WorldWideScience

Sample records for networked rh processing

  1. Reconfigurable network processing platforms

    NARCIS (Netherlands)

    Kachris, C.

    2007-01-01

    This dissertation presents our investigation on how to efficiently exploit reconfigurable hardware to design flexible, high performance, and power efficient network devices capable to adapt to varying processing requirements of network applications and traffic. The proposed reconfigurable network

  2. Structure and catalytic processes of N-containing species on Rh(111) from first principles

    NARCIS (Netherlands)

    Ricart, J.M.; Ample, F.; Clotet, A.; Curulla Ferre, D.; Niemantsverdriet, J.W.; Paul, J.F.; Perez-Ramirez, J.

    2005-01-01

    Density functional theory has been used to gain molecular understanding of various catalytic processes involving N species on Rh(111). These include CN, N2, and HCN formation and N2O decomposition. Our calculations substantiate the conclusion that, starting from chemisorbed C and N atomic species,

  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

    International Nuclear Information System (INIS)

    Dias, Ricardo Rodrigues

    2009-01-01

    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 2 PtCl 6 .6H 2 O (Aldrich), SnCl 2 .2H 2 O (Aldrich),and RhCl 2 .XH 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 2θ = 40 0 , 47 0 , 67 0 and 82 0 , 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 PtSn/C and PtSnRh/C two additional peaks were observed at 2θ = 34 0 and 52 0 that were identified as a SnO 2 phase. PtSn/C (50:50) and PtSnRh/C (50:40:10) electrocatalyst showed the best performance for ethanol oxidation at room temperature. For methanol oxidation at room temperature PtRu/C, PtSn/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. Rh Incompatibility

    Science.gov (United States)

    ... type is called Rh. Rh factor is a protein on red blood cells. Most people are Rh-positive; they have Rh factor. Rh-negative people don't have it. Rh factor is inherited though genes. When you're pregnant, blood from your baby can cross into your ...

  5. Networked business process management

    NARCIS (Netherlands)

    Grefen, P.W.P.J.

    2013-01-01

    In the current economy, a shift can be seen from stand-alone business organizations to networks of tightly collaborating business organizations. To allow this tight collaboration, business process management in these collaborative networks is becoming increasingly important. This paper discusses

  6. 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)

  7. 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 2θ = 40{sup 0}, 47{sup 0}, 67{sup 0} and 82{sup 0}, 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 PtSn/C and PtSnRh/C two additional peaks were observed at 2θ = 34{sup 0} and 52{sup 0} that were identified as a SnO{sub 2} phase. PtSn/C (50:50) and PtSnRh/C (50:40:10) electrocatalyst showed the best performance for ethanol oxidation at room temperature. For methanol oxidation at room temperature PtRu/C, PtSn/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)

  8. Profiling and functional data on the developing olfactory/GnRH system reveal cellular and molecular pathways essential for this process and potentially relevant for the Kallmann syndrome

    Directory of Open Access Journals (Sweden)

    Giulia eGaraffo

    2013-12-01

    Full Text Available During embryonic development, immature neurons in the olfactory epithelium (OE extend axons through the nasal mesenchyme, to contact projection neurons in the olfactory bulb. Axon navigation is accompanied by migration of the GnRH+ neurons, which enter the anterior forebrain and home in the septo-hypothalamic area. This process can be interrupted at various points and lead to the onset of the Kallmann syndrome (KS, a disorder characterized by anosmia and central hypogonadotropic hypogonadism. Several genes has been identified in human and mice that cause KS or a KS-like phenotype. In mice a set of transcription factors appears to be required for olfactory connectivity and GnRH neuron migration; thus we explored the transcriptional network underlying this developmental process by profiling the OE and the adjacent mesenchyme at three embryonic ages. We also profiled the OE from embryos null for Dlx5, a homeogene that causes a KS-like phenotype when deleted. We identified 20 interesting genes belonging to the following categories: 1 transmembrane adhesion/receptor, 2 axon-glia interaction, 3 scaffold/adapter for signalling, 4 synaptic proteins. We tested some of them in zebrafish embryos: the depletion of five (of six Dlx5 targets affected axonal extension and targeting, while three (of three affected GnRH neuron position and neurite organization. Thus, we confirmed the importance of cell-cell and cell-matrix interactions and identified new molecules needed for olfactory connection and GnRH neuron migration. Using available and newly generated data, we predicted/prioritized putative KS-disease genes, by building conserved co-expression networks with all known disease genes in human and mouse. The results show the overall validity of approaches based on high-throughput data and predictive bioinformatics to identify genes potentially relevant for the molecular pathogenesis of KS. A number of candidate will be discussed, that should be tested in

  9. 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)

  10. Status of microwave process development for RH-TRU [remote-handled transuranic] wastes at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    White, T.L.; Youngblood, E.L.; Berry, J.B.; Mattus, A.J.

    1990-01-01

    The Oak Ridge National Laboratory (ORNL) Waste Handling and Packaging Plant is developing a microwave process to reduce and solidify remote-handled transuranic (RH-TRU) liquids and sludges presently stored in large tanks at ORNL. Testing has recently begun on an in-drum microwave process using nonradioactive RH-TRU surrogates. The microwave process development effort has focused on an in-drum process to dry the RH-TRU liquids and sludges in the final storage container and then melt the salt residues to form a solid monolith. A 1/3-scale proprietary microwave applicator was designed, fabricated, and tested to demonstrate the essential features of the microwave design and to provide input into the design of the full-scale applicator. The microwave fields are uniform in one dimension to reduce the formation of hot spots on the microwaved wasteform. The final wasteform meets the waste acceptance criteria for the Waste Isolation Pilot Plant, a federal repository for defense transuranic wastes near Carlsbad, New Mexico. 7 refs., 1 fig., 1 tab

  11. 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.

  12. Modeling study on the flow patterns of gas-liquid flow for fast decarburization during the RH process

    Science.gov (United States)

    Li, Yi-hong; Bao, Yan-ping; Wang, Rui; Ma, Li-feng; Liu, Jian-sheng

    2018-02-01

    A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber: boiling pattern (BP), transition pattern (TP), and wave pattern (WP). The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.

  13. Transuranic Waste Processing Center (TWPC) Legacy Tank RH-TRU Sludge Processing and Compliance Strategy - 13255

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, Ben C.; Heacker, Fred K.; Shannon, Christopher [Wastren Advantage, Inc., Transuranic Waste Processing Center, 100 WIPP Road, Lenoir City, Tennessee 37771 (United States); and others

    2013-07-01

    The U.S. Department of Energy (DOE) needs to safely and efficiently treat its 'legacy' transuranic (TRU) waste and mixed low-level waste (LLW) from past research and defense activities at the Oak Ridge National Laboratory (ORNL) so that the waste is prepared for safe and secure disposal. The TWPC operates an Environmental Management (EM) waste processing facility on the Oak Ridge Reservation (ORR). The TWPC is classified as a Hazard Category 2, non-reactor nuclear facility. This facility receives, treats, and packages low-level waste and TRU waste stored at various facilities on the ORR for eventual off-site disposal at various DOE sites and commercial facilities. The Remote Handled TRU Waste Sludge held in the Melton Valley Storage Tanks (MVSTs) was produced as a result of the collection, treatment, and storage of liquid radioactive waste originating from the ORNL radiochemical processing and radioisotope production programs. The MVSTs contain most of the associated waste from the Gunite and Associated Tanks (GAAT) in the ORNL's Tank Farms in Bethel Valley and the sludge (SL) and associated waste from the Old Hydro-fracture Facility tanks and other Federal Facility Agreement (FFA) tanks. The SL Processing Facility Build-outs (SL-PFB) Project is integral to the EM cleanup mission at ORNL and is being accelerated by DOE to meet updated regulatory commitments in the Site Treatment Plan. To meet these commitments a Baseline (BL) Change Proposal (BCP) is being submitted to provide continued spending authority as the project re-initiation extends across fiscal year 2012 (FY2012) into fiscal year 2013. Future waste from the ORNL Building 3019 U-233 Disposition project, in the form of U-233 dissolved in nitric acid and water, down-blended with depleted uranyl nitrate solution is also expected to be transferred to the 7856 MVST Annex Facility (formally the Capacity Increase Project (CIP) Tanks) for co-processing with the SL. The SL-PFB project will construct

  14. Transuranic Waste Processing Center (TWPC) Legacy Tank RH-TRU Sludge Processing and Compliance Strategy - 13255

    International Nuclear Information System (INIS)

    Rogers, Ben C.; Heacker, Fred K.; Shannon, Christopher

    2013-01-01

    The U.S. Department of Energy (DOE) needs to safely and efficiently treat its 'legacy' transuranic (TRU) waste and mixed low-level waste (LLW) from past research and defense activities at the Oak Ridge National Laboratory (ORNL) so that the waste is prepared for safe and secure disposal. The TWPC operates an Environmental Management (EM) waste processing facility on the Oak Ridge Reservation (ORR). The TWPC is classified as a Hazard Category 2, non-reactor nuclear facility. This facility receives, treats, and packages low-level waste and TRU waste stored at various facilities on the ORR for eventual off-site disposal at various DOE sites and commercial facilities. The Remote Handled TRU Waste Sludge held in the Melton Valley Storage Tanks (MVSTs) was produced as a result of the collection, treatment, and storage of liquid radioactive waste originating from the ORNL radiochemical processing and radioisotope production programs. The MVSTs contain most of the associated waste from the Gunite and Associated Tanks (GAAT) in the ORNL's Tank Farms in Bethel Valley and the sludge (SL) and associated waste from the Old Hydro-fracture Facility tanks and other Federal Facility Agreement (FFA) tanks. The SL Processing Facility Build-outs (SL-PFB) Project is integral to the EM cleanup mission at ORNL and is being accelerated by DOE to meet updated regulatory commitments in the Site Treatment Plan. To meet these commitments a Baseline (BL) Change Proposal (BCP) is being submitted to provide continued spending authority as the project re-initiation extends across fiscal year 2012 (FY2012) into fiscal year 2013. Future waste from the ORNL Building 3019 U-233 Disposition project, in the form of U-233 dissolved in nitric acid and water, down-blended with depleted uranyl nitrate solution is also expected to be transferred to the 7856 MVST Annex Facility (formally the Capacity Increase Project (CIP) Tanks) for co-processing with the SL. The SL-PFB project will construct and install

  15. 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.

  16. 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: Polymer science Impact factor: 6.459, year: 2016

  17. 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.

  18. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  19. Analysis of decarburization in RH process of vacuum degasification; Analise da descarburacao do aco no processo rh de desgaseificacao a vacuo

    Energy Technology Data Exchange (ETDEWEB)

    Souza Costa, Sergio L. de; Oliveira Barros, Hudson N. de; Almeida, Claudio X [USIMINAS, Ipatinga, MG (Brazil). Centro de Pesquisas

    1990-12-31

    USIMINAS has made significant progress in the development of technology to produce ultra low carbon steels using the RH vacuum degassing unit in its number 1 BOF Shop. The decarburization rate is controlled by the circulation rate of liquid steel. On substituting conventional legs with oval shaped legs the circulation rate increased from 40 t/min to 80 t/min with a consequent increase in the global decarburization constant from 0.13 min{sup -1} to 0.28 min{sup -1}. With those practice it has been possible to achieve carbon levels as low as 45 ppm in ten minutes. (author). 5 refs., 8 figs., 2 tabs.

  20. Epidemic processes in complex networks

    OpenAIRE

    Pastor Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

    2015-01-01

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The t...

  1. Epidemic processes in complex networks

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

    2015-07-01

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

  2. AtRH57, a DEAD-box RNA helicase, is involved in feedback inhibition of glucose-mediated abscisic acid accumulation during seedling development and additively affects pre-ribosomal RNA processing with high glucose.

    Science.gov (United States)

    Hsu, Yi-Feng; Chen, Yun-Chu; Hsiao, Yu-Chun; Wang, Bing-Jyun; Lin, Shih-Yun; Cheng, Wan-Hsing; Jauh, Guang-Yuh; Harada, John J; Wang, Co-Shine

    2014-01-01

    The Arabidopsis thaliana T-DNA insertion mutant rh57-1 exhibited hypersensitivity to glucose (Glc) and abscisic acid (ABA). The other two rh57 mutants also showed Glc hypersensitivity similar to rh57-1, strongly suggesting that the Glc-hypersensitive feature of these mutants results from mutation of AtRH57. rh57-1 and rh57-3 displayed severely impaired seedling growth when grown in Glc concentrations higher than 3%. The gene, AtRH57 (At3g09720), was expressed in all Arabidopsis organs and its transcript was significantly induced by ABA, high Glc and salt. The new AtRH57 belongs to class II DEAD-box RNA helicase gene family. Transient expression of AtRH57-EGFP (enhanced green fluorescent protein) in onion cells indicated that AtRH57 was localized in the nucleus and nucleolus. Purified AtRH57-His protein was shown to unwind double-stranded RNA independent of ATP in vitro. The ABA biosynthesis inhibitor fluridone profoundly redeemed seedling growth arrest mediated by sugar. rh57-1 showed increased ABA levels when exposed to high Glc. Quantitative real time polymerase chain reaction analysis showed that AtRH57 acts in a signaling network downstream of HXK1. A feedback inhibition of ABA accumulation mediated by AtRH57 exists within the sugar-mediated ABA signaling. AtRH57 mutation and high Glc conditions additively caused a severe defect in small ribosomal subunit formation. The accumulation of abnormal pre-rRNA and resistance to protein synthesis-related antibiotics were observed in rh57 mutants and in the wild-type Col-0 under high Glc conditions. These results suggested that AtRH57 plays an important role in rRNA biogenesis in Arabidopsis and participates in response to sugar involving Glc- and ABA signaling during germination and seedling growth. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

  3. Rh Incompatibility (For Parents)

    Science.gov (United States)

    ... work to destroy, foreign substances) against the Rh proteins. Other ways Rh-negative pregnant women can be exposed to the Rh protein that might cause antibody production include blood transfusions ...

  4. Cooperative spreading processes in multiplex networks.

    Science.gov (United States)

    Wei, Xiang; Chen, Shihua; Wu, Xiaoqun; Ning, Di; Lu, Jun-An

    2016-06-01

    This study is concerned with the dynamic behaviors of epidemic spreading in multiplex networks. A model composed of two interacting complex networks is proposed to describe cooperative spreading processes, wherein the virus spreading in one layer can penetrate into the other to promote the spreading process. The global epidemic threshold of the model is smaller than the epidemic thresholds of the corresponding isolated networks. Thus, global epidemic onset arises in the interacting networks even though an epidemic onset does not arise in each isolated network. Simulations verify the analysis results and indicate that cooperative spreading processes in multiplex networks enhance the final infection fraction.

  5. 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.

  6. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  7. A Process Management System for Networked Manufacturing

    Science.gov (United States)

    Liu, Tingting; Wang, Huifen; Liu, Linyan

    With the development of computer, communication and network, networked manufacturing has become one of the main manufacturing paradigms in the 21st century. Under the networked manufacturing environment, there exist a large number of cooperative tasks susceptible to alterations, conflicts caused by resources and problems of cost and quality. This increases the complexity of administration. Process management is a technology used to design, enact, control, and analyze networked manufacturing processes. It supports efficient execution, effective management, conflict resolution, cost containment and quality control. In this paper we propose an integrated process management system for networked manufacturing. Requirements of process management are analyzed and architecture of the system is presented. And a process model considering process cost and quality is developed. Finally a case study is provided to explain how the system runs efficiently.

  8. Social Network Supported Process Recommender System

    Directory of Open Access Journals (Sweden)

    Yanming Ye

    2014-01-01

    Full Text Available 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.

  9. 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.

  10. A comparative DFT study on the dehydrogenation of methanol on Rh(100) and Rh(110)

    Science.gov (United States)

    Zhang, Minhua; Wu, Xingyu; Yu, Yingzhe

    2018-04-01

    Numerous density functional theory calculations have been performed to investigate the complete mechanisms of methanol dehydrogenation on Rh(100) and Rh(110) surfaces. The adsorption properties of relevant species were discussed in details. In addition, a comprehensive reaction network including four reaction pathways was built and analyzed. It is found that the initial Osbnd H bond scission of CH3OH seems to be more favorable than Csbnd H bond cleavage on both Rh(100) and Rh(110) surfaces from the perspective of activation barriers. It is also concluded that path1 (CH3OH → CH3O → CH2O → CHO → CO) is the predominant pathway on both Rh(100) and Rh (110) surfaces. On the whole, in most of the dehydrogenation reactions investigated, the energy barriers on Rh(100) are lower than those on Rh (110). Remarkable differences in the activity and predominant reaction pathway on Rh(100), Rh(110) and Rh(111) indicate that the dehydrogenation of methanol might be structure-sensitive.

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

    DEFF Research Database (Denmark)

    Petersen, Rasmus Rosenqvist

    important challenge for criminal network investigation, despite the massive attention it receives from research and media. Challenges such as the investigation process, the context of the investigation, human factors such as thinking and creativity, and political decisions and legal laws are all challenges...... that could mean the success or failure of criminal network investigations. % include commission reports as indications of process related problems .. to "play a little politics" !! Information, process, and human factors, are challenges we find to be addressable by software system support. Based on those......Criminal network investigations such as police investigations, intelligence analysis, and investigative journalism involve a range of complex knowledge management processes and tasks. Criminal network investigators collect, process, and analyze information related to a specific target to create...

  12. Environmental application of millimetre-scale sponge iron (s-Fe"0) particles (IV): New insights into visible light photo-Fenton-like process with optimum dosage of H_2O_2 and RhB photosensitizers

    International Nuclear Information System (INIS)

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

    2017-01-01

    Highlights: • Synergistic action of Rhodamine B (RhB), visible light, H_2O_2 and s-Fe"0 is essential. • The complexes of RhB and Fe"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"0), H_2O_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"0, (2) the photo-Fenton-like removal of RhB over iron oxides generated from the corrosion of s-Fe"0, (3) the homogeneous photo-Fenton removal of RhB over Fe"2"+ or Fe"3"+, (4) the Fe"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"0 nor the photo-Fenton-like process over FeOOH, Fe_3O_4 and Fe_2O_3, achieved efficient removal of RhB. For comparison, in homogeneous photo-Fenton process, the presence of Fe"3"+ ions, rather than Fe"2"+ ions, effectively eliminated RhB. Furthermore, the UV–vis spectra showing new absorbance at ∼ 285 nm indicate the complexes of RhB and Fe"3"+ ions, adopting vis photons to form excited state and further eject one electron via ligand-to-metal charge-transfer to activate H_2O_2. Additionally, efficient TBBPA removal was obtained only in the presence of RhB. Accordingly, the s-Fe"0– based photo-Fenton-like process assisted with dyestuff wastewater is promising for removing a series of persistent organic pollutants.

  13. Mapping stochastic processes onto complex networks

    International Nuclear Information System (INIS)

    Shirazi, A H; Reza Jafari, G; Davoudi, J; Peinke, J; Reza Rahimi Tabar, M; Sahimi, Muhammad

    2009-01-01

    We introduce a method by which stochastic processes are mapped onto complex networks. As examples, we construct the networks for such time series as those for free-jet and low-temperature helium turbulence, the German stock market index (the DAX), and white noise. The networks are further studied by contrasting their geometrical properties, such as the mean length, diameter, clustering, and average number of connections per node. By comparing the network properties of the original time series investigated with those for the shuffled and surrogate series, we are able to quantify the effect of the long-range correlations and the fatness of the probability distribution functions of the series on the networks constructed. Most importantly, we demonstrate that the time series can be reconstructed with high precision by means of a simple random walk on their corresponding networks

  14. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    Software process improvement in small, agile organizations is often problematic. Model-based approaches seem to overlook problems. We have been seeking an alternative approach to overcome this through action research. Here we report on a piece of action research from which we developed an approach...... 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...... software process improvement....

  15. Image processing with a cellular nonlinear network

    International Nuclear Information System (INIS)

    Morfu, S.

    2005-01-01

    A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

  16. Reprocessing process simulation network; PRONET

    International Nuclear Information System (INIS)

    Mitsui, T.; Takada, H.; Kamishima, N.; Tsukamoto, T.; Harada, N.; Fujita, N.; Gonda, K.

    1991-01-01

    The effectiveness of simulation technology and its wide application to nuclear fuel reprocessing plants has been recognized recently. The principal aim of applying simulation is to predict the process behavior accurately based on the quantitative relations among substances in physical and chemical phenomena. Mitsubishi Heavy Industries Ltd. has engaged positively in the development and the application study of this technology. All the software products of its recent activities were summarized in the integrated form named 'PRONET'. The PRONET is classified into two independent software groups from the viewpoint of computer system. One is off-line Process Simulation Group, and the other is Dynamic Real-time Simulator Group. The former is called 'PRONET System', and the latter is called 'PRONET Simulator'. These have several subsystems with the prefix 'MR' meaning Mitsubishi Reprocessing Plant. Each MR subsystem is explained in this report. The technical background, the objective of the PRONET, the system and the function of the PRONET, and the future application to an on-line real-time simulator and the development of MR EXPERT are described. (K.I.)

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

    International Nuclear Information System (INIS)

    Ren, Yanlin; Fan, Guangyin; Wang, Chenyu

    2014-01-01

    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 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 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

  18. Optimal Information Processing in Biochemical Networks

    Science.gov (United States)

    Wiggins, Chris

    2012-02-01

    A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

  19. Morphological Characterization of the Action Potential Initiation Segment in GnRH Neuron Dendrites and Axons of Male Mice.

    Science.gov (United States)

    Herde, Michel K; Herbison, Allan E

    2015-11-01

    GnRH neurons are the final output neurons of the hypothalamic network controlling fertility in mammals. In the present study, we used ankyrin G immunohistochemistry and neurobiotin filling of live GnRH neurons in brain slices from GnRH-green fluorescent protein transgenic male mice to examine in detail the location of action potential initiation in GnRH neurons with somata residing at different locations in the basal forebrain. We found that the vast majority of GnRH neurons are bipolar in morphology, elaborating a thick (primary) and thinner (secondary) dendrite from opposite poles of the soma. In addition, an axon-like process arising predominantly from a proximal dendrite was observed in a subpopulation of GnRH neurons. Ankyrin G immunohistochemistry revealed the presence of a single action potential initiation zone ∼27 μm in length primarily in the secondary dendrite of GnRH neurons and located 30 to 140 μm distant from the cell soma, depending on the type of process and location of the cell body. In addition to dendrites, the GnRH neurons with cell bodies located close to hypothalamic circumventricular organs often elaborated ankyrin G-positive axon-like structures. Almost all GnRH neurons (>90%) had their action potential initiation site in a process that initially, or ultimately after a hairpin loop, was coursing in the direction of the median eminence. These studies indicate that action potentials are initiated in different dendritic and axonal compartments of the GnRH neuron in a manner that is dependent partly on the neuroanatomical location of the cell body.

  20. Business Process Modeling Languages Supporting Collaborative Networks

    NARCIS (Netherlands)

    Soleimani Malekan, H.; Afsarmanesh, H.; Hammoudi, S.; Maciaszek, L.A.; Cordeiro, J.; Dietz, J.L.G.

    2013-01-01

    Formalizing the definition of Business Processes (BPs) performed within each enterprise is fundamental for effective deployment of their competencies and capabilities within Collaborative Networks (CN). In our approach, every enterprise in the CN is represented by its set of BPs, so that other

  1. 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...... under market and technical uncertainty....

  2. Generalized epidemic process on modular networks.

    Science.gov (United States)

    Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong

    2014-05-01

    Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

  3. 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*.

  4. Information governance in dynamic networked business process management

    NARCIS (Netherlands)

    Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.

    2016-01-01

    Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).

  5. Rh Factor Blood Test

    Science.gov (United States)

    ... Also, talk with your health care provider about scheduling an Rh immune globulin injection during your pregnancy ... of Privacy Practices Notice of Nondiscrimination Manage Cookies Advertising Mayo Clinic is a not-for-profit organization ...

  6. RH Packaging Operations Manual

    International Nuclear Information System (INIS)

    Washington TRU Solutions LLC

    2003-01-01

    This procedure provides operating instructions for the RH-TRU 72-B Road Cask, Waste Shipping Package. In this document, ''Packaging'' refers to the assembly of components necessary to ensure compliance with the packaging requirements (not loaded with a payload). ''Package'' refers to a Type B packaging that, with its radioactive contents, is designed to retain the integrity of its containment and shielding when subject to the normal conditions of transport and hypothetical accident test conditions set forth in 10 CFR Part 71. Loading of the RH 72-B cask can be done two ways, on the RH cask trailer in the vertical position or by removing the cask from the trailer and loading it in a facility designed for remote-handling (RH). Before loading the 72-B cask, loading procedures and changes to the loading procedures for the 72-B cask must be sent to CBFO at sitedocuments at wipp.ws for approval

  7. Development, upscaling and validation of the purification process for human-cl rhFVIII (Nuwiq®), a new generation recombinant factor VIII produced in a human cell-line.

    Science.gov (United States)

    Winge, Stefan; Yderland, Louise; Kannicht, Christoph; Hermans, Pim; Adema, Simon; Schmidt, Torben; Gilljam, Gustav; Linhult, Martin; Tiemeyer, Maya; Belyanskaya, Larisa; Walter, Olaf

    2015-11-01

    Human-cl rhFVIII (Nuwiq®), a new generation recombinant factor VIII (rFVIII), is the first rFVIII produced in a human cell-line approved by the European Medicines Agency. To describe the development, upscaling and process validation for industrial-scale human-cl rhFVIII purification. The purification process involves one centrifugation, two filtration, five chromatography columns and two dedicated pathogen clearance steps (solvent/detergent treatment and 20 nm nanofiltration). The key purification step uses an affinity resin (VIIISelect) with high specificity for FVIII, removing essentially all host-cell proteins with >80% product recovery. The production-scale multi-step purification process efficiently removes process- and product-related impurities and results in a high-purity rhFVIII product, with an overall yield of ∼50%. Specific activity of the final product was >9000 IU/mg, and the ratio between active FVIII and total FVIII protein present was >0.9. The entire production process is free of animal-derived products. Leaching of potential harmful compounds from chromatography resins and all pathogens tested were below the limit of quantification in the final product. Human-cl rhFVIII can be produced at 500 L bioreactor scale, maintaining high purity and recoveries. The innovative purification process ensures a high-purity and high-quality human-cl rhFVIII product with a high pathogen safety margin. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  8. The roles of resuspension, diffusion and biogeochemical processes on oxygen dynamics offshore of the Rhône River, France: a numerical modeling study

    Science.gov (United States)

    Moriarty, Julia M.; Harris, Courtney K.; Fennel, Katja; Friedrichs, Marjorie A. M.; Xu, Kehui; Rabouille, Christophe

    2017-04-01

    Observations indicate that resuspension and associated fluxes of organic material and porewater between the seabed and overlying water can alter biogeochemical dynamics in some environments, but measuring the role of sediment processes on oxygen and nutrient dynamics is challenging. A modeling approach offers a means of quantifying these fluxes for a range of conditions, but models have typically relied on simplifying assumptions regarding seabed-water-column interactions. Thus, to evaluate the role of resuspension on biogeochemical dynamics, we developed a coupled hydrodynamic, sediment transport, and biogeochemical model (HydroBioSed) within the Regional Ocean Modeling System (ROMS). This coupled model accounts for processes including the storage of particulate organic matter (POM) and dissolved nutrients within the seabed; fluxes of this material between the seabed and the water column via erosion, deposition, and diffusion at the sediment-water interface; and biogeochemical reactions within the seabed. A one-dimensional version of HydroBioSed was then implemented for the Rhône subaqueous delta in France. To isolate the role of resuspension on biogeochemical dynamics, this model implementation was run for a 2-month period that included three resuspension events; also, the supply of organic matter, oxygen, and nutrients to the model was held constant in time. Consistent with time series observations from the Rhône Delta, model results showed that erosion increased the diffusive flux of oxygen into the seabed by increasing the vertical gradient of oxygen at the seabed-water interface. This enhanced supply of oxygen to the seabed, as well as resuspension-induced increases in ammonium availability in surficial sediments, allowed seabed oxygen consumption to increase via nitrification. This increase in nitrification compensated for the decrease in seabed oxygen consumption due to aerobic remineralization that occurred as organic matter was entrained into the water

  9. 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.

  10. 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.

  11. Performance PtSnRh electrocatalysts supported on carbon-Sb2O5.SbO2 for the electro-oxidation of ethanol, prepared by an alcohol-reduction process

    International Nuclear Information System (INIS)

    Castro, Jose Carlos

    2013-01-01

    PtSnRh electrocatalysts supported on carbon-Sb 2 O 5 .SnO 2 , with metal loading of 20 wt%, were prepared by an alcohol-reduction process, using H 2 PtCl 6 .6H 2 O (Aldrich), RhCl 3 .xH 2 O (Aldrich) and SnCl 2 .2H 2 O (Aldrich), as source of metals; Sb 2 O 5 .SnO 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 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)

  12. Advanced business process management in networked E-business scenarios

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Türetken, O.

    2017-01-01

    In the modern economy, we see a shift towards networked business scenarios. In many contemporary situations, the operation of multiple organizations is tightly coupled in collaborative business networks. To allow this tightly coupled collaboration, business process management (BPM) in these

  13. 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

  14. Constitutional studies in the palladium-rhodium-tellurium (-oxygen) system. A contribution to elucidate the behaviour of Pd, Rh and Te in the vitrification process of high-level waste concentrates (HLWC)

    International Nuclear Information System (INIS)

    Hartmann, T.

    1996-01-01

    In the vitrification process of high-level waste concentrates (HLWC) from the reprocessing of nuclear spent fuel elements, about 30 different elements have to be immobilized in a solid matrix consisting of an alkali borosilicate glass. Most of the waste oxides are dissolved in the alkali borosilicate melt and become structural elements of the glasses when cooled. This, however, applies only partly to the platinum metals Ru, which forms RuO 2 , and palladium and rhodium, which deposit as sparingly soluble and electrically conducting tellurides. This might considerably impair the technical process of HLWC vitrification. Therefore, constitutional studies on the Pd-Rh-Te system became necessary. The phase diagram of the Pd-Rh-Te ternary system at temperatures of 1150, 1100, 1050, 1000, 950, 900 and 750 C was determined under inertial conditions. Oxygen exerts a major influence on the system. Already under limited availability of oxygen, the rhodium contents of the solid solution phases α 1 and α 2 are clearly diminished. Rhodium of the phases becomes oxidized selectively. The three-phase field α 1 +α 2 +L is shifted to higher palladium and tellurium contents, even oxygen is available to a limited extend only. With the oxygen in the air, the extension of the three-phase space is reduced markedly. The complex process chemistry of Pf, Rh and Te during the vitrification can be described by the state of the Pd-Rh-Te ternary system after annealing in (air) oxygen for limited periods of time. (orig./MM) [de

  15. Synthesis and Design of Integrated Process and Water Networks

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...... 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...

  16. Kriteria Pemilihan Pemasok Menggunakan Analytical Network Process

    Directory of Open Access Journals (Sweden)

    Dewi Kurniawati

    2013-01-01

    Full Text Available The selection of supplier is a strategic decision in supply chain which increase competitive advantages. Every manufacture needs to have a standard supplier selection that appropriate with the requirement of the company. The aims of this paper are promoting some criterias of supplier selection and testing whether there are differences interests against priority criteria referred to of strata tenure distinct. Weights and priorities of the criteria tested with a method of analytic network process (ANP are also intended to bring up a relation of mutual influence among the criteria. ANP can be used to help making decision of selection supplier and to manage supply chain performance. This paper shows the criteria that influence are the past perfomance, price, communication systems, and a supplier of professionalism is the priority for the production of the company. In the other hand, the importance of management is the delivery time, consistent quality, price, and number of delivery. The difference in perspective is influenced by the level of interest and different responsibilities. The difference this assessment formed the basis of decision-making and strategic policies of the supply chain according to the condition of the company.

  17. 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

  18. Multidimensional epidemic thresholds in diffusion processes over interdependent networks

    International Nuclear Information System (INIS)

    Salehi, Mostafa; Siyari, Payam; Magnani, Matteo; Montesi, Danilo

    2015-01-01

    Highlights: •We propose a new concept of multidimensional epidemic threshold for interdependent networks. •We analytically derive and numerically illustrate the conditions for multilayer epidemics. •We study the evolution of infection density and diffusion dynamics. -- Abstract: Several systems can be modeled as sets of interdependent networks where each network contains distinct nodes. Diffusion processes like the spreading of a disease or the propagation of information constitute fundamental phenomena occurring over such coupled networks. In this paper we propose a new concept of multidimensional epidemic threshold characterizing diffusion processes over interdependent networks, allowing different diffusion rates on the different networks and arbitrary degree distributions. We analytically derive and numerically illustrate the conditions for multilayer epidemics, i.e., the appearance of a giant connected component spanning all the networks. Furthermore, we study the evolution of infection density and diffusion dynamics with extensive simulation experiments on synthetic and real networks

  19. Towards Business Process Management in networked ecosystems

    NARCIS (Netherlands)

    Johan Versendaal; dr. Martijn Zoet; Jeroen Grondelle

    2014-01-01

    Managing and supporting the collaboration between different actors is key in any organizational context, whether of a hierarchical or a networked nature. In the networked context of ecosystems of service providers and other stakeholders, BPM is faced with different challenges than in a conventional

  20. Origins of gonadotropin-releasing hormone (GnRH) in vertebrates: identification of a novel GnRH in a basal vertebrate, the sea lamprey.

    Science.gov (United States)

    Kavanaugh, Scott I; Nozaki, Masumi; Sower, Stacia A

    2008-08-01

    We cloned a cDNA encoding a novel (GnRH), named lamprey GnRH-II, from the sea lamprey, a basal vertebrate. The deduced amino acid sequence of the newly identified lamprey GnRH-II is QHWSHGWFPG. The architecture of the precursor is similar to that reported for other GnRH precursors consisting of a signal peptide, decapeptide, a downstream processing site, and a GnRH-associated peptide; however, the gene for lamprey GnRH-II does not have introns in comparison with the gene organization for all other vertebrate GnRHs. Lamprey GnRH-II precursor transcript was widely expressed in a variety of tissues. In situ hybridization of the brain showed expression and localization of the transcript in the hypothalamus, medulla, and olfactory regions, whereas immunohistochemistry using a specific antiserum showed only GnRH-II cell bodies and processes in the preoptic nucleus/hypothalamus areas. Lamprey GnRH-II was shown to stimulate the hypothalamic-pituitary axis using in vivo and in vitro studies. Lamprey GnRH-II was also shown to activate the inositol phosphate signaling system in COS-7 cells transiently transfected with the lamprey GnRH receptor. These studies provide evidence for a novel lamprey GnRH that has a role as a third hypothalamic GnRH. In summary, the newly discovered lamprey GnRH-II offers a new paradigm of the origin of the vertebrate GnRH family. We hypothesize that due to a genome/gene duplication event, an ancestral gene gave rise to two lineages of GnRHs: the gnathostome GnRH and lamprey GnRH-II.

  1. CoFeRh alloys

    Energy Technology Data Exchange (ETDEWEB)

    Tabakovic, Ibro [Seagate Technology, Research and Development, Bloomington, MN 55435 (United States)], E-mail: ibro.m.tabakovic@seagate.com; Qiu Jiaoming; Riemer, Steve; Sun Ming; Vas' ko, Vlad; Kief, Mark [Seagate Technology, Research and Development, Bloomington, MN 55435 (United States)

    2008-01-01

    The electrochemical behavior of Rh(III) species in CoFe solution containing RhCl{sub 3}, NH{sub 4}Cl, H{sub 3}BO{sub 3}, CoSO{sub 4}, FeSO{sub 4}, saccharin, and NaLS (Na lauryl sulfate) has been investigated. The electrochemistry of Rh(III) species is influenced by each of the compounds present in CoFe plating solution, but especially by addition of saccharin and H{sub 3}BO{sub 3} to the RhCl{sub 3}-NH{sub 4}Cl solution. The nucleation and growth of Rh on GC (glassy carbon), Ru, and Cu electrodes from NH{sub 4}Cl solution was studied using the potentiostatic current-transient methods. The results support a predominantly progressive nucleation of Rh on all three-electrode surfaces. The nucleation kinetic parameters ANo (steady state nucleation rate) and Ns (saturation nuclear number density) were found to vary with potential and are electrode-dependent in order: GC > Ru{approx}Cu. The electrodeposited Rh films obtained from NH{sub 4}Cl solution and nonmagnetic CoFeRh film obtained from CoFe solution were characterized in terms of the following properties: morphology, surface roughness, crystal structure and chemical composition. The origin of light elements found in Rh and CoFeRh films (O, Cl, S, C, N) was discussed.

  2. CoFeRh alloys

    International Nuclear Information System (INIS)

    Tabakovic, Ibro; Qiu Jiaoming; Riemer, Steve; Sun Ming; Vas'ko, Vlad; Kief, Mark

    2008-01-01

    The electrochemical behavior of Rh(III) species in CoFe solution containing RhCl 3 , NH 4 Cl, H 3 BO 3 , CoSO 4 , FeSO 4 , saccharin, and NaLS (Na lauryl sulfate) has been investigated. The electrochemistry of Rh(III) species is influenced by each of the compounds present in CoFe plating solution, but especially by addition of saccharin and H 3 BO 3 to the RhCl 3 -NH 4 Cl solution. The nucleation and growth of Rh on GC (glassy carbon), Ru, and Cu electrodes from NH 4 Cl solution was studied using the potentiostatic current-transient methods. The results support a predominantly progressive nucleation of Rh on all three-electrode surfaces. The nucleation kinetic parameters ANo (steady state nucleation rate) and Ns (saturation nuclear number density) were found to vary with potential and are electrode-dependent in order: GC > Ru∼Cu. The electrodeposited Rh films obtained from NH 4 Cl solution and nonmagnetic CoFeRh film obtained from CoFe solution were characterized in terms of the following properties: morphology, surface roughness, crystal structure and chemical composition. The origin of light elements found in Rh and CoFeRh films (O, Cl, S, C, N) was discussed

  3. Optical processing for future computer networks

    Science.gov (United States)

    Husain, A.; Haugen, P. R.; Hutcheson, L. D.; Warrior, J.; Murray, N.; Beatty, M.

    1986-01-01

    In the development of future data management systems, such as the NASA Space Station, a major problem represents the design and implementation of a high performance communication network which is self-correcting and repairing, flexible, and evolvable. To obtain the goal of designing such a network, it will be essential to incorporate distributed adaptive network control techniques. The present paper provides an outline of the functional and communication network requirements for the Space Station data management system. Attention is given to the mathematical representation of the operations being carried out to provide the required functionality at each layer of communication protocol on the model. The possible implementation of specific communication functions in optics is also considered.

  4. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; 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......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  5. RH Packaging Program Guidance

    International Nuclear Information System (INIS)

    2008-01-01

    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 and 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 conspicuous

  6. Modelling aspects of distributed processing in telecommunication networks

    NARCIS (Netherlands)

    Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW

    1998-01-01

    The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in

  7. DAPNA: an architectural framework for data processing networks

    NARCIS (Netherlands)

    Sözer, Hasan; Nouta, Sander; Wombacher, Andreas; Perona, Paolo

    2013-01-01

    A data processing network is as a set of (software) components connected through communication channels to apply a series of operations on data. Realization and maintenance of large-scale data processing networks necessitate an architectural approach that supports analysis, verification,

  8. 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.

  9. Developing a network: the PMM process.

    Science.gov (United States)

    Kamara, A

    1997-11-01

    Since 1988, the Prevention of Maternal Mortality (PMM) Network has developed, implemented and evaluated projects that focus directly on prevention of maternal deaths. The Network, which consists of 11 multidisciplinary teams in West Africa and one at Columbia University, grew from discussions between the Carnegie Corporation of New York and researchers at Columbia School of Public Health. Its goals are: to strengthen capacities in developing countries; to provide program models for preventing maternal deaths; and to inform policymakers about the importance of maternal mortality. This paper describes the development and functioning of the Network. The initial steps included identifying interested partners in Africa and encouraging them to form multidisciplinary teams. Each African team received two grants: one to perform a needs assessment and then another to develop and implement projects based on the results. The Columbia team provided technical assistance in a variety of ways, including site visits, workshops and correspondence. Teams tested program models and reported findings both to local policymakers and in international fora. Collaboration with government and community leaders helped facilitate progress at all stages. At the PMM Network Results Conference in 1996, the teams decided to continue their work by forming the Regional PMM (RPMM) Network, an entirely African entity.

  10. RH-TRU Waste Content Codes (RH-TRUCON)

    International Nuclear Information System (INIS)

    2007-01-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is '3.' The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR limits based

  11. RH-TRU Waste Content Codes (RH-TRUCON)

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions LLC

    2007-08-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: • A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. • A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is “3.” The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR

  12. RH-TRU Waste Content Codes (RH-TRUCON)

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions

    2007-05-30

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: • A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. • A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is “3.” The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR

  13. RH-TRU Waste Content Codes (RH-Trucon)

    International Nuclear Information System (INIS)

    2007-01-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is '3.' The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR limits based

  14. Network measures for characterising team adaptation processes

    NARCIS (Netherlands)

    Barth, S.K.; Schraagen, J.M.C.; Schmettow, M.

    2015-01-01

    The aim of this study was to advance the conceptualisation of team adaptation by applying social network analysis (SNA) measures in a field study of a paediatric cardiac surgical team adapting to changes in task complexity and ongoing dynamic complexity. Forty surgical procedures were observed by

  15. 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.

  16. RH Packaging Program Guidance

    International Nuclear Information System (INIS)

    2006-01-01

    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 and 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) 1.8, '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 these

  17. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  18. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  19. 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...

  20. Parallel Distributed Processing theory in the age of deep networks

    OpenAIRE

    Bowers, Jeffrey

    2017-01-01

    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 within cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks le...

  1. 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.

  2. RH Packaging Program Guidance

    International Nuclear Information System (INIS)

    Washington TRU Solutions, LLC

    2003-01-01

    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 and 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 revision and change notices. Sites may prepare their own document using the word

  3. 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...

  4. Concept design on RH maintenance of CFETR Tokamak reactor

    International Nuclear Information System (INIS)

    Song, Yuntao; Wu, Songtao; Wan, Yuanxi; Li, Jiangang; Ye, Minyou; Zheng, Jinxing; Cheng, Yong; Zhao, Wenlong; Wei, Jianghua

    2014-01-01

    Highlights: •We discussed the concept design of the RH maintenance system based on the main design work of the key components for CFETR. •The main design work for RH maintenance in this paper was carried out including the divertor RH system, the blanket RH system and the transfer cask system. •The technical problems encountered in the design process were discussed. •The present concept design of remote maintenance system in this paper can meet the physical and engineering requirement of CFETR. -- Abstract: CFETR which stands for Chinese Fusion Engineering Testing Reactor is a superconducting Tokamak device. The concept design on RH maintenance of CFETR has been done in the past year. It is known that, the RH maintenance is one of the most important parts for Tokamak reactor. The fusion power was designed as 50–200 MW and its duty cycle time (or burning time) was estimated as 30–50%. The center magnetic field strength on the TF magnet is 5.0 T, the maximum capacity of the volt seconds provided by center solenoid winding will be about 160 VS. The plasma current will be 10 MA and its major radius and minor radius is 5.7 m and 1.6 m respectively. All the components of CFETR which provide their basic functions must be maintained and inspected during the reactor lifetime. Thus, the remote handling (RH) maintenance system should be a key component, which must be detailedly designed during the concept design processing of CFETR, for the operation of reactor. The main design work for RH maintenance in this paper was carried out including the divertor RH system, the blanket RH system and the transfer cask system. What is more, the technical problems encountered in the design process will also be discussed

  5. Identifying and tracking dynamic processes in social networks

    Science.gov (United States)

    Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

    2006-05-01

    The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

  6. 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.

  7. 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

  8. RH-TRU Waste Content Codes (RH TRUCON)

    International Nuclear Information System (INIS)

    2007-01-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: (1) A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. (2) A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is ''3''. The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR

  9. RH-TRU Waste Content Codes (RH TRUCON)

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions

    2007-05-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: • A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. • A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is “3.” The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR

  10. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

    NARCIS (Netherlands)

    Veldhoen, S.; Hupkes, D.; Zuidema, W.

    2016-01-01

    We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

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

    OpenAIRE

    Lei, Yanjun; Jiang, Xin; 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 a...

  12. 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.

  13. Optical Multiple Access Network (OMAN) for advanced processing satellite applications

    Science.gov (United States)

    Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

    1991-01-01

    An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

  14. Understanding human visual processing with Deep Neural Networks

    OpenAIRE

    Thorat, Sushrut

    2016-01-01

    This presentation has 2 parts:1. An introduction to the vision processing - neuroscience, and machine vision.2. Discussion of one of the first papers relating Deep Networks to the visual ventral stream. (Khaligh-Razavi, 2014)

  15. 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.

  16. Processing horizontal networks measured by integrated terrestrial and GPS technologies

    Directory of Open Access Journals (Sweden)

    Vincent Jakub

    2003-09-01

    Full Text Available Local horizontal networks in which GPS and terrestrial measurements (TER are done are often established at present. Iin other networks, the previous terrestrial measurements can be completed with quantities from contemporary GPS observations (tunnel nets, mining nets with surface and underground parts and other long-shaped nets.The processing of such heterobeneous (GPS, TER networks whose terrestrial measurements are performed as point coordinate measurements (∆X, ∆Y using (geodetic total stationIn is presented in this paper. In such network structures it is then available:- the values ∆X, ∆Y from TER observations which are transformed in the plane of S-JTSK for adjustement,- the values ∆X, ∆Y in the plane S-JTSK that can be obtained by 3D transformation of WGS84 netpoint coordinates from GPS observations to corresponding coordinates S-JTSK.For common adjusting all the ∆X, ∆Y, some elements of the network geometry (e.g. distances should be measured by both methods (GPS, TER. This approach makes possible an effective homogenisation of both network parts what is equivalent to saying that an expressive influence reduction on local frame realizations of S-JTSK in the whole network can be made.Results of network processing obtained in proposed manner are acceptable in general and they are equivalent (accuracy, reliability to results of another processing methods.

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

    International Nuclear Information System (INIS)

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

    1991-01-01

    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

  18. Precision Scaling of Neural Networks for Efficient Audio Processing

    OpenAIRE

    Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

    2017-01-01

    While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

  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. 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.

  1. Neural network training by Kalman filtering in process system monitoring

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-03-01

    Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

  2. Software/hardware distributed processing network supporting the Ada environment

    Science.gov (United States)

    Wood, Richard J.; Pryk, Zen

    1993-09-01

    A high-performance, fault-tolerant, distributed network has been developed, tested, and demonstrated. The network is based on the MIPS Computer Systems, Inc. R3000 Risc for processing, VHSIC ASICs for high speed, reliable, inter-node communications and compatible commercial memory and I/O boards. The network is an evolution of the Advanced Onboard Signal Processor (AOSP) architecture. It supports Ada application software with an Ada- implemented operating system. A six-node implementation (capable of expansion up to 256 nodes) of the RISC multiprocessor architecture provides 120 MIPS of scalar throughput, 96 Mbytes of RAM and 24 Mbytes of non-volatile memory. The network provides for all ground processing applications, has merit for space-qualified RISC-based network, and interfaces to advanced Computer Aided Software Engineering (CASE) tools for application software development.

  3. Robust collaborative process interactions under system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2013-01-01

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes its state, it sends messages to the relevant processes to inform about this change. However, server crashes

  4. Social network analysis 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...

  5. Process efficiency. Redesigning social networks to improve surgery patient flow.

    Science.gov (United States)

    Samarth, Chandrika N; Gloor, Peter A

    2009-01-01

    We propose a novel approach to improve throughput of the surgery patient flow process of a Boston area teaching hospital. A social network analysis was conducted in an effort to demonstrate that process efficiency gains could be achieved through redesign of social network patterns at the workplace; in conjunction with redesign of organization structure and the implementation of workflow over an integrated information technology system. Key knowledge experts and coordinators in times of crisis were identified and a new communication structure more conducive to trust and knowledge sharing was suggested. The new communication structure is scalable without compromising on coordination required among key roles in the network for achieving efficiency gains.

  6. Rh-Ni and Rh-Co Catalysts for Autothermal Reforming of Gasoline

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Yeongyu; Lee, Daehyung; Kim, Yongmin; Lee, Jinhee; Nam, Sukwoo; Choi, Daeki; Yoon, Chang Won [Korea Institute of Science and Technology, Seoul (Korea, Republic of)

    2014-01-15

    Rh doped Ni and Co catalysts, Rh-M/CeO{sub 2}(20 wt %)-Al{sub 2}O{sub 3} (0.2 wt % of Rh; M = Ni or Co, 20 wt %) were synthesized to produce hydrogen via autothermal reforming (ATR) of commercial gasoline at 700 .deg. C under the conditions of a S/C ratio of 2.0, an O/C ratio of 0.84, and a gas hourly space velocity (GHSV) of 20,000 h{sup -1}. The Rh-Ni/CeO{sub 2}(20 wt %)-Al{sub 2}O{sub 3} catalyst (1) exhibited excellent activities, with H{sub 2} and (H{sub 2}+CO) yields of 2.04 and 2.58 mol/mol C, respectively. In addition, this catalyst proved to be highly stable over 100 h without catalyst deactivation, as evidenced by energy dispersive spectroscopy (EDX) and elemental analyses. Compared to 1, Rh-Co/CeO{sub 2}(20 wt %)-Al{sub 2}O{sub 3} catalyst (2) exhibited relatively low stability, and its activity decreased after 57 h. In line with this observation, elemental analyses confirmed that nearly no carbon species were formed at 1 while carbon deposits (10 wt %) were found at 2 following the reaction, which suggests that carbon coking is the main process for catalyst deactivation.

  7. Engineering processes for the African VLBI network

    Science.gov (United States)

    Thondikulam, Venkatasubramani L.; Loots, Anita; Gaylard, Michael

    2013-04-01

    The African VLBI Network (AVN) is an initiative by the SKA-SA and HartRAO, business units of the National Research Foundation (NRF), Department of Science and Technology (DST), South Africa. The aim is to fill the existing gap of Very Long Baseline Interferometry (VLBI)-capable radio telescopes in the African continent by a combination of new build as well as conversion of large redundant telecommunication antennas through an Inter-Governmental collaborative programme in Science and Technology. The issue of human capital development in the Continent in the techniques of radio astronomy engineering and science is a strong force to drive the project and is expected to contribute significantly to the success of Square Kilometer Array (SKA) in the Continent.

  8. Parallel processing data network of master and slave transputers controlled by a serial control network

    Science.gov (United States)

    Crosetto, Dario B.

    1996-01-01

    The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

  9. Scalable Networked Information Processing Environment (SNIPE)

    Energy Technology Data Exchange (ETDEWEB)

    Fagg, G.E.; Moore, K. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science; Dongarra, J.J. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science]|[Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Geist, A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

    1997-11-01

    SNIPE is a metacomputing system that aims to provide a reliable, secure, fault tolerant environment for long term distributed computing applications and data stores across the global Internet. This system combines global naming and replication of both processing and data to support large scale information processing applications leading to better availability and reliability than currently available with typical cluster computing and/or distributed computer environments.

  10. Global tree network for computing structures enabling global processing operations

    Science.gov (United States)

    Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

    2010-01-19

    A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

  11. Competing Contact Processes on Homogeneous Networks with Tunable Clusterization

    Science.gov (United States)

    Rybak, Marcin; Kułakowski, Krzysztof

    2013-03-01

    We investigate two homogeneous networks: the Watts-Strogatz network with mean degree ⟨k⟩ = 4 and the Erdös-Rényi network with ⟨k⟩ = 10. In both kinds of networks, the clustering coefficient C is a tunable control parameter. The network is an area of two competing contact processes, where nodes can be in two states, S or D. A node S becomes D with probability 1 if at least two its mutually linked neighbors are D. A node D becomes S with a given probability p if at least one of its neighbors is S. The competition between the processes is described by a phase diagram, where the critical probability pc depends on the clustering coefficient C. For p > pc the rate of state S increases in time, seemingly to dominate in the whole system. Below pc, the majority of nodes is in the D-state. The numerical results indicate that for the Watts-Strogatz network the D-process is activated at the finite value of the clustering coefficient C, close to 0.3. On the contrary, for the Erdös-Rényi network the transition is observed at the whole investigated range of C.

  12. 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

  13. Geomorphological response of a landscape to long-term tectonic and glacial processes: the upper Rhône basin, Central Swiss Alps

    Science.gov (United States)

    Stutenbecker, Laura; Schlunegger, Fritz

    2015-04-01

    The Rhône River in the Central Swiss Alps drains a 5380 km2 large basin that shows a high spatial variability of bedrock lithology, exhumation rate, glacial conditioning and climate. All of these factors were recently discussed to control erosion rates in orogenic settings in general, and particularly in the Alps (e.g. Wittmann et al. 2007, Vernon et al. 2008, Norton et al. 2010a). Thanks to various and densely distributed data, the upper Rhône basin located between the Aar massif and Lake Geneva is a suitable natural laboratory to analyze the landscape's geomorphological state and controlling factors at a basin-scale. In this study, we extract geomorphological parameters along the channels of ca. 50 tributary basins of various sizes that contribute to the sediment budget of the Rhône River either through sediment supply by torrents or debris flows. Their catchments are located in either granitic basement rocks (External Massifs), oceanic meta-sedimentary and ophiolitic rocks (Penninic nappes) or fine-grained continental-margin sediments (Helvetic nappes). The analysis of longitudinal river profiles from DEMs and slope/area relationships show that all tributary rivers within the Rhône basin are in topographic transient state that is expressed by mainly convex or concave-convex channel shapes with several knickpoints of either tectonic-lithological or glacial origin. Furthermore, the frequency distribution of elevations (hypsometry) along the river channel allows identifying glacially inherited morphologies and the recent erosional front. The combination of those different geomorphological data yields to a categorization of the tributary rivers into three endmember groups: (1) streams with highly convex profiles, testifying to a strong glacial inheritance, (2) concave-convex channels with several knickzones and inherited morphologies of past glaciations, (3) predominantly concave, relatively steep rivers with minor knickpoints and inner gorges. Assuming that

  14. Design of common heat exchanger network for batch processes

    International Nuclear Information System (INIS)

    Anastasovski, Aleksandar

    2014-01-01

    Heat integration of energy streams is very important for the efficient energy recovery in production systems. Pinch technology is a very useful tool for heat integration and maximizing energy efficiency. Creating of heat exchangers network as a common solution for systems in batch mode that will be applicable in all existing time slices is very difficult. This paper suggests a new methodology for design of common heat exchanger network for batch processes. Heat exchanger network designs were created for all determined repeatable and non-repeatable time periods – time slices. They are the basis for creating the common heat exchanger network. The common heat exchanger network as solution, satisfies all heat-transfer needs for each time period and for every existing combination of selected streams in the production process. This methodology use split of some heat exchangers into two or more heat exchange units or heat exchange zones. The reason for that is the multipurpose use of heat exchangers between different pairs of streams in different time periods. Splitting of large heat exchangers would maximize the total heat transfer usage of heat exchange units. Final solution contains heat exchangers with the minimum heat load as well as the minimum need of heat transfer area. The solution is applicable for all determined time periods and all existing stream combinations. - Highlights: •Methodology for design of energy efficient systems in batch processes. •Common Heat Exchanger Network solution based on designs with Pinch technology. •Multipurpose use of heat exchangers in batch processes

  15. Towards the understanding of network information processing in biology

    Science.gov (United States)

    Singh, Vijay

    Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

  16. Rh-flash acquisition card

    International Nuclear Information System (INIS)

    Bourrion, O.

    2003-01-01

    The rh-flash card main purpose is to convert and store the image of the analog data present at input into an output buffer, namely in a given timing window besides a stop signal (like a digital oscilloscope). It is conceived in VME format 1U wide with an additional connector. Novelty of this card is its ability to sample at a high frequency, due to flash coders, and this at a high repetition rate. To do that the card allows the storage of the data considered 'useful' and that is done by storing only the data exceeding a certain threshold. This can be useful for instance for viewing peaks in a spectrum, and obtaining their relative location. The goal is to stock and process the data sampled before and after the arrival of a stop signal (what entails a storage depth). A threshold is defined and any peak exceeding its level will really be stored in the output buffer which is readable through the VME bus. The peak values will be stored as well as m preceding and n subsequent values (both programmable). Obviously, if the threshold is zero the system of data processing is off and all data will be stored. The document is structured on six sections titled: 1. Description; 2. Specifications; 3. Explaining the design of channels; 4. Explaining the shared part of the design; 5. Addressing (→ user guide); 6. Software precautions. (author)

  17. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  18. Renal fascial network in retroperitoneal extension of pathologic processes

    International Nuclear Information System (INIS)

    Raptopoulos, V.; Kleinman, P.K.; Marks, S.C. Jr.; Davidoff, A.

    1987-01-01

    The concept of the fascial network emerged after careful analysis of CT scans of 100 patients with a variety of retroperitoneal abnormalities, and after correlation of CT scans and anatomic dissections performed on eight unembalmed cadavers in which different-colored barium-mixed liquid latex was injected in various retroperitoneal compartments. Fat lobules are supported and connected with each other by surrounding thin layers of connective tissue. Thicker connective tissue lamellae (septa) connect and support organs and fascia. Thus, a fascial network infrastructure exists in which fat lobules act as mechanical barriers to the spread of pathologic processes, while these processes tend to take the course of least resistance by spreading along or dissecting within fascial and septal planes. The fascial network acts as a roadway, conduit, and barrier to spread in the retroperitoneum and fatty tissue in general. The insights afforded by the fascial network concept unwind the traditional views regarding the dynamics of retroperitoneal pathology

  19. A fuzzy art neural network based color image processing and ...

    African Journals Online (AJOL)

    To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

  20. All-optical signal processing for optical packet switching networks

    NARCIS (Netherlands)

    Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

    2005-01-01

    We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

  1. GnRH signalling pathways and GnRH-induced homologous desensitization in a gonadotrope cell line (alphaT3-1).

    Science.gov (United States)

    Poulin, B; Rich, N; Mas, J L; Kordon, C; Enjalbert, A; Drouva, S V

    1998-07-25

    Exposure of the gonadotrope cells to gonadotropin-releasing hormone (GnRH) reduces their responsiveness to a new GnRH stimulation (homologous desensitization). The time frame as well as the mechanisms underlying this phenomenon are yet unclear. We studied in a gonadotrope cell line (alphaT3-1) the effects of short as well as long term GnRH pretreatments on the GnRH-induced phospholipases-C (PLC), -A2 (PLA2) and -D (PLD) activities, by measuring the production of IP3, total inositol phosphates (IPs), arachidonic acid (AA) and phosphatidylethanol (PEt) respectively. We demonstrated that although rapid desensitization of GnRH-induced IP3 formation did not occur in these cells, persistent stimulation of cells with GnRH or its analogue resulted in a time-dependent attenuation of GnRH-elicited IPs formation. GnRH-induced IPs desensitization was potentiated after direct activation of PKC by the phorbol ester TPA, suggesting the involvement of distinct mechanisms in the uncoupling exerted by either GnRH or TPA on GnRH-stimulated PI hydrolysis. The levels of individual phosphoinositides remained unchanged under any desensitization condition applied. Interestingly, while the GnRH-induced PLA2 activity was rapidly desensitized (2.5 min) after GnRH pretreatments, the neuropeptide-evoked PLD activation was affected at later times, indicating an important time-dependent contribution of these enzymatic activities in the sequential events underlying the GnRH-induced homologous desensitization processes in the gonadotropes. Under GnRH desensitization conditions, TPA was still able to induce PLD activation and to further potentiate the GnRH-evoked PLD activity. AlphaT3-1 cells possess several PKC isoforms which, except PKCzeta, were differentially down-regulated by TPA (PKCalpha, betaII, delta, epsilon, eta) or GnRH (PKCbetaII, delta, epsilon, eta). In spite of the presence of PKC inhibitors or down-regulation of PKC isoforms by TPA, the desensitizing effect of the neuropeptide on

  2. Optimization of blanking process using neural network simulation

    International Nuclear Information System (INIS)

    Hambli, R.

    2005-01-01

    The present work describes a methodology using the finite element method and neural network simulation in order to predict the optimum punch-die clearance during sheet metal blanking processes. A damage model is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. Numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling. The comparative study between the numerical results and the experimental ones shows the good agreement. (author)

  3. Bayesian network modeling of operator's state recognition process

    International Nuclear Information System (INIS)

    Hatakeyama, Naoki; Furuta, Kazuo

    2000-01-01

    Nowadays we are facing a difficult problem of establishing a good relation between humans and machines. To solve this problem, we suppose that machine system need to have a model of human behavior. In this study we model the state cognition process of a PWR plant operator as an example. We use a Bayesian network as an inference engine. We incorporate the knowledge hierarchy in the Bayesian network and confirm its validity using the example of PWR plant operator. (author)

  4. Natural Language Processing with Small Feed-Forward Networks

    OpenAIRE

    Botha, Jan A.; Pitler, Emily; Ma, Ji; Bakalov, Anton; Salcianu, Alex; Weiss, David; McDonald, Ryan; Petrov, Slav

    2017-01-01

    We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models. Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to allocate a small memory...

  5. Improving Earth/Prediction Models to Improve Network Processing

    Science.gov (United States)

    Wagner, G. S.

    2017-12-01

    The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

  6. Sustainable Process Networks for CO2 Conversion

    DEFF Research Database (Denmark)

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

    According to various organizations, especially the Intergovernmental Panel on Climate Change, global warming is an ever-increasing threat to the environment and poses a problem if not addressed. As a result, efforts are being made across academic and industrial fields to find methods of reducing...... drawbacks to this geologic storage system: the CO2 is not eliminated, the implementation is limited due to natural phenomena, and the capturing methods are often expensive. Thus, it is desirable to develop an alternative strategy for reducing the CO2 emissions [2]. An additional process that reduces...... 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...

  7. Multimodal processes scheduling in mesh-like network environment

    Directory of Open Access Journals (Sweden)

    Bocewicz Grzegorz

    2015-06-01

    Full Text Available Multimodal processes planning and scheduling play a pivotal role in many different domains including city networks, multimodal transportation systems, computer and telecommunication networks and so on. Multimodal process can be seen as a process partially processed by locally executed cyclic processes. In that context the concept of a Mesh-like Multimodal Transportation Network (MMTN in which several isomorphic subnetworks interact each other via distinguished subsets of common shared intermodal transport interchange facilities (such as a railway station, bus station or bus/tram stop as to provide a variety of demand-responsive passenger transportation services is examined. Consider a mesh-like layout of a passengers transport network equipped with different lines including buses, trams, metro, trains etc. where passenger flows are treated as multimodal processes. The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multimodal transportation processes scheduling encompassing passenger flow itineraries. Then, the main objective is to provide conditions guaranteeing solvability of particular transport lines scheduling, i.e. guaranteeing the right match-up of local cyclic acting bus, tram, metro and train schedules to a given passengers flow itineraries.

  8. pn: A Tool for Improved Derivation of Process Networks

    Directory of Open Access Journals (Sweden)

    Sven Verdoolaege

    2007-04-01

    Full Text Available Current emerging embedded System-on-Chip platforms are increasingly becoming multiprocessor architectures. System designers experience significant difficulties in programming these platforms. The applications are typically specified as sequential programs that do not reveal the available parallelism in an application, thereby hindering the efficient mapping of an application onto a parallel multiprocessor platform. In this paper, we present our compiler techniques for facilitating the migration from a sequential application specification to a parallel application specification using the process network model of computation. Our work is inspired by a previous research project called Compaan. With our techniques we address optimization issues such as the generation of process networks with simplified topology and communication without sacrificing the process networks' performance. Moreover, we describe a technique for compile-time memory requirement estimation which we consider as an important contribution of this paper. We demonstrate the usefulness of our techniques on several examples.

  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. Nonlinear identification of process dynamics using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Atiya, A.F.; Chong, K.T.

    1992-01-01

    In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

  12. 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.

  13. Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations.

    Science.gov (United States)

    Gerlach, Kathy D; Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L

    2014-12-01

    We spend much of our daily lives imagining how we can reach future goals and what will happen when we attain them. Despite the prevalence of such goal-directed simulations, neuroimaging studies on planning have mainly focused on executive processes in the frontal lobe. This experiment examined the neural basis of process simulations, during which participants imagined themselves going through steps toward attaining a goal, and outcome simulations, during which participants imagined events they associated with achieving a goal. In the scanner, participants engaged in these simulation tasks and an odd/even control task. We hypothesized that process simulations would recruit default and frontoparietal control network regions, and that outcome simulations, which allow us to anticipate the affective consequences of achieving goals, would recruit default and reward-processing regions. Our analysis of brain activity that covaried with process and outcome simulations confirmed these hypotheses. A functional connectivity analysis with posterior cingulate, dorsolateral prefrontal cortex and anterior inferior parietal lobule seeds showed that their activity was correlated during process simulations and associated with a distributed network of default and frontoparietal control network regions. During outcome simulations, medial prefrontal cortex and amygdala seeds covaried together and formed a functional network with default and reward-processing regions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Processing of seismic signals from a seismometer network

    International Nuclear Information System (INIS)

    Key, F.A.; Warburton, P.J.

    1983-08-01

    A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

  15. Introduction to spiking neural networks: Information processing, learning and applications.

    Science.gov (United States)

    Ponulak, Filip; Kasinski, Andrzej

    2011-01-01

    The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

  16. Two Distinct Scene-Processing Networks Connecting Vision and Memory.

    Science.gov (United States)

    Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

    2016-01-01

    A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

  17. Probing the interaction of Rh, Co and bimetallic Rh-Co nanoparticles with the CeO2 support: catalytic materials for alternative energy generation.

    Science.gov (United States)

    Varga, E; Pusztai, P; Óvári, L; Oszkó, A; Erdőhelyi, A; Papp, C; Steinrück, H-P; Kónya, Z; Kiss, J

    2015-10-28

    The interaction of CeO2-supported Rh, Co and bimetallic Rh-Co nanoparticles, which are active catalysts in hydrogen production via steam reforming of ethanol, a process related to renewable energy generation, was studied by X-ray diffraction (XRD), high resolution electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS) and low energy ion scattering (LEIS). Furthermore, diffuse reflectance infrared spectroscopy (DRIFTS) of adsorbed CO as a probe molecule was used to characterize the morphology of metal particles. At small loadings (0.1%), Rh is in a much dispersed state on ceria, while at higher contents (1-5%), Rh forms 2-8 nm particles. Between 473-673 K pronounced oxygen transfer from ceria to Rh is observed and at 773 K significant agglomeration of Rh occurs. On reduced ceria, XPS indicates a possible electron transfer from Rh to ceria. The formation of smaller ceria crystallites upon loading with Co was concluded from XRD and HRTEM; for 10% Co, the CeO2 particle size decreased from 27.6 to 10.7 nm. A strong dissolution of Co into ceria and a certain extent of encapsulation by ceria were deduced by XRD, XPS and LEIS. In the bimetallic system, the presence of Rh enhances the reduction of cobalt and ceria. During thermal treatments, reoxidation of Co occurs, and Rh agglomeration as well as oxygen migration from ceria to Rh are hindered in the presence of cobalt.

  18. Collaborative In-Network Processing for Target Tracking

    Directory of Open Access Journals (Sweden)

    Juan Liu

    2003-03-01

    Full Text Available This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

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

    DEFF Research Database (Denmark)

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

    2006-01-01

    This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... 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...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

  20. Multiple-predators-based capture process on complex networks

    International Nuclear Information System (INIS)

    Sharafat, Rajput Ramiz; Pu Cunlai; Li Jie; Chen Rongbin; Xu Zhongqi

    2017-01-01

    The predator/prey (capture) problem is a prototype of many network-related applications. We study the capture process on complex networks by considering multiple predators from multiple sources. In our model, some lions start from multiple sources simultaneously to capture the lamb by biased random walks, which are controlled with a free parameter α . We derive the distribution of the lamb’s lifetime and the expected lifetime 〈 T 〉. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. Moreover, we study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than on large-degree nodes to prolong the lifetime of the lamb. The dense or homogeneous network structures are against the survival of the lamb. We also discuss how to improve the capture efficiency in our model. (paper)

  1. An application of neural networks to process and materials control

    International Nuclear Information System (INIS)

    Howell, J.A.; Whiteson, R.

    1991-01-01

    Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. They can learn (make internal models from experience or observations). The problem of anomaly detection in materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observables must be chosen. These observables must in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, we discuss the issues involved in applying a neural network model to anomaly detection in materials control systems. These issues include data selection and representation, network architecture, prediction of events, the use of simulated data, and software tools. 10 refs., 4 figs., 1 tab

  2. MODEL ANALYTICAL NETWORK PROCESS (ANP DALAM PENGEMBANGAN PARIWISATA DI JEMBER

    Directory of Open Access Journals (Sweden)

    Sukidin Sukidin

    2015-04-01

    Full Text Available Abstrak    : Model Analytical Network Process (ANP dalam Pengembangan Pariwisata di Jember. Penelitian ini mengkaji kebijakan pengembangan pariwisata di Jember, terutama kebijakan pengembangan agrowisata perkebunan kopi dengan menggunakan Jember Fashion Carnival (JFC sebagai event marketing. Metode yang digunakan adalah soft system methodology dengan menggunakan metode analitis jaringan (Analytical Network Process. Penelitian ini menemukan bahwa pengembangan pariwisata di Jember masih dilakukan dengan menggunakan pendekatan konvensional, belum terkoordinasi dengan baik, dan lebih mengandalkan satu even (atraksi pariwisata, yakni JFC, sebagai lokomotif daya tarik pariwisata Jember. Model pengembangan konvensional ini perlu dirancang kembali untuk memperoleh pariwisata Jember yang berkesinambungan. Kata kunci: pergeseran paradigma, industry pariwisata, even pariwisata, agrowisata Abstract: Analytical Network Process (ANP Model in the Tourism Development in Jember. The purpose of this study is to conduct a review of the policy of tourism development in Jember, especially development policies for coffee plantation agro-tourism by using Jember Fashion Carnival (JFC as event marketing. The research method used is soft system methodology using Analytical Network Process. The result shows that the tourism development in Jember is done using a conventional approach, lack of coordination, and merely focus on a single event tourism, i.e. the JFC, as locomotive tourism attraction in Jember. This conventional development model needs to be redesigned to reach Jember sustainable tourism development. Keywords: paradigm shift, tourism industry, agro-tourism

  3. 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…

  4. Mapping debris flow susceptibility using analytical network process ...

    Indian Academy of Sciences (India)

    Evangelin Ramani Sujatha

    2017-11-23

    Nov 23, 2017 ... methods known as the analytical network process (ANP) is used to map the ..... ciated in any prospective way, through feedbacks ..... slide susceptibility by means of multivariate statistical .... and bivariate statistics: A case study in southern Italy;. Nat. ... combination applied to Tevankarai Stream Watershed,.

  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......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...

  6. Synthesis of a parallel data stream processor from data flow process networks

    NARCIS (Netherlands)

    Zissulescu-Ianculescu, Claudiu

    2008-01-01

    In this talk, we address the problem of synthesizing Process Network specifications to FPGA execution platforms. The process networks we consider are special cases of Kahn Process Networks. We call them COMPAAN Data Flow Process Networks (CDFPN) because they are provided by a translator called the

  7. Network formation determined by the diffusion process of random walkers

    International Nuclear Information System (INIS)

    Ikeda, Nobutoshi

    2008-01-01

    We studied the diffusion process of random walkers in networks formed by their traces. This model considers the rise and fall of links determined by the frequency of transports of random walkers. In order to examine the relation between the formed network and the diffusion process, a situation in which multiple random walkers start from the same vertex is investigated. The difference in diffusion rate of random walkers according to the difference in dimension of the initial lattice is very important for determining the time evolution of the networks. For example, complete subgraphs can be formed on a one-dimensional lattice while a graph with a power-law vertex degree distribution is formed on a two-dimensional lattice. We derived some formulae for predicting network changes for the 1D case, such as the time evolution of the size of nearly complete subgraphs and conditions for their collapse. The networks formed on the 2D lattice are characterized by the existence of clusters of highly connected vertices and their life time. As the life time of such clusters tends to be small, the exponent of the power-law distribution changes from γ ≅ 1-2 to γ ≅ 3

  8. Competing spreading processes and immunization in multiplex networks

    International Nuclear Information System (INIS)

    Gao, Bo; Deng, Zhenghong; Zhao, Dawei

    2016-01-01

    Epidemic spreading on physical contact network will naturally introduce the human awareness information diffusion on virtual contact network, and the awareness diffusion will in turn depress the epidemic spreading, thus forming the competing spreading processes of epidemic and awareness in a multiplex networks. In this paper, we study the competing dynamics of epidemic and awareness, both of which follow the SIR process, in a two-layer networks based on microscopic Markov chain approach and numerical simulations. We find that strong capacities of awareness diffusion and self-protection of individuals could lead to a much higher epidemic threshold and a smaller outbreak size. However, the self-awareness of individuals has no obvious effect on the epidemic threshold and outbreak size. In addition, the immunization of the physical contact network under the interplay between of epidemic and awareness spreading is also investigated. The targeted immunization is found performs much better than random immunization, and the awareness diffusion could reduce the immunization threshold for both type of random and targeted immunization significantly.

  9. Multimedia information processing in the SWAN mobile networked computing system

    Science.gov (United States)

    Agrawal, Prathima; Hyden, Eoin; Krzyzanowsji, Paul; Srivastava, Mani B.; Trotter, John

    1996-03-01

    Anytime anywhere wireless access to databases, such as medical and inventory records, can simplify workflow management in a business, and reduce or even eliminate the cost of moving paper documents. Moreover, continual progress in wireless access technology promises to provide per-user bandwidths of the order of a few Mbps, at least in indoor environments. When combined with the emerging high-speed integrated service wired networks, it enables ubiquitous and tetherless access to and processing of multimedia information by mobile users. To leverage on this synergy an indoor wireless network based on room-sized cells and multimedia mobile end-points is being developed at AT&T Bell Laboratories. This research network, called SWAN (Seamless Wireless ATM Networking), allows users carrying multimedia end-points such as PDAs, laptops, and portable multimedia terminals, to seamlessly roam while accessing multimedia data streams from the wired backbone network. A distinguishing feature of the SWAN network is its use of end-to-end ATM connectivity as opposed to the connectionless mobile-IP connectivity used by present day wireless data LANs. This choice allows the wireless resource in a cell to be intelligently allocated amongst various ATM virtual circuits according to their quality of service requirements. But an efficient implementation of ATM in a wireless environment requires a proper mobile network architecture. In particular, the wireless link and medium-access layers need to be cognizant of the ATM traffic, while the ATM layers need to be cognizant of the mobility enabled by the wireless layers. This paper presents an overview of SWAN's network architecture, briefly discusses the issues in making ATM mobile and wireless, and describes initial multimedia applications for SWAN.

  10. Qualia could arise from information processing in local cortical networks.

    Science.gov (United States)

    Orpwood, Roger

    2013-01-01

    Re-entrant feedback, either within sensory cortex or arising from prefrontal areas, has been strongly linked to the emergence of consciousness, both in theoretical and experimental work. This idea, together with evidence for local micro-consciousness, suggests the generation of qualia could in some way result from local network activity under re-entrant activation. This paper explores the possibility by examining the processing of information by local cortical networks. It highlights the difference between the information structure (how the information is physically embodied), and the information message (what the information is about). It focuses on the network's ability to recognize information structures amongst its inputs under conditions of extensive local feedback, and to then assign information messages to those structures. It is shown that if the re-entrant feedback enables the network to achieve an attractor state, then the message assigned in any given pass of information through the network is a representation of the message assigned in the previous pass-through of information. Based on this ability the paper argues that as information is repeatedly cycled through the network, the information message that is assigned evolves from a recognition of what the input structure is, to what it is like, to how it appears, to how it seems. It could enable individual networks to be the site of qualia generation. The paper goes on to show networks in cortical layers 2/3 and 5a have the connectivity required for the behavior proposed, and reviews some evidence for a link between such local cortical cyclic activity and conscious percepts. It concludes with some predictions based on the theory discussed.

  11. Applying Trusted Network Technology To Process Control Systems

    Science.gov (United States)

    Okhravi, Hamed; Nicol, David

    Interconnections between process control networks and enterprise networks expose instrumentation and control systems and the critical infrastructure components they operate to a variety of cyber attacks. Several architectural standards and security best practices have been proposed for industrial control systems. However, they are based on older architectures and do not leverage the latest hardware and software technologies. This paper describes new technologies that can be applied to the design of next generation security architectures for industrial control systems. The technologies are discussed along with their security benefits and design trade-offs.

  12. 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.

  13. 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.

  14. Congestion estimation technique in the optical network unit registration process.

    Science.gov (United States)

    Kim, Geunyong; Yoo, Hark; Lee, Dongsoo; Kim, Youngsun; Lim, Hyuk

    2016-07-01

    We present a congestion estimation technique (CET) to estimate the optical network unit (ONU) registration success ratio for the ONU registration process in passive optical networks. An optical line terminal (OLT) estimates the number of collided ONUs via the proposed scheme during the serial number state. The OLT can obtain congestion level among ONUs to be registered such that this information may be exploited to change the size of a quiet window to decrease the collision probability. We verified the efficiency of the proposed method through simulation and experimental results.

  15. Uncertainty Reduction for Stochastic Processes on Complex Networks

    Science.gov (United States)

    Radicchi, Filippo; Castellano, Claudio

    2018-05-01

    Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.

  16. 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.

  17. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  18. Modeling of an industrial drying process by artificial neural networks

    Directory of Open Access Journals (Sweden)

    E. Assidjo

    2008-09-01

    Full Text Available A suitable method is needed to solve the nonquality problem in the grated coconut industry due to the poor control of product humidity during the process. In this study the possibility of using an artificial neural network (ANN, precisely a Multilayer Perceptron, for modeling the drying step of the production of grated coconut process is highlighted. Drying must confer to the product a final moisture of 3%. Unfortunately, under industrial conditions, this moisture varies from 1.9 to 4.8 %. In order to control this parameter and consequently reduce the proportion of the product that does not meet the humidity specification, a 9-4-1 neural network architecture was established using data gathered from an industrial plant. This Multilayer Perceptron can satisfactorily model the process with less bias, ranging from -0.35 to 0.34%, and can reduce the rate of rejected products from 92% to 3% during the first cycle of drying.

  19. Critical behavior of the contact process in a multiscale network

    Science.gov (United States)

    Ferreira, Silvio C.; Martins, Marcelo L.

    2007-09-01

    Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barabási-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak’s duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. Modeling the Male Reproductive Endocrine Axis: Potential Role for a Delay Mechanism in the Inhibitory Action of Gonadal Steroids on GnRH Pulse Frequency.

    Science.gov (United States)

    Ferasyi, Teuku R; Barrett, P Hugh R; Blache, Dominique; Martin, Graeme B

    2016-05-01

    We developed a compartmental model so we could test mechanistic concepts in the control of the male reproductive endocrine axis. Using SAAM II computer software and a bank of experimental data from male sheep, we began by modeling GnRH-LH feed-forward and LH-T feedback. A key assumption was that the primary control signal comes from a hypothetical neural network (the PULSAR) that emits a digital (pulsatile) signal of variable frequency that drives GnRH secretion in square wave-like pulses. This model produced endocrine profiles that matched experimental observations for the testis-intact animal and for changes in GnRH pulse frequency after castration and T replacement. In the second stage of the model development, we introduced a delay in the negative feedback caused by the aromatization of T to estradiol at the brain level, a concept supported by empirical observations. The simulations showed how changes in the process of aromatization could affect the response of the pulsatile signal to inhibition by steroid feedback. The sensitivity of the PULSAR to estradiol was a critical factor, but the most striking observation was the effect of time delays. With longer delays, there was a reduction in the rate of aromatization and therefore a decrease in local estradiol concentrations, and the outcome was multiple-pulse events in the secretion of GnRH/LH, reflecting experimental observations. In conclusion, our model successfully emulates the GnRH-LH-T-GnRH loop, accommodates a pivotal role for central aromatization in negative feedback, and suggests that time delays in negative feedback are an important aspect of the control of GnRH pulse frequency.

  5. Successful synthesis and thermal stability of immiscible metal Au-Rh, Au-Ir andAu-Ir-Rh nanoalloys

    Science.gov (United States)

    Shubin, Yury; Plyusnin, Pavel; Sharafutdinov, Marat; Makotchenko, Evgenia; Korenev, Sergey

    2017-05-01

    We successfully prepared face-centred cubic nanoalloys in systems of Au-Ir, Au-Rh and Au-Ir-Rh, with large bulk miscibility gaps, in one-run reactions under thermal decomposition of specially synthesised single-source precursors, namely, [AuEn2][Ir(NO2)6], [AuEn2][Ir(NO2)6] х [Rh(NO2)6]1-х and [AuEn2][Rh(NO2)6]. The precursors employed contain all desired metals ‘mixed’ at the atomic level, thus providing significant advantages for obtaining alloys. The observations using high-resolution transmission electron microscopy show that the nanoalloy structures are composed of well-dispersed aggregates of crystalline domains with a mean size of 5 ± 3 nm. Еnergy dispersive x-ray spectroscopy and x-ray powder diffraction (XRD) measurements confirm the formation of AuIr, AuRh, AuIr0.75Rh0.25, AuIr0.50Rh0.50 and AuIr0.25Rh0.75 metastable solid solutions. In situ high-temperature synchrotron XRD (HTXRD) was used to study the formation mechanism of nanoalloys. The observed transformations are described by the ‘conversion chemistry’ mechanism characterised by the primary development of particles comprising atoms of only one type, followed by a chemical reaction resulting in the final formation of a nanoalloy. The obtained metastable nanoalloys exhibit essential thermal stability. Exposure to 180 °C for 30 h does not cause any dealloying process.

  6. Signal Processing Device (SPD) for networked radiation monitoring system

    International Nuclear Information System (INIS)

    Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

    2010-01-01

    A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

  7. 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.

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

    DEFF Research Database (Denmark)

    Parraguez, Pedro

    projects often fail to be on time, on budget, and meeting specifications. Despite the wealth of process models available, previous approaches have been insufficient to provide a networked perspective that allows the challenging combination of organisational and process complexity to unfold. The lack...

  9. Process for forming synapses in neural networks and resistor therefor

    Science.gov (United States)

    Fu, Chi Y.

    1996-01-01

    Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

  10. 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.

  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. 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

  13. 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.

  14. 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

  15. Processing of chromatic information in a deep convolutional neural network.

    Science.gov (United States)

    Flachot, Alban; Gegenfurtner, Karl R

    2018-04-01

    Deep convolutional neural networks are a class of machine-learning algorithms capable of solving non-trivial tasks, such as object recognition, with human-like performance. Little is known about the exact computations that deep neural networks learn, and to what extent these computations are similar to the ones performed by the primate brain. Here, we investigate how color information is processed in the different layers of the AlexNet deep neural network, originally trained on object classification of over 1.2M images of objects in their natural contexts. We found that the color-responsive units in the first layer of AlexNet learned linear features and were broadly tuned to two directions in color space, analogously to what is known of color responsive cells in the primate thalamus. Moreover, these directions are decorrelated and lead to statistically efficient representations, similar to the cardinal directions of the second-stage color mechanisms in primates. We also found, in analogy to the early stages of the primate visual system, that chromatic and achromatic information were segregated in the early layers of the network. Units in the higher layers of AlexNet exhibit on average a lower responsivity for color than units at earlier stages.

  16. Processes linked to contact changes in adoptive kinship networks.

    Science.gov (United States)

    Dunbar, Nora; van Dulmen, Manfred H M; Ayers-Lopez, Susan; Berge, Jerica M; Christian, Cinda; Gossman, Ginger; Henney, M Susan M; Mendenhall, Tai J; Grotevant, Harold D; McRoy, Ruth G

    2006-12-01

    The purpose of this study was to reveal underlying processes in adoptive kinship networks that experienced increases or decreases in levels of openness during the child's adolescent years. Intensive case study analyses were conducted for 8 adoptive kinship networks (each including an adoptive mother, adoptive father, adopted adolescent, and birth mother), half of whom had experienced an increase in openness from indirect (mediated) to direct (fully disclosed) contact and half of whom had ceased indirect contact between Waves 1 and 2 of a longitudinal study. Adoptive mothers tended to be more involved in contact with the birth mother than were adoptive fathers or adopted adolescents. Members of adoptive kinship networks in which a decrease in level of contact took place had incongruent perspectives about who initiated the stop in contact and why the stop took place. Birth mothers were less satisfied with their degree of contact than were adoptive parents. Adults' satisfaction with contact was related to feelings of control over type and amount of interactions and permeability of family boundaries. In all adoptive kinship networks, responsibility for contact had shifted toward the adopted adolescent regardless of whether the adolescent was aware of this change in responsibility.

  17. Proceedings: Distributed digital systems, plant process computers, and networks

    International Nuclear Information System (INIS)

    1995-03-01

    These are the proceedings of a workshop on Distributed Digital Systems, Plant Process Computers, and Networks held in Charlotte, North Carolina on August 16--18, 1994. The purpose of the workshop was to provide a forum for technology transfer, technical information exchange, and education. The workshop was attended by more than 100 representatives of electric utilities, equipment manufacturers, engineering service organizations, and government agencies. The workshop consisted of three days of presentations, exhibitions, a panel discussion and attendee interactions. Original plant process computers at the nuclear power plants are becoming obsolete resulting in increasing difficulties in their effectiveness to support plant operations and maintenance. Some utilities have already replaced their plant process computers by more powerful modern computers while many other utilities intend to replace their aging plant process computers in the future. Information on recent and planned implementations are presented. Choosing an appropriate communications and computing network architecture facilitates integrating new systems and provides functional modularity for both hardware and software. Control room improvements such as CRT-based distributed monitoring and control, as well as digital decision and diagnostic aids, can improve plant operations. Commercially available digital products connected to the plant communications system are now readily available to provide distributed processing where needed. Plant operations, maintenance activities, and engineering analyses can be supported in a cost-effective manner. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database

  18. 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.

  19. Cellular Neural Network for Real Time Image Processing

    International Nuclear Information System (INIS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-01-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  20. Changed processing of visual sexual stimuli under GnRH-therapy – a single case study in pedophilia using eye tracking and fMRI

    Science.gov (United States)

    2014-01-01

    Background Antiandrogen therapy (ADT) has been used for 30 years to treat pedophilic patients. The aim of the treatment is a reduction in sexual drive and, in consequence, a reduced risk of recidivism. Yet the therapeutic success of antiandrogens is uncertain especially regarding recidivism. Meta-analyses and reviews report only moderate and often mutually inconsistent effects. Case presentation Based on the case of a 47 year old exclusively pedophilic forensic inpatient, we examined the effectiveness of a new eye tracking method and a new functional magnetic resonance imaging (fMRI)-design in regard to the evaluation of ADT in pedophiles. We analyzed the potential of these methods in exploring the impact of ADT on automatic and controlled attentional processes in pedophiles. Eye tracking and fMRI measures were conducted before the initial ADT as well as four months after the onset of ADT. The patient simultaneously viewed an image of a child and an image of an adult while eye movements were measured. During the fMRI-measure the same stimuli were presented subliminally. Eye movements demonstrated that controlled attentional processes change under ADT, whereas automatic processes remained mostly unchanged. We assume that these results reflect either the increased ability of the patient to control his eye movements while viewing prepubertal stimuli or his better ability to manipulate his answer in a socially desirable manner. Unchanged automatic attentional processes could reflect the stable pedophilic preference of the patient. Using fMRI, the subliminal presentation of sexually relevant stimuli led to changed activation patterns under the influence of ADT in occipital and parietal brain regions, the hippocampus, and also in the orbitofrontal cortex. We suggest that even at an unconscious level ADT can lead to changed processing of sexually relevant stimuli, reflecting changes of cognitive and perceptive automatic processes. Conclusion We are convinced that our

  1. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1992-01-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper the authors illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. The authors also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. The authors outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. The authors also present some of the difficulties encountered in applying these networks

  2. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1991-07-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper we illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. We also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. We outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. We also present some of the difficulties encountered in applying these networks. (author) 13 figs., 9 refs

  3. Competing contact processes in the Watts-Strogatz network

    Science.gov (United States)

    Rybak, Marcin; Malarz, Krzysztof; Kułakowski, Krzysztof

    2016-06-01

    We investigate two competing contact processes on a set of Watts-Strogatz networks with the clustering coefficient tuned by rewiring. The base for network construction is one-dimensional chain of N sites, where each site i is directly linked to nodes labelled as i ± 1 and i ± 2. So initially, each node has the same degree k i = 4. The periodic boundary conditions are assumed as well. For each node i the links to sites i + 1 and i + 2 are rewired to two randomly selected nodes so far not-connected to node i. An increase of the rewiring probability q influences the nodes degree distribution and the network clusterization coefficient 𝓒. For given values of rewiring probability q the set 𝓝(q)={𝓝1,𝓝2,...,𝓝 M } of M networks is generated. The network's nodes are decorated with spin-like variables s i ∈ { S,D }. During simulation each S node having a D-site in its neighbourhood converts this neighbour from D to S state. Conversely, a node in D state having at least one neighbour also in state D-state converts all nearest-neighbours of this pair into D-state. The latter is realized with probability p. We plot the dependence of the nodes S final density n S T on initial nodes S fraction n S 0. Then, we construct the surface of the unstable fixed points in (𝓒, p, n S 0) space. The system evolves more often toward n S T for (𝓒, p, n S 0) points situated above this surface while starting simulation with (𝓒, p, n S 0) parameters situated below this surface leads system to n S T =0. The points on this surface correspond to such value of initial fraction n S * of S nodes (for fixed values 𝓒 and p) for which their final density is n S T=1/2.

  4. 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.

  5. Distributed Sensing and Processing for Multi-Camera Networks

    Science.gov (United States)

    Sankaranarayanan, Aswin C.; Chellappa, Rama; Baraniuk, Richard G.

    Sensor networks with large numbers of cameras are becoming increasingly prevalent in a wide range of applications, including video conferencing, motion capture, surveillance, and clinical diagnostics. In this chapter, we identify some of the fundamental challenges in designing such systems: robust statistical inference, computationally efficiency, and opportunistic and parsimonious sensing. We show that the geometric constraints induced by the imaging process are extremely useful for identifying and designing optimal estimators for object detection and tracking tasks. We also derive pipelined and parallelized implementations of popular tools used for statistical inference in non-linear systems, of which multi-camera systems are examples. Finally, we highlight the use of the emerging theory of compressive sensing in reducing the amount of data sensed and communicated by a camera network.

  6. 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)

    1998-12-31

    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.

  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. 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.

  9. Competing spreading processes on multiplex networks: awareness and epidemics.

    Science.gov (United States)

    Granell, Clara; Gómez, Sergio; Arenas, Alex

    2014-07-01

    Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013).] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

  10. 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.

    2015-01-01

    SUMMARY Objective 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. Methods 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 ispilateral and contralateral to the side of seizure onset were delineated in TLE and compared to the healthy controls with right and left side combined. Diffusion tensor images were acquired to investigate structural connectivity between face regions that differed in fMRI signals between the two groups. Results In temporal lobe epilepsy, 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 while controls showed no significant asymmetry. Furthermore, compared to controls, patients with TLE showed decreased activation of the occipital face responsive region in the ipsilateral side and an increased activity of the anterior temporal lobe in the contralateral side 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 temporal lobe epilepsy showed reduced integrity. Significance 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. PMID:25823855

  11. 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

  12. 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.

  13. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

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

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...

  14. 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.

  15. 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.

  16. Integration of social networks in the teaching and learning process

    Directory of Open Access Journals (Sweden)

    Cynthia Dedós Reyes

    2015-09-01

    Full Text Available In this research we explored the integration of social media in the process of learning and teaching, in a private higher education institution, in Puerto Rico. Attention was given to the perspectives of teachers and students. The participants —9 part-time teachers and 118 students— were selected based on availability. The results showed that teachers and students alike use social the network You Tube for academic purposes; and use Facebook, Twitter, and blogs for social purposes and entertainment. Results also revealed that there is no significant contrast between the perspectives of teachers and students digital immigrants.

  17. Use of neural networks in process engineering. Thermodynamics, diffusion, and process control and simulation applications

    International Nuclear Information System (INIS)

    Otero, F

    1998-01-01

    This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control

  18. Magnetic properties of Co-Rh and Ni-Rh nanowires

    International Nuclear Information System (INIS)

    Sondon, Tristana; Saul, Andres; Guevara, Javier

    2007-01-01

    We have calculated the magnetic properties of pure Ni, Co and Rh, and alloyed Co-Rh and Ni-Rh free-standing nanowires by an ab initio method. We have found that the pure Co and Ni wires present an enhanced magnetic moment with respect to their bulk values, and we have obtained that a magnetic order appears for pure Rh wires. For concentrations up to 50% Rh, in the alloyed Ni-Rh linear chains there is an enhancement of the total magnetic moment with respect to the pure nanowires, and in the case of Co-Rh the alloying with Rh enhances the Co magnetic moment. In both systems we obtain very high Rh magnetic moments

  19. Characterization of Rh films on Ta(110)

    International Nuclear Information System (INIS)

    Jiang, L.Q.; Ruckman, M.W.; Strongin, M.

    1989-01-01

    The surface and electronic structure of Rh films on Ta(110) up to several monolayers thick on Ta(110) are characterized by photoemission, Auger emission, low energy electron diffraction and low energy ion scattering. From the variation of the Rh Auger peak-to-peak intensity as a function of evaporation time, Rh/Ta(110) appears to grow in the Stranski-Krastanov mode at room temperature. However, the LEIS data show that the Rh adatoms begin to cluster on Ta(110) before growth of the monolayer is completed. Diffuse LEED scattering suggests that the Rh films are disordered. Photoemission shows that Rh chemisorption on Ta(110) generates two peaks located at 1.2 and 2. 5 eV binding energy during the initial phase of thin film growth (0 3.7 ML). Photoemission data for CO covered surfaces show that CO dissociates on the Rh/Ta(110) surface for Rh coverages less than 2.5 ML and also show that the Rh clusters develop at least one site capable of molecular CO adsorption above 0.3 ML Rh coverage. 38 refs., 5 figs

  20. A method of network topology optimization design considering application process characteristic

    Science.gov (United States)

    Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

    2018-03-01

    Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

  1. Final Design Report for the RH LLW Disposal Facility (RDF) Project, Revision 3

    International Nuclear Information System (INIS)

    Austad, Stephanie Lee

    2015-01-01

    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.

  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. USC orthogonal multiprocessor for image processing with neural networks

    Science.gov (United States)

    Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

    1990-07-01

    This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

  4. Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process

    Directory of Open Access Journals (Sweden)

    Nicolae Morariu

    2008-01-01

    Full Text Available This paper aims to describe the implementa-tion of a neural network and a genetic algorithm system in order to forecast certain economic indicators of a free market economy. In a free market economy forecasting process precedes the economic planning (a management function, providing important information for the result of the last process. Forecasting represents a starting point in setting of target for a firm, an organization or even a branch of the economy. Thus, the forecasting method used can influence in a significant mode the evolution of an entity. In the following we will describe the forecasting of an economic indicator using two intelligent systems. The difference between the results obtained by this two systems are described in chapter IV.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. Eigenanalysis of a neural network for optic flow processing

    International Nuclear Information System (INIS)

    Weber, F; Eichner, H; Borst, A; Cuntz, H

    2008-01-01

    Flies gain information about self-motion during free flight by processing images of the environment moving across their retina. The visual course control center in the brain of the blowfly contains, among others, a population of ten neurons, the so-called vertical system (VS) cells that are mainly sensitive to downward motion. VS cells are assumed to encode information about rotational optic flow induced by self-motion (Krapp and Hengstenberg 1996 Nature 384 463-6). Recent evidence supports a connectivity scheme between the VS cells where neurons with neighboring receptive fields are connected to each other by electrical synapses at the axonal terminals, whereas the boundary neurons in the network are reciprocally coupled via inhibitory synapses (Haag and Borst 2004 Nat. Neurosci. 7 628-34; Farrow et al 2005 J. Neurosci. 25 3985-93; Cuntz et al 2007 Proc. Natl Acad. Sci. USA). Here, we investigate the functional properties of the VS network and its connectivity scheme by reducing a biophysically realistic network to a simplified model, where each cell is represented by a dendritic and axonal compartment only. Eigenanalysis of this model reveals that the whole population of VS cells projects the synaptic input provided from local motion detectors on to its behaviorally relevant components. The two major eigenvectors consist of a horizontal and a slanted line representing the distribution of vertical motion components across the fly's azimuth. They are, thus, ideally suited for reliably encoding translational and rotational whole-field optic flow induced by respective flight maneuvers. The dimensionality reduction compensates for the contrast and texture dependence of the local motion detectors of the correlation-type, which becomes particularly pronounced when confronted with natural images and their highly inhomogeneous contrast distribution

  12. Characterization of Rh films on Ta(110)

    International Nuclear Information System (INIS)

    Jiang, L.Q.; Ruckman, M.W.; Strongin, M.

    1990-01-01

    The surface and electronic structure of Rh films on Ta(110) up to several monolayers thick on Ta(110) are characterized by photoemission, Auger emission, low-energy electron diffraction (LEED) and low-energy ion scattering (LEIS). From the variation of the Rh Auger peak-to-peak intensity as a function of evaporation time, Rh appears to grow in the Stranski--Krastanov mode at room temperature. However, the LEIS data show that the Rh adatoms begin to cluster on Ta(110) before growth of the monolayer is completed. Diffuse LEED scattering suggests that the Rh films are disordered. Photoemission shows that Rh chemisorption on Ta(110) generates two peaks located at -1.5 and -2.5 eV binding energy during the initial phase of thin-film growth (0 3.7 ML). CO dissociates on the Rh/Ta(110) surface for Rh coverages<2.5 ML and the surface develops a site capable of molecular CO adsorption above 0.3-ML Rh coverage

  13. PHANTOMS: Nanotechnology network for information processing and storage*

    Science.gov (United States)

    Correia, Antonio

    2001-06-01

    It is now accepted that nanotechnology is one of the key enabling technologies for sustainable and competitive growth in Europe. Nanoelectronics is certainly the branch with the most significant commercial impact and covers a huge range of interdisciplinary areas of research and development such as molecular electronics, bioelectronics, spintronics, nanoimprint, nanoscale optics, lithography, architecture and nanoprobes. It is also accepted that a significant investment will be required to ensure Europe's competitiveness in nanotechnology. At this stage it is impossible to predict the exact course that the nanoelectronics revolution will take and, therefore, its effect on our daily lives. We can, however, be resonably sure that nanotechnology will have a profound impact on the future development of many commercial sectors. The greatest impact is likely to be in the electronics sector, where the demand for technologies permitting faster processing of data at lower costs will remain undiminished. In order to avoid European industry and R & D being left behind the United States and Japan in this fast emerging nanoelectronics field, the PHANTOMS Network Scheme will promote European science and research through a pluri-national networking action, put together research capacities present in the various European regions and stimulate commercial nanoelectronic applications.

  14. 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.

  15. Developmental process emerges from extended brain-body-behavior networks

    Science.gov (United States)

    Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

    2014-01-01

    Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

  16. Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

    Science.gov (United States)

    Gao, Chao; Tang, Shaoting; Li, Weihua; Yang, Yaqian; Zheng, Zhiming

    2018-04-01

    Recently, the interplay between epidemic spreading and awareness diffusion has aroused the interest of many researchers, who have studied models mainly based on linear coupling relations between information and epidemic layers. However, in real-world networks the relation between two layers may be closely correlated with the property of individual nodes and exhibits nonlinear dynamical features. Here we propose a nonlinear coupled information-epidemic model (I-E model) and present a comprehensive analysis in a more generalized scenario where the upload rate differs from node to node, deletion rate varies between susceptible and infected states, and infection rate changes between unaware and aware states. In particular, we develop a theoretical framework of the intra- and inter-layer dynamical processes with a microscopic Markov chain approach (MMCA), and derive an analytic epidemic threshold. Our results suggest that the change of upload and deletion rate has little effect on the diffusion dynamics in the epidemic layer.

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

    Science.gov (United States)

    Orbán, Levente L; Chartier, Sylvain

    2015-01-01

    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.

  18. 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

  19. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    Science.gov (United States)

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high. Copyright © 2015 Elsevier

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    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. PMID:26505473

  4. 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.

  5. 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

  6. 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

    serum antibodies exhibited cross-strain functional growth inhibition activity (GIA) in vitro, targeted linear and conformational epitopes within RH5, and inhibited key interactions within the RH5 invasion complex. This is the first time to our knowledge that substantial RH5-specific responses have been...

  7. 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...

  8. RH-TRU Waste Content Codes

    Energy Technology Data Exchange (ETDEWEB)

    Washington TRU Solutions

    2007-07-01

    The Remote-Handled Transuranic (RH-TRU) Content Codes (RH-TRUCON) document describes the inventory of RH-TRU waste within the transportation parameters specified by the Remote-Handled Transuranic Waste Authorized Methods for Payload Control (RH-TRAMPAC).1 The RH-TRAMPAC defines the allowable payload for the RH-TRU 72-B. This document is a catalog of RH-TRU 72-B authorized contents by site. A content code is defined by the following components: • A two-letter site abbreviation that designates the physical location of the generated/stored waste (e.g., ID for Idaho National Laboratory [INL]). The site-specific letter designations for each of the sites are provided in Table 1. • A three-digit code that designates the physical and chemical form of the waste (e.g., content code 317 denotes TRU Metal Waste). For RH-TRU waste to be transported in the RH-TRU 72-B, the first number of this three-digit code is “3.” The second and third numbers of the three-digit code describe the physical and chemical form of the waste. Table 2 provides a brief description of each generic code. Content codes are further defined as subcodes by an alpha trailer after the three-digit code to allow segregation of wastes that differ in one or more parameter(s). For example, the alpha trailers of the subcodes ID 322A and ID 322B may be used to differentiate between waste packaging configurations. As detailed in the RH-TRAMPAC, compliance with flammable gas limits may be demonstrated through the evaluation of compliance with either a decay heat limit or flammable gas generation rate (FGGR) limit per container specified in approved content codes. As applicable, if a container meets the watt*year criteria specified by the RH-TRAMPAC, the decay heat limits based on the dose-dependent G value may be used as specified in an approved content code. If a site implements the administrative controls outlined in the RH-TRAMPAC and Appendix 2.4 of the RH-TRU Payload Appendices, the decay heat or FGGR

  9. Managing logistical processes in franchise retail trade networks

    OpenAIRE

    Grigorenko Tatyana N.; Kochubey Dmitriy V.

    2013-01-01

    The article analyses approaches to organisation of internal logistics of franchise trade networks and methodical provision of assessment of results of logistical activity at companies of franchise networks. The article justifies urgency of application of referent models of management of supply chains in construction of a system of management of logistical activity of franchise networks. It offers classification of models of management of internal logistics of franchise retail trade networks. ...

  10. Hydrogen Detection With a Gas Sensor Array – Processing and Recognition of Dynamic Responses Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Gwiżdż Patryk

    2015-03-01

    Full Text Available An array consisting of four commercial gas sensors with target specifications for hydrocarbons, ammonia, alcohol, explosive gases has been constructed and tested. The sensors in the array operate in the dynamic mode upon the temperature modulation from 350°C to 500°C. Changes in the sensor operating temperature lead to distinct resistance responses affected by the gas type, its concentration and the humidity level. The measurements are performed upon various hydrogen (17-3000 ppm, methane (167-3000 ppm and propane (167-3000 ppm concentrations at relative humidity levels of 0-75%RH. The measured dynamic response signals are further processed with the Discrete Fourier Transform. Absolute values of the dc component and the first five harmonics of each sensor are analysed by a feed-forward back-propagation neural network. The ultimate aim of this research is to achieve a reliable hydrogen detection despite an interference of the humidity and residual gases.

  11. Coarse-grained simulation of a real-time process control network under peak load

    International Nuclear Information System (INIS)

    George, A.D.; Clapp, N.E. Jr.

    1992-01-01

    This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

  12. 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.

  13. New superconductor LaRhSb

    International Nuclear Information System (INIS)

    Nishigori, S.; Moriwaki, H.; Suzuki, T.; Fujita, T.; Tanaka, H.; Takabatake, T.; Fujii, H.

    1994-01-01

    Superconductivity in LaRhSb was newly found below the transition temperature T c = 2.67 K by the measurements of the electrical resistivity, magnetic susceptibility and specific heat in magnetic fields. The characteristics of the superconductivity determined in this study indicate that LaRhSb is a type II superconductor following the BCS theory. (orig.)

  14. Rh-catalyzed linear hydroformylation of styrene

    NARCIS (Netherlands)

    Boymans, E.H.; Janssen, M.C.C.; Mueller, C.; Lutz, M.; Vogt, D.

    2012-01-01

    Usually the Rh-catalyzed hydroformylation of styrene predominantly yields the branched, chiral aldehyde. An inversion of regioselectivity can be achieved using strong p-acceptor ligands. Binaphthol-based diphosphite and bis(dipyrrolyl-phosphorodiamidite) ligands were applied in the Rh-catalyzed

  15. High level cognitive information processing in neural networks

    Science.gov (United States)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  16. Exploiting global information in complex network repair processes

    Institute of Scientific and Technical Information of China (English)

    Tianyu WANG; Jun ZHANG; Sebastian WANDELT

    2017-01-01

    Robustness of complex networks has been studied for decades,with a particular focus on network attack.Research on network repair,on the other hand,has been conducted only very lately,given the even higher complexity and absence of an effective evaluation metric.A recently proposed network repair strategy is self-healing,which aims to repair networks for larger compo nents at a low cost only with local information.In this paper,we discuss the effectiveness and effi ciency of self-healing,which limits network repair to be a multi-objective optimization problem and makes it difficult to measure its optimality.This leads us to a new network repair evaluation metric.Since the time complexity of the computation is very high,we devise a greedy ranking strategy.Evaluations on both real-world and random networks show the effectiveness of our new metric and repair strategy.Our study contributes to optimal network repair algorithms and provides a gold standard for future studies on network repair.

  17. Simulating the formation of keratin filament networks by a piecewise-deterministic Markov process.

    Science.gov (United States)

    Beil, Michael; Lück, Sebastian; Fleischer, Frank; Portet, Stéphanie; Arendt, Wolfgang; Schmidt, Volker

    2009-02-21

    Keratin intermediate filament networks are part of the cytoskeleton in epithelial cells. They were found to regulate viscoelastic properties and motility of cancer cells. Due to unique biochemical properties of keratin polymers, the knowledge of the mechanisms controlling keratin network formation is incomplete. A combination of deterministic and stochastic modeling techniques can be a valuable source of information since they can describe known mechanisms of network evolution while reflecting the uncertainty with respect to a variety of molecular events. We applied the concept of piecewise-deterministic Markov processes to the modeling of keratin network formation with high spatiotemporal resolution. The deterministic component describes the diffusion-driven evolution of a pool of soluble keratin filament precursors fueling various network formation processes. Instants of network formation events are determined by a stochastic point process on the time axis. A probability distribution controlled by model parameters exercises control over the frequency of different mechanisms of network formation to be triggered. Locations of the network formation events are assigned dependent on the spatial distribution of the soluble pool of filament precursors. Based on this modeling approach, simulation studies revealed that the architecture of keratin networks mostly depends on the balance between filament elongation and branching processes. The spatial distribution of network mesh size, which strongly influences the mechanical characteristics of filament networks, is modulated by lateral annealing processes. This mechanism which is a specific feature of intermediate filament networks appears to be a major and fast regulator of cell mechanics.

  18. 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.

  19. 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.

  20. 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.

  1. 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 (Qua...... and financial risk models. Through the solution of a small benchmark problem, the impact of financial factors on the optimal network configuration is presented and discussed....

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. 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

  7. 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

  8. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

  9. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

  10. 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...

  11. 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.

  12. On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes

    Science.gov (United States)

    Russo, Giovanni; Shorten, Robert

    2018-04-01

    This paper is concerned with the study of common noise-induced synchronization phenomena in complex networks of diffusively coupled nonlinear systems. We consider the case where common noise propagation depends on the network state and, as a result, the noise diffusion process at the nodes depends on the state of the network. For such networks, we present an algebraic sufficient condition for the onset of synchronization, which depends on the network topology, the dynamics at the nodes, the coupling strength and the noise diffusion. Our result explicitly shows that certain noise diffusion processes can drive an unsynchronized network towards synchronization. In order to illustrate the effectiveness of our result, we consider two applications: collective decision processes and synchronization of chaotic systems. We explicitly show that, in the former application, a sufficiently large noise can drive a population towards a common decision, while, in the latter, we show how common noise can synchronize a network of Lorentz chaotic systems.

  13. An exploratory study on the potential value add of social networking to the Entrepreneurial process

    Directory of Open Access Journals (Sweden)

    Alex Antonites

    2011-12-01

    Full Text Available It is widely established in scientific literature that entrepreneurship directly contributes to both employment generation and economic growth. Entrepreneurship is said to be subject to a very specific process which includes opportunity recognition, resource allocation, innovation and networking. Networking specifically, is an essential part of the entrepreneurial process as it is employed to assist entrepreneurs to capitalise on opportunities, allocate resources, find ways to innovate and contest ambiguity. With the advent of Web 2.0 and online social networking platforms the way in which people exchange information and network has changed significantly and has spawned a new social culture on a global level. The purpose of this study is to examine the value that online social networking adds to the entrepreneurial process, specifically focussing on the South African landscape. Keywords and phrases: Entrepreneurship; Networking; Social capital; Social networking; Social media

  14. 103Ru/103mRh generator

    International Nuclear Information System (INIS)

    Bartos, B.; Kowalska, E.; Bilewicz, A.; Skarnemark, G.

    2009-01-01

    103m Rh is a very promising radionuclide for Auger electron therapy due to its very low photon/electron ratio. The goal of the present work was the elaboration a method for production of large quantities of 103m Rh for generator system. It was found that the combination of solvent extraction with evaporation of 103 RuO 4 followed by decomposition of H 5 IO 6 makes it possible to produce 103m Rh of high radionuclidic and chemical purity. (author)

  15. Scattering of fast neutrons from 103Rh

    International Nuclear Information System (INIS)

    Barnard, E.; Reitmann, D.

    1978-01-01

    The scattering of fast neutrons from 103 Rh was studied by means of (n, n), (n, n') and (n, n'γ) measurements at neutron energies up to 2 MeV. More than fifty unknown γ-transitions were identified and a level scheme established which includes fifteen unreported excited states. Branching ratios, spins and parities for these levels were deduced, as well as the effective activation cross sections for the 103 Rh(n, n')sup(103m)Rh reaction. The results are compared with existing data and with calculations based on the optical and statistical models. (Auth.)

  16. 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....

  17. 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.

  18. Network design in a process of transition; Netzberechnung im Wandel

    Energy Technology Data Exchange (ETDEWEB)

    Schmieg, M. [Digsilent GmbH, Gomaringen (Germany)

    1998-08-01

    In the wake of liberalisation of the energy markets, new problems are encountered in connection with transmission network planning and operation, including a shift in aspects in network design, and new requirements are to be considered. The PowerFactory software warrants to network owners reliable performance of the necessary calculation and monitoring functions along with features allowing easy adaptation to individual operating concepts. (orig./CB) [Deutsch] Die Liberalisierung der Energiemaerkte wirft in puncto Netzplanung und Netzbetrieb neue Fragen auf, verschiebt die Schwerpunkte der Netzberechnung und stellt veraenderte Anforderungen. Die PowerFactory-Software verspricht dem Anwender die langfristig notwendigen Berechungs- und Ueberwachungsfunktionen und laesst sich einfach an individuelle Betriebskonzepte anpassen. (orig.)

  19. Information quality in dynamic networked business process management

    NARCIS (Netherlands)

    Rasouli, M.; Eshuis, H.; Trienekens, J.J.M.; Kusters, R.J.; Grefen, P.W.P.J.; Devruyne, C.; Panetto, H.; Meersman, R.; Dillon, T.; Weichhart, G.; An, Y.; Ardagna, C.A.

    2015-01-01

    The competition in globalized markets forces organizations to provide mass-customized integrated solutions for customers. Mass-customization of integrated solutions by business network requires adaptive interactions between parties to address emerging requirements of customers. These adaptive

  20. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  1. 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.

  2. Initial process of updating the core of a network

    OpenAIRE

    TORTAJADA RODRÍGUEZ, MARCOS

    2013-01-01

    This report concerns my internship in the MI2S between the months of March and July of 2013, being employed by the Centre National de Recherche Scientifique. The CNRS is the most important public organization for scientific research, its aim is to coordinate the activities of the laboratories to make the scientific research more efficient. As a part of my course of Computer Networks and Telecommunications specializing in Wireless Networks and Security (a French professional bac...

  3. Neural network post-processing of grayscale optical correlator

    Science.gov (United States)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  4. Social Networking: Product or Process and What Shade of Grey?

    OpenAIRE

    Gelfand, Julia (UCI); Lin, Anthony (UCI); GreyNet, Grey Literature Network Service

    2011-01-01

    Social networking which debuted in 1997 is now an established and common method of communication with much variation and is increasingly related to and supportive of academic publishing, scholarship and generating new information. Some of the most mature and popular sites are Facebook, Bebo, Twitter, Linked-In and Plaxo plus many more specialized examples. As many professional societies and individuals choose to develop a presence on social networking sites (SNSs), the utility of them has b...

  5. Absolute calibration of the Rh-103(n,n')Rh-103m reaction rate

    International Nuclear Information System (INIS)

    Taylor, W.H.; Murphy, M.F.; March, M.R.

    1979-05-01

    The uncertainties in determining the absolute values of the Rh-103(n, n') Rh-103m reaction rate (which is widely used as a neutron damage flux monitor) have been reduced to approximately +-5%. This has been achieved with the use of a calibrated source of Pd-103-Rh-103m activity supplied by the IAEA. Agreement to within 3% between measured and calculated values of the reaction rate (normalised to the U-238 fission rate) has been achieved. (author)

  6. 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.

  7. Third Party Referrals in the Venture Capital Financing Process: Do Network Ties Matter?

    NARCIS (Netherlands)

    Heuven, J.M.J.

    2008-01-01

    In this paper we focus on the role of third party referrals in the venture capital funding process. Taking network theory as our theoretical perspective we explore if and how third parties play a role in the funding process. Hereby we focus on both the network ties between new venture teams and

  8. 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...

  9. The Interaction between Personality, Social Network Position and Involvement in Innovation Process

    NARCIS (Netherlands)

    E. Dolgova (Evgenia); W. van Olffen (Woody); F.A.J. van den Bosch (Frans); H.W. Volberda (Henk)

    2010-01-01

    textabstractAbstract This dissertation proposal investigates how personality and individuals’ social network position affect individuals’ involvement into the innovation process. It posits that people would feel inclined to become involved into the different phases of the innovation process

  10. Impact of degree truncation on the spread of a contagious process on networks.

    Science.gov (United States)

    Harling, Guy; Onnela, Jukka-Pekka

    2018-03-01

    Understanding how person-to-person contagious processes spread through a population requires accurate information on connections between population members. However, such connectivity data, when collected via interview, is often incomplete due to partial recall, respondent fatigue or study design, e.g., fixed choice designs (FCD) truncate out-degree by limiting the number of contacts each respondent can report. Past research has shown how FCD truncation affects network properties, but its implications for predicted speed and size of spreading processes remain largely unexplored. To study the impact of degree truncation on predictions of spreading process outcomes, we generated collections of synthetic networks containing specific properties (degree distribution, degree-assortativity, clustering), and also used empirical social network data from 75 villages in Karnataka, India. We simulated FCD using various truncation thresholds and ran a susceptible-infectious-recovered (SIR) process on each network. We found that spreading processes propagated on truncated networks resulted in slower and smaller epidemics, with a sudden decrease in prediction accuracy at a level of truncation that varied by network type. Our results have implications beyond FCD to truncation due to any limited sampling from a larger network. We conclude that knowledge of network structure is important for understanding the accuracy of predictions of process spread on degree truncated networks.

  11. 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.

  12. Comparison of long GnRH agonist versus GnRH antagonist protocol in poor responders

    Directory of Open Access Journals (Sweden)

    Sadık Şahin

    2014-12-01

    Full Text Available Objective: To compare long GnRH agonist with GnRH antagonist protocol in poor responders. Materials and Methods: Medical charts of 531 poor responder women undergoing in-vitro fertilization (IVF cycle at Zeynep Kamil Maternity and Children’s Hospital, IVF Center were retrospectively analysed. Those who received at least 300 IU/daily gonadotropin and had ≤3 oocytes retrieved were enrolled in the study. Poor responders were categorized into two groups as those who received long GnRH agonist or GnRH antagonist regimen. Results: Treatment duration and total gonadotropin dosage were significantly higher in women undergoing the long GnRH agonist regimen compared with the GnRH antagonist regimen (p<0.001 for both. Although the number of total and mature oocytes retrieved was similar between the groups, good quality embryos were found to be higher in the GnRH antagonist regimen. The day of embryo transfer and number of transferred embryos were similar in the groups. No statistically significant differences were detected in pregnancy (10.5% vs 14.1%, clinical pregnancy (7.7% vs 10.6% and early pregnancy loss rates (27.2% vs 35% between the groups. Conclusion: GnRH antagonist regimen may be preferable to long GnRH regimen as it could decrease the cost and treatment duration in poor responders.

  13. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

    Science.gov (United States)

    Zhang, Wenhao; Li, Hanyu; Yang, Minda; Mesgarani, Nima

    2016-03-01

    A characteristic property of biological neurons is their ability to dynamically change the synaptic efficacy in response to variable input conditions. This mechanism, known as synaptic depression, significantly contributes to the formation of normalized representation of speech features. Synaptic depression also contributes to the robust performance of biological systems. In this paper, we describe how synaptic depression can be modeled and incorporated into deep neural network architectures to improve their generalization ability. We observed that when synaptic depression is added to the hidden layers of a neural network, it reduces the effect of changing background activity in the node activations. In addition, we show that when synaptic depression is included in a deep neural network trained for phoneme classification, the performance of the network improves under noisy conditions not included in the training phase. Our results suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions.

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

    DEFF Research Database (Denmark)

    Fjelde, Tina

    2002-01-01

    /s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

  15. 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...... 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....

  16. Modeling Wireless Sensor Networks for Monitoring in Biological Processes

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil

    parameters, as the use of wired sensors is impractical. In this thesis, a ZigBee based wireless sensor network was employed and only a part of the herd was monitored, as monitoring each individual animal in a large herd under practical conditions is inefficient. Investigations to show that the monitored...... (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...

  17. Adaptive Smoothing in fMRI Data Processing Neural Networks

    DEFF Research Database (Denmark)

    Vilamala, Albert; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

    2017-01-01

    in isolation. With the advent of new tools for deep learning, recent work has proposed to turn these pipelines into end-to-end learning networks. This change of paradigm offers new avenues to improvement as it allows for a global optimisation. The current work aims at benefitting from this paradigm shift...... by defining a smoothing step as a layer in these networks able to adaptively modulate the degree of smoothing required by each brain volume to better accomplish a given data analysis task. The viability is evaluated on real fMRI data where subjects did alternate between left and right finger tapping tasks....

  18. Virtual optical network provisioning with unified service logic processing model for software-defined multidomain optical networks

    Science.gov (United States)

    Zhao, Yongli; Li, Shikun; Song, Yinan; Sun, Ji; Zhang, Jie

    2015-12-01

    Hierarchical control architecture is designed for software-defined multidomain optical networks (SD-MDONs), and a unified service logic processing model (USLPM) is first proposed for various applications. USLPM-based virtual optical network (VON) provisioning process is designed, and two VON mapping algorithms are proposed: random node selection and per controller computation (RNS&PCC) and balanced node selection and hierarchical controller computation (BNS&HCC). Then an SD-MDON testbed is built with OpenFlow extension in order to support optical transport equipment. Finally, VON provisioning service is experimentally demonstrated on the testbed along with performance verification.

  19. 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.

  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...

  1. 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

  2. Hypersensitivity reaction with intravenous GnRH after pulsatile subcutaneous GnRH treatment in male hypogonadotrophic hypogonadism.

    OpenAIRE

    Popović, V.; Milosević, Z.; Djukanović, R.; Micić, D.; Nesović, M.; Manojlović, D.; Djordjević, P.; Mićić, J.

    1988-01-01

    Chronic pulsatile subcutaneous administration of low doses of gonadotrophin releasing hormone (GnRH) is an effective therapy for men with hypogonadotrophic hypogonadism. Hypersensitivity reactions to GnRH are rare. We wish to report hypersensitivity reactions with intravenous GnRH after low dose subcutaneous pulsatile GnRH treatment in two men with hypogonadotrophic hypogonadism due to suprasellar disease.

  3. Polymorphism in the Mr 32,000 Rh protein purified from Rh(D)-positive and -negative erythrocytes

    International Nuclear Information System (INIS)

    Saboori, A.M.; Smith, B.L.; Agre, P.

    1988-01-01

    A M r 32,000 integral membrane protein has previously been identified on erythrocytes bearing the Rh(D) antigen and is thought to contain the antigenic variations responsible for the different Rh phenotypes. To study it on a biochemical level, a simple large-scale method was developed to purify the M r 32,000 Rh protein from multiple units of Rh(D)-positive and -negative blood. Erythrocyte membrane vesicles were solubilized in NaDodSO 4 , and a tracer of immunoprecipitated 125 I surface-labeled Rh protein was added. The Rh protein was purified to homogeneity by hydroxylapatite chromatography followed by preparative NaDodSO 4 /PAGE. Approximately 25 nmol of pure Rh protein was recovered from each unit of Rh(D)-positive and -negative blood. Rh protein purified from both Rh phenotypes appeared similar by one-dimensional NaDodSO 4 /PAGE, and the N-terminal amino acid sequences for the first 20 residues were identical. Rh proteins purified from Rh(D)-positive and -negative blood were compared by two-dimensional iodopeptide mapping after 125 I-labeling and α-chymotrypsin digestion. The peptide maps were very similar. These data indicate that a similar core Rh protein exists in both Rh(D)-positive and -negative erythrocytes, and the Rh proteins from erythrocytes with different Rh phenotypes contain distinct structural polymorphisms

  4. Ginsenoside Rh2 enhances the antitumor immunological response of a melanoma mice model.

    Science.gov (United States)

    Wang, Meng; Yan, Shi-Ju; Zhang, Hong-Tao; Li, Nan; Liu, Tao; Zhang, Ying-Long; Li, Xiao-Xiang; Ma, Qiong; Qiu, Xiu-Chun; Fan, Qing-Yu; Ma, Bao-An

    2017-02-01

    The treatment of malignant tumors following surgery is important in preventing relapse. Among all the post-surgery treatments, immunomodulators have demonstrated satisfactory effects on preventing recurrence according to recent studies. Ginsenoside is a compound isolated from panax ginseng, which is a famous traditional Chinese medicine. Ginsenoside aids in killing tumor cells through numerous processes, including the antitumor processes of ginsenoside Rh2 and Rg1, and also affects the inflammatory processes of the immune system. However, the role that ginsenoside serves in antitumor immunological activity remains to be elucidated. Therefore, the present study aimed to analyze the effect of ginsenoside Rh2 on the antitumor immunological response. With a melanoma mice model, ginsenoside Rh2 was demonstrated to inhibit tumor growth and improved the survival time of the mice. Ginsenoside Rh2 enhanced T-lymphocyte infiltration in the tumor and triggered cytotoxicity in spleen lymphocytes. In addition, the immunological response triggered by ginsenoside Rh2 could be transferred to other mice. In conclusion, the present study provides evidence that ginsenoside Rh2 treatment enhanced the antitumor immunological response, which may be a potential therapy for melanoma.

  5. The default network and self-generated thought: component processes, dynamic control, and clinical relevance

    Science.gov (United States)

    Andrews-Hanna, Jessica R.; Smallwood, Jonathan; Spreng, R. Nathan

    2014-01-01

    Though only a decade has elapsed since the default network was first emphasized as being a large-scale brain system, recent years have brought great insight into the network’s adaptive functions. A growing theme highlights the default network as playing a key role in internally-directed—or self-generated—thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the default network. First, we present evidence that self-generated thought is a multi-faceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the default network, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced. PMID:24502540

  6. An integrated knowledge-based framework for synthesis and design of enterprise-wide processing networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    material, product portfolio and process technology selection for a given market scenario, their sustainability metrics and risk of investment under market uncertainties enabling risk-aware decision making. The framework is highlighted with successful applications for soybean oil processing (food technology......, 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 optimization...

  7. Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks

    DEFF Research Database (Denmark)

    Talebnia, Farid; Mighani, Moein; Rahimnejad, Mostafa

    2015-01-01

    and 67% of maximum theoretical value. Next, data of the experimental runs were exploited for modeling the processes by artificial neural networks (ANNs) and performance of the developed models was evaluated. The ANN-based models showed a great potential for time-course prediction of the studied processes....... Efficiency of the joint network for simulating the whole process was also determined and promising results were obtained....

  8. A study of the discovery process in 802.11 networks

    OpenAIRE

    Castignani , German; Arcia Moret , Andres Emilio; Montavont , Nicolas

    2011-01-01

    International audience; Today wireless communications are a synonym of mobility and resource sharing. These characteristics, proper of both infrastructure and ad-hoc networks, heavily relies on a general resource discovery process. The discovery process, being an unavoidable procedure, has to be fast and reliable to mitigate the effect of network disruptions. In this article, by means of simulations and a real testbed, our contribution is twofold. First we assess the discovery process focusin...

  9. Large-scale functional networks connect differently for processing words and symbol strings.

    Science.gov (United States)

    Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

    2018-01-01

    Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

  10. Preparation and Thermoelectric Characteristics of ITO/PtRh:PtRh Thin Film Thermocouple.

    Science.gov (United States)

    Zhao, Xiaohui; Wang, Hongmin; Zhao, Zixiang; Zhang, Wanli; Jiang, Hongchuan

    2017-12-15

    Thin film thermocouples (TFTCs) can provide more precise in situ temperature measurement for aerospace propulsion systems without disturbance of gas flow and surface temperature distribution of the hot components. ITO/PtRh:PtRh TFTC with multilayer structure was deposited on alumina ceramic substrate by magnetron sputtering. After annealing, the TFTC was statically calibrated for multiple cycles with temperature up to 1000 °C. The TFTC with excellent stability and repeatability was realized for the negligible variation of EMF in different calibration cycles. It is believed that owing to oxygen diffusion barriers by the oxidation of top PtRh layer and Schottky barriers formed at the grain boundaries of ITO, the variation of the carrier concentration of ITO film is minimized. Meanwhile, the life time of TFTC is more than 30 h in harsh environment. This makes ITO/PtRh:PtRh TFTC a promising candidate for precise surface temperature measurement of hot components of aeroengines.

  11. XANES and XMCD studies of FeRh and CoRh nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Smekhova, A; Wilhelm, F; Rogalev, A [European Synchrotron Radiation Facility, Grenoble Cedex 9, 38043 (France); Atamena, N; Ciuculescu, D; Amiens, C [Laboratoire de Chimie de Coordination, UPR 8241-CNRS, Toulouse Cedex 04, 31077 (France); Lecante, P, E-mail: smeal@esrf.f [Centre d' Elaboration de Materiaux et d' Etudes Structurales, UPR 8011-CNRS, Toulouse Cedex 04, 31055 (France)

    2010-01-01

    Element-selective magnetic properties of new core-shell bimetallic MRh (M=Fe or Co) nanoparticles (NP{sub S}) of 50/50 composition with either M-Rh or Rh-M core/shell order and an average diameter of {approx}2 nm have been investigated by X-ray Absorption Spectroscopy (XANES) and X-Ray Magnetic Circular Dichroism (XMCD) technique. XANES spectra at the Rh L{sub 2,3} edges exhibit the same characteristic features for all systems having the Rh metal enriched shell. XMCD experiments at the same edges have shown that 4d states of Rh atoms acquire a magnetic moment as a result of hybridization with iron or cobalt 3d states. As expected the value of this induced moment depends on the 3d transition metal and on the core/shell chemical order in the nanoparticle.

  12. Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

    OpenAIRE

    Béjar Haro, Benjamín

    2013-01-01

    Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of es...

  13. Culture, agency and power: Theoretical reflections on informal economic networks and political process

    OpenAIRE

    Meagher, Kate

    2009-01-01

    Do network theory really offer a suitable concept for the theorization of informal processes of economic regulation and institutional change? This working paper challenges both essentialist and skeptical attitudes to networks through an examination of the positive and negative effects of network governance in contemporary societies in a range of regional contexts. The analysis focuses on three broad principles of non-state organization - culture, agency and power - and their role in shaping p...

  14. Hygroscopicity of internally mixed particles composed of (NH4)2SO4 and citric acid under pulsed RH change.

    Science.gov (United States)

    Shi, Xiao-Min; Wu, Feng-Min; Jing, Bo; Wang, Na; Xu, Lin-Lin; Pang, Shu-Feng; Zhang, Yun-Hong

    2017-12-01

    In this research, we applied a pulsed RH controlling system and a rapid scan vacuum FTIR spectrometer (PRHCS-RSVFTIR) to investigate hygroscopicity of internally mixed (NH 4 ) 2 SO 4 (AS)/citric acid (CA) particles. The water content and efflorescence ratio of AS in the particles and ambient relative humidity (RH) as a function of time were obtained with a subsecond time resolution. The hygroscopic behavior of AS aerosols in two different RH control processes (equilibrium and RH pulsed processes) showed that AS droplets crystallize with RH ranging from 42% to 26.5%. It was found that the half-life time ratio between the water content in the CA particles and the gas phase under RH pulsed change was greater than one under low RH conditions (humidity (ERH) of the mixed particles with AS/CA by molar ratio 3:1 was found between 22.7% and 5.9%, which was much lower than AS particles. No efflorescence process was observed for the 1:1 mixed particles, indicating that CA greatly suppressed nucleation of AS. Our results have shown that the PRHCS-RSVFTIR is effective to simulate hygroscopicity and water transport of aerosols under fast variations in RH in atmosphere. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-01

    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.

  16. 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.

  17. 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.

  18. Study on algorithm of process neural network for soft sensing in sewage disposal system

    Science.gov (United States)

    Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

    2006-11-01

    A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

  19. Class A Network Dataring gauges - 1991 data processing and analysis

    OpenAIRE

    Shaw, S.M.

    1992-01-01

    This report presents a summary of still water level data processing for 1991 from 34 modernised dataring sites around the UK coast. Details of geographic position, reference levels, processing, statistics and analyses are included.

  20. 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

  1. A Recommended Framework for the Network-Centric Acquisition Process

    Science.gov (United States)

    2009-09-01

    ISO /IEC 12207 , Systems and Software Engineering-Software Life-Cycle Processes  ANSI/EIA 632, Processes for Engineering a System. There are...engineering [46]. Some of the process models presented in the DAG are:  ISO /IEC 15288, Systems and Software Engineering-System Life-Cycle Processes...e.g., ISO , IA, Security, etc.). Vetting developers helps ensure that they are using industry best industry practices and maximize the IA compliance

  2. 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.

  3. Functional network connectivity underlying food processing: disturbed salience and visual processing in overweight and obese adults.

    Science.gov (United States)

    Kullmann, Stephanie; Pape, Anna-Antonia; Heni, Martin; Ketterer, Caroline; Schick, Fritz; Häring, Hans-Ulrich; Fritsche, Andreas; Preissl, Hubert; Veit, Ralf

    2013-05-01

    In order to adequately explore the neurobiological basis of eating behavior of humans and their changes with body weight, interactions between brain areas or networks need to be investigated. In the current functional magnetic resonance imaging study, we examined the modulating effects of stimulus category (food vs. nonfood), caloric content of food, and body weight on the time course and functional connectivity of 5 brain networks by means of independent component analysis in healthy lean and overweight/obese adults. These functional networks included motor sensory, default-mode, extrastriate visual, temporal visual association, and salience networks. We found an extensive modulation elicited by food stimuli in the 2 visual and salience networks, with a dissociable pattern in the time course and functional connectivity between lean and overweight/obese subjects. Specifically, only in lean subjects, the temporal visual association network was modulated by the stimulus category and the salience network by caloric content, whereas overweight and obese subjects showed a generalized augmented response in the salience network. Furthermore, overweight/obese subjects showed changes in functional connectivity in networks important for object recognition, motivational salience, and executive control. These alterations could potentially lead to top-down deficiencies driving the overconsumption of food in the obese population.

  4. 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

  5. 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,

  6. Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

    KAUST Repository

    Alsibyani, Hassan M.

    2018-01-01

    . For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing

  7. Fault detection and diagnosis for complex multivariable processes using neural networks

    International Nuclear Information System (INIS)

    Weerasinghe, M.

    1998-06-01

    Development of a reliable fault diagnosis method for large-scale industrial plants is laborious and often difficult to achieve due to the complexity of the targeted systems. The main objective of this thesis is to investigate the application of neural networks to the diagnosis of non-catastrophic faults in an industrial nuclear fuel processing plant. The proposed methods were initially developed by application to a simulated chemical process prior to further validation on real industrial data. The diagnosis of faults at a single operating point is first investigated. Statistical data conditioning methods of data scaling and principal component analysis are investigated to facilitate fault classification and reduce the complexity of neural networks. Successful fault diagnosis was achieved with significantly smaller networks than using all process variables as network inputs. Industrial processes often manufacture at various operating points, but demonstrated applications of neural networks for fault diagnosis usually only consider a single (primary) operating point. Developing a standard neural network scheme for fault diagnosis at all operating points would be usually impractical due to the unavailability of suitable training data for less frequently used (secondary) operating points. To overcome this problem, the application of a single neural network for the diagnosis of faults operating at different points is investigated. The data conditioning followed the same techniques as used for the fault diagnosis of a single operating point. The results showed that a single neural network could be successfully used to diagnose faults at operating points other than that it is trained for, and the data conditioning significantly improved the classification. Artificial neural networks have been shown to be an effective tool for process fault diagnosis. However, a main criticism is that details of the procedures taken to reach the fault diagnosis decisions are embedded in

  8. 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.

  9. Critical behavior of the contact process on small-world networks

    Science.gov (United States)

    Ferreira, Ronan S.; Ferreira, Silvio C.

    2013-11-01

    We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

  10. Analysing the Outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center

    OpenAIRE

    Marjeta, Katri

    2011-01-01

    Marjeta, Katri. 2011. Analysing the outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center. Master´s thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 57. Due to confidentiality issues, this work has been modified from its original form. The aim of this Master Thesis work is to describe and analyze the outbound logistics process enhancement projects executed in Nokia-Siemens Networks Global Distribution Center after the N...

  11. The governance of regional networks in the process of European integration

    OpenAIRE

    Cappellin, Riccardo

    2001-01-01

    The paper illustrates the model of territorial networks and it investigates the role of institutions in a bottom-up approach of economic and institutional integration aiming to tackle the negative impacts of the globalization process on the economic development. The first chapter illustrates in analytical terms the model of territorial networks and the multidimen-sional nature of the process of integration, in a regional and international setting and it contrasts it with the traditional neocl...

  12. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  13. A collaborative processes synchronization method with regard to system crashes and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2014-01-01

    Processes can synchronize their states by exchanging messages. System crashes and network failures may cause message loss, so that state changes of a process may remain unnoticed by its partner processes, resulting in state inconsistency or deadlocks. In this paper we define a method to transform a

  14. Robust client/server shared state interactions of collaborative process with system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes state, it sends messages to relevant processes to inform about this change. However, server crashes and

  15. Predictive business process monitoring with LSTM neural networks

    NARCIS (Netherlands)

    Tax, N.; Verenich, I.; La Rosa, M.; Dumas, M.; Pohl, Klaus; Dubois, Eric

    2017-01-01

    Predictive business process monitoring methods exploit logs of completed cases of a process in order to make predictions about running cases thereof. Existing methods in this space are tailor-made for specific prediction tasks. Moreover, their relative accuracy is highly sensitive to the dataset at

  16. 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

    ). The applicability of this methodology is highlighted in each level of modeling through the analysis of a lipid process that has significant relevance in the edible oil and biodiesel industries since it determines the quality of the final oil product, the physical refining process of oils and fats....

  17. Absolute calibration of the Rh-103 (n, n') Rh-103m reaction rate

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, W.H.; Murphy, M.F.; March, M.R. [Reactor Physics Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)

    1979-05-15

    The uncertainties in determining the absolute values of the Rh-103 (n, n') Rh-103m reaction rate (which is widely used as a neutron damage flux monitor) have been reduced to {approx}{+-}5%. This has been achieved with the use of a calibrated source of Pd-103-Rh-103m activity supplied by the I.A.E.A. Agreement to within 3% between measured and calculated values of the reaction rate (normalised to the U-238 fission rate) has been achieved. (author)

  18. 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)

  19. Absolute calibration of the Rh-103 (n, n') Rh-103m reaction rate

    International Nuclear Information System (INIS)

    Taylor, W.H.; Murphy, M.F.; March, M.R.

    1979-05-01

    The uncertainties in determining the absolute values of the Rh-103 (n, n') Rh-103m reaction rate (which is widely used as a neutron damage flux monitor) have been reduced to ∼±5%. This has been achieved with the use of a calibrated source of Pd-103-Rh-103m activity supplied by the I.A.E.A. Agreement to within 3% between measured and calculated values of the reaction rate (normalised to the U-238 fission rate) has been achieved. (author)

  20. Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers

    International Nuclear Information System (INIS)

    Mikulandrić, Robert; Lončar, Dražen; Böhning, Dorith; Böhme, Rene; Beckmann, Michael

    2014-01-01

    Highlights: • 2 Different equilibrium models are developed and their performance is analysed. • Neural network prediction models for 2 different fixed bed gasifier types are developed. • The influence of different input parameters on neural network model performance is analysed. • Methodology for neural network model development for different gasifier types is described. • Neural network models are verified for various operating conditions based on measured data. - Abstract: The number of the small and middle-scale biomass gasification combined heat and power plants as well as syngas production plants has been significantly increased in the last decade mostly due to extensive incentives. However, existing issues regarding syngas quality, process efficiency, emissions and environmental standards are preventing biomass gasification technology to become more economically viable. To encounter these issues, special attention is given to the development of mathematical models which can be used for a process analysis or plant control purposes. The presented paper analyses possibilities of neural networks to predict process parameters with high speed and accuracy. After a related literature review and measurement data analysis, different modelling approaches for the process parameter prediction that can be used for an on-line process control were developed and their performance were analysed. Neural network models showed good capability to predict biomass gasification process parameters with reasonable accuracy and speed. Measurement data for the model development, verification and performance analysis were derived from biomass gasification plant operated by Technical University Dresden

  1. Neuroregulatory and neuroendocrine GnRH pathways in the hypothalamus and forebrain of the baboon.

    Science.gov (United States)

    Marshall, P E; Goldsmith, P C

    1980-07-14

    The distribution of neurons containing gonadotropin-releasing hormone (GnRH) in the baboon hypothalamus and forebrain was studied immunocytochemically by light and electron microscopy. GnRH was present in the perikarya, axonal and dendritic processes of immunoreactive neurons. Three populations of GnRH neurons could be distinguished. Most of the GnRH neurons which are assumed to directly influence the anterior pituitary were in the medial basal hypothalamus. Other cells that projected to the median eminence were found scattered throughout the hypothalamus. A second, larger population of neurons apparently was not involved with control of the anterior pituitary. These neurons were generally found within afferent and efferent pathways of the hypothalamus and forebrain, and may receive external information affecting reproduction. A few neurons projecting to the median eminence were also observed sending collaterals to other brain areas. Thus, in addition to their neuroendocrine role, these cells possibly have neuroregulatory functions. The inference is made that these bifunctional neurons, together with the widely observed GnRH-GnRH cellular interactions may help to synchronize ovulation and sexual behavior.

  2. Rendezvous effects in the diffusion process on bipartite metapopulation networks.

    Science.gov (United States)

    Cao, Lang; Li, Xun; Wang, Bing; Aihara, Kazuyuki

    2011-10-01

    Epidemic outbreaks have been shown to be closely related to the rendezvous-induced transmission of infection, which is caused by casual contact with infected individuals in public gatherings. To investigate rendezvous effects in the spread of infectious diseases, we propose an epidemic model on metapopulation networks bipartite-divided into two sets of location and rendezvous nodes. At a given transition rate γ(kk')(p), each individual transfers from location k to rendezvous p (where rendezvous-induced disease incidence occurs) and thereafter moves to location k'. We find that the eigenstructure of a transition-rate-dependent matrix determines the epidemic threshold condition. Both analytical and numerical results show that rendezvous-induced transmission accelerates the progress of infectious diseases, implying the significance of outbreak control measures including prevention of public gatherings or decentralization of a large-scale rendezvous into downsized ones.

  3. 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, ant...

  4. Preparation of a 102Rh tracer

    International Nuclear Information System (INIS)

    Gorski, B.; Heinig, W.

    1986-01-01

    Electronic emission detectors used in reactors for the control of the neutron flux density contain rhodium as an emitter material. By dissolving the emitter material in a mixture of hydrobromic acid and bromine it is possible to get 102 Rh labelled solutions of the spent detectors. The preparation and purification of the solutions are described. (author)

  5. 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...

  6. 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.

  7. Biosynthesis of gonadotropin-releasing hormone (GnRH) and GnRH receptor (GnRHR) in hypothalamic-pituitary unit of anoestrous and cyclic ewes.

    Science.gov (United States)

    Ciechanowska, M O; Łapot, M; Mateusiak, K; Paruszewska, E; Malewski, T; Przekop, F

    2017-02-01

    This study was performed to explain how the molecular processes governing the biosynthesis of gonadotropin-releasing hormone (GnRH) and GnRH receptor (GnRHR) in the hypothalamic-pituitary unit are reflected by luteinizing hormone (LH) secretion in sheep during anoestrous period and during luteal and follicular phases of the oestrous cycle. Using an enzyme-linked immunosorbent assay (ELISA), we analyzed the levels of GnRH and GnRHR in preoptic area (POA), anterior (AH) and ventromedial hypothalamus (VM), stalk-median eminence (SME), and GnRHR in the anterior pituitary gland (AP). Radioimmunoassay has also been used to define changes in plasma LH concentrations. The study provides evidence that the levels of GnRH in the whole hypothalamus of anoestrous ewes were lower than that in sheep during the follicular phase of the oestrous cycle (POA: p pituitary unit, as well as LH level, in the blood in anoestrous ewes were significantly lower than those detected in animals of both cyclic groups. Our data suggest that decrease in LH secretion during the long photoperiod in sheep may be due to low translational activity of genes encoding both GnRH and GnRHR.

  8. 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.

  9. GPS data processing of networks with mixed single- and dual-frequency receivers for deformation monitoring

    Science.gov (United States)

    Zou, X.; Deng, Z.; Ge, M.; Dick, G.; Jiang, W.; Liu, J.

    2010-07-01

    In order to obtain crustal deformations of higher spatial resolution, existing GPS networks must be densified. This densification can be carried out using single-frequency receivers at moderate costs. However, ionospheric delay handling is required in the data processing. We adapt the Satellite-specific Epoch-differenced Ionospheric Delay model (SEID) for GPS networks with mixed single- and dual-frequency receivers. The SEID model is modified to utilize the observations from the three nearest dual-frequency reference stations in order to avoid contaminations from more remote stations. As data of only three stations are used, an efficient missing data constructing approach with polynomial fitting is implemented to minimize data losses. Data from large scale reference networks extended with single-frequency receivers can now be processed, based on the adapted SEID model. A new data processing scheme is developed in order to make use of existing GPS data processing software packages without any modifications. This processing scheme is evaluated using a sub-network of the German SAPOS network. The results verify that the new scheme provides an efficient way to densify existing GPS networks with single-frequency receivers.

  10. Using an Artificial Neural Network Approach for Supplier Evaluation Process and a Sectoral Application

    Directory of Open Access Journals (Sweden)

    A. Yeşim Yayla

    2011-02-01

    Full Text Available In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network's independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network's input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network's inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network's outputs. The data set of the network's are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.

  11. Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

    Science.gov (United States)

    Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

    2015-01-01

    The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

  12. 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.

  13. 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.

  14. 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.

  15. {sup 103}Rh NMR investigation of the superconductor Rh{sub 17}S{sub 15}

    Energy Technology Data Exchange (ETDEWEB)

    Koyama, T., E-mail: t-koyama@sci.u-hyogo.ac.j [Graduate School of Material Science, University of Hyogo, Kamigori, Hyogo 678-1297 (Japan); Kanda, K.; Motoyama, G.; Ueda, K.; Mito, T.; Kohara, T. [Graduate School of Material Science, University of Hyogo, Kamigori, Hyogo 678-1297 (Japan); Nakamura, H. [Department of Materials Science and Engineering, Kyoto University, Kyoto 606-8501 (Japan)

    2010-12-15

    We present {sup 103}Rh NMR studies for the superconductor Rh{sub 17}S{sub 15} (T{sub c} 5.4 K). We have identified the observed NMR lines corresponding to four different Rh sites in the cubic unit cell and deduced the temperature (T) dependence of the Knight shift components in Rh 24m site whose point symmetry is not axial. The isotropic part of the Knight shift K decreases with T in the normal state, indicating the negative hyperfine coupling and the enhancement of the spin susceptibility at lower T. The sudden change of K below T{sub c} is an indication of the spin-singlet Cooper paring.

  16. Living in the branches: population dynamics and ecological processes in dendritic networks

    Science.gov (United States)

    Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

    2007-01-01

    Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

  17. Urbanisation processes in Slovenia and their effects on urban networks

    Directory of Open Access Journals (Sweden)

    Kaliopa Dimitrovska Andrews

    2000-01-01

    Full Text Available The article presents processes of changes in the structure of settlement systems in Europe and Slovenia. Hypotheses that have to be given adequate respect as starting points in the development of the urban system follow particular levels of discourse, from the European and national, regional level to the local level. Thus directing urbanisation is different on different levels. Two examples of directing urbanisation processes on the local level are presented, for the functional urban region of Ljubljana and the municipality of Domžale. In conclusion ideas about measures and instruments for achieving urban development policies are shown.

  18. Remarks on the 103Rh(n,n') sup(103m)Rh excitation curve

    International Nuclear Information System (INIS)

    Pazsit, A.; Peto, G.; Csikai, J.; Jozsa, I.; Bacso, J.

    1975-01-01

    The cross sections of the 103 Rh(n,n')sup(103m)Rh reaction have been measured at 2.7MeV and 14.8MeV neutron energies as well as for neutron spectra of 252 Cf and 239 Pu-α-Be sources; the results are 999+-111mb, 216+-26mb, 757+-53mb and 918+-64mb, respectively. (author)

  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. Affective and executive network processing associated with persuasive antidrug messages.

    Science.gov (United States)

    Ramsay, Ian S; Yzer, Marco C; Luciana, Monica; Vohs, Kathleen D; MacDonald, Angus W

    2013-07-01

    Previous research has highlighted brain regions associated with socioemotional processes in persuasive message encoding, whereas cognitive models of persuasion suggest that executive brain areas may also be important. The current study aimed to identify lateral prefrontal brain areas associated with persuasive message viewing and understand how activity in these executive regions might interact with activity in the amygdala and medial pFC. Seventy adolescents were scanned using fMRI while they watched 10 strongly convincing antidrug public service announcements (PSAs), 10 weakly convincing antidrug PSAs, and 10 advertisements (ads) unrelated to drugs. Antidrug PSAs compared with nondrug ads more strongly elicited arousal-related activity in the amygdala and medial pFC. Within antidrug PSAs, those that were prerated as strongly persuasive versus weakly persuasive showed significant differences in arousal-related activity in executive processing areas of the lateral pFC. In support of the notion that persuasiveness involves both affective and executive processes, functional connectivity analyses showed greater coactivation between the lateral pFC and amygdala during PSAs known to be strongly (vs. weakly) convincing. These findings demonstrate that persuasive messages elicit activation in brain regions responsible for both emotional arousal and executive control and represent a crucial step toward a better understanding of the neural processes responsible for persuasion and subsequent behavior change.

  1. The gamma model : a new neural network for temporal processing

    NARCIS (Netherlands)

    Vries, de B.

    1992-01-01

    In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

  2. Origin of room temperature ferromagnetic moment in Rh-rich [Rh/Fe] multilayer thin films

    International Nuclear Information System (INIS)

    Kande, Dhishan; Laughlin, David; Zhu Jiangang

    2010-01-01

    B2 ordered FeRh thin films switch from antiferromagnetic (AFM) to ferromagnetic (FM) state on heating above 350 K and switch back on cooling, with a hysteresis. This property makes FeRh a very attractive choice as a write-assist layer material for low temperature heat assisted magnetic recording (HAMR) media. Studies have shown that as we decrease the thickness of the FeRh films, the B2 phase is no longer AFM even below 350 K and there is a thickness dependant FM stabilization of the B2 phase. It was also proved that slightly Rh-richer compositions (>50 at. % Rh) were more preferable to stabilize the AFM phase. The current study focuses on growing highly ordered FeRh films by alternate layer rf sputtering of thin layers of iron and rhodium onto a heated substrate. It has been shown that films with rhodium content beyond 55 at. % contain a disordered bcc FM phase which gives rise to residual moment at room temperature even for thicker films.

  3. Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks

    Science.gov (United States)

    Forman, Yakir; Cameron, Maria

    2017-07-01

    We model an isothermal aggregation process of particles/atoms interacting according to the Lennard-Jones pair potential by mapping the energy landscapes of each cluster size N onto stochastic networks, computing transition probabilities from the network for an N-particle cluster to the one for N+1, and connecting these networks into a single joint network. The attachment rate is a control parameter. The resulting network representing the aggregation of up to 14 particles contains 6427 vertices. It is not only time-irreversible but also reducible. To analyze its transient dynamics, we introduce the sequence of the expected initial and pre-attachment distributions and compute them for a wide range of attachment rates and three values of temperature. As a result, we find the configurations most likely to be observed in the process of aggregation for each cluster size. We examine the attachment process and conduct a structural analysis of the sets of local energy minima for every cluster size. We show that both processes taking place in the network, attachment and relaxation, lead to the dominance of icosahedral packing in small (up to 14 atom) clusters.

  4. Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

    1992-01-01

    This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

  5. Epidemic spreading in annealed directed networks: susceptible-infected-susceptible model and contact process.

    Science.gov (United States)

    Kwon, Sungchul; Kim, Yup

    2013-01-01

    We investigate epidemic spreading in annealed directed scale-free networks with the in-degree (k) distribution P(in)(k)~k(-γ(in)) and the out-degree (ℓ) distribution, P(out)(ℓ)~ℓ(-γ(out)). The correlation of each node on the networks is controlled by the probability r(0≤r≤1) in two different algorithms, the so-called k and ℓ algorithms. For r=1, the k algorithm gives =, whereas the ℓ algorithm gives =. For r=0, = for both algorithms. As the prototype of epidemic spreading, the susceptible-infected-susceptible model and contact process on the networks are analyzed using the heterogeneous mean-field theory and Monte Carlo simulations. The directedness of links and the correlation of the network are found to play important roles in the spreading, so that critical behaviors of both models are distinct from those on undirected scale-free networks.

  6. Lipid Processing Technology: Building a Multilevel Modeling Network

    OpenAIRE

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

    2011-01-01

    Over the past few decades, the world’s fats and oils production has been growing rapidly, far beyond the need for human nutrition. This overproduction combined with the growing consumer preferences for healthier food products and the interest in 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 establis...

  7. 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

  8. 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

  9. 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...

  10. From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Juan Andres Laura

    2018-03-01

    Full Text Available In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered.

  11. Synthesis and Design of Biorefinery Processing Networks with Uncertainty and Sustainability analysis

    DEFF Research Database (Denmark)

    Cheali, Peam; Gernaey, Krist; Sin, Gürkan

    combinations of processing networks. The optimization of the network is formulated as a mixed integer nonlinear programming type of problem and solved in GAMS. The methodology was applied for designing optimal biorefinery networks considering biochemical routes. Furthermore, the methodology has also been...... for processing renewable feedstocks, with the aim of bridging the gap for fuel, chemical and material production. This project is focusing on biorefinery network design, in particular for early stage design and development studies. Optimal biorefinery design is a challenging problem. It is a multi......-objective decision-making problem not only with respect to technical and economic feasibility but also with respect to environmental impacts, sustainability constraints and limited availability & uncertainties of input data at the early design stage. It is therefore useful to develop a systematic methodology...

  12. Adsorption of Rh(III) complexes from chloride solutions obtained by leaching chlorinated spent automotive catalysts on ion-exchange resin Diaion WA21J

    International Nuclear Information System (INIS)

    Shen Shaobo; Pan Tonglin; Liu Xinqiang; Yuan Lei; Wang Jinchao; Zhang Yongjian; Guo Zhanchen

    2010-01-01

    It was found that Rh, Pd and Pt contained in the spent ceramic automotive catalysts could be effectively extracted by dry chlorination with chlorine. In order to concentrate Rh(III) ions contained in the chloride solutions obtained, thermodynamic and kinetics studies for adsorption of Rh(III) complexes from the chloride solutions on an anionic exchange resin Diaion WA21J were carried out. Rh, Pd, Pt, Al, Fe, Si, Zn and Pb from the chloride solution could be adsorbed on the resin. The distribution coefficients (K d ) of Rh(III) decreased with the increase in initial Rh(III) concentration or in adsorption temperature. The isothermal adsorption of Rh(III) was found to fit Langmuir, Freundlich and Dubinin-Kaganer-Radushkevich models under the adsorption conditions. The maximum monolayer adsorption capacities Q max based on Langmuir adsorption isotherms were 6.39, 6.61 and 5.81 mg/g for temperatures 18, 28 and 40 deg. C, respectively. The apparent adsorption energy of Rh was about -7.6 kJ/mol and thus Rh(III) adsorption was a physical type. The experimental data obtained could be better simulated by pseudo-first-order kinetic model and the activation energy obtained was 6.54 J/mol. The adsorption rate of Rh(III) was controlled by intraparticle diffusion in most of time of adsorption process.

  13. Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

    NARCIS (Netherlands)

    Kroese, D.P.; Scheinhardt, W.R.W.; Taylor, P.G.

    2004-01-01

    Quasi-birth-and-death (QBD) processes with infinite “phase spaces" can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase" giving the state of the first queue and the “level" giving the state of the second

  14. 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.

  15. The key network communication technology in large radiation image cooperative process system

    International Nuclear Information System (INIS)

    Li Zheng; Kang Kejun; Gao Wenhuan; Wang Jingjin

    1998-01-01

    Large container inspection system (LCIS) based on radiation imaging technology is a powerful tool for the customs to check the contents inside a large container without opening it. An image distributed network system is composed of operation manager station, image acquisition station, environment control station, inspection processing station, check-in station, check-out station, database station by using advanced network technology. Mass data, such as container image data, container general information, manifest scanning data, commands and status, must be on-line transferred between different stations. Advanced network communication technology is presented

  16. 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

  17. Contagion processes on the static and activity-driven coupling networks

    Science.gov (United States)

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

    2016-03-01

    The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated as either static or time-varying, supposing the whole network is observed in the same time window. In this paper, we consider the epidemics spreading on a network which has both static and time-varying structures. 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 the static ("strong") structure and the dynamic ("weak") structure. Epidemic thresholds of the SIS and SIR models are studied using the SADC model both analytically and numerically under various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from the SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that a weak structure might make the epidemic threshold low in homogeneous networks but high in heterogeneous cases. Furthermore, we show that the weak structure has a substantive effect on the outbreak of the epidemics. This result might be useful in designing some efficient control strategies for epidemics spreading in networks.

  18. Mapping industrial systems - a supply network perspective on enabling technologies, processes and actors

    OpenAIRE

    Srai, Jagjit Singh

    2016-01-01

    This is the author accepted manuscript. The final version is available from InderScience Publishers via http://dx.doi.org/10.1504/IJMTM.2017.10002927 This paper develops a multi-layered multi-stage mapping approach to explore the characteristics of emerging industry supply networks (EI SNs), and how enabling production technologies and supply chain processes are supported by institutional, industrial and supply network actors. The mapping methodology involves the systematic capture of mate...

  19. Breakout Prediction Based on BP Neural Network in Continuous Casting Process

    Directory of Open Access Journals (Sweden)

    Zhang Ben-guo

    2016-01-01

    Full Text Available An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.

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

    Science.gov (United States)

    Vestergaard, Christian L; Génois, Mathieu

    2015-10-01

    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.

  1. Status of Utilizing Social Media Networks in the Teaching-Learning Process at Public Jordanian Universities

    Directory of Open Access Journals (Sweden)

    Muneera Abdalkareem Alshdefait

    2018-03-01

    Full Text Available This study aimed at finding out the status of utilizing social media networks in the teaching-learning process at public Jordanian Universities. To achieve the goal of the study, the descriptive developmental method was used and a questionnaire was developed, consisting of (35 statements. The questionnaire was checked for its validity and reliability. Then it was distributed to a sample of (382 male and female students from the undergraduate and graduate levels. The study results showed that the participants gave a low score to the status of utilizing social media networks in the teaching-learning process at public Jordanian universities. The results also showed that there were statistically significant differences between the participants of the study according to the academic rank attributed to the graduate students, and according to gender attributed to male students at the instrument macro level and on all dimensions of the two variables. In light of these results, the study recommended that public universities should utilize modern technology in the educational process, urge and encourage the teaching staff members to use the social media networks in the teaching-learning process and raise the students' awareness about the benefits of using social media networks. Keywords: Social media networks, Teaching-learning process, Public Jordanian Universities

  2. 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

  3. 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.

  4. Expression of the GnRH and GnRH receptor (GnRH-R) genes in the hypothalamus and of the GnRH-R gene in the anterior pituitary gland of anestrous and luteal phase ewes.

    Science.gov (United States)

    Ciechanowska, Magdalena; Lapot, Magdalena; Malewski, Tadeusz; Mateusiak, Krystyna; Misztal, Tomasz; Przekop, Franciszek

    2008-11-01

    Data exists showing that seasonal changes in the innervations of GnRH cells in the hypothalamus and functions of some neural systems affecting GnRH neurons are associated with GnRH release in ewes. Consequently, we put the question as to how the expression of GnRH gene and GnRH-R gene in the hypothalamus and GnRH-R gene in the anterior pituitary gland is reflected with LH secretion in anestrous and luteal phase ewes. Analysis of GnRH gene expression by RT-PCR in anestrous ewes indicated comparable levels of GnRH mRNA in the preoptic area, anterior and ventromedial hypothalamus. GnRH-R mRNA at different concentrations was found throughout the preoptic area, anterior and ventromedial hypothalamus, stalk/median eminence and in the anterior pituitary gland. The highest GnRH-R mRNA levels were detected in the stalk/median eminence and in the anterior pituitary gland. During the luteal phase of the estrous cycle in ewes, the levels of GnRH mRNA and GnRH-R mRNA in all structures were significantly higher than in anestrous ewes. Also LH concentrations in blood plasma of luteal phase ewes were significantly higher than those of anestrous ewes. In conclusion, results from this study suggest that low expression of the GnRH and GnRH-R genes in the hypothalamus and of the GnRH-R gene in the anterior pituitary gland, amongst others, may be responsible for a decrease in LH secretion and the anovulatory state in ewes during the long photoperiod.

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

    Science.gov (United States)

    2010-09-01

    44 TACFIRE TACtical FIRE direction system 51 TACOPDAT TACtical Operational DATa 20 TBMCS Theater Battle Management...the MAAP process is complete, the ATO data is finally compiled into Theater Battle Management Core System ( TBMCS ), united with any inputs to SPINS...table. 3.1.5 Other NTO Process Considerations The Air Force uses Theater Battle Management Core System ( TBMCS ) to assist in planning and executing

  6. Image processing and analysis using neural networks for optometry area

    Science.gov (United States)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  7. Recent advances in the chemistry of Rh carbenoids: multicomponent reactions of diazocarbonyl compounds

    International Nuclear Information System (INIS)

    Medvedev, J J; Nikolaev, V A

    2015-01-01

    Multicomponent reactions of diazo compounds catalyzed by Rh II complexes become a powerful tool for organic synthesis. They enable three- or four-step processes to be carried out as one-pot procedures (actually as one step) with high stereoselectivity to give complex organic molecules, including biologically active compounds. This review addresses recent results in the chemistry of Rh-catalyzed multicomponent reactions of diazocarbonyl compounds with the intermediate formation of N-, O- and C=O–ylides. The diastereo- and enantioselectivity of these reactions and the possibility of using various co-catalysts to increase the efficiency of the processes under consideration are discussed. The bibliography includes 120 references

  8. 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.

  9. Measurement of 103mRh produced by the 103Rh(γ,γ')103mRh reaction with liquid scintillation counting

    International Nuclear Information System (INIS)

    Sekine, T.; Yoshihara, Kenji; Pavlicsek, I.; Lakosi, L.; Veres, A.

    1989-01-01

    A liquid scintillation counting technique was applied to measure the isotope 103m Rh (half life = 56.12 min) which is difficult to detect because its γ-ray is of low energy and low emission probability. Tris-(2,4-pentanedionato)rhodium(III) (Rh(acac) 3 ) was irradiated with bremsstrahlung of accelerated 3.2 MeV electrons by LINAC. The method has given a reliable calibration curve for the determination of 103m Rh radioactivity below Rh(acac) 3 concentrations of 2 mM. The integrated cross section of 103 Rh(γ,γ') 103m Rh determined by this method was found to be 6.8±3.4 μb MeV at 3.2 MeV. (author) 8 refs.; 5 figs

  10. 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...

  11. 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.

  12. THE USE OF SOCIAL NETWORKS IN THE PROCESS OF LEARNING ENGLISH AS A SECOND LANGUAGE

    Directory of Open Access Journals (Sweden)

    Halyna I. Sotska

    2018-02-01

    Full Text Available In the recent decade many changes in the process of education took place because of the development of information and communication technologies. Online social groups tend to be used by teachers and students for formal (study and informal (personal communication purposes. An efficient teacher may turn social networks into an effective tool, encouraging students to communicate in the target language. With the help of social networks the teacher can activate students in the process of learning, create situations for better understanding and perceiving the material. The use of such approaches as blended learning, corporative learning and active learning helps make the classes more attractive and effective. Moreover, social networks can help in the development of students’ creativity, provision of feedback and cooperative learning. The article deals with the question of influence of Massive online open courses on effectiveness of the educational process for students who learn English as a second language.

  13. Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

    Science.gov (United States)

    Gros, Claudius

    2007-02-01

    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

  14. High activity of cubic PtRh alloys supported on graphene towards ethanol electrooxidation.

    Science.gov (United States)

    Rao, Lu; Jiang, Yan-Xia; Zhang, Bin-Wei; Cai, Yuan-Rong; Sun, Shi-Gang

    2014-07-21

    Cubic PtRh alloys supported on graphene (PtxRhy/GN) with different atomic ratio of Pt and Rh were directly synthesized for the first time using the modified polyol method with Br(-) for the shape-directing agents. The process didn't use surface-capping agents such as PVP that easily occupy the active sites of electrocatalysts and are difficult to remove. Graphene is the key factor for cubic shape besides Br(-) and keeping catalysts high-dispersed. The X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM) were used to characterize the structure and morphology of these electrocatalysts. The results showed that they were composed of homogeneous cubic PtRh alloys. Traditional electrochemical methods, such as cyclic voltammetry and chronoamperometry, were used to investigate the electrocatalytic properties of PtxRhy/GN towards ethanol electrooxidation. It can be seen that PtxRhy/GN with all atomic ratios exhibited high catalytic activity, and the most active one has a composition with Pt : Rh = 9 : 1 atomic ratio. Electrochemical in situ FTIR spectroscopy was used to evaluate the cleavage of C-C bond in ethanol at room temperature in acidic solutions, the results illustrated that Rh in an alloy can promote the split of C-C bond in ethanol, and the alloy catalyst with atomic ratio Pt : Rh = 1 : 1 showed obviously better performance for the C-C bond breaking in ethanol and higher selectivity for the enhanced activity of ethanol complete oxidation to CO2 than alloys with other ratios of Pt and Rh. The investigation indicates that high activity of PtxRhy/GN electrocatalyst towards ethanol oxidation is due to the specific shape of alloys and the synergistic effect of two metal elements as well as graphene support.

  15. 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.

  16. 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

  17. GnRH Neurons on LSD: A Year of Rejecting Hypotheses That May Have Made Karl Popper Proud.

    Science.gov (United States)

    Moenter, Suzanne M

    2018-01-01

    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 © 2018 Endocrine Society.

  18. Prediction of deformations of steel plate by artificial neural network in forming process with induction heating

    International Nuclear Information System (INIS)

    Nguyen, Truong Thinh; Yang, Young Soo; Bae, Kang Yul; Choi, Sung Nam

    2009-01-01

    To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses on the plate to obtain deformations during the heating process are then performed with a commercial FEM program for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs. The predicted outputs from the neural network are compared with those of the experiments and the numerical results. They are in good agreement

  19. Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.

    1993-11-01

    The primary purpose of the current research was to develop an integrated approach by combining information compression methods and artificial neural networks for the monitoring of plant components using nondestructive examination data. Specifically, data from eddy current inspection of heat exchanger tubing were utilized to evaluate this technology. The focus of the research was to develop and test various data compression methods (for eddy current data) and the performance of different neural network paradigms for defect classification and defect parameter estimation. Feedforward, fully-connected neural networks, that use the back-propagation algorithm for network training, were implemented for defect classification and defect parameter estimation using a modular network architecture. A large eddy current tube inspection database was acquired from the Metals and Ceramics Division of ORNL. These data were used to study the performance of artificial neural networks for defect type classification and for estimating defect parameters. A PC-based data preprocessing and display program was also developed as part of an expert system for data management and decision making. The results of the analysis showed that for effective (low-error) defect classification and estimation of parameters, it is necessary to identify proper feature vectors using different data representation methods. The integration of data compression and artificial neural networks for information processing was established as an effective technique for automation of diagnostics using nondestructive examination methods

  20. Information processing in the transcriptional regulatory network of yeast: Functional robustness

    Directory of Open Access Journals (Sweden)

    Dehmer Matthias

    2009-03-01

    Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.

  1. 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.

  2. Electronic structure of Rh-based CuRh0.9Mg0.1O2 oxide thermoelectrics

    Science.gov (United States)

    Vilmercati, P.; Martin, E.; Cheney, C. Parks; Bondino, F.; Magnano, E.; Parmigiani, F.; Sasagawa, T.; Mannella, N.

    2013-03-01

    The electronic structure of the Rh-based CuRh0.9Mg0.1O2 oxide thermoelectric compound has been studied with a multitechnique approach consisting of photoemission, x-ray absorption, and x-ray emission spectroscopies. The data indicate that the region of the valence band in the proximity of the Fermi level is dominated by Rh-derived states. These findings outline the importance of the electronic structure of the Rh ions for the large thermoelectric power in CuRh0.9Mg0.1O2 at high temperature.

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

    Science.gov (United States)

    Taylor, Dane; Klimm, Florian; Harrington, Heather A; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A; Mucha, Peter J

    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.

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

    Science.gov (United States)

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-07-01

    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.

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

    KAUST Repository

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramá r, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-01-01

    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.

  6. 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.

  7. 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.

  8. 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.

  9. Critical regimes driven by recurrent mobility patterns of reaction-diffusion processes in networks

    Science.gov (United States)

    Gómez-Gardeñes, J.; Soriano-Paños, D.; Arenas, A.

    2018-04-01

    Reaction-diffusion processes1 have been widely used to study dynamical processes in epidemics2-4 and ecology5 in networked metapopulations. In the context of epidemics6, reaction processes are understood as contagions within each subpopulation (patch), while diffusion represents the mobility of individuals between patches. Recently, the characteristics of human mobility7, such as its recurrent nature, have been proven crucial to understand the phase transition to endemic epidemic states8,9. Here, by developing a framework able to cope with the elementary epidemic processes, the spatial distribution of populations and the commuting mobility patterns, we discover three different critical regimes of the epidemic incidence as a function of these parameters. Interestingly, we reveal a regime of the reaction-diffussion process in which, counter-intuitively, mobility is detrimental to the spread of disease. We analytically determine the precise conditions for the emergence of any of the three possible critical regimes in real and synthetic networks.

  10. Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

    Science.gov (United States)

    Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

    2018-05-01

    The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

  11. 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.

  12. Dynamical analysis of yeast protein interaction network during the sake brewing process.

    Science.gov (United States)

    Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

    2011-12-01

    Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

  13. 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.

  14. Laser Processed Silver Nanowire Network Transparent Electrodes for Novel Electronic Devices

    Science.gov (United States)

    Spechler, Joshua Allen

    Silver nanowire network transparent conducting layers are poised to make headway into a space previously dominated by transparent conducting oxides due to the promise of a flexible, scaleable, lab-atmosphere processable alternative. However, there are many challenges standing in the way between research scale use and consumer technology scale adaptation of this technology. In this thesis we will explore many, and overcome a few of these challenges. We will address the poor conductivity at the narrow nanowire-nanowire junction points in the network by developing a laser based process to weld nanowires together on a microscopic scale. We address the need for a comparative metric for transparent conductors in general, by taking a device level rather than a component level view of these layers. We also address the mechanical, physical, and thermal limitations to the silver nanowire networks by making composites from materials including a colorless polyimide and titania sol-gel. Additionally, we verify our findings by integrating these processes into devices. Studying a hybrid organic/inorganic heterojunction photovoltaic device we show the benefits of a laser processed electrode. Green phosphorescent organic light emitting diodes fabricated on a solution phase processed silver nanowire based electrode show favorable device metrics compared to a conductive oxide electrode based control. The work in this thesis is intended to push the adoption of silver nanowire networks to further allow new device architectures, and thereby new device applications.

  15. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  16. Preparation and evaluation of self-microemulsions for improved bioavailability of ginsenoside-Rh1 and Rh2.

    Science.gov (United States)

    Yang, Feifei; Zhou, Jing; Hu, Xiao; Yu, Stephanie Kyoungchun; Liu, Chunyu; Pan, Ruile; Chang, Qi; Liu, Xinmin; Liao, Yonghong

    2017-10-01

    Due to intestinal cytochrome P450 (CYP450)-mediated metabolism and P-glycoprotein (P-gp) efflux, poor oral bioavailability hinders ginsenoside-Rh1 (Rh1) and ginsenoside-Rh2 (Rh2) from clinical application. In this study, Rh1 and Rh2 were incorporated into two self-microemulsions (SME-1 and SME-2) to improve oral bioavailability. SME-1 contained both CYP450 and P-gp inhibitory excipients while SME-2 only consisted of P-gp inhibitory excipients. Results for release, cellular uptake, transport, and lymph node distribution demonstrated no significant difference between either self-microemulsions in vivo, but were elevated significantly in comparison to the free drug. The pharmaceutical profiles in vivo showed that the bioavailability of Rh1 in SME-1 (33.25%) was significantly higher than that in either SME-2 (21.28%) or free drug (12.92%). There was no significant difference in bioavailability for Rh2 between SME-1 (48.69%) or SME-2 (41.73%), although they both had remarkable increase in comparison to free drug (15.02%). We confirmed that SME containing CYP450 and P-gp inhibitory excipient could distinctively improve the oral availabilities of Rh1 compared to free drug or SME containing P-gp inhibitory excipient. No notable increase was observed between either SME for Rh2, suggesting that Rh2 undergoes P-gp-mediated efflux, but may not undergo distinct CYP450-mediated metabolism.

  17. Automated processing of measuring information and control processes of eutrophication in water for household purpose, based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    О.М. Безвесільна

    2006-04-01

    Full Text Available  The possibilities of application  informational-computer technologies for automated handling of a measuring information about development of seaweed (evtrofication in household reservoirs are considered. The input data’s for a research of processes evtrofication are videoimages of tests of water, which are used for the definition of geometric characteristics, number and biomass of seaweed. For handling a measuring information the methods of digital handling videoimages and mathematical means of artificial neural networks are offered.

  18. Magnetic and structural characterizations on nanoparticles of FePt, FeRh and their composites

    International Nuclear Information System (INIS)

    Ko, Hnin Yu Yu; Suzuki, Takao; Nam, Nguyen T.; Phuoc, Nguyen N.; Cao Jiangwei; Hirotsu, Yoshihiko

    2008-01-01

    The various compositions of FePt and FeRh nanoparticles, and their composite particles have been fabricated by the solution-phase chemical method and their magnetic properties characterized. High-resolution transmission electron microscopic observations indicate that mono-dispersed FeRh and FePt/FeRh nanoparticles are fabricated with the average size of 3-5 nm. However, larger size particles are distributed in the annealed state. From X-ray diffraction results, the as-deposited FeRh nanoparticles reveal a chemically disordered fcc structure which can be transformed into CsCl-type structure through thermal annealing. Similarly, the annealed FePt nanoparticles show the L1 0 -phase fct structure although the fcc structure is apparent in the as-deposited state. It is also found that the first time in the exchange bias effect in the composite of ferromagnetic (FePt) and anti-ferromagnetic (FeRh) nanoparticles; result in a shift of the hysteresis loop after field cooling process

  19. Immuno-modulatory effect of local rhEGF treatment during tissue repair in diabetic ulcers.

    Science.gov (United States)

    García-Honduvilla, Natalio; Cifuentes, Alberto; Ortega, Miguel A; Pastor, Marta; Gainza, Garazi; Gainza, Eusebio; Buján, Julia; Álvarez-Mon, Melchor

    2018-04-01

    Wound healing is a complex process that can be severely impaired due to pathological situations such as diabetes mellitus. Diabetic foot ulcers are a common complication of this pathology and are characterized by an excessive inflammatory response. In this work, the effects of local treatment with recombinant human epidermal growth factor (rhEGF) were studied using a full-thickness wound healing model in streptozotocin-induced diabetic rats. Wound healing process was assessed with different concentrations of rhEGF (0.1, 0.5, 2.0 and 8.0 µg/mL), placebo and both diabetic and non-diabetic controls ( n  = 53). The macroscopic healing observed in treated diabetic rats was affected by rhEGF concentration. Histologically, we also observed an improvement in the epithelialization, granulation tissue formation and maturation in treated groups, finding again the best response at doses of 0.5 and 2.0 µg/mL. Afterwards, the tissue immune response over time was assessed in diabetic rats using the most effective concentrations of rhEGF (0.5 and 2.0 µg/mL), compared to controls. The presence of macrophages, CD4 + T lymphocytes and CD8 + T lymphocytes, in the reparative tissue was quantified, and cytokine expression was measured by quantitative real-time PCR. rhEGF treatment caused a reduction in the number of infiltrating macrophages in the healing tissue of diabetic, as well as diminished activation of these leukocytes. These findings show that local administration of rhEGF improves the healing process of excisional wounds and the quality of the neoformed tissue in a dose-dependent manner. Besides, this treatment reduces the local inflammation associated with diabetic healing, indicating immuno-modulatory properties. © 2018 The authors.

  20. Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

    Directory of Open Access Journals (Sweden)

    L. Khaouane

    2013-03-01

    Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

  1. A Decision Processing Algorithm for CDC Location Under Minimum Cost SCM Network

    Science.gov (United States)

    Park, N. K.; Kim, J. Y.; Choi, W. Y.; Tian, Z. M.; Kim, D. J.

    Location of CDC in the matter of network on Supply Chain is becoming on the high concern these days. Present status of methods on CDC has been mainly based on the calculation manually by the spread sheet to achieve the goal of minimum logistics cost. This study is focused on the development of new processing algorithm to overcome the limit of present methods, and examination of the propriety of this algorithm by case study. The algorithm suggested by this study is based on the principle of optimization on the directive GRAPH of SCM model and suggest the algorithm utilizing the traditionally introduced MST, shortest paths finding methods, etc. By the aftermath of this study, it helps to assess suitability of the present on-going SCM network and could be the criterion on the decision-making process for the optimal SCM network building-up for the demand prospect in the future.

  2. 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 < 0.001), harem-tending behavior (P < 0.001), and agonistic behavior (P = 0.02). There was no difference between the mean body condition of control females (4

  3. 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.

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

    International Nuclear Information System (INIS)

    Elzendoorn, B.S.Q.; Baar, M. de; Hamilton, D.; Heemskerk, C.J.M.; Koning, J.F.; Ronden, D.M.S.

    2012-01-01

    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.

  5. Waste Isolation Pilot Plant RH TRU waste preoperational checkout: Final report

    International Nuclear Information System (INIS)

    1988-06-01

    This report documents the results of the Waste Isolation Pilot Plant (WIPP) Remote-Handled Transuranic (RH TRU) Waste Preoperational Checkout. The primary objective of this checkout was to demonstrate the process of handling RH TRU waste packages, from receipt through emplacement underground, using equipment, personnel, procedures, and methods to be used with actual waste packages. A further objective was to measure operational time lines to provide bases for confirming the WIPP design through put capability and for projecting operator radiation doses. Successful completion of this checkout is a prerequisite to the receipt of actual RH TRU waste. This checkout was witnessed in part by members of the Environmental Evaluation Group (EEG) of the state of New Mexico. Further, this report satisfies a key milestone contained in the Agreement for Consultation and Cooperation with the state of New Mexico. 4 refs., 26 figs., 4 tabs

  6. 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.

  7. 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

  8. 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…

  9. The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe

    NARCIS (Netherlands)

    Mahdavi, M. (Mahdi); J. Vissers (Jan); S. Elkhuizen (Sylvia); Van Dijk, M. (Mattees); Vanhala, A. (Antero); Karampli, E. (Eleftheria); R. Faubel (Raquel); P. Forte (Paul); Coroian, E. (Elena); J.J. van de Klundert (Joris)

    2018-01-01

    textabstractBackground While health service provisioning for the chronic condition Type 2 Diabetes (T2D) often involves a network of organisations and professionals, most evidence on the relationships between the structures and processes of service provisioning and the outcomes considers single

  10. A System for Acquisition, Processing and Visualization of Image Time Series from Multiple Camera Networks

    Directory of Open Access Journals (Sweden)

    Cemal Melih Tanis

    2018-06-01

    Full Text Available A system for multiple camera networks is proposed for continuous monitoring of ecosystems by processing image time series. The system is built around the Finnish Meteorological Image PROcessing Toolbox (FMIPROT, which includes data acquisition, processing and visualization from multiple camera networks. The toolbox has a user-friendly graphical user interface (GUI for which only minimal computer knowledge and skills are required to use it. Images from camera networks are acquired and handled automatically according to the common communication protocols, e.g., File Transfer Protocol (FTP. Processing features include GUI based selection of the region of interest (ROI, automatic analysis chain, extraction of ROI based indices such as the green fraction index (GF, red fraction index (RF, blue fraction index (BF, green-red vegetation index (GRVI, and green excess (GEI index, as well as a custom index defined by a user-provided mathematical formula. Analysis results are visualized on interactive plots both on the GUI and hypertext markup language (HTML reports. The users can implement their own developed algorithms to extract information from digital image series for any purpose. The toolbox can also be run in non-GUI mode, which allows running series of analyses in servers unattended and scheduled. The system is demonstrated using an environmental camera network in Finland.

  11. Analysis and Control of Epidemics: A survey of spreading processes on complex networks

    OpenAIRE

    Nowzari, Cameron; Preciado, Victor M.; Pappas, George J.

    2015-01-01

    This article reviews and presents various solved and open problems in the development, analysis, and control of epidemic models. We are interested in presenting a relatively concise report for new engineers looking to enter the field of spreading processes on complex networks.

  12. 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

  13. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-31

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

  14. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-01

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

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

    Science.gov (United States)

    Kang, Hyunchul

    2015-01-01

    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. PMID:25774710

  16. 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.

  17. Peculiarities of Blood Group Distribution among Infants Born to Mothers with Negative Rh-Factor (Findings of 2014)

    OpenAIRE

    Oksana G. Cherniukh

    2016-01-01

    Our works consider the investigation of possible manifestation of hyperbilirubinemia in infants against the ground of genetic incompatibilities of the fetus according to АВ0 system and Rh-factor (D) concerning the maternal organism. From this point of view we deal with jaundice of mixed genesis against erythroblastosis domination as a primary antenatal factor of pathological process formation. The present study presents the results of distribution of the group and rhesus determinants (Rh D...

  18. 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.

  19. Dissociable intrinsic functional networks support noun-object and verb-action processing.

    Science.gov (United States)

    Yang, Huichao; Lin, Qixiang; Han, Zaizhu; Li, Hongyu; Song, Luping; Chen, Lingjuan; He, Yong; Bi, Yanchao

    2017-12-01

    The processing mechanism of verbs-actions and nouns-objects is a central topic of language research, with robust evidence for behavioral dissociation. The neural basis for these two major word and/or conceptual classes, however, remains controversial. Two experiments were conducted to study this question from the network perspective. Experiment 1 found that nodes of the same class, obtained through task-evoked brain imaging meta-analyses, were more strongly connected with each other than nodes of different classes during resting-state, forming segregated network modules. Experiment 2 examined the behavioral relevance of these intrinsic networks using data from 88 brain-damaged patients, finding that across patients the relative strength of functional connectivity of the two networks significantly correlated with the noun-object vs. verb-action relative behavioral performances. In summary, we found that verbs-actions and nouns-objects are supported by separable intrinsic functional networks and that the integrity of such networks accounts for the relative noun-object- and verb-action-selective deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    B. N. Holben

    2018-01-01

    Full Text Available 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.

  1. Improved Seismic Acquisition System and Data Processing for the Italian National Seismic Network

    Science.gov (United States)

    Badiali, L.; Marcocci, C.; Mele, F.; Piscini, A.

    2001-12-01

    A new system for acquiring and processing digital signals has been developed in the last few years at the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system makes extensive use of the internet communication protocol standards such as TCP and UDP which are used as the transport highway inside the Italian network, and possibly in a near future outside, to share or redirect data among processes. The Italian National Seismic Network has been working for about 18 years equipped with vertical short period seismometers and transmitting through analog lines, to the computer center in Rome. We are now concentrating our efforts on speeding the migration towards a fully digital network based on about 150 stations equipped with either broad band or 5 seconds sensors connected to the data center partly through wired digital communication and partly through satellite digital communication. The overall process is layered through intranet and/or internet. Every layer gathers data in a simple format and provides data in a processed format, ready to be distributed towards the next layer. The lowest level acquires seismic data (raw waveforms) coming from the remote stations. It handshakes, checks and sends data in LAN or WAN according to a distribution list where other machines with their programs are waiting for. At the next level there are the picking procedures, or "pickers", on a per instrument basis, looking for phases. A picker spreads phases, again through the LAN or WAN and according to a distribution list, to one or more waiting locating machines tuned to generate a seismic event. The event locating procedure itself, the higher level in this stack, can exchange information with other similar procedures. Such a layered and distributed structure with nearby targets allows other seismic networks to join the processing and data collection of the same ongoing event, creating a virtual network larger than the original one. At present we plan to cooperate with other

  2. Ternary rhombohedral Laves phases RE_2Rh_3Ga (RE = Y, La-Nd, Sm, Gd-Er)

    International Nuclear Information System (INIS)

    Seidel, Stefan; Benndorf, Christopher; Heletta, Lukas; Poettgen, Rainer; Eckert, Hellmut; Sao Paulo Univ., Sao Carlos

    2017-01-01

    The ordered Laves phases RE_2Rh_3Ga (RE=Y, La-Nd, Sm, Gd-Er) were synthesized by arc-melting of the elements and subsequent annealing. The samples were characterized by powder X-ray diffraction (XRD). They crystallize with the rhombohedral Mg_2Ni_3Si type structure, space group R3m. Three structures were refined from single crystal X-ray diffractometer data: a=557.1(1), c=1183.1(2), wR2=0.0591, 159 F"2 values, 10 variables for Y_2Rh_3Ga, a=562.5(2), c=1194.4(2) pm, wR2=0.0519, 206 F"2 values, 11 variables for Ce_2Rh_3Ga and a=556.7(2), c=1184.1(3) pm, wR2=0.0396, 176 F"2 values, 11 variables for Tb_2Rh_3Ga. The Rh_3Ga tetrahedra are condensed via common corners and the large cavities left by the network are filled by the rare earth atoms. The RE_2Rh_3Ga Laves phases crystallize with a translationengleiche subgroup of the cubic RERh_2 Laves phases with MgCu_2 type. Magnetic susceptibility measurements reveal Pauli paramagnetism for Y_2Rh_3Ga and La_2Rh_3Ga. Ce_2Rh_3Ga shows intermediate cerium valence while all other RE_2Rh_3Ga phases are Curie-Weiss paramagnets which order magnetically at low temperatures. The "8"9Y and "7"1Ga solid state nuclear magnetic resonance (NMR) spectra of the diamagnetic representative Y_2Rh_3Ga show well-defined single resonances in agreement with an ordered bulk phase. In comparison to the binary Laves phase YRh_2 a strongly increased "8"9Y resonance frequency is observed owing to a higher s-electron spin density at the "8"9Y nuclei as proven by density of states (DOS) calculations.

  3. 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...

  4. 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.

  5. Imbalance of default mode and regulatory networks during externally focused processing in depression

    Science.gov (United States)

    Belleau, Emily L.; Taubitz, Lauren E.

    2015-01-01

    Attentional control difficulties likely underlie rumination, a core cognitive vulnerability in major depressive disorder (MDD). Abnormalities in the default mode, executive and salience networks are implicated in both rumination and attentional control difficulties in MDD. In the current study, individuals with MDD (n = 16) and healthy controls (n = 16) completed tasks designed to elicit self-focused (ruminative) and externally-focused thinking during fMRI scanning. The MDD group showed greater default mode network connectivity and less executive and salience network connectivity during the external-focus condition. Contrary to our predictions, there were no differences in connectivity between the groups during the self-focus condition. Thus, it appears that when directed to engage in self-referential thinking, both depressed and non-depressed individuals similarly recruit networks supporting this process. In contrast, when instructed to engage in non-self-focused thought, non-depressed individuals show a pattern of network connectivity indicative of minimized self-referential processing, whereas depressed individuals fail to reallocate neural resources in a manner consistent with effective down regulation of self-focused thought. This is consistent with difficulties in regulating self-focused thinking in order to engage in more goal-directed behavior that is seen in individuals with MDD. PMID:25274576

  6. 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. PMID:22163948

  7. 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.

  8. Deployment of wireless sensor network in pyrochemical processing of metallic fuels

    International Nuclear Information System (INIS)

    Baghyalakshmi, D.; Shrikrishnan, T.S.; Ebenezer, Jemimah; Madhusoodanan, K.; Satya Murty, S.A.V.; Vannia Perumal, S.; Venkatesh, P.; Prabhakara Reddy, B.

    2016-01-01

    With the advent of wireless sensor networking technology, industries started adapting the wireless monitoring systems in phases to measure and control various process parameters. To test the feasibility for implementing Wireless Sensor Network to measure the potentials of an electrochemical cell and the temperatures of actinide drawdown process at Pyrochemical process studies laboratory, at Chemistry Group, IGCAR, Kalpakkam, experiments have been carried out. An experimental setup with two Wireless Sensor Networking nodes has been deployed inside argon atmosphere glove boxes. The Electrorefining studies on U and U based alloys and the studies on actinide recovery from the electrolyte salt in actinide drawdown process are carried out in the glove box. The WSN measuring system was tested and validated by measuring the potentials of an electrochemical cell and the temperatures of actinide drawdown process. The WSN system is proposed to be installed in the hot cells of the Chemistry Group where irradiated U-Zr fuel is reprocessed. This paper briefs the need for remote measuring in pyrochemical reprocessing and validation of the remote signals by measuring the potentials of an electrochemical cell and the temperatures of the actinide draw down process. (author)

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

    NARCIS (Netherlands)

    Elzendoorn, B. S. Q.; M.R. de Baar,; Hamilton, D.; Heemskerk, C. J. M.; Koning, J. F.; Ronden, D. M. S.

    2012-01-01

    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

  10. Rh(III)-catalyzed olefination of N-sulfonyl imines: synthesis of ortho-olefinated benzaldehydes.

    Science.gov (United States)

    Zhang, Tao; Wu, Lamei; Li, Xingwei

    2013-12-20

    Rh(III)-catalyzed olefination of N-sulfonyl imines using acrylates and styrenes has been achieved for the synthesis of ortho-olefinated benaldehydes. This reaction proceeds via a chelation assisted C-H olefination/in situ hydrolysis process.

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

    DEFF Research Database (Denmark)

    He, Feng Q; Ollert, Markus

    2018-01-01

    Identification of key genes for a given physiological or pathological process is an essential but still very challenging task for the entire biomedical research community. Statistics-based approaches, such as genome-wide association study (GWAS)- or quantitative trait locus (QTL)-related analysis...... have already made enormous contributions to identifying key genes associated with a given disease or phenotype, the success of which is however very much dependent on a huge number of samples. Recent advances in network biology, especially network inference directly from genome-scale data...

  12. Low cost fabrication and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks

    CSIR Research Space (South Africa)

    Land, K

    2011-09-01

    Full Text Available and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land, Mesuli B. Mbanjwa, Klariska Govindasamy, and Jan G. Korvink Citation: Biomicrofluidics 5, 036502 (2011); doi: 10.1063/1.3641859 View online: http... polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land,1,2,a) Mesuli B. Mbanjwa,1,3 Klariska Govindasamy,1 and Jan G. Korvink2,4 1Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa 2University of Freiburg, Department...

  13. Photonuclear excitation of 103Rh by synchrotron radiation

    International Nuclear Information System (INIS)

    Kaji, Harumi; Yoshihara, Kenji; Mukoyama, Takeshi; Nakajima, Tetsuo

    1989-01-01

    Photonuclear excitation of 103 Rh nucleus was studied by the use of synchrotron radiation at KEK. Formation of excited state was confirmed by observing Rh K X-rays emitted following the isomeric transition of 103m Rh with a low-energy photon spectrometer. The induced activity due to 103 Rh(γ,γ') 103m Rh reaction was determined carefully by subtracting the fluorescent K X-rays due to natural background radiation. The integral cross-section for 103m Rh by resonance absorption at 295 keV is found to be (1∼2)x10 -28 cm 2 ·eV and is compared with that estimated from the previous experimental value for the 1277-keV level and the calculated value

  14. 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...... 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...... human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during...

  15. A Sparse Auto Encoder Deep Process Neural Network Model and its Application

    Directory of Open Access Journals (Sweden)

    Xu Shaohua

    2017-01-01

    Full Text Available Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process neural network (PNN and the data feature extraction and hierarchical sparse representation mechanism of sparse automatic encoder (SAE. Based on the feedforward PNN model, SAE-DPNN is constructed by stacking the process neurons, SAE network and softmax classifier. It can maintain the time-sequence and structure of the input signal, express and synthesize the process distribution characteristics of multidimensional time-varying signals and their combinations. SAE-DPNN improves the identification of complex features and distinguishes between different types of signals, realizes the direct classification of time-varying signals. In this paper, the feature extraction and representation mechanism of time-varying signal in SAE-DPNN are analyzed, and a specific learning algorithm is given. The experimental results verify the effectiveness of the model and algorithm.

  16. 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.

  17. Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Bennett, Matthew R. [Department of Biochemistry and Cell Biology, Rice University, Houston, Texas 77204, USA and Institute of Biosciences and Bioengineering, Rice University, Houston, Texas 77005 (United States); Josić, Krešimir [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204 (United States)

    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.

  18. Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  19. Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

    KAUST Repository

    Alsibyani, Hassan M.

    2018-05-15

    Cloud computing usage is increasing and a common concern is the privacy and security of the data and computation. Third party cloud environments are not considered fit for processing private information because the data will be revealed to the cloud provider. However, Trusted Execution Environments (TEEs), such as Intel SGX, provide a way for applications to run privately and securely on untrusted platforms. Nonetheless, using a TEE by itself for stream processing systems is not sufficient since network communication patterns may leak properties of the data under processing. This work addresses leaky topology structures and suggests mitigation techniques for each of these. We create specific metrics to evaluate leaks occurring from the network patterns; the metrics measure information leaked when the stream processing system is running. We consider routing techniques for inter-stage communication in a streaming application to mitigate this data leakage. We consider a dynamic policy to change the mitigation technique depending on how much information is currently leaking. Additionally, we consider techniques to hide irregularities resulting from a filtering stage in a topology. We also consider leakages resulting from applications containing cycles. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing system.

  20. Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

    Science.gov (United States)

    Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

    2018-06-01

    Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

  1. Relationships between music training, speech processing, and word learning: a network perspective.

    Science.gov (United States)

    Elmer, Stefan; Jäncke, Lutz

    2018-03-15

    Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

  2. 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.

  3. 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...

  4. 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.

  5. A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

    Science.gov (United States)

    Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

    2011-01-01

    To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

  6. Microwave sinthesys and characterization of Pt and Pt-Rh-Sn electrocatalysts for ethanol oxidation

    Directory of Open Access Journals (Sweden)

    Jovanović Vladislava M.

    2011-01-01

    Full Text Available Carbon supported Pt and Pt-Rh-Sn catalysts were synthesized by microwave-polyol method in ethylene glycol solution and investigated for the ethanol electro-oxidation reaction. The catalysts were characterized in terms of structure, morphology and composition by employing XRD, STM and EDX techniques. STM analysis indicated rather uniform particles and particle size of below 2 nm for both catalysts. XRD analysis of the Pt/C catalyst revealed two phases, one with the main characteristic peaks of face centered cubic crystal structure (fcc of platinum and another related to graphite like structure of carbon support Vulcan XC-72R. However, in XRD pattern of the Pt-Rh-Sn/C catalyst diffraction peaks for Pt, Rh or Sn cannot be resolved, indicating an extremely low crystallinity. The small particle sizes and homogeneous size distributions of both catalysts should be attributed to the advantages of microwave assisted modified polyol process in ethylene glycol solution. Pt-Rh- Sn/C catalyst is highly active for the ethanol oxidation with the onset potential shifted for more than 150 mV to negative values and with currents nearly 5 times higher in comparison to Pt/C catalyst. The stability tests of the catalysts, as studied by the chronoamperometric experiments, reveal that the Pt-Rh-Sn/C catalyst is evidently less poisoned then Pt/C catalyst. The increased activity of Pt-Rh-Sn/C in comparison to Pt/C catalyst is most probably promoted by bifunctional mechanism and the electronic effect of alloyed metals.

  7. {sup 103}Rh-NMR studies in the superconductor Rh{sub 17}S{sub 15}

    Energy Technology Data Exchange (ETDEWEB)

    Koyama, T; Kanda, K; Ueda, K; Mito, T; Kohara, T [Graduate School of Material Science, University of Hyogo, Kamigori, Hyogo 678-1297 (Japan); Nakamura, H, E-mail: t-koyama@sci.u-hyogo.ac.j [Department of Materials Science and Engineering, Kyoto University, Kyoto 606-8501 (Japan)

    2010-01-15

    {sup 103}Rh nuclear magnetic resonance (NMR) measurements have been performed in the superconductor Rh{sub 17}S{sub 15} with the transition temperature T{sub C}=5.4 K. The observed {sup 103}Rh-NMR spectrum shows an asymmetric shape with several peaks, reflecting the local symmetry around each Rh site. We have identified the observed NMR lines corresponding to four different Rh sites and obtained the temperature (T) dependence of the Knight shift of 24m site. The isotropic part of the Knight shift K{sub iso} decreases with decreasing T, indicating the existence of the electron correlation in Rh{sub 17}S{sub 15}. In the superconducting state, the resonance lines shift to higher frequencies owing to a decrease of the spin part of the Knight shift with negative hyperfine coupling.

  8. Risk-based design of process systems using discrete-time Bayesian networks

    International Nuclear Information System (INIS)

    Khakzad, Nima; Khan, Faisal; Amyotte, Paul

    2013-01-01

    Temporal Bayesian networks have gained popularity as a robust technique to model dynamic systems in which the components' sequential dependency, as well as their functional dependency, cannot be ignored. In this regard, discrete-time Bayesian networks have been proposed as a viable alternative to solve dynamic fault trees without resort to Markov chains. This approach overcomes the drawbacks of Markov chains such as the state-space explosion and the error-prone conversion procedure from dynamic fault tree. It also benefits from the inherent advantages of Bayesian networks such as probability updating. However, effective mapping of the dynamic gates of dynamic fault trees into Bayesian networks while avoiding the consequent huge multi-dimensional probability tables has always been a matter of concern. In this paper, a new general formalism has been developed to model two important elements of dynamic fault tree, i.e., cold spare gate and sequential enforcing gate, with any arbitrary probability distribution functions. Also, an innovative Neutral Dependency algorithm has been introduced to model dynamic gates such as priority-AND gate, thus reducing the dimension of conditional probability tables by an order of magnitude. The second part of the paper is devoted to the application of discrete-time Bayesian networks in the risk assessment and safety analysis of complex process systems. It has been shown how dynamic techniques can effectively be applied for optimal allocation of safety systems to obtain maximum risk reduction.

  9. Information processing in echo state networks at the edge of chaos.

    Science.gov (United States)

    Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

    2012-09-01

    We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.

  10. 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

  11. Reduced connectivity in the self-processing network of schizophrenia patients with poor insight.

    Directory of Open Access Journals (Sweden)

    Edith J Liemburg

    Full Text Available 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 self-referential processing. We hypothesized that during resting state the DMN network would show decreased connectivity in schizophrenia patients with poor insight compared to patients with good insight. Patients with schizophrenia were recruited from mental health care centers in the north of the Netherlands and categorized in groups having good insight (n= 25 or poor insight (n = 19. All subjects underwent a resting state fMRI scan. A healthy control group (n = 30 was used as a reference. Functional connectivity of the anterior and posterior part of the DMN, identified using Independent Component Analysis, was compared between groups. Patients with poor insight showed lower connectivity of the ACC within the anterior DMN component and precuneus within the posterior DMN component compared to patients with good insight. Connectivity between the anterior and posterior part of the DMN was lower in patients than controls, and qualitatively different between the good and poor insight patient groups. As predicted, subjects with poor insight in psychosis showed decreased connectivity in DMN regions implicated in self-referential processing, although this concerned only part of the network. This finding is compatible with theories implying a role of reduced self-referential processing as a mechanism contributing to poor insight.

  12. 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.

  13. ‘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.

  14. 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.

  15. Using the artificial neural network to control the steam turbine heating process

    International Nuclear Information System (INIS)

    Nowak, Grzegorz; Rusin, Andrzej

    2016-01-01

    Highlights: • Inverse Artificial Neural Network has a potential to control the start-up process of a steam turbine. • Two serial neural networks made it possible to model the rotor stress based of steam parameters. • An ANN with feedback enables transient stress modelling with good accuracy. - Abstract: Due to the significant share of renewable energy sources (RES) – wind farms in particular – in the power sector of many countries, power generation systems become sensitive to variable weather conditions. Under unfavourable changes in weather, ensuring required energy supplies involves hasty start-ups of conventional steam power units whose operation should be characterized by higher and higher flexibility. Controlling the process of power engineering machinery operation requires fast predictive models that will make it possible to analyse many parallel scenarios and select the most favourable one. This approach is employed by the algorithm for the inverse neural network control presented in this paper. Based on the current thermal state of the turbine casing, the algorithm controls the steam temperature at the turbine inlet to keep both the start-up rate and the safety of the machine at the allowable level. The method used herein is based on two artificial neural networks (ANN) working in series.

  16. The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe.

    Science.gov (United States)

    Mahdavi, Mahdi; Vissers, Jan; Elkhuizen, Sylvia; van Dijk, Mattees; Vanhala, Antero; Karampli, Eleftheria; Faubel, Raquel; Forte, Paul; Coroian, Elena; van de Klundert, Joris

    2018-01-01

    While health service provisioning for the chronic condition Type 2 Diabetes (T2D) often involves a network of organisations and professionals, most evidence on the relationships between the structures and processes of service provisioning and the outcomes considers single organisations or solo practitioners. Extending Donabedian's Structure-Process-Outcome (SPO) model, we investigate how differences in quality of life, effective coverage of diabetes, and service satisfaction are associated with differences in the structures, processes, and context of T2D services in six regions in Finland, Germany, Greece, Netherlands, Spain, and UK. Data collection consisted of: a) systematic modelling of provider network's structures and processes, and b) a cross-sectional survey of patient reported outcomes and other information. The survey resulted in data from 1459 T2D patients, during 2011-2012. Stepwise linear regression models were used to identify how independent cumulative proportion of variance in quality of life and service satisfaction are related to differences in context, structure and process. The selected context, structure and process variables are based on Donabedian's SPO model, a service quality research instrument (SERVQUAL), and previous organization and professional level evidence. Additional analysis deepens the possible bidirectional relation between outcomes and processes. The regression models explain 44% of variance in service satisfaction, mostly by structure and process variables (such as human resource use and the SERVQUAL dimensions). The models explained 23% of variance in quality of life between the networks, much of which is related to contextual variables. Our results suggest that effectiveness of A1c control is negatively correlated with process variables such as total hours of care provided per year and cost of services per year. While the selected structure and process variables explain much of the variance in service satisfaction, this is

  17. Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

    Science.gov (United States)

    Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

    2018-05-01

    The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

  18. Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

    Science.gov (United States)

    Raskovic, Dejan

    Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

  19. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  20. Node-making process in network meta-analysis of nonpharmacological treatment are poorly reported.

    Science.gov (United States)

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

    2018-05-01

    To identify methods to support the node-making process in network meta-analyses (NMAs) of nonpharmacological 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 nonpharmacological 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 nonpharmacological 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

  1. 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.

  2. 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

  3. Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

    Science.gov (United States)

    Navarro, Robert

    2006-01-01

    The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

  4. 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.

  5. 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.

  6. 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...... 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...... the network. The innovation thus grew strong enough to replace existing practices and identities and to embed new ones into new organizational structures and a new business-concept...

  7. 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 ...

  8. 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.

  9. Status of Utilizing Social Media Networks in the Teaching-Learning Process at Public Jordanian Universities

    OpenAIRE

    Muneera Abdalkareem Alshdefait; Mohammad . S. Alzboon

    2018-01-01

    This study aimed at finding out the status of utilizing social media networks in the teaching-learning process at public Jordanian Universities. To achieve the goal of the study, the descriptive developmental method was used and a questionnaire was developed, consisting of (35) statements. The questionnaire was checked for its validity and reliability. Then it was distributed to a sample of (382) male and female students from the undergraduate and graduate levels. The study results showed tha...

  10. Physical removal of metallic carbon nanotubes from nanotube network devices using a thermal and fluidic process

    International Nuclear Information System (INIS)

    Ford, Alexandra C; Shaughnessy, Michael; Wong, Bryan M; Kane, Alexander A; Krafcik, Karen L; Léonard, François; Kuznetsov, Oleksandr V; Billups, W Edward; Hauge, Robert H

    2013-01-01

    Electronic and optoelectronic devices based on thin films of carbon nanotubes are currently limited by the presence of metallic nanotubes. Here we present a novel approach based on nanotube alkyl functionalization to physically remove the metallic nanotubes from such network devices. The process relies on preferential thermal desorption of the alkyls from the semiconducting nanotubes and the subsequent dissolution and selective removal of the metallic nanotubes in chloroform. The approach is versatile and is applied to devices post-fabrication. (paper)

  11. Analysis of the packet formation process in packet-switched networks

    Science.gov (United States)

    Meditch, J. S.

    Two new queueing system models for the packet formation process in packet-switched telecommunication networks are developed, and their applications in process stability, performance analysis, and optimization studies are illustrated. The first, an M/M/1 queueing system characterization of the process, is a highly aggregated model which is useful for preliminary studies. The second, a marked extension of an earlier M/G/1 model, permits one to investigate stability, performance characteristics, and design of the packet formation process in terms of the details of processor architecture, and hardware and software implementations with processor structure and as many parameters as desired as variables. The two new models together with the earlier M/G/1 characterization span the spectrum of modeling complexity for the packet formation process from basic to advanced.

  12. Forward and reverse mapping for milling process using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rashmi L. Malghan

    2018-02-01

    Full Text Available The data set presented is related to the milling process of AA6061-4.5%Cu-5%SiCp composite. The data primarily concentrates on predicting values of some machining responses, such as cutting force, surface finish and power utilization utilizing using forward back propagation neural network based approach, i.e. ANN based on three process parameters, such as spindle speed, feed rate and depth of cut.The comparing reverse model is likewise created to prescribe the ideal settings of processing parameters for accomplishing the desired responses as indicated by the necessities of the end clients. These modelling approaches are very proficient to foresee the benefits of machining responses and also process parameter settings in light of the experimental technique. Keywords: ANN, Forward mapping, Reverse mapping, Milling process

  13. Large magnetoresistance in Er7Rh3

    International Nuclear Information System (INIS)

    Sengupta, Kaushik; Sampathkumaran, E.V.

    2005-01-01

    The compound Er 2 Rh 3 has been known to order antiferromagnetically below (T N =14K), and to exhibit a change in the sign of temperature coefficient of electrical resistivity (ρ) in the paramagnetic state around 120 K. Here we report the influence of external magnetic field (H) on the ρ(T) behavior of this compound (1.8-300 K). While the ρ behavior in the paramagnetic state, qualitatively speaking, is found to be robust to the application of H, the magnitude of the magnetoresistance (MR) is significant for moderate applications of H, even at temperatures for above T N untypical of metallic systems. In addition, large values are observed in the magnetically ordered state. (author)

  14. Business Strategy Formulation By Shareholders and Company Management using The Analytical Network Process (ANPBusiness Strategy Formulation by Shareholders and Company Management Using Analytical Network Process (ANP

    Directory of Open Access Journals (Sweden)

    Faizal Faizal

    2016-11-01

    Full Text Available This research aimed to identify the business strategy formulation by the shareholders and the management of the company. Ten companies were selected to be the objects of this research. Those companies were the information technology, telecommunication, printing, mining, construction and chemical companies in Indonesia. The research was conducted by using the Analytical Network Process (ANP and considering the chosen respondents as the decision makers (experts of those companies. The respondents were chosen by using the non-probabilitty sampling method. The result shows that the roles of the company managements are considered m ore influental (0,57143 than the roles of the shareholders (0,28571. From the output of stakeholder’s condition, the best-stratified priority strategies are differentiation (0,600515, cost of leadership (0,230754 and focus (0,168731.

  15. Statistical learning problem of artificial neural network to control roofing process

    Directory of Open Access Journals (Sweden)

    Lapidus Azariy

    2017-01-01

    Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A key question for supervised learning is how many number of training examples we need to approximate the true relationship between network inputs and output with the desired accuracy. Also designing of ANN architecture is related to learning problem known as “curse of dimensionality”. This problem is important for the study of construction process management because of the difficulty to get training data from construction sites. In previous studies the authors have designed a 4-layer feedforward ANN with a unit model of 12-5-4-1 to approximate estimation and prediction of roofing process. This paper presented the statistical learning side of created ANN with simple-error-minimization algorithm. The sample size to efficient training and the confidence interval of network outputs defined. In conclusion the authors predicted successful ANN learning in a large construction business company within a short space of time.

  16. Self-processing and the default mode network: Interactions with the mirror neuron system

    Directory of Open Access Journals (Sweden)

    Istvan eMolnar-Szakacs

    2013-09-01

    Full Text Available Recent evidence for the fractionation of the default mode network (DMN into functionally distinguishable subdivisions with unique patterns of connectivity calls for a reconceptualization of the relationship between this network and self-referential processing. Advances in resting-state functional connectivity analyses are beginning to reveal increasingly complex patterns of organization within the key nodes of the DMN - medial prefrontal cortex (MPFC and posterior cingulate cortex (PCC – as well as between these nodes and other brain systems. Here we review recent examinations of the relationships between the DMN and various aspects of self-relevant and social-cognitive processing in light of emerging evidence for heterogeneity within this network. Drawing from a rapidly evolving social cognitive neuroscience literature, we propose that embodied simulation and mentalizing are processes which allow us to gain insight into another's physical and mental state by providing privileged access to our own physical and mental states. Embodiment implies that the same neural systems are engaged for self- and other-understanding through a simulation mechanism, while mentalizing refers to the use of high-level conceptual information to make inferences about the mental states of self and others. These mechanisms work together to provide a coherent representation of the self and by extension, of others. Nodes of the DMN selectively interact with brain systems for embodiment and mentalizing, including the mirror neuron system, to produce appropriate mappings in the service of social cognitive demands.

  17. Morphological and Physiological Interactions Between GnRH3 and Hypocretin/Orexin Neuronal Systems in Zebrafish (Danio rerio).

    Science.gov (United States)

    Zhao, Yali; Singh, Chanpreet; Prober, David A; Wayne, Nancy L

    2016-10-01

    GnRH neurons integrate internal and external cues to control sexual maturation and fertility. Homeostasis of energy balance and food intake correlates strongly with the status of reproduction. Neuropeptides secreted by the hypothalamus involved in modulating energy balance and feeding may play additional roles in the regulation of reproduction. Hypocretin (Hcrt) (also known as orexin) is one such peptide, primarily controlling sleep/wakefulness, food intake, and reward processing. There is a growing body of evidence indicating that Hcrt/orexin (Hcrt) modulates reproduction through interacting with the hypothalamo-pituitary-gonadal axis in mammals. To explore potential morphological and functional interactions between the GnRH and Hcrt neuronal systems, we employed a variety of experimental approaches including confocal imaging, immunohistochemistry, and electrophysiology in transgenic zebrafish, in which fluorescent proteins are genetically expressed in GnRH3 and Hcrt neurons. Our imaging data revealed close apposition and direct connection between GnRH3 and Hcrt neuronal systems in the hypothalamus during larval development through adulthood. Furthermore, the Hcrt receptor (HcrtR) is expressed in GnRH3 neurons. Electrophysiological data revealed a reversible inhibitory effect of Hcrt on GnRH3 neuron electrical activity, which was blocked by the HcrtR antagonist almorexant. In addition, Hcrt had no effect on the electrical activity of GnRH3 neurons in the HcrtR null mutant zebrafish (HcrtR -/- ). Our findings demonstrate a close anatomical and functional relationship between Hcrt and GnRH neuronal systems in zebrafish. It is the first demonstration of a link between neuronal circuits controlling sleeping/arousal/feeding and reproduction in zebrafish, an important animal model for investigating the molecular genetics of development.

  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. Rh Factor: How It Can Affect Your Pregnancy

    Science.gov (United States)

    ... father or the mother. Can the Rh factor cause problems during pregnancy? Yes. During pregnancy, problems can occur if you ... can die from anemia. Can the Rh factor cause problems during my first pregnancy? Health problems usually do not occur during an ...

  20. Photoelectrochemical properties of LaRhO3

    International Nuclear Information System (INIS)

    Viswanathan, B.; Narayanan, S.R.; Viswanath, R.P.; Varadrajan, T.K.

    1982-01-01

    The photoelectrochemical properties of LaRhO 3 at different values of pH were studied by current-voltage measurements and cyclic voltammetry and the results obtained are compared with those obtained for LaRhO 3 , a potential photoelectrode. (author)

  1. GnRH injection before artificial insemination (AI) alters follicle ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-08-04

    Aug 4, 2009 ... releasing hormone (GnRH) injection on day 6 of the estrous cycle. The estrous cycles ... follicle at the time of GnRH injection (Silcox et al., 1993;. Twagiramungu .... Waves and their Effect on pregnancy rate in the Cow. Reprod.

  2. 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.

  3. 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.

  4. 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...

  5. Application of knowledge-based network processing to automated gas chromatography data interpretation

    International Nuclear Information System (INIS)

    Levis, A.P.; Timpany, R.G.; Klotter, D.A.

    1995-01-01

    A method of translating a two-way table of qualified symptom/cause relationships into a four layer Expert Network for diagnosis of machine or sample preparation failure for Gas Chromatography is presented. This method has proven to successfully capture an expert's ability to predict causes of failure in a Gas Chromatograph based on a small set of symptoms, derived from a chromatogram, in spite of poorly defined category delineations and definitions. In addition, the resulting network possesses the advantages inherent in most neural networks: the ability to function correctly in the presence of missing or uncertain inputs and the ability to improve performance through data-based training procedures. Acquisition of knowledge from the domain experts produced a group of imprecise cause-to-symptom relationships. These are reproduced as parallel pathways composed of Symptom-Filter-Combination-Cause node chains in the network representation. Each symptom signal is passed through a Filter node to determine if the signal should be interpreted as positive or negative evidence and then modified according to the relationship established by the domain experts. The signals from several processed symptoms are then combined in the Combination node(s) for a given cause. The resulting value is passed to the Cause node and the highest valued Cause node is then selected as the most probable cause of failure

  6. Moran model as a dynamical process on networks and its implications for neutral speciation

    Science.gov (United States)

    de Aguiar, Marcus A. M.; Bar-Yam, Yaneer

    2011-03-01

    In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.

  7. Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

    Science.gov (United States)

    Anderson, Brian A

    2017-03-01

    Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. Photonuclear excitation of 103Rh by synchrotron radiation

    International Nuclear Information System (INIS)

    Yoshihara, Kenji; Kaji, Harumi; Sekine, Tsutomu; Mukoyama, Takeshi

    1989-01-01

    Photonuclear excitation of the 103 Rh nucleus was studied using synchrotron radiation. Formation of the excited state was confirmed by observing K X-rays emitted following the isomeric transition of the 103m Rh with a low-energy photon spectrometer. The intensity of induced activity due to 103 Rh(γ,γ') 103m Rh reaction was determined carefully by subtracting the fluorescent K X-rays due to natural background radiation. The integral cross-section for isomer production of 103m Rh by resonance absorption of photons at 295 keV is found to be (2.1±0.8) x 10 -28 cm 2 eV and is compared with that estimated from the previous experimental value for the 1277-keV level. (author)

  9. Cumulative Significance of Hyporheic Exchange and Biogeochemical Processing in River Networks

    Science.gov (United States)

    Harvey, J. W.; Gomez-Velez, J. D.

    2014-12-01

    Biogeochemical reactions in rivers that decrease excessive loads of nutrients, metals, organic compounds, etc. are enhanced by hydrologic interactions with microbially and geochemically active sediments of the hyporheic zone. The significance of reactions in individual hyporheic flow paths has been shown to be controlled by the contact time between river water and sediment and the intrinsic reaction rate in the sediment. However, little is known about how the cumulative effects of hyporheic processing in large river basins. We used the river network model NEXSS (Gomez-Velez and Harvey, submitted) to simulate hyporheic exchange through synthetic river networks based on the best available models of network topology, hydraulic geometry and scaling of geomorphic features, grain size, hydraulic conductivity, and intrinsic reaction rates of nutrients and metals in river sediment. The dimensionless reaction significance factor, RSF (Harvey et al., 2013) was used to quantify the cumulative removal fraction of a reactive solute by hyporheic processing. SF scales reaction progress in a single pass through the hyporheic zone with the proportion of stream discharge passing through the hyporheic zone for a specified distance. Reaction progress is optimal where the intrinsic reaction timescale in sediment matches the residence time of hyporheic flow and is less efficient in longer residence time hyporheic flow as a result of the decreasing proportion of river flow that is processed by longer residence time hyporheic flow paths. In contrast, higher fluxes through short residence time hyporheic flow paths may be inefficient because of the repeated surface-subsurface exchanges required to complete the reaction. Using NEXSS we found that reaction efficiency may be high in both small streams and large rivers, although for different reasons. In small streams reaction progress generally is dominated by faster pathways of vertical exchange beneath submerged bedforms. Slower exchange

  10. 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.

  11. Effect of endotoxin on the expression of GnRH and GnRHR genes in the hypothalamus and anterior pituitary gland of anestrous ewes.

    Science.gov (United States)

    Herman, Andrzej Przemysław; Tomaszewska-Zaremba, Dorota

    2010-07-01

    An immune/inflammatory challenge can affect reproduction at the level of the hypothalamus, pituitary gland, or gonads. Nonetheless, the major impact is thought to occur within the brain or the pituitary gland. The present study was designed to examine the effect of intravenous (i.v.) lipopolysaccharide (LPS) injection on the expression of gonadotropin-releasing hormone (GnRH) and the gonadotropin-releasing hormone receptor (GnRHR) genes in the hypothalamic structures where GnRH neurons are located as well as in the anterior pituitary gland (AP) of anestrous ewes. We also determined the effect of LPS on luteinizing hormone (LH) release. It was found that i.v. LPS injection significantly decreased GnRH and GnRHR mRNAs levels in the preoptic area (40%, ppituitary cells to GnRH stimulation. The presence of GnRH mRNA in the median eminence, the hypothalamic structure where GnRH-ergic neurons' terminals are located, suggests that the axonal transport of GnRH mRNA may occur in these neurons. This phenomenon could play an important role in the physiology of GnRH neurons. Our data demonstrate that immune stress could be important inhibitor of this process. Copyright 2010 Elsevier B.V. All rights reserved.

  12. Production of Pd 103 seed from Rh targets for brachytherapy

    International Nuclear Information System (INIS)

    Afarideh, H.; Ardaneh, K.; Sadeghi, M.

    2000-01-01

    The suitability of a given radionuclide for brachytherapy is determined by its half-life, the type of energy, and abundance (number per decay) of its emission. The half-life of a radionuclide must be long enough to permit shipping and implant preparation with an acceptable loss of source strength due to decay, but it must also be short enough to permit source sizes sufficiently small for the intended application. Pd-103 is a low energy photon emitter available for permanent interstitial implantation. Pd-103 has energy and safety characteristics similar to I-125, but its initial peripheral dose rate is approximately three times greater. This may provide improved control of rapidly proliferating tumours. Although Pd-103 has been used for various kinds of cancers, it is almost exclusively used for prostate cancer, the most common cancer, and the death rate from this cancer is the highest. There are two cyclotron production routes for Pd-103, Ag (p,xn) 103 Pd and Rh (p,n) 103 Pd. For a cyclotron with low energy (such as 30Mev that we have in Iran, Karaj, NRCAM) only Rh target can be used. The target material should be deposited on a special designed Cu substrate and the separation process should isolate the desired radionuclide from target material as well as Cu. Our work plan for production of Pd 103 in Karaj, Iran, is as follows: In the first year of the CRP we are going to complete the literature survey of Pd production and perform the relevant experiments as described later. In the second year of the CRP we will construct suitable hot cells for Pd production and also do research for development of Pd seeds. In the last year of the CRP we are going to finalise all the work done during the last two years and propose the automation system for routine production

  13. 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.

  14. [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.

  15. Research of processes of eutrophication of Teteriv river reservoir based on neural networks mass

    Directory of Open Access Journals (Sweden)

    Yelnikova T.A.

    2016-12-01

    Full Text Available Methods of process control of eutrophication in water are based on water sampling, handling them in the laboratory and calculation of indexes of pond ecosystem. However, these methods have some significant drawbacks associated with using manual labor. The method of determining of the geometric parameters of phytoplankton through the use of neural networks for processing water samples is developed. Due to this method eutrophic processes of reservoirs of river Teteriv are investigated. A comparative analysis of eutrophic processes of reservoirs "Denyshi" and “Vidsichne” intake during 2014-2015 years are given. The differences between qualitative and quantitative composition of phytoplankton algae in two reservoirs of the river Teteriv used for water supply of Zhitomir city area are found out. The influence of exogenous and endogenous factors on the expansion of phytoplankton is researched. Research results can be used for monitoring and forecasting of ecological state of water for household purposes, used for water supply of cities.

  16. 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.

  17. 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...

  18. Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders.

    Science.gov (United States)

    Kana, Rajesh K; Sartin, Emma B; Stevens, Carl; Deshpande, Hrishikesh D; Klein, Christopher; Klinger, Mark R; Klinger, Laura Grofer

    2017-07-28

    The social communication impairments defining autism spectrum disorders (ASD) may be built upon core deficits in perspective-taking, language processing, and self-other representation. Self-referential processing entails the ability to incorporate self-awareness, self-judgment, and self-memory in information processing. Very few studies have examined the neural bases of integrating self-other representation and semantic processing in individuals with ASD. The main objective of this functional MRI study is to examine the role of language and social brain networks in self-other processing in young adults with ASD. Nineteen high-functioning male adults with ASD and 19 age-sex-and-IQ-matched typically developing (TD) control participants made "yes" or "no" judgments of whether an adjective, presented visually, described them (self) or their favorite teacher (other). Both ASD and TD participants showed significantly increased activity in the medial prefrontal cortex (MPFC) during self and other processing relative to letter search. Analyses of group differences revealed significantly reduced activity in left inferior frontal gyrus (LIFG), and left inferior parietal lobule (LIPL) in ASD participants, relative to TD controls. ASD participants also showed significantly weaker functional connectivity of the anterior cingulate cortex (ACC) with several brain areas while processing self-related words. The LIFG and IPL are important regions functionally at the intersection of language and social roles; reduced recruitment of these regions in ASD participants may suggest poor level of semantic and social processing. In addition, poor connectivity of the ACC may suggest the difficulty in meeting the linguistic and social demands of this task in ASD. Overall, this study provides new evidence of the altered recruitment of the neural networks underlying language and social cognition in ASD. Published by Elsevier Ltd.

  19. 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

  20. 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.