uncertainty provided by high entropy as coded by spatiotemporal patterns is not required. With this, we were able to reveal that information processing can be optimized in neuronal networks beyond critical states.

  11. Optimizing information processing in neuronal networks beyond critical states.

    Directory of Open Access Journals (Sweden)

    Mariana Sacrini Ayres Ferraz

    Full Text Available Critical dynamics have been postulated as an ideal regime for neuronal networks in the brain, considering optimal dynamic range and information processing. Herein, we focused on how information entropy encoded in spatiotemporal activity patterns may vary in critical networks. We employed branching process based models to investigate how entropy can be embedded in spatiotemporal patterns. We determined that the information capacity of critical networks may vary depending on the manipulation of microscopic parameters. Specifically, the mean number of connections governed the number of spatiotemporal patterns in the networks. These findings are compatible with those of the real neuronal networks observed in specific brain circuitries, where critical behavior is necessary for the optimal dynamic range response but the uncertainty provided by high entropy as coded by spatiotemporal patterns is not required. With this, we were able to reveal that information processing can be optimized in neuronal networks beyond critical states.

  12. Cyclotron production of the 105,106mAg, 100,101Pd, 100,101m,105Rh radionuclides by natPd(p,x) nuclear processes

    Science.gov (United States)

    Khandaker, Mayeen Uddin; Kim, Kwangsoo; Kim, Guinyun; Otuka, Naohiko

    2010-07-01

    Production cross-sections of the 105g+m,106mAg, 100,101Pd, and 100g+m,101m,105g+mRh radionuclides through proton-induced reactions on natural palladium were measured up to 40 MeV by using a stacked-foil activation technique combined with high-resolution γ-ray spectrometry. The production cross-sections of 101Pd and 100g+m,105g+mRh radionuclides have been reported here for the first time from the natPd(p,x) nuclear processes. The present results are compared with the available literature values as well as the theoretical data calculated by the TALYS and the ALICE-IPPE computer codes. A quantitative comparison of the present results with the theoretical data has also been done with several deviation factor definitions. Optimal production pathways of the therapeutic 105gRh radionuclide with minimal contamination using cyclotrons are discussed elaborately.

  13. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels...

  14. Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

    DEFF Research Database (Denmark)

    Qu, Qiang; Liu, Siyuan; Jensen, Christian S.

    2014-01-01

    The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...

  15. The impact of a network split on cascading failure processes

    OpenAIRE

    Sloothaak, Fiona; Borst, Sem C.; Zwart, Bert

    2017-01-01

    Cascading failure models are typically used to capture the phenomenon where failures possibly trigger further failures in succession, causing knock-on effects. In many networks this ultimately leads to a disintegrated network where the failure propagation continues independently across the various components. In order to gain insight in the impact of network splitting on cascading failure processes, we extend a well-established cascading failure model for which the number of failures obeys a ...

  16. Advanced information processing system: Input/output network management software

    Science.gov (United States)

    Nagle, Gail; Alger, Linda; Kemp, Alexander

    1988-01-01

    The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

  17. Physiology of the gonadotrophin-releasing hormone (GnRH) neurone: studies from embryonic GnRH neurones.

    Science.gov (United States)

    Constantin, S

    2011-06-01

    Gonadotrophin-releasing hormone (GnRH)-secreting neurones are the final output of the central nervous system driving fertility in all mammals. Although it has been known for decades that the efficiency of communication between the hypothalamus and the pituitary depends on the pulsatile profile of GnRH secretion, how GnRH neuronal activity is patterned to generate pulses at the median eminence is unknown. To date, the scattered distribution of the GnRH cell bodies remains the main limitation to assessing the cellular events that could lead to pulsatile GnRH secretion. Taking advantage of the unique developmental feature of GnRH neurones, the nasal explant model allows primary GnRH neurones to be maintained within a micro-network where pulsatile secretion is preserved and where individual cellular activity can be monitored simultaneously across the cell population. This review summarises the data obtained from work using this in vitro model, and brings some insights into GnRH cellular physiology. © 2011 The Author. Journal of Neuroendocrinology © 2011 Blackwell Publishing Ltd.

  18. RH Packaging Program Guidance

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions LLC

    2008-01-12

    The purpose of this program guidance document is to provide the technical requirements for use, operation, inspection, and maintenance of the RH-TRU 72-B Waste Shipping Package (also known as the "RH-TRU 72-B cask") and directly related components. This document complies with the requirements as specified in the RH-TRU 72-B Safety Analysis Report for Packaging (SARP), and Nuclear Regulatory Commission (NRC) Certificate of Compliance (C of C) 9212. If there is a conflict between this document and the SARP and/or C of C, the C of C shall govern. The C of C states: "...each package must be prepared for shipment and operated in accordance with the procedures described in Chapter 7.0, Operating Procedures, of the application." It further states: "...each package must be tested and maintained in accordance with the procedures described in Chapter 8.0, Acceptance Tests and Maintenance Program of the Application." Chapter 9.0 of the SARP tasks the Waste Isolation Pilot Plant (WIPP) Management and Operating (M&O) Contractor with assuring the packaging is used in accordance with the requirements of the C of C. Because the packaging is NRC-approved, users need to be familiar with Title 10 Code of Federal Regulations (CFR) §71.8, "Deliberate Misconduct." Any time a user suspects or has indications that the conditions of approval in the C of C were not met, the U.S. Department of Energy (DOE) Carlsbad Field Office (CBFO) shall be notified immediately. The CBFO will evaluate the issue and notify the NRC if required.In accordance with 10 CFR Part 71, "Packaging and Transportation of Radioactive Material," certificate holders, packaging users, and contractors or subcontractors who use, design, fabricate, test, maintain, or modify the packaging shall post copies of (1) 10 CFR Part 21, "Reporting of Defects and Noncompliance," regulations, (2) Section 206 of the Energy Reorganization Act of 1974, and (3) NRC Form 3, Notice to Employees. These documents must be posted in a

  19. A network perspective on the processes of empowered organizations.

    Science.gov (United States)

    Neal, Zachary P

    2014-06-01

    Organizational empowerment is a multi-faceted concept that involves processes occurring both within and between organizations that facilitate achievement of their goals. This paper takes a closer look at three interorganizational processes that lead to empowered organizations: building alliances, getting the word out, and capturing others' attention. These processes are located within the broader nomological network of empowerment and organizational empowerment, and are linked to particular patterns of interorganizational relationships that facilitate organizations' ability to engage in them. A new network-based measure, γ-centrality, is introduced to capture the particular network structure associated with each process to be assessed. It is demonstrated first in a hypothetical organizational network, then applied to take a closer look at organizational empowerment in the context of a coordinating council composed of human service agencies. The paper concludes with a discussion of the implications of relationships between these processes, and the potential for unintended consequences in the empowerment of organizations.

  20. Contagion processes on urban bus networks in Indian cities

    CERN Document Server

    Chatterjee, Atanu; Jagannathan, Krishna

    2015-01-01

    Bus transportation is considered as one of the most convenient and cheapest modes of public transportation in Indian cities. Due to their cost-effectiveness and wide reachability, they help a significant portion of the human population in cities to reach their destinations every day. Although from a transportation point of view they have numerous advantages over other modes of public transportation, they also pose a serious threat of contagious diseases spreading throughout the city. The presence of numerous local spatial constraints makes the process and extent of epidemic spreading extremely difficult to predict. Also, majority of the studies have focused on the contagion processes on scale-free network topologies whereas, spatially-constrained real-world networks such as, bus networks exhibit a wide-spectrum of network topology. Therefore, we aim in this study to understand this complex dynamical process of epidemic outbreak and information diffusion on the bus networks for six different Indian cities usin...

  1. Pre-Processing Rules for Triangulation of Probabilistic Networks

    NARCIS (Netherlands)

    Bodlaender, H.L.; Koster, A.M.C.A.; Eijkhof, F. van den

    2003-01-01

    The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a network’s graph. In this paper, we show that pre-processing can help in finding good triangulations for probabilistic networks, that is, triangulations with a minimal maximum clique

  2. Towards Device-Independent Information Processing on General Quantum Networks

    Science.gov (United States)

    Lee, Ciarán M.; Hoban, Matty J.

    2018-01-01

    The violation of certain Bell inequalities allows for device-independent information processing secure against nonsignaling eavesdroppers. However, this only holds for the Bell network, in which two or more agents perform local measurements on a single shared source of entanglement. To overcome the practical constraints that entangled systems can only be transmitted over relatively short distances, large-scale multisource networks have been employed. Do there exist analogs of Bell inequalities for such networks, whose violation is a resource for device independence? In this Letter, the violation of recently derived polynomial Bell inequalities will be shown to allow for device independence on multisource networks, secure against nonsignaling eavesdroppers.

  3. Environmental application of millimetre-scale sponge iron (s-Fe{sup 0}) particles (IV): New insights into visible light photo-Fenton-like process with optimum dosage of H{sub 2}O{sub 2} and RhB photosensitizers

    Energy Technology Data Exchange (ETDEWEB)

    Ju, Yongming, E-mail: juyongming@scies.org [South China Institute of Environmental Sciences, Ministry of Environmental Protection (MEP), Guangzhou 510655 (China); Innovative Laboratory for Environmental Functional Materials and Environmental Applications of Microwave Irradiation, South China Subcenter of State Environmental Dioxin Monitoring Center, Guangzhou 510655 (China); Guangdong Key Laboratory of Agro-Environment Integrated Control, South China Institute of Environmental Sciences, Guangzhou 510655 (China); Yu, Yunjiang, E-mail: yuyunjiang@scies.org [South China Institute of Environmental Sciences, Ministry of Environmental Protection (MEP), Guangzhou 510655 (China); Wang, Xiaoyan; Xiang, Mingdeng; Li, Liangzhong [South China Institute of Environmental Sciences, Ministry of Environmental Protection (MEP), Guangzhou 510655 (China); Deng, Dongyang [South China Institute of Environmental Sciences, Ministry of Environmental Protection (MEP), Guangzhou 510655 (China); Innovative Laboratory for Environmental Functional Materials and Environmental Applications of Microwave Irradiation, South China Subcenter of State Environmental Dioxin Monitoring Center, Guangzhou 510655 (China); Guangdong Key Laboratory of Agro-Environment Integrated Control, South China Institute of Environmental Sciences, Guangzhou 510655 (China); Dionysiou, Dionysios D., E-mail: dionysios.d.dionysiou@uc.edu [Environmental Engineering and Science Program, Department of Biomedical, Chemical and Environmental Engineering (DBCEE), University of Cincinnati, Cincinnati, Ohio, 45221-0012 (United States)

    2017-02-05

    Highlights: • Synergistic action of Rhodamine B (RhB), visible light, H{sub 2}O{sub 2} and s-Fe{sup 0} is essential. • The complexes of RhB and Fe{sup 3+} eject one electron via ligand-to-metal charge-transfer. • RhB assists the photo-Fenton-like removal of tetrabromobisphenol A (TBBPA). - Abstract: In this study, we firstly develop the photo-Fenton-like system with millimetric sponge iron (s-Fe{sup 0}), H{sub 2}O{sub 2}, visible light (vis, λ ≥ 420 nm) and rhodamine B (RhB), and present a comprehensive study concerning the mechanism. Thus, we investigate (1) the adsorption of RhB onto s-Fe{sup 0}, (2) the photo-Fenton-like removal of RhB over iron oxides generated from the corrosion of s-Fe{sup 0}, (3) the homogeneous photo-Fenton removal of RhB over Fe{sup 2+} or Fe{sup 3+}, (4) the Fe{sup 3+}-RhB complexes, and (5) the photo-Fenton-like removal of tetrabromobisphenol A (TBBPA). The results show that neither the adsorption process over s-Fe{sup 0} nor the photo-Fenton-like process over FeOOH, Fe{sub 3}O{sub 4} and Fe{sub 2}O{sub 3}, achieved efficient removal of RhB. For comparison, in homogeneous photo-Fenton process, the presence of Fe{sup 3+} ions, rather than Fe{sup 2+} ions, effectively eliminated RhB. Furthermore, the UV–vis spectra showing new absorbance at ∼ 285 nm indicate the complexes of RhB and Fe{sup 3+} ions, adopting vis photons to form excited state and further eject one electron via ligand-to-metal charge-transfer to activate H{sub 2}O{sub 2}. Additionally, efficient TBBPA removal was obtained only in the presence of RhB. Accordingly, the s-Fe{sup 0}– based photo-Fenton-like process assisted with dyestuff wastewater is promising for removing a series of persistent organic pollutants.

  4. Contagion processes on the static and activity driven coupling networks

    CERN Document Server

    Lei, Yanjun; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

    2015-01-01

    The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity driven coupling (SADC) network model to characterize the coupling between static (strong) structure and dynamic (weak) structure. Epidemic thresholds of SIS and SIR model are studied on SADC both analytically and numerically with various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that weak structure...

  5. Parallel Distributed Processing Theory in the Age of Deep Networks.

    Science.gov (United States)

    Bowers, Jeffrey S

    2017-12-01

    Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

  6. Hybrid digital signal processing and neural networks applications in PWRs

    Energy Technology Data Exchange (ETDEWEB)

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  7. Neural PID Control Strategy for Networked Process Control

    Directory of Open Access Journals (Sweden)

    Jianhua Zhang

    2013-01-01

    Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

  8. RH Packaging Program Guidance

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions LLC

    2006-11-07

    The purpose of this program guidance document is to provide the technical requirements for use, operation, inspection, and maintenance of the RH-TRU 72-B Waste Shipping Package and directly related components. This document complies with the requirements as specified in the RH-TRU 72-B Safety Analysis Report for Packaging (SARP), and Nuclear Regulatory Commission (NRC) Certificate of Compliance (C of C) 9212. If there is a conflict between this document and the SARP and/or C of C, the C of C shall govern. The C of C states: "...each package must be prepared for shipment and operated in accordance with the procedures described in Chapter 7.0, Operating Procedures, of the application." It further states: "...each package must be tested and maintained in accordance with the procedures described in Chapter 8.0, Acceptance Tests and Maintenance Program of the Application." Chapter 9.0 of the SARP tasks the Waste Isolation Pilot Plant (WIPP) Management and Operating (M&O) Contractor with assuring the packaging is used in accordance with the requirements of the C of C. Because the packaging is NRC-approved, users need to be familiar with 10 Code of Federal Regulations (CFR) §71.8, "Deliberate Misconduct." Any time a user suspects or has indications that the conditions of approval in the C of C were not met, the U.S. Department of Energy (DOE) Carlsbad Field Office (CBFO) shall be notified immediately. CBFO will evaluate the issue and notify the NRC if required. In accordance with 10 CFR Part 71, "Packaging and Transportation of Radioactive Material," certificate holders, packaging users, and contractors or subcontractors who use, design, fabricate, test, maintain, or modify the packaging shall post copies of (1) 10 CFR Part 21, "Reporting of Defects and Noncompliance," regulations, (2) Section 206 of the Energy Reorganization Act of 1974, and (3) NRC Form 3, Notice to Employees. These documents must be posted in a conspicuous location where the activities subject to

  9. RH Packaging Program Guidance

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions, LLC

    2003-08-25

    The purpose of this program guidance document is to provide technical requirements for use, operation, inspection, and maintenance of the RH-TRU 72-B Waste Shipping Package and directly related components. This document complies with the requirements as specified in the RH-TRU 72-B Safety Analysis Report for Packaging (SARP), and Nuclear Regulatory Commission (NRC) Certificate of Compliance (C of C) 9212. If there is a conflict between this document and the SARP and/or C of C, the SARP and/or C of C shall govern. The C of C states: ''...each package must be prepared for shipment and operated in accordance with the procedures described in Chapter 7.0, ''Operating Procedures,'' of the application.'' It further states: ''...each package must be tested and maintained in accordance with the procedures described in Chapter 8.0, ''Acceptance Tests and Maintenance Program of the Application.'' Chapter 9.0 of the SARP tasks the Waste Isolation Pilot Plant (WIPP) Management and Operating (M&O) contractor with assuring the packaging is used in accordance with the requirements of the C of C. Because the packaging is NRC approved, users need to be familiar with 10 CFR {section} 71.11, ''Deliberate Misconduct.'' Any time a user suspects or has indications that the conditions of approval in the C of C were not met, the Carlsbad Field Office (CBFO) shall be notified immediately. CBFO will evaluate the issue and notify the NRC if required. This document details the instructions to be followed to operate, maintain, and test the RH-TRU 72-B packaging. This Program Guidance standardizes instructions for all users. Users shall follow these instructions. Following these instructions assures that operations are safe and meet the requirements of the SARP. This document is available on the Internet at: ttp://www.ws/library/t2omi/t2omi.htm. Users are responsible for ensuring they are using the current

  10. Developing an intelligence analysis process through social network analysis

    Science.gov (United States)

    Waskiewicz, Todd; LaMonica, Peter

    2008-04-01

    Intelligence analysts are tasked with making sense of enormous amounts of data and gaining an awareness of a situation that can be acted upon. This process can be extremely difficult and time consuming. Trying to differentiate between important pieces of information and extraneous data only complicates the problem. When dealing with data containing entities and relationships, social network analysis (SNA) techniques can be employed to make this job easier. Applying network measures to social network graphs can identify the most significant nodes (entities) and edges (relationships) and help the analyst further focus on key areas of concern. Strange developed a model that identifies high value targets such as centers of gravity and critical vulnerabilities. SNA lends itself to the discovery of these high value targets and the Air Force Research Laboratory (AFRL) has investigated several network measures such as centrality, betweenness, and grouping to identify centers of gravity and critical vulnerabilities. Using these network measures, a process for the intelligence analyst has been developed to aid analysts in identifying points of tactical emphasis. Organizational Risk Analyzer (ORA) and Terrorist Modus Operandi Discovery System (TMODS) are the two applications used to compute the network measures and identify the points to be acted upon. Therefore, the result of leveraging social network analysis techniques and applications will provide the analyst and the intelligence community with more focused and concentrated analysis results allowing them to more easily exploit key attributes of a network, thus saving time, money, and manpower.

  11. Structure and catalytic reactivity of Rh oxides

    DEFF Research Database (Denmark)

    Gustafson, J.; Westerström, R.; Resta, A.

    2009-01-01

    Using a combination of experimental and theoretical techniques, we show that a thin RhO2 surface oxide film forms prior to the bulk Rh2O3 corundum oxide on all close-packed single crystal Rh surfaces. Based on previous reports, we argue that the RhO2 surface oxide also forms on vicinal Rh surface...

  12. IJA: An Efficient Algorithm for Query Processing in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dong Hwa Kim

    2011-01-01

    Full Text Available One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm.

  13. IJA: An Efficient Algorithm for Query Processing in Sensor Networks

    Science.gov (United States)

    Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

    2011-01-01

    One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm. PMID:22319375

  14. The GnRH receptor and the response of gonadotrope cells to GnRH pulse frequency code. A story of an atypical adaptation of cell function relying on a lack of receptor homologous desensitization.

    Directory of Open Access Journals (Sweden)

    Christian Bleux

    2010-01-01

    Full Text Available Brain control of the reproductive system is mediated through hypothalamic gonadotropin-releasing hormone (GnRH which activates specific receptors (GnRHR present at the surface of the pituitary gonadotropes to trigger secretion of the two gonadotropins LH and FSH. A unique feature of this system is the high dependence on the secretion mode of GnRH, which is basically pulsatile but undergoes considerable fluctuations in pulse frequency pattern in response to endogenous or external factors. How the physiological fluctuations of GnRH secretion that orchestrate normal reproduction are decoded by the gonadotrope cell machinery to ultimately control gonadotropin release and/or subunit gene transcription has been the subject of intensive studies during the past decades. Surprisingly, the mammalian GnRHR is unique among G protein-coupled receptor family as it lacks the carboxy-terminal tail usually involved in classical endocytotic process. Accordingly, it does not desensitize properly and internalizes very poorly. Both this atypical intrinsic property and post-receptor events may thus contribute to decode the GnRH signal. This includes the participation of a network of signaling pathways that differently respond to GnRH together with a growing amount of genes differentially sensitive to pulse frequency. Among these are two pairs of genes, the transcription factors EGR-1 and NAB, and the regulatory factors activin and follistatin, that function as intracellular autoregulatory feedback loops controlling respectively LHbeta and FSHbeta gene expression and hence, LH and FSH synthesis. Pituitary gonadotropes thus represent a unique model of cells functionally adapted to respond to a considerably fluctuating neuroendocrine stimulation, from short individual pulses to sustained GnRH as observed at the proestrus of ovarian cycle. Altogether, the data emphasize the adaptative reciprocal complementarity of hypothalamic GnRH neurones and pituitary gonadotropes to

  15. Metabolic network modularity arising from simple growth processes.

    Science.gov (United States)

    Takemoto, Kazuhiro

    2012-09-01

    Metabolic networks consist of linked functional components, or modules. The mechanism underlying metabolic network modularity is of great interest not only to researchers of basic science but also to those in fields of engineering. Previous studies have suggested a theoretical model, which proposes that a change in the evolutionary goal (system-specific purpose) increases network modularity, and this hypothesis was supported by statistical data analysis. Nevertheless, further investigation has uncovered additional possibilities that might explain the origin of network modularity. In this work we propose an evolving network model without tuning parameters to describe metabolic networks. We demonstrate, quantitatively, that metabolic network modularity can arise from simple growth processes, independent of the change in the evolutionary goal. Our model is applicable to a wide range of organisms and appears to suggest that metabolic network modularity can be more simply determined than previously thought. Nonetheless, our proposition does not serve to contradict the previous model; it strives to provide an insight from a different angle in the ongoing efforts to understand metabolic evolution, with the hope of eventually achieving the synthetic engineering of metabolic networks.

  16. Quantum Information Processing with Modular Networks

    Science.gov (United States)

    Crocker, Clayton; Inlek, Ismail V.; Hucul, David; Sosnova, Ksenia; Vittorini, Grahame; Monroe, Chris

    2015-05-01

    Trapped atomic ions are qubit standards for the production of entangled states in quantum information science and metrology applications. Trapped ions can exhibit very long coherence times, external fields can drive strong local interactions via phonons, and remote qubits can be entangled via photons. Transferring quantum information across spatially separated ion trap modules for a scalable quantum network architecture relies on the juxtaposition of both phononic and photonic buses. We report the successful combination of these protocols within and between two ion trap modules on a unit structure of this architecture where the remote entanglement generation rate exceeds the experimentally measured decoherence rate. Additionally, we report an experimental implementation of a technique to maintain phase coherence between spatially and temporally distributed quantum gate operations, a crucial prerequisite for scalability. Finally, we discuss our progress towards addressing the issue of uncontrolled cross-talk between photonic qubits and memory qubits by implementing a second ion species, Barium, to generate the photonic link. This work is supported by the ARO with funding from the IARPA MQCO program, the DARPA Quiness Program, the ARO MURI on Hybrid Quantum Circuits, the AFOSR MURI on Quantum Transduction, and the NSF Physics Frontier Center at JQI.

  17. Designer networks for time series processing

    DEFF Research Database (Denmark)

    Svarer, C; Hansen, Lars Kai; Larsen, Jan

    1993-01-01

    The conventional tapped-delay neural net may be analyzed using statistical methods and the results of such analysis can be applied to model optimization. The authors review and extend efforts to demonstrate the power of this strategy within time series processing. They attempt to design compact...

  18. SOCIAL NETWORKS AS A MEANS OF LEARNING PROCESS

    Directory of Open Access Journals (Sweden)

    T. Arhipova

    2015-02-01

    Full Text Available This paper presents an analysis of social networks in terms of their possible use in the education system. The integration of new information and communication technologies with the technologies of learning is gradually changing the concept of modern education and promotes educational environment focused on the interests and personal development, achievement of her current levels of education, internationalization and increasing access to educational resources, creating conditions for mobility of students and teachers improving the quality of education and the formation of a single educational space. The peculiarity of such an environment is to provide creative research activity of the teacher and students in the learning process. Network services provide the means by which students can act as active creators of media content. The paper presents the results of a study of the advantages and disadvantages of using web communities in the educational process. Articulated pedagogical conditions of the effective organization of educational process in the virtual learning environment using social networks. The experience of the use of social networks in the learning process of the university. Such networking technologies, such as forums, blogs, wikis, educational portals and automated systems for distance learning, having undoubted didactic and methodological advantages, inferior social networks in terms of involving users in their communication space, as well as compliance with the intellectual, creative and social needs.

  19. Performance PtSnRh electrocatalysts supported on carbon-Sb{sub 2}O{sub 5}.SbO{sub 2} for the electro-oxidation of ethanol, prepared by an alcohol-reduction process; Desempenho de eletrocatalisadores PtSnRh suportados em carbono-Sb{sub 2}O{sub 5}.SnO{sub 2} para a oxidacao eletroquimica do etanol, preparados pelo metodo de reducao por alcool

    Energy Technology Data Exchange (ETDEWEB)

    Castro, Jose Carlos

    2013-07-01

    PtSnRh electrocatalysts supported on carbon-Sb{sub 2}O{sub 5}.SnO{sub 2}, with metal loading of 20 wt%, were prepared by an alcohol-reduction process, using H{sub 2}PtCl{sub 6}.6H{sub 2}O (Aldrich), RhCl{sub 3}.xH{sub 2}O (Aldrich) and SnCl{sub 2}.2H{sub 2}O (Aldrich), as source of metals; Sb{sub 2}O{sub 5}.SnO{sub 2} (ATO) and carbon Vulcan XC72, as support; and ethylene glycol as reducing agent. The electrocatalysts obtained were characterized physically by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The diffractograms showed which PtSnRh/C-ATO electrocatalysts had FCC structure of Pt and Pt alloys, besides several peaks associated with SnO{sub 2} and ATO. The average sizes of crystallites were between 2 and 4 nm. TEM micrographs showed a good distribution of the nanoparticles on the support. The average sizes of particles were between 2 and 3 nm, with good agreement for the average size of the crystallites. The performances of the electrocatalysts were analyzed by electrochemical techniques and in real conditions of operation using single direct ethanol fuel cell. In the chronoamperometry at 50 deg C, the electrocatalysts with carbon (85 wt%) and ATO (15 wt%) support, showed the best activity, and the atomic proportions which achieved the best results were PtSnRh(70:25:05) e (90:05:05). PtSnRh(70:25:05)/85C+15ATO electrocatalysts showed the best performance in a direct ethanol fuel cell. (author)

  20. Exploratory use of a Bayesian network process for translating ...

    African Journals Online (AJOL)

    Water resource management is complex, and should ideally be a co-operative, stakeholder-driven problem-solving process. Bayesian networks (BNs) are one participatory tool being increasingly used to facilitate this process. The upper Mgeni catchment in the province of KwaZulu-Natal, South Africa, is a key water ...

  1. Cortical network architecture for context processing in primate brain.

    Science.gov (United States)

    Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

    2015-09-29

    Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

  2. Social networks in nursing work processes: an integrative literature review

    OpenAIRE

    Ana Cláudia Mesquita; Cristina Mara Zamarioli; Francine Lima Fulquini; Emilia Campos de Carvalho; Emilia Luigia Saporiti Angerami

    2017-01-01

    Abstract OBJECTIVE To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. METHOD An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. RESULTS The sample consisted of 27 international articles which w...

  3. Discovering Implicit Networks from Point Process Data

    Science.gov (United States)

    2013-08-03

    VIOLENCE −87.9 −87.85 −87.8 −87.75 −87.7 −87.65 −87.6 −87.55 −87.5 41.6 41.65 41.7 41.75 41.8 41.85 41.9 41.95 42 42.05 42.1 L a tit u d e Longitude Murder...with compact support. ‣Gaussian process for log background rate ‣Smoothly-varying or periodic external effects. ‣ Conjugate gamma priors for weights...weights: Gibbs ( conjugate gamma posterior) ‣ Latent parent explanations: parallel Gibbs ‣ Background rates: elliptical slice sampling ‣ Temporal kernels

  4. A Networked Perspective on the Engineering Design Process: At the Intersection of Process and Organisation Architectures

    DEFF Research Database (Denmark)

    Parraguez, Pedro

    The design process of engineering systems frequently involves hundreds of activities and people over long periods of time and is implemented through complex networks of information exchanges. Such socio-technical complexity makes design processes hard to manage, and as a result, engineering design...... of a networked perspective also has limited the study of the relationships between process complexity and process performance. This thesis argues that to understand and improve design processes, we must look beyond the planned process and unfold the network structure and composition that actually implement...... the process. This combination of process structure—how people and activities are connected—and composition—the functional diversity of the groups participating in the process—is referred to as the actual design process architecture. This thesis reports on research undertaken to develop, apply and test...

  5. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...... generation of pikes. When a stimulus is applied to the network, the spontaneous rings may prevail and hamper detection of the effects of the stimulus. Therefore, the spontaneous rings cannot be ignored and the response latency has to be detected on top of a background signal. Everything becomes more dicult...

  6. A Generic Methodology for Superstructure Optimization of Different Processing Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei

    problem.The proposed methodology involves the use of additional methods and tools, such as a database and an external software for solving the network optimization problem. The database has been created using an ontology-based knowledge representation consisting in various layers of data...... in a software interface that guides the user through the problem formulation and solution steps and integrates the various methods and tools for efficient flow of information between them. By using this interface, the user can retrieve and/or modify existing networks and alternatives from the database, as well...... of sustainable processing networks containing three stages: (i) synthesis stage, (ii) design stage, and (iii) innovation stage. In this work, a focus is placed on the first stage, the synthesis stage. Process synthesis becomes necessary in determining the appropriate processing routes to produce a selection...

  7. Signal propagation in cortical networks: a digital signal processing approach.

    Science.gov (United States)

    Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

    2009-01-01

    This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.

  8. Rh-Based Mixed Alcohol Synthesis Catalysts: Characterization and Computational Report

    Energy Technology Data Exchange (ETDEWEB)

    Albrecht, Karl O.; Glezakou, Vassiliki Alexandra; Rousseau, Roger J.; Engelhard, Mark H.; Varga, Tamas; Colby, Robert J.; Jaffe, John E.; Li, Xiaohong S.; Mei, Donghai; Windisch, Charles F.; Kathmann, Shawn M.; Lemmon, Teresa L.; Gray, Michel J.; Hart, Todd R.; Thompson, Becky L.; Gerber, Mark A.

    2013-08-01

    The U.S. Department of Energy is conducting a program focused on developing a process for the conversion of biomass to bio-based fuels and co-products. Biomass-derived syngas is converted thermochemically within a temperature range of 240 to 330°C and at elevated pressure (e.g., 1200 psig) over a catalyst. Ethanol is the desired reaction product, although other side compounds are produced, including C3 to C5 alcohols; higher (i.e., greater than C1) oxygenates such as methyl acetate, ethyl acetate, acetic acid and acetaldehyde; and higher hydrocarbon gases such as methane, ethane/ethene, propane/propene, etc. Saturated hydrocarbon gases (especially methane) are undesirable because they represent a diminished yield of carbon to the desired ethanol product and represent compounds that must be steam reformed at high energy cost to reproduce CO and H2. Ethanol produced by the thermochemical reaction of syngas could be separated and blended directly with gasoline to produce a liquid transportation fuel. Additionally, higher oxygenates and unsaturated hydrocarbon side products such as olefins also could be further processed to liquid fuels. The goal of the current project is the development of a Rh-based catalyst with high activity and selectivity to C2+ oxygenates. This report chronicles an effort to characterize numerous supports and catalysts to identify particular traits that could be correlated with the most active and/or selective catalysts. Carbon and silica supports and catalysts were analyzed. Generally, analyses provided guidance in the selection of acceptable catalyst supports. For example, supports with high surface areas due to a high number of micropores were generally found to be poor at producing oxygenates, possibly because of mass transfer limitations of the products formed out of the micropores. To probe fundamental aspects of the complicated reaction network of CO with H2, a computational/ theoretical investigation using quantum mechanical and ab

  9. A Generic Methodology for Superstructure Optimization of Different Processing Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei

    2016-01-01

    In this paper, we propose a generic computer-aided methodology for synthesis of different processing networks using superstructure optimization. The methodology can handle different network optimization problems of various application fields. It integrates databases with a common data architecture......, a generic model to represent the processing steps, and appropriate optimization tools. A special software interface has been created to automate the steps in the methodology workflow, allow the transfer of data between tools and obtain the mathematical representation of the problem as required...

  10. Possibilistic networks for uncertainty knowledge processing in student diagnosis

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2006-12-01

    Full Text Available In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.

  11. Hierarchical neural networks perform both serial and parallel processing.

    Science.gov (United States)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

    2015-06-01

    In this work we study a Hebbian neural network, where neurons are arranged according to a hierarchical architecture such that their couplings scale with their reciprocal distance. As a full statistical mechanics solution is not yet available, after a streamlined introduction to the state of the art via that route, the problem is consistently approached through signal-to-noise technique and extensive numerical simulations. Focusing on the low-storage regime, where the amount of stored patterns grows at most logarithmical with the system size, we prove that these non-mean-field Hopfield-like networks display a richer phase diagram than their classical counterparts. In particular, these networks are able to perform serial processing (i.e. retrieve one pattern at a time through a complete rearrangement of the whole ensemble of neurons) as well as parallel processing (i.e. retrieve several patterns simultaneously, delegating the management of different patterns to diverse communities that build network). The tune between the two regimes is given by the rate of the coupling decay and by the level of noise affecting the system. The price to pay for those remarkable capabilities lies in a network's capacity smaller than the mean field counterpart, thus yielding a new budget principle: the wider the multitasking capabilities, the lower the network load and vice versa. This may have important implications in our understanding of biological complexity. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Evaluating Functional Autocorrelation within Spatially Distributed Neural Processing Networks*

    Science.gov (United States)

    Derado, Gordana; Bowman, F. Dubois; Ely, Timothy D.; Kilts, Clinton D.

    2010-01-01

    Data-driven statistical approaches, such as cluster analysis or independent component analysis, applied to in vivo functional neuroimaging data help to identify neural processing networks that exhibit similar task-related or restingstate patterns of activity. Ideally, the measured brain activity for voxels within such networks should exhibit high autocorrelation. An important limitation is that the algorithms do not typically quantify or statistically test the strength or nature of the within-network relatedness between voxels. To extend the results given by such data-driven analyses, we propose the use of Moran’s I statistic to measure the degree of functional autocorrelation within identified neural processing networks and to evaluate the statistical significance of the observed associations. We adapt the conventional definition of Moran’s I, for applicability to neuroimaging analyses, by defining the global autocorrelation index using network-based neighborhoods. Also, we compute network-specific contributions to the overall autocorrelation. We present results from a bootstrap analysis that provide empirical support for the use of our hypothesis testing framework. We illustrate our methodology using positron emission tomography (PET) data from a study that examines the neural representation of working memory among individuals with schizophrenia and functional magnetic resonance imaging (fMRI) data from a study of depression. PMID:21643436

  13. Social networks in nursing work processes: an integrative literature review

    Directory of Open Access Journals (Sweden)

    Ana Cláudia Mesquita

    Full Text Available Abstract OBJECTIVE To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. METHOD An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. RESULTS The sample consisted of 27 international articles which were published between 2011 and 2016. The social networks used were Facebook (66.5%, Twitter (30% and WhatsApp (3.5%. In 70.5% of the studies, social networks were used for research purposes, in 18.5% they were used as a tool aimed to assist students in academic activities, and in 11% for executing interventions via the internet. CONCLUSION Nurses have used social networks in their work processes such as Facebook, Twitter and WhatsApp to research, teach and watch. The articles show several benefits in using such tools in the nursing profession; however, ethical considerations regarding the use of social networks deserve further discussion.

  14. Generalized k-core pruning process on directed networks

    Science.gov (United States)

    Zhao, Jin-Hua

    2017-06-01

    The resilience of a complex interconnected system concerns the size of the macroscopic functioning node clusters after external perturbations based on a random or designed scheme. For a representation of interconnected systems with directional or asymmetrical interactions among constituents, the directed network is a convenient choice. Yet, how the interaction directions affect the network resilience still lacks a thorough exploration. Here, we study the resilience of directed networks with a generalized k-core pruning process as a simple failure procedure based on both the in- and out-degrees of nodes, in which any node with an in-degree  networks more vulnerable against perturbations based on in- and out-degrees separately.

  15. Specificity, promiscuity, and the structure of complex information processing networks

    Science.gov (United States)

    Myers, Christopher

    2006-03-01

    Both the top-down designs of engineered systems and the bottom-up serendipities of biological evolution must negotiate tradeoffs between specificity and control: overly specific interactions between components can make systems brittle and unevolvable, while more generic interactions can require elaborate control in order to aggregate specificity from distributed pieces. Complex information processing systems reveal network organizations that navigate this landscape of constraints: regulatory and signaling networks in cells involve the coordination of molecular interactions that are surprisingly promiscuous, and object-oriented design in software systems emphasizes the polymorphic composition of objects of minimal necessary specificity [C.R. Myers, Phys Rev E 68, 046116 (2003)]. Models of information processing arising both in systems biology and engineered computation are explored to better understand how particular network organizations can coordinate the activity of promiscuous components to achieve robust and evolvable function.

  16. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

  17. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    Science.gov (United States)

    Kim, Ji Chul; Large, Edward W

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing.

  18. Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

    Science.gov (United States)

    Moisl, Hermann

    It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

  19. Le rôle des grandes infrastructures dans la structuration des espaces régionaux : le cas de l’arrivée du TGV dans le réseau métropolitain Rhin-Rhône The role of the main infrastructures in the structuring process of the regional areas : the case of the TGV in the Rhin-Rhône metropolitan region

    Directory of Open Access Journals (Sweden)

    Cyprien Richer

    2012-12-01

    Full Text Available Dans un contexte d’émergence d’un réseau métropolitain entre des aires urbaines de Bourgogne, Franche-Comté et Sud-Alsace débordant sur la Suisse et l’Allemagne, cet article porte sur les effets territoriaux potentiels d’un projet de grande infrastructure, la ligne à grande vitesse Rhin-Rhône, actuellement en construction. Après avoir mené une réflexion sur la morphologie des réseaux de transport dans ces espaces qualifiés “d’intermédiaires”, il mesure les perspectives qu’ouvre le TGV Rhin-Rhône en matière de déplacements et d’accessibilité métropolitaine. Il identifie les tensions et recompositions des jeux d’acteurs dans ce projet d’infrastructure. L’objectif de cette contribution est d’analyser les opportunités et les risques que comporte, pour ces territoires régionaux, l’aménagement du réseau TGV construit pour répondre à des enjeux relevant d’autres échelles spatiales.In the context of an emerging transborder metropolitan region between urban areas of France (Dijon, Besançon, Mulhouse, Switzerland (Basel, Neuchâtel and Germany (Fribourg, this article deals with the potential territorial effects of a main infrastructure project, the Rhin-Rhône high-speed lane (TGV, currently in construction. After a reflexion on the morphology of the transport network in the intermediate spaces, we measure the prospects of mobility offered by the TGV Rhin-Rhône. This work will identify the tensions and recompositions in the role-playing of actors in this project of high-speed rail infrastructure. The issue of this paper is to analyze the opportunities and the risks resulting from the construction of the TGV network, built to answer to stakes of a higher space scale.

  20. Probabilistic Models and Process Calculi for Mobile Ad Hoc Networks

    DEFF Research Database (Denmark)

    Song, Lei

    , thus the network topology may undergo constant changes. Moreover the devices in an MANET are loosely connected not depending on pre-installed infrastructure or central control components, they exchange messages via wireless connections which are less reliable compared to wired connections. Therefore...... issues in MANETs e.g. mobility and unreliable connections. Specially speaking, 1. We first propose a discrete probabilistic process calculus with which we can model in an MANET that the wireless connection is not reliable, and the network topology may undergo changes. We equip each wireless connection...

  1. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  2. Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Caiyun Huang

    2014-07-01

    Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

  3. Promoting information diffusion through interlayer recovery processes in multiplex networks

    Science.gov (United States)

    Wang, Xin; Li, Weihua; Liu, Longzhao; Pei, Sen; Tang, Shaoting; Zheng, Zhiming

    2017-09-01

    For information diffusion in multiplex networks, the effect of interlayer contagion on spreading dynamics has been explored in different settings. Nevertheless, the impact of interlayer recovery processes, i.e., the transition of nodes to stiflers in all layers after they become stiflers in any layer, still remains unclear. In this paper, we propose a modified ignorant-spreader-stifler model of rumor spreading equipped with an interlayer recovery mechanism. We find that the information diffusion can be effectively promoted for a range of interlayer recovery rates. By combining the mean-field approximation and the Markov chain approach, we derive the evolution equations of the diffusion process in two-layer homogeneous multiplex networks. The optimal interlayer recovery rate that achieves the maximal enhancement can be calculated by solving the equations numerically. In addition, we find that the promoting effect on a certain layer can be strengthened if information spreads more extensively within the counterpart layer. When applying the model to two-layer scale-free multiplex networks, with or without degree correlation, similar promoting effect is also observed in simulations. Our work indicates that the interlayer recovery process is beneficial to information diffusion in multiplex networks, which may have implications for designing efficient spreading strategies.

  4. The transmission process: A combinatorial stochastic process for the evolution of transmission trees over networks.

    Science.gov (United States)

    Sainudiin, Raazesh; Welch, David

    2016-12-07

    We derive a combinatorial stochastic process for the evolution of the transmission tree over the infected vertices of a host contact network in a susceptible-infected (SI) model of an epidemic. Models of transmission trees are crucial to understanding the evolution of pathogen populations. We provide an explicit description of the transmission process on the product state space of (rooted planar ranked labelled) binary transmission trees and labelled host contact networks with SI-tags as a discrete-state continuous-time Markov chain. We give the exact probability of any transmission tree when the host contact network is a complete, star or path network - three illustrative examples. We then develop a biparametric Beta-splitting model that directly generates transmission trees with exact probabilities as a function of the model parameters, but without explicitly modelling the underlying contact network, and show that for specific values of the parameters we can recover the exact probabilities for our three example networks through the Markov chain construction that explicitly models the underlying contact network. We use the maximum likelihood estimator (MLE) to consistently infer the two parameters driving the transmission process based on observations of the transmission trees and use the exact MLE to characterize equivalence classes over the space of contact networks with a single initial infection. An exploratory simulation study of the MLEs from transmission trees sampled from three other deterministic and four random families of classical contact networks is conducted to shed light on the relation between the MLEs of these families with some implications for statistical inference along with pointers to further extensions of our models. The insights developed here are also applicable to the simplest models of "meme" evolution in online social media networks through transmission events that can be distilled from observable actions such as "likes", "mentions

  5. Managing the energy efficiency of a process sensor network

    Energy Technology Data Exchange (ETDEWEB)

    Karjalainen, S.; Karjalainen, T. (Univ. of Oulu, Measurement and Sensor Lab., Kajaani (Finland)). email: seppo.karjalainen@oulu.fi

    2009-07-01

    A wireless data transfer is nowadays quite easy and affordable to implement in most cases. If the wireless sensor network (Wsrn) is deployed in a very difficult environment or requires great data transfer speeds, as in many industrial and process environments, this might not always be the case. The main reason slowing the deployment of WSNs is the difficulty of supplying enough energy to the sensor nodes. In most cases all of the energy the node consumes must be stored or produced at the node. The difficulty of supplying enough energy for the nodes can shorten the maintenance interval of the nodes to an unpractical level. In this research project we study the possibilities of managing the energy efficiency (saving energy, producing energy) of a wireless process measurement system. The main focus areas of the project are saving and producing energy at the network nodes. Energy consumption is the main limitation while designing WSNs. To extend each sensor node's lifetime it is necessary to reduce power dissipation as much as possible. A sensor node is a complex device comprising of various parts, each of which must be carefully selected and utilized in order to reach the lowest possible energy consumption. The level of energy efficiency of a sensor network is greatly affected by the way we balance the goal of low energy consumption with the other requirements placed on the network. The requirements for a deployed WSN depend on the application and the operating environment. Hence, the generalization of the requirements in detail is not practical. Nonetheless sensor network applications possess several characteristics, based on which general requirements for the node platforms, protocols and applications can be defined. The relative importance of each requirement depends heavily on the application area. In this project we produce a report covering all the various aspects of managing the energy efficiency in a wireless sensor network. The physical components and

  6. Analytical network process based optimum cluster head selection in wireless sensor network.

    Science.gov (United States)

    Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

    2017-01-01

    Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of

  7. A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

    Science.gov (United States)

    Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi’i

    2017-11-01

    Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.

  8. Quantum Processes and Dynamic Networks in Physical and Biological Systems.

    Science.gov (United States)

    Dudziak, Martin Joseph

    Quantum theory since its earliest formulations in the Copenhagen Interpretation has been difficult to integrate with general relativity and with classical Newtonian physics. There has been traditionally a regard for quantum phenomena as being a limiting case for a natural order that is fundamentally classical except for microscopic extrema where quantum mechanics must be applied, more as a mathematical reconciliation rather than as a description and explanation. Macroscopic sciences including the study of biological neural networks, cellular energy transports and the broad field of non-linear and chaotic systems point to a quantum dimension extending across all scales of measurement and encompassing all of Nature as a fundamentally quantum universe. Theory and observation lead to a number of hypotheses all of which point to dynamic, evolving networks of fundamental or elementary processes as the underlying logico-physical structure (manifestation) in Nature and a strongly quantized dimension to macroscalar processes such as are found in biological, ecological and social systems. The fundamental thesis advanced and presented herein is that quantum phenomena may be the direct consequence of a universe built not from objects and substance but from interacting, interdependent processes collectively operating as sets and networks, giving rise to systems that on microcosmic or macroscopic scales function wholistically and organically, exhibiting non-locality and other non -classical phenomena. The argument is made that such effects as non-locality are not aberrations or departures from the norm but ordinary consequences of the process-network dynamics of Nature. Quantum processes are taken to be the fundamental action-events within Nature; rather than being the exception quantum theory is the rule. The argument is also presented that the study of quantum physics could benefit from the study of selective higher-scale complex systems, such as neural processes in the brain

  9. Parallel processing of blocks of data in the network

    Science.gov (United States)

    Wang, Jingyan; Heng, Wei

    2008-11-01

    It is hard and expensive to increase the speed of data processing by just improving the capability of the hardware. This paper puts forward a platform of image transmission and reception among computers in the network in order to speed up the data processing under the limitation of the existing hardware conditions. The basic idea is that the transmitter divides an integrated data into several parts and sends each of them to different computers in the network. Then these parallel receivers process their own received data and send them to the same terminal computer which function is to put the renewed data together according to certain order so that the original data is processed just like one high-performance computer does. The capability is expanded by updating the data periodically and processing several data simultaneously without interfering each other. The work of calculating and processing is accomplished by those parallel computers while the transmitter and receiver have low burden so that they can fulfill other work. Performance results show that the data processing speed can be increased by this method and the more computers, the better the performance.

  10. Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

    Science.gov (United States)

    Kirst, Christoph

    It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

  11. Neural networks for process control and optimization: two industrial applications.

    Science.gov (United States)

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  12. Supply Chain Management: from Linear Interactions to Networked Processes

    Directory of Open Access Journals (Sweden)

    Doina FOTACHE

    2006-01-01

    Full Text Available Supply Chain Management is a distinctive product, with a tremendous impact on the software applications market. SCM applications are back-end solutions intended to link suppliers, manufacturers, distributors and resellers in a production and distribution network, which allows the enterprise to track and consolidate the flows of materials and data trough the process of manufacturing and distribution of goods/services. The advent of the Web as a major means of conducting business transactions and business-tobusiness communications, coupled with evolving web-based supply chain management (SCM technology, has resulted in a transition period from “linear” supply chain models to "networked" supply chain models. The technologies to enable dynamic process changes and real time interactions between extended supply chain partners are emerging and being deployed at an accelerated pace.

  13. Mashup Model and Verification Using Mashup Processing Network

    Science.gov (United States)

    Zahoor, Ehtesham; Perrin, Olivier; Godart, Claude

    Mashups are defined to be lightweight Web applications aggregating data from different Web services, built using ad-hoc composition and being not concerned with long term stability and robustness. In this paper we present a pattern based approach, called Mashup Processing Network (MPN). The idea is based on Event Processing Network and is supposed to facilitate the creation, modeling and the verification of mashups. MPN provides a view of how different actors interact for the mashup development namely the producer, consumer, mashup processing agent and the communication channels. It also supports modeling transformations and validations of data and offers validation of both functional and non-functional requirements, such as reliable messaging and security, that are key issues within the enterprise context. We have enriched the model with a set of processing operations and categorize them into data composition, transformation and validation categories. These processing operations can be seen as a set of patterns for facilitating the mashup development process. MPN also paves a way for realizing Mashup Oriented Architecture where mashups along with services are used as building blocks for application development.

  14. Exchange and crystal-field interactions in the antiferromagnets GdRh sub 2 Si sub 2 and TbRh sub 2 Si sub 2

    Energy Technology Data Exchange (ETDEWEB)

    Szytula, A. (Inst. of Physics, Jagiellonian Univ., Cracow (Poland)); Radwanski, R.J.; Boer, F.R. de (Van der Waals-Zeeman Lab., Univ. van Amsterdam (Netherlands))

    1992-02-01

    Magnetization curves up to 35 T have been measured at 4.2 K on free powder particles of the antiferromagnets GdRh{sub 2}Si{sub 2} and TbRh{sub 2}Si{sub 2}. The magnetization process is analyzed within a two-sublattice model for antiferromagnets. For GdRh{sub 2}Si{sub 2} the intersublattice molecular-field coefficient amounts to 7.2 T f.u./{mu}{sub B}. For TbRh{sub 2}Si{sub 2} metamagnetic transitions at 8 and 15 T are observed. (orig.).

  15. Information processing and routing in wireless sensor networks

    CERN Document Server

    Yu, Yang; Krishnamachari, Bhaskar

    2006-01-01

    This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail - information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of en

  16. Social networks in nursing work processes: an integrative literature review.

    Science.gov (United States)

    Mesquita, Ana Cláudia; Zamarioli, Cristina Mara; Fulquini, Francine Lima; Carvalho, Emilia Campos de; Angerami, Emilia Luigia Saporiti

    2017-03-20

    To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. The sample consisted of 27 international articles which were published between 2011 and 2016. The social networks used were Facebook (66.5%), Twitter (30%) and WhatsApp (3.5%). In 70.5% of the studies, social networks were used for research purposes, in 18.5% they were used as a tool aimed to assist students in academic activities, and in 11% for executing interventions via the internet. Nurses have used social networks in their work processes such as Facebook, Twitter and WhatsApp to research, teach and watch. The articles show several benefits in using such tools in the nursing profession; however, ethical considerations regarding the use of social networks deserve further discussion. Identificar e analisar as evidências disponíveis na literatura sobre a utilização de redes sociais nos processos de trabalho em enfermagem. Revisão integrativa da literatura realizada em janeiro de 2016, nas bases de dados PubMed, CINAHL, EMBASE e LILACS, com os descritores social media, social networking, nursing, enfermagem, redes sociais, mídias sociais e a palavra-chave nursing practice, sem restrição de ano. A amostra foi composta por 27 artigos, os quais foram publicados entre 2011 e 2016, todos internacionais. As redes sociais utilizadas foram o Facebook (66,5%), o Twitter (30%) e o WhatsApp (3,5%). Em 70,5% dos estudos as redes sociais foram utilizadas para fins de pesquisa, em 18,5% como ferramenta para auxiliar estudantes nas atividades acadêmicas, e em 11% para a realização de intervenções via internet. Em seus processos de trabalho, os enfermeiros têm utilizado

  17. Graphics processing unit-based alignment of protein interaction networks.

    Science.gov (United States)

    Xie, Jiang; Zhou, Zhonghua; Ma, Jin; Xiang, Chaojuan; Nie, Qing; Zhang, Wu

    2015-08-01

    Network alignment is an important bridge to understanding human protein-protein interactions (PPIs) and functions through model organisms. However, the underlying subgraph isomorphism problem complicates and increases the time required to align protein interaction networks (PINs). Parallel computing technology is an effective solution to the challenge of aligning large-scale networks via sequential computing. In this study, the typical Hungarian-Greedy Algorithm (HGA) is used as an example for PIN alignment. The authors propose a HGA with 2-nearest neighbours (HGA-2N) and implement its graphics processing unit (GPU) acceleration. Numerical experiments demonstrate that HGA-2N can find alignments that are close to those found by HGA while dramatically reducing computing time. The GPU implementation of HGA-2N optimises the parallel pattern, computing mode and storage mode and it improves the computing time ratio between the CPU and GPU compared with HGA when large-scale networks are considered. By using HGA-2N in GPUs, conserved PPIs can be observed, and potential PPIs can be predicted. Among the predictions based on 25 common Gene Ontology terms, 42.8% can be found in the Human Protein Reference Database. Furthermore, a new method of reconstructing phylogenetic trees is introduced, which shows the same relationships among five herpes viruses that are obtained using other methods.

  18. Test of the Use of Regional Networks for OPUS Processing

    Science.gov (United States)

    Weston, Neil D.; Ray, Jim R.

    2010-05-01

    We investigate the performance of two processing methodologies for the Online Positioning User Service (OPUS), a web-based tool to process GPS data offered by the National Geodetic Survey, NOAA. The current operational implementation of OPUS (OPUS-S) uses reference station data from the U.S. National CORS Network and fixed IGS ephemerides to compute independent, double-differenced baseline solutions between the unknown and three neighboring CORS reference stations. All computations use relative antenna patterns, phase ambiguity integer fixing, relative troposphere modeling (GPT and GMF a priori models), and are performed in the ITRF2000 (IGb00) reference frame. The most accurate IGS orbits available at the time of processing are used. Although the three baselines are not strictly independent because of local biases, such as multipath at the rover, the solutions are analyzed to identify problems with any of the baselines before they are averaged to obtain a final set of coordinates and uncertainties. A new OPUS processing methodology has been tested using a network approach (OPUS-Net). Otherwise the analysis models and weighted least squares adjustment method are unchanged, except that models for absolute antenna patterns and ocean tide loading are also implemented. The network consists of a rover, three nearby CORS reference stations, and up to 10 reference stations from the global IGS network (IGS05). The multipliers for the a priori weights for the CORS and IGS reference station monument sigmas (meters) in the adjustment are 0.1 and 1000.0 respectively, mainly because the coordinates and velocities for the IGS05 stations are much more precisely known and monitored. To evaluate the positioning performance of the two OPUS approaches, GPS reference station data from three CORS stations (azco, brew, p036) were used as rovers. Approximately 360 daily datasets from each of the three stations collected in 2008 were submitted to each OPUS version for processing. The

  19. Bioorganometallic Chemistry, Part 15. A novel molecular recognition process of host, trans-[Cp*Rh({eta}{sup 1}(N3)-1-methylcytosine)({mu}-OH)]{sub 2} (OTf){sub 2}, with l-aromatic amino acid guests: selective hydrogen bonding to the {mu}-OH groups and the 1-methylcytosine ligands

    Energy Technology Data Exchange (ETDEWEB)

    Elduque, Anabel; Carmona, Daniel; Oro, Luis; Eisenstein, Miriam; Fish, Richard H.

    2002-11-01

    The {sup 1}H-NMR and computer docking experiments have elucidated a novel molecular recognition process of host, trans-[Cp*Rh({eta}{sup 1}(Ne)-1-methylcytosine)({mu}-OH)]{sub 2}(OTf){sub 2} (1), with L-aromatic amino acids, which is predicated on a selective hydrogen bonding regime of the NH{sub 3}{sup +} of the amino acid to one of the Rh-{mu}-OH groups, as well as to a C{double_bond}O group of one of the other 1-methycytosine ligands, while the COO{sup -} H-bonds to an NH{sub 2} of the other 1-methycytosine ligand.

  20. GnRH tandem peptides for inducing an immunogenic response to GnRH-I without cross-reactivity to other GnRH isoforms

    NARCIS (Netherlands)

    Turkstra, J.A.; Schaaper, W.M.M.; Oonk, H.B.; Meloen, R.H.

    2005-01-01

    Gonadotropin releasing hormone (GnRH) occurs in various isoforms in mammals, i.e. GnRH-I (mammalian GnRH), GnRH-II (chicken GnRH-II), GnRH-III (salmon GnRH) and two forms of lamprey GnRH. The function of the latter four molecules have only been partially investigated. Also not much is known about

  1. 103Rh NMR spectroscopy and its application to rhodium chemistry.

    Science.gov (United States)

    Ernsting, Jan Meine; Gaemers, Sander; Elsevier, Cornelis J

    2004-09-01

    Rhodium is used for a number of large processes that rely on homogeneous rhodium-catalyzed reactions, for instance rhodium-catalyzed hydroformylation of alkenes, carbonylation of methanol to acetic acid and hydrodesulfurization of thiophene derivatives (in crude oil). Many laboratory applications in organometallic chemistry and catalysis involve organorhodium chemistry and a wealth of rhodium coordination compounds is known. For these and other areas, 103Rh NMR spectroscopy appears to be a very useful analytical tool. In this review, most of the literature concerning 103Rh NMR spectroscopy published from 1989 up to and including 2003 has been covered. After an introduction to several experimental methods for the detection of the insensitive 103Rh nucleus, a discussion of factors affecting the transition metal chemical shift is given. Computational aspects and calculations of chemical shifts are also briefly addressed. Next, the application of 103Rh NMR in coordination and organometallic chemistry is elaborated in more detail by highlighting recent developments in measurement and interpretation of 103Rh NMR data, in relation to rhodium-assisted reactions and homogeneous catalysis. The dependence of the 103Rh chemical shift on the ligands at rhodium in the first coordination sphere, on the complex geometry, oxidation state, temperature, solvent and concentration is treated. Several classes of compounds and special cases such as chiral rhodium compounds are reviewed. Finally, a section on scalar coupling to rhodium is provided. 2004 John Wiley & Sons, Ltd.

  2. The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing Archival/Methodology, and Results

    Science.gov (United States)

    Blakeslee, R. J.; Bailey, J. C.; Pinto, O.; Athayde, A.; Renno, N.; Weidman, C. D.

    2003-01-01

    A four station Advanced Lightning Direction Finder (ALDF) network was established in the state of Rondonia in western Brazil in 1999 through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of- arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the Internet. The network, which is still operational, was deployed to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in November 1997. The measurements are also being used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-time series observations produced by this network will help establish a regional lightning climatological database, supplementing other databases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at the NASA/Marshall Space Flight Center have been applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The data will also be corrected for the network detection efficiency. The processing methodology and the results from the analysis of four years of network operations will be presented.

  3. A Study of Rank Defect and Network Effect in Processing the CMONOC Network on Bernese

    Directory of Open Access Journals (Sweden)

    Weiwei Wu

    2018-02-01

    Full Text Available High-precision GPS data processing on Bernese has been employed to routinely resolve daily position solutions of GPS stations in the Crustal Movement Observation Network of China (CMONOC. The rank-deficient problems of the normal equation (NEQ system and the network effect on the frame alignment of NEQs in the processing of CMONOC data on Bernese still present difficulties. In this study, we diagnose the rank-deficient problems of the original NEQ, review the efficiency of the controlled datum removal (CDR method in filtering out the three frame-origin-related datum contents, investigate the reliabilities of the inherited frame orientation and scale information from the fixation of the GPS satellite orbits and the Earth rotation parameters in establishing the NEQ of the CMONOC network on Bernese, and analyze the impact of the network effect on the position time series of GPS stations. Our results confirm the nonsingularity of the original NEQ and the efficiency of the CDR filtering in resolving the rank-deficient problems; show that the frame origin parameters are weakly defined and should be stripped off, while the frame orientation and scale parameters should be retained due to their insufficient redefinition from the minimal constraint (MC implementation through inhomogeneous and asymmetrical fiducial networks; and reveal the superiority of a globally distributed fiducial network for frame alignment of the reconstructed NEQs via No-Net-Translation (NNT MC conditions. Finally, we attribute the two apparent discontinuities in the position time series to the terrestrial reference frame (TRF conversions of the GPS satellite orbits, and identify it as the orbit TRF effect.

  4. Part I: A Comparative Thermal Aging Study on the Regenerability of Rh/Al2O3 and Rh/CexOy-ZrO2 as Model Catalysts for Automotive Three Way Catalysts

    Directory of Open Access Journals (Sweden)

    Qinghe Zheng

    2015-10-01

    Full Text Available The rhodium (Rh component in automotive three way catalysts (TWC experiences severe thermal deactivation during fuel shutoff, an engine mode (e.g., at downhill coasting used for enhancing fuel economy. In a subsequent switch to a slightly fuel rich condition, in situ catalyst regeneration is accomplished by reduction with H2 generated through steam reforming catalyzed by Rh0 sites. The present work reports the effects of the two processes on the activity and properties of 0.5% Rh/Al2O3 and 0.5% Rh/CexOy-ZrO2 (CZO as model catalysts for Rh-TWC. A very brief introduction of three way catalysts and system considerations is also given. During simulated fuel shutoff, catalyst deactivation is accelerated with increasing aging temperature from 800 °C to 1050 °C. Rh on a CZO support experiences less deactivation and faster regeneration than Rh on Al2O3. Catalyst characterization techniques including BET surface area, CO chemisorption, TPR, and XPS measurements were applied to examine the roles of metal-support interactions in each catalyst system. For Rh/Al2O3, strong metal-support interactions with the formation of stable rhodium aluminate (Rh(AlO2y complex dominates in fuel shutoff, leading to more difficult catalyst regeneration. For Rh/CZO, Rh sites were partially oxidized to Rh2O3 and were relatively easy to be reduced to active Rh0 during regeneration.

  5. Forecasting financial asset processes: stochastic dynamics via learning neural networks.

    Science.gov (United States)

    Giebel, S; Rainer, M

    2010-01-01

    Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

  6. Distributed Signal Processing for Wireless EEG Sensor Networks.

    Science.gov (United States)

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  7. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P.J.; Gu, F.; Ball, A.D. [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1997-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  8. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  9. Bayesian networks applied to process diagnostics. Applications in energy industry

    Energy Technology Data Exchange (ETDEWEB)

    Widarsson, Bjoern (ed.); Karlsson, Christer; Dahlquist, Erik [Maelardalen Univ., Vaesteraas (Sweden); Nielsen, Thomas D.; Jensen, Finn V. [Aalborg Univ. (Denmark)

    2004-10-01

    Uncertainty in process operation occurs frequently in heat and power industry. This makes it hard to find the occurrence of an abnormal process state from a number of process signals (measurements) or find the correct cause to an abnormality. Among several other methods, Bayesian Networks (BN) is a method to build a model which can handle uncertainty in both process signals and the process itself. The purpose of this project is to investigate the possibilities to use BN for fault detection and diagnostics in combined heat and power industries through execution of two different applications. Participants from Aalborg University represent the knowledge of BN and participants from Maelardalen University have the experience from modelling heat and power applications. The co-operation also includes two energy companies; Elsam A/S (Nordjyllandsverket) and Maelarenergi AB (Vaesteraas CHP-plant), where the two applications are made with support from the plant personnel. The project ended out in two quite different applications. At Nordjyllandsverket, an application based (due to the lack of process knowledge) on pure operation data is build with capability to detect an abnormal process state in a coal mill. Detection is made through a conflict analysis when entering process signals into a model built by analysing the operation database. The application at Maelarenergi is built with a combination of process knowledge and operation data and can detect various faults caused by the fuel. The process knowledge is used to build a causal network structure and the structure is then trained by data from the operation database. Both applications are made as off-online applications, but they are ready for being run on-line. The performance of fault detection and diagnostics are good, but a lack of abnormal process states with known cause reduces the evaluation possibilities. Advantages with combining expert knowledge of the process with operation data are the possibility to represent

  10. Building a multilevel modeling network for lipid processing systems

    DEFF Research Database (Denmark)

    Mustaffa, Azizul Azri; Díaz Tovar, Carlos Axel; Hukkerikar, Amol

    2011-01-01

    data collected from existing process plants, and application of validated models in design and analysis of unit operations; iv) the information and models developed are used as building blocks in the development of methods and tools for computer-aided synthesis and design of process flowsheets (CAFD......The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...... and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFAC-CI model, development...

  11. Physical Modelling Of The Steel Flow In RH Apparatus

    Directory of Open Access Journals (Sweden)

    Pieprzyca J.

    2015-09-01

    Full Text Available The efficiency of vacuum steel degassing using RH methods depends on many factors. One of the most important are hydrodynamic processes occurring in the ladle and vacuum chamber. It is always hard and expensive to determine the flow character and the way of steel mixing in industrial unit; thus in this case, methods of physical modelling are applied. The article presents the results of research carried out on the water physical model of RH apparatus concerning the influence of the flux value of inert gas introduced through the suck legs on hydrodynamic conditions of the process. Results of the research have visualization character and are presented graphically as a RTD curves. The main aim of such research is to optimize the industrial vacuum steel degassing process by means of RH method.

  12. Statistical process control using optimized neural networks: a case study.

    Science.gov (United States)

    Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

    2014-09-01

    The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  13. A brain network processing the age of faces.

    Directory of Open Access Journals (Sweden)

    György A Homola

    Full Text Available Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.

  14. Analysis of clusterization and networking processes in developing intermodal transportation

    Directory of Open Access Journals (Sweden)

    Sinkevičius Gintaras

    2016-06-01

    Full Text Available Analysis of the processes of clusterization and networking draws attention to the necessity of integration of railway transport into the intermodal or multimodal transport chain. One of the most widespread methods of combined transport is interoperability of railway and road transport. The objective is to create an uninterrupted transport chain in combining several modes of transport. The aim of this is to save energy resources, to form an effective, competitive, attractive to the client and safe and environmentally friendly transport system.

  15. RH Department Information Meeting

    CERN Multimedia

    HR Department

    2010-01-01

    Dear Colleagues, HR Department would like to invite you to an information meeting which will be held on Thursday 30 September 2010 at 9:30 am in the Main Auditorium (Building 500)* A welcome coffee will be available from 9:00 a.m. The presentation will cover the CERN Competency Model which consists of the technical and behavioral competencies that are intrinsic to our Organization and its application in the various HR processes. This presentation will be followed by a questions & answers session. We look forward to seeing you all on 30 September! Best regards, Anne-Sylvie Catherin Head, Human Resources Department *This meeting will be simultaneously retransmitted and thereafter available at the following address: http://webcast.cern.ch.

  16. Modeling Nitrogen Processing in Northeast US River Networks

    Science.gov (United States)

    Whittinghill, K. A.; Stewart, R.; Mineau, M.; Wollheim, W. M.; Lammers, R. B.

    2013-12-01

    Due to increased nitrogen (N) pollution from anthropogenic sources, the need for aquatic ecosystem services such as N removal has also increased. River networks provide a buffering mechanism that retains or removes anthropogenic N inputs. However, the effectiveness of N removal in rivers may decline with increased loading and, consequently, excess N is eventually delivered to estuaries. We used a spatially distributed river network N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES) to examine the geography of N removal capacity of Northeast river systems under various land use and climate conditions. FrAMES accounts for accumulation and routing of runoff, water temperatures, and serial biogeochemical processing using reactivity derived from the Lotic Intersite Nitrogen Experiment (LINX2). Nonpoint N loading is driven by empirical relationships with land cover developed from previous research in Northeast watersheds. Point source N loading from wastewater treatment plants is estimated as a function of the population served and the volume of water discharged. We tested model results using historical USGS discharge data and N data from historical grab samples and recently initiated continuous measurements from in-situ aquatic sensors. Model results for major Northeast watersheds illustrate hot spots of ecosystem service activity (i.e. N removal) using high-resolution maps and basin profiles. As expected, N loading increases with increasing suburban or agricultural land use area. Network scale N removal is highest during summer and autumn when discharge is low and river temperatures are high. N removal as the % of N loading increases with catchment size and decreases with increasing N loading, suburban land use, or agricultural land use. Catchments experiencing the highest network scale N removal generally have N inputs (both point and non-point sources) located in lower order streams. Model results can be used to better

  17. Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

    Directory of Open Access Journals (Sweden)

    Cosimo Lacava

    2017-01-01

    Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

  18. Speech Subvocal Signal Processing using Packet Wavelet and Neuronal Network

    Directory of Open Access Journals (Sweden)

    Luis E. Mendoza

    2013-11-01

    Full Text Available This paper presents the results obtained from the recording, processing and classification of words in the Spanish language by means of the analysis of subvocal speech signals. The processed database has six words (forward, backward, right, left, start and stop. In this work, the signals were sensed with surface electrodes placed on the surface of the throat and acquired with a sampling frequency of 50 kHz. The signal conditioning consisted in: the location of area of interest using energy analysis, and filtering using Discrete Wavelet Transform. Finally, the feature extraction was made in the time-frequency domain using Wavelet Packet and statistical techniques for windowing. The classification was carried out with a backpropagation neural network whose training was performed with 70% of the database obtained. The correct classification rate was 75%±2.

  19. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Díaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Mukkerikar, Amol

    2011-01-01

    in design and analysis of unit operations; iv) the information and models developed are used as building blocks in the development of methods and tools for computer-aided synthesis and design of process flowsheets (CAFD). The applicability of this methodology is highlighted in each level of modeling through......The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...... and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFACCI model, development...

  20. Selecting public relations personnel of hospitals by analytic network process.

    Science.gov (United States)

    Liao, Sen-Kuei; Chang, Kuei-Lun

    2009-01-01

    This study describes the use of analytic network process (ANP) in the Taiwanese hospital public relations personnel selection process. Starting with interviewing 48 practitioners and executives in north Taiwan, we collected selection criteria. Then, we retained the 12 critical criteria that were mentioned above 40 times by theses respondents, including: interpersonal skill, experience, negotiation, language, ability to follow orders, cognitive ability, adaptation to environment, adaptation to company, emotion, loyalty, attitude, and Response. Finally, we discussed with the 20 executives to take these important criteria into three perspectives to structure the hierarchy for hospital public relations personnel selection. After discussing with practitioners and executives, we find that selecting criteria are interrelated. The ANP, which incorporates interdependence relationships, is a new approach for multi-criteria decision-making. Thus, we apply ANP to select the most optimal public relations personnel of hospitals. An empirical study of public relations personnel selection problems in Taiwan hospitals is conducted to illustrate how the selection procedure works.

  1. Time-sequential changes of differentially expressed miRNAs during the process of anterior lumbar interbody fusion using equine bone protein extract, rhBMP-2 and autograft

    Science.gov (United States)

    Chen, Da-Fu; Zhou, Zhi-Yu; Dai, Xue-Jun; Gao, Man-Man; Huang, Bao-Ding; Liang, Tang-Zhao; Shi, Rui; Zou, Li-Jin; Li, Hai-Sheng; Bünger, Cody; Tian, Wei; Zou, Xue-Nong

    2014-03-01

    The precise mechanism of bone regeneration in different bone graft substitutes has been well studied in recent researches. However, miRNAs regulation of the bone formation has been always mysterious. We developed the anterior lumbar interbody fusion (ALIF) model in pigs using equine bone protein extract (BPE), recombinant human bone morphogenetic protein-2 (rhBMP-2) on an absorbable collagen sponge (ACS), and autograft as bone graft substitute, respectively. The miRNA and gene expression profiles of different bone graft materials were examined using microarray technology and data analysis, including self-organizing maps, KEGG pathway and Biological process GO analyses. We then jointly analyzed miRNA and mRNA profiles of the bone fusion tissue at different time points respectively. Results showed that miRNAs, including let-7, miR-129, miR-21, miR-133, miR-140, miR-146, miR-184, and miR-224, were involved in the regulation of the immune and inflammation response, which provided suitable inflammatory microenvironment for bone formation. At late stage, several miRNAs directly regulate SMAD4, Estrogen receptor 1 and 5-hydroxytryptamine (serotonin) receptor 2C for bone formation. It can be concluded that miRNAs play important roles in balancing the inflammation and bone formation.

  2. Information processing by networks of quantum decision makers

    Science.gov (United States)

    Yukalov, V. I.; Yukalova, E. P.; Sornette, D.

    2018-02-01

    We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers realizing one-step decisions, in two principal aspects. First, several decision makers are considered simultaneously, who interact with each other through information exchange. Second, a multistep procedure is treated, when the agents exchange information many times. Several decision makers exchanging information and forming their judgment, using quantum rules, form a kind of a quantum information network, where collective decisions develop in time as a result of information exchange. In addition to characterizing collective decisions that arise in human societies, such networks can describe dynamical processes occurring in artificial quantum intelligence composed of several parts or in a cluster of quantum computers. The practical usage of the theory is illustrated on the dynamic disjunction effect for which three quantitative predictions are made: (i) the probabilistic behavior of decision makers at the initial stage of the process is described; (ii) the decrease of the difference between the initial prospect probabilities and the related utility factors is proved; (iii) the existence of a common consensus after multiple exchange of information is predicted. The predicted numerical values are in very good agreement with empirical data.

  3. Memory processes and prefrontal network dysfunction in cryptogenic epilepsy.

    Science.gov (United States)

    Vlooswijk, Marielle C G; Jansen, Jacobus F A; Jeukens, Cécile R L P N; Majoie, H J Marian; Hofman, Paul A M; de Krom, Marc C T F M; Aldenkamp, Albert P; Backes, Walter H

    2011-08-01

    Impaired memory performance is the most frequently reported cognitive problem in patients with chronic epilepsy. To examine memory deficits many studies have focused on the role of the mesiotemporal lobe, mostly with hippocampal abnormalities. However, the role of the prefrontal brain remains unresolved. To investigate the neuronal correlates of working memory dysfunction in patients without structural lesions, a combined study of neurocognitive assessment, hippocampal and cerebral volumetry, and functional magnetic resonance imaging of temporal and frontal memory networks was performed. Thirty-six patients with cryptogenic localization-related epilepsy and 21 healthy controls underwent neuropsychological assessment of intelligence (IQ) and memory. On T(1) -weighted images obtained by 3-Tesla magnetic resonance imaging (MRI), volumetry of the hippocampi and the cerebrum was performed. Functional MRI (fMRI) was performed with a novel picture encoding and Sternberg paradigm that activated different memory-mediating brain regions. Functional connectivity analysis comprised cross-correlation of signal time-series of the most strongly activated regions involved in working memory function. Patients with epilepsy displayed lower IQ values; impaired transient aspects of information processing, as indicated by lower scores on the digit-symbol substitution test (DSST); and decreased short-term memory performance relative to healthy controls, as measured with the Wechsler Adult Intelligence Scale subtests for working memory, and word and figure recognition. This could not be related to any hippocampal volume changes. No group differences were found regarding volumetry or fMRI-derived functional activation. In the Sternberg paradigm, a network involving the anterior cingulate and the middle and inferior frontal gyrus was activated. A reduced strength of four connections in this prefrontal network was associated with the DSST and word recognition performance in the patient

  4. Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

    Directory of Open Access Journals (Sweden)

    Manjunath Patel Gowdru Chandrashekarappa

    2014-01-01

    Full Text Available The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN and genetic algorithm neural network (GA-NN. The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs.

  5. System of Systems Engineering and Integration Process for Network Transport Assessment

    Science.gov (United States)

    2016-09-01

    through the process to ensure oversight of design and tradeoff decisions for network throughput analyses. 14. SUBJECT TERMS network transport , SoS... Distribution is unlimited. SYSTEM OF SYSTEMS ENGINEERING AND INTEGRATION PROCESS FOR NETWORK TRANSPORT ASSESSMENT Matthew B. Rambo Civilian...engineering processes to utilize to address network transport design and testing? 2. How can SoS data throughput requirements be identified and

  6. Network and Database Security: Regulatory Compliance, Network, and Database Security - A Unified Process and Goal

    Directory of Open Access Journals (Sweden)

    Errol A. Blake

    2007-12-01

    Full Text Available Database security has evolved; data security professionals have developed numerous techniques and approaches to assure data confidentiality, integrity, and availability. This paper will show that the Traditional Database Security, which has focused primarily on creating user accounts and managing user privileges to database objects are not enough to protect data confidentiality, integrity, and availability. This paper is a compilation of different journals, articles and classroom discussions will focus on unifying the process of securing data or information whether it is in use, in storage or being transmitted. Promoting a change in Database Curriculum Development trends may also play a role in helping secure databases. This paper will take the approach that if one make a conscientious effort to unifying the Database Security process, which includes Database Management System (DBMS selection process, following regulatory compliances, analyzing and learning from the mistakes of others, Implementing Networking Security Technologies, and Securing the Database, may prevent database breach.

  7. Ku-band signal design study. [space shuttle orbiter data processing network

    Science.gov (United States)

    Rubin, I.

    1978-01-01

    Analytical tools, methods and techniques for assessing the design and performance of the space shuttle orbiter data processing system (DPS) are provided. The computer data processing network is evaluated in the key areas of queueing behavior synchronization and network reliability. The structure of the data processing network is described as well as the system operation principles and the network configuration. The characteristics of the computer systems are indicated. System reliability measures are defined and studied. System and network invulnerability measures are computed. Communication path and network failure analysis techniques are included.

  8. Applying fuzzy analytic network process in quality function deployment model

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Afsharkazemi

    2012-08-01

    Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.

  9. Spiking modular neural networks: A neural network modeling approach for hydrological processes

    National Research Council Canada - National Science Library

    Kamban Parasuraman; Amin Elshorbagy; Sean K. Carey

    2006-01-01

    .... In this study, a novel neural network model called the spiking modular neural networks (SMNNs) is proposed. An SMNN consists of an input layer, a spiking layer, and an associator neural network layer...

  10. Distributed processing and temporal codes in neuronal networks.

    Science.gov (United States)

    Singer, Wolf

    2009-09-01

    The cerebral cortex presents itself as a distributed dynamical system with the characteristics of a small world network. The neuronal correlates of cognitive and executive processes often appear to consist of the coordinated activity of large assemblies of widely distributed neurons. These features require mechanisms for the selective routing of signals across densely interconnected networks, the flexible and context dependent binding of neuronal groups into functionally coherent assemblies and the task and attention dependent integration of subsystems. In order to implement these mechanisms, it is proposed that neuronal responses should convey two orthogonal messages in parallel. They should indicate (1) the presence of the feature to which they are tuned and (2) with which other neurons (specific target cells or members of a coherent assembly) they are communicating. The first message is encoded in the discharge frequency of the neurons (rate code) and it is proposed that the second message is contained in the precise timing relationships between individual spikes of distributed neurons (temporal code). It is further proposed that these precise timing relations are established either by the timing of external events (stimulus locking) or by internal timing mechanisms. The latter are assumed to consist of an oscillatory modulation of neuronal responses in different frequency bands that cover a broad frequency range from 40 Hz (gamma) and ripples. These oscillations limit the communication of cells to short temporal windows whereby the duration of these windows decreases with oscillation frequency. Thus, by varying the phase relationship between oscillating groups, networks of functionally cooperating neurons can be flexibly configurated within hard wired networks. Moreover, by synchronizing the spikes emitted by neuronal populations, the saliency of their responses can be enhanced due to the coincidence sensitivity of receiving neurons in very much the same way as

  11. Measurement of company effectiveness using analytic network process method

    Directory of Open Access Journals (Sweden)

    Goran Janjić

    2017-07-01

    Full Text Available The sustainable development of an organisation is monitored through the organisation’s performance, which beforehand incorporates all stakeholders’ requirements in its strategy. The strategic management concept enables organisations to monitor and evaluate their effectiveness along with efficiency by monitoring of the implementation of set strategic goals. In the process of monitoring and measuring effectiveness, an organisation can use multiple-criteria decision-making methods as help. This study uses the method of analytic network process (ANP to define the weight factors of the mutual influences of all the important elements of an organisation’s strategy. The calculation of an organisation’s effectiveness is based on the weight factors and the degree of fulfilment of the goal values of the strategic map measures. New business conditions influence the changes in the importance of certain elements of an organisation’s business in relation to competitive advantage on the market, and on the market, increasing emphasis is given to non-material resources in the process of selection of the organisation’s most important measures.

  12. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Directory of Open Access Journals (Sweden)

    Mauricio Herrera

    Full Text Available There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  13. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Science.gov (United States)

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  14. Measurement of company effectiveness using analytic network process method

    Science.gov (United States)

    Goran, Janjić; Zorana, Tanasić; Borut, Kosec

    2017-07-01

    The sustainable development of an organisation is monitored through the organisation's performance, which beforehand incorporates all stakeholders' requirements in its strategy. The strategic management concept enables organisations to monitor and evaluate their effectiveness along with efficiency by monitoring of the implementation of set strategic goals. In the process of monitoring and measuring effectiveness, an organisation can use multiple-criteria decision-making methods as help. This study uses the method of analytic network process (ANP) to define the weight factors of the mutual influences of all the important elements of an organisation's strategy. The calculation of an organisation's effectiveness is based on the weight factors and the degree of fulfilment of the goal values of the strategic map measures. New business conditions influence the changes in the importance of certain elements of an organisation's business in relation to competitive advantage on the market, and on the market, increasing emphasis is given to non-material resources in the process of selection of the organisation's most important measures.

  15. Final Design Report for the RH LLW Disposal Facility (RDF) Project

    Energy Technology Data Exchange (ETDEWEB)

    Austad, Stephanie Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    The RH LLW Disposal Facility (RDF) Project was designed by AREVA Federal Services (AFS) and the design process was managed by Battelle Energy Alliance (BEA) for the Department of Energy (DOE). The final design report for the RH LLW Disposal Facility Project is a compilation of the documents and deliverables included in the facility final design.

  16. Final Design Report for the RH LLW Disposal Facility (RDF) Project

    Energy Technology Data Exchange (ETDEWEB)

    Austad, S. L. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-05-01

    The RH LLW Disposal Facility (RDF) Project was designed by AREVA Federal Services (AFS) and the design process was managed by Battelle Energy Alliance (BEA) for the Department of Energy (DOE). The final design report for the RH LLW Disposal Facility Project is a compilation of the documents and deliverables included in the facility final design.

  17. Photocatalytic evaluation of self-assembled porous network structure of ferric oxide film fabricated by dry deposition process

    Energy Technology Data Exchange (ETDEWEB)

    Park, Yunchan; Kim, Hyungsub; Lee, Geon-Yong; Pawar, Rajendra C.; Lee, Jai-Sung; Lee, Caroline Sunyong, E-mail: sunyonglee@hanyang.ac.kr

    2016-09-15

    Ferric oxide powder in the alpha phase (α-Fe{sub 2}O{sub 3}) was deposited on an aluminum oxide (Al{sub 2}O{sub 3}) substrate by a nanoparticle deposition system using the dry deposition method. X-ray diffraction (XRD) images confirmed that the phase of the deposited α-Fe{sub 2}O{sub 3} did not change. The deposited α-Fe{sub 2}O{sub 3} was characterized in terms of its microstructure using scanning electron microscopy (SEM). A porous network microstructure formed when small agglomerates of Fe{sub 2}O{sub 3} (SAF) were deposited. The deposition and formation mechanism of the microstructure were investigated using SEM and three-dimensional (3D) profile analysis. First, a dense coating layer formed when the film was thinner than the particle size. After that, as the film thickness increased to over 5 μm, the porous network structure formed by excavating the surface of the coating layer as it was bombarded by particles. Rhodamine B (RhB) was degraded after 6 h of exposure to the Fe{sub 2}O{sub 3} coating layer with SAF, which has good photocatalytic activity and a high porous network structure. The kinetic rate constants of the SAF and large agglomerates of Fe{sub 2}O{sub 3} (LAF) were calculated to be 0.197(h{sup −1}) and 0.128(h{sup −1}), respectively, based on the absorbance results. Using linear sweep voltammetry, we confirmed that the photoelectric effect occurred in the coating layer by measuring the resulting current under illuminated and dark conditions. - Graphical abstract: Self-assembled porous photocatalytic film fabricated by dry deposition method for water purification. - Highlights: • Different sizes of Fe{sub 2}O{sub 3} agglomerates were used to form porous network structure. • Fe{sub 2}O{sub 3} agglomerate particles were deposited using solvent-free process. • Self-assembled porous network microstructure formed better with small agglomerates of Fe{sub 2}O{sub 3}. • Fabricated porous network structure showed its potential to be used

  18. Factorized time-dependent distributions for certain multiclass queueing networks and an application to enzymatic processing networks

    Science.gov (United States)

    Mather, W.H.; Hasty, J.; Tsimring, L.S.

    2013-01-01

    Motivated by applications in biological systems, we show for certain multiclass queueing networks that time-dependent distributions for the multiclass queue-lengths can have a factorized form which reduces the problem of computing such distributions to a similar problem for related single-class queueing networks. We give an example of the application of this result to an enzymatic processing network. PMID:24596432

  19. Extracting knowledge from supervised neural networks in image processing

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, Lambert; Jain, R.; Abraham, A.; Faucher, C.; van der Zwaag, B.J.

    Despite their success-story, artificial neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a “magic tool��? but possibly even more as a

  20. Evaluating the Performance of Taiwan Homestay Using Analytic Network Process

    Directory of Open Access Journals (Sweden)

    Yi-Chung Hu

    2012-01-01

    Full Text Available Homestay industry in Taiwan is not only thriving, but also its operation is moving gradually toward elaboration strategy and in a specialized-operation manner these years. Nevertheless, the evaluation frameworks of the earlier studies were sporadically constructed from an overall perspective of homestays. Moreover, the functions, operational model, and natures of homestays are dissimilar to those of hotels; therefore, if the evaluation criteria of homestays employ the ones of hotels, it would appear to be incoherent and incompatible. This study has accordingly developed and constructed a set of evaluation indicators tailor-made for homestay sector through discussion of literatures and interviewing experts so that the evaluation framework would be more comprehensive and more practical. In the process of interviewing experts, it was discovered that dependences lay on the aspects and criteria. Consequently, this research chose the ANP (analytic network process to get the weights and, further, to acquire the homestay business performance through fuzzy theory. The result reveals, as regards key aspects, homestay proprietors and customer groups both weight the surroundings of the building and features, service quality, operation, and management most. In respect to overall homestay performance, customer groups consider it has reached the satisfactory level.

  1. Functional reconstitution into liposomes of purified human RhCG ammonia channel.

    Directory of Open Access Journals (Sweden)

    Isabelle Mouro-Chanteloup

    Full Text Available BACKGROUND: Rh glycoproteins (RhAG, RhBG, RhCG are members of the Amt/Mep/Rh family which facilitate movement of ammonium across plasma membranes. Changes in ammonium transport activity following expression of Rh glycoproteins have been described in different heterologous systems such as yeasts, oocytes and eukaryotic cell lines. However, in these complex systems, a potential contribution of endogenous proteins to this function cannot be excluded. To demonstrate that Rh glycoproteins by themselves transport NH(3, human RhCG was purified to homogeneity and reconstituted into liposomes, giving new insights into its channel functional properties. METHODOLOGY/PRINCIPAL FINDINGS: An HA-tag introduced in the second extracellular loop of RhCG was used to purify to homogeneity the HA-tagged RhCG glycoprotein from detergent-solubilized recombinant HEK293E cells. Electron microscopy analysis of negatively stained purified RhCG-HA revealed, after image processing, homogeneous particles of 9 nm diameter with a trimeric protein structure. Reconstitution was performed with sphingomyelin, phosphatidylcholine and phosphatidic acid lipids in the presence of the C(12E(8 detergent which was subsequently removed by Biobeads. Control of protein incorporation was carried out by freeze-fracture electron microscopy. Particle density in liposomes was a function of the Lipid/Protein ratio. When compared to empty liposomes, ammonium permeability was increased two and three fold in RhCG-proteoliposomes, depending on the Lipid/Protein ratio (1/300 and 1/150, respectively. This strong NH(3 transport was reversibly inhibited by mercuric and copper salts and exhibited a low Arrhenius activation energy. CONCLUSIONS/SIGNIFICANCE: This study allowed the determination of ammonia permeability per RhCG monomer, showing that the apparent Punit(NH3 (around 1x10(-3 microm(3xs(-1 is close to the permeability measured in HEK293E cells expressing a recombinant human RhCG (1.60x10

  2. RhMKK9, a rose MAP KINASE KINASE gene, is involved in rehydration-triggered ethylene production in rose gynoecia.

    Science.gov (United States)

    Chen, Jiwei; Zhang, Qian; Wang, Qigang; Feng, Ming; Li, Yang; Meng, Yonglu; Zhang, Yi; Liu, Guoqin; Ma, Zhimin; Wu, Hongzhi; Gao, Junping; Ma, Nan

    2017-02-23

    Flower opening is an important process in the life cycle of flowering plants and is influenced by various endogenous and environmental factors. Our previous work demonstrated that rose (Rosa hybrida) flowers are highly sensitive to dehydration during flower opening and the water recovery process after dehydration induced ethylene production rapidly in flower gynoecia. In addition, this temporal- and spatial-specific ethylene production is attributed to a transient but robust activation of the rose MAP KINASE6-ACC SYNTHASE1 (RhMPK6-RhACS1) cascade in gynoecia. However, the upstream component of RhMPK6-RhACS1 is unknown, although RhMKK9 (MAP KINASE KINASE9), a rose homologue of Arabidopsis MKK9, could activate RhMPK6 in vitro. In this study, we monitored RhMKK2/4/5/9 expression, the potential upstream kinase to RhMPK6, in rose gynoecia during dehydration and rehydration. We found only RhMKK9 was rapidly and strongly induced by rehydration. Silencing of RhMKK9 significantly decreased rehydration-triggered ethylene production. Consistently, the expression of several ethylene-responsive genes was down regulated in the petals of RhMKK9-silenced flowers. Moreover, we detected the DNA methylation level in the promoter and gene body of RhMKK9 by Chop-PCR. The results showed that rehydration specifically elevated the DNA methylation level on the RhMKK9 gene body, whereas it resulted in hypomethylation in its promoter. Our results showed that RhMKK9 possibly acts as the upstream component of the RhMKK9-RhMPK6-RhACS1 cascade and is responsible for water recovery-triggered ethylene production in rose gynoecia, and epigenetic DNA methylation is involved in the regulation of RhMKK9 expression by rehydration.

  3. On the Network Convergence Process in RPL over IEEE 802.15.4 Multihop Networks: Improvement and Trade-Offs

    Directory of Open Access Journals (Sweden)

    Hamidreza Kermajani

    2014-07-01

    Full Text Available The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL has been recently developed by the Internet Engineering Task Force (IETF. Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs.

  4. On the network convergence process in RPL over IEEE 802.15.4 multihop networks: improvement and trade-offs.

    Science.gov (United States)

    Kermajani, Hamidreza; Gomez, Carles

    2014-07-07

    The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently developed by the Internet Engineering Task Force (IETF). Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs.

  5. Early stages of the mobile social network launch process

    OpenAIRE

    Viktorov, Dmitrii

    2014-01-01

    This thesis is concentrated on mobile social network development features and the industry of social networks. The company which this thesis is written for is Guesspoint Ltd. This company is working for the launch of the mobile social network with the same name. The company is based in St.-Petersburg, Russia, but the scale of the future operation is expected to be global. The theoretical part is focused on the scientific explanations of social phenomena and especially on the social networ...

  6. Financial risk analysis in the synthesis and design of processing networks: Balancing risk and return

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sin, Gürkan; Gani, Rafiqul

    2014-01-01

    The construction of a processing network is a corporate investment, that processing companies make with the goal of creating the conditions to increase their value. In a previous work, a computer-aided framework supporting the design of processing network under uncertainty has been presented...

  7. Dense distributed processing in a hindlimb scratch motor network

    DEFF Research Database (Denmark)

    Guzulaitis, Robertas; Hounsgaard, Jørn Dybkjær

    2014-01-01

    In reduced preparations, hindlimb movements can be generated by a minimal network of neurons in the limb innervating spinal segments. The network of neurons that generates real movements is less well delineated. In an ex vivo carapace-spinal cord preparation from adult turtles (Trachemys scripta...... elegans), we show that ventral horn interneurons in mid-thoracic spinal segments are functionally integrated in the hindlimb scratch network. First, mid-thoracic interneurons receive intense synaptic input during scratching and behave like neurons in the hindlimb enlargement. Second, some mid...... of a distributed motor network that secures motor coherence....

  8. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks

    Directory of Open Access Journals (Sweden)

    Francisco eAboitiz

    2014-03-01

    Full Text Available A cardinal symptom of Attenion Deficit and Hyperactivity Disorder (ADHD is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the Default Mode Network (DMN. Related networks are the ventral attentional network (VAN involved in attentional shifting, and the salience network (SN related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produce an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.

  9. Rh Variability in Multi-Ethnic Perspective: Consequences for RH Genotyping

    NARCIS (Netherlands)

    G.H.M. Tax

    2006-01-01

    textabstractThe RhD bloodgroup was first described by Levine en Stetson in 1939 after the manifestation of a hemolytic transfusion reaction in a woman who recently gave birth, after transfusion with her husbands red cells. The RhD-negative woman produced antibodies against the RhD present on the

  10. An isolated nitridyl radical-bridged {Rh(N.)Rh} complex

    NARCIS (Netherlands)

    Gloaguen, Yann; Rebreyend, Christophe; Lutz, Martin|info:eu-repo/dai/nl/304828971; Kumar, Pravin; Huber, Martina; Vandervlugt, Jarl Ivar; Schneider, Sven; Debruin, Bas

    2014-01-01

    Photochemical activation of [(PNNH)Rh(N3)] (PNNH=6-di-(tert- butyl)phosphinomethyl-2,2′-bipyridine) complex2 produced the paramagnetic (S=1/2), [(PNN)Rh-N.-Rh(PNN)] complex3 (PNN-=methylene- deprotonated PNNH), which could be crystallographically characterized. Spectroscopic investigation of 3

  11. GnRH-agonist versus GnRH-antagonist IVF cycles

    DEFF Research Database (Denmark)

    Papanikolaou, E G; Pados, G; Grimbizis, G

    2012-01-01

    In view of the current debate concerning possible differences in efficacy between the two GnRH analogues used in IVF stimulated cycles, the current study aimed to explore whether progesterone control in the late follicular phase differs when GnRH antagonist is used as compared with GnRH agonist...

  12. Using analytic network process for evaluating mobile text entry methods.

    Science.gov (United States)

    Ocampo, Lanndon A; Seva, Rosemary R

    2016-01-01

    This paper highlights a preference evaluation methodology for text entry methods in a touch keyboard smartphone using analytic network process (ANP). Evaluation of text entry methods in literature mainly considers speed and accuracy. This study presents an alternative means for selecting text entry method that considers user preference. A case study was carried out with a group of experts who were asked to develop a selection decision model of five text entry methods. The decision problem is flexible enough to reflect interdependencies of decision elements that are necessary in describing real-life conditions. Results showed that QWERTY method is more preferred than other text entry methods while arrangement of keys is the most preferred criterion in characterizing a sound method. Sensitivity analysis using simulation of normally distributed random numbers under fairly large perturbation reported the foregoing results reliable enough to reflect robust judgment. The main contribution of this paper is the introduction of a multi-criteria decision approach in the preference evaluation of text entry methods. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  13. Supercritical boiler material selection using fuzzy analytic network process

    Directory of Open Access Journals (Sweden)

    Saikat Ranjan Maity

    2012-08-01

    Full Text Available The recent development of world is being adversely affected by the scarcity of power and energy. To survive in the next generation, it is thus necessary to explore the non-conventional energy sources and efficiently consume the available sources. For efficient exploitation of the existing energy sources, a great scope lies in the use of Rankin cycle-based thermal power plants. Today, the gross efficiency of Rankin cycle-based thermal power plants is less than 28% which has been increased up to 40% with reheating and regenerative cycles. But, it can be further improved up to 47% by using supercritical power plant technology. Supercritical power plants use supercritical boilers which are able to withstand a very high temperature (650-720˚C and pressure (22.1 MPa while producing superheated steam. The thermal efficiency of a supercritical boiler greatly depends on the material of its different components. The supercritical boiler material should possess high creep rupture strength, high thermal conductivity, low thermal expansion, high specific heat and very high temperature withstandability. This paper considers a list of seven supercritical boiler materials whose performance is evaluated based on seven pivotal criteria. Given the intricacy and difficulty of this supercritical boiler material selection problem having interactions and interdependencies between different criteria, this paper applies fuzzy analytic network process to select the most appropriate material for a supercritical boiler. Rene 41 is the best supercritical boiler material, whereas, Haynes 230 is the worst preferred choice.

  14. Gaussian process regression for sensor networks under localization uncertainty

    Science.gov (United States)

    Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

    2013-01-01

    In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

  15. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    Directory of Open Access Journals (Sweden)

    Levente L Orbán

    Full Text Available Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  16. Traffic characteristics analysis in optical burst switching networks with optical label processing

    Directory of Open Access Journals (Sweden)

    Edson Moschim

    2007-03-01

    Full Text Available An analysis is carried out with burst-switching optical networks which use label processing consisting of orthogonal optical codes (OOC, considering traffic characteristics such as length/duration and arrival rate of bursts. Main results show that the use of OOC label processing influences on the decrease of burst loss probability, especially for short-lived bursts. Therefore, short bursts that would be blocked in conventional electronic processing networks are transmitted when the OOC label processing is used. Thus, an increase in the network use occurs as well as a decrease in the burst transmission latency, reaching a granularity close to packets networks.

  17. Complex Network Structure Influences Processing in Long-Term and Short-Term Memory

    Science.gov (United States)

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological…

  18. RH ISOIMMUNIZATION BY MULTIPLE ANTIGENS

    OpenAIRE

    Mesquita, S.; Proença, E.; Alexandrino, A.

    2005-01-01

    RESUMO A doença hemolítica perinatal isoimune (DHP) resulta da destruição dos eritrócitos fetais e do recém-nascido por anticorpos maternos dirigidos especificamente contra os antigénios de membrana dessas células. Os autores apresentam um caso de isoimunização Rh a antigénios múltiplos, anti-C, D e E, num 2º filho de um casal com antecedentes de abortamento espontâneo e um 1º filho com DHP anti- CDE e necessidade de transfusão permuta. Apesar da gravidade, com necessidade de várias tra...

  19. The redesign of a warranty distribution network with recovery processes

    NARCIS (Netherlands)

    Ashayeri, J.; Ma, N.; Sotirov, R.

    A warranty distribution network provides aftersales warranty services to customers and resembles a closed-loop supply chain network with specific challenges for reverse flows management like recovery, repair, and reflow of refurbished products. We present here a nonlinear and nonconvex mixed integer

  20. Collaborative Wireless Sensor Networks in Industrial and Business Processes

    NARCIS (Netherlands)

    Marin Perianu, Mihai

    2008-01-01

    Personal computers, mobile telephony and the Internet made the vision of everyone being networked real, at such a level of quality and speed that people could only dream of, one hundred years ago. Nowadays, another dream starts to become reality: the dream of networking everything. The limits of

  1. The Rh complex exports ammonium from human red blood cells

    NARCIS (Netherlands)

    Hemker, Mirte B.; Cheroutre, Goedele; van Zwieten, Rob; Maaskant-van Wijk, Petra A.; Roos, Dirk; Loos, Johannes A.; van der Schoot, C. Ellen; von dem Borne, Albert E. G. Kr

    2003-01-01

    The Rh blood group system represents a major immunodominant protein complex on red blood cells (RBC). Recently, the Rh homologues RhAG and RhCG were shown to promote ammonium ion transport in yeast. In this study, we showed that also in RBC the human Rh complex functions as an exporter of ammonium

  2. Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

    Directory of Open Access Journals (Sweden)

    Juan F. Monsalve-Posada

    2015-01-01

    Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

  3. Genetics of Isolated Hypogonadotropic Hypogonadism: Role of GnRH Receptor and Other Genes

    Directory of Open Access Journals (Sweden)

    Karges Beate

    2012-01-01

    Full Text Available Hypothalamic gonadotropin releasing hormone (GnRH is a key player in normal puberty and sexual development and function. Genetic causes of isolated hypogonadotropic hypogonadism (IHH have been identified during the recent years affecting the synthesis, secretion, or action of GnRH. Developmental defects of GnRH neurons and the olfactory bulb are associated with hyposmia, rarely associated with the clinical phenotypes of synkinesia, cleft palate, ear anomalies, or choanal atresia, and may be due to mutations of KAL1, FGFR1/FGF8, PROKR2/PROK2, or CHD7. Impaired GnRH secretion in normosmic patients with IHH may be caused by deficient hypothalamic GPR54/KISS1, TACR3/TAC3, and leptinR/leptin signalling or mutations within the GNRH1 gene itself. Normosmic IHH is predominantly caused by inactivating mutations in the pituitary GnRH receptor inducing GnRH resistance, while mutations of the β-subunits of LH or FSH are very rare. Inheritance of GnRH deficiency may be oligogenic, explaining variable phenotypes. Future research should identify additional genes involved in the complex network of normal and disturbed puberty and reproduction.

  4. Building the process-drug–side effect network to discover the relationship between biological Processes and side effects

    Science.gov (United States)

    2011-01-01

    Background Side effects are unwanted responses to drug treatment and are important resources for human phenotype information. The recent development of a database on side effects, the side effect resource (SIDER), is a first step in documenting the relationship between drugs and their side effects. It is, however, insufficient to simply find the association of drugs with biological processes; that relationship is crucial because drugs that influence biological processes can have an impact on phenotype. Therefore, knowing which processes respond to drugs that influence the phenotype will enable more effective and systematic study of the effect of drugs on phenotype. To the best of our knowledge, the relationship between biological processes and side effects of drugs has not yet been systematically researched. Methods We propose 3 steps for systematically searching relationships between drugs and biological processes: enrichment scores (ES) calculations, t-score calculation, and threshold-based filtering. Subsequently, the side effect-related biological processes are found by merging the drug-biological process network and the drug-side effect network. Evaluation is conducted in 2 ways: first, by discerning the number of biological processes discovered by our method that co-occur with Gene Ontology (GO) terms in relation to effects extracted from PubMed records using a text-mining technique and second, determining whether there is improvement in performance by limiting response processes by drugs sharing the same side effect to frequent ones alone. Results The multi-level network (the process-drug-side effect network) was built by merging the drug-biological process network and the drug-side effect network. We generated a network of 74 drugs-168 side effects-2209 biological process relation resources. The preliminary results showed that the process-drug-side effect network was able to find meaningful relationships between biological processes and side effects in an

  5. Note: Large area deposition of Rh single and Rh/W/Cu multilayer thin films on stainless steel substrate by pulsed laser deposition technique

    Science.gov (United States)

    Mostako, A. T. T.; Khare, Alika

    2014-04-01

    Mirror like thin films of single layer Rh and multilayer Rh/W/Cu are deposited on highly polished 50 mm diameter stainless steel substrate by Pulsed Laser Deposition (PLD) technique for first mirror application in fusion reactors. For this, the conventional PLD technique has been modified by incorporating substrate rastering stage for large area deposition via PLD. Process optimization to achieve uniformity of deposition as estimated from fringe visibility and thickness is also discussed.

  6. Neural Networks as a Tool for Georadar Data Processing

    Directory of Open Access Journals (Sweden)

    Szymczyk Piotr

    2015-12-01

    Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

  7. Evolutionary Conservation and Diversification of Rh Family Genes and Proteins

    National Research Council Canada - National Science Library

    Cheng-Han Huang; Jianbin Peng

    2005-01-01

    .... In the latter view, Rh and Amt are different biological gas channels. To reconstruct the phytogeny of the Rh family and study its coexistence with and relationship to Amt in depth, we analyzed 111 Rh genes and 260 Amt genes...

  8. Finding the Sweet Spot: Network Structures and Processes for Increased Knowledge Mobilization

    Directory of Open Access Journals (Sweden)

    Patricia Briscoe

    2016-06-01

    Full Text Available The use of networks in public education is one of a number of knowledge mobilization (KMb strategies utilized to promote evidence-based research into practice. However, challenges exist in the ability to effectively mobilizing knowledge through external partnership networks. The purpose of this paper is to further explore how networks work. Data was collected from virtual discussions for an interim report for a province-wide government initiative. A secondary analysis of the data was performed. The findings present network structures and processes that partners were engaged in when building a network within education. The implications of this study show that building a network for successful outcomes is complex and metaphorically similar to finding the “sweet spot.” It is challenging but networks that used strategies to align structures and processes proved to achieve more success in mobilizing research to practice.

  9. Exogenous Kisspeptin Administration as a Probe of GnRH Neuronal Function in Patients With Idiopathic Hypogonadotropic Hypogonadism

    Science.gov (United States)

    Chan, Yee-Ming; Lippincott, Margaret F.; Butler, James P.; Sidhoum, Valerie F.; Li, Cindy X.; Plummer, Lacey

    2014-01-01

    Context: Idiopathic hypogonadotropic hypogonadism (IHH) results from defective synthesis, secretion, or action of GnRH. Kisspeptin is a potent stimulus for GnRH secretion. Objective: We probed the functional capacity of the GnRH neuronal network in patients with IHH. Participants: Eleven subjects with congenital IHH (9 men and 2 women) and one male subject who underwent reversal of IHH were studied. Six of the twelve subjects had an identified genetic cause of their IHH: KAL1 (n = 1), FGFR1 (n = 3), PROKR2 (n = 1), GNRHR (n = 1). Intervention: Subjects underwent q10 min blood sampling to measure GnRH-induced LH secretion at baseline and in response to intravenous boluses of kisspeptin (0.24 nmol/kg) and GnRH (75 ng/kg) both pre- and post-six days of treatment with exogenous GnRH (25 ng/kg sc every 2 h). Results: All subjects with abiding IHH failed to demonstrate a GnRH-induced LH response to exogenous kisspeptin. In contrast, the subject who achieved reversal of his hypogonadotropism demonstrated a robust response to kisspeptin. Conclusions: The functional capacity of the GnRH neuronal network in IHH patients is impaired, as evidenced by their inability to respond to the same dose of kisspeptin that effects a robust GnRH-induced LH response in healthy men and luteal-phase women. This impairment is observed across a range of genotypes, suggesting that it reflects a fundamental property of GnRH neuronal networks that have not been properly engaged during pubertal development. In contrast, a patient who had experienced reversal of his hypogonadotropism responded to exogenous kisspeptin. PMID:25226293

  10. Proceedings of the IEEE 2003 Neural Networks for Signal Processing Workshop

    DEFF Research Database (Denmark)

    Larsen, Jan

    methodology and real-world application domains and is widely entering into everyday solutions adopted by research and industry, going far beyond “traditional” neural networks and academic examples. As reflected in this collection, contemporary neural networks for signal processing combine many ideas from......This proceeding contains refereed papers presented at the thirteenth IEEE Workshop on Neural Networks for Signal Processing (NNSP’2003), held at the Atria-Mercure Conference Center, Toulouse, France, September 17-19, 2003. The Neural Networks for Signal Processing Technical Committee of the IEEE...... Signal Processing Society organized the workshop with sponsorship of the Signal Processing Society and the co-operation of the IEEE Neural Networks Society. The IEEE Press published the previous twelve volumes of the NNSP Workshop proceedings in a hardbound volume. This year, the bound volume...

  11. Assortative and modular networks are shaped by adaptive synchronization processes.

    Science.gov (United States)

    Avalos-Gaytán, Vanesa; Almendral, Juan A; Papo, David; Schaeffer, Satu Elisa; Boccaletti, Stefano

    2012-07-01

    Modular organization and degree-degree correlations are ubiquitous in the connectivity structure of biological, technological, and social interacting systems. So far most studies have concentrated on unveiling both features in real world networks, but a model that succeeds in generating them simultaneously is needed. We consider a network of interacting phase oscillators, and an adaptation mechanism for the coupling that promotes the connection strengths between those elements that are dynamically correlated. We show that, under these circumstances, the dynamical organization of the oscillators shapes the topology of the graph in such a way that modularity and assortativity features emerge spontaneously and simultaneously. In turn, we prove that such an emergent structure is associated with an asymptotic arrangement of the collective dynamical state of the network into cluster synchronization.

  12. S-TSP: a novel routing algorithm for In-network processing of recursive computation in wireless sensor networks

    Science.gov (United States)

    Tang, Tingfang; Guo, Peng; Liu, Xuefeng

    2016-10-01

    In-network processing is an efficient way to reduce the transmission cost in wireless sensor networks (WSNs). The in-network processing of many domain-specific computation tasks in WSNs usually requires to losslessly distribute the computation of the tasks into the sensor nodes, which is however usually not easy. In this paper we are concerned with such kind of tasks whose computation can only be partitioned into recursive computation mode. To distribute the recursive computations into WSNs, it is required to design an appropriate single in-network processing path, along which the intermediate data is forwarded and updated in the WSNs. We address the recursive computation with constant size of computation result, e.g., distributed least square estimation (D-LSE). Finding the optimal in-network processing path to minimize the total transmission cost in WSNs, is a new problem and seldom studied before. To solve it, we propose a novel routing algorithm called as S-TSP, and compare it with some other greedy algorithms. Extensive simulations are conducted, and the results show the good performance of the proposed S-TSP algorithm.

  13. Reliable test for prenatal prediction of fetal RhD type using maternal plasma from RhD negative women

    DEFF Research Database (Denmark)

    Clausen, Frederik Banch; Krog, Grethe Risum; Rieneck, Klaus

    2005-01-01

    The objective of this study was to establish a reliable test for prenatal prediction of fetal RhD type using maternal plasma from RhD negative women. This test is needed for future prenatal Rh prophylaxis.......The objective of this study was to establish a reliable test for prenatal prediction of fetal RhD type using maternal plasma from RhD negative women. This test is needed for future prenatal Rh prophylaxis....

  14. A RhABF2/Ferritin module affects rose (Rosa hybrida) petal dehydration tolerance and senescence by modulating iron levels.

    Science.gov (United States)

    Liu, Jitao; Fan, Youwei; Zou, Jing; Fang, Yiqun; Wang, Linghao; Wang, Meng; Jiang, Xinqiang; Liu, Yiqing; Gao, Junping; Zhang, Changqing

    2017-12-01

    Plants often develop the capacity to tolerate moderate and reversible environmental stresses, such as drought, and to re-establish normal development once the stress has been removed. An example of this phenomenon is provided by cut rose (Rosa hybrida) flowers, which experience typical reversible dehydration stresses during post-harvest handling after harvesting at the bud stages. The molecular mechanisms involved in rose flower dehydration tolerance are not known, however. Here, we characterized a dehydration- and abscisic acid (ABA)-induced ferritin gene (RhFer1). Dehydration-induced free ferrous iron (Fe 2+ ) is preferentially sequestered by RhFer1 and not transported outside of the petal cells, to restrict oxidative stresses during dehydration. Free Fe 2+ accumulation resulted in more serious oxidative stresses and the induction of genes encoding antioxidant enzyme in RhFer1-silenced petals, and poorer dehydration tolerance was observed compared with tobacco rattle virus (TRV) controls. We also determined that RhABF2, an AREB/ABF transcription factor involved in the ABA signaling pathway, can activate RhFer1 expression by directly binding to its promoter. The silencing of RhABF2 decreased dehydration tolerance and disrupted Fe homeostasis in rose petals during dehydration, as did the silencing of RhFer1. Although both RhFer1 and Fe transporter genes are induced during flower natural senescence in plants, the silencing of RhABF2 or RhFer1 accelerates the petal senescence processes. These results suggest that the regulatory module RhABF2/RhFer1 contributes to the maintenance of Fe levels and enhances dehydration tolerance through the action of RhFer1 locally sequestering free Fe 2+ under dehydration conditions, and plays synergistic roles with transporter genes during flower senescence. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  15. The rhesus protein RhCG: a new perspective in ammonium transport and distal urinary acidification.

    Science.gov (United States)

    Wagner, Carsten A; Devuyst, Olivier; Belge, Hendrica; Bourgeois, Soline; Houillier, Pascal

    2011-01-01

    Urinary acidification is a complex process requiring the coordinated action of enzymes and transport proteins and resulting in the removal of acid and the regeneration of bicarbonate. Proton secretion is mediated by luminal H(+)-ATPases and requires the parallel movement of NH₃, and its protonation to NH₄(+), to provide sufficient buffering. It has been long assumed that ammonia secretion is a passive process occurring by means of simple diffusion driven by the urinary trapping of ammonium. However, new data indicate that mammalian cells possess specific membrane proteins from the family of rhesus proteins involved in ammonia/μm permeability. Rhesus proteins were first identified in yeast and later also in plants, algae, and mammals. In rodents, RhBG and RhCG are expressed in the collecting duct, whereas in humans only RhCG was detected. Their expression increases with maturation of the kidney and accelerates after birth in parallel with other acid-base transport proteins. Deletion of RhBG in mice had no effect on renal ammonium excretion, whereas RhCG deficiency reduces renal ammonium secretion strongly, causes metabolic acidosis in acid-challenged mice, and impairs restoration of normal acid-base status. Microperfusion experiments or functional reconstitution in liposomes demonstrates that ammonia is the most likely substrate of RhCG. Similarly, crystal structures of human RhCG and the homologous bacterial AmtB protein suggest that these proteins may form gas channels.

  16. Artificial neural networks in variable process control: application in particleboard manufacture

    Energy Technology Data Exchange (ETDEWEB)

    Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

    2009-07-01

    Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

  17. Behavior of feral horses in response to culling and GnRH immunocontraception

    Science.gov (United States)

    Ransom, Jason I.; Powers, Jenny G.; Garbe, Heidi M.; Oehler, Michael W.; Nett, Terry M.; Baker, Dan L.

    2014-01-01

    Wildlife management actions can alter fundamental behaviors of individuals and groups,which may directly impact their life history parameters in unforeseen ways. This is especially true for highly social animals because changes in one individual’s behavior can cascade throughout its social network. When resources to support populations of social animals are limited and populations become locally overabundant, managers are faced with the daunting challenge of decreasing population size without disrupting core behavioral processes. Increasingly, managers are turning to fertility control technologies to supplement culling in efforts to suppress population growth, but little is quantitatively known about how either of these management tools affects behavior. Gonadotropin releasing hormone (GnRH) is a small neuropeptide that performs an obligatory role in mammalian reproduction and has been formulated into the immunocontraceptive GonaCon-BTM. We investigated the influences of this vaccine on behavior of feral horses (Equus caballus) at Theodore Roosevelt National Park, North Dakota, USA, for a year preceding and a year following nonlethal culling and GnRH-vaccine treatment. We observed horses during the breeding season and found only minimal differences in time budget behaviors of free-ranging female feral horses treated with GnRH and those treated with saline. The differences observed were consistent with the metabolic demands of pregnancy and lactation. We observed similar social behaviors between treatment groups, reflecting limited reproductive behavior among control females due to high rates of pregnancy and suppressed reproductive behavior among treated females due to GnRH-inhibited ovarian activity. In the treatment year, band stallion age was the only supported factor influencing herding behavior (P stallions decreased 50.7% following treatment and culling (P reproductive, and agonistic behavior in the year following culling and treatment (P < 0.04). These

  18. Social Networks as Information Source for the Purchase Decision Process

    Directory of Open Access Journals (Sweden)

    Camila Leoni Nascimento

    2014-12-01

    Full Text Available The social networks have caused changes in the consumption habits and in the ways of relationship among companies and consumers, emerging a more demanding and informed consumer. In this paper it is aimed to assess the social networks as a source of information for the purchase of goods or services. In the study it was applied a research of exploratory nature through the survey method, conducted through personal interviews using a questionnaire with closed-ended questions. The sample of non-probabilistic type was comprised of 200 individuals from a higher education institution of São Paulo State hinterland. The survey data were analyzed descriptively. Overall, the results showed the use of social networks as a source of information search, in which the main motive is the practicality. The results corroborate the studies of Kotler and Keller (2006 when they state that the consumer seeks information on social networks to help him in the purchase, as Edelman and Hirshberg (2006 when approaching the user confidence in their friends’ opinion. For future works it is recommended to check what strategies and in what ways the companies could work in order to provide more detailed data to Internet users, aiming to support them in the decision

  19. Processing of Feature Selectivity in Cortical Networks with Specific Connectivity.

    Directory of Open Access Journals (Sweden)

    Sadra Sadeh

    Full Text Available Although non-specific at the onset of eye opening, networks in rodent visual cortex attain a non-random structure after eye opening, with a specific bias for connections between neurons of similar preferred orientations. As orientation selectivity is already present at eye opening, it remains unclear how this specificity in network wiring contributes to feature selectivity. Using large-scale inhibition-dominated spiking networks as a model, we show that feature-specific connectivity leads to a linear amplification of feedforward tuning, consistent with recent electrophysiological single-neuron recordings in rodent neocortex. Our results show that optimal amplification is achieved at an intermediate regime of specific connectivity. In this configuration a moderate increase of pairwise correlations is observed, consistent with recent experimental findings. Furthermore, we observed that feature-specific connectivity leads to the emergence of orientation-selective reverberating activity, and entails pattern completion in network responses. Our theoretical analysis provides a mechanistic understanding of subnetworks' responses to visual stimuli, and casts light on the regime of operation of sensory cortices in the presence of specific connectivity.

  20. Network resource selection for data transfer processes in scientific workflows

    NARCIS (Netherlands)

    Zhao, Z.; Grosso, P.; Koning, R.; van der Ham, J.; de Laat, C.

    2010-01-01

    Quality of the service (QoS) plays an important role in the life-cycle of scientific workflows for composing and executing applications. However, the quality of network services has so far rarely been considered in composing and executing scientific workflows. Currently, scientific applications tune

  1. RhHB1 mediates the antagonism of gibberellins to ABA and ethylene during rose (Rosa hybrida) petal senescence.

    Science.gov (United States)

    Lü, Peitao; Zhang, Changqing; Liu, Jitao; Liu, Xiaowei; Jiang, Guimei; Jiang, Xinqiang; Khan, Muhammad Ali; Wang, Liangsheng; Hong, Bo; Gao, Junping

    2014-05-01

    Rose (Rosa hybrida) is one of the most important ornamental plants worldwide; however, senescence of its petals terminates the ornamental value of the flower, resulting in major economic loss. It is known that the hormones abscisic acid (ABA) and ethylene promote petal senescence, while gibberellins (GAs) delay the process. However, the molecular mechanisms underlying the antagonistic effects amongst plant hormones during petal senescence are still unclear. Here we isolated RhHB1, a homeodomain-leucine zipper I transcription factor gene, from rose flowers. Quantitative RT-PCR and GUS reporter analyses showed that RhHB1 was strongly expressed in senescing petals, and its expression was induced by ABA or ethylene in petals. ABA or ethylene treatment clearly accelerated rose petal senescence, while application of the gibberellin GA3 delayed the process. However, silencing of RhHB1 delayed the ABA- or ethylene-mediated senescence, and resulted in higher petal anthocyanin levels and lower expression of RhSAG12. Moreover, treatment with paclobutrazol, an inhibitor of GA biosynthesis, repressed these delays. In addition, silencing of RhHB1 blocked the ABA- or ethylene-induced reduction in expression of the GA20 oxidase encoded by RhGA20ox1, a gene in the GA biosynthetic pathway. Furthermore, RhHB1 directly binds to the RhGA20ox1 promoter, and silencing of RhGA20ox1 promoted petal senescence. Eight senescence-related genes showed substantial differences in expression in petals after treatment with GA3 or paclobutrazol. These results suggest that RhHB1 mediates the antagonistic effect of GAs on ABA and ethylene during rose petal senescence, and that the promotion of petal senescence by ABA or ethylene operates through an RhHB1-RhGA20ox1 regulatory checkpoint. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

  2. Spin order and dynamics in the diamond-lattice Heisenberg antiferromagnets CuRh2O4 and CoRh2O4

    Science.gov (United States)

    Ge, L.; Flynn, J.; Paddison, J. A. M.; Stone, M. B.; Calder, S.; Subramanian, M. A.; Ramirez, A. P.; Mourigal, M.

    2017-08-01

    Antiferromagnetic insulators on a diamond lattice are candidate materials to host exotic magnetic phenomena ranging from spin-orbital entanglement to degenerate spiral ground states and topological paramagnetism. Compared to other three-dimensional networks of magnetic ions, such as the geometrically frustrated pyrochlore lattice, the investigation of diamond-lattice magnetism in real materials is less mature. In this work, we characterize the magnetic properties of model A -site spinels CoRh2O4 (cobalt rhodite) and CuRh2O4 (copper rhodite) by means of thermomagnetic and neutron-scattering measurements, and we perform group theory analysis, Rietveld refinement, mean-field theory, and spin-wave theory calculations to analyze the experimental results. Our investigation reveals that cubic CoRh2O4 is a canonical S =3 /2 diamond-lattice Heisenberg antiferromagnet with a nearest-neighbor exchange J =0.63 meV and a Néel ordered ground state below a temperature of 25 K. In tetragonally distorted CuRh2O4 , competing exchange interactions between up to third-nearest-neighbor spins lead to the development of an incommensurate spin helix at 24 K with a magnetic propagation vector km=(0 ,0 ,0.79 ) . Strong reduction of the ordered moment is observed for the S =1 /2 spins in CuRh2O4 and captured by our 1 /S corrections to the staggered magnetization. Our work identifies CoRh2O4 and CuRh2O4 as reference materials to guide future work searching for exotic quantum behavior in diamond-lattice antiferromagnets.

  3. A study on predicting network corrections in PPP-RTK processing

    Science.gov (United States)

    Wang, Kan; Khodabandeh, Amir; Teunissen, Peter

    2017-10-01

    In PPP-RTK processing, the network corrections including the satellite clocks, the satellite phase biases and the ionospheric delays are provided to the users to enable fast single-receiver integer ambiguity resolution. To solve the rank deficiencies in the undifferenced observation equations, the estimable parameters are formed to generate full-rank design matrix. In this contribution, we firstly discuss the interpretation of the estimable parameters without and with a dynamic satellite clock model incorporated in a Kalman filter during the network processing. The functionality of the dynamic satellite clock model is tested in the PPP-RTK processing. Due to the latency generated by the network processing and data transfer, the network corrections are delayed for the real-time user processing. To bridge the latencies, we discuss and compare two prediction approaches making use of the network corrections without and with the dynamic satellite clock model, respectively. The first prediction approach is based on the polynomial fitting of the estimated network parameters, while the second approach directly follows the dynamic model in the Kalman filter of the network processing and utilises the satellite clock drifts estimated in the network processing. Using 1 Hz data from two networks in Australia, the influences of the two prediction approaches on the user positioning results are analysed and compared for latencies ranging from 3 to 10 s. The accuracy of the positioning results decreases with the increasing latency of the network products. For a latency of 3 s, the RMS of the horizontal and the vertical coordinates (with respect to the ground truth) do not show large differences applying both prediction approaches. For a latency of 10 s, the prediction approach making use of the satellite clock model has generated slightly better positioning results with the differences of the RMS at mm-level. Further advantages and disadvantages of both prediction approaches are

  4. Critical behavior of the contact process in annealed scale-free networks

    OpenAIRE

    Noh, Jae Dong; Park, Hyunggyu

    2008-01-01

    Critical behavior of the contact process is studied in annealed scale-free networks by mapping it on the random walk problem. We obtain the analytic results for the critical scaling, using the event-driven dynamics approach. These results are confirmed by numerical simulations. The disorder fluctuation induced by the sampling disorder in annealed networks is also explored. Finally, we discuss over the discrepancy of the finite-size-scaling theory in annealed and quenched networks in spirit of...

  5. Complex network structure influences processing in long-term and short-term memory

    OpenAIRE

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological word-forms influenced retrieval from the mental lexicon (that portion of long-term memory dedicated to language) during the on-line recognition and producti...

  6. Social networks in the R&D process

    DEFF Research Database (Denmark)

    Dahl, Michael S.; Østergaard, Christian Richter

    2005-01-01

    Whether social networks diffuse knowledge across firm boundaries has been the topic of much debate. To inform these theories, this article considers two questions. First, who has contacts across firm boundaries? And second, when do these relations diffuse knowledge? Our empirical evidence comes...... from a survey of 346 engineers in the wireless communication industry around Aalborg in Northern Denmark. Our analysis finds that social contact between these engineers is frequent and is used to diffuse knowledge that receivers find useful. More experienced engineers are more likely to receive...... valuable knowledge from their networks. These findings show that the long-term relationships, which are more likely based on trust and reputation, are also more likely to be a channel valuable knowledge. (c) 2004 Elsevier B.V. All rights reserved....

  7. Digital Signal Processing and Control for the Study of Gene Networks.

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-22

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  8. Space-Time Processing for Tactical Mobile Ad Hoc Networks

    Science.gov (United States)

    2010-05-01

    results quantifying the impact of fading on average symbol and error probability (SEP/ BEP ) are available for various modulation schemes. However, in slow...interference and channel uncertainty issues have a tremendous impact 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 27-08-2010 13. SUPPLEMENTARY...tremendous impact on end-to-end system performance. Tactical applications pose unique requirements for the network, including decentralized control to

  9. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Science.gov (United States)

    Kwak, Doyeon; Kim, Wonjoon

    2017-01-01

    It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  10. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Directory of Open Access Journals (Sweden)

    Doyeon Kwak

    Full Text Available It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  11. Neural-networks-based feedback linearization versus model predictive control of continuous alcoholic fermentation process

    Energy Technology Data Exchange (ETDEWEB)

    Mjalli, F.S.; Al-Asheh, S. [Chemical Engineering Department, Qatar University, Doha (Qatar)

    2005-10-01

    In this work advanced nonlinear neural networks based control system design algorithms are adopted to control a mechanistic model for an ethanol fermentation process. The process model equations for such systems are highly nonlinear. A neural network strategy has been implemented in this work for capturing the dynamics of the mechanistic model for the fermentation process. The neural network achieved has been validated against the mechanistic model. Two neural network based nonlinear control strategies have also been adopted using the model identified. The performance of the feedback linearization technique was compared to neural network model predictive control in terms of stability and set point tracking capabilities. Under servo conditions, the feedback linearization algorithm gave comparable tracking and stability. The feedback linearization controller achieved the control target faster than the model predictive one but with vigorous and sudden controller moves. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

  12. Process identification through modular neural networks and rule extraction (extended abstract)

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.; Blockeel, Hendrik; Denecker, Marc

    2002-01-01

    Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule

  13. Optimization of vertical handover decision processes for fourth generation heterogeneous wireless networks

    OpenAIRE

    Yan, Xiaohuan

    2017-01-01

    This thesis presents a vertical handover decision (VHD) scheme for optimizing the efficiency of vertical handover processes in the Fourth Generation (4G) heterogeneous wireless networks. The scheme consists of three closely integrated modules: Handover necessity estimation, handover target selection, and handover triggering condition estimation. Handover necessity estimation module determines whether a handover is necessary to an available network. Handover target selecti...

  14. Geodetic networks of processing by singular decomposition of the configuration matrix

    Directory of Open Access Journals (Sweden)

    Weiss Gabriel

    1996-12-01

    Full Text Available The paper present a solution of the Gauss-Markov Model for processing geodetic networks with constraints using singular decomposition of the network’s design matrix A. The homogenisation and dehomogenisation of the model needed for this purpose is introduced too. Outputs of the solution are presented by the necessary matrices and upon advantages of this way are discoursed.

  15. Rh Factor: How It Can Affect Your Pregnancy

    Science.gov (United States)

    ... a miscarriage , an ectopic pregnancy , or an induced abortion . If an Rh-negative woman becomes pregnant after one of these events, she does not receive treatment, and the fetus is Rh positive, the fetus may be at risk of Rh-related problems. How does Rh sensitization affect the fetus during ...

  16. Prevention and management of RhD isoimmunization.

    Science.gov (United States)

    Harkness, Ursula F; Spinnato, Joseph A

    2004-12-01

    An Rh-negative woman is at risk for developing Rh isoimmunization upon exposure to RhD antigens from her Rh-positive baby through fetal-maternal hemorrhage. The incidence of Rh isoimmunization and fetal hemolytic disease has decreased substantially since Rh immune globulin was introduced in 1968. When RhD sensitization does occur, careful follow-up of these mothers and judicious intervention can result in good outcomes for most pregnancies. Both Doppler assessment of middle cerebral artery peak systolic velocity and spectral analysis of amniotic fluid at 450 nm (DeltaOD 450) are useful in the diagnosis and management of fetal anemia.

  17. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  18. Modeling Wireless Sensor Networks for Monitoring in Biological Processes

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil

    signal strength). Fusing the two measured behavioral data resulted in an improvement of the classification results regarding the animal behavior mode (activity/inactivity), compared to the results achieved by only monitoring one of the behavioral parameters. Applying a multiple-model adaptive estimation...... (MMAE) approach to the data resulted in the highest classification success rate, due to the use of precise forth-order mathematical models which relate the feed offer to the pitch angle of the neck. This thesis shows that wireless sensor networks can be successfully employed to monitor the behavior...

  19. Social networks and informal learning processes: a research study

    Directory of Open Access Journals (Sweden)

    Stefano Besana

    2012-04-01

    Full Text Available Scopo del presente contributo di ricerca è di presentare i SNS come spazi maturi per l’erogazione di esperienze formative e la gestione dei flussi informativi, nonché dei processi di apprendimento. È pertanto presentato il secondo step di una ricerca che prende le mosse da un’analisi pilota condotta nel 2009 e che ha coinvolto - nel 2010 e nei primi mesi del 2011 - 926 soggetti nel tentativo di definire aspetti positivi, negativi, abitudini d’uso, rappresentazioni più o meno consapevoli e ipotesi d’impiego circa il possibile utilizzo dei Social Network nella didattica.

  20. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  1. Multisensor Network System for Wildfire Detection Using Infrared Image Processing

    Directory of Open Access Journals (Sweden)

    I. Bosch

    2013-01-01

    Full Text Available This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire, for different probability of false alarm (PFA. The necessity of including decision fusion is thereby demonstrated.

  2. Computationally efficient locally-recurrent neural networks for online signal processing

    CERN Document Server

    Hussain, A; Shim, I

    1999-01-01

    A general class of computationally efficient locally recurrent networks (CERN) is described for real-time adaptive signal processing. The structure of the CERN is based on linear-in-the- parameters single-hidden-layered feedforward neural networks such as the radial basis function (RBF) network, the Volterra neural network (VNN) and the functionally expanded neural network (FENN), adapted to employ local output feedback. The corresponding learning algorithms are derived and key structural and computational complexity comparisons are made between the CERN and conventional recurrent neural networks. Two case studies are performed involving the real- time adaptive nonlinear prediction of real-world chaotic, highly non- stationary laser time series and an actual speech signal, which show that a recurrent FENN based adaptive CERN predictor can significantly outperform the corresponding feedforward FENN and conventionally employed linear adaptive filtering models. (13 refs).

  3. Network-Guided Key Gene Discovery for a Given Cellular Process

    DEFF Research Database (Denmark)

    He, Feng Q; Ollert, Markus

    2018-01-01

    and the following-up network analysis, opens up new avenues to predict key genes driving a given biological process or cellular function. Here we review and compare the current approaches in predicting key genes, which have no chances to stand out by classic differential expression analysis, from gene......-regulatory, protein-protein interaction, or gene expression correlation networks. We elaborate these network-based approaches mainly in the context of immunology and infection, and urge more usage of correlation network-based predictions. Such network-based key gene discovery approaches driven by information......-enriched 'omics' data should be very useful for systematic key gene discoveries for any given biochemical process or cellular function, and also valuable for novel drug target discovery and novel diagnostic, prognostic and therapeutic-efficiency marker prediction for a specific disease or disorder....

  4. Network-based business process management: embedding business logic in communications networks

    NARCIS (Netherlands)

    L-F. Pau (Louis-François); P.H.M. Vervest (Peter)

    2003-01-01

    textabstractAdvanced Business Process Management (BPM) tools enable the decomposition of previously integrated and often ill-defined processes into re-usable process modules. These process modules can subsequently be distributed on the Internet over a variety of many different actors, each with

  5. Network complexity as a measure of information processing across resting-state networks: Evidence from the Human Connectome Project

    Directory of Open Access Journals (Sweden)

    Ian M Mcdonough

    2014-06-01

    Full Text Available An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing. While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013 to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy 1 would differ from random noise, 2 would differ between four major resting-state networks previously associated with higher-order cognition, and 3 would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity.

  6. Perinatal mortality in Rh alloimmunized patients.

    Science.gov (United States)

    Nardozza, Luciano Marcondes Machado; Camano, Luiz; Moron, Antonio Fernandes; Chinen, Paulo Alexandre; Torloni, Maria Regina; Cordioli, Eduardo; Araújo Junior, Edward

    2007-06-01

    Evaluate and compare the perinatal mortality of Rh-negative pregnancies managed at São Paulo Federal University during a 9-year period, using either amniocentesis or middle cerebral artery peak systolic velocity. Descriptive observational study involving 291 consecutive Rh-negative pregnancies managed between January 1995 and January 2004. The perinatal mortality of 99 alloimmunized patients was compared with 192 Rh-negative unimmunized patients (control group). The perinatal mortality of patients managed with amniocenteses was compared to those managed with Doppler studies. There were 74 patients managed with amniocenteses and 25 managed with Doppler studies. Perinatal mortality was significantly higher in the 99 Rh-negative isoimmunized patients than in the 192 unimmunized patients (12.1% versus 1%, p=0.0001) and did not differ according to the management protocol used (amniocentesis 13.5% versus cerebral Doppler 8.0%, p=0.725). Mean gestational age and mean weight at birth in pregnancies managed with amniocenteses (35.7 weeks and 2586 g) did not differ significantly from those managed with Doppler (36.3 weeks and 2647 g). Perinatal mortality in Rh-negative alloimmunized patients remains high and does not differ whether pregnancies are managed through amniocentesis or cerebral Doppler evaluation.

  7. The roles of deals and business networks in innovation processes

    OpenAIRE

    Olsen, Per Ingvar; Håkansson, Håkan

    2017-01-01

    The accepted and peer reviewed manuscript to the article Purpose: The purpose of this paper is to analyze the roles of deals in innovations processes, based on the definition of a deal as the interaction of social-material value-creating processes with money-handing processes. Design/methodology/approach:The paper is based on a study of the historical emergence of transaortic valve implantation (TAVI) as an innovative new technology in the area of thoracic surgery in a global setting. T...

  8. Radioimmunoassay in Ascidiella aspersa of a gonadoliberin (GnRH)-like factor with an apparent molecular weight higher than that of mammalian decapeptide

    Energy Technology Data Exchange (ETDEWEB)

    Dufour, S.; Monniot, F.; Monniot, C. and others

    1988-02-21

    A radioimmunoassay (RIA) for mammalian gonadoliberin (mGnRH) showed the presence of a GnRH-like factor in the neural complex of a Protochordate, Ascidiella aspersa (about 0.6 pg eq mGnRH/complex). The slope of the displacement curves was slightly lower than with mGnRH indicating antigene differences. No cross reactive material was found in mantle and siphonal area. The KD on Sephadex G25 was 0.45 versus 0.90 with mGnRH. That suggests that the molecular weight of the Ascidian GnRH-like factor is higher than that of known Vertebrate GnRH's, possibly due to a different processing of the precursor.

  9. Array signal processing in the NASA Deep Space Network

    Science.gov (United States)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  10. Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

    2015-08-01

    With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

  11. Improving the Quality of Service and Security of Military Networks with a Network Tasking Order Process

    Science.gov (United States)

    2010-09-01

    departure/ return locations and times, one- way travel with departure/arrival locations and times, or orbit information with departure/ return locations and...found that their heuristic occasionally returned a better solution than the “optimal” solution found using the MILP approach. This suggests that either...Networks,” IEEE Journal on Selected Areas in Communication, 23: 1556-1563 (August 2005). [39] Lala , Jaynarayan, Douglas Maughan, Catherine McCollum, and

  12. Evaluasi Kinerja Organisasi Publik Dengan Menggunakan Pendekatan Balanced Scorecard dan Analytic Network Process

    Directory of Open Access Journals (Sweden)

    Adi Mora Tunggul

    2016-12-01

    Full Text Available Balanced scorecard is a strategic business management method that links performance evaluation to vision and strategies using a multidimensional set of financial and nonfinancial performance metrics. This study examined both quantitative data for the proposed Analytic Network Process method. The purpose of this research is to build a model that combines the Balanced Scorecard approach and Analytical Network Process to assist in the performance evaluation of public organizations tax services. Balanced Scorecard concept is applied to determine the hierarchy of the financial perspective, customer perspective, internal business processes, and learning and growth perspective as well as their respective performance indicators of public organizations and then Analytical Network Process used to tolerate vagueness and ambiguity of information and built an information system that is applied to facilitate the performance evaluation process. The study provides recommendations to the management of public organizations regarding the tax service strategy to improve the performance of public organizations.

  13. D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

    Directory of Open Access Journals (Sweden)

    Shu-zhi Gao

    2014-01-01

    Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

  14. Managing Distributed Innovation Processes in Virtual Organizations by Applying the Collaborative Network Relationship Analysis

    Science.gov (United States)

    Eschenbächer, Jens; Seifert, Marcus; Thoben, Klaus-Dieter

    Distributed innovation processes are considered as a new option to handle both the complexity and the speed in which new products and services need to be prepared. Indeed most research on innovation processes was focused on multinational companies with an intra-organisational perspective. The phenomena of innovation processes in networks - with an inter-organisational perspective - have been almost neglected. Collaborative networks present a perfect playground for such distributed innovation processes whereas the authors highlight in specific Virtual Organisation because of their dynamic behaviour. Research activities supporting distributed innovation processes in VO are rather new so that little knowledge about the management of such research is available. With the presentation of the collaborative network relationship analysis this gap will be addressed. It will be shown that a qualitative planning of collaboration intensities can support real business cases by proving knowledge and planning data.

  15. Noninvasive fetal RhD genotyping

    DEFF Research Database (Denmark)

    Clausen, Frederik Banch; Damkjær, Merete Berthu; Dziegiel, Morten Hanefeld

    2014-01-01

    Immunization against RhD is the major cause of hemolytic disease of the fetus and newborn (HDFN), which causes fetal or neonatal death. The introduction of postnatal immune prophylaxis in the 1960s drastically reduced immunization incidents in pregnant, D-negative women. In several countries......, antenatal prophylaxis is combined with postnatal prophylaxis to further minimize the immunization risk. Due to lack of knowledge of the fetal RhD type, antenatal prophylaxis is given to all D-negative women. In the European population, approximately 40% of pregnant women carry a D-negative fetus...... and are thus at no risk of immunization. Noninvasive fetal RhD genotyping enables antenatal prophylaxis to be targeted to only those women carrying a D-positive fetus to avoid unnecessary treatment. Based on an analysis of cell-free fetal DNA from the plasma of pregnant women, this approach has recently...

  16. Melatonin Inhibits GnRH-1, GnRH-3 and GnRH Receptor Expression in the Brain of the European Sea Bass, Dicentrarchus labrax

    Directory of Open Access Journals (Sweden)

    José Antonio Muñoz-Cueto

    2013-04-01

    Full Text Available Several evidences supported the existence of melatonin effects on reproductive system in fish. In order to investigate whether melatonin is involved in the modulation of GnRH systems in the European sea bass, we have injected melatonin (0.5 µg/g body mass in male specimens. The brain mRNA transcript levels of the three GnRH forms and the five GnRH receptors present in this species were determined by real time quantitative PCR. Our findings revealed day–night variations in the brain expression of GnRH-1, GnRH-3 and several GnRH receptors (dlGnRHR-II-1c, -2a, which exhibited higher transcript levels at mid-light compared to mid-dark phase of the photocycle. Moreover, an inhibitory effect of melatonin on the nocturnal expression of GnRH-1, GnRH-3, and GnRH receptors subtypes 1c, 2a and 2b was also demonstrated. Interestingly, the inhibitory effect of melatonin affected the expression of hypophysiotrophic GnRH forms and GnRH receptors that exhibit day–night fluctuations, suggesting that exogenous melatonin reinforce physiological mechanisms already established. These interactions between melatoninergic and GnRH systems could be mediating photoperiod effects on reproductive and other rhythmic physiological events in the European sea bass.

  17. Building a Multilevel Modeling Network for Lipid Processing Systems

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    The world’s fats and oils production has been growing rapidly over the past few decades, exceeding the need for human nutrition. This overproduction combined with the increasing interest among the consumers for healthier food products and bio-fuels, has led the oleo chemical industry to face...... for their physical properties and unit operation models for their processing have limited computer-aided methods and tools for process synthesis, modeling and simulation to be widely used for design, analysis, and optimization of these processes. The world’s fats and oils production has been growing rapidly over...... the past few decades, exceeding the need for human nutrition. This overproduction combined with the increasing interest among the consumers for healthier food products and bio-fuels, has led the oleo chemical industry to face in the upcoming years major challenges in terms of design and development...

  18. Exploratory use of a Bayesian network process for translating ...

    African Journals Online (AJOL)

    2016-04-02

    Apr 2, 2016 ... problems. The high number of stakeholders involved in a catchment management forum provided an environment for testing the development of a BN showing relationships between water quality problems and stakeholders in this area. ... co-operative, stakeholder-driven problem-solving process. Even.

  19. Epidemic Processes on Complex Networks : Modelling, Simulation and Algorithms

    NARCIS (Netherlands)

    Van de Bovenkamp, R.

    2015-01-01

    Local interactions on a graph will lead to global dynamic behaviour. In this thesis we focus on two types of dynamic processes on graphs: the Susceptible-Infected-Susceptilbe (SIS) virus spreading model, and gossip style epidemic algorithms. The largest part of this thesis is devoted to the SIS

  20. The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

    Science.gov (United States)

    Blakeslee, Rich; Bailey, Jeff; Koshak, Bill

    1999-01-01

    A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/ Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/Marshall Space Flight Center (MSFC) are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

  1. Building a Multilevel Modeling Network for Lipid Processing Systems

    OpenAIRE

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol; Quaglia, Alberto; Sin, Gürkan; Kontogeorgis, Georgios; Sarup, Bent; Gani, Rafiqul

    2011-01-01

    The world’s fats and oils production has been growing rapidly over the past few decades, exceeding the need for human nutrition. This overproduction combined with the increasing interest among the consumers for healthier food products and bio-fuels, has led the oleo chemical industry to face in the upcoming years major challenges in terms of design and development of better products and more sustainable processes. Although the oleo chemical industry is mature and based on well established pro...

  2. HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP MODEL

    Directory of Open Access Journals (Sweden)

    Chun Meng Tang

    2015-12-01

    Full Text Available Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly competitive. To maintain the current user base and continue to attract new users, how should social networking sites design their sites? Marketers spend a fairly large percent of their marketing budget on social media marketing. To formulate an effective social media strategy, how much do marketers understand the users of social networking sites? Learning from website evaluation studies, this study intends to provide some answers to these questions by examining how university students decide between two popular social networking sites, Facebook and Twitter. We first developed an analytic hierarchy process (AHP model of four main selection criteria and 12 sub-criteria, and then administered a questionnaire to a group of university students attending a course at a Malaysian university. AHP analyses of the responses from 12 respondents provided an insight into the decision-making process involved in students’ selection of social networking sites. It seemed that of the four main criteria, privacy was the top concern, followed by functionality, usability, and content. The sub-criteria that were of key concern to the students were apps, revenue-generating opportunities, ease of use, and information security. Between Facebook and Twitter, the students thought that Facebook was the better choice. This information is useful for social networking site designers to design sites that are more relevant to their users’ needs, and for marketers to craft more effective

  3. Quantifying structural uncertainty on fault networks using a marked point process within a Bayesian framework

    Science.gov (United States)

    Aydin, Orhun; Caers, Jef Karel

    2017-08-01

    Faults are one of the building-blocks for subsurface modeling studies. Incomplete observations of subsurface fault networks lead to uncertainty pertaining to location, geometry and existence of faults. In practice, gaps in incomplete fault network observations are filled based on tectonic knowledge and interpreter's intuition pertaining to fault relationships. Modeling fault network uncertainty with realistic models that represent tectonic knowledge is still a challenge. Although methods that address specific sources of fault network uncertainty and complexities of fault modeling exists, a unifying framework is still lacking. In this paper, we propose a rigorous approach to quantify fault network uncertainty. Fault pattern and intensity information are expressed by means of a marked point process, marked Strauss point process. Fault network information is constrained to fault surface observations (complete or partial) within a Bayesian framework. A structural prior model is defined to quantitatively express fault patterns, geometries and relationships within the Bayesian framework. Structural relationships between faults, in particular fault abutting relations, are represented with a level-set based approach. A Markov Chain Monte Carlo sampler is used to sample posterior fault network realizations that reflect tectonic knowledge and honor fault observations. We apply the methodology to a field study from Nankai Trough & Kumano Basin. The target for uncertainty quantification is a deep site with attenuated seismic data with only partially visible faults and many faults missing from the survey or interpretation. A structural prior model is built from shallow analog sites that are believed to have undergone similar tectonics compared to the site of study. Fault network uncertainty for the field is quantified with fault network realizations that are conditioned to structural rules, tectonic information and partially observed fault surfaces. We show the proposed

  4. Lack of association between Rh status, Rh immune globulin in pregnancy and autism.

    Science.gov (United States)

    Miles, Judith H; Takahashi, T Nicole

    2007-07-01

    Though causes of autism are considered largely genetic, considerable concern remains that exposure to Rh immune globulin (RhIg), which until 2001 in the United States contained the preservative thimerosal, can cause autism. To determine whether mothers of children with autism are more likely to be Rh negative (Rh(-)) or to have received RhIg preserved with thimerosal, which is 49.6% ethyl mercury, we surveyed families of children with an autism spectrum disorder (ASD) ascertained through a University-based autism clinic considered free of ascertainment biases related to type of autism or severity. Between 2004 and 2006, 305 mothers of 321 children with an ASD agreed to participate in a telephone interview. Analysis of complete records including the blood group status and RhIg exposure of 214 families showed that Rh(-) status is no higher in mothers of children with autism than in the general population, exposure to antepartum RhIg, preserved with thimerosal is no higher for children with autism and pregnancies are no more likely to be Rh incompatible. This was also true for autism subgroups defined by behavioral phenotype, gender, IQ, regressive onset, head circumference, dysmorphology, birth status, essential, or complex phenotype. These findings support the consensus that exposure to ethylmercury in thimerosal is not the cause of the increased prevalence of autism. These data are important not only for parents in this country but also for the international health community where thimerosal continues to be used to preserve multi-dose vials which in turn makes vaccines affordable. (c) 2007 Wiley-Liss, Inc.

  5. Integrated Business and Engineering Framework for Synthesis and Design of Enterprise-Wide Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2012-01-01

    The synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc) and engineering levels (considering synthesis, design...... and optimisation of production technology, R&D, etc), all of which have a deep impact on the profitability of processing industries. In this study, an integrated business and engineering framework for synthesis and design of processing networks is presented. The framework employs a systematic approach to manage...... the complexity while solving simultaneously both the business and the engineering aspects of problems, allowing at the same time, comparison of a large number of alternatives at their optimal points. The results identify the optimal raw material, the product portfolio and select the process technology...

  6. The Use of Social Networking to Increase Yield: Applying Persistence Theory to the Graduate Admissions Process

    Science.gov (United States)

    Wright, Russell W.

    2012-01-01

    This quantitative study explored the connection between the use of a private social networking website during the graduate admissions process at a law school in the southeastern United States and the decision to matriculate or withdraw from the program. A theoretical model of persistence over time within the graduate admissions process was…

  7. Prevention of Rh Hemolytic Disease of the Newborn

    Science.gov (United States)

    Jennings, E. R.; Dibbern, H. H.; Hodell, F. H.; Monroe, C. H.; Peckham, N. H.; Sullivan, J. F.; Pollack, W.

    1969-01-01

    Rho(D)-Immune Globulin was given to 322 Rh-negative women delivered of ABO-compatible, Rh-positive infants with no apparent failures to suppress Rh sensitization. In contrast, 32 of 305 mothers of a control group made Rh antibody during the six months following delivery. In subsequent pregnancies, 69 women administered RhoGAM had no evidence of isoimmunization after delivery while six of forty mothers of the control study produced anti-Rh. RhoGAM, given within 72 hours of delivery in the amounts employed, was effective for suppression of Rh immunization. PMID:4181977

  8. Improvement of castable refractories for RH snorkel; RH shinshitsukanyo futeikeizai no kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Nishi, K.; Obana, T.; Fijii, T.; Shimizu, I. [Harima Ceramics Corp., Hyogo (Japan)

    1999-11-01

    Relating to corrosion of RH submerged nozzle, resistance against iron oxide of monolithic refractories was examined. Corrosion and seepage of refractories were measured by rotating corrosion, refractories include alumina-spinel castable, which is applied to RH under tank, and alumina-magnesia castable, which is generally used for RH, submerged nozzle. Alumina-spinel castable is superior in resistance against iron oxide than alumina-magnesia castable, and the resistance decreased with increase of stainless fiber addition to castable. Alumina-spinel castable without stainless fiber was suitable for bottom end of the dipping pipe. (NEDO)

  9. Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

    Directory of Open Access Journals (Sweden)

    Golmohammadi Hassan

    2013-01-01

    Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

  10. Multicriteria Based Next Forwarder Selection for Data Dissemination in Vehicular Ad Hoc Networks Using Analytical Network Process

    Directory of Open Access Journals (Sweden)

    Shahid Latif

    2017-01-01

    Full Text Available Vehicular ad hoc network (VANET is a wireless emerging technology that aims to provide safety and communication services to drivers and passengers. In VANETs, vehicles communicate with other vehicles directly or through road side units (RSU for sharing traffic information. The data dissemination in VANETs is a challenging issue as the vehicles have to share safety critical information in real time. The data distribution is usually done using broadcast method resulting in inefficient use of network resources. Therefore, to avoid the broadcast storm and efficiently use network resources, next forwarder vehicle (NFV is selected to forward data to nearby vehicles. The NFV selection is based on certain parameters like direction, distance, and position of vehicles, which makes it a multicriteria decision problem. In this paper, analytical network process (ANP is used as a multicriteria decision tool to select the optimal vehicle as NFV. The stability of alternatives (candidate vehicles for NFV selection ranking is checked using sensitivity analysis for different scenarios. Mathematical formulation shows that ANP method is applicable for NFV selection in VANETs. Simulation results show that the proposed scheme outperforms other state-of-the-art data dissemination schemes in terms of reachability, latency, collisions, and number of transmitted and duplicate data packets.

  11. Hybrid Neural Network Model of an Industrial Ethanol Fermentation Process Considering the Effect of Temperature

    Science.gov (United States)

    Mantovanelli, Ivana C. C.; Rivera, Elmer Ccopa; da Costa, Aline C.; Filho, Rubens Maciel

    In this work a procedure for the development of a robust mathematical model for an industrial alcoholic fermentation process was evaluated. The proposed model is a hybrid neural model, which combines mass and energy balance equations with functional link networks to describe the kinetics. These networks have been shown to have a good nonlinear approximation capability, although the estimation of its weights is linear. The proposed model considers the effect of temperature on the kinetics and has the neural network weights reestimated always so that a change in operational conditions occurs. This allow to follow the system behavior when changes in operating conditions occur.

  12. Adaptive and Decentralized Operator Placement for In-Network Query Processing

    DEFF Research Database (Denmark)

    Bonfils, B; Bonnet, Philippe

    2003-01-01

    In-network query processing is critical for reducing network traffic when accessing and manipulating sensor data. It requires placing a tree of query operators such as filters and aggregations but also correlations onto sensor nodes in order to minimize the amount of data transmitted in the network...... of operators by walking through neighbor nodes. Simulation results illustrate the potential benefits of our approach. They also show that our placement strategy can achieve near optimal placement onto various graph topologies despite the risks of local minima....

  13. Combined flatland ST radar and digital-barometer network observations of mesoscale processes

    Science.gov (United States)

    Clark, W. L.; Vanzandt, T. E.; Gage, K. S.; Einaudi, F. E.; Rottman, J. W.; Hollinger, S. E.

    1991-01-01

    The paper describes a six-station digital-barometer network centered on the Flatland ST radar to support observational studies of gravity waves and other mesoscale features at the Flatland Atmospheric Observatory in central Illinois. The network's current mode of operation is examined, and a preliminary example of an apparent group of waves evident throughout the network as well as throughout the troposphere is presented. Preliminary results demonstrate the capabilities of the current operational system to study wave convection, wave-front, and other coherent mesoscale interactions and processes throughout the troposphere. Unfiltered traces for the pressure and horizontal zonal wind, for days 351 to 353 UT, 1990, are illustrated.

  14. Algorithm-structured computer arrays and networks architectures and processes for images, percepts, models, information

    CERN Document Server

    Uhr, Leonard

    1984-01-01

    Computer Science and Applied Mathematics: Algorithm-Structured Computer Arrays and Networks: Architectures and Processes for Images, Percepts, Models, Information examines the parallel-array, pipeline, and other network multi-computers.This book describes and explores arrays and networks, those built, being designed, or proposed. The problems of developing higher-level languages for systems and designing algorithm, program, data flow, and computer structure are also discussed. This text likewise describes several sequences of successively more general attempts to combine the power of arrays wi

  15. The Effect of Various Acids on Properties of Microcrystalline Cellulose (MCC) Extracted from Rice Husk (RH)

    Science.gov (United States)

    Nur Hanani, A. S.; Zuliahani, A.; Nawawi, W. I.; Razif, N.; Rozyanty, A. R.

    2017-05-01

    Microcrystalline cellulose (MCC) was successfully extracted from rice husk (RH) via acid hydrolysis process using nitric acid (HNO3) in comparison with sulphuric acid (H2SO4) and hydrochloric acid (HCl). MCC-RH extracted using HNO3 produced the highest percentage yield at 83.5% as compared to H2SO4 and HCl at 80.6% and 81.8% respectively. Analysis of Fourier Transform Infrared (FTIR) spectroscopy affirmed the successive elimination of non-cellulosic material from RH cellulose resulting highly purified MCC-RH. X-ray Diffraction (XRD) analysis showed MCC-RH treated with HCl gives the highest crystallinity index value of 54.2% while HNO3 and H2SO4 produced comparable results of 52.4% and 49.7% respectively. The results indicate successive extraction of MCC-RH using HNO3 that has great potential to replace strong acid such as H2SO4 and HCl in acid hydrolysis.

  16. Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes.

    Science.gov (United States)

    Galtier, Mathieu N; Marini, Camille; Wainrib, Gilles; Jaeger, Herbert

    2014-08-01

    A method is provided for designing and training noise-driven recurrent neural networks as models of stochastic processes. The method unifies and generalizes two known separate modeling approaches, Echo State Networks (ESN) and Linear Inverse Modeling (LIM), under the common principle of relative entropy minimization. The power of the new method is demonstrated on a stochastic approximation of the El Niño phenomenon studied in climate research. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network

    OpenAIRE

    SAĞBAŞ, Aysun; KAHRAMAN, Funda; Esme, Uğur

    2017-01-01

    In this study, it isattempted to model and optimize the wire electrical discharge machining (WEDM)process using Taguchi design of experiment and artificial neural network. Aneural network with back propagation algorithm was developed to predict theperformance characteristic, namely surface roughness. An approach to determineoptimal machining parameters setting was proposed based on the Taguchi designmethod. In addition, analysis of variance (ANOVA) was performed to identify thesignificant par...

  18. Using Single Layer Networks for Discrete, Sequential Data An Example from Natural Language Processing

    CERN Document Server

    Lyon, C; Lyon, Caroline; Frank, Ray

    1997-01-01

    A natural language parser which has been successfully implemented is described. This is a hybrid system, in which neural networks operate within a rule based framework. It can be accessed via telnet for users to try on their own text. (For details, contact the author.) Tested on technical manuals, the parser finds the subject and head of the subject in over 90% of declarative sentences. The neural processing components belong to the class of Generalized Single Layer Networks (GSLN). In general, supervised, feed-forward networks need more than one layer to process data. However, in some cases data can be pre-processed with a non-linear transformation, and then presented in a linearly separable form for subsequent processing by a single layer net. Such networks offer advantages of functional transparency and operational speed. For our parser, the initial stage of processing maps linguistic data onto a higher order representation, which can then be analysed by a single layer network. This transformation is suppo...

  19. Intention processing in communication: a common brain network for language and gestures.

    Science.gov (United States)

    Enrici, Ivan; Adenzato, Mauro; Cappa, Stefano; Bara, Bruno G; Tettamanti, Marco

    2011-09-01

    Human communicative competence is based on the ability to process a specific class of mental states, namely, communicative intention. The present fMRI study aims to analyze whether intention processing in communication is affected by the expressive means through which a communicative intention is conveyed, that is, the linguistic or extralinguistic gestural means. Combined factorial and conjunction analyses were used to test two sets of predictions: first, that a common brain network is recruited for the comprehension of communicative intentions independently of the modality through which they are conveyed; second, that additional brain areas are specifically recruited depending on the communicative modality used, reflecting distinct sensorimotor gateways. Our results clearly showed that a common neural network is engaged in communicative intention processing independently of the modality used. This network includes the precuneus, the left and right posterior STS and TPJ, and the medial pFC. Additional brain areas outside those involved in intention processing are specifically engaged by the particular communicative modality, that is, a peri-sylvian language network for the linguistic modality and a sensorimotor network for the extralinguistic modality. Thus, common representation of communicative intention may be accessed by modality-specific gateways, which are distinct for linguistic versus extralinguistic expressive means. Taken together, our results indicate that the information acquired by different communicative modalities is equivalent from a mental processing standpoint, in particular, at the point at which the actor's communicative intention has to be reconstructed.

  20. Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks

    Science.gov (United States)

    Vestergaard, Christian L.; Génois, Mathieu

    2015-01-01

    Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling. PMID:26517860

  1. Impairment of the face processing network in congenital prosopagnosia.

    Science.gov (United States)

    Avidan, Galia; Behrmann, Marlene

    2014-06-01

    The goal of the current paper is to review recent findings concerning the neural basis of congenital prosopagnosia (CP), a lifelong impairment in face processing that occurs in the absence of explicit brain damage. As such, CP offers a unique model for exploring the psychological and neural bases of normal face processing. We start by providing background about face perception and representation, and then review behavioral evidence gleaned from individuals with CP. We then review recent functional and structural neural investigations which offer a comprehensive account of the mechanisms underlying CP and support a characterization of this impairment as a disconnection syndrome rather than as a syndrome related to focal brain malfunction. We end the paper by offering a general framework for CP which, we believe, best integrates the behavioral and neural findings, and offers a platform for generating hypotheses for future studies. There remain many open issues in our understanding of CP and, to address these unanswered questions, we lay out several future research directions and testable hypotheses for further investigation.

  2. (cGnRH-II) on plasma steroid hormone, maturation and ovulation in ...

    African Journals Online (AJOL)

    PRECIOUS

    2009-12-01

    Dec 1, 2009 ... 100% ovulation was also observed for the fish treated with cGnRH-II 200 μg/kg with the combination of ... fish species. Among other forms of GnRH are salmon. GnRH (sGnRH), mammalian GnRH (mGnRH), catfish. GnRH (cfGnRH), seabass GnRH ..... Review: Gonadatropin action on gametogenesis.

  3. A Middleware Approach to Achieving Fault Tolerance of Kahn Process Networks on Networks on Chips

    Directory of Open Access Journals (Sweden)

    Onur Derin

    2011-01-01

    propose a task-aware middleware concept that allows adaptivity in KPN implemented over a Network on Chip (NoC. We also list our ideas on the development of a simulation platform as an initial step towards creating fault tolerance strategies for KPNs applications running on NoCs. In doing that, we extend our SACRE (Self-Adaptive Component Run Time Environment framework by integrating it with an open source NoC simulator, Noxim. We evaluate the overhead that the middleware brings to the the total execution time and to the total amount of data transferred in the NoC. With this work, we also provide a methodology that can help in identifying the requirements and implementing fault tolerance and adaptivity support on real platforms.

  4. Aberrant salience network (bilateral insula and anterior cingulate cortex) connectivity during information processing in schizophrenia.

    Science.gov (United States)

    White, Thomas P; Joseph, Verghese; Francis, Susan T; Liddle, Peter F

    2010-11-01

    A salience network, comprising bilateral insula and anterior cingulate cortex (ACC), is thought to play a role in recruiting relevant brain regions for the processing of sensory information. Here, we present a functional network connectivity (FNC) analysis of spatial networks identified during somatosensation, performed to test the hypothesis that salience network connectivity is disturbed during information processing in schizophrenia. 19 medicated individuals with schizophrenia and 19 matched healthy controls participated in a functional magnetic resonance imaging study. 100 Hz vibrotactile stimuli were presented to the right index fingertip while whole-head blood oxygenation level-dependent contrast gradient-echo echo-planar images were acquired. Six spatial components of interest were identified using group independent component analysis: (1) bilateral insula, superior temporal and precentral gyrus (INS); (2) dorsal ACC; (3) left dorsolateral frontal and parietal cortex (left central executive network (LCEN)); (4) right dorsolateral frontal and parietal cortex (RCEN); (5) ventromedial frontal cortex (FDMN); and (6) precuneus, posterior cingulate and angular gyrus (PDMN). Maximal-lagged correlation was examined between all pairwise combinations of components. Significantly reduced FNC was observed in schizophrenia compared to controls between: INS and ACC; INS and FDMN; and LCEN and PDMN. There was no evidence of increased FNC in schizophrenia. Reduced salience network connectivity during information processing in schizophrenia suggests disturbance to the system which effects changes between contextually-relevant functional brain states. This aberrance may provide a mechanistic explanation of several clinical features of the disorder. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. in seasonally anoestms GnRH-

    African Journals Online (AJOL)

    luteotrophic effect of progestogen priming followed by a multi- ple injection regime of GnRH. The life-span of corpora lutea induced by HCG was prolonged during postpartum anoestrus in cows pretreated with progesterone implants, but not in cows primed with oestradiol (pratt, Berardinelli, Stevens & Inskeep,. 1982).

  6. Atomic and molecular adsorption on Rh(111)

    DEFF Research Database (Denmark)

    Mavrikakis, Manos; Rempel, J.; Greeley, Jeffrey Philip

    2002-01-01

    A systematic study of the chemisorption of both atomic (H, O, N, S, C), molecular (N-2, CO, NO), and radical (CH3, OH) species on Rh(111) has been performed. Self-consistent, periodic, density functional theory (DFT-GGA) calculations, using both PW91 and RPBE functionals, have been employed to de...

  7. Traffic analysis and signal processing in optical packet switched networks

    DEFF Research Database (Denmark)

    Fjelde, Tina

    2002-01-01

    Gbit/s demultiplexing and 2x10 to 20 Gbit/s multiplexing. Lastly, the IWC’s capabilities as an optical logic gate for enabling more complex signal processing are demonstrated and four applications hereof are discussed. Logic OR and AND are verified in full at 10 Gbit/s using PRBS sequences coupled...... into an MI. Moreover, logic XOR is demonstrated in an MZI at 10 and 20 Gbit/s with good results. Using an MI, the excellent performance of a novel scheme for MPLS label swapping exploiting logic XOR is demonstrated at 10 Gbit/s with a negligible 0.4 dB penalty. Finally, three novel schemes are described...

  8. PIMS Data Storage, Access, and Neural Network Processing

    Science.gov (United States)

    McPherson, Kevin M.; Moskowitz, Milton E.

    1998-01-01

    The Principal Investigator Microgravity Services (PIMS) project at NASA's Lewis Research Center has supported microgravity science Principal Investigator's (PIs) by processing, analyzing, and storing the acceleration environment data recorded on the NASA Space Shuttles and the Russian Mir space station. The acceleration data recorded in support of the microgravity science investigated on these platforms has been generated in discrete blocks totaling approximately 48 gigabytes for the Orbiter missions and 50 gigabytes for the Mir increments. Based on the anticipated volume of acceleration data resulting from continuous or nearly continuous operations, the International Space Station (ISS) presents a unique set of challenges regarding the storage of and access to microgravity acceleration environment data. This paper presents potential microgravity environment data storage, access, and analysis concepts for the ISS era.

  9. Complex network models reveal correlations among network metrics, exercise intensity and role of body changes in the fatigue process.

    Science.gov (United States)

    Pereira, Vanessa Helena; Gama, Maria Carolina Traina; Sousa, Filipe Antônio Barros; Lewis, Theodore Gyle; Gobatto, Claudio Alexandre; Manchado-Gobatto, Fúlvia Barros

    2015-05-21

    The aims of the present study were analyze the fatigue process at distinct intensity efforts and to investigate its occurrence as interactions at distinct body changes during exercise, using complex network models. For this, participants were submitted to four different running intensities until exhaustion, accomplished in a non-motorized treadmill using a tethered system. The intensities were selected according to critical power model. Mechanical (force, peak power, mean power, velocity and work) and physiological related parameters (heart rate, blood lactate, time until peak blood lactate concentration (lactate time), lean mass, anaerobic and aerobic capacities) and IPAQ score were obtained during exercises and it was used to construction of four complex network models. Such models have both, theoretical and mathematical value, and enables us to perceive new insights that go beyond conventional analysis. From these, we ranked the influences of each node at the fatigue process. Our results shows that nodes, links and network metrics are sensibility according to increase of efforts intensities, been the velocity a key factor to exercise maintenance at models/intensities 1 and 2 (higher time efforts) and force and power at models 3 and 4, highlighting mechanical variables in the exhaustion occurrence and even training prescription applications.

  10. Complex network models reveal correlations among network metrics, exercise intensity and role of body changes in the fatigue process

    Science.gov (United States)

    Pereira, Vanessa Helena; Gama, Maria Carolina Traina; Sousa, Filipe Antônio Barros; Lewis, Theodore Gyle; Gobatto, Claudio Alexandre; Manchado-Gobatto, Fúlvia Barros

    2015-05-01

    The aims of the present study were analyze the fatigue process at distinct intensity efforts and to investigate its occurrence as interactions at distinct body changes during exercise, using complex network models. For this, participants were submitted to four different running intensities until exhaustion, accomplished in a non-motorized treadmill using a tethered system. The intensities were selected according to critical power model. Mechanical (force, peak power, mean power, velocity and work) and physiological related parameters (heart rate, blood lactate, time until peak blood lactate concentration (lactate time), lean mass, anaerobic and aerobic capacities) and IPAQ score were obtained during exercises and it was used to construction of four complex network models. Such models have both, theoretical and mathematical value, and enables us to perceive new insights that go beyond conventional analysis. From these, we ranked the influences of each node at the fatigue process. Our results shows that nodes, links and network metrics are sensibility according to increase of efforts intensities, been the velocity a key factor to exercise maintenance at models/intensities 1 and 2 (higher time efforts) and force and power at models 3 and 4, highlighting mechanical variables in the exhaustion occurrence and even training prescription applications.

  11. Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

    Science.gov (United States)

    Mori, Shinichiro

    2017-08-01

    To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  12. Human vaccination against RH5 induces neutralizing antimalarial antibodies that inhibit RH5 invasion complex interactions

    DEFF Research Database (Denmark)

    Payne, Ruth O; Silk, Sarah E; Elias, Sean C

    2017-01-01

    The development of a highly effective vaccine remains a key strategic goal to aid the control and eventual eradication of Plasmodium falciparum malaria. In recent years, the reticulocyte-binding protein homolog 5 (RH5) has emerged as the most promising blood-stage P. falciparum candidate antigen...... to date, capable of conferring protection against stringent challenge in Aotus monkeys. We report on the first clinical trial to our knowledge to assess the RH5 antigen - a dose-escalation phase Ia study in 24 healthy, malaria-naive adult volunteers. We utilized established viral vectors, the replication......-deficient chimpanzee adenovirus serotype 63 (ChAd63), and the attenuated orthopoxvirus modified vaccinia virus Ankara (MVA), encoding RH5 from the 3D7 clone of P. falciparum. Vaccines were administered i.m. in a heterologous prime-boost regimen using an 8-week interval and were well tolerated. Vaccine-induced anti-RH5...

  13. A quantum theoretical approach to information processing in neural networks

    Science.gov (United States)

    Barahona da Fonseca, José; Barahona da Fonseca, Isabel; Suarez Araujo, Carmen Paz; Simões da Fonseca, José

    2000-05-01

    A reinterpretation of experimental data on learning was used to formulate a law on data acquisition similar to the Hamiltonian of a mechanical system. A matrix of costs in decision making specifies values attributable to a barrier that opposed to hypothesis formation about decision making. The interpretation of the encoding costs as frequencies of oscillatory phenomena leads to a quantum paradigm based in the models of photoelectric effect as well as of a particle against a potential barrier. Cognitive processes are envisaged as complex phenomena represented by structures linked by valence bounds. This metaphor is used to find some prerequisites to certain types of conscious experience as well as to find an explanation for some pathological distortions of cognitive operations as they are represented in the context of the isolobal model. Those quantum phenomena are understood as representing an analogue programming for specific special purpose computations. The formation of complex chemical structures within the context of isolobal theory is understood as an analog quantum paradigm for complex cognitive computations.

  14. In-Network Processing on Low-Cost IOT Nodes for Maritime Surveillance

    Science.gov (United States)

    2017-03-01

    PROCESSING ON LOW-COST IOT NODES FOR MARITIME SURVEILLANCE by Andrew R. Belding March 2017 Thesis Advisor: Gurminder Singh Co-Advisor: John H...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IN-NETWORK PROCESSING ON LOW-COST IOT NODES FOR MARITIME SURVEILLANCE 5. FUNDING NUMBERS 6...PROCESSING ON LOW-COST IOT NODES FOR MARITIME SURVEILLANCE Andrew R. Belding Lieutenant Commander, United States Navy B.S., United States Naval

  15. Oximato bridged Rh M and Rh M species (M = Mn, Co, Ni; M = Cu, Ag)

    Indian Academy of Sciences (India)

    WINTEC

    complex [RhCl2(PhL)2]Cu(PPh3)2 the copper atom is coordinated to two oximato oxygen atoms and the ... (M = Cu, Ag) and Rh. III. 2M. II. (M = Mn, Co, Ni) which have been isolated and characterized. Only the species with Ar = Ph are reported here. 2. Experimental .... and Co complexes are EPR silent presumably due to.

  16. Public participation in the process of local public health policy, using policy network analysis.

    Science.gov (United States)

    Park, Yukyung; Kim, Chang-Yup; You, Myoung Soon; Lee, Kun Sei; Park, Eunyoung

    2014-11-01

    To assess the current public participation in-local health policy and its implications through the analysis of policy networks in health center programs. We examined the decision-making process in sub-health center installations and the implementation process in metabolic syndrome management program cases in two districts ('gu's) of Seoul. Participants of the policy network were selected by the snowballing method and completed self-administered questionnaires. Actors, the interactions among actors, and the characteristics of the network were analyzed by Netminer. The results showed that the public is not yet actively participating in the local public health policy processes of decision-making and implementation. In the decision-making process, most of the network actors were in the public sector, while the private sector was a minor actor and participated in only a limited number of issues after the major decisions were made. In the implementation process, the program was led by the health center, while other actors participated passively. Public participation in Korean public health policy is not yet well activated. Preliminary discussions with various stakeholders, including civil society, are needed before making important local public health policy decisions. In addition, efforts to include local institutions and residents in the implementation process with the public officials are necessary to improve the situation.

  17. Role of HLA antigens in Rh (D) alloimmunized pregnant women ...

    Indian Academy of Sciences (India)

    responders) and fifty four mothers who did not develop Rh (D) isoimmunization despite positive pregnancies (nonresponders) were selected for the study. Standard methods of serological HLA typing, ABO and Rh (D) groups, and screening for ...

  18. Construction of a narrative network aimed at implementing inclusive processes

    Directory of Open Access Journals (Sweden)

    Francesca Salis

    2017-01-01

    Full Text Available The concept of inclusion in its complex aspects aimed at overcoming barriers to learning and involvement has led this research in university, in the light of special pedagogy and didactics, on the basis of inclusion index parameters, detecting the levels of integrated planning with the territory. The purpose of this study is not limited to disability and to special education needs but goes further than that encompassing isolation and/or exclusions. As far as the university system is concerned, it becomes significant to enquire about the inclusion process, in this case by means of a narrative approach, bearing in mind that organizational and learning models, together with access modes may give rise to social exclusion.Università e territorio: costruzione di una rete narrativa per l’implementazione dei processi inclusiviIl costrutto di inclusione nelle sue complesse sfaccettature mirate al superamento delle barriere all’apprendimento e alla partecipazione, ha guidato il presente lavoro di ricerca in ambito universitario alla luce della pedagogia e didattica speciale, sulla base dei parametri dell’Index for Inclusion, rilevando i livelli di progettazione integrata con il territorio. Il suo raggio di azione non si limita alla disabilità ma abbraccia tutti i bisogni educativi speciali, e l’isolamento, la marginalizzazione e/o le esclusioni che ne derivano. Rispetto al sistema universitario è rilevante interrogarsi sul processo di inclusione, in questo caso sulla base dell’approccio narrativo, preso atto che il modello organizzativo e le modalità di accesso e formative possono essere causa di esclusione formativa e sociale.

  19. Passive and motivated perception of emotional faces: qualitative and quantitative changes in the face processing network.

    Directory of Open Access Journals (Sweden)

    Laurie R Skelly

    Full Text Available Emotionally expressive faces are processed by a distributed network of interacting sub-cortical and cortical brain regions. The components of this network have been identified and described in large part by the stimulus properties to which they are sensitive, but as face processing research matures interest has broadened to also probe dynamic interactions between these regions and top-down influences such as task demand and context. While some research has tested the robustness of affective face processing by restricting available attentional resources, it is not known whether face network processing can be augmented by increased motivation to attend to affective face stimuli. Short videos of people expressing emotions were presented to healthy participants during functional magnetic resonance imaging. Motivation to attend to the videos was manipulated by providing an incentive for improved recall performance. During the motivated condition, there was greater coherence among nodes of the face processing network, more widespread correlation between signal intensity and performance, and selective signal increases in a task-relevant subset of face processing regions, including the posterior superior temporal sulcus and right amygdala. In addition, an unexpected task-related laterality effect was seen in the amygdala. These findings provide strong evidence that motivation augments co-activity among nodes of the face processing network and the impact of neural activity on performance. These within-subject effects highlight the necessity to consider motivation when interpreting neural function in special populations, and to further explore the effect of task demands on face processing in healthy brains.

  20. On the Modeling and Analysis of Heterogeneous Radio Access Networks using a Poisson Cluster Process

    DEFF Research Database (Denmark)

    Suryaprakash, Vinay; Møller, Jesper; Fettweis, Gerhard P.

    processes, some of which are alluded to (later) in this paper. We model a heterogeneous network consisting of two types of base stations by using a particular Poisson cluster process model. The main contributions are two-fold. First, a complete description of the interference in heterogeneous networks...... is derived in the form of its Laplace functional. Second, using an asymptotic convergence result which was shown in our previous work, we derive the expressions for the mean and variance of the distribution to which the interference converges. The utility of this framework is discussed for both...

  1. Topological data analysis of contagion maps for examining spreading processes on networks

    KAUST Repository

    Taylor, Dane

    2015-07-21

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth\\'s surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct \\'contagion maps\\' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  2. PRELIMINARY MODELING OF AN INDUSTRIAL RECOMBINANT HUMAN ERYTHROPOIETIN PURIFICATION PROCESS BY ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    R. H. R. Garcel1

    2015-09-01

    Full Text Available AbstractIn the present study a preliminary neural network modelling to improve our understanding of Recombinant Human Erythropoietin purification process in a plant was explored. A three layer feed-forward back propagation neural network was constructed for predicting the efficiency of the purification section comprising four chromatographic steps as a function of eleven operational variables. The neural network model performed very well in the training and validation phases. Using the connection weight method the predictor variables were ranked based on their estimated explanatory importance in the neural network and five input variables were found to be predominant over the others. These results provided useful information showing that the first chromatographic step and the third chromatographic step are decisive to achieve high efficiencies in the purification section, thus enriching the control strategy of the plant.

  3. Integrated Quality Evaluation of the In-Situ Networking Measurements and Upscaling Using Gaussian Process Regression

    Science.gov (United States)

    Yin, G.; Li, A.

    2017-09-01

    The flourished development of wireless sensor network technology sheds light to the effective and inexpensive collection of in-situ networking measurements. This will contribute to the temporal validation of coarse resolution remote sensing products. However, the quality evaluation of the in-situ networking measurements and upscaling is still problematic. This study proposed an evaluation method based on Gaussian Process Regression (GPR). Specifically, the qualities of networking measurements and upscaling were evaluated through the relevance of each plot, and the pixelwise coefficient of variation of the scaling results. Both of which can be generated by GPR. The preliminary results demonstrated the potential of the proposed method on quality evaluation of upscaling. Its potential on measurements (per se) quality evaluation will be analysed future.

  4. Modeling the Process of Color Image Recognition Using ART2 Neural Network

    Directory of Open Access Journals (Sweden)

    Todor Petkov

    2015-09-01

    Full Text Available This paper thoroughly describes the use of unsupervised adaptive resonance theory ART2 neural network for the purposes of image color recognition of x-ray images and images taken by nuclear magnetic resonance. In order to train the network, the pixel values of RGB colors are regarded as learning vectors with three values, one for red, one for green and one for blue were used. At the end the trained network was tested by the values of pictures and determines the design, or how to visualize the converted picture. As a result we had the same pictures with colors according to the network. Here we use the generalized net to prepare a model that describes the process of the color image recognition.

  5. Effectiveness evaluation of double-layered satellite network with laser and microwave hybrid links based on fuzzy analytic hierarchy process

    Science.gov (United States)

    Zhang, Wei; Rao, Qiaomeng

    2018-01-01

    In order to solve the problem of high speed, large capacity and limited spectrum resources of satellite communication network, a double-layered satellite network with global seamless coverage based on laser and microwave hybrid links is proposed in this paper. By analyzing the characteristics of the double-layered satellite network with laser and microwave hybrid links, an effectiveness evaluation index system for the network is established. And then, the fuzzy analytic hierarchy process, which combines the analytic hierarchy process and the fuzzy comprehensive evaluation theory, is used to evaluate the effectiveness of the double-layered satellite network with laser and microwave hybrid links. Furthermore, the evaluation result of the proposed hybrid link network is obtained by simulation. The effectiveness evaluation process of the proposed double-layered satellite network with laser and microwave hybrid links can help to optimize the design of hybrid link double-layered satellite network and improve the operating efficiency of the satellite system.

  6. Automatic construction of image inspection algorithm by using image processing network programming

    Science.gov (United States)

    Yoshimura, Yuichiro; Aoki, Kimiya

    2017-03-01

    In this paper, we discuss a method for automatic programming of inspection image processing. In the industrial field, automatic program generators or expert systems are expected to shorten a period required for developing a new appearance inspection system. So-called "image processing expert system" have been studied for over the nearly 30 years. We are convinced of the need to adopt a new idea. Recently, a novel type of evolutionary algorithms, called genetic network programming (GNP), has been proposed. In this study, we use GNP as a method to create an inspection image processing logic. GNP develops many directed graph structures, and shows excellent ability of formulating complex problems. We have converted this network program model to Image Processing Network Programming (IPNP). IPNP selects an appropriate image processing command based on some characteristics of input image data and processing log, and generates a visual inspection software with series of image processing commands. It is verified from experiments that the proposed method is able to create some inspection image processing programs. In the basic experiment with 200 test images, the success rate of detection of target region was 93.5%.

  7. Thermomechanical processing optimization for 304 austenitic stainless steel using artificial neural network and genetic algorithm

    Science.gov (United States)

    Feng, Wen; Yang, Sen

    2016-12-01

    Thermomechanical processing has an important effect on the grain boundary character distribution. To obtain the optimal thermomechanical processing parameters is the key of grain boundary engineering. In this study, genetic algorithm (GA) based on artificial neural network model was proposed to optimize the thermomechanical processing parameters. In this model, a back-propagation neural network (BPNN) was established to map the relationship between thermomechanical processing parameters and the fraction of low-Σ CSL boundaries, and GA integrated with BPNN (BPNN/GA) was applied to optimize the thermomechanical processing parameters. The validation of the optimal thermomechanical processing parameters was verified by an experiment. Moreover, the microstructures and the intergranular corrosion resistance of the base material (BM) and the materials produced by the optimal thermomechanical processing parameters (termed as the GBEM) were studied. Compared to the BM specimen, the fraction of low-Σ CSL boundaries was increased from 56.8 to 77.9% and the random boundary network was interrupted by the low-Σ CSL boundaries, and the intergranular corrosion resistance was improved in the GBEM specimen. The results indicated that the BPNN/GA model was an effective and reliable means for the thermomechanical processing parameters optimization, which resulted in improving the intergranular corrosion resistance in 304 austenitic stainless steel.

  8. Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA.

    Science.gov (United States)

    Bowsher, Clive G

    2011-02-15

    Understanding the encoding and propagation of information by biochemical reaction networks and the relationship of such information processing properties to modular network structure is of fundamental importance in the study of cell signalling and regulation. However, a rigorous, automated approach for general biochemical networks has not been available, and high-throughput analysis has therefore been out of reach. Modularization Identification by Dynamic Independence Algorithms (MIDIA) is a user-friendly, extensible R package that performs automated analysis of how information is processed by biochemical networks. An important component is the algorithm's ability to identify exact network decompositions based on both the mass action kinetics and informational properties of the network. These modularizations are visualized using a tree structure from which important dynamic conditional independence properties can be directly read. Only partial stoichiometric information needs to be used as input to MIDIA, and neither simulations nor knowledge of rate parameters are required. When applied to a signalling network, for example, the method identifies the routes and species involved in the sequential propagation of information between its multiple inputs and outputs. These routes correspond to the relevant paths in the tree structure and may be further visualized using the Input-Output Path Matrix tool. MIDIA remains computationally feasible for the largest network reconstructions currently available and is straightforward to use with models written in Systems Biology Markup Language (SBML). The package is distributed under the GNU General Public License and is available, together with a link to browsable Supplementary Material, at http://code.google.com/p/midia. Further information is at www.maths.bris.ac.uk/~macgb/Software.html.

  9. CÆLIS: software for assimilation, management and processing data of an atmospheric measurement network

    Science.gov (United States)

    Fuertes, David; Toledano, Carlos; González, Ramiro; Berjón, Alberto; Torres, Benjamín; Cachorro, Victoria E.; de Frutos, Ángel M.

    2018-02-01

    Given the importance of the atmospheric aerosol, the number of instruments and measurement networks which focus on its characterization are growing. Many challenges are derived from standardization of protocols, monitoring of the instrument status to evaluate the network data quality and manipulation and distribution of large volume of data (raw and processed). CÆLIS is a software system which aims at simplifying the management of a network, providing tools by monitoring the instruments, processing the data in real time and offering the scientific community a new tool to work with the data. Since 2008 CÆLIS has been successfully applied to the photometer calibration facility managed by the University of Valladolid, Spain, in the framework of Aerosol Robotic Network (AERONET). Thanks to the use of advanced tools, this facility has been able to analyze a growing number of stations and data in real time, which greatly benefits the network management and data quality control. The present work describes the system architecture of CÆLIS and some examples of applications and data processing.

  10. Plasmodium falciparum Reticulocyte Binding-Like Homologue Protein 2 (PfRH2) Is a Key Adhesive Molecule Involved in Erythrocyte Invasion

    Science.gov (United States)

    Sahar, Tajali; Reddy, K. Sony; Bharadwaj, Mitasha; Pandey, Alok K.; Singh, Shailja; Chitnis, Chetan E.; Gaur, Deepak

    2011-01-01

    Erythrocyte invasion by Plasmodium merozoites is a complex, multistep process that is mediated by a number of parasite ligand-erythrocyte receptor interactions. One such family of parasite ligands includes the P. falciparum reticulocyte binding homologue (PfRH) proteins that are homologous with the P. vivax reticulocyte binding proteins and have been shown to play a role in erythrocyte invasion. There are five functional PfRH proteins of which only PfRH2a/2b have not yet been demonstrated to bind erythrocytes. In this study, we demonstrated that native PfRH2a/2b is processed near the N-terminus yielding fragments of 220 kDa and 80 kDa that exhibit differential erythrocyte binding specificities. The erythrocyte binding specificity of the 220 kDa processed fragment of native PfRH2a/2b was sialic acid-independent, trypsin resistant and chymotrypsin sensitive. This specific binding phenotype is consistent with previous studies that disrupted the PfRH2a/2b genes and demonstrated that PfRH2b is involved in a sialic acid independent, trypsin resistant, chymotrypsin sensitive invasion pathway. Interestingly, we found that the smaller 80 kDa PfRH2a/2b fragment is processed from the larger 220 kDa fragment and binds erythrocytes in a sialic acid dependent, trypsin resistant and chymotrypsin sensitive manner. Thus, the two processed fragments of PfRH2a/2b differed with respect to their dependence on sialic acids for erythrocyte binding. Further, we mapped the erythrocyte binding domain of PfRH2a/2b to a conserved 40 kDa N-terminal region (rPfRH240) in the ectodomain that is common to both PfRH2a and PfRH2b. We demonstrated that recombinant rPfRH240 bound human erythrocytes with the same specificity as the native 220 kDa processed protein. Moreover, antibodies generated against rPfRH240 blocked erythrocyte invasion by P. falciparum through a sialic acid independent pathway. PfRH2a/2b thus plays a key role in erythrocyte invasion and its conserved receptor-binding domain

  11. Process reveals structure: How a network is traversed mediates expectations about its architecture.

    Science.gov (United States)

    Karuza, Elisabeth A; Kahn, Ari E; Thompson-Schill, Sharon L; Bassett, Danielle S

    2017-10-06

    Network science has emerged as a powerful tool through which we can study the higher-order architectural properties of the world around us. How human learners exploit this information remains an essential question. Here, we focus on the temporal constraints that govern such a process. Participants viewed a continuous sequence of images generated by three distinct walks on a modular network. Walks varied along two critical dimensions: their predictability and the density with which they sampled from communities of images. Learners exposed to walks that richly sampled from each community exhibited a sharp increase in processing time upon entry into a new community. This effect was eliminated in a highly regular walk that sampled exhaustively from images in short, successive cycles (i.e., that increasingly minimized uncertainty about the nature of upcoming stimuli). These results demonstrate that temporal organization plays an essential role in learners' sensitivity to the network architecture underlying sensory input.

  12. Introduction of A New Toolbox for Processing Digital Images From Multiple Camera Networks: FMIPROT

    Science.gov (United States)

    Melih Tanis, Cemal; Nadir Arslan, Ali

    2017-04-01

    Webcam networks intended for scientific monitoring of ecosystems is providing digital images and other environmental data for various studies. Also, other types of camera networks can also be used for scientific purposes, e.g. usage of traffic webcams for phenological studies, camera networks for ski tracks and avalanche monitoring over mountains for hydrological studies. To efficiently harness the potential of these camera networks, easy to use software which can obtain and handle images from different networks having different protocols and standards is necessary. For the analyses of the images from webcam networks, numerous software packages are freely available. These software packages have different strong features not only for analyzing but also post processing digital images. But specifically for the ease of use, applicability and scalability, a different set of features could be added. Thus, a more customized approach would be of high value, not only for analyzing images of comprehensive camera networks, but also considering the possibility to create operational data extraction and processing with an easy to use toolbox. At this paper, we introduce a new toolbox, entitled; Finnish Meteorological Institute Image PROcessing Tool (FMIPROT) which a customized approach is followed. FMIPROT has currently following features: • straightforward installation, • no software dependencies that require as extra installations, • communication with multiple camera networks, • automatic downloading and handling images, • user friendly and simple user interface, • data filtering, • visualizing results on customizable plots, • plugins; allows users to add their own algorithms. Current image analyses in FMIPROT include "Color Fraction Extraction" and "Vegetation Indices". The analysis of color fraction extraction is calculating the fractions of the colors in a region of interest, for red, green and blue colors along with brightness and luminance parameters. The

  13. Transcriptome analysis of endometrial tissues following GnRH agonist treatment in a mouse adenomyosis model

    Directory of Open Access Journals (Sweden)

    Guo S

    2017-03-01

    size was increased (10±0.28 vs 7±0.28; P<0.05 after GnRH agonist treatment. Three hundred and fifty-nine genes were differentially expressed in the GnRH agonist-treated group compared with the untreated group (218 were downregulated and 141 were upregulated. Differentially expressed genes were related to diverse biological processes, including estrogen metabolism, cell cycle, and metabolite biosynthesis.Conclusion: GnRH agonist treatment appears to improve the pregnancy outcome of adenomyosis in a mouse model. Besides pituitary down-regulation, other possible mechanisms such as the regulation of cell proliferation may play a role in this. These new insights into GnRH agonist mechanisms will be useful for future adenomyosis treatment. Keywords: adenomyosis, GnRH agonist, mouse, RNA-seq, pregnancy outcome

  14. Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

    Directory of Open Access Journals (Sweden)

    Danielle S Bassett

    2010-04-01

    Full Text Available Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.

  15. Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

    Science.gov (United States)

    Bassett, Danielle S; Greenfield, Daniel L; Meyer-Lindenberg, Andreas; Weinberger, Daniel R; Moore, Simon W; Bullmore, Edward T

    2010-04-22

    Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.

  16. Functional Significance of GnRH and Kisspeptin, and Their Cognate Receptors in Teleost Reproduction

    Directory of Open Access Journals (Sweden)

    RENJITHA eGOPURAPPILLY

    2013-03-01

    Full Text Available Guanine nucleotide binding protein (G-protein-coupled receptors (GPCRs are eukaryotic transmembrane proteins found in all living organisms. Their versatility and roles in several physiological processes make them the single largest family of drug targets. Comparative genomic studies using various model organisms have provided useful information about target receptors. The similarity of the genetic makeup of teleosts to that of humans and other vertebrates aligns with the study of GPCRs. Gonadotropin-releasing hormone (GnRH represents a critical step in the reproductive process through its cognate GnRH receptors (GnRHRs. Kisspeptin (Kiss1 and its cognate GPCR, GPR54 (=kisspeptin receptor, Kiss-R, have recently been identified as a critical signalling system in the control of reproduction. The Kiss1/GPR54 system regulates GnRH release, which is vital to pubertal development and vertebrate reproduction. This review highlights the physiological role of kisspeptin-Kiss-R signalling in the reproductive neuroendocrine axis in teleosts through the modulation of GnRH release. Moreover, we also review the recent developments in GnRHR and Kiss-R with respect to their structural variants, signalling mechanisms, ligand interactions and functional significance. Finally, we discuss the recent progress in identifying many teleost GnRH-GnRHR and kisspeptin-Kiss-R systems and will consider their physiological significance in the control of reproduction.

  17. Functional Significance of GnRH and Kisspeptin, and Their Cognate Receptors in Teleost Reproduction

    Science.gov (United States)

    Gopurappilly, Renjitha; Ogawa, Satoshi; Parhar, Ishwar S.

    2012-01-01

    Guanine nucleotide binding protein (G-protein)-coupled receptors (GPCRs) are eukaryotic transmembrane proteins found in all living organisms. Their versatility and roles in several physiological processes make them the single largest family of drug targets. Comparative genomic studies using various model organisms have provided useful information about target receptors. The similarity of the genetic makeup of teleosts to that of humans and other vertebrates aligns with the study of GPCRs. Gonadotropin-releasing hormone (GnRH) represents a critical step in the reproductive process through its cognate GnRH receptors (GnRHRs). Kisspeptin (Kiss1) and its cognate GPCR, GPR54 (=kisspeptin receptor, Kiss-R), have recently been identified as a critical signaling system in the control of reproduction. The Kiss1/Kiss-R system regulates GnRH release, which is vital to pubertal development and vertebrate reproduction. This review highlights the physiological role of kisspeptin-Kiss-R signaling in the reproductive neuroendocrine axis in teleosts through the modulation of GnRH release. Moreover, we also review the recent developments in GnRHR and Kiss-R with respect to their structural variants, signaling mechanisms, ligand interactions, and functional significance. Finally, we discuss the recent progress in identifying many teleost GnRH-GnRHR and kisspeptin-Kiss-R systems and consider their physiological significance in the control of reproduction. PMID:23482509

  18. Multivoxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

    DEFF Research Database (Denmark)

    Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.

    2013-01-01

    The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection, and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations...... presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple...... within a multivoxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was used to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while...

  19. Processing of signals from an ion-elective electrode array by a neural network

    NARCIS (Netherlands)

    Bos, M.; Bos, A.; van der Linden, W.E.

    1990-01-01

    Neural network software is described for processing the signals of arrays of ion-selective electrodes. The performance of the software was tested in the simultaneous determination of calcium and copper(II) ions in binary mixtures of copper(II) nitrate and calcium chloride and the simultaneous

  20. Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    Sloep, P. B. (2009). Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation. In V. Hornung-Prähauser & M. Luckmann (Eds.), Kreativität und Innovationskompetenz im digitalen Netz - Creativity and Innovation Competencies in the Web, Sammlung von

  1. The rearrangement process in a two-stage broadcast switching network

    DEFF Research Database (Denmark)

    Jacobsen, Søren B.

    1988-01-01

    The rearrangement process in the two-stage broadcast switching network presented by F.K. Hwang and G.W. Richards (ibid., vol.COM-33, no.10, p.1025-1035, Oct. 1985) is considered. By defining a certain function it is possible to calculate an upper bound on the number of connections to be moved...

  2. Efficient Multidimensional Top-k Query Processing in Wireless Multihop Networks

    Directory of Open Access Journals (Sweden)

    Daichi Amagata

    2015-01-01

    processing in a wireless distributed network. In this study, we investigated how to process multidimensional top-k queries efficiently in a wireless multihop network. A major challenge for multidimensional top-k queries is that answers for different users are typically different, because each user has a unique preference and search range. Meanwhile, it is desirable for wireless networks to reduce unnecessary traffic even if users issue top-k queries with their own unique preferences. Therefore, we address the above problem and propose a top-k query processing method in wireless multihop networks, called ClusTo. ClusTo performs a novel clustering scheme for multidimensional top-k query processing and routes queries based on the cluster while guaranteeing the user’s specified search range. Moreover, ClusTo takes a dynamic threshold approach to suppress unnecessary query transmissions to nodes which do not contribute to top-k data retrieval. Extensive experiments on both real and synthetic data have demonstrated that ClusTo outperforms existing methods in terms of traffic and delay.

  3. Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

    DEFF Research Database (Denmark)

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

    2006-01-01

    for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...

  4. A Comparison of Neural Networks and Fuzzy Logic Methods for Process Modeling

    Science.gov (United States)

    Cios, Krzysztof J.; Sala, Dorel M.; Berke, Laszlo

    1996-01-01

    The goal of this work was to analyze the potential of neural networks and fuzzy logic methods to develop approximate response surfaces as process modeling, that is for mapping of input into output. Structural response was chosen as an example. Each of the many methods surveyed are explained and the results are presented. Future research directions are also discussed.

  5. Process optimization of gravure printed light-emitting polymer layers by a neural network approach

    NARCIS (Netherlands)

    Michels, J.J.; Winter, S.H.P.M. de; Symonds, L.H.G.

    2009-01-01

    We demonstrate that artificial neural network modeling is a viable tool to predict the processing dependence of gravure printed light-emitting polymer layers for flexible OLED lighting applications. The (local) thickness of gravure printed light-emitting polymer (LEP) layers was analyzed using

  6. A Process Model of Small Business Owner-Managers' Learning in Peer Networks

    Science.gov (United States)

    Zhang, Jing; Hamilton, Eleanor

    2009-01-01

    Purpose: The purpose of this study is to explore how owner-managers of small businesses can learn in peer networks to improve their management skills. It aims to offer a new way of understanding owner-managers' learning as part of a social process, by highlighting the complex, interactive relationship that exists between the owner-manager, his or…

  7. Reduced Connectivity in the Self-Processing Network of Schizophrenia Patients with Poor Insight

    NARCIS (Netherlands)

    Liemburg, Edith J.; van der Meer, Lisette; Swart, Marte; Curcic-Blake, Branislava; Bruggeman, Richard; Knegtering, Henderikus; Aleman, Andre

    2012-01-01

    Lack of insight (unawareness of illness) is a common and clinically relevant feature of schizophrenia. Reduced levels of self-referential processing have been proposed as a mechanism underlying poor insight. The default mode network (DMN) has been implicated as a key node in the circuit for

  8. Style et rhétorique

    DEFF Research Database (Denmark)

    Pedersen, Eva de la Fuente

    2006-01-01

    En se forgeant un style presque inimitable, qui paraît ébauché, Rembrandt a suscité l'admiration de ses contemporains. Au-delà son apparente spontanéité, ce style fait certainement écho aux préoccupations des théoriciens de l'art contemporains qui attendaient de la peinture, comme de la rhétorique...

  9. In-Network Processing of an Iceberg Join Query in Wireless Sensor Networks Based on 2-Way Fragment Semijoins

    Directory of Open Access Journals (Sweden)

    Hyunchul Kang

    2015-03-01

    Full Text Available We investigate the in-network processing of an iceberg join query in wireless sensor networks (WSNs. An iceberg join is a special type of join where only those joined tuples whose cardinality exceeds a certain threshold (called iceberg threshold are qualified for the result. Processing such a join involves the value matching for the join predicate as well as the checking of the cardinality constraint for the iceberg threshold. In the previous scheme, the value matching is carried out as the main task for filtering non-joinable tuples while the iceberg threshold is treated as an additional constraint. We take an alternative approach, meeting the cardinality constraint first and matching values next. In this approach, with a logical fragmentation of the join operand relations on the aggregate counts of the joining attribute values, the optimal sequence of 2-way fragment semijoins is generated, where each fragment semijoin employs a Bloom filter as a synopsis of the joining attribute values. This sequence filters non-joinable tuples in an energy-efficient way in WSNs. Through implementation and a set of detailed experiments, we show that our alternative approach considerably outperforms the previous one.

  10. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

    Science.gov (United States)

    Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

    2018-01-01

    Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

  11. A Monte Carlo EM approach for partially observable diffusion processes: theory and applications to neural networks.

    Science.gov (United States)

    Movellan, Javier R; Mineiro, Paul; Williams, R J

    2002-07-01

    We present a Monte Carlo approach for training partially observable diffusion processes. We apply the approach to diffusion networks, a stochastic version of continuous recurrent neural networks. The approach is aimed at learning probability distributions of continuous paths, not just expected values. Interestingly, the relevant activation statistics used by the learning rule presented here are inner products in the Hilbert space of square integrable functions. These inner products can be computed using Hebbian operations and do not require backpropagation of error signals. Moreover, standard kernel methods could potentially be applied to compute such inner products. We propose that the main reason that recurrent neural networks have not worked well in engineering applications (e.g., speech recognition) is that they implicitly rely on a very simplistic likelihood model. The diffusion network approach proposed here is much richer and may open new avenues for applications of recurrent neural networks. We present some analysis and simulations to support this view. Very encouraging results were obtained on a visual speech recognition task in which neural networks outperformed hidden Markov models.

  12. EFFICIENCY IMPROVEMENT OF MENEGMENT'S PROCESS COST MENEGMENT IN NETWORK RETAIL BUSINESSES

    OpenAIRE

    Aida Rezyapova

    2016-01-01

    The paper describes the proprietary methodology of distributing administrative expenses in the network retail businesses within the process approach to management, which has been developed to improve the quality of trade expenses administration. To this end, the author suggests using the original base unit (cost driver) in the course of distribution of the subject expenses to improve the accuracy of calculating the trade process efficiency. The author gives reasons to the necessity of applyin...

  13. Knowledge Management Process And Technology Capacityin A Social Sciences Network Research

    OpenAIRE

    VELÁZQUEZ, Lucia Patricia CARRILLO

    2010-01-01

    We understand KM (Knowledge Management) as a strategic process to promote, create and transform the competitive capacity in all kind of organization through diverse knowledge representations. Due to theory development of KM that it has been transform as an emerging discipline. That is closely linked with the telematic technology because it makes possible to operate the KM process. If we observe a network research as an organizational complex system the capacity to appropriate, develop and to ...

  14. Media support for population and RH issues.

    Science.gov (United States)

    1999-12-01

    This article reports the JOICFP press mission, which was instituted in collaboration with the UN Population Fund (UNFPA) of Fiji and participated by three representatives of the mass media. Conducted from September 27 to October 4, this mission aimed to raise the level of understanding of journalists on population and reproductive health (RH) programs supported by the UNFPA in collaboration with its cooperating agencies and nongovernmental organizations (NGOs) in Fiji. It was also hoped that the project will encourage the journalists to write and produced television (TV) programs that would increase the Japanese public's awareness of world population and RH issues. Mission activities included observing training, visiting adolescent clinics, and meeting with beneficiaries and recipients of services provided at various levels. The journalists were satisfied with the tour and appreciated the balance between field observations and discussions. Upon returning to Japan, they wrote and produced several articles and TV programs relating to the mission. Raising public awareness of population and RH issues is important, and working closely with the media can help assure that the message of the NGOs will be heard.

  15. Pregnancy outcome for Rh-alloimmunized women.

    Science.gov (United States)

    Nardozza, L M M; Camano, L; Moron, A F; da Silva Pares, D B; Chinen, P A; Torloni, M R

    2005-08-01

    To compare perinatal results of Rh-alloimmunized pregnancies managed with spectrophotometric amniotic fluid analysis or fetal middle cerebral artery Doppler ultrasonographic velocimetry. A descriptive observational study involving 291 consecutive Rh-negative pregnancies. Group 1 consisted of 74 isoimmunized women managed with amniotic fluid spectrophotometry; group 2 of 25 isoimmunized women managed with Doppler ultrasonography; and group 3 of 192 nonimmunized Rh-negative women. The variables analyzed were need for intrauterine or neonatal transfusion, mode and time of delivery, birth weight, neonatal hematocrit, and perinatal mortality. Need for intrauterine transfusion, birth weight, prematurity, rate of cesarean section, and perinatal mortality were similar in groups 1 and 2. Neonatal hematocrit was significantly lower and the need for neonatal transfusion was significantly higher when spectrophotometry rather than Doppler ultrasonographic velocimetry was used. Fetuses managed with Doppler ultrasonographic velocimetry had a higher hematocrit at birth and a lesser need for neonatal transfusion, suggesting that this noninvasive method of monitoring fetal anemia is a better choice.

  16. Cross-coherent vector sensor processing for spatially distributed glider networks.

    Science.gov (United States)

    Nichols, Brendan; Sabra, Karim G

    2015-09-01

    Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

  17. Using data- and network science to reveal iterations and phase-transitions in the design process

    DEFF Research Database (Denmark)

    Piccolo, Sebastiano; Jørgensen, Sune Lehmann; Maier, Anja

    2017-01-01

    Understanding the role of iterations is a prevalent topic in both design research and design practice. Furthermore, the increasing amount of data produced and stored by companies leaves traces and enables the application of data science to learn from past design processes. In this article, we...... analyse a documentlog to show the temporal evolution of a real design process of a power plant by using exploratory data analysis and network analysis. We show how the iterative nature of the design process is reflected in archival data and how one might re-construct the design process, involving...

  18. Model Building and Optimization Analysis of MDF Continuous Hot-Pressing Process by Neural Network

    Directory of Open Access Journals (Sweden)

    Qingfa Li

    2016-01-01

    Full Text Available We propose a one-layer neural network for solving a class of constrained optimization problems, which is brought forward from the MDF continuous hot-pressing process. The objective function of the optimization problem is the sum of a nonsmooth convex function and a smooth nonconvex pseudoconvex function, and the feasible set consists of two parts, one is a closed convex subset of Rn, and the other is defined by a class of smooth convex functions. By the theories of smoothing techniques, projection, penalty function, and regularization term, the proposed network is modeled by a differential equation, which can be implemented easily. Without any other condition, we prove the global existence of the solutions of the proposed neural network with any initial point in the closed convex subset. We show that any accumulation point of the solutions of the proposed neural network is not only a feasible point, but also an optimal solution of the considered optimization problem though the objective function is not convex. Numerical experiments on the MDF hot-pressing process including the model building and parameter optimization are tested based on the real data set, which indicate the good performance of the proposed neural network in applications.

  19. The sound of emotions-Towards a unifying neural network perspective of affective sound processing.

    Science.gov (United States)

    Frühholz, Sascha; Trost, Wiebke; Kotz, Sonja A

    2016-09-01

    Affective sounds are an integral part of the natural and social environment that shape and influence behavior across a multitude of species. In human primates, these affective sounds span a repertoire of environmental and human sounds when we vocalize or produce music. In terms of neural processing, cortical and subcortical brain areas constitute a distributed network that supports our listening experience to these affective sounds. Taking an exhaustive cross-domain view, we accordingly suggest a common neural network that facilitates the decoding of the emotional meaning from a wide source of sounds rather than a traditional view that postulates distinct neural systems for specific affective sound types. This new integrative neural network view unifies the decoding of affective valence in sounds, and ascribes differential as well as complementary functional roles to specific nodes within a common neural network. It also highlights the importance of an extended brain network beyond the central limbic and auditory brain systems engaged in the processing of affective sounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. A wireless sensor network for vineyard monitoring that uses image processing.

    Science.gov (United States)

    Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

    2011-01-01

    The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.

  1. Analyzing psychotherapy process as intersubjective sensemaking: an approach based on discourse analysis and neural networks.

    Science.gov (United States)

    Nitti, Mariangela; Ciavolino, Enrico; Salvatore, Sergio; Gennaro, Alessandro

    2010-09-01

    The authors propose a method for analyzing the psychotherapy process: discourse flow analysis (DFA). DFA is a technique representing the verbal interaction between therapist and patient as a discourse network, aimed at measuring the therapist-patient discourse ability to generate new meanings through time. DFA assumes that the main function of psychotherapy is to produce semiotic novelty. DFA is applied to the verbatim transcript of the psychotherapy. It defines the main meanings active within the therapeutic discourse by means of the combined use of text analysis and statistical techniques. Subsequently, it represents the dynamic interconnections among these meanings in terms of a "discursive network." The dynamic and structural indexes of the discursive network have been shown to provide a valid representation of the patient-therapist communicative flow as well as an estimation of its clinical quality. Finally, a neural network is designed specifically to identify patterns of functioning of the discursive network and to verify the clinical validity of these patterns in terms of their association with specific phases of the psychotherapy process. An application of the DFA to a case of psychotherapy is provided to illustrate the method and the kinds of results it produces.

  2. Extending pathways and processes using molecular interaction networks to analyse cancer genome data

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2010-12-01

    Full Text Available Abstract Background Cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways. Results We present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. The added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. Finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. Significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes. Conclusions The proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data.

  3. GnRH neurons on LSD: a year of rejecting hypotheses that may have made Karl Popper proud.

    Science.gov (United States)

    Moenter, Suzanne M

    2017-11-08

    Gonadotropin-releasing hormone (GnRH) neurons are critical to many aspects of fertility regulation, from producing episodic release critical to both sexes, to providing a central signal to induce the ovulatory cascade in females. This year saw progress through the rejection, and occasional support, of hypotheses in understanding how GnRH neurons contribute to these processes. This brief review provides one laboratory's view of new insights into possible roles for these cells in development, adult reproductive function, and what may go wrong with GnRH neurons in some cases of infertility. Copyright © 2017 Endocrine Society.

  4. System Cu-Rh-O: Phase diagram and thermodynamic properties of ternary oxides CuRhO2 and CuRh204

    OpenAIRE

    Jacob, KT; Uda, T.; Waseda, Y; Okabe, TH

    1999-01-01

    An isothermal section of the phase diagram for the system Cu-Rh-O at 1273 K has been established by equilibration of samples representing eighteen different compositions, and phase identification after quenching by optical and scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy dispersive analysis of X-rays (EDX). In addition to the binary oxides Cu2O, CuO, and Rh2O3, two ternary oxides CuRhO2 and CuRh2O4 were identified. Both the ternary oxides were in equilibrium with me...

  5. CH{sub 4} dehydrogenation on Cu(1 1 1), Cu@Cu(1 1 1), Rh@Cu(1 1 1) and RhCu(1 1 1) surfaces: A comparison studies of catalytic activity

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Riguang; Duan, Tian [Key Laboratory of Coal Science and Technology of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, Shanxi (China); Ling, Lixia [Key Laboratory of Coal Science and Technology of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, Shanxi (China); Research Institute of Special Chemicals, Taiyuan University of Technology, Taiyuan 030024, Shanxi (China); Wang, Baojun, E-mail: wangbaojun@tyut.edu.cn [Key Laboratory of Coal Science and Technology of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, Shanxi (China)

    2015-06-30

    Highlights: • Adsorbed Rh atom on Cu catalyst exhibits better catalytic activity for CH{sub 4} dehydrogenation. • The adsorbed Rh atom is the reaction active center for CH{sub 4} dehydrogenation. • The morphology of Cu substrate has negligible effect on CH{sub 4} dehydrogenation. - Abstract: In the CVD growth of graphene, the reaction barriers of the dehydrogenation for hydrocarbon molecules directly decide the graphene CVD growth temperature. In this study, density functional theory method has been employed to comparatively probe into CH{sub 4} dehydrogenation on four types of Cu(1 1 1) surface, including the flat Cu(1 1 1) surface (labeled as Cu(1 1 1)) and the Cu(1 1 1) surface with one surface Cu atom substituted by one Rh atom (labeled as RhCu(1 1 1)), as well as the Cu(1 1 1) surface with one Cu or Rh adatom (labeled as Cu@Cu(1 1 1) and Rh@Cu(1 1 1), respectively). Our results show that the highest barrier of the whole CH{sub 4} dehydrogenation process is remarkably reduced from 448.7 and 418.4 kJ mol{sup −1} on the flat Cu(1 1 1) and Cu@Cu(1 1 1) surfaces to 258.9 kJ mol{sup −1} on RhCu(1 1 1) surface, and to 180.0 kJ mol{sup −1} on Rh@Cu(1 1 1) surface, indicating that the adsorbed or substituted Rh atom on Cu catalyst can exhibit better catalytic activity for CH{sub 4} complete dehydrogenation; meanwhile, since the differences for the highest barrier between Cu@Cu(1 1 1) and Cu(1 1 1) surfaces are smaller, the catalytic behaviors of Cu@Cu(1 1 1) surface are very close to the flat Cu(1 1 1) surface, suggesting that the morphology of Cu substrate does not obviously affect the dehydrogenation of CH{sub 4}, which accords with the reported experimental observations. As a result, the adsorbed or substituted Rh atom on Cu catalyst exhibit a better catalytic activity for CH{sub 4} dehydrogenation compared to the pure Cu catalyst, especially on Rh-adsorbed Cu catalyst, we can conclude that the potential of synthesizing high-quality graphene with the

  6. Aeronautical Satellite-Assisted Process for Information Exchange Through Network Technologies (Aero-SAPIENT) Conducted

    Science.gov (United States)

    Zernic, Michael J.

    2002-01-01

    Broadband satellite communications for aeronautics marries communication and network technologies to address NASA's goals in information technology base research and development, thereby serving the safety and capacity needs of the National Airspace System. This marriage of technology increases the interactivity between airborne vehicles and ground systems. It improves decision-making and efficiency, reduces operation costs, and improves the safety and capacity of the National Airspace System. To this end, a collaborative project called the Aeronautical Satellite Assisted Process for Information Exchange through Network Technologies, or Aero-SAPIENT, was conducted out of Tinker AFB, Oklahoma, during November and December 2000.

  7. Segmentation and classification of shallow subbottom acoustic data, using image processing and neural networks

    Science.gov (United States)

    Yegireddi, Satyanarayana; Thomas, Nitheesh

    2014-06-01

    Subbottom acoustic profiler provides acoustic imaging of the subbottom structure constituting the upper sediment layers of the seabed, which is essential for geological and offshore geo-engineering studies. Delineation of the subbottom structure from a noisy acoustic data and classification of the sediment strata is a challenging task with the conventional signal processing techniques. Image processing techniques utilise the spatial variability of the image characteristics, known for their potential in medical imaging and pattern recognition applications. In the present study, they are found to be good in demarcating the boundaries of the sediment layers associated with weak acoustic reflectivity, masked by noisy background. The study deals with application of image processing techniques, like segmentation in identification of subbottom features and extraction of textural feature vectors using grey level co-occurrence matrix statistics. And also attempted classification using Self Organised Map, an unsupervised neural network model utilising these feature vectors. The methodology was successfully demonstrated in demarcating the different sediment layers from the subbottom images and established the sediments constituting the inferred four subsurface sediment layers differ from each other. The network model was also tested for its consistency, with repeated runs of different configuration of the network. Also the ability of simulated network was tested using a few untrained test images representing the similar environment and the classification results show a good agreement with the anticipated.

  8. Inferring Transition Rates of Networks from Populations in Continuous-Time Markov Processes.

    Science.gov (United States)

    Dixit, Purushottam D; Jain, Abhinav; Stock, Gerhard; Dill, Ken A

    2015-11-10

    We are interested inferring rate processes on networks. In particular, given a network's topology, the stationary populations on its nodes, and a few global dynamical observables, can we infer all the transition rates between nodes? We draw inferences using the principle of maximum caliber (maximum path entropy). We have previously derived results for discrete-time Markov processes. Here, we treat continuous-time processes, such as dynamics among metastable states of proteins. The present work leads to a particularly important analytical result: namely, that when the network is constrained only by a mean jump rate, the rate matrix is given by a square-root dependence of the rate, kab ∝ (πb/πa)(1/2), on πa and πb, the stationary-state populations at nodes a and b. This leads to a fast way to estimate all of the microscopic rates in the system. As an illustration, we show that the method accurately predicts the nonequilibrium transition rates in an in silico gene expression network and transition probabilities among the metastable states of a small peptide at equilibrium. We note also that the method makes sensible predictions for so-called extra-thermodynamic relationships, such as those of Bronsted, Hammond, and others.

  9. The effect of network structure on innovation initiation process: an evolutionary dynamics approach

    CERN Document Server

    Jafari, Afshin; Zolfagharzadeh, Mohammad Mahdi; Mohammadi, Mehdi

    2016-01-01

    In this paper we have proposed a basic agent-based model based on evolutionary dynamics for investigating innovation initiation process. In our model we suppose each agent will represent a firm which is interacting with other firms through a given network structure. We consider a two-hit process for presenting a potentially successful innovation in this model and therefore at each time step each firm can be in on of three different stages which are respectively, Ordinary, Innovative, and Successful. We design different experiments in order to investigate how different interaction networks may affect the process of presenting a successful innovation to the market. In this experiments, we use five different network structures, i.e. Erd\\H{o}s and R\\'enyi, Ring Lattice, Small World, Scale-Free and Distance-Based networks. According to the results of the simulations, for less frequent innovations like radical innovation, local structures are showing a better performance comparing to Scale-Free and Erd\\H{o}s and R\\...

  10. EFFICIENCY IMPROVEMENT OF MENEGMENT'S PROCESS COST MENEGMENT IN NETWORK RETAIL BUSINESSES

    Directory of Open Access Journals (Sweden)

    Aida Rezyapova

    2016-12-01

    Full Text Available The paper describes the proprietary methodology of distributing administrative expenses in the network retail businesses within the process approach to management, which has been developed to improve the quality of trade expenses administration. To this end, the author suggests using the original base unit (cost driver in the course of distribution of the subject expenses to improve the accuracy of calculating the trade process efficiency. The author gives reasons to the necessity of applying a comprehensive approach in its selection. This implies use, as the base unit, of a coefficient representing shop turnover per 1m2 of sales area. The author has made a coefficient rating to formalize the relationship between the management results and economic factors of the trade businesses risk. This approach takes into account the commodity prime cost, and the quality and economic efficiency of the management processes in selling subdivisions of a network business.

  11. Modeling delay in genetic networks: from delay birth-death processes to delay stochastic differential equations.

    Science.gov (United States)

    Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Bennett, Matthew R; Josić, Krešimir; Ott, William

    2014-05-28

    Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

  12. Portraying the unique contribution of the default mode network to internally driven mnemonic processes.

    Science.gov (United States)

    Shapira-Lichter, Irit; Oren, Noga; Jacob, Yael; Gruberger, Michal; Hendler, Talma

    2013-03-26

    Numerous neuroimaging studies have implicated default mode network (DMN) involvement in both internally driven processes and memory. Nevertheless, it is unclear whether memory operations reflect a particular case of internally driven processing or alternatively involve the DMN in a distinct manner, possibly depending on memory type. This question is critical for refining neurocognitive memory theorem in the context of other endogenic processes and elucidating the functional significance of this key network. We used functional MRI to examine DMN activity and connectivity patterns while participants overtly generated words according to nonmnemonic (phonemic) or mnemonic (semantic or episodic) cues. Overall, mnemonic word fluency was found to elicit greater DMN activity and stronger within-network functional connectivity compared with nonmnemonic fluency. Furthermore, two levels of functional organization of memory retrieval were shown. First, across both mnemonic tasks, activity was greater mainly in the posterior cingulate cortex, implying selective contribution to generic aspects of memory beyond its general involvement in endogenous processes. Second, parts of the DMN showed distinct selectivity for each of the mnemonic conditions; greater recruitment of the anterior prefrontal cortex, retroesplenial cortex, and hippocampi and elevated connectivity between anterior and posterior medial DMN nodes characterized the semantic condition, whereas increased recruitment of posterior DMN components and elevated connectivity between them characterized the episodic condition. This finding emphasizes the involvement of DMN elements in discrete aspects of memory retrieval. Altogether, our results show a specific contribution of the DMN to memory processes, corresponding to the specific type of memory retrieval.

  13. Analysis of eco-hydrological control and feedback using data-derived entropic process networks

    Science.gov (United States)

    Ruddell, B. L.; Praveen, K.

    2007-12-01

    We hypothesize that plant ecosystems form self-organizing systems on the landscape which function to control their immediate surroundings towards the end of improving the efficiency of community carbon assimilation. Self- organization is difficult to define, but the concept requires the presence of feedbacks. Flows of control and feedbacks may be studied using network theory. This research uses entropy-based statistics of information flow to render the eco-hydrological system as a process network empirically derived from multivariate timeseries datasets. The resulting process network is analyzed to identify ecosystem controls and feedbacks and to separate different modes of system behavior. This approach is applied to the central corn belt eco-region using FLUXNET eddy-covariance timeseries data. Results indicate that plant respiration is a dominant controller of the interaction in the network of variables, including CO2 flux and sensible heat flux under well-watered conditions, and latent heat flux (but not CO2 flux) under drought conditions. Respiration is not controlled directly by other processes in the network, indicating that respiration is an independent (information-driven) mechanism of control by plants. Under drought conditions the ecosystem loses its ability to control CO2 assimilation through respiration, in agreement with the Ball-Berry model. CO2 flux inhabits a control feedback loop via latent and sensible heat flux, precipitation and cloud conditions, suggesting that carbon assimilation activity forms the basis of a self-organizing system spanning the Atmospheric Boundary Layer. Our finding that plants regulate their environment and CO2 uptake by modifying respiration, and that carbon assimilation feeds back on itself via atmospheric processes, supports the hypothesis that this ecosystem is self-organizing.

  14. Noninvertibility and resonance in discrete-time neural networks for time-series processing

    Science.gov (United States)

    Gicquel, N.; Anderson, J. S.; Kevrekidis, I. G.

    1998-01-01

    We present a computer-assisted study emphasizing certain elements of the dynamics of artificial neural networks (ANNs) used for discrete time-series processing and nonlinear system identification. The structure of the network gives rise to the possibility of multiple inverses of a phase point backward in time; this is not possible for the continuous-time system from which the time series are obtained. Using a two-dimensional illustrative model in an oscillatory regime, we study here the interaction of attractors predicted by the discrete-time ANN model (invariant circles and periodic points locked on them) with critical curves. These curves constitute a generalization of critical points for maps of the interval (in the sense of Julia-Fatou); their interaction with the model-predicted attractors plays a crucial role in the organization of the bifurcation structure and ultimately in determining the dynamic behavior predicted by the neural network.

  15. Exact mean field dynamics for epidemic-like processes on heterogeneous networks

    CERN Document Server

    Lucas, Andrew

    2012-01-01

    We show that the mean field equations for the SIR epidemic can be exactly solved for a network with arbitrary degree distribution. Our exact solution consists of reducing the dynamics to a lone first order differential equation, which has a solution in terms of an integral over functions dependent on the degree distribution of the network, and reconstructing all mean field functions of interest from this integral. Irreversibility of the SIR epidemic is crucial for the solution. We also find exact solutions to the sexually transmitted disease SI epidemic on bipartite graphs, to a simplified rumor spreading model, and to a new model for recommendation spreading, via similar techniques. Numerical simulations of these processes on scale free networks demonstrate the qualitative validity of mean field theory in most regimes.

  16. Networks of power in digital copyright law and policy political salience, expertise and the legislative process

    CERN Document Server

    Farrand, Benjamin

    2014-01-01

    In this book, Benjamin Farrand employs an interdisciplinary approach that combines legal analysis with political theory to explore the development of copyright law in the EU. Farrand utilises Foucault's concept of Networks of Power and Culpepper's Quiet Politics to assess the adoption and enforcement of copyright law in the EU, including the role of industry representative, cross-border licensing, and judicial approaches to territorial restrictions. Focusing in particular on legislative initiatives concerning copyright, digital music and the internet, Networks of Power in Digital Copyright Law and Policy: Political Salience, Expertise and the Legislative Process demonstrates the connection between copyright law and complex network relationships. This book presents an original socio-political theoretical framework for assessing developments in copyright law that will interest researchers and post-graduate students of law and politics, as well as those more particularly concerned with political theory, EU and c...

  17. Stochastic dynamical model of a growing citation network based on a self-exciting point process.

    Science.gov (United States)

    Golosovsky, Michael; Solomon, Sorin

    2012-08-31

    We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

  18. Tracking disease progression by searching paths in a temporal network of biological processes.

    Science.gov (United States)

    Anand, Rajat; Chatterjee, Samrat

    2017-01-01

    Metabolic disorders such as obesity and diabetes are diseases which develop gradually over time through the perturbations of biological processes. These perturbed biological processes usually work in an interdependent way. Systematic experiments tracking disease progression at gene level are usually conducted through a temporal microarray data. There is a need for developing methods to analyze such highly complex data to capture disease progression at the molecular level. In the present study, we have considered temporal microarray data from an experiment conducted to study development of obesity and diabetes in mice. We first constructed a network between biological processes through common genes. We analyzed the data to obtain perturbed biological processes at each time point. Finally, we used the biological process network to find links between these perturbed biological processes. This enabled us to identify paths linking initial perturbed processes with final perturbed processes which capture disease progression. Using different datasets and statistical tests, we established that these paths are highly precise to the dataset from which these are obtained. We also established that the connecting genes present in these paths might contain some biological information and thus can be used for further mechanistic studies. The methods developed in our study are also applicable to a broad array of temporal data.

  19. Artificial neural network approach to modeling of alcoholic fermentation of thick juice from sugar beet processing

    Directory of Open Access Journals (Sweden)

    Jokić Aleksandar I.

    2012-01-01

    Full Text Available In this paper the bioethanol production in batch culture by free Saccharomyces cerevisiae cells from thick juice as intermediate product of sugar beet processing was examined. The obtained results suggest that it is possible to decrease fermentation time for the cultivation medium based on thick juice with starting sugar content of 5-15 g kg-1. For the fermentation of cultivation medium based on thick juice with starting sugar content of 20 and 25 g kg-1 significant increase in ethanol content was attained during the whole fermentation process, resulting in 12.51 and 10.95 dm3 m-3 ethanol contents after 48 h, respectively. Other goals of this work were to investigate the possibilities for experimental results prediction using artificial neural networks (ANNs and to find its optimal topology. A feed-forward back-propagation artificial neural network was used to test the hypothesis. As input variables fermentation time and starting sugar content were used. Neural networks had one output value, ethanol content, yeast cell number or sugar content. There was one hidden layer and the optimal number of neurons was found to be nine for all selected network outputs. In this study transfer function was tansig and the selected learning rule was Levenberg-Marquardt. Results suggest that artificial neural networks are good prediction tool for selected network outputs. It was found that experimental results are in very good agreement with computed ones. The coefficient of determination (the R-squared was found to be 0.9997, 0.9997 and 0.9999 for ethanol content, yeast cell number and sugar content, respectively.

  20. Application of Neural Network Modeling to Identify Auditory Processing Disorders in School-Age Children

    Directory of Open Access Journals (Sweden)

    Sridhar Krishnamurti

    2015-01-01

    Full Text Available P300 Auditory Event-Related Potentials (P3AERPs were recorded in nine school-age children with auditory processing disorders and nine age- and gender-matched controls in response to tone burst stimuli presented at varying rates (1/second or 3/second under varying levels of competing noise (0 dB, 40 dB, or 60 dB SPL. Neural network modeling results indicated that speed of information processing and task-related demands significantly influenced P3AERP latency in children with auditory processing disorders. Competing noise and rapid stimulus rates influenced P3AERP amplitude in both groups.

  1. The improvement of maintenance service for traction networks equipment on the base of process approach

    Directory of Open Access Journals (Sweden)

    D. V. Mironov

    2014-12-01

    Full Text Available Purpose. The new methods development for improving the maintenance service for equipment of traction networks in order to increase its efficiency and quality. Methodology. In world practice of solving problems related to the quality of products and services is usually achieved by introducing quality management system in to the enterprises. The provisions of quality management system were used for solving the problem. The technologies of process engineering were used for describing the main stages of maintenance service. Findings. The development of high-speed movement and growth of its intensity, the use of electric rolling stock of a new generation require the introduction of new methods diagnostics of equipment technical state and improvement of the existing maintenance system and repair of power supply. Developing a model of business-processes, their optimization with using techniques of process engineering and system management is needed for the transition to the management system based on the process approach. From the standpoint of the process approach and in accordance with the requirements of the quality management system (ISO 9001-2009, the operation of the E (Department of electrification and power supply infrastructure sector is represented as a scheme of business-processes in which the guaranteed supply with electricity of railway and third-party consumers is defined as the main business-process of management. Each of the sub-process of power supply for consumers is described in details. The use methods and main stages of process approach for sample management system reorganization were investigated. The methodology and the application method of PDCA (Plan-Do-Check-Act closed loop to the equipment maintenance system were described. The monitoring process of traction networks maintenance using the process approach was divided into components after investigations. The technical documentation of maintenance service was investigated in

  2. Face Patch Resting State Networks Link Face Processing to Social Cognition.

    Directory of Open Access Journals (Sweden)

    Caspar M Schwiedrzik

    Full Text Available Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

  3. Face Patch Resting State Networks Link Face Processing to Social Cognition

    Science.gov (United States)

    Schwiedrzik, Caspar M.; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A.

    2015-01-01

    Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills. PMID:26348613

  4. Face Patch Resting State Networks Link Face Processing to Social Cognition.

    Science.gov (United States)

    Schwiedrzik, Caspar M; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A

    2015-01-01

    Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

  5. Analysis and validation center for ITER RH maintenance scenarios in a virtual environment

    Energy Technology Data Exchange (ETDEWEB)

    Elzendoorn, B.S.Q., E-mail: B.S.Q.Elzendoorn@rijnhuizen.nl [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Partner in the Trilateral Euregio Cluster and ITER-NL, PO Box 1207, 3430 BE, Nieuwegein (Netherlands); Baar, M. de [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Partner in the Trilateral Euregio Cluster and ITER-NL, PO Box 1207, 3430 BE, Nieuwegein (Netherlands); Hamilton, D. [ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 St. Paul-lez-Durance Cedex (France); Heemskerk, C.J.M. [Heemskerk Innovative Technology, Sassenheim (Netherlands); Koning, J.F.; Ronden, D.M.S. [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Partner in the Trilateral Euregio Cluster and ITER-NL, PO Box 1207, 3430 BE, Nieuwegein (Netherlands)

    2012-03-15

    A facility for detailed simulation of maintenance processes in the ITER Hot Cell Facility (HCF) has been taken into operation. The facility mimics the Remote Handling (RH) work-cells as are presently foreseen. Novel virtual reality (VR) technology, extended with a physics engine is used to create a realistic setting in which a team of Remote Handling (RH) operators can interact with a virtual Hot Cell environment. The physics engine is used to emulate the Hot Cell behavior and to provide tactile feed-back of the (virtual) slave. Multi-operator maintenance scenarios can be developed and tested in virtual reality. Complex interactions between the RH operators and the HCF control system software will be tested. Task performance will be quantified and operational resource consumption will be estimated.

  6. ‘Living' theory: a pedagogical framework for process support in networked learning

    Directory of Open Access Journals (Sweden)

    Philipa Levy

    2006-12-01

    Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

  7. Information theory and signal transduction systems: from molecular information processing to network inference.

    Science.gov (United States)

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. A neural network based model to analyze rice parboiling process with small dataset.

    Science.gov (United States)

    Behroozi-Khazaei, Nasser; Nasirahmadi, Abozar

    2017-07-01

    In this study, milling recovery, head rice yield, degree of milling and whiteness were utilized to characterize the milling quality of Tarom parboiled rice variety. The parboiled rice was prepared with three soaking temperatures and steaming times. Then the samples were dried to three levels of final moisture contents [8, 10 and 12% (w.b)]. Modeling of process and validating of the results with small dataset are always challenging. So, the aim of this study was to develop models based on the milling quality data in parboiling process by means of multivariate regression and artificial neural network. In order to validate the neural network model with a little dataset, K-fold cross validation method was applied. The ANN structure with one hidden layer and Tansig transfer function by 18 neurons in the hidden layer was selected as the best model in this study. The results indicated that the neural network could model the parboiling process with higher degree of accuracy. This method was a promising procedure to create accuracy and can be used as a reliable model to select the best parameters for the parboiling process with little experiment dataset.

  9. Process Network Approach to Understanding How Forest Ecosystems Adapt to Changes

    Science.gov (United States)

    Kim, J.; Yun, J.; Hong, J.; Kwon, H.; Chun, J.

    2011-12-01

    Sustainability challenges are transforming science and its role in society. Complex systems science has emerged as an inevitable field of education and research, which transcends disciplinary boundaries and focuses on understanding of the dynamics of complex social-ecological systems (SES). SES is a combined system of social and ecological components and drivers that interact and give rise to results, which could not be understood on the basis of sociological or ecological considerations alone. However, both systems may be viewed as a network of processes, and such a network hierarchy may serve as a hinge to bridge social and ecological systems. As a first step toward such effort, we attempted to delineate and interpret such process networks in forest ecosystems, which play a critical role in the cycles of carbon and water from local to global scales. These cycles and their variability, in turn, play an important role in the emergent and self-organizing interactions between forest ecosystems and their environment. Ruddell and Kumar (2009) define a process network as a network of feedback loops and the related time scales, which describe the magnitude and direction of the flow of energy, matter, and information between the different variables in a complex system. Observational evidence, based on micrometeorological eddy covariance measurements, suggests that heterogeneity and disturbances in forest ecosystems in monsoon East Asia may facilitate to build resilience for adaptation to change. Yet, the principles that characterize the role of variability in these interactions remain elusive. In this presentation, we report results from the analysis of multivariate ecohydrologic and biogeochemical time series data obtained from temperate forest ecosystems in East Asia based on information flow statistics.

  10. The feasibility of genome-scale biological network inference using Graphics Processing Units.

    Science.gov (United States)

    Thiagarajan, Raghuram; Alavi, Amir; Podichetty, Jagdeep T; Bazil, Jason N; Beard, Daniel A

    2017-01-01

    Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical inference-based approaches and methods to identify dynamical systems models that are capable of fitting multivariate data. Availability of large data sets and so-called 'big data' applications in biology present great opportunities as well as major challenges for systems identification/reverse engineering applications. For example, both inverse identification and forward simulations of genome-scale gene regulatory network models pose compute-intensive problems. This issue is addressed here by combining the processing power of Graphics Processing Units (GPUs) and a parallel reverse engineering algorithm for inference of regulatory networks. It is shown that, given an appropriate data set, information on genome-scale networks (systems of 1000 or more state variables) can be inferred using a reverse-engineering algorithm in a matter of days on a small-scale modern GPU cluster.

  11. Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system.

    Science.gov (United States)

    Ma, Xiaofeng; Kohashi, Tsunehiko; Carlson, Bruce A

    2013-07-01

    Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

  12. Functional MRI reveals compromised neural integrity of the face processing network in congenital prosopagnosia

    Science.gov (United States)

    Avidan, Galia; Behrmann, Marlene

    2009-01-01

    Summary There is growing consensus that the summed activity of multiple nodes of a distributed cortical network supports face recognition in humans, including “core” ventral occipito-temporal cortex (VOTC) regions [1-3], as well as “extended” regions outside VOTC [4, 5]. Surprisingly, many individuals with congenital prosopagnosia – a lifelong impairment in face processing [6-9] -- exhibit normal BOLD activation in the “core” VOTC regions [10] (but see [11]). Interestingly, these same individuals evince a reduction in the structural integrity of the white matter tracts connecting VOTC to anterior temporal and frontal cortices [12] which form part of the “extended” face network. These findings suggest that the profound impairment in congenital prosopagnosia may arise not from a dysfunction of the core VOTC areas per se but from a failure to propagate signals between the intact VOTC and the extended nodes of the network. Here, using the fMR adaptation paradigm with famous and unknown faces, we show that individuals with congenital prosopagnosia evince normal adaptation effects in VOTC, indicating sensitivity to facial identity, but, unlike controls, show no differential activation for familiar versus unknown faces outside VOTC, particularly in the precuneus/posterior cingulate cortex and the anterior paracingulate cortex. These results indicate that normal BOLD activation in VOTC is insufficient to subserve intact face recognition, and support the hypothesis that disrupted information propagation between VOTC and the extended face processing network underlies the functional impairment in congenital prosopagnosia. PMID:19481456

  13. Analyzing long-term correlated stochastic processes by means of recurrence networks: potentials and pitfalls.

    Science.gov (United States)

    Zou, Yong; Donner, Reik V; Kurths, Jürgen

    2015-02-01

    Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm [Liu et al. Phys. Rev. E 89, 032814 (2014)] are mainly due to an inappropriate treatment disregarding the intrinsic nonstationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, given a proper selection of its intrinsic methodological parameters, whereas it is prone to fail to uniquely retrieve RN properties for nonstationary stochastic processes like fBm.

  14. On the increase in network robustness and decrease in network response ability during the aging process: a systems biology approach via microarray data.

    Science.gov (United States)

    Tu, Chien-Ta; Chen, Bor-Sen

    2013-01-01

    Aging, an extremely complex and system-level process, has attracted much attention in medical research, especially since chronic diseases are quite prevalent in the elderly population. These may be the result of both gene mutations that lead to intrinsic perturbations and environmental changes that may stimulate signaling in the body. Therefore, analysis of network robustness to tolerate intrinsic perturbations and network response ability of gene networks to respond to external stimuli during the aging process may provide insight into the systematic changes caused by aging. We first propose novel methods to estimate network robustness and measure network response ability of gene regulatory networks by using their corresponding microarray data in the aging process. Then, we find that an aging-related gene network is more robust to intrinsic perturbations in the elderly than the young, and therefore is less responsive to external stimuli. Finally, we find that the response abilities of individual genes, especially FOXOs, NF-κB, and p53, are significantly different in the young versus the aged subjects. These observations are consistent with experimental findings in the aged population, e.g., elevated incidence of tumorigenesis and diminished resistance to oxidative stress. The proposed method can also be used for exploring and analyzing the dynamic properties of other biological processes via corresponding microarray data to provide useful information on clinical strategy and drug target selection.

  15. Intrauterine Transfusion in Maternal Rh Immunization

    OpenAIRE

    Cabral Antonio Carlos Vieira; Taveira Marcos Roberto; Lopes Ana Paula Brum Miranda; Pereira Alamanda Kfoury; Leite Henrique Vitor

    2001-01-01

    Objetivos: avaliar os resultados do tratamento intra-útero de fetos anêmicos devido a isoimunização materna pelo fator Rh. Pacientes e Métodos: foram acompanhados 61 fetos submetidos a transfusão intra-uterina seja por via intraperitoneal, intravascular ou combinada. Os casos de fetos hidrópicos corresponderam a 19,7% do total, sendo que nestes a via de tratamento sempre foi a intravascular. Foram realizadas em média 2,7 transfusões por feto, com um total de 163 procedimentos. A indicação par...

  16. Chiral bands in {sup 105}Rh

    Energy Technology Data Exchange (ETDEWEB)

    Alcantara-Nunez, J.A.; Oliveira, J.R.B.; Cybulska, E.W.; Medina, N.H.; Rao, M.N.; Ribas, R.V.; Rizzutto, M.A.; Seale, W.A.; Falla-Sotelo, F.; Wiedemann, K.T. [Sao Paulo Univ., SP (Brazil). Inst. de Fisica; Dimitrov, V.I.; Frauendorf, S. [University of Notre Dame, Notre Dame, IN (United States). Dept. of Physics; Research Center Rossendorf, Dresden (Germany). Institute for Nuclear and Hadronic Physics

    2004-09-15

    The {sup 105}Rh nucleus has been studied by in-beam {gamma} spectroscopy with the heavy-ion fusion-evaporation reaction {sup 100}Mo({sup 11}B, {alpha}2n{gamma}) at 43 MeV. A rich variety of structures was observed at high and low spin, using {gamma}-{gamma}-t and {gamma}-{gamma}-particle coincidences and directional correlation ratios. Four magnetic dipole bands have also been observed at high spin. Two of them are nearly degenerate in excitation energy and could be chiral partners, as predicted by Tilted Axis Cranking calculations. (author)

  17. Bilirubin encephalopathy due to Rh incompatibility

    Directory of Open Access Journals (Sweden)

    Taísa Roberta Ramos Nantes de Castilho

    2011-06-01

    Full Text Available The authors present the case of a newborn of an Rh-factorsensitizedmother, who received early hospital discharge while icteric only to be readmitted at an Emergency Service at five days of age with signs of kernicterus. Despite treatment given, the neonate progressed with a clinical picture of bilirubin encephalopathy. The lack of interaction between the obstetric and neonatal teams, premature hospital discharge, and lack of concern of neonatologists with jaundice in a full-term infant are highlighted as causes of a condition that should have disappeared if there had been adequateprevention.

  18. Node making process in network meta-analysis of non-pharmacological treatment are poorly reported.

    Science.gov (United States)

    James, Arthur; Yavchitz, Amélie; Ravaud, Philippe; Boutron, Isabelle

    2017-11-28

    Identify methods to support the node-making process in network meta-analyses (NMAs) of non-pharmacological treatments. We proceeded in two stages. First, we conducted a literature review of guidelines and methodological articles about NMAs to identify methods proposed to lump interventions into nodes. Second, we conducted a systematic review of NMAs of non-pharmacological treatments to extract methods used by authors to support their node-making process. MEDLINE and Google Scholar were searched to identify articles assessing NMA guidelines or methodology intended for NMA authors. MEDLINE, CENTRAL and EMBASE were searched to identify reports of NMAs including at least one non-pharmacological treatment. Both searches involved articles available from database inception to March 2016. From the methodological review, we identified and extracted methods proposed to lump interventions into nodes. From the systematic review, the reporting of the network was assessed as long as the method described supported the node-making process. Among the 116 articles retrieved in the literature review, 12 (10%) discussed the concept of lumping or splitting interventions in NMAs. No consensual method was identified during the methodological review, and expert consensus was the only method proposed to support the node-making process. Among 5187 references for the systematic review, we included 110 reports of NMAs published between 2007 and 2016. The nodes were described in the introduction section of 88 reports (80%), which suggested that the node content might have been a priori decided before the systematic review. Nine reports (8.1%) described a specific process or justification to build nodes for the network. Two methods were identified: 1) fit a previously published classification and 2) expert consensus. Despite the importance of NMA in the delivery of evidence when several interventions are available for a single indication, recommendations on the reporting of the node

  19. Synthesis of neural networks for spatio-temporal spike pattern recognition and processing

    Directory of Open Access Journals (Sweden)

    Jonathan C Tapson

    2013-08-01

    Full Text Available The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify – arbitrarily - neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times.

  20. Optimization of magnetically driven directional solidification of silicon using artificial neural networks and Gaussian process models

    Science.gov (United States)

    Dropka, Natasha; Holena, Martin

    2017-08-01

    In directional solidification of silicon, the solid-liquid interface shape plays a crucial role for the quality of crystals. The interface shape can be influenced by forced convection using travelling magnetic fields. Up to now, there is no general and explicit methodology to identify the relation and the optimum combination of magnetic and growth parameters e.g., frequency, phase shift, current magnitude and interface deflection in a buoyancy regime. In the present study, 2D CFD modeling was used to generate data for the design and training of artificial neural networks and for Gaussian process modeling. The aim was to quickly assess the complex nonlinear dependences among the parameters and to optimize them for the interface flattening. The first encouraging results are presented and the pros and cons of artificial neural networks and Gaussian process modeling discussed.

  1. Information Processing in Single Cells and Small Networks: Insights from Compartmental Models

    Science.gov (United States)

    Poirazi, Panayiota

    2009-03-01

    The goal of this paper is to present a set of predictions generated by detailed compartmental models regarding the ways in which information may be processed, encoded and propagated by single cells and neural assemblies. Towards this goal, I will review a number of modelling studies from our lab that investigate how single pyramidal neurons and small neural networks in different brain regions process incoming signals that are associated with learning and memory. I will first discuss the computational capabilities of individual pyramidal neurons in the hippocampus [1-3] and how these properties may allow a single cell to discriminate between different memories [4]. I will then present biophysical models of prefrontal layer V neurons and small networks that exhibit sustained activity under realistic synaptic stimulation and discuss their potential role in working memory [5].

  2. Determination of Optimal Opening Scheme for Electromagnetic Loop Networks Based on Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Yang Li

    2016-01-01

    Full Text Available Studying optimization and decision for opening electromagnetic loop networks plays an important role in planning and operation of power grids. First, the basic principle of fuzzy analytic hierarchy process (FAHP is introduced, and then an improved FAHP-based scheme evaluation method is proposed for decoupling electromagnetic loop networks based on a set of indicators reflecting the performance of the candidate schemes. The proposed method combines the advantages of analytic hierarchy process (AHP and fuzzy comprehensive evaluation. On the one hand, AHP effectively combines qualitative and quantitative analysis to ensure the rationality of the evaluation model; on the other hand, the judgment matrix and qualitative indicators are expressed with trapezoidal fuzzy numbers to make decision-making more realistic. The effectiveness of the proposed method is validated by the application results on the real power system of Liaoning province of China.

  3. Recognition of Roasted Coffee Bean Levels using Image Processing and Neural Network

    Science.gov (United States)

    Nasution, T. H.; Andayani, U.

    2017-03-01

    The coffee beans roast levels have some characteristics. However, some people cannot recognize the coffee beans roast level. In this research, we propose to design a method to recognize the coffee beans roast level of images digital by processing the image and classifying with backpropagation neural network. The steps consist of how to collect the images data with image acquisition, pre-processing, feature extraction using Gray Level Co-occurrence Matrix (GLCM) method and finally normalization of data extraction using decimal scaling features. The values of decimal scaling features become an input of classifying in backpropagation neural network. We use the method of backpropagation to recognize the coffee beans roast levels. The results showed that the proposed method is able to identify the coffee roasts beans level with an accuracy of 97.5%.

  4. Dynamical Behavior of Delayed Reaction-Diffusion Hopfield Neural Networks Driven by Infinite Dimensional Wiener Processes.

    Science.gov (United States)

    Liang, Xiao; Wang, Linshan; Wang, Yangfan; Wang, Ruili

    2016-09-01

    In this paper, we focus on the long time behavior of the mild solution to delayed reaction-diffusion Hopfield neural networks (DRDHNNs) driven by infinite dimensional Wiener processes. We analyze the existence, uniqueness, and stability of this system under the local Lipschitz function by constructing an appropriate Lyapunov-Krasovskii function and utilizing the semigroup theory. Some easy-to-test criteria affecting the well-posedness and stability of the networks, such as infinite dimensional noise and diffusion effect, are obtained. The criteria can be used as theoretic guidance to stabilize DRDHNNs in practical applications when infinite dimensional noise is taken into consideration. Meanwhile, considering the fact that the standard Brownian motion is a special case of infinite dimensional Wiener process, we undertake an analysis of the local Lipschitz condition, which has a wider range than the global Lipschitz condition. Two samples are given to examine the availability of the results in this paper. Simulations are also given using the MATLAB.

  5. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  6. Green supply chain management strategy selection using analytic network process: case study at PT XYZ

    Science.gov (United States)

    Adelina, W.; Kusumastuti, R. D.

    2017-01-01

    This study is about business strategy selection for green supply chain management (GSCM) for PT XYZ by using Analytic Network Process (ANP). GSCM is initiated as a response to reduce environmental impacts from industrial activities. The purposes of this study are identifying criteria and sub criteria in selecting GSCM Strategy, and analysing a suitable GSCM strategy for PT XYZ. This study proposes ANP network with 6 criteria and 29 sub criteria, which are obtained from the literature and experts’ judgements. One of the six criteria contains GSCM strategy options, namely risk-based strategy, efficiency-based strategy, innovation-based strategy, and closed loop strategy. ANP solves complex GSCM strategy-selection by using a more structured process and considering green perspectives from experts. The result indicates that innovation-based strategy is the most suitable green supply chain management strategy for PT XYZ.

  7. The improving of the heat networks operating process under the conditions of the energy efficiency providing

    Directory of Open Access Journals (Sweden)

    Blinova Tatiana

    2016-01-01

    Full Text Available Among the priorities it is important to highlight the modernization and improvement of energy efficiency of housing and communal services, as well as the transition to the principle of using the most efficient technologies used in reproduction (construction, creation of objects of municipal infrastructure and housing modernization. The main hypothesis of this study lies in the fact that in modern conditions the realization of the most important priorities of the state policy in the sphere of housing and communal services, is possible in the conditions of use of the most effective control technologies for the reproduction of thermal networks. It is possible to raise the level of information security Heat Distribution Company, and other market participants by improving business processes through the development of organizational and economic mechanism in the conditions of complex monitoring of heat network operation processes

  8. Sensitivity analysis of a branching process evolving on a network with application in epidemiology

    CERN Document Server

    Hautphenne, Sophie; Delvenne, Jean-Charles; Blondel, Vincent D

    2015-01-01

    We perform an analytical sensitivity analysis for a model of a continuous-time branching process evolving on a fixed network. This allows us to determine the relative importance of the model parameters to the growth of the population on the network. We then apply our results to the early stages of an influenza-like epidemic spreading among a set of cities connected by air routes in the United States. We also consider vaccination and analyze the sensitivity of the total size of the epidemic with respect to the fraction of vaccinated people. Our analysis shows that the epidemic growth is more sensitive with respect to transmission rates within cities than travel rates between cities. More generally, we highlight the fact that branching processes offer a powerful stochastic modeling tool with analytical formulas for sensitivity which are easy to use in practice.

  9. Inferring long memory processes in the climate network via ordinal pattern analysis

    CERN Document Server

    Barreiro, Marcelo; Masoller, Cristina

    2010-01-01

    We use ordinal patterns and symbolic analysis to construct global climate networks and uncover long and short term memory processes. The data analyzed is the monthly averaged surface air temperature (SAT field) and the results suggest that the time variability of the SAT field is determined by patterns of oscillatory behavior that repeat from time to time, with a periodicity related to intraseasonal oscillations and to El Ni\\~{n}o on seasonal-to-interannual time scales.

  10. Administrative professional's role in the processing, retrieval, dissemination and repackaging of information in the networked enterprise

    OpenAIRE

    2008-01-01

    The purpose of this research was to establish the administrative professional's role in the processing, retrieval, dissemination and repackaging of digital information in the networked enterprise, and to determine how the administrative professional can add value to the organisation and enhance its competitive position in industry. The digital economy has changed business practices to such an extent that research of the digital office environment and the administrative professional’s role in ...

  11. ANALYTIC NETWORK PROCESS AND BALANCED SCORECARD APPLIED TO THE PERFORMANCE EVALUATION OF PUBLIC HEALTH SYSTEMS

    Directory of Open Access Journals (Sweden)

    Marco Aurélio Reis dos Santos

    2015-08-01

    Full Text Available The performance of public health systems is an issue of great concern. After all, to assure people's quality of life, public health systems need different kinds of resources. Balanced Scorecard provides a multi-dimensional evaluation framework. This paper presents the application of the Analytic Network Process and Balanced Scorecard in the performance evaluation of a public health system in a typical medium-sized Southeastern town in Brazil.

  12. Neural network computation for the evaluation of process rendering: application to thermally sprayed coatings

    Directory of Open Access Journals (Sweden)

    Guessasma Sofiane

    2017-01-01

    Full Text Available In this work, neural network computation is attempted to relate alumina and titania phase changes of a coating microstructure with respect to energetic parameters of atmospheric plasma straying (APS process. Experimental results were analysed using standard fitting routines and neural computation to quantify the effect of arc current, hydrogen ratio and total plasma flow rate. For a large parameter domain, phase changes were 10% for alumina and 8% for titania with a significant control of titania phase.

  13. Fighting Dark Networks: Using Social Network Analysis to Implement the Special Operations Targeting Process for Direct and Indirect Approaches

    Science.gov (United States)

    2013-03-01

    environmental impacts -- must be considered. H. A FINAL WORD ON SNA CONCEPTS AND DARK NETWORKS. To construct a useful database of network relational...http://www.jstor.org/stable/2780199?origin= JSTOR -pdf. 145 30 Martin Kilduff and Wenpin Tsai, Social Networks and Organizations (London: SAGE, 2003

  14. Analysis and design of networks-on-chip under high process variation

    CERN Document Server

    Ezz-Eldin, Rabab; Hamed, Hesham F A

    2015-01-01

    This book describes in detail the impact of process variations on Network-on-Chip (NoC) performance. The authors evaluate various NoC topologies under high process variation and explain the design of efficient NoCs, with advanced technologies. The discussion includes variation in logic and interconnect, in order to evaluate the delay and throughput variation with different NoC topologies. The authors describe an asynchronous router, as a robust design to mitigate the impact of process variation in NoCs and the performance of different routing algorithms is determined with/without process variation for various traffic patterns. Additionally, a novel Process variation Delay and Congestion aware Routing algorithm (PDCR) is described for asynchronous NoC design, which outperforms different adaptive routing algorithms in the average delay and saturation throughput for various traffic patterns. Demonstrates the impact of process variation on Networks-on-Chip of different topologies;  Includes an overview of the sy...

  15. Impairments in the Face-Processing Network in Developmental Prosopagnosia and Semantic Dementia.

    Science.gov (United States)

    Mendez, Mario F; Ringman, John M; Shapira, Jill S

    2015-12-01

    Developmental prosopagnosia (DP) and semantic dementia (SD) may be the two most common neurologic disorders of face processing, but their main clinical and pathophysiologic differences have not been established. To identify those features, we compared patients with DP and SD. Five patients with DP, five with right temporal-predominant SD, and ten normal controls underwent cognitive, visual perceptual, and face-processing tasks. Although the patients with SD were more cognitively impaired than those with DP, the two groups did not differ statistically on the visual perceptual tests. On the face-processing tasks, the DP group had difficulty with configural analysis and they reported relying on serial, feature-by-feature analysis or awareness of salient features to recognize faces. By contrast, the SD group had problems with person knowledge and made semantically related errors. The SD group had better face familiarity scores, suggesting a potentially useful clinical test for distinguishing SD from DP. These two disorders of face processing represent clinically distinguishable disturbances along a right hemisphere face-processing network: DP, characterized by early configural agnosia for faces, and SD, characterized primarily by a multimodal person knowledge disorder. We discuss these preliminary findings in the context of the current literature on the face-processing network; recent studies suggest an additional right anterior temporal, unimodal face familiarity-memory deficit consistent with an "associative prosopagnosia."

  16. Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

    Science.gov (United States)

    Bianchini, Monica; Scarselli, Franco

    In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

  17. Magnetic interactions and spin configuration in FeRh and Fe/FeRh systems

    Energy Technology Data Exchange (ETDEWEB)

    Kuncser, V. E-mail: kuncser@alpha2.infim.ro; Keune, W.; Sahoo, B.; Duman, E.; Acet, M.; Radu, F.; Valeanu, M.; Crisan, O.; Filoti, G

    2004-05-01

    The magnetic interactions and the Fe spin structure have been studied in Fe(6 nm)/FeRh systems by magnetometry, magneto-optic Kerr effect and conversion electron Moessbauer spectroscopy. A spin-flop coupling mechanism, with the interfacial spins of the ferromagnetic phase perpendicular to the spins of the antiferromagnetic phase was experimentally proved.

  18. Design of special purpose database for credit cooperation bank business processing network system

    Science.gov (United States)

    Yu, Yongling; Zong, Sisheng; Shi, Jinfa

    2011-12-01

    With the popularization of e-finance in the city, the construction of e-finance is transfering to the vast rural market, and quickly to develop in depth. Developing the business processing network system suitable for the rural credit cooperative Banks can make business processing conveniently, and have a good application prospect. In this paper, We analyse the necessity of adopting special purpose distributed database in Credit Cooperation Band System, give corresponding distributed database system structure , design the specical purpose database and interface technology . The application in Tongbai Rural Credit Cooperatives has shown that system has better performance and higher efficiency.

  19. Characterizing Design Process Interfaces as Organization Networks: Insights for Engineering Systems Management

    DEFF Research Database (Denmark)

    Ruiz, Pedro Parraguez; Eppinger, Steven; Maier, Anja

    2016-01-01

    The engineering design literature has provided guidance on how to identify and analyze design activities and their information dependencies. However, a systematic characterization of process interfaces between engineering design activities is missing, and the impact of structural and compositional...... and interpret the effect of those characteristics on interface problems. As a result, we show how structural and compositional aspects of the organization networks between information-dependent activities provide valuable insights to better manage complex engineering design processes. The proposed approach...... and organization architectures, the systematic identification of key performance metrics associated with interface problems, and improved support for engineering managers by means of a better overview of information flows between activities....

  20. Glial-gonadotrophin hormone (GnRH) neurone interactions in the median eminence and the control of GnRH secretion.

    Science.gov (United States)

    Ojeda, S R; Lomniczi, A; Sandau, U S

    2008-06-01

    A wealth of information now exists showing that glial cells are actively involved in the cell-cell communication process generating and disseminating information within the central nervous system. In the hypothalamus, two types of glial cells, astrocytes and ependymal cells lining the latero-ventral portion of the third ventricle (known as tanycytes), regulate the secretory activity of neuroendocrine neurones. This function, initially described for astrocytes apposing magnocellular neurones, has been more recently characterised for neurones secreting gonadotrophin hormone-releasing hormone (GnRH). The available evidence suggests that glial cells of the median eminence regulate GnRH secretion via two related mechanisms. One involves the production of growth factors acting via receptors with tyrosine kinase activity. The other involves plastic rearrangements of glia-GnRH neurone adhesiveness. GnRH axons reach the median eminence, at least in part, directed by basic fibroblast growth factor. Their secretory activity is facilitated by insulin-like growth factor 1 and members of the epidermal growth factor family. A structural complement to these soluble molecules is provided by at least three cell-cell adhesion systems endowed with signalling capabilities. One of them uses the neuronal cell adhesion molecule (NCAM), another employs the synaptic cell adhesion molecule (SynCAM), and the third one consists of neuronal contactin interacting with glial receptor-like protein tyrosine phosphatase-beta. It is envisioned that, within the median eminence, soluble factors and adhesion molecules work coordinately to control delivery of GnRH to the portal vasculature.

  1. Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves In The Predicting Process

    Science.gov (United States)

    Wanto, Anjar; Zarlis, Muhammad; Sawaluddin; Hartama, Dedy

    2017-12-01

    Backpropagation is a good artificial neural network algorithm used to predict, one of which is to predict the rate of Consumer Price Index (CPI) based on the foodstuff sector. While conjugate gradient fletcher reeves is a suitable optimization method when juxtaposed with backpropagation method, because this method can shorten iteration without reducing the quality of training and testing result. Consumer Price Index (CPI) data that will be predicted to come from the Central Statistics Agency (BPS) Pematangsiantar. The results of this study will be expected to contribute to the government in making policies to improve economic growth. In this study, the data obtained will be processed by conducting training and testing with artificial neural network backpropagation by using parameter learning rate 0,01 and target error minimum that is 0.001-0,09. The training network is built with binary and bipolar sigmoid activation functions. After the results with backpropagation are obtained, it will then be optimized using the conjugate gradient fletcher reeves method by conducting the same training and testing based on 5 predefined network architectures. The result, the method used can increase the speed and accuracy result.

  2. Models of neural networks temporal aspects of coding and information processing in biological systems

    CERN Document Server

    Hemmen, J; Schulten, Klaus

    1994-01-01

    Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

  3. Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks

    Science.gov (United States)

    Cota, Wesley; Ferreira, Silvio C.

    2017-10-01

    Numerical simulation of continuous-time Markovian processes is an essential and widely applied tool in the investigation of epidemic spreading on complex networks. Due to the high heterogeneity of the connectivity structure through which epidemic is transmitted, efficient and accurate implementations of generic epidemic processes are not trivial and deviations from statistically exact prescriptions can lead to uncontrolled biases. Based on the Gillespie algorithm (GA), in which only steps that change the state are considered, we develop numerical recipes and describe their computer implementations for statistically exact and computationally efficient simulations of generic Markovian epidemic processes aiming at highly heterogeneous and large networks. The central point of the recipes investigated here is to include phantom processes, that do not change the states but do count for time increments. We compare the efficiencies for the susceptible-infected-susceptible, contact process and susceptible-infected-recovered models, that are particular cases of a generic model considered here. We numerically confirm that the simulation outcomes of the optimized algorithms are statistically indistinguishable from the original GA and can be several orders of magnitude more efficient.

  4. A convergent model for distributed processing of Big Sensor Data in urban engineering networks

    Science.gov (United States)

    Parygin, D. S.; Finogeev, A. G.; Kamaev, V. A.; Finogeev, A. A.; Gnedkova, E. P.; Tyukov, A. P.

    2017-01-01

    The problems of development and research of a convergent model of the grid, cloud, fog and mobile computing for analytical Big Sensor Data processing are reviewed. The model is meant to create monitoring systems of spatially distributed objects of urban engineering networks and processes. The proposed approach is the convergence model of the distributed data processing organization. The fog computing model is used for the processing and aggregation of sensor data at the network nodes and/or industrial controllers. The program agents are loaded to perform computing tasks for the primary processing and data aggregation. The grid and the cloud computing models are used for integral indicators mining and accumulating. A computing cluster has a three-tier architecture, which includes the main server at the first level, a cluster of SCADA system servers at the second level, a lot of GPU video cards with the support for the Compute Unified Device Architecture at the third level. The mobile computing model is applied to visualize the results of intellectual analysis with the elements of augmented reality and geo-information technologies. The integrated indicators are transferred to the data center for accumulation in a multidimensional storage for the purpose of data mining and knowledge gaining.

  5. Magnetic cellular nonlinear network with spin wave bus for image processing

    Science.gov (United States)

    Khitun, Alexander; Bao, Mingqiang; Wang, Kang L.

    2010-03-01

    We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film-spin wave bus. The magneto-electric cell is an artificial two-phase multiferroic structure comprising piezoelectric and ferromagnetic materials. A bit of information is assigned to the cell's magnetic polarization, which can be controlled by the applied voltage. The information exchange among the cells is via the spin waves propagating in the spin wave bus. Each cell changes its state as a combined effect: magneto-electric coupling and the interaction with the spin waves. The distinct feature of a network with a spin wave bus is the ability to control the inter-cell communication by an external global parameter — magnetic field. The latter makes it possible to realize different image processing functions on the same template without rewiring or reconfiguration. We present the results of numerical simulations illustrating image filtering, erosion, dilation, horizontal and vertical line detection, inversion and edge detection accomplished on one template by the proper choice of the strength and direction of the external magnetic field. We also present numerical assets on the major network parameters such as cell density, power dissipation and functional throughput, and compare them with the parameters projected for other nano-architectures such as CMOL-CrossNet, Quantum-Dot Cellular Automata, and Quantum Dot-Image Processor. Potentially, the utilization of spin wave phenomena at the nanometer scale may provide a route to low-power consumption and functional logic circuits for special task data processing.

  6. The Interrelationship of Estrogen Receptor and GnRH in a Basal Vertebrate, the Sea Lamprey

    Directory of Open Access Journals (Sweden)

    Stacia A Sower

    2011-10-01

    Full Text Available The hypothalamic-pituitary system is considered to be a vertebrate innovation and seminal event that emerged prior to or during the differentiation of the ancestral agnathans. Lampreys are the earliest evolved vertebrates for which there is a demonstrated neuroendocrine system. Lampreys have three hypothalamic GnRHs (lGnRH-I, -II, and –III and two and possibly three pituitary GnRH receptors involved in mediating reproductive processes. Estradiol is considered to be a major reproductive steroid in both male and female lampreys. The purpose of this study was to investigate estrogen receptor (ER expression in the lamprey brain in adult sea lampreys. Expression of ER mRNA was confirmed in the adult lamprey brain using RT-PCR. Using digoxigenin (DIG-labeled probes, ER expression was shown to yield moderate, but distinct reaction products in specific neuronal nuclei of the lamprey brain, including the olfactory lobe, hypothalamus, habenular area, and hindbrain. Expression of ER in the hypothalamic area of the brain provides evidence of potential interaction between estradiol and GnRH(s, and is consistent with previous evidence showing estrogen feedback on GnRH in adult lamprey brain. Earlier studies have reported that there is a close distribution of GAD (GABA and lamprey GnRH in the preoptic region in adult lampreys. The establishment of a direct estradiol-kisspeptin-GABA-GnRH interaction in lamprey has yet to be determined and will require future functional and co-localization studies. The phylogenetic position of lampreys as a basal vertebrate allows lampreys to be a basis for understanding the molecular evolution of the neuroendocrine system that arose in the vertebrates.

  7. Group scheduling based on control-packet batch processing in optical burst switched networks

    Science.gov (United States)

    Yuan, Chi; Li, Zhengbin; He, Yongqi; Xu, Anshi

    2007-11-01

    Optical burst switching (OBS) is proposed as a high-speed, flexible, and transparent technology. It is thought to be the best way to adapt the bursty IP traffic over optical wavelength division multiplexing (WDM) networks. OBS technology facilitates the efficient integration of both IP and WDM. It provides statistical multiplexing gains and avoids long end to end setup time of traditional virtual circuit configuration. However, there are still a lot of challenges, one of which is burst contention. Owing to the fact that random access memory like buffering is not available in the optical domain at present, there exists a real possibility that bursts may contend with one another at a switching node. Many contention resolutions are proposed. The major contention resolutions in literature are wavelength conversion, fiber delay lines, and deflecting routing. In this paper, a new data burst scheduling scheme, called group scheduling based on control-packet batch processing (GSCBP) was proposed to reduce burst contention. Like transmission control protocol, GSCBP has a batch processing window. Control packets which located in the batch processing window are batch processed. A heuristic scheduling algorithm arranges the relevant bursts' route based on the processing result and the network resource. A new node architecture supporting group scheduling was presented. The GSCBP algorithm is combined with wavelength converter and/or fiber delay lines which is shared by some data channels. Meanwhile, an extended open shortest path first (E-OSPF) routing strategy was proposed for OBS. Both GSCBP and E-OSPF are introduced into 14-node national science foundation network by means of simulations. The ETE delay, burst blocking probability, as well as burst dropping probability were attained. Results show that the GSBCP lead to the higher-priority traffic drop rate decrease one order of magnitude, if drop rate and ETE delay of lower priority traffic is sacrificed.

  8. Anatomical alterations of the visual motion processing network in migraine with and without aura.

    Directory of Open Access Journals (Sweden)

    Cristina Granziera

    2006-10-01

    Full Text Available Patients suffering from migraine with aura (MWA and migraine without aura (MWoA show abnormalities in visual motion perception during and between attacks. Whether this represents the consequences of structural changes in motion-processing networks in migraineurs is unknown. Moreover, the diagnosis of migraine relies on patient's history, and finding differences in the brain of migraineurs might help to contribute to basic research aimed at better understanding the pathophysiology of migraine.To investigate a common potential anatomical basis for these disturbances, we used high-resolution cortical thickness measurement and diffusion tensor imaging (DTI to examine the motion-processing network in 24 migraine patients (12 with MWA and 12 MWoA and 15 age-matched healthy controls (HCs. We found increased cortical thickness of motion-processing visual areas MT+ and V3A in migraineurs compared to HCs. Cortical thickness increases were accompanied by abnormalities of the subjacent white matter. In addition, DTI revealed that migraineurs have alterations in superior colliculus and the lateral geniculate nucleus, which are also involved in visual processing.A structural abnormality in the network of motion-processing areas could account for, or be the result of, the cortical hyperexcitability observed in migraineurs. The finding in patients with both MWA and MWoA of thickness abnormalities in area V3A, previously described as a source in spreading changes involved in visual aura, raises the question as to whether a "silent" cortical spreading depression develops as well in MWoA. In addition, these experimental data may provide clinicians and researchers with a noninvasively acquirable migraine biomarker.

  9. The impact of nuclear mass models on r-process nucleosynthesis network calculations

    Science.gov (United States)

    Vaughan, Kelly

    2002-10-01

    An insight into understanding various nucleosynthesis processes is via modelling of the process with network calculations. My project focus is r-process network calculations where the r-process is nucleosynthesis via rapid neutron capture thought to take place in high entropy supernova bubbles. One of the main uncertainties of the simulations is the Nuclear Physics input. My project investigates the role that nuclear masses play in the resulting abundances. The code tecode, involves rapid (n,γ) capture reactions in competition with photodisintegration and β decay onto seed nuclei. In order to fully analyze the effects of nuclear mass models on the relative isotopic abundances, calculations were done from the network code, keeping the initial environmental parameters constant throughout. The supernova model investigated by Qian et al (1996) in which two r-processes, of high and low frequency with seed nucleus ^90Se and of fixed luminosity (fracL_ν_e(0)r_7(0)^2 ˜= 8.77), contribute to the nucleosynthesis of the heavier elements. These two r-processes, however, do not contribute equally to the total abundance observed. The total isotopic abundance produced from both events was therefore calculated using equation refabund. Y(H+L) = fracY(H)+fY(L)f+1 nuclear mass models. The mass models tested are the HFBCS model (Hartree-Fock BCS) derived from first principles, the ETFSI-Q model (Extended Thomas-Fermi with Strutinsky Integral including shell Quenching) known for its particular successes in the replication of Solar System abundances, and the P-Scheme Model tePscheme. The aims of this research is to test the applicability of the P-Scheme in relation to the other mass models to the r-process network calculations. 02 Pscheme Aprahamian,A., Gadala-Maria,A. & Cuka,N. 1996, Revista Mexicana de Fisica,42,1 code Surman,R. & Engel,J. 1998, Phys.Rev. C,54,4 thebibliography

  10. Realization of Associative Memory in an Enzymatic Process: Toward Biomolecular Networks with Learning and Unlearning Functionalities.

    Science.gov (United States)

    Bocharova, Vera; MacVittie, Kevin; Chinnapareddy, Soujanya; Halámek, Jan; Privman, Vladimir; Katz, Evgeny

    2012-05-17

    We report a realization of an associative memory signal/information processing system based on simple enzyme-catalyzed biochemical reactions. Optically detected chemical output is always obtained in response to the triggering input, but the system can also "learn" by association, to later respond to the second input if it is initially applied in combination with the triggering input as the "training" step. This second chemical input is not self-reinforcing in the present system, which therefore can later "unlearn" to react to the second input if it is applied several times on its own. Such processing steps realized with (bio)chemical kinetics promise applications of bioinspired/memory-involving components in "networked" (concatenated) biomolecular processes for multisignal sensing and complex information processing.

  11. [GSH fermentation process modeling using entropy-criterion based RBF neural network model].

    Science.gov (United States)

    Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

    2008-05-01

    The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

  12. Comparisons process-to-bay level peer-to-peer network delay in IEC 61850 substation communication systems

    Directory of Open Access Journals (Sweden)

    Nasser Hasan Ali

    2014-12-01

    Full Text Available This paper presents the application of IEC 61850 protocol in electrical power engineering industry for data communication systems between substations. This IEC 61850 protocol presents new challenges for real-time communication performance between Intelligent Electronic Devices (IEDs within substation because of the Generic Object Oriented Substation Event (GOOSE messages. The analyses of substation Ethernet and WLAN (wireless LAN communication delay, its impact factors, various methods and different network topologies which can improve the real-time performance are discussed. For basic analysis of data flow within a substation, the Optimized Network Engineering Tool (OPNET software is used. The process-to-bay level network simulation model is performed by using the OPNET software. The Ethernet delay and WLAN peer-to-peer performance of the process-to-bay level network simulation results are analyzed which is based on AP (access point, switched, shared Ethernet network or peer-to-peer network.

  13. Experimental and theoretical studies of the reaction of Rh+ with CS2 in the gas phase: thermochemistry of RhS+ and RhCS+.

    Science.gov (United States)

    Armentrout, P B; Kretzschmar, Ilona

    2009-10-15

    The gas-phase reactivity of the atomic transition-metal cation rhodium, Rh(+), with CS(2) is investigated using guided-ion-beam mass spectrometry (GIBMS). Endothermic reactions forming RhS(+) and RhCS(+) are observed. Analysis of the kinetic energy dependence of the cross sections for formation of these two products yields the 0 K bond energies of D(0)(Rh(+)-S) = 2.61 +/- 0.12 eV and D(0)(Rh(+)-CS) = 2.66 +/- 0.19 eV. These compare favorably with quantum chemical calculations at the CCSD(T)/Def2TZVPP//B3LYP/Def2TZVPP and CCSD(T)/Def2TZVPP levels of theory, where the former is also used to explore the complete potential energy surface of the reaction. It is found that the reaction initially involves insertion of the rhodium cation into one of the CS bonds of CS(2), followed by metal ligand cleavages to form the two product channels. The formation of ground state RhS(+) products is spin-forbidden, whereas RhCS(+) formation is spin-allowed. Crossing points between the triplet and quintet surfaces are located in the region of the SRh(+)(CS) intermediate, which suggests that coupling between the surfaces is reasonably efficient, consistent with experiment.

  14. [Effects of ginsenoside Rh2(GS-Rh2) on cell cycle of Eca-109 esophageal carcinoma cell line].

    Science.gov (United States)

    Li, Li; Qi, Feng-ying; Liu, Jun-ru; Zuo, Lian-fu

    2005-10-01

    To investigate the effects of ginsenoside Rh2 (GS-Rh2) on growth inhibition and cell cycle of Eca-109 esophageal carcinoma cell line in culture. The effects of GS-Rh2 on cell growth inhibition was detected by MTT assay. Cell cycle was analyzed by flow cytometry (FCM). Cell morphology was observed by a light microscope after HE staining. The protein expression of cell cycle components (cyclinE, CDK2, p21WAF1) were examined by immunocytochemistry and Western blot. The mRNA expression were examined by semiquantitative RT-PCR. GS-Rh2 inhibited the proliferation of Eca-109 cells in dose and time-dependent manners. The inhibition rate was about 50% after 1-day treatment with 20 microg x mL(-1) GS-Rh2 x 20 microg x mL(-1) GS-Rh2 induced the mature differentiation and morphological reversion. With increasing dose of GS-Rh2 treatment, the cell number of G0/G1 phase was increased, whereas it decreased at S and G2/M phase. There was significant difference between 10, 20 microg x mL(-1) GS-Rh2 groups and the corresponding group without GS-Rh2 treatement. After treating cells by 20 microg x mL(-1) GS-Rh2 for 1, 2, 3 days individually, the protein and mRNA expression of both cyclinE and CDK2 reduced, while the expression of p21WAF1 enhanced gradually. GS-Rh2 could arrest Eca-109 cells at G0/G1 phase and induce cell differentiation tending to normal. Furthermore, GS-Rh2 had an effect on expression of cell cycle components (cyclinE, CDK2 and p21WAF1) to inhibit Eca-109 cell proliferation.

  15. Thermodynamic calculations for biochemical transport and reaction processes in metabolic networks.

    Science.gov (United States)

    Jol, Stefan J; Kümmel, Anne; Hatzimanikatis, Vassily; Beard, Daniel A; Heinemann, Matthias

    2010-11-17

    Thermodynamic analysis of metabolic networks has recently generated increasing interest for its ability to add constraints on metabolic network operation, and to combine metabolic fluxes and metabolite measurements in a mechanistic manner. Concepts for the calculation of the change in Gibbs energy of biochemical reactions have long been established. However, a concept for incorporation of cross-membrane transport in these calculations is still missing, although the theory for calculating thermodynamic properties of transport processes is long known. Here, we have developed two equivalent equations to calculate the change in Gibbs energy of combined transport and reaction processes based on two different ways of treating biochemical thermodynamics. We illustrate the need for these equations by showing that in some cases there is a significant difference between the proposed correct calculation and using an approximative method. With the developed equations, thermodynamic analysis of metabolic networks spanning over multiple physical compartments can now be correctly described. Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  16. Physics of the Mind:. Opinion Dynamics and Decision Making Processes Based on a Binary Network Model

    Science.gov (United States)

    Kusmartsev, F. V.; Kürten, Karl E.

    2009-12-01

    We propose a new theory of the human mind. The formation of human mind is considered as a collective process of the mutual interaction of people via exchange of opinions and formation of collective decisions. We investigate the associated dynamical processes of the decision making when people are put in different conditions including risk situations in natural catastrophes when the decision must be made very fast or at national elections. We also investigate conditions at which the fast formation of opinion is arising as a result of open discussions or public vote. Under a risk condition the system is very close to chaos and therefore the opinion formation is related to the order disorder transition. We study dramatic changes which may happen with societies which in physical terms may be considered as phase transitions from ordered to chaotic behavior. Our results are applicable to changes which are arising in various social networks as well as in opinion formation arising as a result of open discussions. One focus of this study is the determination of critical parameters, which influence a formation of stable mind, public opinion and where the society is placed "at the edge of chaos". We show that social networks have both, the necessary stability and the potential for evolutionary improvements or self-destruction. We also show that the time needed for a discussion to take a proper decision depends crucially on the nature of the interactions between the entities as well as on the topology of the social networks.

  17. A Rotational Motion Perception Neural Network Based on Asymmetric Spatiotemporal Visual Information Processing.

    Science.gov (United States)

    Hu, Bin; Yue, Shigang; Zhang, Zhuhong

    All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion

  18. Multilevel Approximations of Markovian Jump Processes with Applications in Communication Networks

    KAUST Repository

    Vilanova, Pedro

    2015-05-04

    This thesis focuses on the development and analysis of efficient simulation and inference techniques for Markovian pure jump processes with a view towards applications in dense communication networks. These techniques are especially relevant for modeling networks of smart devices —tiny, abundant microprocessors with integrated sensors and wireless communication abilities— that form highly complex and diverse communication networks. During 2010, the number of devices connected to the Internet exceeded the number of people on Earth: over 12.5 billion devices. By 2015, Cisco’s Internet Business Solutions Group predicts that this number will exceed 25 billion. The first part of this work proposes novel numerical methods to estimate, in an efficient and accurate way, observables from realizations of Markovian jump processes. In particular, hybrid Monte Carlo type methods are developed that combine the exact and approximate simulation algorithms to exploit their respective advantages. These methods are tailored to keep a global computational error below a prescribed global error tolerance and within a given statistical confidence level. Indeed, the computational work of these methods is similar to the one of an exact method, but with a smaller constant. Finally, the methods are extended to systems with a disparity of time scales. The second part develops novel inference methods to estimate the parameters of Markovian pure jump process. First, an indirect inference approach is presented, which is based on upscaled representations and does not require sampling. This method is simpler than dealing directly with the likelihood of the process, which, in general, cannot be expressed in closed form and whose maximization requires computationally intensive sampling techniques. Second, a forward-reverse Monte Carlo Expectation-Maximization algorithm is provided to approximate a local maximum or saddle point of the likelihood function of the parameters given a set of

  19. Age differences in default and reward networks during processing of personally relevant information.

    Science.gov (United States)

    Grady, Cheryl L; Grigg, Omer; Ng, Charisa

    2012-06-01

    We recently found activity in default mode and reward-related regions during self-relevant tasks in young adults. Here we examine the effect of aging on engagement of the default network (DN) and reward network (RN) during these tasks. Previous studies have shown reduced engagement of the DN and reward areas in older adults, but the influence of age on these circuits during self-relevant tasks has not been examined. The tasks involved judging personality traits about one's self or a well known other person. There were no age differences in reaction time on the tasks but older adults had more positive Self and Other judgments, whereas younger adults had more negative judgments. Both groups had increased DN and RN activity during the self-relevant tasks, relative to non-self tasks, but this increase was reduced in older compared to young adults. Functional connectivity of both networks during the tasks was weaker in the older relative to younger adults. Intrinsic functional connectivity, measured at rest, also was weaker in the older adults in the DN, but not in the RN. These results suggest that, in younger adults, the processing of personally relevant information involves robust activation of and functional connectivity within these two networks, in line with current models that emphasize strong links between the self and reward. The finding that older adults had more positive judgments, but weaker engagement and less consistent functional connectivity in these networks, suggests potential brain mechanisms for the "positivity bias" with aging. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Using artificial neural networks to model extrusion processes for the manufacturing of polymeric micro-tubes

    Science.gov (United States)

    Mekras, N.; Artemakis, I.

    2012-09-01

    In this paper a methodology and an application example are presented aiming to show how Artificial Neural Networks (ANNs) can be used to model manufacturing processes when mathematical models are missing or are not applicable e.g. due to the micro- & nano-scaling, due to non-conventional processes, etc. Besides the ANNs methodology, the results of a Software System developed will be presented, which was used to create ANNs models for micro & nano manufacturing processes. More specifically results of a specific application example will be presented, concerning the modeling of extrusion processes for polymeric micro-tubes. ANNs models are capable for modeling manufacturing processes as far as adequate experimental and/or historical data of processes' inputs & outputs are available for their training. The POLYTUBES ANNs models have been trained and tested with experimental data records of process' inputs and outputs concerning a micro-extrusion process of polymeric micro-tubes for several materials such as: COC, PC, PET, PETG, PP and PVDF. The main ANN model of the extrusion application example has 3 inputs and 9 outputs. The inputs are: tube's inner & outer diameters, and the material density. The model outputs are 9 process parameters, which correspond to the specific inputs e.g. process temperature, die inner & outer diameters, extrusion pressure, draw speed etc. The training of the ANN model was completed, when the errors for the model's outputs, which expressed the difference between the training target values and the ANNs outputs, were minimized to acceptable levels. After the training, the micro-extrusion ANN is capable to simulate the process and can be used to calculate model's outputs, which are the process parameters for any new set of inputs. By this way a satisfactory functional approximation of the whole process is achieved. This research work has been supported by the EU FP7 NMP project POLYTUBES.

  1. Processing of a geodetic network determined in ETRS-89 with application of different cofactors

    Directory of Open Access Journals (Sweden)

    Slavomír Labant

    2012-12-01

    Full Text Available At present, manufacturers characterize the accuracy of vectors measured by the static method of GNSS technology usingrelationship 5 mm + 1⋅ D ppm . The advantage of the GNSS system over other terrestrial technologies is that it is not affectedby uncertainties in the ground layers of the atmosphere. The paper presents experimental measurement of the 3D geodetic network usingthe technology of global navigation satellite systems, processing and analysis of measurements taken at the Čierny Váh pumping hydropowerstation. Observations were carried out in July 2008. The aim of the paper is to assess parameters used in the model to estimateparameters of the first and second order of the network structures.

  2. Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks

    Directory of Open Access Journals (Sweden)

    Dede Sutarya

    2014-01-01

    Full Text Available Nonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. An identification scheme of nonlinear systems for sintering furnace temperature in nuclear fuel fabrication using neural network autoregressive with exogenous inputs (NNARX model investigated in this paper. The main contribution of this paper is to identify the appropriate model and structure to be applied in control temperature in the sintering process in nuclear fuel fabrication, that is, a nonlinear dynamical system. Satisfactory agreement between identified and experimental data is found with normalized sum square error 1.9e-03 for heating step and 6.3859e-08 for soaking step. That result shows the model successfully predict the evolution of the temperature in the furnace.

  3. Sustainability performance measurement with Analytic Network Process and balanced scorecard: Cuban practical case

    Directory of Open Access Journals (Sweden)

    Frank Medel-González

    2016-01-01

    Full Text Available Abstract The recent years has arisen a global discussion in relation with how to incorporate sustainability at a business level. Corporate sustainability is a multidimensional concept, is the translation of Sustainable Development concept at a business level. Sustainability in organizations must be managed and assessed by decision makers, for that reason a multi-criteria sustainability performance measurement is necessary. The aim of this paper is combine different important tools that helps to make operative corporate sustainability and sustainability performance measurement in Cuban organizations. The combination of Sustainability Balanced Scorecard, multi-criteria decisions models like: Analytic Network Process, and Matrix of Sustainable Strategic Alignment, can help managers in sustainability performance measurement and assessment. The result of this paper focus in a Corporate Sustainability Measurement Network design as a first approach for further sustainability performance measurement systems development emphasizing in multi-criteria analysis.

  4. The relationship between human behavior and the process of epidemic spreading in a real social network

    Science.gov (United States)

    Grabowski, A.; Rosińska, M.

    2012-07-01

    On the basis of experimental data on interactions between humans we have investigated the process of epidemic spreading in a social network. We found that the distribution of the number of contacts maintained in one day is exponential. Data on frequency and duration of interpersonal interactions are presented. They allow us to simulate the spread of droplet-/-air-borne infections and to investigate the influence of human dynamics on the epidemic spread. Specifically, we investigated the influence of the distribution of frequency and duration of those contacts on magnitude, epidemic threshold and peak timing of epidemics propagating in respective networks. It turns out that a large increase in the magnitude of an epidemic and a decrease in epidemic threshold are visible if and only if both are taken into account. We have found that correlation between contact frequency and duration strongly influences the effectiveness of control measures like mass immunization campaigns.

  5. A robust evaluation of sustainability initiatives with analytic network process (ANP

    Directory of Open Access Journals (Sweden)

    Lanndon Ocampo

    2015-07-01

    Full Text Available This paper presents a methodology on evaluating sustainable manufacturing initiatives using analytic network process (ANP as its base.The evaluation method is anchored on the comprehensive sustainable manufacturing framework proposed recently in literature. A numerical example that involves an evaluation of five sustainable manufacturing initiatives is shown in this work. Results show that sustainable manufacturing implies enhancing customer and community well-being by means of addressing environmental issues related to pollution due to toxic substances, greenhouse gas emissions and air emissions. To test the robustness of the results, two approaches are introduced in this work: (1 using Monte Carlo simulation and (2 introducing structural changes on the evaluation model. It suggests that the results are robust to random variations and to marginal changes of the network structure. The contribution of this work lies on presenting a sustainable manufacturing evaluation approach that addresses complexity and robustness in decision-making. 

  6. Peers and the Emergence of Alcohol Use: Influence and Selection Processes in Adolescent Friendship Networks.

    Science.gov (United States)

    Osgood, D Wayne; Ragan, Daniel T; Wallace, Lacey; Gest, Scott D; Feinberg, Mark E; Moody, James

    2013-09-01

    This study addresses not only influence and selection of friends as sources of similarity in alcohol use, but also peer processes leading drinkers to be chosen as friends more often than non-drinkers, which increases the number of adolescents subject to their influence. Analyses apply a stochastic actor-based model to friendship networks assessed five times from 6th through 9th grades for 50 grade cohort networks in Iowa and Pennsylvania, which include 13,214 individuals. Results show definite influence and selection for similarity in alcohol use, as well as reciprocal influences between drinking and frequently being chosen as a friend. These findings suggest that adolescents view alcohol use as an attractive, high status activity and that friendships expose adolescents to opportunities for drinking.

  7. A dedicated network for social interaction processing in the primate brain.

    Science.gov (United States)

    Sliwa, J; Freiwald, W A

    2017-05-19

    Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities. Copyright © 2017, American Association for the Advancement of Science.

  8. Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

    DEFF Research Database (Denmark)

    Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

    2015-01-01

    also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time......Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

  9. Altered organization of face-processing networks in temporal lobe epilepsy.

    Science.gov (United States)

    Riley, Jeffrey D; Fling, Brett W; Cramer, Steven C; Lin, Jack J

    2015-05-01

    Deficits in social cognition are common and significant in people with temporal lobe epilepsy (TLE), but the functional and structural underpinnings remain unclear. The present study investigated how the side of seizure focus impacts face-processing networks in temporal lobe epilepsy. We used functional magnetic resonance imaging (fMRI) of a face-processing paradigm to identify face-responsive regions in 24 individuals with unilateral temporal lobe epilepsy (left = 15; right = 9) and 19 healthy controls. fMRI signals of face-responsive regions ipsilateral and contralateral to the side of seizure onset were delineated in TLE and compared to the healthy controls with right and left sides combined. Diffusion tensor images were acquired to investigate structural connectivity between face regions that differed in fMRI signals between the two groups. In TLE, activation of the cortical face-processing networks varied according to side of seizure onset. In temporal lobe epilepsy, the laterality of amygdala activation was shifted to the side contralateral to the seizure focus, whereas controls showed no significant asymmetry. Furthermore, compared to controls, patients with TLE showed decreased activation of the occipital face-responsive region on the ipsilateral side and an increased activity of the anterior temporal lobe in the side contralateral to the seizure focus. Probabilistic tractography revealed that the occipital face area and anterior temporal lobe are connected via the inferior longitudinal fasciculus, which in individuals with TLE showed reduced integrity. Taken together, these findings suggest that brain function and white matter integrity of networks subserving face processing are impaired on the side of seizure onset, accompanied by altered responses on the side contralateral to the seizure. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

  10. The effect of mild-to-moderate hearing loss on auditory and emotion processing networks

    Directory of Open Access Journals (Sweden)

    Fatima T Husain

    2014-02-01

    Full Text Available We investigated the impact of hearing loss on emotional processing using task- and rest-based functional magnetic resonance imaging. Two age-matched groups of middle-aged participants were recruited: one with bilateral high-frequency hearing loss (HL and a control group with normal hearing (NH. During the task-based portion of the experiment, participants were instructed to rate affective stimuli from the International Affective Digital Sounds database as pleasant, unpleasant, or neutral. In the resting state experiment, participants were told to fixate on a '+' sign on a screen for five minutes. The results of both the task-based and resting state studies suggest that NH and HL patients differ in their emotional response. Specifically, in the task-based study, we found slower response to affective but not neutral sounds by the HL group compared to the NH group. This was reflected in the brain activation patterns, with the NH group employing the expected limbic and auditory regions including the left amygdala, left parahippocampus, right middle temporal gyrus and left superior temporal gyrus to a greater extent in processing affective stimuli when compared to the HL group. In the resting state study, we observed no significant differences in connectivity of the auditory network between the groups. In the dorsal attention network, HL patients exhibited decreased connectivity between seed regions and left insula and left postcentral gyrus compared to controls. The default mode network was also altered, showing increased connectivity between seeds and left middle frontal gyrus in the HL group. Further targeted analysis revealed increased intrinsic connectivity between the right middle temporal gyrus and the right precentral gyrus. The results from both studies suggest neuronal reorganization as a consequence of hearing loss, most notably in networks responding to emotional sounds.

  11. Glucocorticoid Administration Improves Aberrant Fear-Processing Networks in Spider Phobia.

    Science.gov (United States)

    Nakataki, Masahito; Soravia, Leila M; Schwab, Simon; Horn, Helge; Dierks, Thomas; Strik, Werner; Wiest, Roland; Heinrichs, Markus; de Quervain, Dominique J-F; Federspiel, Andrea; Morishima, Yosuke

    2017-01-01

    Glucocorticoids reduce phobic fear in patients with anxiety disorders. Previous studies have shown that fear-related activation of the amygdala can be mediated through the visual cortical pathway, which includes the fusiform gyrus, or through other pathways. However, it is not clear which of the pathways that activate the amygdala is responsible for the pathophysiology of a specific phobia and how glucocorticoid treatment alleviates fear processing in these neural networks. We recorded the brain activity with functional magnetic resonance imaging in patients with spider phobia, who received either 20 mg of cortisol or a placebo while viewing pictures of spiders. We also tested healthy participants who did not receive any medication during the same task. We performed dynamic causal modelling (DCM), a connectivity analysis, to examine the effects of cortisol on the networks involved in processing fear and to examine if there was an association between these networks and the symptoms of the phobia. Cortisol administration suppressed the phobic stimuli-related amygdala activity to levels comparable to the healthy participants and reduced subjective phobic fear. The DCM analysis revealed that cortisol administration suppressed the aberrant inputs into the amygdala that did not originate from the visual cortical pathway, but rather from a fast subcortical pathway mediated by the pulvinar nucleus, and suppressed the interactions between the amygdala and fusiform gyrus. This network changes were distinguishable from healthy participants and considered the residual changes under cortisol administration. We also found that the strengths of the aberrant inputs into the amygdala were positively correlated with the severity of spider phobia. This study demonstrates that patients with spider phobia show an aberrant functional connectivity of the amygdala when they are exposed to phobia-related stimuli and that cortisol administration can alleviate this fear-specific neural

  12. A Network Analysis of Online Audience Behaviour: Towards a Better Comprehension of the Agenda Setting Process

    Directory of Open Access Journals (Sweden)

    Sílvia Majó-Vázquez

    2015-06-01

    Full Text Available

    By constructing the network of media audience, this study sheds light on the predominant modes of exposure to online political information in Spain. Novelty data from a panel of thirty thousand individuals is used for the research. The preliminary results bring evidences for reviewing the line of reasoning that advocates for the prevailing fragmentation of the public sphere. More notably, the results contribute to proving  that a substantial level of audience concentration still remains in the web. The highest levels of audience overlapping are found in those media outlets that are driving the media agenda in the offline sphere. Therefore the study proffers evidence that the structure of the online public sphere might guarantee the necessary shared informational experiences for a deliberative democracy.

    The implications of the current networked audience behaviour for the study of the agenda setting process are discussed along with the chances for a shared public agenda in  Spanish society. Observational methods and content analysis have been used in the study of the agenda setting process so far. However, the current communication environment characterized by unlimited, decentralized and abundant sources of political information prompts the application of new analytical approaches. Networks are at the heart of online communication and network science allows for analyzing its structure. It provides the affordances to map and study audience aggregated behaviour when searching for political information. In doing in so, it also unveils the mechanisms that might still guarantee a public agenda in the digital age.

  13. The Earthscope USArray Array Network Facility (ANF): Evolution of Data Acquisition, Processing, and Storage Systems

    Science.gov (United States)

    Davis, G. A.; Battistuz, B.; Foley, S.; Vernon, F. L.; Eakins, J. A.

    2009-12-01

    Since April 2004 the Earthscope USArray Transportable Array (TA) network has grown to over 400 broadband seismic stations that stream multi-channel data in near real-time to the Array Network Facility in San Diego. In total, over 1.7 terabytes per year of 24-bit, 40 samples-per-second seismic and state of health data is recorded from the stations. The ANF provides analysts access to real-time and archived data, as well as state-of-health data, metadata, and interactive tools for station engineers and the public via a website. Additional processing and recovery of missing data from on-site recorders (balers) at the stations is performed before the final data is transmitted to the IRIS Data Management Center (DMC). Assembly of the final data set requires additional storage and processing capabilities to combine the real-time data with baler data. The infrastructure supporting these diverse computational and storage needs currently consists of twelve virtualized Sun Solaris Zones executing on nine physical server systems. The servers are protected against failure by redundant power, storage, and networking connections. Storage needs are provided by a hybrid iSCSI and Fiber Channel Storage Area Network (SAN) with access to over 40 terabytes of RAID 5 and 6 storage. Processing tasks are assigned to systems based on parallelization and floating-point calculation needs. On-site buffering at the data-loggers provide protection in case of short-term network or hardware problems, while backup acquisition systems at the San Diego Supercomputer Center and the DMC protect against catastrophic failure of the primary site. Configuration management and monitoring of these systems is accomplished with open-source (Cfengine, Nagios, Solaris Community Software) and commercial tools (Intermapper). In the evolution from a single server to multiple virtualized server instances, Sun Cluster software was evaluated and found to be unstable in our environment. Shared filesystem

  14. Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Goeb, S.; Oliveros, E.; Bossmann, S.H.; Braun, A.M. [Lehrstuhl fuer Umweltmesstechnik, Engler-Bunte-Institut, Universitaet Karlsruhe, Karlsruhe (Germany); Guardani, R.; Nascimento, C.A.O. [Process Control and Simulation Laboratory, Chemical Engineering Department, University of Sao Paulo, Sao Paulo (Brazil)

    1999-07-01

    We have investigated the kinetics of the degradation of 2,4-dimethyl aniline (2,4-xylidine), chosen as a model pollutant, by the photochemically enhanced Fenton reaction. This process, which may be efficiently applied to the treatment of industrial waste waters, involves a series of complex reactions leading eventually to the mineralization of the organic pollutant. A model based on artificial neural networks has been developed for fitting the experimental data obtained in a laboratory batch reactor. The model can describe the evolution of the pollutant concentration during irradiation time under various conditions. It has been used for simulating the behaviour of the reaction system in sensitivity studies aimed at optimizing the amounts of reactants employed in the process - an iron(II) salt and hydrogen peroxide. The results show that the process is much more sensitive to the iron(II) salt concentration than to the hydrogen peroxide concentration, a favorable condition in terms of economic feasibility. (author)

  15. Situating social influence processes: dynamic, multidirectional flows of influence within social networks.

    Science.gov (United States)

    Mason, Winter A; Conrey, Frederica R; Smith, Eliot R

    2007-08-01

    Social psychologists have studied the psychological processes involved in persuasion, conformity, and other forms of social influence, but they have rarely modeled the ways influence processes play out when multiple sources and multiple targets of influence interact over time. However, workers in other fields from sociology and economics to cognitive science and physics have recognized the importance of social influence and have developed models of influence flow in populations and groups-generally without relying on detailed social psychological findings. This article reviews models of social influence from a number of fields, categorizing them using four conceptual dimensions to delineate the universe of possible models. The goal is to encourage interdisciplinary collaborations to build models that incorporate the detailed, microlevel understanding of influence processes derived from focused laboratory studies but contextualized in ways that recognize how multidirectional, dynamic influences are situated in people's social networks and relationships.

  16. Mastering the political Process of Building Innovation Networks - A Case from the Danish Construction Industry

    DEFF Research Database (Denmark)

    Stissing Jensen, Jens; Koch, Christian; Thomassen, Mikkel

    2008-01-01

    Drawing on network of innovation and organizational politics perspectives this paper analyzes the role of an innovation broker organization in developing and supporting an inter-organizational innovation process in the Danish construction industry. The aim is to implement an ICT-based product...... synchronization. These minimal structures were both conceptual and processual. In the development phase these structures facilitated a processes of experimentation in which the utilization of the configurator were utilized to organize the development of several aspects and activities such as branding, product...... configuration tool to support the production, sale, and installation of balconies. It is suggested that the innovation broker was successful in stabilizing the innovation process by supplying minimal structures which provided a template which facilitated a combination of individual flexibility and overall...

  17. Co-Rh modified natural zeolites as new catalytic materials to oxidize propane and naphthalene from emission sources

    Directory of Open Access Journals (Sweden)

    Leguizamon Aparicio María Silvia

    2016-01-01

    Full Text Available Natural zeolites as a raw material to prepare catalytic precursors for the oxidation reaction of linear and poly-aromatic hydrocarbons are reported in this work. The process consisted in the formation of mono- and bi-metallic species containing Co and Co-Rh on natural zeolite tuffs. The materials are analyzed by different physicochemical techniques and used as catalysts for propane and naphthalene oxidation in emissions sources. Comparatively, Rh-zeolites are the most active catalysts for propane conversion. In this case, the formation of mixed oxides seems to be conditioned by surface properties. It could also be suggested that the Rh incorporation on a non-active phase in bimetallic catalysts impacts the effectiveness of the system. In addition, the NO presence increases the activity of bimetallic materials. Rh-Co zeolite systems markedly influence the naphthalene combustion temperature. Whereas in the absence of a catalyst a conversion rate of 50% and 100% is reached at 430 °C and 485 °C, respectively. It is interesting to observe that for RhCoCli-Mor and RhCoCli catalyst the 100% conversion is reached at 250 °C.

  18. Application of Humidity-Controlled Dynamic Mechanical Analysis (DMA-RH to Moisture-Sensitive Edible Casein Films for Use in Food Packaging

    Directory of Open Access Journals (Sweden)

    Laetitia M. Bonnaillie

    2015-01-01

    Full Text Available Protein-based and other hydrophilic thin films are promising materials for the manufacture of edible food packaging and other food and non-food applications. Calcium caseinate (CaCas films are highly hygroscopic and physical characterization under broad environmental conditions is critical to application development and film optimization. A new technology, humidity-controlled dynamic mechanical analysis (DMA-RH was explored to characterize CaCas/glycerol films (3:1 ratio during isohume temperature (T ramps and steps, and isothermal RH ramps and steps, to determine their mechanical and moisture-sorption properties during extensive T and RH variations. When RH and/or T increased, CaCas/Gly films became strongly plasticized and underwent several primary and secondary humidity-dependent transition temperatures (or transition humidities; the CaCas/Gly network hypothetically rearranged itself to adapt to the increased water-content and heat-induced molecular mobility. Between 5–40 °C and 20%–61% RH, moisture-sorption was rapid and proportional to humidity between transition points and accelerated greatly during transitions. CaCas/Gly films seemed unsuitable for storage or utilization in warm/humid conditions as they lost their mechanical integrity around Tm ~ 40 °C at 50% RH and Tm decreased greatly with increased RH. However, below Tm, both moisture- and heat-induced structural changes in the films were fully reversible and casein films may withstand a variety of moderate abuse conditions.

  19. Using artificial neural networks to model aluminium based sheet forming processes and tools details

    Science.gov (United States)

    Mekras, N.

    2017-09-01

    In this paper, a methodology and a software system will be presented concerning the use of Artificial Neural Networks (ANNs) for modeling aluminium based sheet forming processes. ANNs models’ creation is based on the training of the ANNs using experimental, trial and historical data records of processes’ inputs and outputs. ANNs models are useful in cases that processes’ mathematical models are not accurate enough, are not well defined or are missing e.g. in cases of complex product shapes, new material alloys, new process requirements, micro-scale products, etc. Usually, after the design and modeling of the forming tools (die, punch, etc.) and before mass production, a set of trials takes place at the shop floor for finalizing processes and tools details concerning e.g. tools’ minimum radii, die/punch clearance, press speed, process temperature, etc. and in relation with the material type, the sheet thickness and the quality achieved from the trials. Using data from the shop floor trials and forming theory data, ANNs models can be trained and created, and can be used to estimate processes and tools final details, hence supporting efficient set-up of processes and tools before mass production starts. The proposed ANNs methodology and the respective software system are implemented within the EU H2020 project LoCoMaTech for the aluminium-based sheet forming process HFQ (solution Heat treatment, cold die Forming and Quenching).

  20. Prevalence of Rh Phenotypes among Blood Donors in Kano, Nigeria

    African Journals Online (AJOL)

    Background: The Rh antigens have been reported to cause acute and delayed haemolytic transfusion reactions apart from the dreadful Haemolytic Disease of the Newborn. The aim of this study was determine the prevalence of Rh phenotypes that would serve as a baseline data towards provision of safe blood transfusion ...

  1. Optimisation of GnRH antagonist use in ART

    NARCIS (Netherlands)

    Hamdine, O.

    2014-01-01

    This thesis focuses on the optimisation of controlled ovarian stimulation for IVF using exogenous FSH and GnRH antagonist co-treatment, by studying the timing of the initiation of GnRH antagonist co-medication and the role of ovarian reserve markers in optimising ovarian response and reproductive

  2. GnRH injection before artificial insemination (AI) alters follicle ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-08-04

    Aug 4, 2009 ... control group of Animals no injection of GnRH was performed. GnRH administered (Gonadorelin, 5 ml, intramuscular, made by. Aburaihan company, Tehran, Iran) on Day 6 of the estrous cycle. (estrus = Day 0). Ultrasonography examination. Ovarian follicular development was monitored daily by transrectal.

  3. A novel strategy for the treatment of chronic wounds based on the topical administration of rhEGF-loaded lipid nanoparticles: In vitro bioactivity and in vivo effectiveness in healing-impaired db/db mice.

    Science.gov (United States)

    Gainza, Garazi; Pastor, Marta; Aguirre, José Javier; Villullas, Silvia; Pedraz, José Luis; Hernandez, Rosa Maria; Igartua, Manoli

    2014-07-10

    Lipid nanoparticles are currently receiving increasing interest because they permit the topical administration of proteins, such as recombinant human epidermal growth factor (rhEGF), in a sustained and effective manner. Because chronic wounds have become a major healthcare burden, the topical administration of rhEGF-loaded lipid nanoparticles, namely solid lipid nanoparticles (SLN) and nanostructured lipid carries (NLC), appears to be an interesting and suitable strategy for the treatment of chronic wounds. Both rhEGF-loaded lipid nanoparticles were prepared through the emulsification-ultrasonication method; however, the NLC-rhEGF preparation did not require the use of any organic solvents. The characterisation of the nanoparticles (NP) revealed that the encapsulation efficiency (EE) of NLC-rhEGF was significantly greater than obtained with SLN-rhEGF. The in vitro experiments demonstrated that gamma sterilisation is a suitable process for the final sterilisation because no loss in activity was observed after the sterilisation process. In addition, the proliferation assays revealed that the bioactivity of the nanoformulations was even higher than that of free rhEGF. Finally, the effectiveness of the rhEGF-loaded lipid nanoparticles was assayed in a full-thickness wound model in db/db mice. The data demonstrated that four topical administrations of SLN-rhEGF and NLC-rhEGF significantly improved healing in terms of wound closure, restoration of the inflammatory process, and re-epithelisation grade. In addition, the data did not reveal any differences in the in vivo effectiveness between the different rhEGF-loaded lipid nanoparticles. Overall, these findings demonstrate the promising potential of rhEGF-loaded lipid nanoparticles, particularly NLC-rhEGF, for the promotion of faster and more effective healing and suggest their future application for the treatment of chronic wounds. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

    Science.gov (United States)

    Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

    2011-01-01

    Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This

  5. A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures.

    Science.gov (United States)

    Promentilla, Michael Angelo B; Furuichi, T; Ishii, K; Tanikawa, N

    2008-08-01

    The Analytic Network Process (ANP) has been proposed to incorporate interdependence and feedback effect in the prioritization of remedial countermeasures using a hierarchical network decision model, but this approach seems to be incapable of capturing the vagueness and fuzziness during value judgment elicitation. The aim of this paper is to present an evaluation method using a fuzzy ANP (FANP) approach to address this shortcoming. Triangular fuzzy numbers (TFN) and their degree of fuzziness are used in the semantic scale as human judgment expressed in natural language is most often vague and fuzzy. The method employs the alpha-cuts, interval arithmetic and optimism index to transform the fuzzy comparative judgment matrix into set of crisp matrices, and then calculates the desired priorities using the eigenvector method. A numerical example, which was drawn from a real-life case study of an uncontrolled landfill in Japan, is presented to demonstrate the process. Results from the sensitivity analysis describe how the fuzziness in judgment could affect the solution robustness of the prioritization method. The proposed FANP approach therefore could effectively deal with the uncertain judgment inherent in the decision making process and derive the meaningful priorities explicitly from a complex decision structure in the evaluation of contaminated site remedial countermeasures.

  6. Penerapan Cutomer Relationship Management (CRM Dengan Menggunakan Metode Analytic Network Process (ANP Pada Perusahaan Ritel

    Directory of Open Access Journals (Sweden)

    Nofiyati Nofiyati

    2016-01-01

    Full Text Available Retail industry or retail business is a fast-growing business in the midst of global competition conditions. One strategy to attract more consumers are Customer Relationship Management (CRM. The successful implementation of CRM in the enterprise is influenced by several environmental perspectives, strategies, customers and products / services, processes, participants, infrastructure, and information technology are integrated in the framework of Work System (WS. This research was carried out by applying the method of Multiple Criteria Decision Making (MCDM that is able to accommodate the outer and inner linkage from multiple nodes / indicators are considered, namely the Analytical Network Process (ANP to rank the quality of implementation CRM in retail companies and strong influential node / indicator of the best retail among three alternative the consisting of Alfamart, Indomaret and Smesco mart. From the results of application ANP method, obtained the rank quality of implementation CRM in retail companies with first rank is Indomaret the value of 1.0000; and the second is Alfamart with a value 0.9575; and the third is Smesco mart with a value of 0.8034. While node / indicator strong influence on the the best retail is level of chaos, long and short term planning, customer service, system integration, appropriate skills, technical infrastructure, easily of use and accessibility of information.   Keywords: Ritel, Customer Relationship Management (CRM, Analytic Network Process (ANP, Kerangka Work System (WS.

  7. The new Athens center on data processing from the neutron monitor network in real time

    Directory of Open Access Journals (Sweden)

    Mavromichalaki

    2005-11-01

    Full Text Available The ground-based neutron monitors (NMs record galactic and solar relativistic cosmic rays which can play a useful key role in space weather forecasting, as a result of their interaction with interplanetary disturbances. The Earth's-based neutron monitor network has been used in order to produce a real-time prediction of space weather phenomena. Therefore, the Athens Neutron Monitor Data Processing Center (ANMODAP takes advantage of this unique multi-directional device to solve problems concerning the diagnosis and forecasting of space weather. At this moment there has been a multi-sided use of neutron monitors. On the one hand, a preliminary alert for ground level enhancements (GLEs may be provided due to relativistic solar particles and can be registered around 20 to 30 min before the arrival of the main part of lower energy particles responsible for radiation hazard. To make a more reliable prognosis of these events, real time data from channels of lower energy particles and X-ray intensity from the GOES satellite are involved in the analysis. The other possibility is to search in real time for predictors of geomagnetic storms when they occur simultaneously with Forbush effects, using hourly, on-line accessible neutron monitor data from the worldwide network and applying a special method of processing. This chance of prognosis is only being elaborated and considered here as one of the possible uses of the Neutron Monitor Network for forecasting the arrival of interplanetary disturbance to the Earth. The achievements, the processes and the future results, are discussed in this work.

  8. The new Athens center on data processing from the neutron monitor network in real time

    Directory of Open Access Journals (Sweden)

    Mavromichalaki

    2005-11-01

    Full Text Available The ground-based neutron monitors (NMs record galactic and solar relativistic cosmic rays which can play a useful key role in space weather forecasting, as a result of their interaction with interplanetary disturbances. The Earth's-based neutron monitor network has been used in order to produce a real-time prediction of space weather phenomena. Therefore, the Athens Neutron Monitor Data Processing Center (ANMODAP takes advantage of this unique multi-directional device to solve problems concerning the diagnosis and forecasting of space weather. At this moment there has been a multi-sided use of neutron monitors. On the one hand, a preliminary alert for ground level enhancements (GLEs may be provided due to relativistic solar particles and can be registered around 20 to 30 min before the arrival of the main part of lower energy particles responsible for radiation hazard. To make a more reliable prognosis of these events, real time data from channels of lower energy particles and X-ray intensity from the GOES satellite are involved in the analysis. The other possibility is to search in real time for predictors of geomagnetic storms when they occur simultaneously with Forbush effects, using hourly, on-line accessible neutron monitor data from the worldwide network and applying a special method of processing. This chance of prognosis is only being elaborated and considered here as one of the possible uses of the Neutron Monitor Network for forecasting the arrival of interplanetary disturbance to the Earth. The achievements, the processes and the future results, are discussed in this work.

  9. ICE: A Scalable, Low-Cost FPGA-Based Telescope Signal Processing and Networking System

    Science.gov (United States)

    Bandura, K.; Bender, A. N.; Cliche, J. F.; de Haan, T.; Dobbs, M. A.; Gilbert, A. J.; Griffin, S.; Hsyu, G.; Ittah, D.; Parra, J. Mena; Montgomery, J.; Pinsonneault-Marotte, T.; Siegel, S.; Smecher, G.; Tang, Q. Y.; Vanderlinde, K.; Whitehorn, N.

    2016-03-01

    We present an overview of the ‘ICE’ hardware and software framework that implements large arrays of interconnected field-programmable gate array (FPGA)-based data acquisition, signal processing and networking nodes economically. The system was conceived for application to radio, millimeter and sub-millimeter telescope readout systems that have requirements beyond typical off-the-shelf processing systems, such as careful control of interference signals produced by the digital electronics, and clocking of all elements in the system from a single precise observatory-derived oscillator. A new generation of telescopes operating at these frequency bands and designed with a vastly increased emphasis on digital signal processing to support their detector multiplexing technology or high-bandwidth correlators — data rates exceeding a terabyte per second — are becoming common. The ICE system is built around a custom FPGA motherboard that makes use of an Xilinx Kintex-7 FPGA and ARM-based co-processor. The system is specialized for specific applications through software, firmware and custom mezzanine daughter boards that interface to the FPGA through the industry-standard FPGA mezzanine card (FMC) specifications. For high density applications, the motherboards are packaged in 16-slot crates with ICE backplanes that implement a low-cost passive full-mesh network between the motherboards in a crate, allow high bandwidth interconnection between crates and enable data offload to a computer cluster. A Python-based control software library automatically detects and operates the hardware in the array. Examples of specific telescope applications of the ICE framework are presented, namely the frequency-multiplexed bolometer readout systems used for the South Pole Telescope (SPT) and Simons Array and the digitizer, F-engine, and networking engine for the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) radio

  10. TOLNET – A Tropospheric Ozone Lidar Profiling Network for Satellite Continuity and Process Studies

    Directory of Open Access Journals (Sweden)

    Newchurch Michael J.

    2016-01-01

    Full Text Available Ozone lidars measure continuous, high-resolution ozone profiles critical for process studies and for satellite validation in the lower troposphere. However, the effectiveness of lidar validation by using single-station data is limited. Recently, NASA initiated an interagency ozone lidar observation network under the name TOLNet to promote cooperative multiple-station ozone-lidar observations to provide highly timeresolved (few minutes tropospheric-ozone vertical profiles useful for air-quality studies, model evaluation, and satellite validation. This article briefly describes the concept, stations, major specifications of the TOLNet instruments, and data archiving.

  11. General purpose graphics-processing-unit implementation of cosmological domain wall network evolution

    Science.gov (United States)

    Correia, J. R. C. C. C.; Martins, C. J. A. P.

    2017-10-01

    Topological defects unavoidably form at symmetry breaking phase transitions in the early universe. To probe the parameter space of theoretical models and set tighter experimental constraints (exploiting the recent advances in astrophysical observations), one requires more and more demanding simulations, and therefore more hardware resources and computation time. Improving the speed and efficiency of existing codes is essential. Here we present a general purpose graphics-processing-unit implementation of the canonical Press-Ryden-Spergel algorithm for the evolution of cosmological domain wall networks. This is ported to the Open Computing Language standard, and as a consequence significant speedups are achieved both in two-dimensional (2D) and 3D simulations.

  12. Reaction time as a stochastic process implemented by functional brain networks.

    Science.gov (United States)

    Siettos, Constantinos I; Smyrnis, Nikolaos

    2017-04-01

    Many studies focus on anatomical brain connectivity in an effort to explain the effect of practice on reaction time (RT) that is observed in many cognitive tasks. In this commentary, we suggest that RT reflects a stochastic process that varies in each single repetition of any cognitive task and cannot be attributed only to anatomical properties of the underlying neuronal circuit. Based on recent evidence from Magnetoencephalographic, Electroencephalographic, and fMRI studies, we further propose that the functional properties of key brain areas and their self-organization into functional connectivity networks contribute to the RT and could also explain the effects of training on the distribution of the RT.

  13. General purpose graphics-processing-unit implementation of cosmological domain wall network evolution.

    Science.gov (United States)

    Correia, J R C C C; Martins, C J A P

    2017-10-01

    Topological defects unavoidably form at symmetry breaking phase transitions in the early universe. To probe the parameter space of theoretical models and set tighter experimental constraints (exploiting the recent advances in astrophysical observations), one requires more and more demanding simulations, and therefore more hardware resources and computation time. Improving the speed and efficiency of existing codes is essential. Here we present a general purpose graphics-processing-unit implementation of the canonical Press-Ryden-Spergel algorithm for the evolution of cosmological domain wall networks. This is ported to the Open Computing Language standard, and as a consequence significant speedups are achieved both in two-dimensional (2D) and 3D simulations.

  14. Analytic network process (ANP approach for product mix planning in railway industry

    Directory of Open Access Journals (Sweden)

    Hadi Pazoki Toroudi

    2016-08-01

    Full Text Available Given the competitive environment in the global market in recent years, organizations need to plan for increased profitability and optimize their performance. Planning for an appropriate product mix plays essential role for the success of most production units. This paper applies analytical network process (ANP approach for product mix planning for a part supplier in Iran. The proposed method uses four criteria including cost of production, sales figures, supply of raw materials and quality of products. In addition, the study proposes different set of products as alternatives for production planning. The preliminary results have indicated that that the proposed study of this paper could increase productivity, significantly.

  15. Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the Babao River basin, China

    NARCIS (Netherlands)

    Ge, Y.; Wang, J.H.; Heuvelink, G.B.M.; Jin, R.; Li, X.; Wang, J.F.

    2015-01-01

    Optimal selection of observation locations is an essential task in designing an effective ecohydrological process monitoring network, which provides information on ecohydrological variables by capturing their spatial variation and distribution. This article presents a geostatistical method for

  16. Transition from intelligence cycle to intelligence process: the network-centric intelligence in narrow seas

    Science.gov (United States)

    Büker, Engin

    2015-05-01

    The defence technologies which have been developing and changing rapidly, today make it difficult to be able to foresee the next environment and spectrum of warfare. When said change and development is looked in specific to the naval operations, it can be said that the possible battlefield and scenarios to be developed in the near and middle terms (5-20 years) are more clarified with compare to other force components. Network Centric Naval Warfare Concept that was developed for the floating, diving and flying fleet platforms which serves away from its own mainland for miles, will keep its significance in the future. Accordingly, Network Centric Intelligence structure completely integrating with the command and control systems will have relatively more importance. This study will firstly try to figure out the transition from the traditional intelligence cycle that is still used in conventional war to Network Centric Intelligence Production Process. In the last part, the use of this new approach on the base of UAV that is alternative to satellite based command control and data transfer systems in the joint operations in narrow seas will be examined, a model suggestion for the use of operative and strategic UAVs which are assured within the scope of the NATO AGS2 for this aim will be brought.

  17. Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.

    Science.gov (United States)

    Takahashi, Maria Beatriz; Leme, Jaci; Caricati, Celso Pereira; Tonso, Aldo; Fernández Núñez, Eutimio Gustavo; Rocha, José Celso

    2015-06-01

    Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV-Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV-Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 10(5) ± 1.90 10(5) cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV-VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

  18. Experimental study and artificial neural network modeling of tartrazine removal by photocatalytic process under solar light.

    Science.gov (United States)

    Sebti, Aicha; Souahi, Fatiha; Mohellebi, Faroudja; Igoud, Sadek

    2017-07-01

    This research focuses on the application of an artificial neural network (ANN) to predict the removal efficiency of tartrazine from simulated wastewater using a photocatalytic process under solar illumination. A program is developed in Matlab software to optimize the neural network architecture and select the suitable combination of training algorithm, activation function and hidden neurons number. The experimental results of a batch reactor operated under different conditions of pH, TiO2 concentration, initial organic pollutant concentration and solar radiation intensity are used to train, validate and test the networks. While negligible mineralization is demonstrated, the experimental results show that under sunlight irradiation, 85% of tartrazine is removed after 300 min using only 0.3 g/L of TiO2 powder. Therefore, irradiation time is prolonged and almost 66% of total organic carbon is reduced after 15 hours. ANN 5-8-1 with Bayesian regulation back-propagation algorithm and hyperbolic tangent sigmoid transfer function is found to be able to predict the response with high accuracy. In addition, the connection weights approach is used to assess the importance contribution of each input variable on the ANN model response. Among the five experimental parameters, the irradiation time has the greatest effect on the removal efficiency of tartrazine.

  19. Identifying influential nodes based on graph signal processing in complex networks

    Science.gov (United States)

    Zhao, Jia; Yu, Li; Li, Jing-Ru; Zhou, Peng

    2015-05-01

    Identifying influential nodes in complex networks is of both theoretical and practical importance. Existing methods identify influential nodes based on their positions in the network and assume that the nodes are homogeneous. However, node heterogeneity (i.e., different attributes such as interest, energy, age, and so on) ubiquitously exists and needs to be taken into consideration. In this paper, we conduct an investigation into node attributes and propose a graph signal processing based centrality (GSPC) method to identify influential nodes considering both the node attributes and the network topology. We first evaluate our GSPC method using two real-world datasets. The results show that our GSPC method effectively identifies influential nodes, which correspond well with the underlying ground truth. This is compatible to the previous eigenvector centrality and principal component centrality methods under circumstances where the nodes are homogeneous. In addition, spreading analysis shows that the GSPC method has a positive effect on the spreading dynamics. Project supported by the National Natural Science Foundation of China (Grant No. 61231010) and the Fundamental Research Funds for the Central Universities, China (Grant No. HUST No. 2012QN076).

  20. Forest point processes for the automatic extraction of networks in raster data

    Science.gov (United States)

    Schmidt, Alena; Lafarge, Florent; Brenner, Claus; Rottensteiner, Franz; Heipke, Christian

    2017-04-01

    In this paper, we propose a new stochastic approach for the automatic detection of network structures in raster data. We represent a network as a set of trees with acyclic planar graphs. We embed this model in the probabilistic framework of spatial point processes and determine the most probable configuration of trees by stochastic sampling. That is, different configurations are constructed randomly by modifying the graph parameters and by adding or removing nodes and edges to/ from the current trees. Each configuration is evaluated based on the probabilities for these changes and an energy function describing the conformity with a predefined model. By using the Reversible jump Markov chain Monte Carlo sampler, an approximation of the global optimum of the energy function is iteratively reached. Although our main target application is the extraction of rivers and tidal channels in digital terrain models, experiments with other types of networks in images show the transferability to further applications. Qualitative and quantitative evaluations demonstrate the competitiveness of our approach with respect to existing algorithms.

  1. Use of uniform designs in combination with neural networks for viral infection process development.

    Science.gov (United States)

    Buenno, Laís Hara; Rocha, José Celso; Leme, Jaci; Caricati, Celso Pereira; Tonso, Aldo; Fernández Núñez, Eutimio Gustavo

    2015-01-01

    This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions. © 2015 American Institute of Chemical Engineers.

  2. Emotion perception and executive control interact in the salience network during emotionally charged working memory processing.

    Science.gov (United States)

    Luo, Yu; Qin, Shaozheng; Fernández, Guillén; Zhang, Yu; Klumpers, Floris; Li, Hong

    2014-11-01

    Processing of emotional stimuli can either hinder or facilitate ongoing working memory (WM); however, the neural basis of these effects remains largely unknown. Here we examined the neural mechanisms of these paradoxical effects by implementing a novel emotional WM task in an fMRI study. Twenty-five young healthy participants performed an N-back task with fearful and neutral faces as stimuli. Participants made more errors when performing 0-back task with fearful versus neutral faces, whereas they made fewer errors when performing 2-back task with fearful versus neutral faces. These emotional impairment and enhancement on behavioral performance paralleled significant interactions in distributed regions in the salience network including anterior insula (AI) and dorsal cingulate cortex (dACC), as well as in emotion perception network including amygdala and temporal-occipital association cortex (TOC). The dorsal AI (dAI) and dACC were more activated when comparing fearful with neutral faces in 0-back task. Contrarily, dAI showed reduced activation, while TOC and amygdala showed stronger responses to fearful as compared to neutral faces in the 2-back task. These findings provide direct neural evidence to the emerging dual competition model suggesting that the salience network plays a critical role in mediating interaction between emotion perception and executive control when facing ever-changing behavioral demands. Copyright © 2014 Wiley Periodicals, Inc.

  3. Advanced digital signal processing for short-haul and access network

    Science.gov (United States)

    Zhang, Junwen; Yu, Jianjun; Chi, Nan

    2016-02-01

    Digital signal processing (DSP) has been proved to be a successful technology recently in high speed and high spectrum-efficiency optical short-haul and access network, which enables high performances based on digital equalizations and compensations. In this paper, we investigate advanced DSP at the transmitter and receiver side for signal pre-equalization and post-equalization in an optical access network. A novel DSP-based digital and optical pre-equalization scheme has been proposed for bandwidth-limited high speed short-distance communication system, which is based on the feedback of receiver-side adaptive equalizers, such as least-mean-squares (LMS) algorithm and constant or multi-modulus algorithms (CMA, MMA). Based on this scheme, we experimentally demonstrate 400GE on a single optical carrier based on the highest ETDM 120-GBaud PDM-PAM-4 signal, using one external modulator and coherent detection. A line rate of 480-Gb/s is achieved, which enables 20% forward-error correction (FEC) overhead to keep the 400-Gb/s net information rate. The performance after fiber transmission shows large margin for both short range and metro/regional networks. We also extend the advanced DSP for short haul optical access networks by using high order QAMs. We propose and demonstrate a high speed multi-band CAP-WDM-PON system on intensity modulation, direct detection and digital equalizations. A hybrid modified cascaded MMA post-equalization schemes are used to equalize the multi-band CAP-mQAM signals. Using this scheme, we successfully demonstrates 550Gb/s high capacity WDMPON system with 11 WDM channels, 55 sub-bands, and 10-Gb/s per user in the downstream over 40-km SMF.

  4. Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

    Directory of Open Access Journals (Sweden)

    E. M. A. Perrier

    2010-10-01

    Full Text Available Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009. Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

  5. Production Supervision Incorporated With Network Technology-A Solution For Controlling In-Process Inventory

    Directory of Open Access Journals (Sweden)

    Suraj Yadav

    2013-06-01

    Full Text Available In context to the manufacturing management in medium scale production floor, work-in-process (WIP management or the inprocess inventory and control as the inevitable result of the production process has become a vital link of production plan. Due to the growing production requirements and the potential economic benefits of manufacturing process flow, enterprises have been pushed to integrate work-in-process management with their manufacturing process and the larger the company the larger the list of in-process inventory and this all are typically hard to manage so for the same respect the author in this paper has lighted on the integration of sophisticated electronics and networking technologies with the W.I.P with an native and low cost solution for managing the same, specially for the medium scaled company dealing with large number of product or with the customized product with reference to study of present scenario of a multinational company’s plant engineering department.

  6. Receptor-mediated binding and uptake of GnRH agonist and antagonist by pituitary cells

    Energy Technology Data Exchange (ETDEWEB)

    Jennes, L.; Stumpf, W.E.; Conn, P.M.

    1984-01-01

    The intracellular pathway of an enzyme resistant GnRH agonist (D- Lys6 -GnRH) conjugated to ferritin or to colloidal gold was followed in cultured pituitary cells. After an initial uniform distribution over the cell surface of gonadotropes, the electrondense marker was internalized, either individually or in small groups. After longer incubation times, the marker appeared in the lysosomal compartment and the Golgi apparatus, where it could be found in the vesicular as well as cisternal portion. In addition, the receptor-mediated endocytosis of the GnRH antagonist D-p-Glu1-D-Phe2-D-Trp3-D- Lys6 -GnRH was studied by light and electron microscopic autoradiography after 30 and 60 min of incubation to ensure uptake. At both time points, in in vitro as well as in vivo studies, silver grains were localized over cytoplasmic organelles of castration cells, including dilated endoplasmic reticulum, lysosomes, and clear vesicles. No consistent association with cell nuclei, mitochondria, or secretory vesicles could be observed. The results suggest that both agonist and antagonist are binding selectively to the plasma membrane of gonadotropes and subsequently are taken up via receptor-mediated endocytosis for degradation or possible action on synthetic processes.

  7. Hydrodeoxygenation of Phenol to Benzene and Cyclohexane on Rh(111) and Rh(211) Surfaces: Insights from Density Functional Theory

    DEFF Research Database (Denmark)

    Garcia-Pintos, Delfina; Voss, Johannes; Jensen, Anker Degn

    2016-01-01

    Herein we describe the C-O cleavage of phenol and cyclohexanol over Rh (111) and Rh (211) surfaces using density functional theory calculations. Our analysis is complemented by a microkinetic model of the reactions, which indicates that the C-O bond cleavage of cyclohexanol is easier than that of...

  8. GnRH agonist versus GnRH antagonist in in vitro fertilization and embryo transfer (IVF/ET

    Directory of Open Access Journals (Sweden)

    Depalo Raffaella

    2012-04-01

    Full Text Available Abstract Several protocols are actually available for in Vitro Fertilization and Embryo Transfer. The review summarizes the main differences and the clinic characteristics of the protocols in use with GnRH agonists and GnRH antagonists by emphasizing the major outcomes and hormonal changes associated with each protocol. The majority of randomized clinical trials clearly shows that in “in Vitro” Fertilization and Embryo Transfer, the combination of exogenous Gonadotropin plus a Gonadotropin Releasing Hormone (GnRH agonist, which is able to suppress pituitary FSH and LH secretion, is associated with increased pregnancy rate as compared with the use of gonadotropins without a GnRH agonist. Protocols with GnRH antagonists are effective in preventing a premature rise of LH and induce a shorter and more cost-effective ovarian stimulation compared to the long agonist protocol. However, a different synchronization of follicular recruitment and growth occurs with GnRH agonists than with GnRH antagonists. Future developments have to be focused on timing of the administration of GnRH antagonists, by giving a great attention to new strategies of stimulation in patients in which radio-chemotherapy cycles are needed.

  9. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

    Science.gov (United States)

    Khanali, Majid; Mobli, Hossein; Hosseinzadeh-Bandbafha, Homa

    2017-12-01

    In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R 2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for

  10. Subjective loudness and reality of auditory verbal hallucinations and activation of the inner speech processing network.

    Science.gov (United States)

    Vercammen, Ans; Knegtering, Henderikus; Bruggeman, Richard; Aleman, André

    2011-09-01

    One of the most influential cognitive models of auditory verbal hallucinations (AVH) suggests that a failure to adequately monitor the production of one's own inner speech leads to verbal thought being misidentified as an alien voice. However, it is unclear whether this theory can explain the phenomenological complexity of AVH. We aimed to assess whether subjective perceptual and experiential characteristics may be linked to neural activation in the inner speech processing network. Twenty-two patients with schizophrenia and AVH underwent a 3-T functional magnetic resonance imaging scan, while performing a metrical stress evaluation task, which has been shown to activate both inner speech production and perception regions. Regions of interest (ROIs) comprising the putative inner speech network were defined using the Anatomical Automatic Labeling system. Correlations were calculated between scores on the "loudness" and "reality" subscales of the Auditory Hallucination Rating Scale (AHRS) and activation in these ROIs. Second, the AHRS subscales, and general AVH severity, indexed by the Positive and Negative Syndrome Scale, were correlated with a language lateralization index. Louder AVH were associated with reduced task-related activity in bilateral angular gyrus, anterior cingulate gyrus, left inferior frontal gyrus, left insula, and left temporal cortex. This could potentially be due to a competition for shared neural resources. Reality on the other hand was found to be associated with reduced language lateralization. Strong activation of the inner speech processing network may contribute to the subjective loudness of AVH. However, a relatively increased contribution from right hemisphere language areas may be responsible for the more complex experiential characteristics, such as the nonself source or how real AVH are.

  11. Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models

    Science.gov (United States)

    Plant, Nathaniel G.; Holland, K. Todd

    2011-01-01

    Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.

  12. Integrating RFID Technology and EPC Network into a B2B Retail Supply Chain: A Step Toward Intelligent Business Processes

    Directory of Open Access Journals (Sweden)

    Samuel Fosso Wamba

    2007-06-01

    Full Text Available This article introduces RFID technology and the EPC Network and investigates their potential for B-to-B eCommerce supply chain management. Based on empirical data gathered from four tightly interrelated firms from three layers of a supply chain, several scenarios integrating RFID and the EPC Network have been tested and evaluated. In the context of warehousing activities in one specific retail supply chain, the results indicate that i the business process approach seems quite appropriate to capture the real potential of RFID and the EPC Network; ii RFID technology and the EPC Network can improve the “shipping” and the “receiving” processes; iii they can automatically trigger some business processes; iv they foster a higher level of information sharing between supply chain members; and v they promote the emergence of new business processes such as “process-to-process,” “process-to-machine,” and “machine-to-machine.” The paper helps to improve our understanding of the real potential of RFID and the EPC Network for business processes.

  13. Joint preprocesser-based detector for cooperative networks with limited hardware processing capability

    KAUST Repository

    Abuzaid, Abdulrahman I.

    2015-02-01

    In this letter, a joint detector for cooperative communication networks is proposed when the destination has limited hardware processing capability. The transmitter sends its symbols with the help of L relays. As the destination has limited hardware, only U out of L signals are processed and the energy of the remaining relays is lost. To solve this problem, a joint preprocessing based detector is proposed. This joint preprocessor based detector operate on the principles of minimizing the symbol error rate (SER). For a realistic assessment, pilot symbol aided channel estimation is incorporated for this proposed detector. From our simulations, it can be observed that our proposed detector achieves the same SER performance as that of the maximum likelihood (ML) detector with all participating relays. Additionally, our detector outperforms selection combining (SC), channel shortening (CS) scheme and reduced-rank techniques when using the same U. Our proposed scheme has low computational complexity.

  14. Toward a network model of MHC class II-restricted antigen processing

    Directory of Open Access Journals (Sweden)

    Laurence C Eisenlohr

    2013-12-01

    Full Text Available The standard model of Major Histocompatibility Complex class II (MHCII-restricted antigen processing depicts a straightforward, linear pathway: Internalized antigens are converted into peptides that load in a chaperone dependent manner onto nascent MHCII in the late endosome, the complexes subsequently trafficking to the cell surface for recognition by CD4+ T cells (TCD4+. Several variations on this theme, both moderate and radical, have come to light but these alternatives have remained peripheral, the conventional pathway generally presumed to be the primary driver of TCD4+ responses. Here we continue to press for the conceptual repositioning of these alternatives toward the center while proposing that MHCII processing be thought of less in terms of discrete pathways and more in terms of a network whose major and minor conduits are variable depending upon many factors, including the epitope, the nature of the antigen, the source of the antigen, and the identity of the antigen-presenting cell.

  15. A probablistic neural network classification system for signal and image processing

    Energy Technology Data Exchange (ETDEWEB)

    Bowman, B. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

  16. An Integrated Business and Engineering Framework for Synthesis and Design of Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto

    , in which all the aspects of the problem (technical, economical, regulatory, logistical, etc.) need to be considered simultaneously, in order to be able to identify the optimal design. Through the developments realized in the last decades, Process Systems Engineering has shown the potential to contribute...... for synthesis and design of processing networks in the industrial sector is still lower than what could be expected. One of the key reasons for this lack of acceptance lays in their complexity. The formulation of these problems, in fact, often results in a time-consuming activity, due to the number of data...... that need to be gathered and of equations that need to be specified. The solution of the optimization problem formulated, moreover, requires expertise in discrete optimization, which is often not part of the standard skills set of design engineers and decision-makers. This Ph.D. project, therefore, aims...

  17. Implicit and Explicit Social Mentalizing: Dual Processes driven by a Shared Neural Network

    Directory of Open Access Journals (Sweden)

    Frank eVan Overwalle

    2013-09-01

    Full Text Available Recent social neuroscientific evidence indicates that implicit and explicit inferences on the mind of another person (i.e., intentions, attributions or traits, are subserved by a shared mentalizing network. Under both implicit and explicit instructions, ERP studies reveal that early inferences occur at about the same time, and fMRI studies demonstrate an overlap in core mentalizing areas, including the temporo-parietal junction and the medial prefrontal cortex. These results suggest a rapid shared implicit intuition followed by a slower explicit verification processes (as revealed by additional brain activation during explicit versus implicit inferences. These data provide support for a default-adjustment dual-process framework of social mentalizing.

  18. Variability of the institutional review board process within a national research network.

    Science.gov (United States)

    Khan, Muhammad A; Barratt, Michelle S; Krugman, Scott D; Serwint, Janet R; Dumont-Driscoll, Marilyn

    2014-06-01

    To determine the variability of the institutional review board (IRB) process for a minimal risk multicenter study. Participants included 24 Continuity Research Network (CORNET) sites of the Academic Pediatric Association that participated in a cross-sectional study. Each site obtained individual institutional IRB approval. An anonymous questionnaire went to site investigators about the IRB process at their institution. Twenty-two of 24 sites (92%) responded. Preparation time ranged from 1 to 20 hours, mean of 7.1 hours. Individuals submitting ≤3 IRB applications/year required more time for completion than those submitting >3/year (P variable across study sites. These findings indicate that multicenter research projects should anticipate barriers to timely study implementation. Improved IRB standardization or centralization for multicenter clinical studies would facilitate this type of practice-based clinical research.

  19. Computerized system of automated recording and processing of seismic data from the Upper Silesian microseismic network

    Energy Technology Data Exchange (ETDEWEB)

    Kornowski, J.; Sokolowski, H.

    1981-05-01

    This paper describes operation of the Upper Silesian microseismic network, developed and directed by the Central Mining Institute. Seismic events are detected by the T-8100 Racal-Thermionic multi-channel system with Willmore MK II seismic detectors, and are transmitted to the computer center, equipped with the PDP 11/45 minicomputer produced by the Digital Equipment Corp, by means of an FM system. The recording and processing system consists of the following stages: seismic event recording, determining time of seismic events, detection of shocks and elimination of disturbances, assessment of seismic energy of rocks, identifying time of shock recording, determining shock epicenter, storage of information on shocks. Basic computer codes of the system are described: shock detection, determination of time, determination of shock epicenters, statistical processing, and storage. The system collects and stores information on earthquakes and shocks caused by rock bursts. (6 refs.) (In Polish)

  20. Instrumentation, Field Network And Process Automation for the LHC Cryogenic Line Tests

    CERN Document Server

    Bager, T; Bertrand, G; Casas-Cubillos, J; Gomes, P; Parente, C; Riddone, G; Suraci, A

    2000-01-01

    This paper describes the cryogenic control system and associated instrumentation of the test facility for 3 pre-series units of the LHC Cryogenic Distribution Line. For each unit, the process automation is based on a Programmable Logic Con-troller implementing more than 30 closed control loops and handling alarms, in-terlocks and overall process management. More than 160 sensors and actuators are distributed over 150 m on a Profibus DP/PA network. Parameterization, cali-bration and diagnosis are remotely available through the bus. Considering the diversity, amount and geographical distribution of the instru-mentation involved, this is a representative approach to the cryogenic control system for CERN's next accelerator.

  1. Neural networks and differential evolution algorithm applied for modelling the depollution process of some gaseous streams.

    Science.gov (United States)

    Curteanu, Silvia; Suditu, Gabriel Dan; Buburuzan, Adela Marina; Dragoi, Elena Niculina

    2014-11-01

    The depollution of some gaseous streams containing n-hexane is studied by adsorption in a fixed bed column, under dynamic conditions, using granular activated carbon and two types of non-functionalized hypercross-linked polymeric resins. In order to model the process, a new neuro-evolutionary approach is proposed. It is a combination of a modified differential evolution (DE) with neural networks (NNs) and two local search algorithms, the global and local optimizers, working together to determine the optimal NN model. The main elements that characterize the applied variant of DE consist in using an opposition-based learning initialization, a simple self-adaptive procedure for the control parameters, and a modified mutation principle based on the fitness function as a criterion for reorganization. The results obtained prove that the proposed algorithm is able to determine a good model of the considered process, its performance being better than those of an available phenomenological model.

  2. Top-down network analysis to drive bottom-up modeling of physiological processes.

    Science.gov (United States)

    Poirel, Christopher L; Rodrigues, Richard R; Chen, Katherine C; Tyson, John J; Murali, T M

    2013-05-01

    Top-down analyses in systems biology can automatically find correlations among genes and proteins in large-scale datasets. However, it is often difficult to design experiments from these results. In contrast, bottom-up approaches painstakingly craft detailed models that can be simulated computationally to suggest wet lab experiments. However, developing the models is a manual process that can take many years. These approaches have largely been developed independently. We present LINKER, an efficient and automated data-driven method that can analyze molecular interactomes to propose extensions to models that can be simulated. LINKER combines teleporting random walks and k-shortest path computations to discover connections from a source protein to a set of proteins collectively involved in a particular cellular process. We evaluate the efficacy of LINKER by applying it to a well-known dynamic model of the cell division cycle in Saccharomyces cerevisiae. Compared to other state-of-the-art methods, subnetworks computed by LINKER are heavily enriched in Gene Ontology (GO) terms relevant to the cell cycle. Finally, we highlight how networks computed by LINKER elucidate the role of a protein kinase (Cdc5) in the mitotic exit network of a dynamic model of the cell cycle.

  3. Temperature and relative humidity estimation and prediction in the tobacco drying process using Artificial Neural Networks.

    Science.gov (United States)

    Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén

    2012-10-17

    This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.

  4. Pore network modeling of drainage process in patterned porous media: a quasi-static study

    KAUST Repository

    Zhang, Tao

    2015-04-17

    This work represents a preliminary investigation on the role of wettability conditions on the flow of a two-phase system in porous media. Since such effects have been lumped implicitly in relative permeability-saturation and capillary pressure-saturation relationships, it is quite challenging to isolate its effects explicitly in real porous media applications. However, within the framework of pore network models, it is easy to highlight the effects of wettability conditions on the transport of two-phase systems. We employ quasi-static investigation in which the system undergo slow movement based on slight increment of the imposed pressure. Several numerical experiments of the drainage process are conducted to displace a wetting fluid with a non-wetting one. In all these experiments the network is assigned different scenarios of various wettability patterns. The aim is to show that the drainage process is very much affected by the imposed pattern of wettability. The wettability conditions are imposed by assigning the value of contact angle to each pore throat according to predefined patterns.

  5. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  6. Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks

    Science.gov (United States)

    Richter, Philipp; Toledano-Ayala, Manuel

    2015-01-01

    Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996

  7. Distributed processing and network of data acquisition and diagnostics control for Large Helical Device (LHD)

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi, H.; Kojima, M.; Hidekuma, S. [National Inst. for Fusion Science, Toki, Gifu (Japan)

    1997-11-01

    The LHD (Large Helical Device) data processing system has been designed in order to deal with the huge amount of diagnostics data of 600-900 MB per 10-second short-pulse experiment. It prepares the first plasma experiment in March 1998. The recent increase of the data volume obliged to adopt the fully distributed system structure which uses multiple data transfer paths in parallel and separates all of the computer functions into clients and servers. The fundamental element installed for every diagnostic device consists of two kinds of server computers; the data acquisition PC/Windows NT and the real-time diagnostics control VME/VxWorks. To cope with diversified kinds of both device control channels and diagnostics data, the object-oriented method are utilized wholly for the development of this system. It not only reduces the development burden, but also widen the software portability and flexibility. 100Mbps EDDI-based fast networks will re-integrate the distributed server computers so that they can behave as one virtual macro-machine for users. Network methods applied for the LHD data processing system are completely based on the TCP/IP internet technology, and it provides the same accessibility to the remote collaborators as local participants can operate. (author)

  8. Annual gonadal cycles in birds: modeling the effects of photoperiod on seasonal changes in GnRH-1 secretion.

    Science.gov (United States)

    Dawson, Alistair

    2015-04-01

    This paper reviews current knowledge of photoperiod control of GnRH-1 secretion and proposes a model in which two processes act together to regulate GnRH1 secretion. Photo-induction controls GnRH1 secretion and is directly related to prevailing photoperiod. Photo-inhibition, a longer term process, acts through GnRH1 synthesis. It progresses each day during daylight hours, but reverses during darkness. Thus, photo-inhibition gradually increases when photoperiods exceed 12h, and reverses under shorter photoperiods. GnRH1 secretion on any particular day is the net result of these two processes acting in tandem. The only difference between species is their sensitivity to photo-inhibition. This can potentially explain differences in timing and duration of breeding seasons between species, why some species become absolutely photorefractory and others relatively photorefractory, why breeding seasons end at the same time at different latitudes within species, and why experimental protocols sometimes produce results that appear counter to what happens naturally. Copyright © 2014 The Author. Published by Elsevier Inc. All rights reserved.

  9. APLIKASI ANALYTIC NETWORK PROCESS (ANP PADA PERANCANGAN SISTEM PENGUKURAN KINERJA (Studi Kasus pada PT. X

    Directory of Open Access Journals (Sweden)

    Iwan Vanany

    2003-01-01

    Full Text Available The paper discusses the application of Analytic Network Process (ANP to support the weighted of design performance measurement system with Balanced Scorecard method. During the time, the weighted uses method that disregarding interdependence between objectives strategy and Key Performance Indicator (KPI's. The method which often used in this weighted is Analytical Hierarchy Process (AHP. In fact this condition does not express the concept of strategy map of Balanced Scorecard. Therefore is needed apply the other weighted method which attention to the interdependence between Key Performance Indicator (KPI. Application of the weighted with ANP method is conducted at one of the power company. This company represents result of restructuring of PT. PLN (Persero. The result of design performance measurement system of PT. X are objective strategy, Key Performance Indicator (KPI and strategy map, will be weighted by method of ANP. Further more Modeling of ANP based on strategy map. The result of application indicates that related of model of strategy map in Balanced Scorecard at PT. X is Feedback Network (hiernet with phenomenon of inner and dependence of outer dependence. The perspective on Balanced Scorecard is identically with cluster on ANP, while objective strategy and KPI are identically with sub-element and element. Result of weighted with ANP method shows the existence of culmination of weighted on financial perspective of Strategy Map at PT. X. Abstract in Bahasa Indonesia : Makalah ini membahas aplikasi Analytic Network Process (ANP untuk mendukung pembobotan pada perancangan sistem pengukuran kinerja dengan metode Balanced Scorecard. Selama ini, pembobotan yang ada menggunakan metode yang mengabaikan saling keterkaitan antar strategi objektif dengan Key Performance Indicator (KPI-KPI -nya. Metode yang sering digunakan didalam pembobotan ini adalah Analytical Hierarchy Process (AHP. Kondisi ini sebenarnya tidak mencerminkan konsep Strategy Map

  10. Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm.

    Science.gov (United States)

    Alluri, Vinoo; Toiviainen, Petri; Jääskeläinen, Iiro P; Glerean, Enrico; Sams, Mikko; Brattico, Elvira

    2012-02-15

    We investigated the neural underpinnings of timbral, tonal, and rhythmic features of a naturalistic musical stimulus. Participants were scanned with functional Magnetic Resonance Imaging (fMRI) while listening to a stimulus with a rich musical structure, a modern tango. We correlated temporal evolutions of timbral, tonal, and rhythmic features of the stimulus, extracted using acoustic feature extraction procedures, with the fMRI time series. Results corroborate those obtained with controlled stimuli in previous studies and highlight additional areas recruited during musical feature processing. While timbral feature processing was associated with activations in cognitive areas of the cerebellum, and sensory and default mode network cerebrocortical areas, musical pulse and tonality processing recruited cortical and subcortical cognitive, motor and emotion-related circuits. In sum, by combining neuroimaging, acoustic feature extraction and behavioral methods, we revealed the large-scale cognitive, motor and limbic brain circuitry dedicated to acoustic feature processing during listening to a naturalistic stimulus. In addition to these novel findings, our study has practical relevance as it provides a powerful means to localize neural processing of individual acoustical features, be it those of music, speech, or soundscapes, in ecological settings. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Crosstalk between endophytes and a plant host within information-processing networks

    Directory of Open Access Journals (Sweden)

    Kozyrovska N. O.

    2013-05-01

    Full Text Available Plants are heavily populated by pro- and eukaryotic microorganisms and represent therefore the tremendous complexity as a biological system. This system exists as an information-processing entity with rather complex processes of communication, occurring throughout the individual plant. The plant cellular information-proces- sing network constitutes the foundation for processes like growth, defense, and adaptation to the environment. Up to date, the molecular mechanisms, underlying perception, transfer, analysis, and storage of the endogenous and environmental information within the plant, remain to be fully understood. The associated microorganisms and their investment in the information conditioning are often ignored. Endophytes as plant partners are indispen- sable integrative part of the plant system. Diverse endophytic microorganisms comprise «normal» microbiota that plays a role in plant immunity and helps the plant system to survive in the environment (providing assistance in defense, nutrition, detoxification etc.. The role of endophytic microbiota in the processing of information may be presumed, taking into account a plant-microbial co-evolution and empirical data. Since the literature are be- ginning to emerge on this topic, in this article, I review key works in the field of plant-endophytes interactions in the context of information processing and represent the opinion on their putative role in plant information web under defense and the adaptation to changed conditions.

  12. Enabling model checking for collaborative process analysis: from BPMN to `Network of Timed Automata'

    Science.gov (United States)

    Mallek, Sihem; Daclin, Nicolas; Chapurlat, Vincent; Vallespir, Bruno

    2015-04-01

    Interoperability is a prerequisite for partners involved in performing collaboration. As a consequence, the lack of interoperability is now considered a major obstacle. The research work presented in this paper aims to develop an approach that allows specifying and verifying a set of interoperability requirements to be satisfied by each partner in the collaborative process prior to process implementation. To enable the verification of these interoperability requirements, it is necessary first and foremost to generate a model of the targeted collaborative process; for this research effort, the standardised language BPMN 2.0 is used. Afterwards, a verification technique must be introduced, and model checking is the preferred option herein. This paper focuses on application of the model checker UPPAAL in order to verify interoperability requirements for the given collaborative process model. At first, this step entails translating the collaborative process model from BPMN into a UPPAAL modelling language called 'Network of Timed Automata'. Second, it becomes necessary to formalise interoperability requirements into properties with the dedicated UPPAAL language, i.e. the temporal logic TCTL.

  13. An integrated knowledge-based framework for synthesis and design of enterprise-wide processing networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    Today chemical processing industries manufacture a wide range of products and provide services that touch billions of people’s lives across the globe in many different ways. Making this requires an effective management of innovation in product and process development. On the other hand, the synth......Today chemical processing industries manufacture a wide range of products and provide services that touch billions of people’s lives across the globe in many different ways. Making this requires an effective management of innovation in product and process development. On the other hand...... of production technology, its feasibility, sustainability, R&D needs, etc), all of which have a deep impact on the profitability of knowledge based industries. In this talk, an integrated business and engineering framework for synthesis and design of processing network within enterprise wide context...... is presented. A systematic approach is used to manage the complexity and solving simultaneously both the business and the engineering dimension of the problem. This allows generation and comparison of a large number of alternatives at their optimal point. The result is the identification of the optimal raw...

  14. Hydroformylation of 1-Hexene over Rh/Nano-Oxide Catalysts

    Directory of Open Access Journals (Sweden)

    Sari Suvanto

    2013-03-01

    Full Text Available The effect of nanostructured supports on the activity of Rh catalysts was studied by comparing the catalytic performance of nano- and bulk-oxide supported Rh/ZnO, Rh/SiO2 and Rh/TiO2 systems in 1-hexene hydroformylation. The highest activity with 100% total conversion and 96% yield of aldehydes was obtained with the Rh/nano-ZnO catalyst. The Rh/nano-ZnO catalyst was found to be more stable and active than the corresponding rhodium catalyst supported on bulk ZnO. The favorable morphology of Rh/nano-ZnO particles led to an increased metal content and an increased number of weak acid sites compared to the bulk ZnO supported catalysts. Both these factors favored the improved catalytic performance. Improvements of catalytic properties were obtained also with the nano-SiO2 and nano-TiO2 supports in comparison with the bulk supports. All of the catalysts were characterized by scanning electron microscope (SEM, inductively coupled plasma mass spectrometry (ICP-MS, BET, powder X-ray diffraction (PXRD and NH3- temperature-programmed desorption (TPD.

  15. Mechanism of NH4(+) Recruitment and NH3 Transport in Rh Proteins.

    Science.gov (United States)

    Baday, Sefer; Orabi, Esam A; Wang, Shihao; Lamoureux, Guillaume; Bernèche, Simon

    2015-08-04

    In human cells, membrane proteins of the rhesus (Rh) family excrete ammonium and play a role in pH regulation. Based on high-resolution structures, Rh proteins are generally understood to act as NH3 channels. Given that cell membranes are permeable to gases like NH3, the role of such proteins remains a paradox. Using molecular and quantum mechanical calculations, we show that a crystallographically identified site in the RhCG pore actually recruits NH4(+), which is found in higher concentration and binds with higher affinity than NH3, increasing the efficiency of the transport mechanism. A proton is transferred from NH4(+) to a signature histidine (the only moiety thermodynamically likely to accept a proton) followed by the diffusion of NH3 down the pore. The excess proton is circulated back to the extracellular vestibule through a hydrogen bond network, which involves a highly conserved and functionally important aspartic acid, resulting in the net transport of NH3. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. The Mechanisms of Interpersonal Privacy in Social Networking Websites: A Study of Subconscious Processes, Social Network Analysis, and Fear of Social Exclusion

    Science.gov (United States)

    Hammer, Bryan

    2013-01-01

    With increasing usage of social networking sites like Facebook there is a need to study privacy. Previous research has placed more emphasis on outcome-oriented contexts, such as e-commerce sites. In process-oriented contexts, like Facebook, privacy has become a source of conflict for users. The majority of architectural privacy (e.g. privacy…

  17. HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP) MODEL

    OpenAIRE

    Chun Meng Tang; Miang Hong Ngerng

    2015-01-01

    Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly co...

  18. Prioritizing of effective factors on development of medicinal plants cultivation using analytic network process

    Directory of Open Access Journals (Sweden)

    Ghorbanali Rassam

    2014-07-01

    Full Text Available For the overall development of medicinal plants cultivation in Iran, there is a need to identify various effective factors on medicinal plant cultivation. A proper method for identifying the most effective factor on the development of the medicinal plants cultivation is essential. This research conducted in order to prioritizing of the effective criteria for the development of medicinal plant cultivation in North Khorasan province in Iran using Analytical Network Process (ANP method. The multi-criteria decision making (MCDM is suggested to be a viable method for factor selection and the analytic network process (ANP has been used as a tool for MCDM. For this purpose a list of effective factors offered to expert group. Then pair wise comparison questionnaires were distributed between relevant researchers and local producer experts of province to get their opinions about the priority of criteria and sub- criteria. The questionnaires were analyzed using Super Decision software. We illustrated the use of the ANP by ranking main effective factors such as economic, educational-extension services, cultural-social and supportive policies on development of medicinal plants. The main objective of the present study was to develop ANP as a decision making tool for prioritizing factors affecting the development of medicinal plants cultivation. Results showed that the ANP methodology was perfectly suited to tackling the complex interrelations involved in selection factor in this case. Also the results of the process revealed that among the factors, supporting the cultivation of medicinal plants, build the infrastructure for marketing support, having educated farmer and easy access to production input have most impact on the development of medicinal plant cultivation.

  19. An optimal high contrast e-beam lithography process for the patterning of dense fin networks

    Energy Technology Data Exchange (ETDEWEB)

    Fruleux-Cornu, F. [Institut d' Electronique, de Microelectronique et de Nanotechnologie, CNRS UMR 8520, Avenue Poincare, BP 60069, 59652 Villeneuve d' Ascq cedex (France)]. E-mail: frederique.fruleux@isen.fr; Penaud, J. [Institut d' Electronique, de Microelectronique et de Nanotechnologie, CNRS UMR 8520, Avenue Poincare, BP 60069, 59652 Villeneuve d' Ascq cedex (France); Dubois, E. [Institut d' Electronique, de Microelectronique et de Nanotechnologie, CNRS UMR 8520, Avenue Poincare, BP 60069, 59652 Villeneuve d' Ascq cedex (France); Francois, M. [Institut d' Electronique, de Microelectronique et de Nanotechnologie, CNRS UMR 8520, Avenue Poincare, BP 60069, 59652 Villeneuve d' Ascq cedex (France); Muller, M. [Institut d' Electronique, de Microelectronique et de Nanotechnologie, CNRS UMR 8520, Avenue Poincare, BP 60069, 59652 Villeneuve d' Ascq cedex (France)

    2006-07-15

    There are many difficulties to overcome towards the integration of 10 nm CMOS technology. One such major challenge is to keep a tight control of the leakage current of devices while increasing the current drive at a reduced supply voltage. In this context, multi-gated structures, which are used to control the transport in ultra-thin channel (e.g. FinFET), are a promising solution. A critical step during the fabrication process of a FinFET is the patterning of dense, high aspect ratio fins. High demand is therefore placed on e-beam lithography techniques to obtain narrow, sharp, densely packed resist lines. This paper presents a detailed study on the optimum e-beam exposure process using a negative tone e-beam resist, namely Hydrogen Silsesquioxane (HSQ). The impact of the pre-exposure bake temperature, of the Tetramethyl Ammonium Hydroxide (TMAH) concentration in development solution and of development time has been investigated. The standard process uses 2.38% TMAH as a developer, samples being pre-baked on a hotplate at a temperature between 150 and 220 deg. C for 2 min. By using a lower pre-bake temperature of 90 deg. C and a more concentrated TMAH solution dosed at 25%, a seven-fold improvement of contrast can be obtained in terms of contrast values. Cross sectional SEM views show fin networks with a pitch ranging from 40 nm to 200 nm. The line profiles are steep and an excellent uniformity is obtained across the whole network, even for lines located at the edge. Dense patterns are presented with lines as narrow as 15 nm and with a 25 nm space.

  20. Dissimilatory nitrate reduction processes in sediments of urban river networks: Spatiotemporal variations and environmental implications.

    Science.gov (United States)

    Cheng, Lv; Li, Xiaofei; Lin, Xianbiao; Hou, Lijun; Liu, Min; Li, Ye; Liu, Sai; Hu, Xiaoting

    2016-12-01

    Urbanizations have increased the loadings of reactive nitrogen in urban riverine environments. However, limited information about dissimilatory nitrate reduction processes and associated contributions to nitrogen removal is available for urban riverine environments. In this study, sediment slurry experiments were conducted with nitrogen isotope-tracing technique to investigate the potential rates of denitrification, anaerobic ammonium oxidation (anammox) and dissimilatory nitrate reduction to ammonium (DNRA) and their contributions to nitrate reduction in sediments of urban river networks, Shanghai. The potential rates of denitrification, anammox and DNRA measured in the study area ranged from 0.193 to 98.7 nmol N g-1 h-1 dry weight (dw), 0.0387-23.7 nmol N g-1 h-1 dw and 0-10.3 nmol N g-1 h-1 dw, respectively. Denitrification and DNRA rates were higher in summer than in winter, while anammox rates were greater in winter than in summer for most sites. Dissolved oxygen, total organic carbon, nitrate, ammonium, sulfide, Fe(II) and Fe(III) were found to have significant influence on these nitrate reduction processes. Denitrification contributed 11.5-99.5%% to total nitrate reduction, as compared to 0.343-81.6% for anammox and 0-52.3% for DNRA. It is estimated that nitrogen loss of approximately 1.33 × 105 t N year-1 was linked to both denitrification and anammox processes, which accounted for about 20.1% of total inorganic nitrogen transported annually into the urban river networks of Shanghai. Overall, these results show the potential importance of denitrification and anammox in nitrogen removal and provide new insight into the mechanisms of nitrogen cycles in urban riverine environments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. The importance of establishing an international network of tissue banks and regional tissue processing centers.

    Science.gov (United States)

    Morales Pedraza, Jorge

    2014-03-01

    During the past four decades, many tissue banks have been established across the world with the aim of supplying sterilized tissues for clinical use and research purposes. Between 1972 and 2005, the International Atomic Energy Agency supported the establishment of more than sixty of these tissue banks in Latin America and the Caribbean, Asia and the Pacific, Africa and Eastern Europe; promoted the use of the ionizing radiation technique for the sterilization of the processed tissues; and encouraged cooperation between the established tissue banks during the implementation of its program on radiation and tissue banking at national, regional and international levels. Taking into account that several of the established tissue banks have gained a rich experience in the procurement, processing, sterilization, storage, and medical use of sterilized tissues, it is time now to strengthen further international and regional cooperation among interested tissue banks located in different countries. The purpose of this cooperation is to share the experience gained by these banks in the procurement, processing, sterilization, storage, and used of different types of tissues in certain medical treatments and research activities. This could be done through the establishment of a network of tissue banks and a limited number of regional tissue processing centers in different regions of the world.

  2. Intrinsic Default Mode Network Connectivity Predicts Spontaneous Verbal Descriptions of Autobiographical Memories during Social Processing.

    Science.gov (United States)

    Yang, Xiao-Fei; Bossmann, Julia; Schiffhauer, Birte; Jordan, Matthew; Immordino-Yang, Mary Helen

    2012-01-01

    Neural systems activated in a coordinated way during rest, known as the default mode network (DMN), also support autobiographical memory (AM) retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity). Here we examined 18 participants' spontaneous descriptions of autobiographical memories during a 2 h, private, open-ended interview in which they reacted to a series of true stories about real people's social situations and responded to the prompt, "how does this person's story make you feel?" We classified these descriptions as either containing factual information ("semantic" AMs) or more elaborate descriptions of emotionally meaningful events ("episodic" AMs). We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants' intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  3. MODELING AND MATHEMATICAL PROCESSING OF GEODETIC LEVELING NETWORK WHILE MONITORING SETTLEMENT OF UNIQUE ENGINEERING STRUCTURES

    Directory of Open Access Journals (Sweden)

    D. V. Usov

    2009-01-01

    Full Text Available The paper shows that reliability and trust of geodetic structure monitoring are related with new principles of leveling network construction, their testing and mathematical processing. Two indices, point density and errors in their altitude location, have been considered recently as the main characteristics of geodetic construction quality used for geodetic monitoring of  engineering object settlements.As it is an evitable distortion of the measuring data in the process of its accumulation and processing due to influence of additional factors (rough and systematic measurement errors, original data errors and so on, nowadays while evaluating the quality of geodetic constructions one more important characteristic is to be taken into account that is reliability of the geodetic construction.The majority of standard geodetic construction schemes do not have a sufficient reliability rate for definitive determination of construction settlements in any measuring cycle. Due to this very reason a problem concerning higher reliability of geodetic constructions and efficiency of their mathematical processing and, in consequence, provision of more accurate determination of engineering object settlements is considered as an actual one and it finds its solution in the paper.

  4. Creative thinking as orchestrated by semantic processing versus cognitive control brain networks

    Directory of Open Access Journals (Sweden)

    Anna eAbraham

    2014-02-01

    Full Text Available Creativity is primarily investigated within the neuroscientific perspective as a unitary construct. While such an approach is beneficial when trying to infer the general picture regarding creativity and brain function, it is insufficient if the objective is to uncover the information processing brain mechanisms by which creativity occurs. As creative thinking emerges through the dynamic interplay between several cognitive processes, assessing the neural correlates of these operations would enable the development and characterization of an information processing framework from which to better understand this complex ability. This article focuses on two aspects of creative cognition that are central to generating original ideas. Conceptual expansion refers to the ability to widen one’s conceptual structures to include unusual or novel associations, while overcoming knowledge constraints refers to our ability to override the constraining influence imposed by salient or pertinent knowledge when trying to be creative. Neuroimaging and neuropsychological evidence is presented to illustrate how semantic processing and cognitive control networks in the brain differentially modulate these critical facets of creative cognition.

  5. Genetic Distance and Genetic Identity between Hindu and Muslim populations of Barak Valley for ABO and Rh genes

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-09-01

    Full Text Available A genetic study was carried out in two endogamous populations namely Hindus and Muslims in the Barak Valley Zone of Assam in India. Nei�s genetic distance and genetic identity between two populations were calculated on the basis of estimated allele frequencies of ABO and Rh blood group genes. The genetic distance between Hindus and Muslims was 0.12% for ABO gene and 0.10% for Rh gene. The genetic identity between two populations was estimated as 99.88% for ABO gene and 99.90% for Rh gene suggesting very high genetic similarity between these two populations. Observed heterozygosity estimate was higher in Hindus (0.5598 for ABO gene and 0.2822 for Rh gene than Muslims (0.5346 for ABO gene and 0.2408 for Rh gene indicating lesser inbreeding in Hindus than Muslims. Fixation index was lower in Hindus (16.02% for ABO gene and 43.56% for Rh gene than Muslims (19.80% for ABO gene and 51.84% for Rh gene. Panmictic index was higher in Hindus than Muslims for both the genes. Fixation and panmictic indices revealed that during evolutionary process the Hindus maintained more outbreeding feature than the Muslims in the valley. In this study, the concepts of genetic load of a population and genotype fitness were extended to alleles to estimate the magnitude of allele genetic load (GL and allele fitness for 3 alleles in ABO gene and for 2 alleles in Rh gene in two populations. The genetic load for O, A and B alleles were lower in Hindus than Muslims. Similar results for genetic load were found for the alleles of Rh gene in the comparison of two populations. The fitness estimates of O, A and B alleles for ABO gene and D and d alleles for Rh gene were higher in Hindus than Muslims. A population with low allele genetic load (GL and high allele fitness (AF might have greater survival advantage in nature in the absence of heterozygote advantage and higher adaptive value of the allele with increased frequency.

  6. Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird–plant network

    Science.gov (United States)

    Vizentin-Bugoni, Jeferson; Maruyama, Pietro Kiyoshi; Sazima, Marlies

    2014-01-01

    Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird–plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought. PMID:24552835

  7. Water Relationships in the U.S. Southwest: Characterizing Water Management Networks Using Natural Language Processing

    Directory of Open Access Journals (Sweden)

    John T. Murphy

    2014-06-01

    Full Text Available Natural language processing (NLP and named entity recognition (NER techniques are applied to collections of newspaper articles from four cities in the U.S. Southwest. The results are used to generate a network of water management institutions that reflect public perceptions of water management and the structure of water management in these areas. This structure can be highly centralized or fragmented; in the latter case, multiple peer institutions exist that may cooperate or be in conflict. This is reflected in the public discourse of the water consumers in these areas and can, we contend, impact the potential responses of management agencies to challenges of water supply and quality and, in some cases, limit their effectiveness. Flagstaff, AZ, Tucson, AZ, Las Vegas, NV, and the Grand Valley, CO, are examined, including more than 110,000 articles from 2004–2012. Documents are scored by association with water topics, and phrases likely to be institutions are extracted via custom NLP and NER algorithms; those institutions associated with water-related documents are used to form networks via document co-location. The Grand Valley is shown to have a markedly different structure, which we contend reflects the different historical trajectory of its development and its current state, which includes multiple institutions of roughly equal scope and size. These results demonstrate the utility of using NLP and NER methods to understanding the structure and variation of water management systems.

  8. Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

    Science.gov (United States)

    Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

    2012-01-01

    In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

  9. An Intrinsic Encoding of a Subset of C and its Application to TLS Network Packet Processing

    Directory of Open Access Journals (Sweden)

    Reynald Affeldt

    2014-09-01

    Full Text Available TLS is such a widespread security protocol that errors in its implementation can have disastrous consequences. This responsibility is mostly borne by programmers, caught between specifications with the ambiguities of natural language and error-prone low-level parsing of network packets. We report here on the construction in the Coq proof-assistant of libraries to model, specify, and verify C programs to process TLS packets. We provide in particular an encoding of the core subset of C whose originality lies in its use of dependent types to guarantee statically well-formedness of datatypes and correct typing. We further equip this encoding with a Separation logic that enables byte-level reasoning and also provide a logical view of data structures. We also formalize a significant part of the RFC for TLS, again using dependent types to capture succinctly constraints that are left implicit in the prose document. Finally, we apply the above framework to an existing implementation of TLS (namely, PolarSSL of which we specify and verify a parsing function for network packets. Thanks to this experiment, we were able to spot ambiguities in the RFC and to correct bugs in the C source code.

  10. Measuring microscopic evolution processes of complex networks based on empirical data

    Science.gov (United States)

    Chi, Liping

    2015-04-01

    Aiming at understanding the microscopic mechanism of complex systems in real world, we perform the measurement that characterizes the evolution properties on two empirical data sets. In the Autonomous Systems Internet data, the network size keeps growing although the system suffers a high rate of node deletion (r = 0.4) and link deletion (q = 0.81). However, the average degree keeps almost unchanged during the whole time range. At each time step the external links attached to a new node are about c = 1.1 and the internal links added between existing nodes are approximately m = 8. For the Scientific Collaboration data, it is a cumulated result of all the authors from 1893 up to the considered year. There is no deletion of nodes and links, r = q = 0. The external and internal links at each time step are c = 1.04 and m = 0, correspondingly. The exponents of degree distribution p(k) ∼ k-γ of these two empirical datasets γdata are in good agreement with that obtained theoretically γtheory. The results indicate that these evolution quantities may provide an insight into capturing the microscopic dynamical processes that govern the network topology.

  11. Experimental and Computational Studies of Cortical Neural Network Properties Through Signal Processing

    Science.gov (United States)

    Clawson, Wesley Patrick

    Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized using mutual information between sensory input, visual stimulus, and neural response,. The primary finding of our experiments in the visual cortex in turtles and neuronal network modeling confirms this theoretical prediction. We show that sensory discrimination is maximized when visual cortex operates near criticality. In addition to presenting this primary finding in detail, this thesis will also address our preliminary results on change-point-detection in experimentally measured cortical dynamics.

  12. Changing Seasonality in the Arctic and its Influences on Biogeochemical Processing in Tundra River Networks

    Science.gov (United States)

    Bowden, W. B.; Gooseff, M. N.; Wollheim, W. M.; Herstand, M. R.; Treat, C. C.; Whittinghill, K. A.; Wlostowski, A. N.

    2011-12-01

    One of the primary expressions of climate change in the arctic is a change in "seasonality"; i.e., changes in the timing, duration, and characteristics of the traditional arctic seasons. These changes are most likely to affect temperature and precipitation patterns but will have relatively little effect on the annual light regime. Temperature, precipitation, and light are crucial drivers in any ecosystem and so the potential that the relationships between these three master environmental variables will change in the future has important consequences. Our research addresses how river networks process critical nutrients (C, N, and P) delivered from land as they are transported to coastal zones. We are currently focusing on land-water interactions in headwater streams. As in any ecosystem, temperature strongly influences microbial processing in soils and thus net mineralization of organic nutrients. Nutrients made available by microbial processing in the soil will be used by vegetation as long as the vegetation actively grows. However, active growth by vegetation is highly dependent on the annual light regime, which is not changing substantially. Thus, as arctic seasonality changes there is a growing asynchrony developing between production of nutrients by soil microbes and the demand for nutrients by vegetation, with greater production of nutrients by temperature-dependent microbes than demand by light-dependent vegetation. It is reasonable to expect that the "excess" nutrients produced in this way will migrate to streams and we hypothesize that this seasonal subsidy may strongly influence the structure and function of arctic stream ecosystems. Previous stream research in the arctic largely ignored the spring and fall tail seasons. Preliminary findings indicate that the seasonal asynchrony has profound influences on nutrient concentrations and autotrophic biomass in arctic streams. We expect this to have important influences on key processes such as primary

  13. RhD Specific Antibodies Are Not Detectable in HLA-DRB11501* Mice Challenged with Human RhD Positive Erythrocytes

    Directory of Open Access Journals (Sweden)

    Lidice Bernardo

    2014-01-01

    Full Text Available The ability to study the immune response to the RhD antigen in the prevention of hemolytic disease of the fetus and newborn has been hampered by the lack of a mouse model of RhD immunization. However, the ability of transgenic mice expressing human HLA DRB11501* to respond to immunization with purified RhD has allowed this question to be revisited. In this work we aimed at inducing anti-RhD antibodies by administering human RhD+ RBCs to mice transgenic for the human HLA DRB11501* as well as to several standard inbred and outbred laboratory strains including C57BL/6, DBA1/J, CFW(SW, CD1(ICR, and NSA(CF-1. DRB11501* mice were additionally immunized with putative extracellular immunogenic RhD peptides. DRB11501* mice immunized with RhD+ erythrocytes developed an erythrocyte-reactive antibody response. Antibodies specific for RhD could not however be detected by flow cytometry. Despite this, DRB11501* mice were capable of recognizing immunogenic sequences of Rh as injection with Rh peptides induced antibodies reactive with RhD sequences, consistent with the presence of B cell repertoires capable of recognizing RhD. We conclude that while HLA DRB11501* transgenic mice may have the capability of responding to immunogenic sequences within RhD, an immune response to human RBC expressing RhD is not directly observed.

  14. Processing of odor stimuli by neuronal network models of the olfactory bulb

    Science.gov (United States)

    Wick, Stuart; Wiechert, Martin; Riecke, Hermann; Friedrich, Rainer

    2007-03-01

    The space of perceptable odors is high-dimensional and its representation in the various brain structures is still poorly understood. We focus on the olfactory bulb, which constitutes the first processing stage for odor stimuli after they have been sensed by receptor neurons. Experimentally it is found that the correlations between the outputs of the bulb are significantly reduced relative to those of the corresponding inputs, thus enhancing the discriminability of similar odors. We have generated a firing-rate-based network model with parameters derived from experimental data that reproduces decorrelation. Here we use this model to investigate the dependence of stimulus representations on odor concentration. We address the possibility of a change in perceived odor identity with changing concentration and the dependence of odor discriminability on odor concentration. We interpret some of our results within a simple mean-field model for the neural activity.

  15. Nature as a network of morphological infocomputational processes for cognitive agents

    Science.gov (United States)

    Dodig-Crnkovic, Gordana

    2017-01-01

    This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted.

  16. [The interaction between nerve cells and carbon nanotube networks made by CVD process investigation].

    Science.gov (United States)

    Bobrinetskiĭ, I I; Seleznev, A S; Gaĭduchenko, I A; Fedorov, G E; Domantovskiĭ, A G; Presniakov, M Iu; Podcherniaeva, R Ia; Mikhaĭlova, G R; Suetina, I A

    2013-01-01

    In this research we investigate neuroblastoma cells cultivated on single-walled carbon nanotubes networks made by CVD method on silicon substrates. The complex analysis of grown cells made by atomic force, electron microscopy and Raman spectroscopy was carried out and the effect of nanotube growth process on proliferation factor was investigated. It is shown that despite of a weak decrease in proliferation, cell morphology remains unchanged and no physical or chemical interaction between carbon nanotubes and cells is observed. The results of the research can be used to investigate the interaction between conductive nanomaterials and cells for the development of neural replacement implants. Also they can be useful in bio-electronic interface investigation of signal propagation in neurons.

  17. Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

    Energy Technology Data Exchange (ETDEWEB)

    Yildiz, Sayiter [Engineering Faculty, Cumhuriyet University, Sivas (Turkmenistan)

    2017-09-15

    Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R{sup 2} value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R{sup 2} values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

  18. Forbidden versus permitted interactions: Disentangling processes from patterns in ecological network analysis.

    Science.gov (United States)

    Strona, Giovanni; Veech, Joseph A

    2017-07-01

    Several studies have identified the tendency for species to share interacting partners as a key property to the functioning and stability of ecological networks. However, assessing this pattern has proved challenging in several regards, such as finding proper metrics to assess node overlap (sharing), and using robust null modeling to disentangle significance from randomness. Here, we bring attention to an additional, largely neglected challenge in assessing species' tendency to share interacting partners. In particular, we discuss and illustrate with two different case studies how identifying the set of "permitted" interactions for a given species (i.e. interactions that are not impeded, e.g. by lack of functional trait compatibility) is paramount to understand the ecological and co-evolutionary processes at the basis of node overlap and segregation patterns.

  19. Analytic network process model for sustainable lean and green manufacturing performance indicator

    Science.gov (United States)

    Aminuddin, Adam Shariff Adli; Nawawi, Mohd Kamal Mohd; Mohamed, Nik Mohd Zuki Nik

    2014-09-01

    Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

  20. Comparison of the Helicobacter Pylori Diagnosis Methods with Analytic Network Process

    Directory of Open Access Journals (Sweden)

    Hacer KONAKLI

    2015-11-01

    Full Text Available Helicobacter pylori is infecting %70-80 of the world’s population and is assumed to cause gastric diseases. Diagnosis of the bacteria is crucial for the treatment of the bacteria related infections. Histology, culture, urea breath test, stool antigen test some of the diagnosis methods each having specific strength and weaknesses as sensitivity, specificity, cost, easiness, time, effectiveness in the treatment and laboratory requirements. In this study, three of the commonly used H. pylori diagnosis methods: histology, culture and urea breath test, are evaluated with Analytic network process (ANP and the rank of the criteria and alternatives are obtained. The evaluation of the methods and the rank of the diagnosis methods can reduce time, cost, and validity of the test results.